Episodes of Care: Background and Issues

1. Episodes of Care: Background and Issues James M Naessens, ScD Division of Health Care Policy & Research Mayo Clinic

2. Outline • Episodes of Care • Background • Approaches • Current Issues with Episodes • CMS • Health Affairs Sept/Oct 2009 • Mayo Clinic Studies • Referral Practice • Chronic Disease Cohorts

3. Episodes of Care • Concept first introduced in 1960’s by Solon J, et al.^ • Advanced by Hornbrook M, et al.* “series of temporally contiguous health care services related to treatment of a given spell of illness or provided in response to a specific request by the patient” ^ American Journal of Public Health. 1967;57:401-408 * Med Care Rev. 1985;42:163-218

4. Episode of Care Uses • Provide measurement and treatment guidelines for physicians • Define boundaries of reimbursement • Determine risk adjustment • For health care utilization analysis • Operational aspects of health care delivery (Mayo Clinic medical record management)

5. Episode of Care Current Basis for Payment Projects • Geisinger - Cardiac Surgery “guarantee” • Medicare Acute Care Demonstration Project – bundling for ortho and CV procedures • Medicare Physician Hospital Collaboration demonstration – immediate post hospital period

6. Our ProblemOutpatient Care Analysis • Capitated model / primary care • Patient • Fee for service model • Encounter • Service • Referral care • Episode (??)

7. Billing Data (Input into MEG)

8. Example: one patient’s visits for one month Episode 1 Episode 3 Episode 2 Episode 1 Episode 3 Episode 2 Episode 1 Episode 1 Colored days represent days the patient was received services.

9. Episode Groupers • Rosen and Mayer-Oakes* compared four major episode grouper programs: • Episode Treatment Groups (ETG) • Clinical Episode Groups (CEG) • Physician Review System • CareTrend With no distinctly superior product *Jt Comm J Qual Improv. 1999;25:111-28

10. Episode Groupers:Methodological Issues • Starting Point (diagnosis, symptom or visit) • End Point (defined length or “clean period”) • Comprehensiveness of Services (concurrent episodes?) • Clinical Complexity (chronic disease with flare-ups, unrelated acute illness, multiple comorbidities) • Provider Attribution

11. CMS Episode Grouper Listening Session November 10, 2009 • CMS intends on using input to write RFP on developing a transparent software for episodes of care for Medicare beneficiaries • Multiple Chronic Conditions • Post-acute Care • Length of Chronic Episode • Physician Services • Risk Adjustment

12. Health Affairs Sept/Oct 2009 issue • Episode-Based Performance Measurement And Payment: Making It A RealityPeter S. Hussey et al. • From Volume To Value: Better Ways To Pay For Health CareHarold D. Miller • Measurement Of And Reward For Efficiency In California’s Pay-For-Performance ProgramJames C. Robinson et al.

13. Hussey article • Applies ETGs and MEGs to Medicare part A & B data for 3 states, 2004-6. • Identifies Issues with: • Defining Episodes • Different settings • Single- vs. multi-condition focus • Within group heterogeneity • Attributing responsibility • Calls for more empirical work

14. Miller article • Suggests that each of 4 methods: FFS, Episodes, Capitation, Comprehensive care payments (condition-adjusted capitation) has role • Issues to address: • Bundling challenges • Setting payment amounts • Assuring quality • Aligning incentives

15. Robinson article • Reviews the California Integrated Healthcare Association Pay for Performance experience addressing efficiency using episodes (MEG) • Issues: • Small numbers of patients/episode • Incomplete data • Weights (standard or actual costs)

16. Mayo Cardiovascular Referral Practice Study Goals • Do Medstat’s Episodes provide a useful management tool to help understand a multi-specialty group practice? • Can we use MEG as a basis to understand different use patterns between rural and urban patients?

17. Methods Patients • All patients seen in 2003 • For outpatient service • By a cardiovascular provider • N=102,406 Setting • Mayo Clinic, Rochester, Minnesota

18. Primary care vs. referral Mayo Health System Local vs. regional vs. national Comparisons of Interest

19. Episode Outcomes • Cardiovascular intensity • Low Diagnostic • Cardiovascular E & M • High Diagnostic • Therapy Procedures • Hospitalization • Cost

20. Statistical Methodology • Outcome models • Do the types of episodes differ? • Are the outcomes (average cost, hospitalization, and cardiovascular intensity) different between rural vs. urban patient after incorporating episode type, severity of episode and comorbidity?

21. Statistical Methodology • Logistic and linear regression models developed to account for impacts of Mayo primary care, distance traveled, age, gender, pay source, and physician vs. self-referred. • Impact of rural-urban influence added to adjusted model.

22. Summary Findings • 96,601 patients with CV provided service in 2003 • 287,162 outpatient CV visits and 29,369 hospitalizations in 464,067 episodes (90,922 CV episodes)

23. Most Frequent Episodes with Cardiologist E & M Visit

24. Episodes withCardiologist E & M Visit • 14 conditions had 1000+ episodes • 22 conditions had 500 - 999 episodes • 74 conditions had 100 - 499 episodes • 62 conditions had 50 - 99 episodes • 450 conditions had episodes

25. Influence of Distance and Primary Care

26. Cardiovascular IntensityEpisodes with CV E & M

27. Cardiovascular IntensityEpisodes with CV E & M

28. Mean Charge per Episode

29. SummaryEpisodes in Specialty Practice • Episodes of care were able to categorize both primary care and referral patients. • However, after adjustment mean costs per episode differed significantly between the two groups for many types of episodes. • Episodes developed for managed care practices may have limited utility for referral specialty practices. • Further assessment needed on the differences between primary care and referral practice episodes.

30. Mayo Chronic Disease Cohort Study Goal • How well do various systems capture and characterize the health care costs of people with chronic disease?

31. Methods Patients • Mayo employees/dependents with continuous health benefit enrollment from 2003-2006 • Cohort 1: Meet HEDIS definitions for diabetes in 2000-2003 • Cohort 2: Meet HEDIS definitions for CAD in 2000-2003 Data Source • Medical and Pharmacy Claims

32. Methods • Generate Total Costs for 2003-2006 • Apply Prometheus Models to Cohort • Apply ETGs to Cohort • WORK IN PROGRESS!

33. Diabetes Cohort 92% 96% 96% 21%

34. CAD Cohort 60% 69% 16%

35. SummaryEpisodes in Chronic Disease Cohorts • Different schemes identify different patients in disease cohorts. • ETGs and Prometheus capture only a portion of costs of Diabetes and CAD cohorts. • ETG hierarchy influences what they consider as disease-related costs.