IMPACT OF GENERAL PRACTITIONER PAYMENT SCHEME ON HEALTH CARE SYSTEM IN AVOIDABLE HOSPITALIZATION FOR AMBULATORY CARE SENSITIVE CONDITIONS By Ukeme E. U. Eka B.Sc, University of Port Harcourt, Rivers State, Nigeria THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN COMMUNITY HEALTH SCIENCES THE UNIVERSITY OF NORTHERN BRITISH COLUMBIA April, 2011 © Ukeme E.U. Eka, 2011 1*1 Library and Archives Canada Bibliotheque et Archives Canada Published Heritage Branch Direction du Patrimoine de I'edition 395 Wellington Street OttawaONK1A0N4 Canada 395, rue Wellington OttawaONK1A0N4 Canada Your file Votre reference ISBN: 978-0-494-75160-2 Our file Notre reference ISBN: 978-0-494-75160-2 NOTICE: AVIS: The author has granted a nonexclusive license allowing Library and Archives Canada to reproduce, publish, archive, preserve, conserve, communicate to the public by telecommunication or on the Internet, loan, distribute and sell theses worldwide, for commercial or noncommercial purposes, in microform, paper, electronic and/or any other formats. L'auteur a accorde une licence non exclusive permettant a la Bibliotheque et Archives Canada de reproduire, publier, archiver, sauvegarder, conserver, transmettre au public par telecommunication ou par I'lnternet, preter, distribuer et vendre des theses partout dans le monde, a des fins commerciales ou autres, sur support microforme, papier, electronique et/ou autres formats. The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission. L'auteur conserve la propriete du droit d'auteur et des droits moraux qui protege cette these. Ni la these ni des extraits substantiels de celle-ci ne doivent etre im primes ou autrement reproduits sans son autorisation. In compliance with the Canadian Privacy Act some supporting forms may have been removed from this thesis. Conformement a la loi canadienne sur la protection de la vie privee, quelques formulaires secondaires ont ete enleves de cette these. While these forms may be included in the document page count, their removal does not represent any loss of content from the thesis. Bien que ces formulaires aient inclus dans la pagination, il n'y aura aucun contenu manquant. 1+1 Canada Abstract This study compares the effectiveness of primary care interventions provided by general practitioners (GP) remunerated under the fee-for-service (FFS) or alternative payment plan (APP), using hospitalization rates for ambulatory care sensitive conditions (ACSC) in select Northern British Columbia (BC) communities. This study used BC Ministry of Health hospital separation data held at Population Data BC. Bivariate statistics were used to compare hospitalization rates for ACSC between both groups. The results indicate overall hospitalization rates of ACSC were higher in APP than FFS communities. Further, several ACSC showed varying hospitalization rates (asthma, pneumonia, COPD, diabetes, angina, gastroenteritis/dehydration and convulsion/epilepsy) and length of hospitalizations (convulsion/epilepsy and dental conditions) between both groups. In summary, this research informs policy on the effectiveness of GP remuneration adopted in Northern BC using hospitalization rates for ACSC. Further research is needed to further validate the findings of this study. n Table of Content Abstract ii Table of Contents v List of Tables v List of Figures vii Acknowledgement iix Chapter One: Introduction Conceptual Framework Research Objectives Objective and Hypotheses Significance 1 4 4 5 6 Chapter Two: Literature Review General Practitioner Remuneration and Incentives Fee-for service (FFS) Alternative payment plan (APP) Primary Health Care Ambulatory Care Sensitive Conditions Summary 8 9 14 20 31 34 38 Chapter Three: Methods Research Design Study populations Community profile Estimation of Study population Selection of ACSC hospitalizations Data sources Ethics Approval Data Analysis Hospitalization and ACSC hospitalization rates 39 39 39 40 45 47 49 50 50 50 Chapter Four: Results Preliminary Data Analysis Hospitalization Rates for ACSC Rates of hospitalizations for chronic ACSC conditions Rates of hospitalizations for acute ACSC conditions Rates of hospitalizations for vaccine preventable ACSC conditions Statistical Difference between APP and FFS Communities Analysis of hospitalization rates for ACSC specific conditions 52 52 53 56 66 73 81 82 iii Length of Hospital Stay in APP and FFS Communities 86 Length of hospital stay in APP and FFS communities for chronic ACSC 86 Length of hospital stays in APP and FFS communities for acute ACSC 88 Length of hospital stays in APP and FFS communities for vaccine preventable ACSC. 89 Summary of Finding 89 Chapter Five: Discussion Key Findings and Contribution Rates of hospitalization and ACSC Statistical analysis Length of hospital stay 91 91 93 95 96 Chapter Six: Conclusion Returning to the Conceptual Model Hypothesis results Study limitations Implication of this study 97 98 99 101 103 Reference 105 Appendix A: Conditions Suggesting Potentially Avoidable Hospitalizations, with Corresponding ICD-9 and ICD-10-CA Codes 111 Appendix B: APP and FFS Communities, and Flags 139 Appendix C: Ethics Approval from the UNBC Research Ethics Board 140 IV List of Tables Table 1: Summary of Alternative Clinical Payment Type by Province and Territory, 20052006 13 Table 2: Physicians' Fee-for-service Remuneration Method as a percentage of all Payment to all Physicians 18 Table 3: Physicians' Alternative Remuneration Method as a percentage of all Payment to all Physicians 19 Table 4: Evaluating Physician Remuneration Methods 30 Table 5: Selected Characteristics of Study Population 43 Table 6: Population per Census Year in APP and FFS Communities 46 Table 7: Estimation of Community Population 46 Table 8: Definition of Ambulatory Care Sensitive Conditions 4-£ Table 9: Age and Gender Proportion of ACSC Hospitalization in APP and FFS Communities 53 Table 10: Rates of ACSC Hospitalizations in APP and FFS Communities, 1992/93-2008/09 55 Table 11: Rates for Chronic ACSC Hospitalizations in APP Communities, 95% Confidence Intervals, 1992/93-2008/09 57 Table 12: Rates for Acute ACSC Hospitalizations in FFS Communities, 95% Confidence Intervals, J 992/93-2008/09 68 Table 13: Rates for Vaccine Preventable Conditions ACSC Hospitalizations in APP Communities, 95% Confidence Intervals, 1992/93-2008/09 74 Table 14: Overall Analysis of ACSC Hospitalizations Rates per 1000 Population in APP and FFS Communities 82 Table 15: Contrast of APP Communities with FFS Communities in Hospitalization for Chronic ACSC 84 Table 16: Contrast of APP Communities with FFS Communities in Hospitalization for Acute ACSC 85 v Table 17: Contrast of APP Communities with FFS Communities in Hospitalization for Vaccine Preventable ACSC 86 Table 18: Contrast of APP Communities with FFS Communities in Length of Hospital Stay for Acute ACSC 87 Table 19: Contrast of APP Communities with FFS Communities in Length of Hospital Stay for Acute ACSC 88 Table 20: Contrast of APP Communities with FFS Communities in Length of Hospital Stay for Vaccine ACSC 889 Table 21: Summary of Findings 90 vi List of Figures Figure 1. Conceptual model for comparison of general practitioner remunerations 7 Figure 2. Rates of ACSC hospitalizations in APP and FFS communities 54 Figure 3. Rates of hospitalization for asthma, 1992/93 - 2008/09 58 Figure 4. Rates of hospitalization for bronchitis, 1992/93-2008/09 59 Figure 5. Rates of hospitalization for convulsion and epilepsy, 1992/93 - 2008/09 59 Figure 6. Rates of hospitalization for pneumonia, 1992/93 - 2008/09 61 Figure 7. Rates of hospitalization for COPD, 1992/93 - 2008/09 61 Figure 8. Rates of hospitalization for hypertensions, 1992/93 - 2008/09 62 Figure 9. Rates of hospitalization for diabetes and allied conditions, 1992/93 - 2008/09 63 Figure 10. Rates of hospitalization for angina pectoris, 1992/93 - 2008/09 65 Figure 11. Rates of hospitalization for heart failure and pulmonary edema, 1992/93 2008/09 65 Figure 12. Rates of hospitalization for anemia, 1992/93 - 2008/09 66 Figure 13. Rates of hospitalization for pelvic inflammatory disease, 1992/93 - 2008/09 69 Figure 14. Rates of hospitalization for severe ENT infections, 1992/93 -2008/09 70 Figure 15. Rates of hospitalization for gastroenteritis and dehydration, 1992/93 - 2008/09. 70 Figure 16. Rates of hospitalization for dental conditions, 1992/93-2008/09 72 Figure 17. Rates of hospitalization for cellulitis, 1992/93 - 2008/09 72 Figure 18. Rates of hospitalization for influenza, 1992/93-2008/09 75 Figure 19. Rates of hospitalization for rubella, 1992/93 - 2008/09 76 Figure 20. Rates of hospitalization for pneumococcal, 1992/93-2008/09 76 Figure 21. Rates of hospitalization for rubella, 1992/93-2008/09 77 vii Figure 22. Rates of hospitalization for hemophilus influenza type B, 1992/93 - 2008/09 77 Figure 23. Rates of hospitalization for hepatitis A, 1992/93-2008/09 78 Figure 24. Rates of hospitalization for hepatitis B, 1992/93 - 2008/09 778 Figure 25. Rates of hospitalization for diphtheria, 1992/93 - 2008/09 79 Figure 26. Rates of hospitalization for mumps, 1992/93 - 2008/09 79 Figure 27. Rates of hospitalization for measles, 1992/93 - 2008/09 80 Figure 28. Rates of hospitalization for meningitis, 1992/93 - 2008/09 80 Figure 29. Rates of hospitalization for pulmonary/other tuberculosis, 1992/93 - 2008/09....81 Figure 30. Conceptual model for comparison of general practitioner remunerations 98 viii Acknowledgement Completion of this thesis represents an academic and personal accomplishment that would not have been possible without the divine enablement of my Lord Jesus Christ, as well as support and encouragement of so many individuals. I would like to acknowledge and thank each of my committee members: Dr. Peter MacMillan, an exceptional educator with a tremendous amount of wisdom who served as co-supervisor and whose knowledge of research and statistical methods were important in determining and verifying the study and who was diligent and patient in reviewing the work and providing advice along the way. I appreciate your efforts in bringing the team together for meetings, providing my valued advice, and ensuring the many necessary reports are finished and filed on time. I am very grateful for mentorship of Dr. Josee Lavoie, who served as co-supervisor and agreed to take me on as a research assistant two years ago, and who has patiently guided me through my studies, in addition to your painstaking supervision of this study. I sincerely appreciate the way you stood by a student who is independent minded or obstinate through years of difficult and stressful challenges of course work and research, as well as personal and professional challenges. I may not have made it to the finish line without your guidance and support, occasional reprimanding when it was needed, praise and encouragement when it was needed as well, and most importantly, the fact that you stood by me through some very difficult times. I will be eternally grateful. Dr. Suzanne Johnston who served as a committee member and whose knowledge and experience of the health care sector was important in expanding my understanding, and whose support was always provided in a kind and patient manner as well as reviewing the work and providing advice along the way. I would like to thank BC Ministry of Health and Population Data BC for providing the data for this study. Finally, and most importantly, I could not have completed an expedition such as this without the love and support of family and friends. I feel immeasurable gratitude for the support of my parents Eddie and Teresa Eka, and my sibling Enefiok, Emem, Nsikak, Utibe, Imaobong and my niece Tehillah. I thank them for their love and sacrifices. I would also like to acknowledge my friend Fisayo for her understanding, support and encouragement particularly during the data entering stage of this study. Thank you. "But regarding anything beyond this, dear friend, go easy. There's no end to the publishing of books, and constant study wears you out so you 're no good for anything else. The last and final word is this: Fear God. Do what he tells you " Ecclesiastes 12:12-13 (MSG) IX Chapter One: Introduction Universal access to medically necessary care remains one of the chief principles of a publicly funded health care system. In the Canadian health care system, the general practitioner (GP) acts as the gate keeper charged with coordinating and providing longitudinal relational care (Brown, Goldacre, Hicks Rourke, McMurray, Brown et al., 2001; Fleming, 1995). In Canada, the GP is the cornerstone of primary care and they work both independently and in group practices (Holden & Madore, 2002). This system has been practiced since the 1970s in most Canadian provinces (Health Canada, 2005). Currently however, the cost of this system is exceeding available resources (Fujisawa & Lafortune, 2008; Lee et al., 1999). Escalating care costs and modes of remunerating physicians continues to be a key policy challenge in the Canadian health care system (Xu & Yu 2003). The primary care physician is an important component of the health care system in Canada. The payment of general practitioners (GPs) is one of the largest drivers of health service cost (Fujisawa & Lafortune, 2008). Hence, reforms of both GP practice approaches and payment schemes have occurred in several countries, (Scott & Hall, 1995). Despite these reforms, there is only modest empirical evidence about the impact of GP remuneration plans on GP performance, patient health outcomes and the overall cost of care. This evidence is paramount since it is an indicator of the effectiveness of the health care system (Scott & Hall, 1995). Over the past decade, several GP payment schemes have been adopted in Canada (Xu & Yu, 2003). The two most prominent payment schemes adopted for GPs are the alternative payment plan (APP), which is payment by contract, salary or capitation and the fee-for1 service (FFS) plan, where GPs are compensated for each unit of service according to a provincially bargained fee schedule (Matthew & Lockhart 2003; Holden & Madore, 2002). The FFS payment is the most predominant form of payment for GP: the Canadian Institute for Health Information (CIHI) reported that approximately eighty percent of family physicians in 2004 received payment by FFS and approximately twenty percent received payment alternatively, i.e., salary, capitation, and contract (CIHI, 2005). Further, with the increasing criticism of the FFS remuneration for GP particularly with regards the objectives of the health care system such as improved outcomes for patients, improved provider satisfaction, and decreased costs (Berwick, Nolan & Whittington 2008; Beasley, 2009), health care policy makers in Canadian provinces have implemented several forms of alternative payment methods for GPs, such as salaries and mixed payment method (Wranik & Durier-Copp, 2010). Moreover, the government and policy makers seem to believe that having an alternative remuneration will tackle these challenges as well as encourage more GPs to become involved in primary health care reform (Martin & Hogg, 2004). The alternative remuneration schemes for GPs are also not devoid of criticisms, as several studies have highlighted their disadvantages, such as under servicing and loss of physician autonomy (Devlin & Sarma, 2008; Holden & Madore, 2002; Xu & Yu, 2003; Lee et al., 1999). Thus, an effective remuneration scheme for GP should be focused on improving access to care, quality, integration, health outcomes and decrease cost.. Additionally, reforming the method of payment could have a significant potential to modify the focus of primary health service delivery and potentially, patient outcomes. Opportune access to primary care is an important indicator for an effective health care system (Shah, Gunraj & Hux, 2003). The gauging of such access to care is dependent on 2 the individual or community health profile and the organization of health delivery system (Shah et al., 2003). One marker for gauging this access to care is to evaluate the hospitalizations for medical conditions that could have been prevented or effectively managed in an outpatient ambulatory setting. These medical conditions are known as ambulatory care sensitive conditions (ACSC), and consists of asthma, hypertension, diabetes, congestive heart failure, chronic obstructive pulmonary disease (COPD) etc (Shah et al., 2003; Billings, Zeitel, Lukomnik, Carey, Blank & Newman, 1993; Pappas, Hadden, Korak & Fisher, 1997; Bindman, Grumbach, Osmond, Komaromy, Vranizan, Karen et al., 1995; Ansari, Laditka, Laditka, 2006; Rizza, Bianco, Pavia & Angelillo, 2007; Chen, Zhang, Sun & Mueller, 2009; Gao, Manns, Culleton, Tonelli, Quan, Crowshoe et al., 2008; Blustein, Hanson & Shea, 1998). Thus hospitalizations for these diagnoses that are best treated in primary health care settings are one indicator of access to or quality of care. Disparities in ACSC hospitalizations can be used to evaluate health system performance, quality of care and inform policy development (Brown et al., 2001; Ricketts, Randolph, Howard, Pathman, & Carey, 2001). Hospitalization for ACSC are considered as potentially avoidable, since because hospitalization may be prevented with timely and opportune access to primary care, however, less likely to be considered as 'inappropriate' since not all hospitalizations are avoidable (Brown et al., 2001; Lavoie, Forget, Prakash, Dahl, Martens & O'Neil, 2010; Starfield, Shi, Macinko, 2005; Parker, Simon, Parham, Teague & Li, 2005). 3 Conceptual Framework The purpose of this study was to explore the differences in rates of hospitalizations for ACSC in select communities where GPs are remunerated either by FFS or APP. I acknowledge that not all hospitalizations are avoidable (Starfield et al., 2005; Lavoie et al. 2010), however, timely and effective access to and quality of primary care and intervention may prevent hospitalizations for these conditions (Lavoie et al., 2010). Thus, an effective GP remuneration plan can be defined conceptually as a remuneration plan that translates into better health outcomes, lower cost and improved physician satisfaction. Figure 1 below illustrates this correlation and outlines the conceptual model upon which this thesis is based. Research Objectives The purpose of this study was to explore the impact of two GP payment schemes (fee-for-service or alternative payment plans) on the quality of primary care interventions by comparing the rates of avoidable hospitalization for ACSC in eight communities (McBride, Fraser Lake, Valemount, Queen Charlotte, Prince Rupert, Stewart, Smithers, and Tumbler Ridge), where GPs are remunerated exclusively with FFS or APP. These communities were chosen because comparing ACSC hospitalization rates at a community level using GP remuneration was possible, since GPs are remunerated either by the FFS or APP. Moreover, research indicates that ACSC hospitalization rates are generally higher in individuals living in rural communities. Specifically, I will ascertain whether or not rates of avoidable hospitalization for ACSC are higher in communities where a GP is remunerated by FFS in comparison to communities where a GP receives payment through the APP. Additionally, the 4 study will also explore trends in rates of avoidable hospitalization for ACSC in either and both types of communities. Objective and Hypotheses The objective of this study was to test the following hypotheses: La To compare rates of avoidable hospitalization for ACSC between communities served by GPs remunerated on a FFS payment plan and APP. HI a: There is no difference in the rates of avoidable hospitalization for ACSC between communities with FFS payment plan and APP for the general practitioner. Lb To compare rates of hospitalization for diagnoses classified as ACSC between APP communities and FFS communities. Hlb: There is no difference in rates of hospitalization for diagnosis classified as ACSC in APP communities and FFS communities. 2.a To examine (descriptive only) trends in rates of hospitalization for ACSC between communities served by GPs remunerated on a FFS payment plan and APP. H2a: There is no difference in trends in rates of avoidable hospitalization for ACSC between communities with FFS payment plan and APP for the general practitioner. 3.a To compare length of hospitalization of diagnoses classified as ACSC between communities with FFS payment plan and APP plans for the general practitioner. H3a: There is no difference in length of hospitalizations of diagnoses classified as ACSC between communities with FFS payment plan and APP plans for the general practitioner. 5 Significance This study was poised to make a significant contribution to knowledge and policy. First, the study design is innovative and will bring evidence to an important question: how to best provide payment for GP services. Second, the result of the study will provide information relevant to curtailing the cost of hospitalization for conditions sensitive to the provision of effective PHC. Reducing the rate of ACSC hospitalization can improve patient outcomes, preserve health care dollars and improve service delivery in ambulatory setting. For example, Kruzikas and colleagues hypothesized that, "assuming that an average hospital stay costs $5,300 per admission, even a modest five percent decrease in hospitalizations for this ambulatory care sensitive conditions would save more than $1.3 billion in inpatient cost" (Kruzikas, Jiang, Remus, Barrett, Coffey & Andrews, 2004 ). Third, this study will contribute to the evaluation of access to and quality of primary care system and health care services in the communities studied (Chen et al., 2009). This thesis is organized into five chapters. The next section of the thesis reviews the existing literature on the GP remuneration plans and primary care intervention. The approach used to define ACSC is described and analysed. Findings related to GP remuneration and rates in avoidable hospitalization for ACSC and the overall hospitalization are summarized. This review of literature is followed by a description of the method used in analysis and a presentation of results from each GP remuneration plan at the community level. Finally a discussion of the research finding and implications will be described. 6 Payment Plan Characteristics Fee-For-Service - Increases physician autonomy - High service volume -Limited access for sicker less able patients -Encourage quick, frequent service - Over service Innovation Measure of Performance Lesson from Literature f Quantity of service \ Cost A I Quality of service Avoidable hospitalization forACSC Is there a difference"? Alternative Payment Plans - Increase physician patient relationship - Better cost control - Eliminate over service - Under servicing - Loss physician autonomy I Quantity of service t Saving V Avoidable hospitalization for ACSC 1" Quality of service Figure J. Conceptual model for comparison of general practitioner remunerations. 7 Chapter Two: Literature Review The Canadian health care system continues to evolve in the range of health care services provided and user demands (Pfaff, Guerriero, Martalog, Arscott, Fontaine & Laforet, 2009). These changes have impacted GP practice as well as their perspectives on quality of care (Lepnurm, Dobson & Backman & Keegan, 2006). The primary care system has formed the bedrock of the Canadian health care system; a vibrant primary health system has been shown to correlate with a healthy and productive population (Katz, Soodeen, Bogdanovic, De Coster & Chateau, 2006). In Canada, the primary health care delivery system is built around the GP playing a central role as the front line practitioner within the health care system. The ageing population, together with the increasing rates of chronic disease, indicate that a growing number of patients are in need of a high level care provided in a more comprehensive, longitudinal and accessible setting. This generates an additional burden on the health care system, as demonstrated in the number of hospitalizations that are preventable (Sanchez, Vellanky, Herring, Liang & Jia, 2008). Thus, implementing adequate and effective incentives for GPs to be productive and provide quality care is pivotal to the challenges of the primary health care system. The literature review reported in this Chapter has been organized into three sections. First, I will discuss GP remuneration plans including advantages and disadvantages to the health care system. Second, I will discuss and outline the significance of primary care intervention to the health care system. Third, I will discuss researchers' efforts to clarify and define the concept of avoidable hospitalization for ambulatory care sensitive conditions. 8 A literature search was undertaken using CINAHL and Medline databases. CINAHL (1990 - July 2010) search terms included, "general practitioner remuneration plans", "primary care intervention", "ambulatory care sensitive conditions", "primary health care", "fee-for-service payment plan" and "alternative payment plan" and resulted in 853 articles. The MEDLINE (1996 - July 2009) search included the MESH terms "primary care intervention", "general practitioner remuneration plan" and "ambulatory care sensitive conditions" and resulted in 705 articles. All abstracts were reviewed and all articles with a declared focus on GP remuneration plans, ambulatory care sensitive conditions, and primary care intervention were retrieved. Published bibliographies and web sites of Canadian professional associations and organizations were also utilized to identify additional relevant work on GP remuneration plans, ambulatory care sensitive conditions, and primary care intervention. General Practitioner Remuneration and Incentives General practitioner remuneration schemes are central to the health care debate in Canada and around the world. Over the past decade, the escalating cost of health care services and the drive to sustain the publicly financed health care system (Devlin & Sarma, 2008; Fujisawa & Lafortune, 2008), particularly with an aging population, has shifted the focus of policy makers to the general practitioner remuneration and practice style (Wright, 1996; Lee, Cowie & Slobodian, 1999; Scott & Hall, 1995). In 2000, CIHI reported that approximately 13 billion was spent on physician services, reflecting 13.3% of the overall health care cost (CIHI, 2001). In spite of the significant reform initiatives and strategies that have been enacted, the question remains how GPs can be adequately reimbursed so it 9 translates into improved outcomes for patients, improved provider satisfaction, and decreased costs. The OECD countries have adopted a range of remuneration methods for their GPs in the private and public sectors. As a result, policy makers in several countries have modified their remuneration system for physicians, so as to encourage productivity, as well as to contain the cost of care (Simeons & Hurst, 2006). Some OECD countries (Greece, Portugal, Spain and Sweden), where health care is financed through taxation, hire GPs directly and remunerate by salary, while in others (such as in Australia, Norway, the United Kingdom, Denmark, and New Zealand), where GPs are freelance remuneration occurs through capitation/blended or salary or fee-for-service (Simeons & Hurst, 2006). GPs in countries with an insurance-based system are remunerated mainly through the fee-for-service method, such as in Austria, Belgium, France, Germany, Japan, Switzerland, the United States and Korea (Simeons & Hurst, 2006). Over the past decade, several GP payment schemes have been adopted in Canada (Xu & Yu, 2003). A summary of the alternative clinical payment types adopted by the Canadian provinces and territories is represented in Table 1, below. The most prominent form of GP remuneration in Canada is fee-for-service payments, where GPs are compensated for each unit for service according to the bargained fees (Wranik & Durier-Copp, 2010; Holden & Madore, 2002; Devlin & Sarma, 2008). There appears to be a move towards the alternative payment plans (APP) among physicians, government and regional health authorities as shown on Tables 2 and 3, below. Moreover, in British Columbia and Quebec, policy makers are increasingly remunerating GP through the alternative methods (Xu & Yu, 2003). CIHI 10 reported that in 2004\2005 approximately 80% of remuneration to family physician was on fee-for-service basis (Wranik & Durier-Copp, 2010). The other type of GP remuneration is the APP, which includes salary, sessional fees, capitation, and blended funding arrangement. Other less common APP payment mechanisms include service arrangement (utilized in recruitment and retention of general practitioners in rural areas, and may come as contractual payments or the blended payment, i.e., APP and FFS); and block funding, where annual budgets are negotiated for a group of general practitioners to provide all their medical services for a specific period of time at specific sites. This is mainly used in academic medical centre for clinical services, education and research (Martin & Hogg, 2004). In Canada, the APP remuneration plan accounts for approximately 20% of primary care physician's remuneration plan (CIHI, 2008). Regardless of the widespread utilization of fee-for service payment, recent assessments particularly among researchers and policy makers have shown that the fee-for-service payment is not the most efficient mode of GP payment (Wranik & Durier-Copp, 2010; Xu & Yu, 2003). Studies conducted in Ontario and Quebec have shown that salaried general practitioners practicing in community health centres provide more preventive services than their fee for service counterparts or colleagues. These findings are however debatable because they are based on personal perception and a low response rates (Lee et al., 1999). Several studies have shown that the methods of payment for GPs influences their behaviour, the mode of service delivery, quality and cost of health care provided (Gosden, Pedersen & Torgerson, 1999; Scott & Hall, 1995). Further, given that efficiency, equity and quality are greatly dependent on workers' incentive, an adequate understanding of 11 determinants of physician behavior is essential, in order to carve out appropriate policy to guide allocation and incentive (financial) decisions that may improve quality and access to care. Thus, an adequate evaluation of GP remuneration on health care service delivery should be based on the performance measured in terms of patient health outcomes, patient and provider satisfaction, decrease cost and quality of primary physician services. Additionally, the quality of primary physician services plays an important role in the utilization and effectiveness of specialized health services (Hogg et al. 2007). To date, there has been a paucity of research on the influence of the various GP remuneration plans with regard to how it translates into better delivery of in primary care (Devlin & Sarma, 2008), particularly in Canada where GP remuneration reforms are still in their infancy. Hence, this study will be relevant for policy on efficient and effective physician remuneration. In the next section will discuss the various GP payment methods adopted in Canada. 12 Table 1 Summary of Alternative Clinical Payment Type by Province and Territory, 2005-2006 N.W.T. Y.T. B.C. AB. SASK. MB. ONT. QUE. N.B. N.S. CIHI, 2008 P.E.I. N.L. Salary Yes - Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Sessional Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Capitation - - - Yes - Yes - - - Block Funding - - - Yes - Yes Yes - Yes - Blended - - Yes Yes Yes - Yes - - Yes Emergency and on Call - - - Yes - Contract/unspecified - Yes Yes Yes Yes - Yes - Yes Yes Information collection Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Others - - - - - Yes Alternative Payment Types Yes - - Yes Yes Yes . . . Note. The blank space represents year that data were not submitted. Further, most of the provinces may not have reported on a particular payment type/s because the amount of physician receiving remuneration under the plan may be insignificant. 13 Fee-for service (FFS) The FFS payment scheme remunerates GPs based on a negotiated rate for each individual service they provide to a given patient (Drossos, 2002; Matthew & Lockhart 2003). Thus the GP makes claims for each unit of service provided to patients from the provincial or territorial health insurance plan (Xu & Yu, 2003; Holden & Madore, 2002). The general practitioners' gross annual income will be dependent on the number of hours worked, patients treated and the varieties of health service provided (Drossos, 2002; Holden & Madore, 2002). The FFS payment scheme is implemented in whole or part in several OECD member countries. In countries like Japan, Australia, Germany, and Belgium physicians are remunerated exclusively under the FFS. Others like Norway and the United States have incorporated portions of the FFS scheme in reimbursing physicians (Fujisawa & Lafortune, 2008; Holden & Madore, 2002). In 2005-2006 fiscal years, the CIHI reported that the "total in-province" FFS payment (without payments for services like radiology, laboratory and anaesthesia, as well as anaesthesia specialty) to physicians were approximately $10.2 billion, in addition to $248 million for standardized service delivered (CIHI, 2008). Further, of this $10.2 billion; approximately $4.9 billion (48%) and $5.3 billion (52%) accounted for FFS payments to general practitioners and specialist respectively. Additionally, of the $248 million for standardized services, the general practitioners and specialist received approximately $161 million (65%) and $87 million (35%) (CIHI, 2008). Furthermore, of the overall $10.2 billion for fee-for-service remuneration, Ontario reported $4.3 billion (42%) while combine FFS payment of $4.5 billion (44%) was reported in provinces of Alberta, British Columbia and 14 Quebec (CIHI, 2008). Also, consultation and visits accounted for 86.2% of the claims and payment to FFS family physician, which is 81.1% of the services provided (CIHI, 2008). Table 2 presents a summary FFS remuneration for physicians' method as a percentage to all physicians. In British Columbia (BC) 87.5% of physicians, 72.9 in Manitoba (MB), 91.5 in Ontario (ONT), 72.1 in Nova Scotia (NS), 81.9 in Prince Edward Island (PEI), 97.2 in Alberta (AB), and 80.8 in Quebec (QUE) were remunerated under the FFS method in 2000-2001 fiscal year. Conversely, in 2005-2006 fiscal year, 79.6% of physicians in BC, 68.7 in MB, 81.6 in ONT, 57.2 in NS, 64.2 in PEI, 87.7 in AB, and 75.9 in QUE were remunerated under the fee-for-service method in 2000-2001 fiscal year (CIHI, 2008). This decline in FFS remuneration for physician in Canadian provinces and territories reflects a gradual shift to alternative forms of remuneration for physician. There is considerable empirical evidence documenting the merits and the demerits of utilizing the FFS approach in remunerating general practitioners. The intrinsic worth of FFS will be highlighted in relation to improved patients' outcome and improved provider satisfaction, and decreased costs. First, under the FFS, several studies have shown that patients cared for under FFS GPs have better access to health care services in comparison to patients under the care of a GPs paid under an alternative remuneration (Xu & Yu, 2003; Holden & Madore, 2002; Drossos, 2002). Second, several studies have documented that, under the FFS, GPs are being paid according to the number of patients treated. Thus the amount of patients treated will equate to the amount of income. Consequently, this makes the FFS remuneration scheme more enticing to primary care physicians because they tend to have control over their net revenue (Holden & Madore, 2002; Drossos, 2002). Third, as mentioned previously, GPs under FFS are remunerated based on the number of patients seen 15 and treated. Thus, this creates a compelling incentive for the GPs to provide health care services in a more economic and efficient fashion (Holden & Madore, 2002), thereby benefiting the healthcare system economically. Finally, the FFS scheme makes it easier for government to initiate targeted FFS codes like, health promotion, disease-prevention services, and chronic disease management programs (Xu &Yu, 2003). On the other hand, the demerits of FFS remuneration for the general practitioner are also well documented in the literature. Firstly, GPs are remunerated according the number of patients treated. Thus this may provide GPs with a financial incentive to opt for procedureoriented specialty and reject engaging in non-billable services, such as using fewer expensive sources of care and patients consultation (Matthew & Lockhart 2003). These conclusions were echoed by Holden and Madore (2002) who reported that GPs under the FFS remuneration scheme over-strain the health care system with unnecessarily expensive procedures on the grounds that they have the propensity to pay better. The fees may also vary depending on the kind of service delivered; thus, there is an incentive to deliver more services so as to increase income (Gosden et al 2001; Devlin & Sarma, 2008; Xu & Yu, 2003; Holden & Madore, 2002). As a result, incentive-driven services may result in 'supplier induced demand' (SID), where patients are over treated (Gosden et al., 2001; Drossos, 2002), hence, increasing the overall health care cost (Xu & Yu, 2003). Consequently, uncontrolled health care cost as a result of GPs budgetary cost has made it difficult for health authorities to curb the overall cost of health care and the impact on the health system (Holden & Madore, 2002). In Canada, the uncontrollable FFS expenditure has resulted in five Canadian provinces (British Columbia, Manitoba, Ontario, Quebec and Saskatchewan) incorporating some cost containment strategies like placing a 16 ceiling on the maximum number and kind of services a FFS physician can claim in a fiscal year (Xu & Yu, 2003). Similarly, this same cost containment strategy is being implemented in Germany and has been proven effective (Fujisawa & Lafortune, 2008). Another demerit of the FFS payment plan documented in the literature is that, given visit-time limitations, GPs under the FFS are remunerated on the basis of the number of patients seen or treated, i.e., incentivized to provide a more frequent and quicker services (Holden & Madore, 2002). Thus patients have insufficient visit-time with the GP, particularly among elderly patients with complex morbidities. As a result, elderly and sicker patients may be discriminated against or denied access to quality care (Xu & Yu, 2003; Drossos, 2002). 17 Table 2 Physicians' Fee-for-service Remuneration Method as a percentage of all Payment to all Physicians N.W.T. Y.T. B.C. AB. SASK. MB. ONT. QUE. N.B. N.S. CIHI, 2008 P.E.I. N.L. 2000-2001 - - 87.5 97.2 78 72.9 91.5 80.8 83.5 72.1 81.9 67.6 2001-2002 - 95.3 82.5 93.2 75.8 72 88.1 78.7 82 69.8 81.9 60.7 2002-2003 - 92 80.8 91.3 72.9 70.5 88.5 78.1 81.5 68.4 75 57.8 2003-2004 2.6 88.5 80.3 90.9 74.1 70.1 84.0 77 77.9 64.3 69.5 58.2 2004-2005 5.6 83.7 80.1 89.2 73.6 70.4 83.2 76.1 76.3 58.5 66.9 58.8 2005-2006 3.9 84 79.6 87.7 74.1 68.7 81.6 75.9 74.7 57.2 64.2 62 Fiscal Year Note. The blank space represents year that data were not submitted. Further, most of the provinces may not have reported on a particular payment type/s because the amount of physician receiving remuneration under the plan may be insignificant. 18 Table 3 Physicians' Alternative Remuneration Method as a percentage of all Payment to all Physicians B.C. AB. SASK. MB. ONT. QUE. N.B. N.S. CIHI, 2008 P.E.I. N.L. 12.5 2.8 22 27.1 8.5 19.1 16.5 27.9 18.1 32.3 4.7 17.5 6.8 24.2 28 11.9 21.3 18 30.2 18.1 39.3 N.W.T. Y.T. Fiscal Year 2000-2001 2001-2002 2002-2003 97.4 8 19.2 8.7 27.1 29.5 11.5 21.9 18.5 31.6 25 42.2 2003-2004 94.4 11.5 19.7 9.1 25.9 29.9 16 23 22.1 35.7 30.5 41.8 2004-2005 94.4 16.3 19.9 10.8 26.4 29.6 16.8 23.9 23.7 41.5 33.1 41.2 2005-2006 96.1 16 20.4 12.3 25.9 31.3 18.4 24.1 25.3 42.8 35.8 38 Note. The blank space represents year that data were not submitted. Further, most of the provinces may not have reported on a particular payment type/s because the amount of physician receiving remuneration under the plan may be insignificant. Alternative payment plan (APP) The escalating health care cost and the increasing aging population creates a significant challenge to the sustainability of the health care delivery system, particularly the publicly funded system (Delvin & Sarma, 2008; Hurst, Forde, Reiter-Theil, Slowther, Perrier & Pegoraro et al., 2007). Consequently, several industrialized countries have reformed or are in the process of reforming, their health care delivery system as a result of budgetary constraints (Delvin & Sarma, 2008), focusing particularly on the mode of physician remuneration. In contrast to the fee-for-service, the most predominant mechanism of payment for general practitioners, quite a number of alternative payment mechanisms are also being employed. In 2005-2006, CIHI reported that the overall payments made to physician through the alternative payment mechanism was approximately $2.98 billion, representative of 21.3% of the overall payments made to physicians for clinical services in Canada (CIHI, 2008). Further, over the previous six years the overall expenditure for alternative payments to physician for clinical services increased significantly, from $1.31 billion (13.0%) in 2000-2001 to $2.98 billion (20.3%) in 2005-2006 (CIHI, 2008). From Table 3, a summary of physicians' alternative remuneration method as a percentage of all payment to all physicians showed that, 12.5% of physicians in BC, 27.1 in MB, 8.5 in ONT, 27.9 in NS, 18.1 in PEI, 2.8 in AB, and 19.1 in QUE were remunerated under the alternative method in 2000-2001 fiscal year. Conversely, in 2005-2006 fiscal year, the proportion of alternative payment mechanism varied substantially across province in Canada, ranging from 96.1% in Northwest Territories to 42.8% in NS, 38.0% in NL, 35.8% in PEI, 31.3% in MB to 25.9% in SASK, 25.3% in NB, 24.1% in QUE, 20.4% in BC, 18.4% in ONT, 16.0% in the YT and 12.3% in AB (CIHI, 2008). 20 A review of academic and grey literature on alternative remuneration plans for GPs demonstrated that there are merits and demerits of remunerating physicians through this mechanism. Thus, in evaluating Alternative Payment Plans, I will focus on four most widely used alternative remuneration plans, i.e., salary, capitation, sessional fees and blended remuneration mechanism. Salary remuneration mechanism. The salary remuneration mechanism is a defined payment to the GPs negotiated annually between the physician and the government, regardless of the volume of services executed (Wranik & Durier-Copp, 2010; Xu & Yu, 2003; Fujisawa & Lafortune, 2008; Holden & Madore, 2002). Thus, under the salary remuneration mechanism, services are impartial since it is independent of the amount or cost of services provided (Xu & Yu, 2003). Moreover, GPs negotiate their salaries and enjoy certain additional benefits (Wranik & Durier-Copp, 2010), that can be adjusted based on seniority and promotions (Holden & Madore, 2002). The salary is a predominant form of remuneration for GP in a number of OECD countries, including Iceland, Finland (Fujisawa & Lafortune, 2008), Sweden and France (Holden & Madore, 2002). This is due to the fact that GPs in these countries are employees of the public health authority, giving the public sector a significant role (Fujisawa & Lafortune, 2008; Holden & Madore, 2002). Traditionally, most GPs under the salary remuneration mechanism signed a contract with the ministry or health authority (Wranik & Durier-Copp, 2010) and are required to work a specific number of hours per week and most often a specific geographical location or population (Wranik & Durier-Copp, 2010). The salary remuneration mechanism is operational in all Canadian jurisdictions with an intention of curbing the cost of care increasing quantity of services, and improving GP 21 recruitment and retention (Wranik & Durier-Copp, 2010). However, recruitment and retention of GPs in rural and remote communities has been difficult (Wranik & Durier-Copp, 2010). This may be as a result of the inadequate availability of social amenities and general living conditions in rural and remote communities (Wranik & Durier-Copp, 2010). Further, remunerating GPs practicing in rural and remote via salary rather through capitation or FFS plan will boost their retention, since a "low patient base" and sparse population of the rural and remote communities may be a major determinant. Therefore APP provides a stable, predictable and high income for GPs working in remote and rural communities (Wranik & Durier-Copp, 2010). There are several advantages associated with the salary remuneration mechanism for general practitioners. First, as a corollary to salary remuneration, general practitioners have no reason to over-service, prescribe avoidable treatments or visits irrespective of the type or level of services provided, contrary to the FFSs mechanism that rewards GP for such behaviour (Holden & Madore, 2002; Xu & Yu, 2003). Thus, APP is more likely to result in consistency and sureness of services and procedures performed (Holden & Madore, 2002). Secondly, the salary remuneration mechanism eradicates any form of financial penalties associated with lengthy patient visits under the FFS. Thus, GPs have the liberty to have a thorough consultation, thereby promoting more preventive care resulting in improved health care outcomes (Holden & Madore, 2002). Third, the salary remuneration mechanism has the potential to induce a more efficient use of health care resources (Holden & Madore, 2002; Devlin & Sarma, 2008). Since salaried GPs are associated with larger primary care centres that utilize a variety of health care providers, health care centres and authorities have the potential to effectively distribute patients and responsibilities to their employees in a more 22 efficient and cost-effective approach (Holden & Madore, 2002). Further, this eliminates the propensity of'cream-skimming'1 associated with capitation mechanisms and a subjective selection with the FFS remuneration mechanism (Xu & Yu, 2003). APP also allows for increased consultation with the interdisciplinary team resulting in more comprehensive care to patients. On the other hand, several studies have identified a number of demerits associated with salary remuneration mechanisms for GPs. First, salaried GPs have little incentive to see more patients, since salary remuneration is independent to the level of service provided, whereas, the FFS remuneration is dependent on the level of services provided (Lee et al., 1999; Holden & Madore, 2002; Xu & Yu, 2003; Devlin & Sarma, 2008). Many studies have demonstrated that salaried practitioners provide fewer services in comparison to GP under the FFS remuneration (Xu & Yu, 2003). This may be due to the fact that salaried GP are more likely to be working in underserviced or high-need population where comprehensive care and more consultation time are required per patient (Tu, Cauch-Dudek & Chen, 2009; Delvin, Sarma & Hogg, 2006). Second, salaried GPs have little incentive to retain steady patient populations, hence posing a significant challenge for patient-physician relationship and continuity of care (Xu & Yu, 2003; Holden & Madore, 2002). This is more prevalent in urban areas than rural and remote areas. Third, GPs under the salary remuneration 1 'Cream skimming' is a term that refers to "choosing patients for some characteristic(s) other than their need for care, which enhances the profitability or reputation of the provider" (Friesner & Rosenman, 2009). 23 mechanism may have diminished satisfaction with the health care system, since physician autonomy is reduced as a result of more governmental control (Xu & Yu, 2003). Fourth, under the salary remuneration mechanism, the supply of medical services and physicians are independent of the costs, thus an increase in demand of medical services may result in increased wait times (Devlin & Sarma, 2008) and a reduction in the number of patient visits may result in increasing the cost of care, i.e., hiring more GPs (Holden & Madore, 2002). Finally, under the salary remuneration mechanism, patients may slip through the health care system particularly those at the margin, because the hours of operation under the contractual arrangement may not correspond with the timing or access the high-need population requiring care (Holden & Madore, 2002). Capitation remuneration mechanism The capitation remuneration mechanism, also known as 'rostering' (Xu & Yu, 2003; The College of Family Physician of Canada (CFPC), 2007), is the flat payment to the GP for each patient enrolled with them, in return for a commitment that they will provide a basket of services to their patients or practice population over a period of time (Fujisawa & Lafortune, 2008; CFPC, 2007; Gosden, Forland, Kristiansen, Sutton, Leese, Giuffrida et al., 2006; Xu & Yu, 2003; Drossos, 2002, Holden & Madore, 2002). This implies that the remuneration of GPs is dependent on the number of patients on their list and the level of care provided per patient, which is typically negotiated between the health care providers and funders. The capitation fee per patient amount is adjusted according to sex, age, and geographical location (Fujisawa& Lafortune, 2008; Drossos, 2002; Holden & Madore, 2002). The efficiency of the capitation mechanism is dependent on the patients' commitment, meaning that patients must be committed to seeking primary care services from a pre-determined GP or group practice 24 (Holden & Madore, 2002). This commitment on the patient's part can be done in two ways: through a voluntary patient enrolment or propinquity-based registration where patients are automatically enlisted or assigned to a particular practice in their region (the latter is predominant in rural and remote area) (Holden & Madore, 2002). In many industrialized countries like Italy, New Zealand and the Netherlands, capitation is the most prominent form of remunerating GPs. In 2007 the College of Family Physician of Canada (CFPC) reported that the capitation remuneration mechanism is increasingly becoming the preferred mechanism of GP remuneration in Canada. Moreover, several health authorities have been directed by provincial and territorial governments to take up the responsibility to remunerating general practitioners for the services provided to local population. Further, the escalating cost for health care associated with physician remuneration has motivated health authorities to seek means of containing the cost of health care by budgeting general practitioners remuneration in a rather predictable manner (CFPC, 2007). Capitation is particularly interesting to health authorities, because health care funding is based on need rather than entirely on service utilization (2007). Hence, the capitation is a rising method for remunerating general practitioners (Tu et al., 2009; Fujisawa & Lafortune, 2008). Moreover, newer capitation mechanisms in Canada include financial incentives for reaching certain goals for preventive care (Tu et al., 2009). This contributes to better care of chronic diseases. Several potential advantages of capitation remuneration for general practitioners have being highlighted in the literature. First, GPs remunerated by capitation have incentives to contain costs and financial risk, due to the predetermined payments to the GPs for the care of their enrolees (Gosden et al, 2006; Xu & Yu, 2003). Further, this offers fiscal predictability 25 to the payer, as well as relative income predictability for the GP (CFPC, 2007). Second, there is less incentive for GPs under capitation to over-service or provide unnecessary care, since, revenue received and the number of services provided are negatively correlated (Xu & Yu, 2003; Holden & Madore, 2002). Third, the capitation mechanism offers a long term relationship or longitudinal relationship between the patient and physician or a specific population and the physician. This aligns patients with a suitable GP, encouraging continuity, preventive and completeness of care. Thus GPs are remunerated for affirmative health outcome of their patients rather than for the amount services of provided as in the fee-forservice (CFPC, 2007; Xu & Yu, 2003; Holden & Madore, 2002; Drossos, 2002). Fourth, GPs under the capitation mechanism are remunerated based on the number of patients enrolled with them; hence, this provides a strong incentive to GPs to offer services that resonate with the needs of their patients, thereby promoting and sustaining strong patient satisfaction (Holden & Madore, 2002). There are several problems associated with the capitation remuneration mechanism that health care experts have identified. First, the capitation mechanisms as mentioned previously incentivizes GPs to provide health care services in a practical, cost-effective manner, thereby providing only that care which is appropriate. On one hand, this may result in GPs providing fewer services (fewer examination, attention and shorter consultation time) than the population may actually need, since the GP is required to roster a large number of patient in other to stay within the capitated amount negotiated (CFPC, 2007; Gosden et al., 2006; Xu & Yu, 2003; Drossos, 2002; Holden & Madore, 2002). Second, several empirical studies have argued that GPs under the capitation remuneration have the potential to "cherry pick" patients that are easier to care for rather than those who have with complex morbidities 26 because of their health status, particularly in cases where rostering is by recruitment and alternatives are limited (CFPC, 2007; Gosden et al., 2006; Xu & Yu, 2003; Holden & Madore, 2002). Third, in rural and remote communities with an inadequate number of GPs, patients under a GP paid with the capitation mechanism have limited freedom of choice, since recruitment is by geographic rostering (Holden & Madore, 2002). Blended remuneration mechanism An effective remuneration for GPs should translate into an effective delivery of care that is in compliance with overarching objectives of the health care system (cost control, quality of care and good patients' access to care). However, the outstanding question remains, how best can general practitioners be remunerated thereby actualizing these objectives (Xu & Yu, 2003)? Several empirical studies have suggested that the blended remuneration mechanism may be central to this goal, since the blended remuneration is not only a specific mechanism of remuneration but a combination of several remuneration types (Xu & Yu, 2003; Holden & Madore, 2002). Further, the policy shift of the GP to a blended capitation model as promoted by the Canadian Primary Health Care Transition Fund (PHCTF)2 is focused on improving access to health care, health outcome, quality and cost efficiency (Martin & Hogg, 2004). The two prominent blended remuneration types documented in the literature particular to the Canadian health care system are blended capitation model and the blended complement model. The 'blended capitation model', also known as the Family Health Network (Glazier, Klein-Geltink, Kopp & Sibley, 2009), makes a based payment to a GP per patient in return 2 The PHCTF was established in 2000, with $800 million fund setup to support efforts of provinces and territories to develop and implement transitional primary health care renewal initiatives (Health Canada, 2004). 27 for the provision of comprehensive care, in addition to incentives for the provision of specific primary care services (Ontario Ministry of Health and Long-Term Care, 2009). Second, the 'blended complement model' provides compensation based on the number of physicians within the group. Thus general practitioners are offered a base payment for the provision of comprehensive care, in addition to incentives for provision of specific primary health care services, as well as funding for emergency service (Ontario Ministry of Health and Long-Term Care, 2009). There are several empirical advantages and disadvantages that have been identified with the blended remuneration mechanism for GPs. The advantages of remunerating GPs include minimizing the tendency to under-service and 'cherry-pick' patients, as well as curbing the overall health care cost (Ontario Ministry of Health and Long-Term Care, 2009; Xu & Yu, 2003; Holden & Madore, 2002). On the other hand, the disadvantages of blended payment include difficulties in setting or developing combination proportions, since blended remuneration is a combination of two or more payment types (Xu & Yu, 2003). Furthermore, the blended remuneration attenuates the advantages of the "pure" remuneration scheme (Holden & Madore, 2002). Moreover, the blended remuneration requires maintaining different payment schedules, thus may increase the administrative burden and cost (Holden & Madore, 2002). In sum, the fee-for services remains the most prominent form of remunerating GPs in Canada with exception of the territories. Provincial and territorial governments negotiate the fee schedule with the health care providers. The Canada Health Act prohibits provinces from allowing private billing for publicly insured services by physicians, otherwise they are penalized financially. In most provinces, budget cap was introduced for fee-for-services 28 payments to GPs. The essence of this ceiling was to curb the increasing cost of care. The advantages and disadvantages of the fee-for service remuneration for general practitioners are itemized on Table 4. In recent years, all Canadian jurisdictions have developed one form of alternative remuneration for GPs, such as salary, mixed payment method, and blending FFS with the salary or capitation model. This shift towards an alternative payment is an attempt to control the cost of care and also to transfer some of fiscal the responsibility from funders to providers, like in the capitation-based models in primary health care. The merits and demerits of the alternative are also itemized on Table 4. In 2004, approximately 20% of physicians (including both GPs and specialists) received a form of alternative remuneration other than FFS (Fujisawa & Lafortune, 2008). In Alberta and British Columbia, physicians are either paid by contract, session or salary; in Ontario50 % of general practitioner are remunerated with the alternative model other than fee-for-service (Fujisawa & Lafortune, 2008). Alternative forms of remuneration also exist in most other provinces in Canada. Remuneration of health professional remains one of the largest drivers of cost of provision of health services. Thus making remuneration a pivotal concern for policy makers endeavouring to improve efficiency, access and quality of care provided while curbing the escalating cost of care, particularly in the primary health care. 29 Table 4 Evaluating Physician Remuneration Methods Remuneration Type Fee-for-service Salary Capitation Blended Advantages Disadvantages i. Better accessibility ii. Target income iii. Better Physician autonomy iv. High volume driven v. Incentives for health promotion i. No incentive to over service ii. Reduces cream-skimming iii. Increased budget certainty iv. More efficient use of resources v. Consistency and sureness of service provided i. Improved budget certainty ii. Better patient-physician relationship iii. services resonant with patient needs iv. Less incentive to over-service v. Income predictability for physicians i. Reduces under-servicing i. Incentives to over service ii. Limited for sicker less capable patients iii. Promotes quicker and frequent services iv. Short visit and consultation with GP v. Unpredictable budget ii. Reduces cream-skimming iii. Curbs health care cost i. No incentive to see more patient ii. No incentive for continuity of care iii. Reduced Physician autonomy iv. Inadequate services for vulnerable population i. Reduced Physician autonomy ii. Cream-skimming in recruitment iii. Providing only necessary care iv. Incentives to over service i. Difficulty in developing combination proportion ii. Increased administrative burden and cost 30 Primary Health Care In this era of shrinking health care resources and budgetary constraints, the capacity of health care providers to respond to the need of the increasing ageing population and those with chronic diseases has become severely limited. Hence, recent cost reduction strategies have resulted in the need to identify where and how health care resources might be effectively invested and monitored to yield the desirable goal of efficient care delivery (World Health Organization, 1996; Roos, Walld, Uhanova & Bond, 2005). It is generally accepted that an integrated primary health care (PHC) sector plays a key role in delivering preventive services, diagnosis, in long term disease management, and in the coordinating of specialized care (Shah et al., 2003). Thus, exploring the relevance of an effective primary health care system to health service utilization delivered in ambulatory care settings is important is important to curbing health care cost and improved patient outcome. Further, high rates of hospitalization for ACSCs may provide indirect evidence of problems associated with patient access to primary care. In the Canadian context, a commonly used definition from the Canadian Health Services Research Foundation (CHSRF) is: "primary health care is defined as a set of universally accessible first-level services that promote health, prevent disease, and provide diagnostic, curative, rehabilitative, supportive and palliative services" (Lamarche, Beaulieu, Pineault, Contandriopoulos, Denis & Haggerty, 2003, pp. 2). Primary care according to Starfield (1998), is "that level of a health service system that provides entry into the system for all new needs and problems, provides person-focused (not disease-oriented) care over time, provides care for all but very uncommon or unusual conditions, and co-ordinates or integrates care provided elsewhere by others." (pp. 8-9). This implies that primary care is an 31 integral part health care system or primary health care, since primary care focuses on health care services that include health promotion, diagnosis, prevention and treatment of illness and injury (Health Canada, 2006). The 1978 Declaration of Alma-Ata defined primary health care as: ...essential health care based on practical, scientifically sound and socially acceptable methods and technology made universally accessible to individuals and families in the community, through their full participation and at a cost that the community can afford to maintain at every stage of their development in the spirit of self-reliance and self-determination. It forms an integral part both of the country's health system, of which it is the central function and main focus, and of the overall social and economic development of the community. It is the first level of contact of individuals, the family and the community with the national health system, bringing health care as close as possible to where people live and work, and constitutes the first element of a continuing health care process (World Health Organization, 1978, pp. 1-2). Primary health care provides a two-fold function in the health care system. First, primary health care provides direct first-contact services with the health care system via providers like general practitioner, pharmacist, nurse practitioners, and telephone counseling services. Second, primary health care coordinates services to maintain continuity of care, as well as easy movement within the system. This enables care to be integrated when patients require specialized care from specialist (Health Canada, 2006). According to Lamarche et al. (2003), the six broad outcomes the primary health care system should produce are effectiveness (ability to improve or maintain health); productivity 32 (the cost, type, nature of service for health concern); accessibility (easy accessing general practitioner, specialized and diagnostic services); continuity (extent to which care is provided as a consistent progression of episode); quality (appropriateness of care as perceived patient and provider); and responsiveness (accommodation for the expectation and preference of patient and provider). Further, with the ageing population and the increasing rate of chronic illnesses, the approach to treatment has to be modified as well. Thus primary health care plays an integral role in education, promotion and prevention of chronic diseases, since the major goal of primary health care is to enable patient to take responsibility for their own care (Khan, Mcintosh, Sanmartin, Watson & Leeb, 2008). This was echoed by the WHO in a statement that: The service delivery reforms advocated by the PHC [Primary Health Care] movement aim to put people at the centre of health care, so as to make services more effective, efficient and equitable. Health services that do this start from a close and direct relationship between individuals and communities and their caregivers. This, then, provides the basis for person-centredness, continuity, comprehensiveness and integration, which constitute the distinctive features of primary care (WHO, 2008, pp. 43). Consequently, timely access to primary health care is an essential quality indicator of the performance of the overall health care system. One instrument for measuring access to PHC is to examine the rate of health service utilization for ambulatory care sensitive conditions, ACSC, (Shah et al 2003; Billings et al., 1993; Pappas et al., 1997; Bindman et al., 1995; Ansari et al, 2006; Rizza et al., 2007; Chen et al., 2009, Gao et al., 2008; Blustein et al., 1998). 33 Ambulatory Care Sensitive Conditions In the Canadian health care system access to care is universal, thus everyone has access to care regardless of their economic status. The Canadian Health Act 1984 specifies that health care services must be publicly administered, universal, accessible, portable and comprehensive (Madore, 2005). Thus, considering this provision in the Canadian Health Act, one may presume all hospitalizations are appropriate, particularly in a scenario where resources are inadequate and the population is ageing. However, in principle, it is well documented in the literature that many hospital resources are used inappropriately, whether by providing services that do not translate into health benefit, or providing services that would have been provided at a different organizational level utilizing lesser resources (CIHI, 2008). This reflects the deficit in preventive care leading up to hospitalizations for conditions sensitive to the primary health care settings. One indirect measure used in defining preventable hospitalizations or the overall performance of the health care system is to identify those conditions for which hospitalizations are generally considered preventable i.e. ambulatory care sensitive conditions (ACSC) (Brown et al, 2001; Shah et al., 2003). The hypothetical concept of ACSC was developed by Billings et al. (1993), and refers to conditions for which hospitalization might be avoided with timely and effective outpatient care, that either prevents the onset of the condition, assists in managing a chronic condition, or helps controlling acute periodic condition (Roos et al. 2005; Caminal, Starfield, Sanchez, Casanova & Morales, 2004; Parker et al., 2005; Rizza et al., 2007; Flores, Abreu, Chaisson & Sun, 2003). The ACSC diagnosis lists generally include the following conditions: asthma, diabetes, chronic obstructive pulmonary disease (COPD), angina pectoris, cellulitis, 34 congestive heart failure (CHF), dehydration, dental conditions, diabetes, gastroenteritis, seizure disorders, hypertension, hypoglycaemia, vaccine-preventable conditions, urinary tract infection, pneumonia, severe ear/nose/throat infection, tuberculosis, nutritional deficiency (Billings, Anderson & Newman, 1996). Hospitalization rates for ACSC conditions have been linked with the absence or presence of adequate and effective principal or preventive care (Roos et al 2005; Billings et al., 1993; Chen et al., 2009). Comparing rates of hospitalization for ACSC across populations or communities can therefore provide insight into the quality of care in the ambulatory care settings of these populations or communities. Further, it is assumed that the disproportionate rates of hospitalization for ACSC in a given population or community indicates delay in diagnosis or treatment of these conditions because of insufficient access to PHC. Moreover, reducing ACSC hospitalization is a cost restraining mechanism that will enhance patients' quality of life and efficient use of the health care delivery system (Clancy, 2005; Chen et al., 2009). In 2001 the Agency for Healthcare Research and Quality (AHRQ) published Preventive Quality Indicators (PQIs) as an instrument to measure rates of ACSC hospitalization, with the presumption that access to primary care could be improved (AHRQ, 2001). The concept of ACSC has been widely researched in several western countries including Canada, Australia and the U.S. (Rizza et al., 2007; Ansari et al., 2006), as well as many European countries (Rizza et al., 2007). Hospitalization rates for ACSC have been widely used as a measure of access to care. However, these rates varies by populations (Billings et al., 1993), with higher rates being documented for Aboriginal people in Canada (Shah et al., 2003; Lavoie et al. 2010) and geographical location, with higher rates in 35 communities with a lower aggregate income level (Billings et al., 1993). Furthermore, other factors that influence rates in ACSC hospitalizations are inadequate access to primary care (Rizza et al., 2007; Bindman et al., 1995); and greater supply of hospital bed (Rizza et al., 2007), as well as socioeconomic indicators, with higher rates among uninsured individuals particularly in the U.S. (Billings et al., 1993). Further, hospitalization for ACSC is higher among rural residents in comparison to the urban counterparts, because rural residents have lower health status and shortage of primary care facilities and physician when compared to their urban counterpart (Chen et al., 2009). This disparity in ACSC rates between rural residents and urban residents may also be as a result of people traveling longer distances for care and are often admitted so as to precipitate care or supports might be inadequate; hence people get admitted into so call "social admissions". Moreover, Billings and colleagues (1996) found that Canadians from low income communities were 40% more likely to be at risk for avoidable hospitalizations in comparison to their counterparts in high income communities (Blustein et al., 1998). In 2010, Lavoie and colleagues used a full range of ACSC diagnosis (chronic, acute and vaccinepreventable) to explore the relationship between of community controlled health services and local access to primary health care services for Aboriginal people in Manitoba. Their study demonstrated that Aboriginal communities with improved access to primary health care at the local level (such as nursing stations) had lesser rates of hospitalization for ACSC, in contrast to communities with limited access to primary health care at local level, where rates hospitalization for ACSC were higher (Lavoie et al., 2010). The Canadian Institute for Health Information (CIHI) identified a significant downward trend in rate of ACSC hospitalization for the Canadian population younger than 36 age 75 (exclude Quebec); however, Canadians aged 64 to 74 accounted for 50% of all ACSC hospitalization (CIHI, 2009). This study explored trends in ACSC hospitalization rates for seven conditions (angina, asthma, COPD, diabetes, epilepsy, heart failure and pulmonary edema, and hypertension). They estimated that about 1 in 8 (13%) medical hospitalizations in Canada for patients younger than 75 years of age were for ACSC (CIHI, 2008). Further, ACSC admission rates ranged from a low of 281 per 100,000 in British Columbia population to a high of 1,298 per 100,000 in Nunavut (CIHI, 2009). The same studies found that ACSC hospitalization rates were 60% higher in rural communities (510 per 100,000 population) in comparison to urban communities (318 per 100,000 population) (CIHI, 2008). Moreover, the rates for ACSC hospitalization increased as income level decreased, since those living in less affluent areas were 2.6 times more likely to be hospitalized for ACSC than those living in an affluent area (CIHI, 2009). Despite the fact that the ACSC lists generally include a core diagnoses group, in most cases the conditions have been modified and selected to align with the population of interest. For instance, Weissman and colleagues excluded pulmonary emboli and stroke in their list of ACSC because avoidable hospitalizations for these conditions were considered to be arguable (Pappas et al., 1997). Furthermore several other researchers have excluded congestive heart failure and pneumonia in their study of older populations because these conditions are viewed as an unavoidable trajectory for elderly people, even though these two conditions are the most common cause hospitalization for elderly people (Bindman et al., 1995; Pappas et al., 1997). One reason for measuring ACSC hospitalization rates was the assumption that these conditions are sensitive to care in the primary health care system. While this method is 37 widely used in the literature, no studies were found that have examined the relationship of GP payment schemes and avoidable hospitalization for ACSC. Hence, this study is innovative and timely, particularly with the changing demographics care should be delivered smartly so it translates into lower cost, improved patient outcome and providers' satisfaction. Additionally, economic incentives for GPs are widely adopted by health care policy-maker to improve allocative effectiveness and quality in primary care (Lippi Bruni et al 2009). In spite of the evidence that incentive-based remuneration can have an influence on GP behavior, there is yet limited evidence to relate the impact of this policy on health outcomes with respect to hospitalization for ACSC (Lippi Bruni et al., 2009). Summary There is a robust body of knowledge in the literature on general practitioner (GP) remuneration, ambulatory care sensitive conditions (ACSC) and primary health care. Several studies have explored the effectiveness of general GP remunerations on the health care system; however no studies were found that have employed health services utilization for ACSC. The literature is consistent in stating that the primary health care system is the bedrock of the health care system, hence adequate access to GPs is central, particularly in countries like Canada where they are the first point of contact with the health care system. One way of measuring access or quality of care is to capture those hospitalizations that could be avoided with high preventive care in the primary care settings. The literature has been inconsistent with the definition of ACSC conditions, as well as their predictors. This is the gap in the literature that this study proposes to address. 38 Chapter Three: Methods This Chapter provides an overview of the methods used in this study. This study was an analysis of health services utilization administrative data in order to examine rates and predictors of hospitalization, as well as trends in hospitalization for ambulatory care sensitive conditions (ACSC). This study employed administrative health utilization data on hospitalizations from the BC Ministry of Health Hospital Separations dataset, housed in Population Data BC for selected communities. Research Design This is a population-based database study. A retrospective cohort analysis of all hospitalizations classified as ACSC from 1992/1993 onward was conducted to compare trends and patterns of hospitalizations for ACSC in select communities with fee-for-service (FFS) and alternative payment plans (APP) for GPs. Descriptive statistics on selected communities were used to predict hospitalization rates for ACSC among selected communities that are matched based on their community and individual level characteristics. I also examined the data for relationships between GP payment schemes and rates of hospitalization for ACSC. Study populations In this study, aggregate-level hospitalization data was used to identify all individuals under 65 years of age on March 31, 2008, who were admitted to hospital for selected conditions classified as ACSC (see Appendix A for list of ICD-9 and ICD-10-CA codes) between April 1, 1992 to March 31, 2008 while living in selected communities (as shown in Appendix B). This study includes northern communities served by GPs remunerated with APP (McBride, Dunster, Fraser Lake, Valemount & Robson; Haida Gwaii (Queen Charlotte 39 & Sandspit) and Stewart) and FFS (Prince Rupert, Tumbler Ridge, Smithers and Telkwa) GP payment plans. Communities with APP and FFS are listed in Appendix B. Postal codes in the database were used to identify all patients in the selected communities hospitalized for ACSC; however, postal codes were not released to the researcher. Geographic information was provided as flags, i.e. ACSC hospitalizations from APP and FFS communities were flagged as APP and FFS respectively; ACSC hospitalizations from postal codes not listed were flagged as NA (see Appendix B). Community profile. A community profile for each community by demographic characteristics was extracted from the 2006 census data as well as Northern Health. This study is intended to investigate the quality of and access to primary care physicians for selected communities. These parameters were measured using the hospitalization for ACSC in five Northwest communities (Prince Rupert, Stewart, Queen Charlotte, and Smithers), three Northern interior communities (Valemount, McBride, and Fraser Lake) and one Northeast community (Tumbler Ridge). The profiles of these communities are discussed based on the demographic characteristics, health status, and health facilities in this community. Of the Northern Interior communities, the population of McBride was approximately 655, with 49.6% male and 50.4%o female; Fraser Lake was approximately 1115, with 51.6% male and 48.4%> female; Valemount was approximately 1020, with 51%> male and 49%> female (see Table 5). Of the Northwest communities, the population of Queen Charlotte with approximately 945, with 51.9%o male and 48.1% female; Stewart was approximately 495, with 49.5%> male and 50.5%> female; Prince Rupert was approximately 12,815, with 49.5%> male and 50.5%> female; Smithers was approximately 5,220, with 48.5%> males and 51.5% female (see Table 5). The 40 population of the Northeast community (Tumbler Ridge) was approximately 2,455 with 53% male and 47% female (see Table 5). The communities in this study have a relatively young population, with the average ranging from 36.1 years in Smithers to 42.9 years in Stewart. The average age for McBride, Prince Rupert, Fraser Lake, Queen Charlotte, Valemount, and Tumbler Ridge are 37.1, 38.5, 39.2, 41.1, 42.2 and 42.3 years respectively (see Table 5). The average age for McBride, v Prince Rupert, Fraser Lake, Queen Charlotte, Valemount, and Tumbler Ridge are 37.1, 38.5, 39.2, 41.1, 42.2 and 42.3 years respectively (see Table 5). The annual number of births for women of childbearing age is approximately 15, 15 -20, 8-10, 48, and 175 in McBride, Fraser Lake, Valemount, Queen Charlotte and Prince Rupert respectively. On the other hand, the annual death rate is 15, 12-15, 12, 30, and 116 in McBride, Fraser Lake, Valemount, Queen Charlotte and Prince Rupert respectively. The average life expectancy for residents in McBride, Fraser Lake, Valemount, and Prince Rupert is 78.5, 76.9 - 77.7, 78.5, and 78.9 years respectively (see Table 5). In Canada, chronic diseases and the risk factors associated with them remain a significant public health concern, since a significant portion of morbidity and mortality among Canadians are attributable to chronic disease (Patra, Popova, Rehm, Bondy, Flint & Giesbrecht, 2007). The four prevalent chronic diseases in McBride, Fraser Lake, Valemount, Queen Charlotte and Prince Rupert include hypertension; asthma, diabetes, and cardiovascular disease (see Table 5). As illustrated on Table 5, all communities have one or more health care facilities that provide primary care services to their residents. In the Northern Interior Health Service Delivery Area (HSDA), the number of primary health care physician per 100,000 population 41 is 104 in 2004/2005 fiscal year, while in the Northwest and Northeast Health Service Delivery Area the number primary health care physician per 100,000 population in 2004/2005 fiscal year was 116 and 79 respectively (Watson et al., 2009). The percentages of individuals age 12 and older that have a regular family physician in Northern Interior, and Northwest/Northeast HSDA are 90% and 88% respectively (Watson et al., 2009). Furthermore, 41% of individuals age 12 and older in both Northern Interior, Northwest/Northeast HSDA have visited a family physician at least 3 times in the past year, in contrast to 10% and 13% respectively, who have consulted a nurse in the past year (Watson et al., 2009). 42 Table 5 Selected Characteristics of Study Population McBride Characteristics Alternative Payment Plan Fraser Lake Valemount Queen Charlotte (Haida Gwaii) Prince Rupert Fee-for-service Tumbler Ridge Smithers Number Number Number Number Number Number Male Female 325 575 520 490 245 6,345 1,300 330 540 500 455 Age Groups (Yrs)3a 250 6,470 1,155 2,530 2,690 0-19 180 320 250 255 120 3,690 595 1,580 20-39 40-64 175 265 410 125 39 240 385 145 42 220 405 80 41 125 205 60 3,015 550 1,040 1,335 65+ Median Age 225 80 37 Number Number 33 Gender Stewart Ethnicity Visible Minority Aboriginal Population Rest of the population Annual average birth rate Annual average death rate Average life expectancy 4,785 1,355 39 43 275 42 1,720 585 36 33 35 60 565 15 20 40 10 1,369 15 200 895 75 135 925 760 Health Status3b 55 430 4,475 6,911 220 2,215 260 765 4,120 15 15-20 8-10 48 175 15 12-15 12 30 116 79 77-78 79 - - 79 313 a Hypertension Estimated Prevalence (existing cases) of selected chronic conditions ' 176(11) 175(13) 712 (68) 2,765 (189) 111(8) 43 Asthma Diabetes Ischemic Heart Disease Congestive Heart Failure Cardiovascular Disease 61(4) Stroke Chronic Kidney Disease COPD Health care Facility Health Facility type 96(6) - 1,275 (72) - - 1,063 (79) 476 (23) 335 (41) - - 726 (47) 168(21) - - - - 45(3) 20(2) 12(2) 61(6) 28(2) 25(4) 70(5) 31(3) 19(3) 279 (27) 63(9) 92 (14) . - 29(3) 6(1) 52(5) 12(2) 45(5) 228 (22) - 10(1) 58(6) - 11(2) 15(3) 49 (10) 26(3) 17(3) 21(2) Community Health Centre Community Health Centre General hospital, Community health centre, medical clinic, city health centre 5,349 4,401 3,184 13(2) District Hospital Emergency room visit 83(6) 2,035 89 (10) 190(37) - 280 (36) - - Health centre Regional hospital, community health centre Community health centre, health unit District hospital, Community health centre 24,662 - 13,701 808 Note. Cells with hyphen indicate that data not available at the time of compilation a The numbers in parenthesis are the incident rates of the chronic condition per year. Also, the health status data used for Queen Charlotte covers all diagnosis for select chronic conditions in Queen Charlotte Local Health Area. 3a Statistics Canada, 2010 3b Northern Health, (n.d) 44 Estimation of Study population I conducted a retrospective population-base study to assess hospitalization rates for ACSC in five APP communities and three FFS communities. Based on Table 5, the total population of the FFS communities is approximately five times that of the APP communities. These significant variations in population size for APP and FFS make it improper to compare the number of hospitalizations for ACSC between both sets of communities. In order to suitably compare ACSC hospitalization in communities under the FFS remuneration versus the APP remuneration, community populations from census data within the study period were processed in order to obtain for each considered community a standard population and single calendar year from 1992 - 2008. Linear interpolation procedure was used to predict the population of calendar years 1992 - 2006. As shown in Table 6, the APP communities showed a positive growth in population between 1991 and 1996 census data; and a negative growth in population between 1996 and 2001, as well as 2001 and 2006 census data, i.e., 0.23%, 0.28% and 0.14% respectively. This implies 0.05%, 0.06% and 0.03% changes per year between 1991, 1996, 2001, and 2006 census year respectively. On the other hand, the FFS communities showed negative growth in population between 1991, 1996, 2001, and 2006 census year data, i.e., 0.01%, 0.17% and 0.09% respectively. This implies 0.00%, 0.03% and 0.02% changes per year between 1991, 1996, 2001, and 2006 census year respectively. I assumed there was no change in the population for calendar year 2007 and 2008 since the last census during the period of study was in 2006 (see Table 7). 45 Table 6 Population per Census Year in APP and FFS Communities Population Under 65yrs by census year APP FFS percentage change 1991-2006 APP FFS percentage change per year by census year APP FFS 1991 1996 2001 2006 4860 25830 6175 25710 4430 21385 3820 19495 0 (0%) 0 (0%) 0.23(23%) 0.01 (1%) 0.28 (28%) 0.14(14%) 0.17(17%) 0.09 (9%) 0(0%) 0(0%) 0.05(5%) 0.00(0%) 0.06(6%) 0.03(3%) 0.03(3%) 0.02(2%) Table 7 Estimation of Community Population 1991 1992 1993 1994 1995 1996 1997 1998 1999 APP 4860 5123 5386 5649 5912 6175 5826 5477 5128 FFS 25830 25806 25782 25758 25734 25710 24845 23980 23115 2000 2001 2002 2003 2004 2005 2006 2007 2008 APP 4779 4430 4308 4186 4064 3942 3820 3820 3820 FFS 22250 21385 21007 20629 20251 19873 19495 19495 19495 Note. Census year and data are in boldface. 46 Selection of ACSC hospitalizations. Ambulatory Care Sensitive Conditions include conditions that can be prevented via vaccination and/or PHC intervention (Ansari et al., 2006). Previous studies have identified hospitalization for ACSC, by focusing on principal diagnosis at hospital discharge abstract (Steiner, Braun, Melinkovich, Glazner, Chandramouli, LeBaron & Davidson, 2003; Falik, Needleman, Wells & Korb, 2001). Data from these abstracts are stored in the Hospital Separation Database (HSD). For this study I adapted the list of ACSC conditions developed by Lavoie et al. (2010). The definition of ACSC by Lavoie and colleagues includes three main categories: chronic conditions, vaccines preventable conditions, acute conditions and their corresponding ICD-9 and 10 codes (International Classification of Disease, 9th and 10th Revision) (see Table 8). This classification is consistent with the widely used definition of ACSC by Billings et al. (1993). Conditions classified as chronic conditions may require partial medical management and episodic office visits (Falik et al., 2001). Conditions classified as acute most likely require timely intervention and care to prevent hospitalization. Furthermore, acute conditions can develop into chronic conditions if preventive measures are not timely. Conditions classified as vaccine preventable conditions could be averted if timely and appropriate vaccination was administered. It is worth noting that the selected conditions were developed to monitor hospitalizations principally in populations under age 65, since some diseases are presented differently in the elderly (Blustein et al., 1998; Billings et al., 1993;Bindmanetal., 1995). The hospital separation abstract is based on the primary diagnosis such as asthma, COPD, congestive heart failure, diabetes mellitus, and hypertension. 47 Table 8 Definition of Ambulatory Care Sensitive Conditions List of ACSC adapted from Lavoie et al. (2010) Asthma Angina Chronic Conditions Vaccine Preventable Conditions Hypertension COPD Heart Failure and pulmonary edema Pneumonia Convulsion & Epilepsy Acute Bronchitis Diabetes with complications Iron deficiency anemia Diptheria Mumps Hemophilus Influenza type B Pertussis Hepatitis A Pneumococcal Hepatitis B Poliomyelitis Influenza Tuberculosis Measles Rubella Meningococcal disease (meningitis) Tetanus Acute Conditions Dental Conditions Gastroenteritis & Dehydration Cellulitis Severe ENT infections Pelvic Inflammatory Disease However, asthma and COPD are also classified as secondary diagnosis so long as the primary diagnosis is either pneumonia or acute bronchitis. Thus the selected conditions are believed to reflect adult chronic conditions that should have benefited from timely outpatient primary care. Consequently, for the purpose of this study, ICD-9 and 10 codes are used in identifying a potential ACSC hospitalization provided the codes were reported as the principal diagnosis for any hospitalization as shown in Appendix C. 48 Data sources The administrative health data used for this study is from the BC Ministry of Health and is held at Population Data BC. The Population Data BC maintains a comprehensive, longitudinal, population-based administrative database comprised of core data from health service utilization and physician billings files and hospitalization for residents of BC. The data obtained reflects population-based health service utilization because the health care delivery system in BC is universal. The hospital separation database for population data BC is comprehensive on health service utilization in BC, regardless of where the hospitalization took place. Hence, hospitalization data is an essential part of this study. The Population Data BC have the authority to hold individual-level personal information based on the information sharing agreements with provincial ministries and other public body data providers. They are permitted to disclose anonymized personal health information without consent for the purposes of evaluating and monitoring health system performance (Population Data BC, 2010). Population Data BC also accepts the responsibility of maintaining the confidentiality of the health information it receives. The protocol for this project was reviewed by the Population Data BC Privacy Officer to ensure that it met the criteria for privacy and confidentiality of data outlined in Population Data BC Privacy Policies and Procedures (Population Data BC, 2010). Overall, the use of administrative data for research brings strengths and limitations to the research project. These are more completely described in Chapter 5: Discussion. 49 Ethics Approval Ethics approval to collect the data related to this study was granted from the University of Northern British Columbia Research Ethics Committee. Data Analysis Hospitalization and ACSC hospitalization rates The community population was used as standard population and was estimated using figures from 1991, 1996, 2001 and 2006 censuses. Overall annual hospitalization rates were calculated as the number of hospitalizations per 1000 population in each fiscal year between April 1, 1992 and March 31, 2008 to examine trends over time. The overall hospitalization rates were first calculated to minimize the impact of rehospitalizations on the rates. In calculation of the rate, the numerator data consisted of the total number of hospitalization of ACSC for each calendar year of the principal and primary diagnoses. Denominator data was derived from estimated annual census data for each community as provided on Table 7. The annual census population estimates for each community were derived through linear interpolation. The incidence rates described above were also calculated for ACSC hospitalization specifically. Data analysis was performed using the Statistical Package for Social Sciences (SPSS) for Windows version 11.5. Descriptive statistics using nonparametric test were used to compare the difference in rate of hospitalization for ACSC in communities with FFS and APP physician remuneration scheme. For all of the analysis, alpha was set at .10, i.e., p <.10. A more liberal alpha (a) was used for this analysis, since it decreases likelihood of making a Type II Error (i.e., saying there is no difference in the population when there is) and the rigor 50 of the test. Moreover, the data for this study consist of yearly rates over 17 years, hence the number of data points is quite small, i.e., 17. This would suggest the probability of high Type II error if a = .05. However, the likelihood of making Type I error increases (i.e., saying there is a difference in the population that might not exist). Furthermore, oc-level of .10 increases power, thereby there is a greater chance of accepting the alternative if it is true (i.e., power) and, consequently the likelihood of rejecting the null hypothesis will be increased. The subsequent chapters present and discuss the results of this study. 51 Chapter Four: Results This chapter outlines the results from the data analyzed for this thesis. The chapter is arranged as follows. First, a descriptive analysis of both payment plans is presented using rates of ACSC hospitalization. Second, statistical difference between ACSC rates in APP and FFS Communities are described in some detail. Third, the lengths of stay in hospital for both plans are presented. This is followed by statistical testing for significance differences between plans. The population used throughout this analysis were taken from the described procedure as shown on Tables 6 and 7 in methodology chapter. Preliminary Data Analysis I decided not to adjust the rates of ACSC hospitalization by age and gender in both APP and FFS communities, since the gender ratio and age 95% CI split by gender indicates that there is no difference between the populations (APP and FFS). Further, the median and mean age split by gender in both communities also indicated that the populations were fairly homogenous (see Table 9 below). Thus, there was no concern to adjust rates of ACSC hospitalizations in these important characteristics that might influence reported proportions of health event rates or physician visits in the APP or FFS communities. 52 Table 9 Age and Gender Proportion ofACSC Hospitalization in APP and FFS Communities Gender Female Male n 505 446 M SD Mdn 34.81 18.99 37 33.46 20.55 31 Gender Female Male M SD Mdn n 2110 36.11 18.67 39 1877 33.03 20.03 30 APP 95% CI [33.15,36.47] [31.55,35.37] FFS 95% CI [35.31,36.91] [32.12,33.94] Gender Ratio 1.13 1 Gender Ratio 1.12 1 Hospitalization Rates for ACSC The hospitalization rates for ACSC discussed includes hospitalization rates for chronic, acute and vaccine preventable conditions. Between 1992- 2008 there were 2,887 ACSC hospitalizations in the APP communities and 12, 270 ACSC hospitalizations in FFS communities. The mean hospitalization rates for all ACSC per 1,000 population in APP communities was 36.94 per 1000 person, in comparison to FFS communities where the mean hospitalization rate was 32.03 per 1000 person (see Table 10). The hospitalization rates in the APP community were lower than the FFS until 1997/98 when they even out. In 2005/06 there was a significant spike in the rates of hospitalization for ACSC in both communities, although the most significant spikes occurred in the APP communities (see Figure 2). The rates of ACSC hospitalizations in the APP communities ranged from a low of 20.57 per 1,000 population in 1996/97 to a high of 68.06 per 1,000 population in 2007/08. The hospitalization rates for ACSC in the FFS communities range from a low of 25.03 per 1,000 population to a high of 44.93 per 1,000 population (see Figure 2). 53 Rates of ACSC Hospitalizations per 1000 persons 80.00 - _#__APP 70.00 - m y\ 60.00 - / 50.00 - j, \ ^__,-""y^'im FFS Linear (APP) ^ Linear (FFS) 4U.UU - - f l W - ! « - ^ 5 ? n » - M ~ " ^ ~ ~ " v B J : ^ S !=flf----Ar "^—Sin 30.00 - ~S1 B v = 2.1307x + 17.767 R2 = 0.663 10.00 - o V = 0.2048X + 30.186 R2 = 0.0333 o 2008/ o 2007/ o 2006/ 2004/ 2003/ 2002/ 2001/ 2000/ 1999/ 1998/ 1997/ 1996/ en en 1995/ c n c n c n c n c n c n o o o o o o 1994/ < * L T ) l D I ^ O O C n O T H t N r O ' * L / l en 1993/ CO ,ID „ i^' 'oo ' en ' 2005/ 0.00 - Figure 2. Rates of ACSC hospitalizations in APP and FFS communities. The second highest rate of ACSC hospitalization in the APP communities was 60.47 per 1,000 population in 2006/07, in comparison to 44.32 per 1,000 population in the FFS communities. ACSC hospitalization rates appear higher in FFS communities in comparison to APP communities. Additionally, the slopes of the APP and FFS communities appears significantly dissimilar as the hospitalization rate for ACSC in the APP communities grew at a rate of 2.1 cases per 1000 persons per year, whereas the FFS communities grew slightly at 0.2 cases per 1000 person per year (see Figure 2). The results are summarized on Table 10. 54 Table 10 Rates of ACSC Hospitalizations in APP andFFS Communities, 1992/93-2008/09 1992/93 1993/94 1994/95 1995/96 1996/97 1997/98 1998/99 1999/00 2000/01 2001/02 2002/03 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 Total ACSC Hospitalizations APP FFS Number of Rates per Number of hospitalizations 1,000 hospitalizations 26.94 920 138 25.81 923 139 132 23.37 823 756 137 23.17 20.57 767 127 30.21 757 176 624 29.03 159 43.88 703 225 204 42.69 666 140 31.60 539 590 173 40.16 144 34.40 676 651 144 35.43 45.92 647 181 60.47 876 231 864 68.06 260 46.34 488 177 Rates per 1,000 35.65 35.80 31.95 29.38 29.83 30.47 26.02 30.41 29.93 25.20 28.09 32.77 32.15 32.56 44.93 44.32 25.03 Rates of hospitalizations for chronic ACSC conditions Chronic ACSC evaluated in this study include hospitalizations for asthma, angina pectoris, heart failure, bronchitis, hypertension, convulsion and epilepsy, diabetes, COPD, pneumonia, and anemia. These chronic conditions were analyzed in groups of related conditions, similar data pattern and dissimilar data pattern. Hospitalization rates for chronic ACSC with similar patterns in the FFS and APP data. The ACSC chronic conditions classified as having similar data pattern include, asthma, bronchitis epilepsy, pneumonia, COPD, hypertension and diabetes. The trend lines of these chronic conditions illustrated similar directional data pattern, which is either increasing or decrease in both APP and FFS communities. The mean hospitalization rates per 1,000 population and the 95% confidence intervals for asthma, bronchitis epilepsy, pneumonia, COPD, hypertension and diabetes in the APP communities were 3.40 [3.22, 3.58], 0.82 [0.66, 0.98], 2.18 [2.03, 2.34], 2.94 [2.62, 3.27], 1.06 [0.78, 1.35], 4.23 [3.85, 4.61] and 3.60 [2.65, 4.54], respectively while the FFS communities had a mean hospitalization rates of 2.55 [2.64, 2.46], 0.79 [0.72, 0.87], 2.82 [2.77, 2.86], 1.65 [1.57, 1.74], 0.49 [0.42, 0.56], 4.49 [4.35, 4.62], and 1.64 [1.36, 1.91], respectively (see Table 11). From Figures 3, 4, and 5, the rates of hospitalization for asthma, bronchitis and epilepsy from 1992/93 - 2008/09 in the APP communities are similar to that of the FFS communities. Also, all three conditions appear to show a downward trend in their hospitalization rates (see Figures 3, 4, and 5). Further, the slopes of the APP and FFS 56 Table 11 Rates for Chronic ACSC Hospitalizations inAPP Communities, 95% Confidence Intervals, 1992/93-2008/09 Asthma Angina Pectoralis Convulsion & Epilepsy Hypertension Bronchitis Pneumonia Heart Failure and Pulmonary Edema Anemia Diabetes with complications COPD and Allied conditions Note. M= mean rate per 1,000 persons. n 282 181 182 313 70 219 33 66 239 74 M 3.40 2.34 2.18 4.23 0.82 2.94 0.42 0.84 3.60 1.06 APP SD 1.55 1.36 1.07 3.41 0.67 2.43 0.34 0.54 7.44 1.27 95% CI [3.22,3.58] [2.14,2.54] [2.03,2.34] [3.85,4.61] [0.66,0.98] [2.62,3.27] [0.30,0.54] [0.71,0.98] [2.65,4.54] [0.78, 1.35] n 1040 355 1106 1644 330 598 203 353 554 175 M 2.55 0.90 2.82 4.49 0.79 1.65 0.53 0.90 1.64 0.49 FFS SD 1.54 0.35 0.73 2.73 0.69 1.08 0.12 0.38 3.31 0.47 95% CI [2.64,2.46] [0.86,0.93] [2.77,2.86] [4.35,4.62] [0.72,0.87] [1.57,1.74] [0.51,0.54] [0.86,0.94] [1.36, 1.91] [0.42,0.56] 57 communities in all three conditions appear to have a similar pattern. The hospitalization rate for asthma in the APP communities decreased at a rate of 0.17 per 1000 persons per year, in comparison to 0.29 per 1000 persons per year in FFS communities (see Figure 3). Likewise the hospitalization rate for bronchitis in the APP communities decreased at a rate of 0.05 per 1000 persons per year, in comparison to 0.12 per 1000 persons per year in FFS communities (see Figure 4). The hospitalization rate for convulsion and epilepsy in the APP communities decreased at a rate of 0.03 per 1000 persons per year, in comparison to 0.11 per 1000 persons per year in FFS communities (see Figure 5). There were slight spikes in hospitalization rates in both types of communities for asthma, bronchitis and epilepsy, but it was very noticeable in the APP communities in comparison to the FFS communities (see Figures 3, 4 and 5). Rates of Asthma Per 1000 Persons 9.00 Linear (FFS) y = -0.1692x +4.9209 R2 = 0.3037 tf tf & $> tf tf $> tf £ £> <£> £ ^ ^ £> ^ ,$> y = -0.2883x +5.1457 R2 = 0.8942 L__ Figure 3. Rates of hospitalization for asthma, 1992/93 - 2008/09. 58 Rates of Bronchitis Per 1000 Persons 3.00 2.50 2.00 1.50 1.00 Linear (FFS) 0.50 0.0521X + 1.2872 R2 = 0.1525 0.00 0.1225X +1.8957 R2 = 0.8092 m •* LTI i£> r-^ oo o i o < H < N m " t f L n u 3 ^ o o c n o o o o o o o o o o 01 Gl fll Ol ffl Ol Ol < N r o « 3 - L / i i x > r ^ o o < n o < - i < - M m « 3 - u " > i o r ^ o o c n c n c n O T c n c n c r i c r i o o o o o o o o o c n o i c n a i o i o c n a i o o o o o o o o o < T - l i H t - l * - ( * - H T - l r - l r - l ( N r M r M C N < N r M ( N < N < N Figure 4. Rates of hospitalization for bronchitis, 1992/93 - 2008/09. Rates of Convulsion / Epilepsy Per 1000 Persons Linear (FFS) y = -0.0256x +2.4123: R2 = 0.0145 | x # \9>* 4> \& \$ # \ # xO° xO* \& \& vO* x # x # xtf \ v # & & $> & ^> & & >f $> $> $> j$> r$> £> ^ £> tf I y = -0.1145X + 3.8467 I R2 = 0.6338 i Figure 5. Rates of hospitalization for convulsion and epilepsy, 1992/93 - 2008/09. 59 Based on Figures 6, 7, and 8, the rates of hospitalization for pneumonia, COPD and hypertension from 1992/93 - 2008/09 in the APP communities are appeared similar to that of the FFS communities, since all three conditions appear to show an upward trend in their hospitalization rates. Further, the slopes of these conditions in the APP and FFS communities appear to have a similar pattern. The hospitalization rate for pneumonia in the APP communities increased at a rate of 0.32 per 1000 persons per year, in comparison to 0.18 per 1000 persons per year in FFS communities (see Figure 6). Likewise the hospitalization rate for COPD in the APP communities decreased at a rate of 0.21 per 1000 persons per year, in comparison to 0.07 per 1000 persons per year in FFS communities (see Figure 7). The hospitalization rate for hypertension in the APP communities decreased at a rate of 0.56 per 1000 persons per year, in comparison to 0.40 per 1000 persons per year in FFS communities (see Figure 5). There were significant spikes in hospitalization rates in both types of communities, but it was very noticeable in the APP communities in comparison to the FFS communities, particularly of pneumonia. Also, the hospitalization rates for hypertension and COPD in the APP communities had significant spikes in 2007/2008 for the (see Figures 6, 7 and 8). 60 Rates of Pneumonia Per 1000 Persons 8.00 Linear (APP) Linear (FFS) y = 0.3202x +0.3944 R2 = 0.4028 voj* v # Jp & K<$> v<#> .<$> ><^ & K<$> v < ^ & K& ^ «§> ,<§> y = 0.1764X + 0.206 R2 = 0.5889 Figure 6. Rates of hospitalization for pneumonia, 1992/93 - 2008/09. Rates on COPD Per 1000 Persons 4.50 •APP •FFS •Linear (APP) Linear (FFS) y = 0.2115x-0.839 R2 = 0.712 & & $> $> & & $> & & ^ & j§> & tf rf r$> $> y = 0.0664x-0.1049 R2 = 0.5145 Figure 7. Rates of hospitalization for COPD, 1992/93 - 2008/09. 61 Rates of Hypertension per 1000 Persons Linear (APP) Linear (FFS) y = 0.558x- 0.7912 R2 = 0.6838 ><£> .o,* & Jp $ .<#> & .<$> ,<£• ,<#. vc?> vO* \& \& \<£ \0% vO9* ^ ^ ^ tf $> $> & & £> ^ £> rf ,$> £> £> ,$> ,$> y = 0.3978x + 0.9068 R2 = 0.5415 Figure 8. Rates of hospitalization for hypertensions, 1992/93 - 2008/09. Interestingly, the hospitalization rates for diabetes in the APP and FFS communities were both flat and near zero until 2005/2006 - 2008/2009, when there was a sudden jump in hospitalization rates for diabetes. This sudden jump in hospitalization rate for diabetes may have being as a result of changes in reporting perhaps. Thus, the slope in both APP and FFS communities appears useless since, hospitalization data are inconsistent. However, in analyzing this rapid three year jump, both communities indicated similar pattern i.e., rising (2005/06 - 2007/08) and falling (2008/09). The APP indicated a higher rate in comparison to their FFS counterpart as shown in Figure 9. 62 Rates on Diabetes Per 1000 Persons 25.00 -i Figure 9. Rates of hospitalization for diabetes and allied conditions, 1992/93 - 2008/09. Hospitalization rates for chronic ACSC with dissimilar patterns in the FFS and APP data. The ACSC chronic conditions classified as having dissimilar data pattern include angina pectoris, heart failure and anemia. The trend lines of these chronic conditions illustrated dissimilar directional data pattern, which may indicated change pattern between both payment plans. The mean hospitalization rates per 1,000 population and the 95% confidence intervals for angina pectoris, heart failure and anemia in the APP communities were 2.34 [2.14, 2.54], 0.42 [0.30, 0.54] and 0.84 [0.30, 0.54] respectively whereas the FFS communities had a mean hospitalization rates of 0.90 [0.86, 0.93], 0.53 [0.51, 0.54], and 0.90 [0.86, 0.94] respectively (see Table 11). 63 From Figures 10, 11, and 12, the rates of hospitalization for angina pectoris, heart failure and anemia from 1992/93 - 2008/09 in the APP communities are dissimilar to that of the FFS communities, since all three conditions appear to show an upward trend in their hospitalization rates in the APP communities and a somewhat flat hospitalization rates in their FFS counterpart. The hospitalization rate for angina pectoris in the APP communities increased at a rate of 0.13 per 1000 persons per year, in comparison to a somewhat flat rate of 0.04 per 1000 persons per year in FFS communities (see Figure 10). Similarly, the hospitalization rate for heart failure in the APP communities indicated a slight upward trend of 0.02 per 1000 persons per year, in comparison to a somewhat fiat rate of O.OOlper 1000 persons per year in FFS communities (see Figure 11). The hospitalization rate for anemia indicated a similar pattern, in the APP communities was slightly up at a rate of 0.04 per 1000 persons per year, in comparison to a decline of 0.04 per 1000 persons per year in FFS communities (see Figure 12). There were significant spikes in hospitalization rates in both types of communities, but it was very noticeable in the APP communities in comparison to the FFS communities, particularly of anemia (see Figures 10, 11 and 12). 64 Rates of Angina Pectoris Per 1000 Persons Linear (FFS) y = 0.1257x+1.5284 R2 = 0.1822 & ^ V \& \<^ \<^ \ # \0° \QN \<^ \ \<^ \& \& \$ \0 % \ v , p p J , J ^ V^ V^ V^ V ^ S ?^1 > V ^& J? T >^j5rd 0 r ' T rd' VjP' V ' V y = -0.043x +1.1931 R2 = 0.3246 Figure 10. Rates of hospitalization for angina pectoris, 1992/93 - 2008/09. Rates on Heart Failure and Pulmonary Edema Per 1000 Persons Linear (FFS) 0.00 -t «3" en LT1 <£) r~- 00 en oi oo en cn cn ~ cn CT> Cn oi en m oi Cn CI Cn CTl CT1 Ol Cn Ol : 0.0169X + 0.2682 R2 = 0.0613 en o o o rM O ro O O in o to o r N r N < N r M < o N f M ( N r \ i 00 o o CM = -0.001x +0.5365 R2 = 0.0016 _J Figure 11. Rates of hospitalization for heart failure and pulmonary edema, 1992/93 2008/09. 65 Figure 12. Rates of hospitalization for anemia, 1992/93 - 2008/09. Rates of hospitalizations for acute ACSC conditions Acute ACSC evaluated in this study include hospitalizations for dental conditions cellulitis, pelvic inflammatory disease, gastroenteritis and dehydration and severe ear, nose and throat infections (ENT). The acute conditions were analyzed in groups of related conditions and similar pattern. Of these acute conditions, pelvic inflammatory disease, ENT and dehydration all indicated similar patterns in rates of hospitalizations, which are either increasing or decreasing rates in hospitalizations in both APP and FFS communities. On the other hand, hospitalization rates for dental conditions and cellulitis indicated change pattern between both payment plans. The mean rate of hospitalizations per 1,000 population for dental conditions, cellulitis, pelvic inflammatory disease, gastroenteritis and dehydration and ENT in the APP communities are 4.98 [4.83, 5.13], 1.55 [1.45, 1.65], 2.12 [1.94, 2.29], 2.70 [2.48, 2.92] and 66 2.61 [2.51, 2.70] respectively, while the FFS communities had mean hospitalizations rates of 4.68 [4.63, 4.73], 1.47 [1.43, 1.51], 1.79 [1.73, 1.85], 3.59 [3.48, 3.70] and 2.64 [2.55, 2.72] per 1000 population for dental conditions, cellulitis, pelvic inflammatory disease, gastroenteritis and dehydration and ENT respectively (see Table 12). From Figures 13 and 14, the rates of hospitalization for pelvic inflammatory disease and ENT from 1992/93 - 2008/09 in the APP communities are similar to that of the FFS communities, since both conditions appear to show a downward trend in their hospitalization rates. Further, the slopes of the APP and FFS communities in both conditions appear to be similar. The hospitalization rate for pelvic inflammatory disease in the APP communities decreased at a rate of 0.14 per 1000 persons per year, in comparison to 0.14 per 1000 persons per year in FFS communities (see Figure 13). Likewise the hospitalization rate for ENT in the APP communities decreased at a rate of 0.07 per 1000 persons per year, in comparison to 0.25 per 1000 persons per year in FFS communities (see Figure 14). Although the hospitalization rates for pelvic inflammatory disease are unidirectional, the decline in ENT appears steeper. There were slight spikes in hospitalization rates in both types of communities for pelvic inflammatory disease and ENT, but it was very noticeable in the APP communities in comparison to the FFS communities (see Figures 13 and 14). 67 Table 12 Rates for Acute ACSC Hospitalizations in FFS Communities, 95% Confidence Intervals, 1992/93-2008/09 Dental conditions Cellulitis Pelvic inflammatory disease Gastroenteritis & Dehydration Severe Ear, Nose and Throat (ENT) infection n 403 126 179 204 M 4.98 1.55 2.12 2.70 APP SD 1.51 0.60 1.19 1.61 95% CI [4.83,5.13] [1.45,1.65] [1.94,2.29] [2.48,2.92] n 1795 575 715 1313 M 4.68 1.47 1.79 3.59 FFS SD 1.09 0.48 0.83 2.00 95% CI [4.63,4.73] [1.43,1.51] [1.73, 1.85] [3.48,3.70] 216 2.61 0.71 [2.51,2.70] 1063 2.64 1.40 [2.55,2.72] Note. M= mean rate per 1,000 persons. Based on Figure 15, the rates of hospitalization for dehydration from 1992/93 2008/09 in the APP communities are appeared similar to that of the FFS communities, since both communities showed an upward trend in their hospitalization rates. Further, the slopes of both APP and FFS communities appear to have a similar directional pattern. The hospitalization rate for dehydration in the APP communities increased at a rate of 0.28 per 1000 persons per year, in comparison to 0.31 per 1000 persons per year in FFS communities (see Figure 15). Both the APP and FFS communities had several fluctuations in the rates of hospitalization of these conditions; however it was noticeable in the APP communities particular in 2006/07 calendar year (see Figure 15). Rates on Pelvic Inflammatory Disease Per 1000 Persons •APP •FFS • Linear (APP) Linear (FFS) y = -0.1436x +3.4114 R2 = 0.37 en en i o i ^ o o c n o o o o o o o o o O r H f M P O I J - L D l O I ^ O O o o o o o o o o o o o o o o o o o o en r H ( N r M r \ i r N i r M r M ( N ( N i N y = -0.1352X + 3.0073 R2 = 0.6843 Figure 13. Rates of hospitalization for pelvic inflammatory disease, 1992/93 - 2008/09. 69 Rates on Severe Ear, Nose and Throat (ENT) Infections Per 1000 Persons Linear (APP) Linear (FFS) y = -0.068x +3.2181 R2 = 0.2345 . # >o^ , # Jp & ,<#> . v o° \ O N & \ \ « ^ \ v<$» \<^ v<3> v ^ ^ ^ ^ $> ^ ^ ^ ^ ^ $> ^ ^ ^> ^ y = -0.2533x + 4.9162 R2 = 0.8342 Figure 14. Rates of hospitalization for severe ENT infections, 1992/93 -2008/09. Rates on Gastroenteritis & Dehydration Per 1000 Persons •APP •FFS •Linear (APP) Linear (FFS) 0.00 + & & $> 4> $> & & & & ^ $> ^> $> ^ £> ^ ^ y = 0.2753x +0.2211 I R2 = 0.7482 j y = 0.3138x +0.7641 R2 = 0.6256 ! Figure 15. Rates of hospitalization for gastroenteritis and dehydration, 1992/93 - 2008/09. 70 From Figures 16 and 17, the rates of hospitalization for dental conditions and cellulitis from 1992/93 - 2008/09 in the APP communities are dissimilar to that of the FFS communities, since both conditions appear to show an upward trend in their hospitalization rates in the APP communities and a somewhat flat hospitalization rates in their FFS counterpart. The hospitalization rate for dental conditions in the APP communities increased at a rate of 0.10 per 1000 persons per year, in comparison to a somewhat flat rate of 0.001 per 1000 persons per year in FFS communities (see Figure 16). Similarly, the hospitalization rate for cellulitis in the APP communities indicated a slight upward trend of 0.003 per 1000 persons per year, in comparison to a slight downward rate of 0.05 per 1000 persons per year in FFS communities (see Figure 17). The hospitalization rate for dental conditions in the APP communities showed a significant spike in 2000/01 and 2001/02, as well as a sharp fall in both communities in 2007/08., In Figure 17, the rates in hospitalization for cellulitis in the APP communities was less in comparison to their FFS counterpart in 1992/93, afterwards the rates fluctuated in both communities until 2001/02 when the APP communities had a sharp spike and the FFS communities had a moderated fall in same year. Interestingly, in 2007/08 both APP and FFS communities had a sharp decline in hospitalization rates for cellulitis (see Figures 16 and 17). This decline may have been as a result of changes in practice or reporting. 71 Rates of Dental Conditions Per 1000 Persons 8.00 7.00 6.00 5.00 4.00 Linear (APP) 3 00 Linear (FFS) 2.00 1.00 y = 0.0977x + 4.0991 R2 = 0.1067 0.00 0"1 CTt CI CT) CT1 CT1 tN O O cncncncncnaicricn o o o o o o in o o o o o m io i ^ o o m is) o o oo en o o 00 o o o o r M ( N r M < N o j r \ i r M ( N r M y = -0.0011x +4.6891 R2 = 3E-05 Figure 16. Rates of hospitalization for dental conditions, 1992/93 - 2008/09. Rates of Cellulitis Per 1000 Persons 3.00 APP FFS Linear (APP) Linear (FFS) y = 0.0025X + 1.5274 R2 = 0.0005 y = -0.0453X + 1.8776 R2 = 0 2225 Figure 17. Rates of hospitalization for cellulitis, 1992/93 - 2008/09. 72 Rates of hospitalizations for vaccine preventable ACSC conditions The conditions shown in Figures 18-29 all have erratic patterns and sudden spikes in data that appear then disappear. Comparison of these conditions, slopes and any statistical inference would not be useful. Simple description of these conditions follows. The results for the vaccine preventable conditions include hospitalizations for diphtheria, hemophilus influenza type B, hepatitis A, hepatitis B, mumps, influenza, measles, meningococcal disease (meningitis), pertussis, pneumococcal, poliomyelitis, tuberculosis, rubella and tetanus. During the period of study, 1992/93 - 2008/09, there was no hospitalization for tetanus and poliomyelitis in either of the communities either. Further, there were no hospitalizations for hepatitis B and diphtheria in the APP communities as well. The mean rate of hospitalizations per 1,000 population for these conditions are summarized in Table 13 The hospitalization rates for vaccine preventable conditions vary throughout the study years for both APP and FFS communities. As illustrated in Figures 18 and 19, the rates of hospitalization for influenza and rubella from 1992/93 - 2008/09 in the FFS indicated erratic spikes in APP communities and a slight spike in their FFS counterpart. Also, their trend lines in both the APP and FFS communities indicate a downward movement and the slope of the trend lines is somewhat similar in both plans (see Figure 18 and 19). The hospitalization rate for pneumococcal from 1992/93 - 2008/09 in the APP communities had a sudden spike whereas their FFS counterpart was somewhat flat. Interestingly, there was a sudden spike in 2000/01 in the APP communities for influenza, rubella and pneumococcal. This sudden spike in hospitalization rates may be as a result of a reporting issue or a systemic glitch, as well as an epidemic outbreak. Their trend lines appear to be declining as well (see Figures 18, 19 and 20 respectively). 73 Table 13 Rates for Vaccine Preventable Conditions ACSC Hospitalizations in APP Communities, 95% Confidence Intervals, 1992/93-2008/09 Influenza Hemophilus Influenza Type B Mumps Rubella Pneumococcal Pertussis Measles Pulmonary / other Tuberculosis Hepatitis A Meningococcal Disease (Meningitis) Hepatitis B Diphtheria Note. M= mean rate per 1,000 persons. n M 27 1 2 26 16 2 22 2 1 1 0 0.32 0.01 0.02 0.29 0.19 0.02 0.26 0.03 0.01 0.01 0 APP SD 95% CI n 0.27 0.05 0.07 0.50 0.19 0.02 0.26 0.03 0.01 0.01 [0.22,0.42] [-0.08,0.10] [-0.07,0.12] [0.09,0.48] [-0.06,0.44] [-0.10,0.14] [-0.05,0.57] [-0.08,0.13] [-0.08,0.10] [-0.08,0.10] 93 4 8 72 105 12 87 11 13 18 27 1 M FFS SD 95% CI 0.23 0.01 0.02 0.17 0.25 0.03 0.23 0.03 0.03 0.04 0.07 0.00 0.18 0.02 0.03 0.20 0.27 0.05 0.63 0.06 0.04 0.06 0.08 0.01 [0.19,0.26] [-0.01,0.03] [0.00,0.04] [0.12,0.22] [0.20,0.31] [0.00,0.06] [0.09,0.36] [0.00,0.07] [0.01,0.05] [0.02,0.07] [0.04,0.10] [-0.02,0.02] 74 The hospitalization rates for pertussis, hemophilus influenza type B and hepatitis A in the APP communities had significant spikes 1998/99, 1993/92 and 1999/00 respectively, whereas in 1995/96 and 1997/98 there was a spike in rates of hospitalization for hepatitis B and diphtheria respectively in the FFS communities (see Figure 21, 22 and 23). This spike in hospitalization rates in APP communities in same study period may have been as a result changes in reporting or an outbreak, particular in remote and rural communities where few cases double the incidence of the disease. The hospitalization rates (per 1,000 population) of mumps, measles, meningitis and tuberculosis are shown on figures 26, 27, 28 and 29 below. Rates of Influenza Per 1000 Persons 0.90 0.80 - Linear (APP) Linear (FFS) y = -0.0251X + 0.5423 R2 = 0.2283 y = -0.0316x +0.5099 R2 = 0.7926 r v i m t L / i i o i ^ o o c n O i - i t N r Q ^ l - L n t o r ^ o o CTicicncnaicncnCTiooooooooo c n a i c n c n a i c n c r i C T i o o o o o o o o o r - H « - l r - ( < - l ! - l < - f < - l * - I C N C N ! r M r \ l r M ( N l r M ( - M < N Figure 18. Rates of hospitalization for influenza, 1992/93 - 2008/09. 75 Rates on Rubella Per 1000 Persons Figure 19. Rates of hospitalization for rubella, 1992/93 - 2008/09. Rates on Pneumococcal Per 1000 Persons Figure 20. Rates of hospitalization for pneumococcal, 1992/93 - 2008/09. 76 Rates on Pertussis Per 1000 Persons Linear (FFS) y = -0.0018X + 0.0376 R2 = 0.0104 y = -0.0027X + 0.0535 R2 = 0.0663 Figure 21. Rates of hospitalization for pertussis, 1992/93 - 2008/09. Figure 22. Rates of hospitalization for hemophilus influenza type B, 1992/93 - 2008/09. 77 0.25 Rates on Hepatitis A Per 1000 Persons 0.20 0.15 Linear (APP) Linear (FFS) 0 10 y = -0.0005X + 0.0158 R2 = 0.0026 0.05 0.00 » i Mi » i » i • i » i MT< + 0 0518 i • i m~i » i M i » i » i • i • H i - y = -0 0021x 2 R = 0.0873 & & & & & & & & & & £ & $> ,$> ,$> £> $> Figure 23. Rates of hospitalization for hepatitis A, 1992/93 - 2008/09. Rates on Hepatitis B Per 1000 Persons 0.35 Linear (APP) Linear (FFS) y = -0 0078x +0.1281 R2 = 0.2394 - y=0 R2 = #N/A <&>•'J> " o K o? db'' c V d?>'' o?'' c?'* cs*°' cO'"' c?>'' c K cP' cfc"'" c^'°^c?>*° ^d>'"'Nc? ^ <&•'' N Nd? Nc? # £> £> ^> £> £> £> £> £> Figure 24. Rates of hospitalization for hepatitis B, 1992/93 - 2008/09. 78 0.05 Rates on Diptheria Per 1000 Persons Linear (APP) Linear (FFS) y=0 R2 = #N/A y = -0.0003X + 0.005 R2 = 0.0234 •9 & & & & & $> & £> £> tf £> £> £> £> ^ rf Figure 25. Rates of hospitalization for diphtheria, 1992/93 - 2008/09. Rates on Mumps Per 1000 Persons Linear (APP) Linear (FFS) y = -0.0021x +0.0421 R2 = 0.0236 y = -0.0018x + 0.0361 N & v * & \<*\\<>\x# & \ # \O ^ \ # \<$* \ * A * A ^ A \ * \ * N cs*N <£>N c£N c^N c$N $> $> ^> # & # ^ & $> ^ $> $> £> $> £> £> £> Figure 26. Rates of hospitalization for mumps, 1992/93 - 2008/09. R2 = 0-0876 Rates on Measles Per 1000 Persons Figure 27. Rates of hospitalization for measles, 1992/93 - 2008/09. Rates on Meningococcal Diease (Meningitis) Per 1000 Persons Figure 28. Rates of hospitalization for meningitis, 1992/93 - 2008/09. 80 Rates on Pulmonary / other Tuberculosis Per 1000 Persons 0.30 T Figure 29. Rates of hospitalization for pulmonary/other tuberculosis, 1992/93 - 2008/09. Statistical Difference between APP and FFS Communities Table 14 indicates that the two remunerations plans for GPs (APP and FFS) are different with regards to mean hospitalization rates for ACSC per 1,000 population. The mean hospitalizations rates per 1,000 population in the APP communities was 36.94 (13.21) whereas the FFS communities had a mean hospitalizations rates of 32.02 (5.67) per 1,000 population for all ACSC. Further, there was a statistical difference in hospitalization rates for ACSC between plans, with the APP showing higher rates in hospitalization for ACSC (/(16) = 1.83, p = .08, d= 0.48). Note however, that the APP rates appear to be trending upwards as shown in Figure 2. This finding demonstrates the importance of my chosen ec-level; since alevel of .05 would not have seen any difference in population even when the effect size (0.48) was small almost medium (see Table 14). 81 From Figure 2, the hospitalization rates for all conditions suggested to be ACSC showed a statistically difference in the means hospitalization rates of both APP and FFS population. Table 14 Overall Analysis ofACSC Hospitalizations Rates per 1000 Population in APP and FFS Communities M SD /(16) P Cohen's d APP 36.94 13.21 1.83 .08 0.48 FFS 32.03 5.67 Analysis of hospitalization rates for ACSC specific conditions Based on figures 22, 23, 24, 25, 26, 27, 28 and 29 a t-test analysis is improper in my opinion. In these cases trend lines are either having irregular ACSC hospitalizations pattern (see Figures 22, 23, 26, 27, 28 and 29) or having a condition show up in one community and not the other (see Figures 24 and 25). Further, the actual number of cases is so low as to make any further analysis meaningless. Chronic ACSC hospitalizations Table 15 clearly indicates that there were statistically significant differences found in hospitalization rates for chronic ACSC with asthma, pneumonia, COPD, diabetes, angina pectoris, convulsion and epilepsy showing a statistical difference in both payment plans. There is overwhelming evidence showing that the mean hospitalization rates for these conditions above are higher in the APP communities in comparison to their FFS counterpart. 82 It is also worth noting that the difference in the hospitalization rates for diabetes with a significant level ofp = (.07) would not have been detected if the alpha level was .05, particularly when the effect size was small (0.34). This reinforces the importance of an alpha level .10. The hospitalization rates for asthma showed a downward trend of 0.29 and 0.17 per year per 1000 for the APP and FFS plans respectively, while convulsion and epilepsy showed downward trends of 0.03 and 0.11 respectively (see Figure 3 and 10). Whereas the hospitalization rate for pneumonia and COPD showed an upward trend of 0.32 and 0.18 per year per 1000 population for the APP and FFS plans respectively, while COPD had an upward trend of 0.21 and 0.07 per year over 1000 population respectively (Figure 4 and 5). Interestingly, the hospitalization rate for angina shows an upward trend of 0.13 per year per 1000 population in the APP communities and a downward in the FFS communities, 0.04 per year per 1000 population (Figure 7). Other chronic conditions (not statistically significant) such as hypertension and diabetes showed upward trends; anemia and heart failure showed both showed an upward trend for APP and a downward trend for FFS ; bronchitis showed a downward trend for APP and an upward trend for FFS. The summary of the means and standard deviations can be found on Table 15. 83 Table 15 Contrast of APP Communities with FFS Communities in Hospitalization for Chronic ACSC i \PP FFS Cohen's ACSC conditions M SD M SD t(l6) P d Asthma 3.40 1.55 2.55 1.54 2.29 .03 0.55 Bronchitis 0.82 0.67 0.79 0.69 0.16 .88 0.04 Pneumonia 2.94 2.43 1.65 1.08 3.46 .00 0.69 COPD 1.06 1.27 0.49 0.47 2.53 .02 0.60 Hypertension 4.23 3.41 4.49 2.73 -0.66 .52 -0.08 Heart Failure 0.42 0.34 0.53 0.12 -1.37 .19 -0.43 Angina Pectoris 2.34 1.36 0.90 0.35 3.87 .00 1.45 Anemia 0.84 0.55 0.90 0.39 -0.32 .75 -0.13 Diabetes 3.60 7.44 1.64 3.31 1.92 .07 0.34 Convulsion/Epilepsy 2.18 1.07 2.82 0.73 -2.38 .03 -0.70 Acute A CSC hospitalization The mean hospitalization rates for gastroenteritis and dehydration were found to be statistically significant with FFS plan showing a higher rate in hospitalization in comparison to APP plan (t(16) = -4.34, p = .00, d = 0.49) (see Table 16). The other acute conditions did not show statistical significant difference in either remuneration plans. The summary of the means and standard deviations can be found on Table 16. The hospitalization rates for gastroenteritis and dehydration showed an upward trend of 0.28 and 0.31 per year per 1000 persons for the APP and FFS plans respectively, Other 84 acute conditions (not statistically significant) dental conditions, cellulitis showed upward trend; anemia and heart failure showed both showed upward trend for APP and a downward trend for FFS; bronchitis showed a downward trend for APP and an upward trend for FFS. Table 16 Contrast of APP Communities with FFS Communities in Hospitalization for Acute ACSC APP FFS Cohen's ACSC conditions M SD M SD >(16) P d Dental Condition 4.98 1.51 4.68 1.09 1.25 .23 0.23 Pelvic inflammatory disease 2.12 1.19 1.79 0.83 1.67 .11 0.32 Gastroenteritis & Dehydration 2.70 1.61 3.59 2.00 -4.34 .00 -0.49 Severe ENT infection 2.61 0.71 2.64 1.40 -0.11 .91 -0.03 Cellulitis 1.55 0.6 1.47 0.48 0.37 .71 0.15 Vaccine preventable ACSC hospitalization There was no statistical significant difference in the hospitalization rates for vaccine preventable conditions, as shown on Table 17. The summary of the means and standard deviations can be found on Table 17. All vaccine preventable conditions had a downward trend in hospitalization for ACSC, with the exception of tuberculosis. 85 Table 17 Contrast ofAPP Communities with FFS Communities in Hospitalization for Vaccine Preventable ACSC APP FFS Cohen's ACSC conditions M SD M SD t(\6) P D Influenza 032 027 023 018 L40 18 0.39 Pneumococcal 0.19 0.51 0.25 0.27 -0.63 .54 -0.15 Rubella 0.29 0.50 0.17 0.20 1.04 .31 0.32 Length of Hospital Stay in APP and FFS Communities The length of stay involves the total number of days a patient was hospitalized for a particular condition. The conditions not reported in this analysis are conditions that have irregular data patterns. These conditions include heart failure, diphtheria, hemophilus influenza Type B, hepatitis A, hepatitis B, measles, meningitis, mumps, pertussis, pneumococcal, poliomyelitis, tuberculosis, and tetanus. A difference in length of hospitalization may indicate systemic or administrative default as well as difficulty in discharge planning, coordination of primary care providers, comorbidites and late diagnosis. Length of hospital stay in APP and FFS communities for chronic ACSC Table 18 summarizes the mean length of hospitalizations for various chronic ACSC in 1992/93 - 2008/09. The mean length of hospitalization varied in each payment plans and conditions during the period of study. Of all chronic ACSC hospitalization, convulsion and epilepsy is the only condition with a statistical significant difference in the length of hospitalization (/(16) = -4.34, p = .00), with Cohen d = 0.49; mean of 1.77 (0.55) and 2.29 86 (1.01) for APP and FFS plan respectively. Thus, the length of hospitalization for convulsion and epilepsy is higher under the FFS plan in comparison to the APP plan. Table 18 Contrast of APP Communities with FFS Communities in Length of Hospital Stay for c^vv^.-.^ ACSC M SD 95% CI f(16) p Cohen's d APP 319 1.90 2.25 FFS 1360 Convulsion and Epilepsy APP 221 1.77 1417 2.29 FFS Hypertension APP 50 1.36 2.13 FFS 140 Bronchitis* 232 2.61 APP 2.31 FFS 701 Pneumonia 4.12 646 APP 1570 4.45 FFS COPD 2.77 APP 149 3.49 FFS 266 Diabetes* 3.14 APP 97 FFS 329 5.95 Angina Pectoris APP 245 2.06 322 2.27 FFS Anemia* APP 13 0.79 2.03 FFS 53 1.08 0.59 [1.78,2.01] [2.22, 2.28] -1.14 .27 -0.41 0.55 1.01 [1.69, 1.84] [2.23, 2.34] -2.17 .05 -0.64 2.37 1.42 [0.64, 1.92] [1.76,2.25] •1.11 .28 -0.39 1.95 1.18 [2.36, 2.86] [2.22, 2.40] 1.48 .16 0.18 2.99 1.38 [3.89, 4.35] [4.38, 4.52] -0.37 .71 -0.14 2.93 3.26 [1.98,2.91] [2.69, 3.47] -0.85 .40 -0.23 1.15 2.12 [2.91,3.37] [5.72,6.18] •1.10 .12 -1.64 1.28 0.72 [1.90,2.22] [2.19,2.35] -0.53 .60 -0.20 1.16 2.72 [0.16, 1.42] [1.29,2.76] -1.56 .15 -0.59 Asthma Note: The degree of freedom for bronchitis, diabetes & anemia are 15, 4 and 11 respectively. 87 Length of hospital stays in APP and FFS communities for acute ACSC Table 19 summarizes the mean length of hospitalizations for various acute ACSC in 1992/93 - 2008/09. The mean length of hospitalization varied in each payment plans and conditions during the period of study. Of all acute ACSC, dental conditions is the only condition with a statistically significant difference in the length of hospitalization (t (16) = 2.31, p = .03), with Cohen d = 0.64; mean of 0.31 (0.34) and 0.14 (0.16) for APP and FFS plan respectively. Thus, this evidence suggests that a patients length of hospitalization for a dental condition is higher under the APP plan in comparison to the FFS plan. This disparity in length of hospitalization between the APP and FFS communities may be as a result of the lack of dental care in remote and rural areas. Table 19 Contrast ofAPP Communities with FFS Communities in Length of Hospital Stay for Acute ACSC N M Dental conditions APP 105 0.31 FFS 200 0.14 Pelvic inflammatory disease APP 195 1.54 FFS 456 1.63 Dehydration APP 214 2.00 FFS 645 1.95 Severe ENT Infection APP 151 1.79 FFS 591 1.28 Cellulitis APP 287 3.67 FFS 1154 3.63 SD 95% CI t(l6) p Cohen's d 0.34 0.16 [0.24,0.37] [0.12,0.16] 2.31 .03 0.64 1.11 0.87 [1.39.1.70] [1.55,1.71] -0.24 .81 -0.08 1.61 0.94 [1.78,2.21] [1.87,2.02] 0.11 .92 0.04 1.75 0.44 [1.51,2.07] [1.25, 1.32] 1.15 .27 0.40 2.10 1.12 [3.43,3.92] [3.56,3.69] 0.07 .94 0.03 88 Length of hospital stays in APP and FFS communities for vaccine preventable ACSC Table 20 summarizes the mean length of hospitalizations for various vaccine preventable ACSC in 1992/93 - 2008/09. The mean length of hospitalization varied in each payment plans and ACSC conditions during the period of study. There were no statistical differences in the length of hospitalization for vaccine preventable conditions in APP and FFS plans with an exception of influenza and rubella as shown on Table 20 below. Table 20 Contrast ofAPP Communities with FFS Communities in Length of Hospital Stay for Vaccine ACSC Influenza APP FFS Rubella APP FFS M SD 95% CI t(\6) p Cohen's d 1.23 1.63 1.27 1.03 [0.81, 1.64] [1.47, 1.80] -1.43 .08 -0.35 1.60 3.68 1.64 1.52 [1.02, 1.83] [2.14, 1.32] -2.30 .04 -1.31 Summary of Finding. Overall, the APP communities showed higher rates of hospitalization for ACSC (t = 1.83, df= 16, p = .08), with Cohen's d = 0.48. Chronic conditions such as asthma, pneumonia, COPD, diabetes, and angina showed a higher rate hospitalization in APP communities, while epilepsy and convulsion, and dehydration showed a higher ration of hospitalization in the FFS communities in comparison to their counterparts. Some conditions such as diphtheria, hepatitis A, hepatitis B, and tuberculosis were unsuitable for statistical testing because of irregular data patterns and very low incidence. The hospitalization rates 89 for all vaccine preventable and acute conditions, with the exception of dehydration, were statistically non-significant in both APP and FFS communities. Furthermore, the length of hospitalization for most chronic, acute and vaccine preventable conditions in APP and FFS plans were not different. Notable exceptions included convulsion and epilepsy, dental conditions, influenza and rubella which indicated statistically significant differences between APP and FFS. The APP had a higher longer hospital stay for dental conditions in comparison to the FFS plan, whereas the FFS had a longer hospital stay for convulsion and epilepsy, influenza and rubella in comparison to the APP plan. Table 21 Summary of Finding Overall ACSC rate APP t FFS 1 T T t T T 4 4 I i i i T ACSC Specific Condition Chronic ACSC Asthma Pneumonia COPD Angina Pectoris Diabetes Convulsion & Epilepsy Acute ACSC Gastroenteritis & Dehydration Length of Hospitalization Chronic ACSC Convulsion & Epilepsy Acute ACSC Dental Conditions Vaccine Preventable ACSC Influenza Rubella i i T t I t t 4 90 Chapter Five: Discussion Key Findings and Contribution This study is the first to compare the rates in hospitalization of ambulatory care sensitive conditions for persons accessing the care of a general practitioner remunerated under the alternative payment plan and fee-for-service remuneration in Northern British Columbia, Canada. Improving access to primary care is one principal objective of healthcare policy makers to improve the health of Canadians, since access to primary care is widely considered to be a necessary building block of an effective health care delivery system. However the literature is inconsistent as to any one measure of access as the best possible indicator of system performance in the primary care settings (Ricketts et al., 2001). Over the past decade, one tool established for analyzing access to care, has been hospitalization rates for ACSC. The findings from ACSC hospitalization rates has being significant, as it provides a practical way of evaluating care delivered in the primary care settings, as well as identifying appropriate areas for improving access and quality of care. The decision to use alpha at .10 in this study, was to ensure no possible difference was missed. While this admittably increases the likelihood of more Type I errors (claims of difference that might not exist), I was more concerned about lessening the Type II errors (capturing all possible differences). Furthermore, having a small sample size (df= 16) poses problems with Type I and II errors. For this study, we included 17 years of data. Increasing the sample size to other communities was not practical. This is one limitation of using an administrative data since analysis is limited to what is provided. Hence, a particular strength 91 of this study is to use alpha-level of .10 for statistical testing, so as to capture all differences that may not have been identified with alpha-level of .05. The analysis applied an interpolation and extrapolation procedure to estimate population size in between census years. This allowed me to complete a population based analysis of ACSC, a widely used indicator for measuring of access and quality of primary care (Ansari et al. 2006; Caminal et al. 2004; Pappas et al., 1997). The definition of ACSC used for this study was adapted from Lavoie et al. (2010), using ten chronic conditions (asthma, angina pectoris, heart failure, convulsion and epilepsy, diabetes, hypertension, COPD, pneumonia, bronchitis and anemia); five acute conditions (dental condition, cellulitis, pelvic inflammatory disease, gastroenteritis and dehydration, severe ENT infections); and fourteen vaccine preventable conditions (diphtheria, hemophilus influenza type B, hepatitis A, hepatitis B, influenza, measles, meningitis, mumps, pertussis, pneumococcal, poliomyelitis, tuberculosis, rubella and tetanus). The major contribution of the study is to provide some insights into how different modes of GPs remuneration can translate into better outcomes for patients, and presumably improve provider satisfaction, as well as decrease costs. Hospitalization rates are often associated with several factors that include personal income and the relative wealth of a person's community, healthcare coverage, race, region, and gender, as well as the correlation among those factors and incidence of the underlying disease (Ricketts et al., 2001). Variations in hospitalization rates for ACSC conditions over time among the APP and FFS communities could prompt further studies as to why these discrepancies occurred. Variation may arise due to changes in reporting or method of delivery care, systemic problems and several confounding factors like physician supply, 92 'social admission', where patient travel longer distance for care and are often hospitalized to precipitate care, hospital bed supply, etc. The reason for the discrepancies as to why certain conditions will be reported in certain calendar year under a particular payment option and not in the following year, are unknown. Possibilities include, for example, an epidemic or mild flu season in one community versus the other. Variations for chronic conditions require further investigation. Other determinants of these variations could be improved vaccination coverage or better recruitment of health professional in one community in comparison to the other. The overarching importance of the ACSC is to showcase these conditions that are thought to be avoidable if patients have timely care. Factors associated with preventable hospitalization or ACSC rates have specifically been examined by a number of researchers (Billings et al., 1993; Pappas et al., 1997; Ricketts et al., 2001). This study is not intended to address the appropriateness of hospitalization or quality of care. This is because diagnoses are not certain until discharge from hospital and abstracts are completed. The assertion remains one of the primary limitations of using administrative hospitalization data to ascertain appropriateness of care. Rates of hospitalization and ACSC Overall there was a statistical significant difference between the two the payment plan (7(16) = 1.83, p = .08), with Cohen's d = 0.48, particularly in four chronic conditions (asthma, COPD, pneumonia and convulsion and epilepsy) and one acute condition (gastroenteritis and dehydration). This is an important addition to the literature, as no study has examined the effectiveness of the GPs payment plans using hospitalization for ACSC. 93 In Table 12, the mean and standard deviation of all hospitalization for ACSC in FFS and APP communities are shown. The figure indicates that the rates of hospitalization for ACSC were higher among the APP communities in comparison to their FFS counterpart, particularly among chronic conditions. Previously the prevalence of hospitalization for conditions thought to be avoidable was calculated and compared between the two groups and the findings recorded in Tables 10 - 15. For the chronic conditions asthma, pneumonia, and COPD, there were statistically significant differences found, with the APP showing a higher rate of hospitalization in comparison to the FFS plans. Also important was higher rates of hospitalization for convulsion and epilepsy, gastroenteritis and dehydration in the FFS community in comparison to the APP communities. For chronic conditions of hypertension, bronchitis, diabetes, heart failure, and anemia there was no statistically significant difference between the two payment plans. In the larger part, this speaks to management of these chronic conditions. In part, several environmental factors like tobacco smoke, allergens, occupational and indoor pollutants may have also contributed to these differences in hospitalization rates for asthma, pneumonia, COPD, angina, diabetes and convulsion in both payment plans. In addition, I could not control for prevalence of diseases in certain communities. For acute conditions of dental conditions, cellulitis, pelvic inflammatory disease, and severe ENT infections there were no statistically significant differences in the hospitalization rates between two payment plans. For vaccine preventable conditions there was no statistically significant difference between the two plan options. This is not surprising following the innovations and health promotion and education around vaccinations. 94 One possible explanation of the difference reported here is that only those diagnoses confirmed by GPs and do not include individual with certain symptoms still to be diagnosed. Thus, the rates of ACSC may have being underestimated. Although there is no significant difference in hospitalizations for several conditions thought to be avoidable between the two payment options, it is noteworthy that the prevalence of certain conditions is dependent on the demographic composition of the population. Thus a community with younger or older population may influence the prevalence of the certain conditions classified as ACSC. Statistical analysis Overall, the mean rates in hospitalization for conditions classified as ACSC were found to have statistically important differences between APP and FFS communities. The APP communities had an increasing rate of 2.13 per year per 1000 population while the FFS had a slight increase of 0.20 per year per 1000 population. These findings suggest that the rate of ACSC hospitalization in the APP communities is significantly higher in comparison to the FFS communities. Further, from Table 15, five chronic conditions showed significant differential trends in hospitalization for ACSC include asthma, convulsion, pneumonia, angina pectoris and COPD. Gastroenteritis and dehydration also showed differential statistical trend in rate of hospitalizations. The overarching objective of exploring rates of hospitalization for ACSC has been that increased rates of these conditions thought to be avoidable via timely access to care may indicate potential problems with the health delivery system. This study compares the rate of ACSC for communities under GPs remunerated with either APP or FFS payment schemes. Specifically, I compared GP remuneration plans using hospitalization for ACSC. The 95 findings from this study showed statistical differences in hospitalization rate for ACSC between both remuneration plans with the higher rate leaning toward the APP plan as compared to the FFS community. The statistical analysis focuses on conditions that had the trend lines running in both the same direction and opposite direction as shown on Figures 2 21. Conditions that had trend lines for only one conditions or irregular pattern were excluded from statistical analysis as shown on Tables 15-17. Length of hospital stay There was no significant difference in length of stay for conditions classified as ACSC in this study. However, there were statistical differences in length of hospitalization for convulsion and epilepsy with the FFS plan showing a longer stay in comparison to the APP plan (see Table 16); and dental conditions where the length of hospitalization was longer under the APP plan as compared to the FFS plan (see Table 17). The literature suggests that several factors have been responsible for prolonged length of stay for ACSC. One such contributor includes re-hospitalization as related to access to care barriers and post discharge follow-up (Porter, Herring, Lacroix, & Levinton, 2007). While not all re-hospitalizations are avoidable, certain factors contribute to repeated admissions among patients hospitalized for ACSC. These factors include discharge planning, non-compliance with treatment, family history (nature causes), coordination of primary care professionals (Porter et al., 2007). 96 Chapter Six: Conclusion Hospitalization rates for ambulatory care sensitive conditions (ACSC) are widely used as an indicator of access and the quality of primary care delivered. This study examines the effectiveness of primary care interventions provided by general practitioners (GP) remunerated under the fee-for-service (FFS) or alternative payment plan (APP), using health service utilization data for ACSC. The main goal of this study was to examine how GP remuneration and incentive contribute to the core objective of a public funded health system like Canada's; i.e., reduce cost of care, improve patient outcome and providers' satisfaction (Berwick et al., 2008; Beasley, 2009). The hospital separation data used for this study was provided by BC Ministry of Health, held at Population Data BC. The Population Data BC maintains comprehensive, longitudinal, population-based administrative database containing all physician billings files and hospitalization also required in this study. The result of this study illustrates the importance of physician remuneration, particularly with regard to hospitalization for ACSC. Increase rates in hospitalization for ACSCs are correlated with inadequate access and delivery of primary care, which leads to deterioration of health conditions and to over utilization of hospitals (Delvin & Sarma, 2008), since proactive utilization health care services is thought to be better use of health care. This study is timely particularly for development of initiatives that will improve access, reduce cost, and improve patients' outcome and providers' satisfaction. 97 Returning to the Conceptual Model In the introduction, a conceptual model was proposed regarding the difference in rates of hospitalizations for ACSC in select communities where general practitioners are remunerated by FFS or APP. This model appeared as follows: Payment Plan Characteristics Fee-For-Service - Increases physician autonomy - High service volume -Limited access for sicker less able patients -Encourage quick, frequent service - Over service Innovation: Measure of Performance Lesson from Literature t Quantity of service Avoidable hospitalization for ACSC TCost | Quality of service Is there a difference? Alternative Payment Plans - Increase physician patient relationship - Better cost control - Eliminate over service - Under servicing - Loss physician autonomy t Quality of service t Saving Avoidable hospitalization for ACSC J. Quantity of service Figure 30. Conceptual model for comparison of general practitioner remunerations. 98 In this thesis, administrative data were analysed to examine the difference in health service utilization for ACSC in select Northern BC communities served by GP under the FFS and APP remuneration. In doing so, this thesis has informed the conceptual model and has provided insights into the difference in hospitalization rates for ACSC in both APP and FFS communities. At the conclusion of this thesis the below were the hypothesis results. Hypothesis results. The hypothesis HI a, that there no difference in the rates of avoidable hospitalization forACSC between communities with FFS payment plan and APP for the general practitioner is not supported as there are differences in rate of hospitalization for ACSC in APP and FFS communities. Likewise, the hypothesis Hlb, that there is no difference in rates of hospitalization for diagnosis classified as ACSC in APP communities and FFS communities is not supported for the chronic conditions of asthma, pneumonia, convulsion and epilepsy, angina pectoris, and chronic obstructive pulmonary disease (COPD), and acute condition gastroenteritis and dehydration. Based on the findings in this study, there are significant differences in hospitalization rates for the above mentioned chronic conditions in the APP and FFS communities. The hypothesis H2a, that there is no difference in trends in rates of hospitalization for ACSC between communities with FFS payment plan and APP for the general practitioner. Based on data erratic patterns rate of change analysis is not useful. The hypothesis H3, that there is no difference in length of hospitalizations of diagnoses classified as ACSC between communities with FFS payment plan and APP plans for the general practitioner is not supported as there are statistical differences in length of 99 hospitalization rate for chronic and acute conditions of convulsion and epilepsy and dental conditions respectively. In sum, the results from this study include the following; first, overall hospitalization rates for ACSC were significantly different between remuneration plans, with the APP plan showing a higher rate of hospitalization for ACSC in comparison to the FFS plan. Furthermore, rates in hospitalization for most chronic conditions (asthma, convulsion and epilepsy, angina pectoris, pneumonia, COPD) and acute conditions (gastroenteritis and dehydration) were found to be different in the two payment plans with the asthma, angina pectoris, pneumonia and COPD showing higher rates of hospitalization in the APP communities compared to FFS communities, while (convulsion and epilepsy) and (gastroenteritis and dehydration) showed higher rates of hospitalization in the FFS communities than APP communities. Second, overall trends in hospitalization rates for ACSC appear to show important differences for between remuneration plans, with the APP plan showing an upward trend in rate of hospitalization for ACSC in comparison to the FFS plan. Furthermore, rates of hospitalization for most chronic condition (asthma, convulsion and epilepsy, angina pectoris, pneumonia, COPD) and acute condition (gastroenteritis and dehydration) were found to be statistically different in both payment plans with the asthma, angina pectoris, pneumonia and COPD showing higher rates of hospitalization in the APP communities than FFS communities, while (convulsion and epilepsy) and (gastroenteritis and dehydration) showed higher rates in hospitalization in the FFS communities than APP communities. Third the length of hospitalization was different in one chronic (convulsion and epilepsy) and acute (dental conditions) conditions. The hospitalization for convulsion and epilepsy was found to be longer for the FFS communities in comparison to APP communities, while there was more lengthy stay for dental condition in the APP communities in comparison to FFS communities. Study limitations. First, this study only examined people aged 65 years and younger. It is possible to arrive at different conclusions when all age groups are examined. However, the under 65 population is an interesting one for the purposes of studying ACSC as the entire population is insured, which reduces insurance as a reason for problems with access to care. Second, this study used administrative health data mandated by the Government of British Columbia for monitoring and financial purposes. One potential limitation of using these data is that they are collected for non-research purposes, and thus may result in possible lack of modification of the variables, missing information and coding errors. However the importance of using administrative data is that they require fewer resources than primary data collection, as well as allow for longitudinal follow-up of individuals. Still, the benefits of using administrative data for specific project outweigh the limitations since using readily available data to measure ACSC is a pragmatic strategy for assessing the performance of the primary care system. Third, in assessing the validity and characteristic of the ACSC measure, this study was restricted by the content of the administrative data available. Using the hospital separation data, I have not control on physician practices and availability, local health practices, severity of illness, area of residence and other social and economic factors that 101 could be responsible for differential rates. Subsequent studies will be required to address these limitations. Fourth, this is an ecological study, in which the unit of analysis is population based rather than individual member of the population. One limitation of this study design is the potential for leakages, where patients from FFS communities receive services from APP GPs and vice versa. Moreover, registry records on patients' may not have been updated at the point of hospitalization However, I will assume the two groups are separate that there were no diffusions across communities, since six digits postal codes for both communities were used in tracking hospitalizations. Further, I reasonable assume that the leakage is on biased in one group than the other. Fifth, this study used the linear interpolation technique to estimate the study population of calendar years 1992 - 2006 and assumed that the community groups were equal for calendar years 2007-2008. Thus the hospitalization rates for ACSC and community population may have been underestimated or overestimated. In spite of this, the bias was not in one community than the other. Sixth, the APP was established in rural and remote communities as a recruitment and retention tool for GPs. However, obtaining data on when the APP was implemented in the APP communities was challenging, as it varied per community. Hence, the study assumed that all GPs in the APP communities were paid under the APP during the period. This may have resulted in a 'mix bag' where GPs may have being remunerated under the FFS plan during the period of study in the APP communities. While possible, this remains unlikely as GPs funded under the APP model were provided with this opportunity because recruitment 102 of GPs under FFS was challenging, leaving the same communities with no local access to GPs. Seventh, my analysis, I used aggregate measures, thereby introducing potential limitations in the analysis of long-term practical use of measures as well as contributing to aggregation bias. However, comparison of rates also focused on individual ACSC conditions, which is very beneficial for targeted interventions and policy making. Finally, this study measured hospitalizations for a population with higher rates ACSC along with an equivalent risk of hospitalization per person; as such the rate of hospitalization will appear greater for those rural communities. Implication of this study Further research. This study is based on data from individual hospitalized for conditions that are thought to be sensitive to primary care to draw an inference about quality of preventive care, management of chronic conditions and access to care. However, further research in this area is required to further validate of the findings of this study by exploring the effect of all confounding factors that may have contributed to the differences in hospitalization rates for ACSC found in both payment plans. The most pressing need for future research in this area is to further validate the odds that a person be hospitalized for ACSC under the APP or FFS remuneration plans. 103 Policy and practice. Hospitalization rates can be used to examine health system performance, evaluate policy changes, as well as assessment of quality preventive care (Lavoie et al., 2010). This study is focused on flagging potential barriers to accessing quality preventive care in primary care settings using physician remuneration plan. This study is based on the assumption that physician remuneration plans and its embedded incentives have an influence on their output. Hence the results of this study are beneficial to stakeholder and policy makers as to the most effective way of remunerating and incentivizing general practitioners so the core goals the health system (reduce cost, improve patient and provider satisfaction) can be achieved. Further, this study explored the rates in hospitalization for individual ACSC hospitalizations, which is very beneficial for targeted interventions and policy making. 104 Reference Agency for Healthcare Research and Quality (2001). 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Charlottetown, PEL The Atlantic Canada Economics Association Meetings. 110 Appendix A: Conditions Suggesting Potentially Avoidable Hospitalizations, with Corresponding ICD-9 and ICD-10-CA Codes i Chronic Conditions ANEMIAS 280 IRON DEFICIENCY ANAEMIAS 280.0 SECONDARY TO BLOOD LOSS (CHRONIC) 280.1 SECONDARY TO INADEQUATE DIETARY IRON INTAKE 280.8 OTHER SPECIFIED IRON DEFICIENCY ANEMIAS 280.9 IRON DEFICIENCY ANEMIA, UNSPECIFIED 281 OTHER DEFICIENCY ANAEMIAS 281.0 PERNICIOUS ANAEMIA 281.1 OTHER VITAMIN-'B 12'DEFICIENCY ANAEMIA 281.2 FOLATE-DEFICIENCY ANAEMIA 281.3 OTHER SPECIFIED MEGALOBLASTIC ANAEMIAS, NOT ELSEWHERE CLASSIFIED 281.4 PROTEIN-DEFICIENCY ANAEMIA 281.8 ANAEMIA ASSOCIATED WITH OTHER SPECIFIED NUTRITIONAL DEFICIENCY 281.9 UNSPECIFIED D50 IRON DEFICIENCY ANAEMIA D50.0 IRON DEFICIENCY ANAEMIA SECONDARY TO BLOOD LOSS (CHRONIC) D50.1 SIDEROPENIC DYSPHAGIA D50.8 OTHER IRON DEFICIENCY ANAEMIAS D50.9 IRON DEFICIENCY ANAEMIA, UNSPECIFIED ANGINA PECTORIS 411.1 INTERMED CORONARY SYND 411.8 ACUTE COR OCCLSN W/OMI AC ISCHEMIC HRT DIS NEC 413 ANGINA DECUBITUS PRINZMETAL ANGINA ANGINA PECTORIS NEC/NOS 120 ANGINA PECTORIS 120.0 UNSTABLE ANGINA 120.1 ANGINA PECTORIS WITH DOCUMENTED SPASM 120.8 OTHER FORMS OF ANGINA PECTORIS 120.80 ATYPICAL ANGINA 120.88 OTHER FORMS OF ANGINA PECTORIS 120.9 ANGINA PECTORIS, UNSPECIFIED 123.82 POSTMYOCARDIAL INFARCTION ANGINA AS CURRENT COMPLICATION FOLLOWING ACUTE MYOCARDIAL INFARCTION 124.0 CORONARY THROMBOSIS NOT RESULTING IN MYOCARDIAL INFARCTION 124.8 OTHER FORMS OF ACUTE ISCHAEMIC HEART DISEASE 111 124.9 ACUTE ISCHAEMIC HEART DISEASE, UNSPECIFIED ASTHMA 493 ASTHMA 493.0 EXTRINSIC ASTHMA 493.1 INTRINSIC ASTHMA 493.9 ASTHMA, UNSPECIFIED J45 ASTHMA J45.0 PREDOMINANTLY ALLERGIC ASTHMA J45.00 PREDOMINANTLY ALLERGIC ASTHMA WITHOUT STATED STATUS ASTHMATICUS J45.01 PREDOMINANTLY ALLERGIC ASTHMA WITH STATED STATUS ASTHMATICUS J45.1 NONALLERGIC ASTHMA J45.10 NONALLERGIC ASTHMA WITHOUT STATED STATUS ASTHMATICUS J45.ll NONALLERGIC ASTHMA WITH STATED STATUS ASTHMATICUS J45.8 MIXED ASTHMA J45.80 MIXED ASTHMA WITHOUT STATED STATUS ASTHMATICUS J45.81 MIXED ASTHMA WITH STATED STATUS ASTHMATICUS J45.9 ASTHMA, UNSPECIFIED J45.90 ASTHMA, UNSPECIFIED, WITHOUT STATED STATUS ASTHMATICUS J45.91 ASTHMA, UNSPECIFIED, WITH STATED STATUS ASTHMATICUS BRONCHITIS 466 ACUTE BRONCHITIS AND BRONCHIOLITIS 466.0 ACUTE BRONCHITIS 466.1 ACUTE BRONCHIOLITIS J20 ACUTE BRONCHITIS J20.0 ACUTE BRONCHITIS DUE TO MYCOPLASMA PNEUMONIAE J20.1 ACUTE BRONCHITIS DUE TO HAEMOPHILUS INFLUENZAE J20.2 ACUTE BRONCHITIS DUE TO STREPTOCOCCUS J20.3 ACUTE BRONCHITIS DUE TO COXSACKIEVIRUS J20.4 ACUTE BRONCHITIS DUE TO PARAINFLUENZA VIRUS J20.5 ACUTE BRONCHITIS DUE TO RESPIRATORY SYNCYTIAL VIRUS J20.6 ACUTE BRONCHITIS DUE TO RHINOVIRUS J20.7 ACUTE BRONCHITIS DUE TO ECHOVIRUS J20.8 ACUTE BRONCHITIS DUE TO OTHER SPECIFIED ORGANISMS J20.80 ACUTE BRONCHITIS DUE TO HUMAN METAPNEUMOVIRUS J20.88 ACUTE BRONCHITIS DUE TO OTHER SPECIFIED ORGANISMS J20.9 ACUTE BRONCHITIS, 112 UNSPECIFIED CONVULSION & EPILEPSY 345 EPILEPSY 345.0 GENERALIZED NONCONVULSIVE EPILEPSY 345.1 GENERALIZED CONVULSIVE EPILEPSY 345.2 PETIT MAL STATUS 345.3 GRAND MAL STATUS 345.4 PARTIAL EPILEPSY, WITH IMPAIRMENT OF CONSCIOUSNESS 345.5 PARTIAL EPILEPSY, WITHOUT MENTION OF IMPAIRMENT OF CONSCIOUSNESS 345.6 INFANTILE SPASMS 345.7 EPILEPSIA PARTIALIS CONTINUA 345.8 OTHER 345.9 UNSPECIFIED 780.3 CONVULSIONS 642.6 ECLAMPSIA G40 EPILEPSY G40.0 LOCALIZATION-RELATED (FOCAL)(PARTIAL) IDIOPATHIC EPILEPSY AND EPILEPTIC SYNDROMES WITH SEIZURES OF LOCALIZED ONSET G40.00 LOCALIZATION-RELATED (FOCAL) (PARTIAL) IDIOPATHIC EPILEPSY AND EPILEPTIC SYNDROMES WITH SEIZURES OF LOCALIZED ONSET, NOT STATED AS INTRACTABLE G40.01 LOCALIZATION-RELATED (FOCAL) (PARTIAL) IDIOPATHIC EPILEPSY AND EPILEPTIC SYNDROMES WITH SEIZURES OF LOCALIZED ONSET, INTRACTABLE G40.1 LOCALIZATION-RELATED (FOCAL)(PARTIAL) SYMPTOMATIC EPILEPSY AND EPILEPTIC SYNDROMES WITH SIMPLE PARTIAL SEIZURES G40.10 LOCALIZATION-RELATED (FOCAL) (PARTIAL) SYMPTOMATIC EPILEPSY AND EPILEPTIC SYNDROMES WITH SIMPLE PARTIAL SEIZURES, NOT STATED AS INTRACTABLE G40.ll LOCALIZATION-RELATED (FOCAL) (PARTIAL) SYMPTOMATIC EPILEPSY AND EPILEPTIC SYNDROMES WITH SIMPLE PARTIAL SEIZURES, INTRACTABLE G40.2 LOCALIZATION-RELATED (FOCAL)(PARTIAL) SYMPTOMATIC EPILEPSY AND EPILEPTIC SYNDROMES WITH COMPLEX PARTIAL SEIZURES G40.20 LOCALIZATION-RELATED (FOCAL) (PARTIAL) SYMPTOMATIC EPILEPSY AND EPILEPTIC SYNDROMES WITH COMPLEX PARTIAL SEIZURES, NOT STATED AS INTRACTABLE G40.21 LOCALIZATION-RELATED (FOCAL) (PARTIAL) SYMPTOMATIC EPILEPSY AND EPILEPTIC SYNDROMES WITH COMPLEX PARTIAL SEIZURES, INTRACTABLE G40.3 GENERALIZED IDIOPATHIC 113 EPILEPSY AND EPILEPTIC SYNDROMESG40.30O G40.30 GENERALIZED IDIOPATHIC EPILEPSY AND EPILEPTIC SYNDROMES, NOT STATED AS INTRACTABLE G40.31 GENERALIZED IDIOPATHIC EPILEPSY AND EPILEPTIC SYNDROMES, INTRACTABLE G40.4 OTHER GENERALIZED EPILEPSY AND EPILEPTIC SYNDROMES G40.40 OTHER GENERALIZED IDIOPATHIC EPILEPSY AND EPILEPTIC SYNDROMES, NOT STATED AS INTRACTABLE G40.41 OTHER GENERALIZED IDIOPATHIC EPILEPSY AND EPILEPTIC SYNDROMES, INTRACTABLE G40.5 SPECIAL EPILEPTIC SYNDROMES G40.50 SPECIAL EPILEPTIC SYNDROMES, NOT STATED AS INTRACTABLE G40.51 SPECIAL EPILEPTIC SYNDROMES, INTRACTABLE G40.6 GRAND MAL SEIZURES, UNSPECIFIED (WITH OR WITHOUT PETIT MAL) G40.60 GRAND MAL SEIZURES, UNSPECIFIED (WITH OR WITHOUT PETIT MAL), NOT STATED AS INTRACTABLE G40.61 GRAND MAL SEIZURES, UNSPECIFIED (WITH OR WITHOUT PETIT MAL), INTRACTABLE G40.7 PETIT MAL, UNSPECIFIED, WITHOUT GRAND MAL SEIZURES G40.70 PETIT MAL, UNSPECIFIED, WITHOUT GRAND MAL SEIZURES, NOT STATED AS INTRACTABLE G40.71 PETIT MAL, UNSPECIFIED, WITHOUT GRAND MAL SEIZURES, INTRACTABLE G40.8 OTHER EPILEPSY G40.80 OTHER EPILEPSY, NOT STATED AS INTRACTABLE G40.81 OTHER EPILEPSY, INTRACTABLE G40.9 EPILEPSY, UNSPECIFIED G40.90 EPILEPSY, UNSPECIFIED, NOT STATED AS INTRACTABLE G40.91 EPILEPSY, UNSPECIFIED, INTRACTABLE 114 G41 STATUS EPILEPTICUS G41.0 GRAND MAL STATUS EPILEPTICUS G41.1 PETIT MAL STATUS EPILEPTICUS G41.2 COMPLEX PARTIAL STATUS EPILEPTICUS G41.8 OTHER STATUS EPILEPTICUS G41.9 STATUS EPILEPTICUS, UNSPECIFIED R56 CONVULSIONS, NOT ELSEWHERE CLASSIFIED R56.0 FEBRILE CONVULSIONS R56.01 COMPLEX FEBRILE CONVULSIONS R56.09 FEBRILE CONVULSIONS, UNSPECIFIED R56.8 OTHER AND UNSPECIFIED CONVULSIONS R56.80 SEIZURE DISORDER, SO DESCRIBED R56.88 OTHER AND UNSPECIFIED CONVULSIONS 015 ECLAMPSIA O15.0 ECLAMPSIA IN PREGNANCY 015.1 ECLAMPSIA IN LABOUR 015.2 ECLAMPSIA IN THE PUERPERIUM 015.9 ECLAMPSIA, UNSPECIFIED AS TO TIME PERIOD CHRONIC OBSTRUCTIVE PULMONARY DISEASE (COPD) AND ALLIED CONDITIONS 490 BRONCHITIS, NOT SPECIFIED AS ACUTE OR CHRONIC 491 CHRONIC BRONCHITIS 491.0 SIMPLE CHRONIC BRONCHITIS 491.1 MUCOPURULENT CHRONIC BRONCHITIS 491.2 OBSTRUCTIVE CHRONIC BRONCHITIS 491.8 OTHER CHRONIC BRONCHITIS 491.9 UNSPECIFIED 492 EMPHYSEMA 494 BRONCHIECTASIS 496 CHRONIC AIRWAYS OBSTRUCTION, NOT ELSEWHERE CLASSIFIED J41 SIMPLE AND MUCOPURULENT CHRONIC BRONCHITIS J41.0 SIMPLE CHRONIC BRONCHITIS J41.1 MUCOPURULENT CHRONIC BRONCHITIS J41.8 MIXED SIMPLE AND MUCOPURULENT CHRONIC BRONCHITIS J42 UNSPECIFIED CHRONIC BRONCHITIS J43 EMPHYSEMA J43.0 MACLEOD'S SYNDROME J43.1 PANLOBULAR EMPHYSEMA J43.2 CENTRILOBULAR EMPHYSEMA J43.8 OTHER EMPHYSEMA J43.9 EMPHYSEMA, UNSPECIFIED J44 OTHER CHRONIC OBSTRUCTIVE PULMONARY DISEASE J44.0 CHRONIC OBSTRUCTIVE PULMONARY DISEASE WITH ACUTE LOWER RESPIRATORY INFECTION J44.1 CHRONIC OBSTRUCTIVE PULMONARY DISEASE WITH ACUTE 115 EXACERBATION, UNSPECIFIED J44.8 OTHER SPECIFIED CHRONIC OBSTRUCTIVE PULMONARY DISEASE J44.9 CHRONIC OBSTRUCTIVE PULMONARY DISEASE, UNSPECIFIED J47 BRONCHIECTASIS DIABETES WITH COMPLICATIONS 250 DIABETES MELLITUS 250.0 DIABETES MELLITUS WITHOUT MENTION OF COMPLICATION 250.1 DIABETES WITH KETOACIDOSIS 250.2 DIABETES WITH COMA 250.3 DIABETES WITH RENAL MANIFESTATIONS 250.4 DIABETES WITH OPHTHALMIC MANIFESTATIONS 250.5 DIABETES WITH NEUROLOGICAL MANIFESTATIONS 250.50 DIABETES WITH OCULAR INVOLVMENT, ADULT 250.51 DIABETES WITH OCULAR INVOLVMENT, JUVENILE 250.6 DIABETES WITH PERIPHERAL CIRCULATORY DISORDERS 250.7 DIABETES WITH OTHER SPECIFIED MANIFESTATIONS 250.8 DIABETES WITH OTHER SPECIFIED MANIFESTATIONS 250.9 DIABETES WITH UNSPECIFIED COMPLICATIONS E10 TYPE 1 DIABETES MELLITUS E10.1 TYPE 1 DIABETES MELLITUS WITH ACIDOSIS E10.10 TYPE 1 DIABETES MELLITUS WITH KETOACIDOSIS E10.ll TYPE 1 DIABETES MELLITUS WITH LACTIC ACIDOSIS E10.12 TYPE 1 DIABETES MELLITUS WITH KETOACIDOSIS WITH LACTIC ACIDOSIS E10.6 TYPE 1 DIABETES MELLITUS WITH OTHER SPECIFIED COMPLICATIONS El 0.60 TYPE 1 DIABETES MELLITUS WITH MUSCULOSKELETAL AND CONNECTIVE TISSUE COMPLICATION E10.61 TYPE 1 DIABETES MELLITUS WITH SKIN AND SUBCUTANEOUS TISSUE COMPLICATION E10.62 TYPE 1 DIABETES MELLITUS WITH PERIODONTAL COMPLICATION E10.63 TYPE 1 DIABETES MELLITUS WITH HYPOGLYCAEMIA E10.64 TYPE 1 DIABETES MELLITUS WITH POOR CONTROL, SO DESCRIBED E10.68 TYPE 1 DIABETES MELLITUS WITH OTHER SPECIFIED COMPLICATION, NOT ELSEWHERE CLASSIFIED E10.7 TYPE 1 DIABETES MELLITUS WITH MULTIPLE COMPLICATIONS E10.70 TYPE 1 DIABETES MELLITUS WITH FOOT ULCER (ANGIOPATHIC) (NEUROPATHIC) E10.71 TYPE 1 DIABETES MELLITUS WITH FOOT ULCER (ANGIOPATHIC) (NEUROPATHIC) WITH GANGRENE E10.78 TYPE 1 DIABETES MELLITUS WITH MULTIPLE OTHER COMPLICATIONS E10.9 TYPE 1 DIABETES MELLITUS WITHOUT (MENTION OF) COMPLICATION E l l TYPE 2 DIABETES MELLITUS E11.0 TYPE 2 DIABETES MELLITUS WITH COMA El 1.1 TYPE 2 DIABETES MELLITUS 116 WITH ACIDOSIS E11.10 TYPE 2 DIABETES MELLITUS WITH KETOACIDOSIS Ell.11 TYPE 2 DIABETES MELLITUS WITH LACTIC ACIDOSIS E11.12 TYPE 2 DIABETES MELLITUS WITH KETOACIDOSIS WITH LACTIC ACIDOSIS E11.6 TYPE 2 DIABETES MELLITUS WITH OTHER SPECIFIED COMPLICATIONS El 1.60 TYPE 2 DIABETES MELLITUS WITH MUSCULOSKELETAL AND CONNECTIVE TISSUE COMPLICATION E11.61 TYPE 2 DIABETES MELLITUS WITH SKIN AND SUBCUTANEOUS TISSUE COMPLICATIONE11.9 El 1.62 TYPE 2 DIABETES MELLITUS WITH PERIODONTAL COMPLICATION El 1.63 TYPE 2 DIABETES MELLITUS WITH HYPOGLYCAEMIA El 1.64 TYPE 2 DIABETES MELLITUS WITH POOR CONTROL, SO DESCRIBED E11.68 TYPE 2 DIABETES MELLITUS WITH OTHER SPECIFIED COMPLICATION, NOT ELSEWHERE CLASSIFIED E11.7 TYPE 2 DIABETES MELLITUS WITH MULTIPLE COMPLICATIONS E11.70 TYPE 2 DIABETES MELLITUS WITH FOOT ULCER (ANGIOPATHIC)(NEUROPATHIC) El 1.71 TYPE 2 DIABETES MELLITUS WITH FOOT ULCER (ANGIOPATHIC) (NEUROPATHIC) WITH GANGRENE E11.78 TYPE 2 DIABETES MELLITUS WITH MULTIPLE OTHER COMPLICATIONS E11.9 TYPE 2 DIABETES MELLITUS WITHOUT (MENTION OF) COMPLICATIONS E13 OTHER SPECIFIED DIABETES MELLITUS E13.0 OTHER SPECIFIED DIABETES MELLITUS WITH COMA E13.1 OTHER SPECIFIED DIABETES MELLITUS WITH ACIDOSIS E13.10 OTHER SPECIFIED DIABETES MELLITUS WITH KETOACIDOSIS E13.ll OTHER SPECIFIED DIABETES MELLITUS WITH LACTIC ACIDOSIS E13.12 OTHER SPECIFIED DIABETES MELLITUS WITH KETOACIDOSIS WITH 117 LACTIC ACIDOSISE13.7 E13.6 OTHER SPECIFIED DIABETES MELLITUS WITH OTHER SPECIFIED COMPLICATIONS E13.60 OTHER SPECIFIED DIABETES MELLITUS WITH MUSCULOSKELETAL AND CONNECTIVE TISSUE COMPLICATION E13.61 OTHER SPECIFIED DIABETES MELLITUS WITH SKIN AND SUBCUTANEOUS TISSUE COMPLICATION E13.62 OTHER SPECIFIED DIABETES MELLITUS WITH PERIODONTAL COMPLICATION E13.63 OTHER SPECIFIED DIABETES MELLITUS WITH HYPOGLYCAEMIA E13.64 OTHER SPECIFIED DIABETES MELLITUS WITH POOR CONTROL, SO DESCRIBED E13.68 OTHER SPECIFIED DIABETES MELLITUS WITH OTHER SPECIFIED COMPLICATION, NOT ELSEWHERE CLASSIFIED E13.7 OTHER SPECIFIED DIABETES MELLITUS WITH MULTIPLE COMPLICATIONS E13.70 OTHER SPECIFIED DIABETES MELLITUS WITH FOOT ULCER (ANGIOPATHIC) (NEUROPATHIC) E13.71 OTHER SPECIFIED DIABETES MELLITUS WITH FOOT ULCER (ANGIOPATHIC) (NEUROPATHIC) WITH GANGRENE E13.78 OTHER SPECIFIED DIABETES MELLITUS WITH MULTIPLE OTHER COMPLICATIONS E13.9 OTHER SPECIFIED DIABETES MELLITUS WITHOUT (MENTION OF) COMPLICATION E14 UNSPECIFIED DIABETES MELLITUS E14.0 UNSPECIFIED DIABETES MELLITUS WITH COMA E14.1 UNSPECIFIED DIABETES MELLITUS WITH ACIDOSIS E14.10 UNSPECIFIED DIABETES MELLITUS WITH KETOACIDOSIS E14.ll UNSPECIFIED DIABETES MELLITUS WITH LACTIC ACIDOSIS E14.12 UNSPECIFIED DIABETES MELLITUS WITH KETOACIDOSIS WITH LACTIC ACIDOSIS 118 E14.6 UNSPECIFIED DIABETES MELLITUS WITH OTHER SPECIFIED COMPLICATIONS E14.60 UNSPECIFIED DIABETES MELLITUS WITH MUSCULOSKELETAL AND CONNECTIVE TISSUE COMPLICATION E14.61 UNSPECIFIED DIABETES MELLITUS WITH SKIN AND SUBCUTANEOUS TISSUE COMPLICATION E14.62 UNSPECIFIED DIABETES MELLITUS WITH PERIODONTAL COMPLICATION E14.63 UNSPECIFIED DIABETES MELLITUS WITH HYPOGLYCAEMIA E14.64 UNSPECIFIED DIABETES MELLITUS WITH POOR CONTROL, SO DESCRIBED E14.68 UNSPECIFIED DIABETES MELLITUS WITH OTHER SPECIFIED COMPLICATION, NOT ELSEWHERE CLASSIFIED E14.7 UNSPECIFIED DIABETES MELLITUS WITH MULTIPLE COMPLICATIONS E14.70 UNSPECIFIED DIABETES MELLITUS WITH FOOT ULCER (ANGIOPATHIC) (NEUROPATHIC) E14.71 UNSPECIFIED DIABETES MELLITUS WITH FOOT ULCER (ANGIOPATHIC) (NEUROPATHIC) WITH GANGRENE E14.78 UNSPECIFIED DIABETES MELLITUS WITH MULTIPLE OTHER COMPLICATIONS E14.9 UNSPECIFIED DIABETES MELLITUS WITHOUT (MENTION OF) COMPLICATION HEART FAILURE AND PULMONARY EDEMA 428 HEART FAILURE 428.0 CONGESTIVE HEART FAILURE 428.1 LEFT HEART FAILURE 428.9 UNSPECIFIED 518.4 ACUTE OEDEMA OF LUNG, UNSPECIFIED 150 HEART FAILURE 150.0 CONGESTIVE HEART FAILURE 150.1 LEFT VENTRICULAR FAILURE 150.9 HEART FAILURE, UNSPECIFIED J81 PULMONARY OEDEMA 111.0 HYPERTENSIVE HEART DISEASE WITH (CONGESTIVE) HEART FAILURE HYPERTENSION 401 ESSENTIAL HYPERTENSION 401.0 SPECIFIED AS MALIGNANT 401.1 SPECIFIED AS BENIGN 401.9 NOT SPECIFIED AS 110 ESSENTIAL (PRIMARY) HYPERTENSION II 0.0 BENIGN HYPERTENSION 110.1 MALIGNANT HYPERTENSION 111 HYPERTENSIVE HEART DISEASE 119 MALIGNANT OR BENIGN 402 HYPERTENSIVE HEART DISEASE 402.0 SPECIFIED AS MALIGNANT 402.1 SPECIFIED AS BENIGN 402.9 NOT SPECIFIED AS MALIGNANT OR BENIGN 403 HYPERTENSIVE RENAL DISEASE 403.0 SPECIFIED AS MALIGNANT 403.1 SPECIFIED AS BENIGN 403.9 NOT SPECIFIED AS MALIGNANT OR BENIGN 404 HYPERTENSIVE HEART AND RENAL DISEASE 404.0 SPECIFIED AS MALIGNANT 404.1 SPECIFIED AS BENIGN 404.9 NOT SPECIFIED AS MALIGNANT OR BENIGN 405 SECONDARY HYPERTENSION 405.0 SPECIFIED AS MALIGNANT 405.1 SPECIFIED AS BENIGN 405.9 NOT SPECIFIED AS MALIGNANT OR BENIGN PNEUMONIA 480 VIRAL PNEUMONIA 480.0 PNEUMONIA DUE TO ADENOVIRUS 480.1 PNEUMONIA DUE TO RESPIRATORY SYNCYTIAL VIRUS 480.2 PNEUMONIA DUE TO PARAINFLUENZA VIRUS 480.8 PNEUMONIA DUE TO OTHER VIRUS, NOT ELSEWHERE CLASSIFIED 480.9 VIRAL PNEUMONIA, UNSPECIFIED 481 PNEUMOCOCCAL PNEUMONIA 482 OTHER BACTERIAL PNEUMONIA 482.0 PNEUMONIA DUE TO KLEBSIELLA PNEUMONIAE 482.1 PNEUMONIA DUE TO PSEUDOMONAS 482.2 PNEUMONIA DUE TO HAEMOPHILUS INFLUENZAE (H.INFLUENZAE) J12 VIRAL PNEUMONIA, NOT ELSEWHERE CLASSIFIED J12.0 ADENOVIRAL PNEUMONIA J12.1 RESPIRATORY SYNCYTIAL VIRUS PNEUMONIA J12.2 PARAINFLUENZA VIRUS PNEUMONIA J12.3 HUMAN METAPNEUMOVIRUS PNEUMONIA J12.8 OTHER VIRAL PNEUMONIA J12.9 VIRAL PNEUMONIA, UNSPECIFIED J13 PNEUMONIA DUE TO STREPTOCOCCUS PNEUMONIA J14 PNEUMONIA DUE TO HAEMOPHILUS INFLUENZA J15 BACTERIAL PNEUMONIA, NOT ELSEWHERE CLASSIFIED J15.0 PNEUMONIA DUE TO KLEBSIELLA PNEUMONIA J15.1 PNEUMONIA DUE TO PSEUDOMONAS J15.2 PNEUMONIA DUE TO STAPHYLOCOCCUS 120 482.3 PNEUMONIA DUE TO STREPTOCOCCUS J15.3 PNEUMONIA DUE TO STREPTOCOCCUS, GROUP B J15.4 PNEUMONIA DUE TO OTHER 482.30 STREPTOCOCCUS, STREPTOCOCCI UNSPECIFIED J15.5 PNEUMONIA DUE TO 482.31 GROUP A ESCHERICHIA COLI 482.32 GROUP B J15.6 PNEUMONIA DUE TO OTHER 482.39 OTHER STREPTOCOCCU! AEROBIC GRAM-NEGATIVE BACTERIA J15.7 PNEUMONIA DUE TO MYCOPLASMA PNEUMONIA J15.8 OTHER BACTERIAL PNEUMONIA J15.9 BACTERIAL PNEUMONIA, UNSPECIFIED 482.4 PNEUMONIA DUE TO J16 PNEUMONIA DUE TO OTHER STAPHYLOCOCCUS INFECTIOUS ORGANISMS, NOT 482.40 PNEUMONIA DUE TO ELSEWHERE CLASSIFIED STAPHYLOCOCCUS, J16.0 CHLAMYDIAL PNEUMONIA UNSPECIFIED J16.8 PNEUMONIA DUE TO OTHER 482.41 METHICILLIN SPECIFIED INFECTIOUS ORGANISMS SUSCEPTIBLE PNEUMONIA J18 PNEUMONIA, ORGANISM DUE TO STAPHYLOCOCCUS UNSPECIFIED AUREUS J18.0 BRONCHOPNEUMONIA, 482.42 METHICILLIN RESISTANT PNEUMONIA DUE UNSPECIFIED J18.1 LOBAR PNEUMONIA, TO STAPHYLOCOCCUS UNSPECIFIED AUREUS J18.2 HYPOSTATIC PNEUMONIA, 482.49 OTHER UNSPECIFIED STAPHYLOCOCCUS J18.8 OTHER PNEUMONIA, ORGANISM PNEUMONIA UNSPECIFIED 482.8 PNEUMONIA DUE TO J18.9 PNEUMONIA, UNSPECIFIED OTHER SPECIFIED BACTERIA 482.81 ANAEROBES 482.82 ESCHERICHIA COLI [E. C 482.83 OTHER GRAMNEGATIVE BACTERIA 482.84 LEGIONNAIRES' DISEASE 482.89 OTHER SPECIFIED BACTERIA 482.9 BACTERIAL PNEUMONIA, UNSPECIFIED 483 PNEUMONIA DUE TO OTHER SPECIFIED ORGANISM 483.0 MYCOPLASMA PNEUMONIAE 483.1 CHLAMYDIA 483.8 OTHER SPECIFIED ORGANISM 484 PNEUMONIA IN INFECTIOUS DISEASES CLASSIFIED ELSEWHERE 484.0 MEASLES 484.1 CYTOMEGALIC INCLUSION DISEASE 121 484.2 ORNITHOSIS 484.3 WHOOPING COUGH 484.4 TULARAEMIA 484.5 ANTHRAX 484.6 ASPERGILLOSIS 484.7 PNEUMONIA IN OTHER SYSTEMIC MYCOSES 484.8 PNEUMONIA IN OTHER INFECTIOUS DISEASES 485 BRONCHOPNEUMONIA, ORGANISM UNSPECIFIED 486 PNEUMONIA, ORGANISM UNSPECIFIED Vaccine Preventable Conditions DIPTHERIA 032 DIPHTHERIA 032.0 FAUCIAL DIPHTHERIA 032.1 NASOPHARYNGEAL DIPHTHERIA 032.2 ANTERIOR NASAL DIPHTHERIA 032.3 LARYNGEAL DIPHTHERIA 032.8 OTHER 032.81 CONIUNCTIVAL DIPHTHERIA 032.82 DIPHTHERITIC MYOCARDITIS A36 DIPHTHERIA A36.0 PHARYNGEAL DIPHTHERIA A36.1 NASOPHARYNGEAL DIPHTHERIA A36.2 LARYNGEAL DIPHTHERIA A36.3 CUTANEOUS DIPHTHERIA A36.8 OTHER DIPHTHERIA A36.9 DIPHTHERIA, UNSPECIFIED 032.83 DIPHTHERITIC PERITON 032.84 DIPHTHERITIC CYSTITIS 032.85 CUTANEOUS DIPHTHERJ 032.89 OTHER 032.9 DIPHTHERIA, UNSPECIFIED HEMOPHILUS INFLUENZA TYPE B 320.0 HEMOPHILUS MENINGITIS GOO BACTERIAL MENINGITIS, NOT ELSEWHERE CLASSIFIED GOO.O HAEMOPHILUS MENINGITIS HEPATITIS A 070.0 VIRAL HEPATITIS A WITH HEPATIC COMA 070.1 VIRAL HEPATITIS A WITHOUT MENTION OF HEPATIC COMA B15 ACUTE HEPATITIS A B15.0 HEPATITIS A WITH HEPATIC COMA B15.9 HEPATITIS A WITHOUT HEPATIC COMA HEPATITIS B 070.2 VIRAL HEPATITIS B B16 ACUTE HEPATITIS B 122 WITH HEPATIC COMA 070.3 VIRAL HEPATITIS B WITHOUT MENTION OF HEPATIC COMA B16.0 ACUTE HEPATITIS B WITH DELTA-AGENT (COINFECTION) WITH HEPATIC COMA B16.1 ACUTE HEPATITIS B WITH DELTA-AGENT (COINFECTION) WITHOUT HEPATIC COMA B16.2 ACUTE HEPATITIS B WITHOUT DELTA-AGENT WITH HEPATIC COMA B16.9 ACUTE HEPATITIS B WITHOUT DELTA-AGENT AND WITHOUT HEPATIC COMA INFLUENZA 487 INFLUENZA 487.0 WITH PNEUMONIA 487.1 WITH OTHER RESPIRATORY MANIFESTATIONS 487.8 WITH OTHER MANIFESTATIONS J10 INFLUENZA DUE TO OTHER IDENTIFIED INFLUENZA VIRUS J10.0 INFLUENZA WITH PNEUMONIA, OTHER INFLUENZA VIRUS IDENTIFIED J10.1 INFLUENZA WITH OTHER RESPIRATORY MANIFESTATIONS, OTHER INFLUENZA VIRUS IDENTIFIED J10.8 INFLUENZA WITH OTHER MANIFESTATIONS, OTHER INFLUENZA VIRUS IDENTIFIED J l l INFLUENZA, VIRUS NOT IDENTIFIED J11.0 INFLUENZA WITH PNEUMONIA, VIRUS NOT IDENTIFIED J l l . l INFLUENZA WITH OTHER RESPIRATORY MANIFESTATIONS, VIRUS NOT IDENTIFIED J11.8 INFLUENZA WITH OTHER MANIFESTATIONS, VIRUS NOT IDENTIFIED MEASLES 055 MEASLES 055.0 POSTMEASLES ENCEPHALITIS 055.1 POSTMEASLES PNEUMONIA 055.2 POSTMEASLES OTITIS 055.7 WITH OTHER COMPLICATIONS 055.71 KERATOCONJUNCTIVITIES, MEASLES 055.79 OTHER 055.8 WITH UNSPECIFIED COMPLICATION 055.9 MEASLES WITHOUT MENTION OF COMPLICATION B05 MEASLES B05.0 MEASLES COMPLICATED BY ENCEPHALITIS B05.1 MEASLES COMPLICATED BY MENINGITIS B05.2 MEASLES COMPLICATED BY PNEUMONIA B05.3 MEASLES COMPLICATED BY OTITIS MEDIA B05.4 MEASLES WITH INTESTINAL COMPLICATIONS B05.8 MEASLES WITH OTHER COMPLICATIONS B05.9 MEASLES WITHOUT COMPLICATION MENINGOCOCCAL 036 MENINGOCOCCAL DISEASE(MENINGITIS INFECTION 036.0 MENINGOCOCCAL ) A39 MENINGOCOCCAL INFECTION A39.0 MENINGOCOCCAL MENINGITIS A39.1 WATERHOUSE-FRIDERICHSEN 123 MENINGITIS 036.1 MENINGOCOCCAL ENCEPHALITIS 036.2 MENINGOCOCCAEMIA 036.3 WATERHOUSEFRIDERICHSEN SYNDROME, MENINGOCOCCAL 036.4 MENINGOCOCCAL CARDITIS 036.40 MENINGOCOCCAL CARDITIS, UNSPECIFIED 036.41 MENINGOCOCCAL PERICARDITIS SYNDROME A39.2 ACUTE MENINGOCOCCAEMIA A39.3 CHRONIC MENINGOCOCCAEMIA A39.4 MENINGOCOCCAEMIA, UNSPECIFIED A39.5 MENINGOCOCCAL HEART DISEASE A39.8 OTHER MENINGOCOCCAL INFECTIONS A39.9 MENINGOCOCCAL INFECTION, UNSPECIFIED 036.42 MENINGOCOCCAL ENDOCARDITIS 036.43 MENINGOCOCCAL MYOCARDITIS 036.8 OTHER 036.81 MENINGOCOCCAL OPTIC NEURITIS 036.82 MENINGOCOCCAL ARTHROPATHY 036.89 OTHER 036.9 UNSPECIFIED MUMPS 072 MUMPS B26 MUMPS B26.0 MUMPS ORCHITIS 072.0 MUMPS ORCHITIS B26.1 MUMPS MENINGITIS B26.2 MUMPS ENCEPHALITIS 072.1 MUMPS MENINGITIS B26.3 MUMPS PANCREATITIS 072.2 MUMPS ENCEPHALITIS B26.8 MUMPS WITH OTHER 072.3 MUMPS PANCREATITIS COMPLICATIONS 072.71 MUMPS HEPATITIS B26.9 MUMPS WITHOUT 072.72 MUMPS POLYNEUROPAr COMPLICATION 072.79 OTHER 072.8 MUMPS WITH UNSPECIFI COMPLICATION 072.9 MUMPS WITHOUT MENTI OF COMPLICATION PERTUSSIS 033 WHOOPING COUGH 033.0 BORDETELLA PERTUSSIS (B.PERTUSSIS) 033.1 BORDETELLA PARAPERTUSSIS (B.PARAPERTUSSIS) 033.8 OTHER SPECIFIED ORGANISM 033.9 WHOOPING COUGH, A37 WHOOPING COUGH A37.0 WHOOPING COUGH DUE TO BORDETELLA PERTUSSIS A37.1 WHOOPING COUGH DUE TO BORDETELLA PARAPERTUSSIS A37.8 WHOOPING COUGH DUE TO OTHER BORDETELLA SPECIES A37.9 WHOOPING COUGH, UNSPECIFIED 124 UNSPECIFIED ORGANISM PNEUMOCOCCAL 038.2 PNEUMOCOCCAL SEPTICAEMIA 041.2 PNEUMOCOCCUS 320.1 PNEUMOCOCCAL MENINGITIS 481 PNEUMOCOCCAL PNEUMONIA [STREPTOCOCCUS PNEUMONIAE PNEUMONIA] 567.1 PNEUMOCOCCAL PERITONITIS 711.0 PYOGENIC ARTHRITIS GOO BACTERIAL MENINGITIS, NOT ELSEWHERE CLASSIFIED G00.1 PNEUMOCOCCAL MENINGITIS A40.3 SEPSIS DUE TO STREPTOCOCCUS PNEUMONIA J13 PNEUMONIA DUE TO STREPTOCOCCUS PNEUMONIA POLIOMYELITIS 045 ACUTE POLIOMYELITIS 045.0 ACUTE PARALYTIC POLIOMYELITIS SPECIFIED AS BULBAR 045.1 ACUTE POLIOMYELITIS WITH OTHER PARALYSIS 045.2 ACUTE NONPARALYTIC POLIOMYELITIS 045.9 ACUTE POLIOMYELITIS, UNSPECIFIED A80 ACUTE POLIOMYELITIS A80.0 ACUTE PARALYTIC POLIOMYELITIS, VACCINEASSOCIATED A80.1 ACUTE PARALYTIC POLIOMYELITIS, WILD VIRUS, IMPORTED A80.2 ACUTE PARALYTIC POLIOMYELITIS, WILD VIRUS, INDIGENOUS A80.3 ACUTE PARALYTIC POLIOMYELITIS, OTHER AND UNSPECIFIED A80.4 ACUTE NONPARALYTIC POLIOMYELITIS A80.9 ACUTE POLIOMYELITIS, UNSPECIFIED TUBERCULOSIS 010 PRIMARY TUBERCULOUS INFECTION 010.0 PRIMARY TUBERCULOUS COMPLEX 010.1 TUBERCULOUS PLEURISY IN PRIMARY PROGRESSIVE TUBERCULOSIS 010.8 OTHER PRIMARY PROGRESSIVE TUBERCULOSIS 010.9 UNSPECIFIED 011 PULMONARY TUBERCULOSIS 011.0 TUBERCULOSIS OF LUNG, INFILTRATIVE 011.1 TUBERCULOSIS OF LUNG, NODULAR 011.2 TUBERCULOSIS OF LUNG WITH CAVITATION 011.3 TUBERCULOSIS OF BRONCHUS A15 RESPIRATORY TUBERCULOSIS, BACTERIOLOGICALLY AND HISTOLOGICALLY CONFIRMED A15.0 TUBERCULOSIS OF LUNG, CONFIRMED BY SPUTUM MICROSCOPY WITH OR WITHOUT CULTURE A15.00 TUBERCULOSIS OF LUNG, CONFIRMED BY SPUTUM MICROSCOPY WITH OR WITHOUT CULTURE, WITH A15.01 TUBERCULOSIS OF LUNG, CONFIRMED BY SPUTUM MICROSCOPY WITH OR WITHOUT CULTURE, WITHOUT A15.1 TUBERCULOSIS OF LUNG, CONFIRMED BY CULTURE ONLY A15.2 TUBERCULOSIS OF LUNG, CONFIRMED HISTOLOGICALLY A15.20 TUBERCULOSIS OF LUNG, 125 011.4 TUBERCULOUS FIBROSIS CONFIRMED HISTOLOGICALLY, WITH CAVITATION OF LUNG A15.21 TUBERCULOSIS OF LUNG, 011.5 TUBERCULOUS BRONCHIECTASIS CONFIRMED HISTOLOGICALLY, WITHOUT CAVITATION OR 011.6 TUBERCULOUS UNSPECIFIED PNEUMONIA (ANY FORM) A15.3 TUBERCULOSIS OF LUNG, 011.7 TUBERCULOUS CONFIRMED BY UNSPECIFIED MEANS PNEUMOTHORAX 011.8 OTHER PULMONARY A15.30 TUBERCULOSIS OF LUNG, CONFIRMED BY UNSPECIFIED MEANS, TUBERCULOSIS WITH CAVITATION 011.9 UNSPECIFIED A15.31 TUBERCULOSIS OF LUNG, 012 OTHER RESPIRATORY CONFIRMED BY UNSPECIFIED MEANS, TUBERCULOSIS WITHOUT CAVITATION OR 012.0 TUBERCULOUS UNSPECIFIED PLEURISY A15.4 TUBERCULOSIS OF 012.1 TUBERCULOSIS OF INTRATHORACIC LYMPH NODES, INTRATHORACIC LYMPH NODES CONFIRMED BACTERIOLOGICALLY AND HISTOLOGICALLY 012.2 ISOLATED TRACHEAL A15.5 TUBERCULOSIS OF LARYNX, OR BRONCHIAL TRACHEA AND BRONCHUS TUBERCULOSIS CONFIRMED BACTERIOLOGICALLY 012.3 TUBERCULOUS AND HISTOLOGICALLY16.210 LARYNGITIS A15.6 TUBERCULOUS PLEURISY, 012.8 OTHER CONFIRMED BACTERIOLOGICALLY 013 TUBERCULOSIS OF AND HISTOLOGICALLY MENINGES AND CENTRAL A15.7 PRIMARY RESPIRATORY NERVOUS SYSTEM TUBERCULOSIS, CONFIRMED 013.0 TUBERCULOUS BACTERIOLOGICALLY AND MENINGITIS HISTOLOGICALLY 013.1 TUBERCULOMA OF A15.8 OTHER RESPIRATORY MENINGES TUBERCULOSIS, CONFIRMED 013.2 TUBERCULOMA OF BACTERIOLOGICALLY AND BRAIN 013.3 TUBERCULOUS ABSCESS HISTOLOGICALLY A15.9 RESPIRATORY TUBERCULOSIS OF BRAIN UNSPECIFIED, CONFIRMED 013.4 TUBERCULOMA OF BACTERIOLOGICALLY AND SPINAL CORD 013.5 TUBERCULOUS ABSCESS HISTOLOGICALLY A15.90 RESPIRATORY TUBERCULOSIS OF SPINAL CORD UNSPECIFIED, CONFIRMED 013.6 TUBERCULOUS BACTERIOLOGICALLY AND ENCEPHALITIS OR MYELITIS HISTOLOGICALLY WITH 013.8 OTHER CAVITATION 013.9 UNSPECIFIED A15.91 RESPIRATORY TUBERCULOSIS 014 TUBERCULOSIS OF UNSPECIFIED, CONFIRMED INTESTINES, PERITONEUM BACTERIOLOGICALLY AND AND MESENTERIC GLANDS HISTOLOGICALLY, WITHOUT 014.0 TUBERCULOUS CAVITATION OR UNSPECIFIED PERITONITIS A16 RESPIRATORY TUBERCULOSIS, 014.8 OTHER 015 TUBERCULOSIS OF BONES NOT CONFIRMED BACTERIOLOGICALLY OR AND JOINTS HISTOLOGICALLY 015.0 VERTEBRAL COLUMN A16.0 TUBERCULOSIS OF LUNG, 015.1 HIP 126 015.2 KNEE 015.7 OTHER BONE 015.8 OTHER JOINT 015.9 UNSPECIFIED 016 TUBERCULOSIS OF GENITOURINARY SYSTEM 016.0 KIDNEY 016.1 BLADDER 016.2 URETER 016.3 OTHER URINARY ORGANS 016.4 EPIDIDYMIS 016.5 OTHER MALE GENITAL ORGANS 016.6 TUBERCULOUS OOPHORITIS AND SALPINGITIS 016.7 FEMALE GENITAL ORGANS 016.9 UNSPECIFIED 017 TUBERCULOSIS OF OTHER ORGANS 017.0 SKIN AND SUBCUTANEOUS CELLULAR TISSUE 017.1 ERYTHEMA NODOSUM WITH HYPERSENSITIVITY REACTION IN TUBERCULOSIS 017.2 PERIPHERAL LYMPH NODES 017.3 EYE 017.4 EAR 017.5 THYROID GLAND 017.6 ADRENAL GLANDS 017.7 SPLEEN 017.8 ESOPHAGUS 017.9OTHER 018 MILIARY TUBERCULOSIS 018.0 ACUTE 018.8 OTHER 018.9 UNSPECIFIED BACTERIOLOGICALLY AND HISTOLOGICALLY NEGATIVE A16.1 TUBERCULOSIS OF LUNG, BACTERIOLOGICAL AND HISTOLOGICAL EXAMINATION NOT DONE A16.10 TUBERCULOSIS OF LUNG, BACTERIOLOGICAL AND HISTOLOGICAL EXAMINATION NOT DONE, WITH CAVITATION A16.ll TUBERCULOSIS OF LUNG, BACTERIOLOGICAL AND HISTOLOGICAL EXAMINATION NOT DONE, WITHOUT CAVITATION OR UNSPECIFIED A16.2 TUBERCULOSIS OF LUNG, WITHOUT MENTION OF BACTERIOLOGICAL OR HISTOLOGICAL CONFIRMATION A16.20 TUBERCULOSIS OF LUNG, WITHOUT MENTION OF BACTERIOLOGICAL OR HISTOLOGICAL CONFIRMATION, WITH CAVITATION A16.21 TUBERCULOSIS OF LUNG, WITHOUT MENTION OF BACTERIOLOGICAL OR HISTOLOGICAL CONFIRMATION, WITHOUT CAVITATION OR UNSPECIFIED3 A16.3 TUBERCULOSIS OF INTRATHORACIC LYMPH NODES, WITHOUT MENTION OF BACTERIOLOGICAL OR HISTOLOGICAL CONFIRMATION A16.4 TUBERCULOSIS OF LARYNX, TRACHEA AND BRONCHUS, WITHOUT MENTION OF BACTERIOLOGICAL OR HISTOLOGICAL CONFIRMATION A16.5 TUBERCULOUS PLEURISY, WITHOUT MENTION OF BACTERIOLOGICAL OR HISTOLOGICAL CONFIRMATION A16.7 PRIMARY RESPIRATORY TUBERCULOSIS WITHOUT MENTION OF BACTERIOLOGICAL OR HISTOLOGICAL CONFIRMATION A16.8 OTHER RESPIRATORY TUBERCULOSIS, WITHOUT MENTION OF BACTERIOLOGICAL OR 127 HISTOLOGICAL CONFIRMATION A16.9 RESPIRATORY TUBERCULOSIS UNSPECIFIED, WITHOUT MENTION OF BACTERIOLOGICAL OR HISTOLOGICAL CONFIRMATION A16.90 RESPIRATORY TUBERCULOSIS UNSPECIFIED, WITHOUT MENTION OF BACTERIOLOGICAL OR HISTOLOGICAL CONFIRMATION, WITH CAVITATION A16.91 RESPIRATORY TUBERCULOSIS UNSPECIFIED, WITHOUT MENTION OF BACTERIOLOGICAL OR HISTOLOGICAL CONFIRMATION, WITHOUT CAVITATION OR UNSPECIFIEDA18.3 A17 TUBERCULOSIS OF NERVOUS SYSTEM A17.0 TUBERCULOUS MENINGITIS A17.1 MENINGEAL TUBERCULOMA A17.8 OTHER TUBERCULOSIS OF NERVOUS SYSTEM A17.9 TUBERCULOSIS OF NERVOUS SYSTEM, UNSPECIFIED A18 TUBERCULOSIS OF OTHER ORGANS A18.0 TUBERCULOSIS OF BONES AND JOINTS A18.1 TUBERCULOSIS OF GENITOURINARY SYSTEM A18.2 TUBERCULOUS PERIPHERAL LYMPHADENOPATHY A18.3 TUBERCULOSIS OF INTESTINES, PERITONEUM AND MESENTERIC LYMPH NODES8.4 A18.4 TUBERCULOSIS OF SKIN AND SUBCUTANEOUS TISSUE A18.5 TUBERCULOSIS OF EYE A18.6 TUBERCULOSIS OF EAR A18.7 TUBERCULOSIS OF ADRENAL GLANDS A18.8 TUBERCULOSIS OF OTHER SPECIFIED ORGANS A19 MILIARY TUBERCULOSIS A19.0 ACUTE MILIARY TUBERCULOSIS OF A SINGLE SPECIFIED SITE A19.1 ACUTE MILIARY TUBERCULOSIS OF MULTIPLE SITES A19.2 ACUTE MILIARY TUBERCULOSIS, UNSPECIFIED A19.8 OTHER MILIARY TUBERCULOSIS A19.9 MILIARY TUBERCULOSIS, 128 UNSPECIFIED RUBELLA 056.0 WITH NEUROLOGICAL COMPLICATIONS 056.00 WITH UNSPECIFIED NEUROLOGICAL COMPLICATION 056.01 ENCEPHALOMYELITIS DUE TO RUBELLA 056.09 OTHER 056.7 WITH OTHER SPECIFIED COMPLICATIONS 056.71 ARTHRITIS DUE TO RUBELLA B06 RUBELLA [GERMAN MEASLES] B06.0 RUBELLA WITH NEUROLOGICAL COMPLICATIONS B06.8 RUBELLA WITH OTHER COMPLICATIONS B06.9 RUBELLA WITHOUT COMPLICATION 056.79 OTHER 056.8 WITH UNSPECIFIED COMPLICATIONS 056.9 RUBELLA WITHOUT MENTION OF COMPLICATION TETANUS 037 TETANUS A34 OBSTETRICAL TETANUS A35 OTHER TETANUS Acute Conditions DENTAL CONDITIONS 521 DISEASES OF HARD K02 DENTAL CARIES TISSUES OF TEETH K02.0 CARIES LIMITED TO ENAMEL 521.0 DENTAL CARIES K02.1 CARIES OF DENTINE K02.2 CARIES OF CEMENTUM 521.00 DENTAL CARIES, UNSPECIFIED K02.3 ARRESTED DENTAL CARIES 521.01 DENTAL CARIES K02.4 ODONTOCLASIA LIMITED TO ENAMEL K02.8 OTHER DENTAL CARIES 521.02 DENTAL CARIES K02.9 DENTAL CARIES, UNSPECIFIED EXTENDING INTO DENTINE K03 OTHER DISEASES OF HARD 521.03 DENTAL CARIES TISSUES OF TEETH EXTENDING INTO PULP K03.0 EXCESSIVE ATTRITION OF 521.04 ARRESTED DENTAL TEETH CARIES K03.1 ABRASION OF TEETH K03.2 EROSION OF TEETH 521.05 ODONTOCLASIA 521.06 DENTAL CARIES PIT K03.3 PATHOLOGICAL RESORPTION AND FISSURE OF TEETH 521.07 DENTAL CARIES OF K03.4 HYPERCEMENTOSIS SMOOTH SURFACE K03.5 ANKYLOSIS OF TEETH 521.08 DENTAL CARIES OF K03.6 DEPOSITS [ACCRETIONS] ON ROOT SURFACE TEETH 521.09 OTHER DENTAL CARIES K03.7 POSTERUPTIVE COLOUR 521.1 EXCESSIVE ATTRITION CHANGES OF DENTAL HARD TISSUES 521.10 EXCESSIVE ATTRITION, K03.8 OTHER SPECIFIED DISEASES OF UNSPECIFIED HARD TISSUES OF TEETH 521.11 EXCESSIVE ATTRITION, K03.9 DISEASE OF HARD TISSUES OF TEETH, UNSPECIFIED 129 K04 DISEASES OF PULP AND PERIAPICAL TISSUES 521.12 EXCESSIVE ATTRITION, K04.0 PULPITIS K04.1 NECROSIS OF PULP EXTENDING INTO DENTINE K04.2 PULP DEGENERATION 521.13 EXCESSIVE ATTRITION, K04.3 ABNORMAL HARD TISSUE EXTENDING INTO PULP FORMATION IN PULP 521.14 EXCESSIVE ATTRITION, K04.4 ACUTE APICAL PERIODONTITIS OF PULPAL ORIGIN LOCALIZED K04.5 CHRONIC APICAL 521.15 EXCESSIVE ATTRITION, PERIODONTITIS K04.6 PERIAPICAL ABSCESS WITH GENERALIZED SINUS 521.2 ABRASION K04.7 PERIAPICAL ABSCESS WITHOUT 521.20 ABRASION, UNSPECIFIE1 SINUS K04.8 RADICULAR CYST 521.21 ABRASION, LIMITED TO K04.9 OTHER AND UNSPECIFIED ENAMEL DISEASES OF PULP AND PERIAPICAL 521.22 ABRASION, EXTENDING TISSUES K05 GINGIVITIS AND PERIODONTAL INTO DENTINE DISEASES 521.23 ABRASION, EXTENDING K05.0 ACUTE GINGIVITIS INTO PULP K05.1 CHRONIC GINGIVITIS5.2 K05.2 ACUTE PERIODONTITIS 521.24 ABRASION, LOCALIZED K05.3 CHRONIC PERIODONTITIS 521.25 ABRASION, GENERALIZI K05.4 PERIODONTOSIS K05.5 OTHER PERIODONTAL DISEASES 521.3 EROSION K05.6 PERIODONTAL DISEASE, 521.30 EROSION, UNSPECIFIED UNSPECIFIED K06 OTHER DISORDERS OF GINGIVA 521.31 EROSION, LIMITED TO AND EDENTULOUS ALVEOLAR RIDGE ENAMEL K06.0 GINGIVAL RECESSION K06.1 GINGIVAL ENLARGEMENT 521.32 EROSION, EXTENDING IT K06.2 GINGIVAL AND EDENTULOUS DENTINE ALVEOLAR RIDGE LESIONS 521.33 EROSION, EXTENDING IT ASSOCIATED WITH TRAUMA K06.8 OTHER SPECIFIED DISORDERS PULP OF GINGIVA AND EDENTULOUS 521.34 EROSION, LOCALIZED ALVEOLAR RIDGE K06.9 DISORDER OF GINGIVA AND 521.35 EROSION, GENERALIZE! EDENTULOUS ALVEOLAR RIDGE, 521.4 PATHOLOGICAL UNSPECIFIED7.6 RESORPTION K08 OTHER DISORDERS OF TEETH AND SUPPORTING STRUCTURES 521.40 PATHOLOGICAL K08.0 EXFOLIATION OF TEETH DUE TO RESORPTION, UNSPECIFIED SYSTEMIC CAUSES 521.41 PATHOLOGICAL K08.1 LOSS OF TEETH DUE TO RESORPTION, INTERNAL ACCIDENT, EXTRACTION OR LOCAL PERIODONTAL DISEASE 521.42 PATHOLOGICAL K08.2 ATROPHY OF EDENTULOUS RESORPTION, EXTERNAL ALVEOLAR RIDGE 521.49 OTHER PATHOLOGICAL K08.3 RETAINED DENTAL ROOT K08.8 OTHER SPECIFIED DISORDERS RESORPTION LIMITED TO ENAMEL 130 521.5 HYPERCEMENTOSIS 521.6 ANKYLOSIS OF TEETH 521.7 POSTERUPTIVE COLOUR CHANGES 521.8 OTHER DISEASES OF HARD TISSUES OF TEETH 521.81 CRACKED TOOTH 521.89 OTHER SPECIFIED DISEASES OF HARD TISSUES OF TEETH 521.9 UNSPECIFIED 522 DISEASES OF PULP AND PERIAPICAL TISSUES 522.0 PULPITIS 522.1 NECROSIS OF THE PULP 522.2 PULP DEGENERATION 522.3 ABNORMAL HARD TISSUE FORMATION IN PULP 522.4 ACUTE APICAL PERIODONTITIS OF PULPAL ORIGIN 522.5 PERIAPICAL ABSCESS WITHOUT SINUS 522.6 CHRONIC APICAL PERIODONTITIS 522.7 PERIAPICAL ABSCESS WITH SINUS 522.8 RADICULAR CYST 522.9 OTHER AND UNSPECIFIED 523 GINGIVAL AND PERIODONTAL DISEASES 523.0 ACUTE GINGIVITIS 523.00 ACUTE GINGIVITIS, PLAQUE INDUCED 523.01 ACUTE GINGIVITIS, NON-PLAQUE INDUCED 523.1 CHRONIC GINGIVITIS 523.10 CHRONIC GINGIVITIS, PLAQUE INDUCED 523.11 CHRONIC GINGIVITIS, NON-PLAQUE INDUCED 523.2 GINGIVAL RECESSION 523.20 GINGIVAL RECESSION, UNSPECIFIED OF TEETH AND SUPPORTING STRUCTURES K08.80 MAXILLARY ALVEOLAR RIDGE HYPERPLASIA K08.81 MANDIBULAR ALVEOLAR RIDGE HYPERPLASIA K08.82 MAXILLARY ALVEOLAR RIDGE HYPOPLASIA10.1 K08.83 MANDIBULAR ALVEOLAR RIDGE HYPOPLASIA K08.87 TOOTHACHE NOS K08.88 OTHER SPECIFIED DISORDERS OF TEETH AND SUPPORTING STRUCTURES K08.9 DISORDER OF TEETH AND SUPPORTING STRUCTURES, UNSPECIFIED K09.8 OTHER CYSTS OF ORAL REGION, NOT ELSEWHERE CLASSIFIED K09.9 CYST OF ORAL REGION, UNSPECIFIED K12 STOMATITIS AND RELATED LESIONS K12.0 RECURRENT ORAL APHTHAE K12.1 OTHER FORMS OF STOMATITIS K12.2 CELLULITIS AND ABSCESS OF MOUTH K12.3 ORAL MUCOSITIS (ULCERATIVE) K13 OTHER DISEASES OF LIP AND ORAL MUCOSA K13.0 DISEASES OF LIPS K13.1 CHEEK AND LIP BITING K13.2 LEUKOPLAKIA AND OTHER DISTURBANCES OF ORAL EPITHELIUM, INCLUDING TONGUE K13.3 HAIRY LEUKOPLAKIA K13.4 GRANULOMA AND GRANULOMA-LIKE LESIONS OF ORAL MUCOSA K13.5 ORAL SUBMUCOUS FIBROSIS K13.6 IRRITATIVE HYPERPLASIA OF ORAL MUCOSA K13.7 OTHER AND UNSPECIFIED LESIONS OF ORAL MUCOSA 523.21 GINGIVAL RECESSION, MINIMAL 523.22 GINGIVAL RECESSION, MODERATE 523.23 GINGIVAL RECESSION, 131 SEVERE 523.24 GINGIVAL RECESSION, LOCALIZED 523.25 GINGIVAL RECESSION, GENERALIZED 523.3 ACUTE PERIODONTITIS 523.30 AGGRESSIVE PERIODONTITIS, UNSPECIFIED 523.31 AGGRESSIVE PERIODONTITIS, LOCALIZED 523.32 AGGRESSIVE PERIODONTITIS, GENERALIZEI 523.33 ACUTE PERIODONTITIS 523.4 CHRONIC PERIODONTITIS 523.40 CHRONIC PERIODONTIT UNSPECIFIED 523.41 CHRONIC PERIODONTIT LOCALIZED 523.42 CHRONIC PERIODONTIT GENERALIZED 523.5 PERIODONTOSIS 523.6 ACCRETIONS ON TEETH 523.8 OTHER PERIODONTAL DISEASES 523.9 UNSPECIFIED 525 OTHER DISEASES AND CONDITIONS OF THE TEETH AND SUPPORTING STRUCTURES 525.0 EXFOLIATION OF TEETH DUE TO SYSTEMIC CAUSES 525.1 LOSS OF TEETH DUE TO ACCIDENT, EXTRACTION OR LOCAL PERIODONTAL DISEASE 525.10 ACQUIRED ABSENCE OF TEETH, UNSPECIFIED 525.11 LOSS OF TEETH DUE TO TRAUMA 525.12 LOSS OF TEETH DUE TO PERIODONTAL DISEASE 525.13 LOSS OF TEETH DUE TO CARIES 525.19 OTHER LOSS OF TEETH 525.2 ATROPHY OF EDENTULOUS ALVEOLAR RIDGE 525.20 UNSPECIFIED ATROPHY OF EDENTULOUS ALVEOLAR RIDGE 525.21 MINIMAL ATROPHY OF r MANDIBLE 525.22 MODERATE ATROPHY O THE MANDIBLE 525.23 SEVERE ATROPHY OF TI MANDIBLE 525.24 MINIMAL ATROPHY OF : MAXILLA 525.25 MODERATE ATROPHY O THE MAXILLA 525.26 SEVERE ATROPHY OF TI MAXILLA 525.3 RETAINED DENTAL ROOT 525.4 COMPLETE EDENTULISM 525.40 COMPLETE EDENTULISM, UNSPECIFIED 525.41 COMPLETE EDENTULISM CLASS I 525.42 COMPLETE EDENTULISM CLASS II 525.43 COMPLETE EDENTULISM CLASS III 525.44 COMPLETE EDENTULISM CLASS IV 525.5 PARTIAL EDENTULISM 525.50 PARTIAL EDENTULISM, UNSPECIFIED 525.51 PARTIAL EDENTULISM, CLASS I 525.52 PARTIAL EDENTULISM, CLASS II 525.53 PARTIAL EDENTULISM, CLASS III 525.54 PARTIAL EDENTULISM, CLASS IV 525.6 UNSATISFACTORY RESTORATION OF TOOTH 525.60 UNSPECIFIED UNSATISFACTORY RESTORATION OF TOOTH 525.61 OPEN RESTORATION MARGINS 525.62 UNREPAIRABLE OVERHANGING OF DENTAL RESTORATIVE MATERIALS 525.63 FRACTURED DENTAL RESTORATIVE MATERIAL WITHOUT LOSS OF MATERIAL 525.64 FRACTURED DENTAL RESTORATIVE MATERIAL WITH LOSS OF MATERIAL 525.65 CONTOUR OF EXISTING RESTORATION OF TOOTH BIOLOGICALLY INCOMPATIBLE WITH ORAL HEALTH 525.66 ALLERGY TO EXISTING DENTAL RESTORATIVE MATERIAL 525.67 POOR AESTHETICS OF EXISTING RESTORATION 525.69 OTHER UNSATISFACTORY RESTORATION OF EXISTING TOOTH 525.7 ENDOSSEOUS DENTAL IMPLANT FAILURE 525.71 OSSEOINTEGRATION FAILURE OF DENTAL IMPLANT 525.72 POST-OSSEOINTEGRATION BIOLOGICAL FAILURE OF DENTAL IMPLANT 525.73 POST-OSSEOINTEGRATION MECHANICAL FAILURE OF DENTAL IMPLANT 525.79 OTHER ENDOSSEOUS DENTAL IMPLANT FAILURE 525.8 OTHER 525.9 UNSPECIFIED 528 DISEASES OF THE ORAL SOFT TISSUES, EXCLUDING LESIONS SPECIFIC FOR GINGIVA AND TONGUE 528.0 STOMATITIS 528.00 STOMATITIS AND MUCOSITIS, UNSPECIFIED 528.01 MUCOSITIS (ULCERATIVE) DUE TO ANTINEOPLASTIC THERAPY 528.02 MUCOSITIS (ULCERATIVE) DUE TO OTHER DRUGS 528.09 OTHER STOMATITIS AND MUCOSITIS (ULCERATIVE) 528.1 CANCRUM ORIS 528.2 ORAL APHTHAE 528.3 CELLULITIS AND ABSCESS 528.4 CYSTS 528.5 DISEASES OF LIPS 528.6 LEUKOPLAKIA OF ORAL MUCOSA, INCLUDING TONGUE 528.7 OTHER DISTURBANCES OF ORAL EPITHELIUM, INCLUDING TONGUE 528.71 MINIMAL KERATINIZED RESIDUAL RIDGE MUCOSA 528.72 EXCESSIVE KERATINIZED RESIDUAL RIDGE MUCOSA 528.79 OTHER DISTURBANCES OF ORAL EPITHELIUM, INCLUDING TONGUE 528.8 ORAL SUBMUCOUS FIBROSIS, INCLUDING OF TONGUE 528.9 OTHER AND UNSPECIFIED CELLULITIS 681 CELLULITIS AND ABSCESS OF FINGER AND TOE 681.0 FINGER 681.00 CELLULITIS AND ABSCESS, UNSPECIFIED 681.01 FELON 681.02 ONYCHIA AND PARONYCHIA OF FINGER 681.1 TOE 681.10 CELLULITIS AND ABSCESS, UNSPECIFIED 681.11 ONYCHIA AND PARONYCHIA OF TOE 681.9 CELLULITIS AND ABSCESS OF UNSPECIFIED DIGIT 682 OTHER CELLULITIS AND ABSCESS 682.0 FACE 682.1 NECK 682.2 TRUNK 682.3 UPPER ARM AND FOREARM 682.4 HAND, EXCEPT FINGERS 682.5 BUTTOCK L03 CELLULITIS L03.0 CELLULITIS OF FINGER AND TOE L03.00 CELLULITIS OF FINGER L03.01 CELLULITIS OF TOE L03.1 CELLULITIS OF OTHER PARTS OF LIMB L03.10 CELLULITIS OF UPPER LIMBL03.11O L03.ll CELLULITIS OF LOWER LIMB L03.2 CELLULITIS OF FACE L03.3 CELLULITIS OF TRUNK L03.30 CELLULITIS OF CHEST WALL L03.31 CELLULITIS OF ABDOMINAL WALL L03.32 CELLULITIS OF UMBILICUS L03.33 CELLULITIS OF GROIN L03.34 CELLULITIS OF BACK [ANY PART EXCEPT BUTTOCK] L03.35 CELLULITIS OF BUTTOCK L03.36 CELLULITIS OF PERINEUM L03.39 CELLULITIS OF TRUNK, UNSPECIFIED L03.8 CELLULITIS OF OTHER SITES L03.9 CELLULITIS, UNSPECIFIED L04 ACUTE LYMPHADENITIS 135 682.6 LEG, EXCEPT FOOT 682.7 FOOT, EXCEPT TOES 682.8 OTHER SPECIFIED SITE 682.9 UNSPECIFIED SITE 683 ACUTE LYMPHADENITIS L04.0 ACUTE LYMPHADENITIS OF FACE, HEAD AND NECK L04.1 ACUTE LYMPHADENITIS OF TRUNK L04.2 ACUTE LYMPHADENITIS OF UPPER LIMB L04.3 ACUTE LYMPHADENITIS OF 686 OTHER LOCAL LOWER LIMB INFECTIONS OF SKIN AND L04.8 ACUTE LYMPHADENITIS OF SUBCUTANEOUS TISSUE OTHER SITES 686.0 PYODERMA L04.9 ACUTE LYMPHADENITIS, 686.00 PYODERMA, UNSPECIFIED UNSPECIFIED L08 OTHER LOCAL INFECTIONS OF 686.01 PYODERMA SKIN AND SUBCUTANEOUS TISSUE GANGRENOSUM L08.0 PYODERMA 686.09 OTHER PYODERMA L08.1 ERYTHRASMA 686.1 PYOGENIC GRANULOMA L08.8 OTHER SPECIFIED LOCAL 686.8 OTHER LOCAL INFECTIONS OF SKIN AND INFECTIONS OF SKIN AND SUBCUTANEOUS TISSUE SUBCUTANEOUS TISSUE L08.9 LOCAL INFECTION OF SKIN AND 686.9 UNSPECIFIED LOCAL SUBCUTANEOUS TISSUE, INFECTIONS OF SKIN AND UNSPECIFIED SUBCUTANEOUS TISSUE L44.4 INFANTILE PAPULAR ACRODERMATITIS [GIANNOTTICROSTI] L88 PYODERMA GANGRENOSUM L92.2 GRANULOMA FACIALE [EOSINOPHILIC GRANULOMA OF SKIN] L98.0 PYOGENIC GRANULOMA L98.3 EOSINOPHILIC CELLULITIS [WELLS] PELVIC INFLAMMATORY DISEASE 614 INFLAMMATORY DISEASE OF OVARY, FALLOPIAN TUBE, PELVIC CELLULAR TISSUE AND PERITONEUM 614.0 ACUTE SALPINGITIS AND OOPHORITIS 614.1 CHRONIC SALPINGITIS AND OOPHORITIS 614.2 SALPINGITIS AND OOPHORITIS, NOT SPECIFIED AS ACUTE, SUBACUTE OR CHRONIC 614.3 ACUTE PARAMETRITIS AND PELVIC CELLULITIS 614.4 CHRONIC OR UNSPECIFIED PARAMETRITIS AND PELVIC CELLULITIS 614.5 ACUTE OR UNSPECIFIED PELVIC PERITONITIS, FEMALE 614.6 PELVIC PERITONEAL ADHESIONS, FEMALE N70 SALPINGITIS AND OOPHORITIS N70.0 ACUTE SALPINGITIS AND OOPHORITIS N70.1 CHRONIC SALPINGITIS AND OOPHORITIS N70.9 SALPINGITIS AND OOPHORITIS, UNSPECIFIED N73 OTHER FEMALE PELVIC INFLAMMATORY DISEASES N73.0 ACUTE PARAMETRITIS AND PELVIC CELLULITIS N73.1 CHRONIC PARAMETRITIS AND PELVIC CELLULITIS N73.2 UNSPECIFIED PARAMETRITIS AND PELVIC CELLULITIS N73.3 FEMALE ACUTE PELVIC PERITONITIS N73.4 FEMALE CHRONIC PELVIC PERITONITIS N73.5 FEMALE PELVIC PERITONITIS, UNSPECIFIED 136 SEVERE EAR, NOSE AND THROAT (ENT) INFECTIONS 614.7 OTHER CHRONIC PELVIC PERITONITIS, FEMALE 614.8 OTHER SPECIFIED INFLAMMATORY DISEASE OF FEMALE PELVIC ORGANS AND TISSUES 614.9 UNSPECIFIED INFLAMMATORY DISEASE OF FEMALE PELVIC ORGANS AND TISSUES N73.6 FEMALE PELVIC PERITONEAL ADHESIONS N73.8 OTHER SPECIFIED FEMALE PELVIC INFLAMMATORY DISEASES N73.9 FEMALE PELVIC INFLAMMATORY DISEASE, UNSPECIFIED N99.4 POSTPROCEDURAL PELVIC PERITONEAL ADHESIONS 382 SUPPURATIVE AND UNSPECIFIED OTITIS MEDIA 382.0 ACUTE SUPPURATIVE OTITIS MEDIA 382.00 ACUTE SUPPURATIVE OTITIS MEDIA WITHOUT SPONTANEOUS RUPTURE OF EAR DRUM 382.01 ACUTE SUPPURATIVE OTITIS MEDIA WITH SPONTANEOUS RUPTURE OF EAR DRUM 382.02 ACUTE SUPPURATIVE OTITIS MEDIA IN DISEASES CLASSIFIED ELSEWHERE 382.1 CHRONIC TUBOTYMPANIC SUPPURATIVE OTITIS MEDIA 382.2 CHRONIC ATTICOANTRAL SUPPURATIVE OTITIS MEDIA 382.3 UNSPECIFIED CHRONIC SUPPURATIVE OTITIS MEDIA 382.4 UNSPECIFIED SUPPURATIVE OTITIS MEDIA 382.9 UNSPECIFIED OTITIS MEDIA 462 ACUTE PHARYNGITIS 463 ACUTE TONSILLITIS 465 ACUTE UPPER RESPIRATORY INFECTIONS OF MULTIPLE OR UNSPECIFIED SITE 465.0 ACUTE LARYNGOPHARYNGITIS 465.8 OTHER MULTIPLE SITES 465.9 UNSPECIFIED SITE 472.1 CHRONIC PHARYNGITIS H66 SUPPURATIVE AND UNSPECIFIED OTITIS MEDIA H66.0 ACUTE SUPPURATIVE OTITIS MEDIA H66.1 CHRONIC TUBOTYMPANIC SUPPURATIVE OTITIS MEDIA H66.2 CHRONIC ATTICOANTRAL SUPPURATIVE OTITIS MEDIA H66.3 OTHER CHRONIC SUPPURATIVE OTITIS MEDIA H66.4 SUPPURATIVE OTITIS MEDIA, UNSPECIFIED H66.9 OTITIS MEDIA, UNSPECIFIED H67 OTITIS MEDIA IN DISEASES CLASSIFIED ELSEWHERE H67.0 OTITIS MEDIA IN BACTERIAL DISEASES CLASSIFIED ELSEWHERE H67.1 OTITIS MEDIA IN VIRAL DISEASES CLASSIFIED ELSEWHERE H67.8 OTITIS MEDIA IN OTHER DISEASES CLASSIFIED ELSEWHERE J02 ACUTE PHARYNGITIS J02.0 STREPTOCOCCAL PHARYNGITIS J02.8 ACUTE PHARYNGITIS DUE TO OTHER SPECIFIED ORGANISMS J02.9 ACUTE PHARYNGITIS, UNSPECIFIED J03 ACUTE TONSILLITIS J03.0 STREPTOCOCCAL TONSILLITIS J03.8 ACUTE TONSILLITIS DUE TO OTHER SPECIFIED ORGANISMS J03.9 ACUTE TONSILLITIS, UNSPECIFIED J06 ACUTE UPPER RESPIRATORY INFECTIONS OF MULTIPLE AND UNSPECIFIED SITES J06.0 ACUTE LARYNGOPHARYNGITIS J06.8 OTHER ACUTE UPPER RESPIRATORY INFECTIONS OF MULTIPLE SITES J06.9 ACUTE UPPER RESPIRATORY 137 INFECTION, UNSPECIFIED J31.2 CHRONIC PHARYNGITIS GASTROENTERITIS & DEHYDRATION 558.9 OTHER AND UNSPECIFIED NONINFECTIOUS GASTROENTERITIS AND COLITIS 276.5 VOLUME DEPLETION 276.50 VOLUME DEPLETION, UNSPECIFIED 276.51 DEHYDRATION 276.52 HYPOVOLEMIA K52.2 ALLERGIC AND DIETETIC GASTROENTERITIS AND COLITIS K52.8 OTHER SPECIFIED NONINFECTIVE GASTROENTERITIS AND COLITIS K52.9 NONINFECTrVE GASTROENTERITIS AND COLITIS, UNSPECIFIED E86 VOLUME DEPLETION E86.0 DEHYDRATION E86.8 OTHER VOLUME DEPLETION 138 Appendix B: APP and FFS Communities, and Flags Alternative Payment Plan (APP) Communities Postal Codes Flag McBride VOJ 2E0 APP Dunster VOJ 1J0 APP Fraser Lake VOJ ISO APP Valemount VOE 2Z0 APP Robson VOG 1X0 APP Haida Gwaii (Queen Charlotte) VOT ISO, VOT 1S1; APP Sandspit VOT 1T0 APP Stewart VOT 1W0 APP Fee for Service (FFS) Communities Postal Codes Flag Prince Rupert V8J0A1-V8J4S4 FFS Tumbler Ridge VOC 2W0 FFS Smithers VOJ 2N0 - VOJ 2N7 FFS Telkwa VOJ 2X0 - VOJ 2X3 FFS 3. Other Flag Postal Codes NOT listed above N/A Appendix C: Ethics Approval from the UNBC Research Ethics Board UNIVERSITY OF NORTHERN BRITISH COLUMBIA RESEARCH ETHICS BOARD MLMOHANDUW To tjk*'f'l" f -wi From Mi'tr / H.irlfir r t..i• i'r , i*."^ ,:,itJt*,' *-0 -p Mi .• i' ••• i t .1 Ar*>: ii!,tt •> ^ (it- - • n . t i . - ,..Jjft at "4 'f v .i:«. w p\,Pv!"-»i' "• """• '""•'-' _v.i] i-'j^i s! t. *(>(• P i - , . .:( ' h t ' i • (>*H,"• H^.ii i 'i i JUCr'-'v'f"; ,'.'• t*•' : t «•>•">! t • 'r».ie witiur ...t ' .• '* •• tU)vt- u t i t * (1 >:<.J> " ^ ' i p e n c u it t ir sett , !t. f" '»>< t-«t(- . 1 ' h i ; , f t ' i i l i* • ! I u.i'l '. ' •' ,t '1*! ' h I* M'f .M I i"»u 't " «'•' t ' L * i.-.V ,i f i ! i f ' l / i . l i ' R F B iit»prOvrf A n v ; ' ! • ) " }•-.<• '" ' . " l f t v i i V f 1 • ' "*i I » 1*0> ' . "-,<,"\ ' V • ip.iut l,U .tUl ' ' ! . « ' ! t , ' h e P i - , i ,n * ("•fir-, B.,,r I tuV.I 4. (• /. f .• .' >-jt.v«!-