1. Barbara Starfield: “ how health systems impact health” Wordle of 305 article titles

2. http://www.acg.jhsph.org/index.php?o ption=com_content&view=article&id= 179&Itemid=393eo link

3. How Information Can Improve Equity and Efficiency in the Delivery of Primary Health Care Karen Kinder, PHD, MBA AAFP Family Medicine Global Workshop San Diego, California October 13, 2011

4. Technologies for Primary Care Primary care assessment - PCATs Morbidity burden: assess and manage ACG System Problem recognition/follow-up (outcomes), including adverse effects - ICPCs

5. EMR (DATABASE WAREHOUSE) ANALYTICAL TOOLS REPORT GENERATORS INTERVENTION PROGRAMS FEEDBACK LOOP IMPROVED POPULATION HEALTH STATUS Information is key to improving health

6. Primary health care is primary care applied on a population level. As a population strategy, it requires the commitment of governments to develop a population-oriented set of primary care services in the context of other levels and types of services.

7. Why Is Primary Care Important? Better health outcomes Lower costs Greater equity in health

8. Relationship between Strength of Primary Care and Combined Outcomes USA GER BEL AUS SWE SP CAN FIN UK NTH DK *1=best 11=worst

9. Average Rankings for World Health Organization Health Indicators for Countries Grouped by Primary Care Orientation DALE: Disability adjusted life expectancy (life lived in good health) Child survival: survival to age 2, with a disparities component Overall health: DALE minus DALE in absence of a health system Maximum DALE for health expenditures minus same in absence of a health system Source: Calculated from WHO, World Health Report 2000. DALEs Child Survival Equity Overall Health Worse primary care (Belgium, France, Germany, US) 16.322.536.3 Better primary care (Australia, Canada, Sweden, Japan, Denmark, Finland, Netherlands, Spain, UK) 11.015.829.1

10. In 7 African countries The highest 1/5 of the population receives well over twice as much financial benefit from overall government health spending (30% vs 12%). For primary care, the poor/rich benefit ratio is much lower (23% vs 15%). “From an equity perspective, the move toward primary care represents a clear step in the right direction.” Source: Gwatkin, Int J Epidemiol 2001; 30:720-3, based on Castro-Leal et al, Bull World Health Organ 2000; 78:66-74.

11. Studies in other developing and middle income countries also show benefit from primary care reform. In Bolivia, reform in deprived areas lowered under-5 mortality rates compared with comparison areas. In Costa Rica, primary care reforms in the 1990s decreased infant mortality and increased life expectancy to rates comparable to those in industrialized countries. In Mexico, improvements in primary care practices reduced child mortality in socially deprived areas. Sources: Perry et al, Health Policy Plann 1998; 13:140-51; Reyes et al, Health Policy Plann 1997; 12:214-23; Rosero-Bixby, Rev Panam Salud Publica 2004; 15:94-103; Rosero-Bixby, Soc Sci Med 2004; 58:1271-84.

12. Primary Care Oriented Countries Have Fewer low birth weight infants Lower infant mortality, especially postneonatal Fewer years of life lost due to suicide Fewer years of life lost due to “all except external” causes Higher life expectancy at all ages except at age 80 BETTER HEALTH AT LOWER COSTS Sources: Starfield. Primary Care: Balancing Health Needs, Services, and Technology. Oxford U. Press, 1998. Starfield & Shi, Health Policy 2002; 60:201-18.

13. Primary Care Oriented Countries Have more equitable resource distributions health insurance or services that are provided by the government little or no private health insurance no or low co-payments for health services Are rated as better by their populations primary care that includes a wider range of services and is family oriented Sources: Starfield. Primary Care: Balancing Health Needs, Services, and Technology. Oxford U. Press, 1998. Starfield & Shi, Health Policy 2002; 60:201-18.

14. In the United States, half of all outpatient visits to specialist physicians are for the purpose of routine follow-up. Does this seem like a prudent use of expensive resources, when primary care physicians could and should be responsible for ongoing patient-focused care over time? Source: Valderas et al, Ann Fam Med 2009;7:104-11. Specialists vs. Primary Care Providers

15. In New Zealand, Australia, and the US, an average of 1.4 problems (excluding visits for prevention) were managed in each visit. However, primary care physicians in the US managed a narrower range: 46 problems accounted for 75% of problems managed in primary care, as compared with 52 in Australia and 57 in New Zealand. Source: Bindman et al, BMJ 2007; 334:1261-6.

16. The Primary Care Assessment Tools (PCATs)* *©Johns Hopkins University

17. Primary care is the provision of first contact, person-focused ongoing care over time that meets the health-related needs of people, referring only those too uncommon to maintain competence, and coordinates care when people receive services at other levels of care.

18. Evaluating the Delivery of Primary Care Professionals knowledgeable about the health system People in communities Patients, professionals, and administrators of health care facilities An existing suite of instruments makes it possible to evaluate the primary care orientation of health systems and facilities. It includes surveys of: It is known as the PCAT (Primary Care Assessment Tool). The PCAT is used to assess the achievement of primary care

19. History of the PCAT The impetus for the development of the primary care assessment tools began in the early 1990s, when the need for health systems oriented around primary (health) care began to be recognized. The first widespread attention to assessment of primary care came with the conduct and publication of the international comparisons of primary care.

20. This international comparison initially selected 10 industrialized countries with populations of at least 4 million and data from the mid 1980s, later expanding the number to 13, with data from the early to mid 1990s. Health statistics were obtained from reputable international sources, and information was obtained from country experts regarding health system characteristics. Clear definitions for each health system characteristic were provided. Sources: Starfield, Lancet 1994;344:1129-33. Starfield & Simpson, JAMA 1993;269:3136-9.

21. Each country was rated (scores of 0, 1, or 2) on the strength of 9 characteristics of health policy that are conducive to strong primary care. Primary Care Orientation of Health Systems: Rating Criteria

22. UK NTH SP FIN CAN AUS SWE JAP GER FR BEL US DK *Best level of health indicator is ranked 1; worst is ranked 13; thus, lower average ranks indicate better performance. Based on data in Starfield & Shi, Health Policy 2002; 60:201-18. System (PHC) and Practice (PC) Characteristics Facilitating Primary Care, Early-Mid 1990s

23. At the same time the international comparisons were being carried out, efforts were initiated to develop a tool that could be used to assess the clinical aspects of primary care. This set of tools because known as the PCAT – Primary Care Assessment Tools. These tools were initially tested for reliability and validity in the United States. Within a decade, they had also been tested in Spain and in Canada.

24. Utility of the PCATs To compare one type of facility with another To compare one type of practitioner with another To compare one country or region with another To detect particular functions that appear to be suboptimal, and explore why

25. PCAT Versions Primary Health Care Systems Assessment Primary Care Adult consumer long/short Child consumer long/short Facility long/short Provider long/short

26. Primary Care Orientation of Health Systems - Domains – First-contact –Person-focus over time –Comprehensiveness –Coordination –Family-centeredness –Community orientation – Cultural competence Source: Starfield. Primary Care: Balancing Health Needs, Services, and Technology. Oxford U. Press, 1998.

27. The Primary Care Assessment Tool  Systems Version This tool assesses the primary health care and primary care characteristics at the system level. It addresses all of the primary care functions. It is being considered for widespread use in comparing the primary care orientation of different health systems, both within and across countries.

28. Domains of the Systems PCAT Equity in distribution of resources Universality of financing Role of government in policy regarding quality, comprehensiveness, and payment for services

29. How Are the Features of Primary Care Actually Measured? Principle: Each domain of primary (health) care has two subdomains, one related to important characteristics of the facility or practice and one related to the performance of the practitioner or facility on primary care functions.

30. Primary Care Domains and Subdomains: First Contact First-contact: accessibility Health system characteristics that facilitate access; e.g., if closed on weekend days would the individual be seen by a practitioner from the facility? First-contact: utilization (consumer only) Use of primary care place for each new need (regular checkup, immunization, an acute illness.)

31. Primary Care Domains and Subdomains: Longitudinality Longitudinality: strength of affiliation (consumer only) Strength of relationship with a specific provider, e.g., degree to which the identified provider is also the place who knows the individual best and from whom care would be sought for a new problem. Longitudinality: interpersonal relationship Person orientation of practitioner/patient interactions, e.g., degree of interest of doctor in the individual as a person, rather than as someone with a medical problem.

32. Primary Care Domains: Comprehensiveness Comprehensiveness in primary care is necessary in order to avoid unnecessary referrals to specialists, especially in people with comorbidity

33. Primary Care Domains and Subdomains: Comprehensiveness Comprehensiveness: services available Availability of 11 specific services, e.g., family planning. Comprehensiveness: services provided Services received from the primary care source, e.g., discussions of ways to stay healthy.

34. Primary Care Domains and Subdomains: Coordination Coordination: medical record continuity (provider only) Do you use flow sheets to assure that needed services are provided? (Also, printed practice guidelines, periodic medical audits, problem lists, medication lists.) Coordination: integration of referrals Quality of primary care-referral interface, e.g., Did the primary care practitioner know you made a visit to a specialist?

35. Primary Care Domains and Subdomains: Family Centeredness Family-focused personnel Methods to record family needs Family representation in policy-making Family focus groups/meetings

36. Primary Care Domains and Subdomains: Community Orientation Knowledge of community characteristics Knowledge of primary care needs Methods to identify community needs Monitoring of service effectiveness

37. Primary Care Domains and Subdomains: Cultural Competence Provides care in native language/ dialect/ has translator/ provides language-appropriate educational materials Employs individuals from community as advocates Appreciates the impact of poverty on health and responsiveness to medical intervention

38. PCAT Languages English Spanish Catalan Portuguese French (Quebecois) Korean Turkish In progress: Mandarin, Maltese

39. Some of the countries in which the PCATs are being used or is planned for use (other than just for research), as of 2011: US (some patient-centered medical home demonstrations); Spain; Brazil; Korea; Turkey; Hong Kong and PRC; Uruguay; Vietnam; Malaysia; South Africa

40. Managing Co-morbidity in a Population

41. Co-morbidity is the concurrent existence of one or more unrelated conditions in an individual with any given condition. Multi-morbidity is the co-occurrence of biologically unrelated illnesses. For convenience and by common terminology, we use co-morbidity to represent both co- and multi- morbidity.

42. People and populations differ in their overall vulnerability and resistance to threats to health. Some have more than their share of illness, and some have less. Morbidity mix (sometimes called case-mix) describes this clustering of ill health in patients and populations.

43. Not all persons have the same need for health care Percent of Population Percent of Health Care Dollars Consumed 1%30% 10%70% 50%97%

44. Comorbidity Prevalence The percentage of Medicare beneficiaries with 5+ treated conditions increased from 31 to 40 to 50 in 1987, 1997, 2002. The percentage of those with 5+ treated conditions who reported being in excellent or good health increased from 10% to 30% between 1987 and 2002. MESSAGE: “Discretionary diagnoses” are increasing in prevalence, particularly those associated with new pharmaceuticals. How much of this is appropriate? Source: Thorpe & Howard, Health Aff 2006; 25:W378-W388.

45. Total morbidity is not the same as the sum of different diseases, because diseases cluster and are inter-related in various ways. A more accurate way of characterizing morbidity is to characterize the pattern of diseases in people and populations.

46. Source: Partnership for Solutions Co-morbidity is the norm among older adults

47. These patterns are linked to the prevalence of chronic co-morbidities (Data for Americans 65+) # Chronic Co-morbidities % Pop. Relative Cost (Per Pt.) Est. % of Total Medicare Costs Avg. # Unique MDs/Yr. Avg. # Filled Rx / Yr. 5+20%3.266%13.849 3-427%.923%7.326 0-253%.111%3.011 Data Source: G. Anderson et. al., Johns Hopkins Univ. 2003. (Derived from Medicare claims and beneficiary survey.)

48. Co-morbidity, Inpatient Hospitalization, Avoidable Events, and Costs* Starfield 10/03Source: Wolff et al, Arch Intern Med 2002; 162:2269-76. *ages 65+, chronic conditions only

49. The greater the morbidity burden, the greater the persistence of any given diagnosis. That is, with high comorbidity, even acute diseases are more likely to persist.

50. With high morbidity burden, the number of different physicians seen rises to a greater extent than is the case for number of visits, for both primary care and specialist care. Therefore, coordination of care is a major challenge for those with high morbidity burden.

51. Controlled for morbidity burden*: The more DIFFERENT generalists seen: higher total costs, medical costs, diagnostic tests and interventions. The more different generalists seen, the more DIFFERENT specialists seen among patients with high morbidity burdens. The effect is independent of the number of generalist visits. That is, the benefits of primary care are greatest for people with the greatest burden of illness. Source: Starfield et al, J Ambul Care Manage 2009;32:216-25. *Using the Johns Hopkins Adjusted Clinical Groups (ACGs)

52. Importance of Co-morbidity Disease case management Guideline relevance Costs and complications Orientation of health systems –Primary care vs specialty care –Appropriate use of specialty services Quality of care: processes vs. outcomes Starfield 10/03

53. Clinical Observations Underpin the ACG System Morbidity is NOT randomly distributed across individuals. –1) Morbidity “clusters”. –2) Diagnoses co-occur. The “illness burden” of providers’ practices is NOT randomly distributed. –1) Some providers care for “sicker” patients. –2) Sick patients choose certain providers referentially.

54. The ACG System: Concept and Method

55. Case Mix Case mix ( risk adjustment ) is the process by which the health status (morbidity profile) of a population is taken into consideration when setting budgets or capitation rates, evaluating provider performance, or assessing outcomes of care.

56. What Can Be Achieved with Case Mix Adjustment Equity and fairness To identify those patients most in need of health care resources To facilitate providers who specialize in treating patients with higher than average illness burden. Create incentives to encourage providers to match services to needs (appropriateness) Ensure appropriate comparisons for research and performance assessment

57. History of ACGs The ACG System grew out of clinical observations made by Barbara Starfield, MD, MPH, in pediatric populations. Research by Dr. Starfield and her colleagues in the early 1980s showed that children using the most health care resources were not those with a single chronic illness, but rather children with multiple, seemingly unrelated conditions. Dr. Starfield was able to extend these findings to all patients and ultimately demonstrate that the clustering of morbidity is a better predictor of health services resource use than the presence of specific diseases.

58. Conceptual Basis for ACGs Individual diagnoses are less important in the care of patients and populations than are patterns and overall burdens of morbidity Models of care need to be based on overall morbidity burdens rather than on specific diagnoses Assessing the appropriateness of care needs to be based on patterns of morbidity rather than on specific diagnoses

59. Overview of the ACG System

60. Overview of Johns Hopkins ACG System TOTAL POPULATION – Not just those who have been in hospital and includes non-users. TOTAL EXPERIENCE - Applied using all diagnoses describing the person. They do not focus on individual visits. Ideally they are derived from primary and specialty ambulatory contacts as well as inpatient. TOTAL PERSON -Comprehensive measure of a population’s risk and morbidity burden. They do not just categorize organ system-based diseases.

61. Visit 1 Treated Morbidities Code A Diagnostic Codes ADG10 Morbidity Groups ACG Category ACG Category Clinical Grouping Data Analysis Clinician Judgment ACG Actuarial Cells Reflect the Constellation Of Health Problems Experienced by a Patient Time Period (e.g., 1 year) Visit 2 Visit 3 Code B Code C Code D ADG21 ADG03

62. What is an ADG? Definition: An ADG is a morbidity cluster that indicates severity and persistence of a patient’s condition treated over time. Diagnoses within the same ADG are similar in terms of clinical criteria and expected need for health care resources. ADGs are not mutually exclusive.

63. Criteria Used to Assign Diseases/Conditions Into ADGs : Duration Acute, chronic or recurrent Severity Minor/stable versus major/unstable Diagnostic certainty Symptoms versus disease Etiology Infectious, injury or other Specialty care involvement

64. Assignment of ICD* Codes to ADGs: Diabetes Mellitus ICD-9 CodeDescriptionADG 250.0Diabetes Mellitus Uncomplicated10: Chronic Medical Stable 250.03Diabetes Mellitus without complications 11: Chronic Medical Unstable 250.1Diabetes with Ketoacidosis09: Likely to Recur, Progressive 362.0Diabetes Retinopathy18: Chronic Specialty, Unstable- Eye * ICD – WHO’s international classification of disease. Can also be use with Read codes and ICPC codes

65. ADGs and Health Care Needs Evidence from BC Percent

66. Visit 1 Treated Morbidities Code A Diagnostic Codes ADG10 Morbidity Groups ACG Category ACG Category Clinical Grouping Data Analysis Clinician Judgment ACG Actuarial Cells Reflect the Constellation Of Health Problems Experienced by a Patient Time Period (e.g., 1 year) Visit 2 Visit 3 Code B Code C Code D ADG21 ADG03

67. Examples of ACG Categories ACGDescription 0200 Acute Minor, Age 2-5 0600 Likely to Recur, without Allergies 1722 Pregnancy: 2-3 ADGs, no major ADGs, not delivered 2800 Acute Major and Likely to Recur 4430 4-5 other ADG combinations, Age > 44, 2+ major ADGs 5322 Infants: 0-5 ADGs, 1+ major ADGs, low birth weight

68. Expanded Diagnosis Clusters (EDCs) EDCs categorize different diseases and conditions Based only on ICD codes (no procedure codes) EDCs complement ACGs by serving as a surrogate for chronic condition episodes. Provides a greater clinical context to the case-mix Useful for examining the epidemiology of a population or comparing two populations Can help identify patients for inclusion in DMPs

69. 27 Major EDCs Administrative Allergy Cardiovascular Dental Ear, Nose, Throat Endocrine Eye Female Reproductive Gastrointestinal/Hepatic General Signs and Symptoms General Surgery Genetic Genito-urinary Hematologic Infections Malignancies Musculoskeletal Neonatal Neurologic Nutrition Psychosocial Reconstructive Renal Respiratory Rheumatologic Skin Toxic Effects and Adverse Events

70. Example: The Cardiovascular EDCs CAR01 Cardio Signs & Symptoms CAR03 Ischemic Heart Disease CAR04 Congenital Heart Disease CAR05 Congestive Heart Failure CAR06 Cardiac Valve Disorders CAR07 Cardio-myopathy CAR08 Heart Murmur CAR09 Cardiac Arrhythmia CAR10 Generalized Atherosclerosis CAR11 Disorder of Lipoid Metabolism CAR12 Acute Myocardial Infarction CAR13 Cardiac Arrest/Shock CAR14 Hypertension w/o Major Comp CAR15 Hypertension w/ Major Comp

71. Assignment of ICD Codes to EDCs: Diabetes Mellitus ICD-9 CodeDescriptionADGEDC 250.0 Diabetes Mellitus Uncomplicated 10: Chronic Medical Stable END06: Type 2 diabetes, w/o complication 250.03 Diabetes Mellitus without complications, uncontrolled 11: Chronic Medical Unstable END08: Type 1 diabetes, w/o complication 250.1 Diabetes with Ketoacidosis 09: Likely to Recur, Progressive END07: Type 2 diabetes, with complication 648.0Gestational Diabetes 11: Chronic Medical Unstable FRE04: Pregnancy and Delivery with Complications 362.0 Diabetes Retinopathy 18: Chronic Specialty, Unstable-Eye EYE13: Diabetic Retinopathy

72. How are EDCs Used? EDCs are used primarily for looking at disease prevalence and Standardized Morbidity Ratios (SMRs) -- which tell us, is the prevalence of the sub-group of analyses different than the overall population from which the sub-group was drawn. EDCs are also used to demonstrate variability of risk within disease category

73. Co-Morbidity Adjusted Costs By Disease Category Disease Group (Based on EDCs) Distribution by “RUB” Morbidity Level Group Relative Cost of those in each RUB Group LowMidHighLowMidHigh Total Population 49.027.54.00.331.649.80 Asthma 24.063.812.20.441.7610.05 Hypertension 20.765.413.90.341.8511.60 Ischemic Heart Dis. 3.949.047.10.582.2012.19 CHF 2.635.162.30.582.3316.47 Diabetes 13.963.222.90.391.9211.75 Osteoporosis 11.150.038.90.332.2712.43 Thrombophlebitis 12.253.833.90.452.1513.68 Depression 8.166.325.6.0422.2013.14

74. ACG Predictive Models

75. The ACG Predictive Models Predictive modeling is a process that applies available data to: Identify persons who have high medical need and are “at risk” for above average future medical service utilization and therefore could benefit from case management programs Predicts future resource use of patient groups within a population

76. Prior High Cost Year-1 (Prior Use) Predicted High Risk Year-2 (Using Year-1 Data) Actual High Cost Year-2 Not High Risk High Risk, Current Costs Low, Future Costs High High Risk, Current Costs Low, Future Costs High Value of Predictive Modeling Population of Persons Enrolled Across Two Year Period

77. Risk Factors in the Johns Hopkins Predictive Model Risk Score Overall Disease Burden (ICD-10  ACG) Age Gender Selected Resource Use Measures ($) Selected Medical Conditions (ICD-10  Expanded Dx Clusters) Special Population Markers (ICD-10  HOSDOM, Frailty) Medications (ATC Codes  Rx-MG)

78. The Johns Hopkins ACG System: An Expanding Suite of Measures and Tools Dx-PM – a “predictive model” that uses diagnoses to calculate a score representing future risk. Based on ACGs, EDCs and special high risk markers. Rx-PM - a predictive model that calculates a score representing future risk and expected resources use based only on pharmacy use history. DxRx-PM - The Rx-PM and Dx-PM measures can be combined if both sources are available to calculate a predictive score.

79. ACG Pharmacy Model

80. Combining both diagnoses and prescription data provides expanded information Condition Total # of patients identified (ICD or pharm.) Percent of patients identified by diagnosis Percent of patients uniquely identified pharmacy Hypertension59,93770%30% Disorders of Lipoid metabolism37,73661%39% Congestive Heart Failure11,22361%39% Chronic Renal Failure164681%19% Depression and Anxiety20,86323%77% Diabetes27,65655%45% Source: US HMO claims dataset of elderly n=90,000 in 2001;

81. Why Look at Pharmacy Data? Pharmacy data capture a unique constellation of clinical information Expediency -- Pharmacy-based claims are usually processed within 24 hours while office or hospital claims can takes several months for adjudication Provides an alternative data source when claims are NOT available

82. Clinical Criteria for Rx-MG Assignment 1)Morbidity-type - symptom v disease 2)Duration of morbidity - chronic v time-limited 3)Stability of morbidity - stable v unstable 4)Route of administration - oral, inhaled, topical, intramuscular, intravenous 5)Therapeutic goal - curative, palliative, preventive

83. The Major Rx-MG Categories Allergy/Immunology Cardiovascular Ears, Nose, Throat Endocrine Eye Female Reproductive Gastrointestinal/Hepatic General Signs & Symptoms Genito-urinary Hematologic Infections Malignancies Musculoskeletal Neurologic Psychosocial Respiratory Skin Toxic Effects/ Adverse Reactions Others / non-specific medications

84. Rx-MG Example: Corticosteroids Active Ingredient Route of Administration Rx-MGDescription methylprednisolone-neomycintopicalSKNx020Skin / Acute and Recurrent PrednisolonecompoundingALLx030Allergy/Immunology / Immune Disorders PrednisoloneinjectableMUSx020Musculoskeletal / Inflammatory Conditions PrednisoloneoralALLx030Allergy/Immunology / Chronic Inflammatory PrednisoloneophthalmicEYEx020Eye / Acute Minor: Palliative Prednisolone-sodium sulfacetamideophthalmicEYEx010Eye / Acute Minor: Curative BeclomethasoneCompoundingRESx030Respiratory / Cystic Fibrosis DexamethasoneNasalALLx010Allergy/Immunology / Acute Minor BetamethasoneInjectableENDx020Endocrine / Chronic medical DexamethasoneCompoundingALLx030Allergy/Immunology / Chronic Inflammatory ciprofloxacin-dexamethasone oticOticEARx010Ears, Nose, Throat / Acute Minor DexamethasoneIntravenousMUSx020Musculoskeletal / Inflammatory Conditions beclomethasoneinhalationRESx040Respiratory / Airway Hyperactivity betamethasone-calcipotriene topicaltopicalSKNx030Skin / Chronic Medical

85. Applications

86. Possible Applications Population based need-assessment across patient populations (e.g.,regions, vulnerable patient groups) Assessing performance of providers (e.g. hospital clinics, doctors, regions). Resource allocation / budgeting across clinics, regions or other care units. “Predictive Risk” measurement to assist in chronic care management. Quality improvement comparisons.

87. Population Profiling

88. Benefits of Health Status Monitoring Understanding population risk and overall morbidity patterns Detection of life style issues that may lead to health problems Ability to identify changes in population health Tailoring of health promotion and education programs

89. Types of Morbidity Varies by Region

90. Capitation, Budgeting & Other Financial Issues

91. Size of the Healthcare Pie Determining the Healthcare Budget Involves a Variety of Factors - Available Budget - Political Forces - Actuarial Forecasts

92. Risk Adjustment Can Be Used To Slice The Pie Risk Adjustment

93. Plans differ in the morbidity burden of their patients Average Risk Using ACGs, risk ratios were determined for each contracting managed care organization / health plan. Expected values were determined separately for the two enrollee groups with this State Medicaid program.

94. Alternative Ways to Apply Case-Mix to Payment Applied concurrently, budgets are adjusted retrospectively based on the experienced morbidity profile of the population. Applied prospectively, capitation amounts are adjusted based on the anticipated need for health care resources. The portion of the payment which is case-mix adjusted is arbitrary.

95. Risk Adjusted Performance Profiling

96. Interpreting Profiling Results… Potential Access Issues / Witholding Services Performance Feedback / Contracting / Incentives Over Utilization / Potential Fraud/Abuse

97. Pharmacy cost x patient: observed ( ) and expected ( ) Overcostundercost Overcost or undercost, related to standard 1,070,970,87 1,140,981,271,020,81 Efficiency Index 0,79 Impact (€) 510.658 280.254481.278 715.386121.540736.869144.487281.209 943.068 0 50 100 150 200 250 300 350 400 Mean Cost (€) 182,58291,57274,75212,19337,71289,03328,99287,14196,36270,49 Mean cost (€) expected 231,02271,59293,94243,63296,59295,57258,10280,21241,01270,49 001002003004005006007008009Average Clinic Profiling Efficiency Index: 0,79 21% undercost 943.000 € Efficiency Index: 1,27 27% overcost 737.000 €

98. Using ACGs to Risk-Adjust Performance “Profiles” of Provider Groups GroupPMPM $Unadjusted Relative Cost ACG “Illness Burden” ACG Adjusted Efficiency Ratio #1$1571.221.021.20 #21531.191.210.99 #31441.120.921.22 #4980.760.691.11 All*$1291.00

99. Risk Adjusted Practice Efficiency of Doctor Group #3 By Service Category Type of ServiceRelative Cost ACG Illness Burden Efficiency Inpatient0.910.901.01 Primary Care1.201.151.04 Surgery2.230.912.45 Medical Specialties1.610.921.75 Lab & x-ray1.770.852.08 Pharmacy.860.851.01 Total1.120.921.22

100. How Profiling Results are Typically Applied Developing financial incentives –Distributing bonuses –Defining tiered networks –Differentiating fee schedules Profiling/Assessment tool –To stimulate voluntary changes in behavior by sharing valid data presented in a useful format. –To identify potential fraud & abuse. Can be developed on a number of entities, to include: physicians, employers, networks, or health systems

101. Care Management & Predictive Modeling

102. Using PM Risk Scores to Target Disease Management Program Participants % Enrollees in Rx-MG Risk Category Resource Use of Cohort Relative to Total Population Condition Below 90% 90-95% Above 95% Below 90% 90-95% Above 95% Diabetes 44.9742.111.91.344.907.44 Congestive Heart Failure 19.7553.526.751.146.027.93 Tier 1 Tier 2 Tier 3

103. The ACG Software provides patient risk information in support of nurse case managers Numerous co-morbidities Seeing 13 doctors At risk for future hospitalization ER Visit with no admission Poly-pharmacy use Tobacco Use

104. Benefits of PM for Care Management Provides robust clinical information –Diagnosis-based condition markers –Pharmacy-based morbidity markers Administratively efficient –Rapid assessment –Reductions in case finding and case preparation –Allows for better allocation of scarce case management resources Identifies up to 25% unique individuals for case management compared to traditional methods –Using pharmacy, this holds true with as little as 1 month of data

105. Real World Experiences

106. Interest in case mix is increasing globally Population health care needs are rising, resource availability is not; focusing on “higher risk” patients makes sense. Data systems and data collection are improving. Management systems are integrating primary, secondary, and community care. There is an increased interest in the equitable delivery of health care.

107. ACG System’s International Presence Several Provinces in Canada Numerous County Councils in Sweden Several Regions of Spain Multiple Primary Care Trusts in the UK Sickness Funds in Germany The largest Health Plan in Israel Two Medical Schemes in South Africa The veterans medical system in Taiwan The Ministry of Health in Malaysia Active piloting in Turkey, Denmark, Hong Kong and Chile Research in Lithuania, Belgium, Korea, Thailand, the PRC and Japan Interest expressed in numerous other countries, including the Middle Eastern Region

108. Success Stories

109. ACGs around the Globe : Concurrent R-squared CountryDependent Variables Key independent variables in model Age, gend er Age, gend er, ADGs ACGs alone United States Total Costs (including pharmacy)0.130.550.37 Canada - ManitobaAmbulatory costs0.080.500.43 TaiwanPhysician Costs0.120.520.47 Dr. Visits0.060.580.53 SwedenPrimary care costs0.11NA0.38 Spain GP visits0.130.590.53 United Kingdom GP visits 0.54

110. ACG System is Customizable Recent Developments enable customizability for Local Diagnostic coding systems Local Pharmaceutical coding systems Incorporation of local resource measures (costing measures) Local Practice Behaviour Patterns Incorporation of available data on socio- economic measures, individual’s functionality, living arrangement, and other non-morbidity based markers Language

111. In Summary

112. Comprehensive measure of risk and morbidity burden. They do not just categorize organ system-based diseases. Roots were primary care / population based. ACGs are applied using all diagnoses (and/or pharmacy information) describing the person. They do not focus on individual visits. Ideally they are derived from primary and specialty ambulatory contacts as well as inpatient Based at internationally respected academic institution provides for stability, transparency, as well as ongoing support and development. We have been doing this for 30 years. Johns Hopkins has been developing collaborative IT / consulting and academic support infrastructure around the globe and currently have projects in 17 countries. The Johns Hopkins ACG System

113. Case Mix is critical to ensuring the equitable delivery of health care, promoting the continuity of care and enabling the targeting of limited resources.

114. We have instruments to assess the utility of health systems, the strength of primary care, and the outcomes as measured by morbidity burden. We need the political will to use them. In Closing…….

115. For More Information PCATs – www.jhsph.edu/pcpc/pca_tools.html ACG System – www.acg.jhsph.edu Dr. Karen Kinder – kkinder@jhsph.edu Starfield 10/03