Predictive Modeling in the Context of Healthcare Reform: Issues and Opportunities Jonathan P. Weiner, DrPH

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Predictive Modeling in the Context of Healthcare Reform: Issues and Opportunities Jonathan P. Weiner, DrPH Professor of Health Policy & Management and of Health Informatics and Executive Director of the ACG R&D Team The Johns Hopkins University, jweiner@jhsph.edu, 410 955-5661 The 3 rd Predictive Modeling Summit, Washington DC, 9/14/09

The Goals of this Session To describe the likely contours of US healthcare reform and the potential intersections with the predictive modeling (PM) / risk adjustment (RA) domains. To suggest how PM / RA could (and should) play key roles within the various streams of reform. To explore potential implications of health care reform for the PM / RA fields. To identify possible future issues and challenges facing the field. 2

Some Frames of Reference As of September 2009, healthcare reform may take various alternative directions. The intersection matrix between all facets of reform and PM/RA is huge. Of necessity I will need to focus on a subset of key issues. This talk will be relevant to all PM / RA approaches, but I will present a few examples based on the Johns Hopkins ACG suite of tools. 3

Working Definitions Case mix / risk adjustment is the process by which the health status of a population is taken into consideration when setting budgets or capitation rates, evaluating provider performance, or assessing outcomes of care. Predictive risk modeling is the prospective (or concurrent) application of risk adjustment measures and statistical forecasting to identify individuals with high medical need who would likely benefit from care management interventions. 4

Underlying Goals of US Healthcare Reform Cover the Uninsured Contain Costs ( Bending the Curve ) Improve Quality / Equity Digitize & Modernize These four goals often intersect 5

What might be included in a US healthcare reform package? 6

Health Reform Contours -1: The Uninsured Medicaid / SCHIP Expansion Health insurance exchanges (for individuals and small groups) Private insurance reform (e.g., limits on medical underwriting) Paying for insurance Subsidies for lower income families Employer pay or play? Individual consumer mandates? Tax increases (e.g. Cadillac plan tax and tax on wealthy) A public option government plan (or cooperatives )? Facilitating state level reform 7

Why risk adjustment is key for any financial exchange between government and health plans Distribution of Expenditures for US Medicare Enrollees (65+) % of Enrollees % of Medical Costs (FFS) (MCO) % of Rx Costs for M+A (MCOs) 2% 24% 32% 11% 10% 60% 68% 36% 50% 96% 97% 91% Sources of Data: FFS - CMS 5% file. MCO- sample of 180,000 enrollees from several Medicare Advantage plans. 8

Morbidity burdens of uninsured likely to be different from insured 6-9 Morbidity Types* * JHU/ADGs 10+ Morbidity- Types Commerical Plan Comm. Hlth Center Source: Dr Barbara Starfield JHU 0 5 10 15 20 25 30 % of Total Population 9

Health Reform Contours - 2: Cost Containment Decreasing Medicare inflation Medicare Advantage capitation cuts Decreasing payments to FFS providers Giving MedPac advisory committee real teeth Value Based coverage (paying for what works)? Payment reforms (as demo projects?) Pay for performance (P4P) Move from FFS towards various bundled payment 10

Why understanding risk is key to bending the curve # Chronic Co- morbidities % Pop. Relative Cost (Per Pt.) Est. % of Total Medicare Costs Avg. # Unique MDs/Yr. Avg. # Filled Rx / Yr. 5+ 20% 3.2 66% 13.8 49 3-4 27%.9 23% 7.3 26 0-2 53%.1 11% 3.0 11 Data Source: G. Anderson et. al., Johns Hopkins Univ. (Derived from Medicare claims and beneficiary surveys.) 11

Health Reform Contours - 3: Quality / Equity Research into what works - Comparative Effectiveness Research (CER) Demo projects or incentives related to: Decreasing variation due to geography / disparities Integrated care / coordinated care Primary care / medical homes Prevention / wellness / population incentives Improving end-of-life care Health workforce training subsidies / incentives 12

Improving Coordination is Key: Costs of care stratified by markers of ambulatory care coordination Total Health Care Costs x 1K $ 30 25 20 15 10 5 Year-1 Year-2 0 Poor Coordination Moderate Coord. Good Coord. Coordination levels measured by ACG Version 9.0. Year-1 coordination markers include: count of unique MDs, presence of PCP, presence of majority source. Analysis based on 418,000 commercial health plan enrollees including M+A for 2005/06. This analysis is case-mix adjusted and includes only persons identified in (Yr-1) as being high morbidity based on ACG Resource Utilization Bands (RUB). 13

Health Reform Contours- 4: Digitize and Modernize Huge investment in electronic health records (EHRs) / Health IT (HIT) for doctors and hospitals Accountable Care Organizations (ACOs) and Health Innovation Zones (HIZs) Modernizing Medicare (including Part D) Standardize administrative structure across public and private sector Greater transparency and accountability 14

How might predictive modeling / risk adjustment be applied within various components of US healthcare reform? 15

How PM / RA could be applied - 1: Expanding Coverage Premium adjustments to account for varying risk within plans comprising health insurance exchange (HIE) or Cooperatives. As part of Medicaid expansion (Most Medicaid states use risk adjusted capitation.) To help private plan actuaries better manage within the new rating environment. By regulators to monitor private health plans 16

A reminder -- there are other tools for controlling adverse risk selection In addition to risk adjusters like HCCs, ACGs or CDPS, there are other mechanisms that will should be in place to address risk selection: Stop loss / reinsurance Retrospective adjustment - settlement Regulation / Monitoring Carve outs (both services and people) 17

There are some models for how exchanges can apply risk adjustment methods Massachusetts Connector Minnesota BHCAG / Smart Buy Alliance Pacific Business Group on Health Various State Medicaid Programs (e.g., Maryland, Minnesota, Tennessee) 18

How PM / RA could be applied - 2: Paying Providers Paying Medicare, Medicaid, or public option plans More accurate adjusted payment of Part D Rx plans (PDPs) Adjusting various P4P performance measures Efficiency Outcomes Adjusting payments to individual doctors / groups, as we move away from FFS; Episode / bundles Global budgets / FFS adjustment 19

Canadian Single Payer (in BC) dramatically decreased case identification of efficiency outliers through risk adjusted performace profiles of PCPs 20

If episodes are used to pay (or assess) providers, we need to account for overall morbidity burden (Analysis of internist PCPs) Episode (ETG) Performance Efficiency Poor Avg. Good Total Morbidity Burden (ACGs) for Patient Panel * Sick 28 19 10 57 Avg 20 16 21 57 Healthy 9 22 26 57 Total 57 57 57 171 Source: commercial health plan ; 171 internal medicine IM PCPs with at least 30 episodes. * ACG morbidity weights based only on in-scope ETG patients. 21

How PM / RA could be applied - 3: Improving Quality Many potential demos could apply innovative PM applications: Medical homes (improving primary care) Disparities identifying persons in need of more care Identifying individuals for improved end-of-life counseling Population / integrated care initiatives could apply PM in many ways, for example ACO s and HIZ s Propensity scores and other higher order statistical applications for CER research 22

Informing Primary Care Reform: US / UK Patterns of Specialist use by Pt. Risk Categories 90 % Patients Referred/Year 80 70 60 50 40 30 20 10 US Health Plans UK 0 0.0 0.5 1.0 1.5 2.0 2.5 Healthier Treated Morbidity Index Score (ACGs) Sicker Source: Forrest et al, BMJ.

How PM / RA could be applied - 4: Private sector innovations / responses Individual / small group health plan premium setting within new federal safe harbors A wide series of care management innovations for newly insured persons with special needs. Improved internal fiscal and operational management and strategic planning within the risk adjusted payment environment. 24

Using PM risk stratification derived only from several months of Rx experience to target and stratify disease management program participation % Enrollees in ACG Rx- MG Risk Category Resource Use of Cohort Relative to Total Population Condition of Interest Low Med. High Low Med. High Diabetes 44.97 42.1 11.9 1.34 4.90 7.44 Congestive Heart Failure 19.75 53.5 26.75 1.14 6.02 7.93 Tier 1 Tier 2 Tier 3 25

How PM / RA could be applied - 5: Digitizing health care As reform leads to eventual adoption of EHR / HIT, there will be numerous opportunities for care supported by electronic PM/RA techniques. Integration of population level PM with patient level clinical decision support systems (CDSS). What I term e-pm Next generation of PM tools will be able to use information derived from EHRs and patientcentered personal health records (PHRs) 26

Electronic Health Records Health IT and the New e- PM context 27

Patient CDSS* Clinical Decision Support Systems Providers PHR Personal Health Record Home Biometrics Web Portal CPOE** Computerized Provider Order Entry EHR Electronic Health Record HIT Enabled Healthcare Clinical HIT support - 1

PM Population Patient MCOs & DMOs CDSS Clinical Decision Support Systems Providers PHR Personal Health Record Home Biometrics Web Portal EHR CPOE Computerized Provider Order Entry Electronic Health Record HIT Enabled Healthcare Population Based PM - 2

e-pm PM Population Patient MCOs & DMOs CDSS Clinical Decision Support Systems Providers PHR Personal Health Record Home Biometrics Web Portal CPOE Computerized Provider Order Entry EHR Electronic Health Record e-pm = the Integration of current CDSS / PM

An early example of an e-pm tool: Electronic monitoring of Rx gaps in care and its potential impact on cost Type of Cost (Annual) No Rx Gap < 60 days gap >90 days Gap Medical Cost $3358 $4052 $5127 (1.0) (1.21) (1.53) Rx Cost 2024 1845 1419 Total Cost 5382 5897 6546 Notes: For 14,185 persons on ACE/ARB Hypertension Meds. Gaps reflect Rx possession gaps >14 days. Based on 2007 sample of enrollees in commercial health plans. Logic based on Johns Hopkins ACG-PM V.9.0, Gaps in Rx care methodology. 31

Some Next Steps, Implications and Challenges. 32

Some future areas of reform-related PM / RA research and development Application of PM / RA tools to improving care among previously uninsured Enhancement of CMS first generation M+A and PDP risk adjusters Increasing PM s impact on clinician practices and patient outcomes in order to bend the curve Integration of PM with EHRs / PHRs. 33

Some future challenges for the PM / RA field related to health reform Need to continue to fully integrate PM / RA into potentially reformed clinical and fiscal operations New paradigms will likely be needed for the way actuaries / health plans manage risk PM and RA may be use more frequently for equity / quality enhancement to increase service use. Transparency and interoperability of PM / RA methods will likely need to increase 34

To discuss all this and more, you are invited to the Johns Hopkins University's 2010 ACG International Risk Adjustment / Predictive Modeling Conference Keep informed of the latest developments in risk adjustment and predictive modeling Loews Ventana Canyon Resort Tucson, AZ May 10-12, 2010 More information at www.acg.jhsph.edu 35

More Information ACG Web Site: www.acg.jhsph.edu Contacts: Amy Salls DST Health Solutions Inc. (Distributor of ACGs in US & Canada) (508) 405-0297 asalls@dsthealthsolutions.com Professor Jonathan Weiner jweiner@jhsph.edu, 410 955-5661 36