The Critical Importance of Targeting (or It s the targeting, stupid. )

Transcription

1 The Critical Importance of Targeting (or It s the targeting, stupid. ) Randall Brown NHPF Targeting High-Cost Medicare Beneficiaries to Improve Care and Reduce Spending: Finding the Bull's-Eye March 9, 2012

2 Overview Why targeting is critical to identifying effective care coordination interventions Evidence from the literature Policy implications for dual eligibles 2

3 Why Targeting is Critical Maximizes net savings potential Focuses provider attention on best opportunities for gains in quality and savings Reduces likelihood that evaluation will miss effective interventions Need to be able to detect much smaller effects using full sample if impacts are limited to a subset of enrollees Power is greater even though sample size is smaller when restrict study to relevant subgroup Common target population enhances opportunities for identifying best practices 3

4 Including Less Severely Ill Beneficiaries Reduces Savings Dollars Net Savings Fee Average Savings Marginal Savings Highest S* Severity Level Lowest 4

5 Including People Who Aren t Affected Doubles Likelihood of Failing to Detect True Effects % of sample in which effects are concentrated 30% 50% 70% Studying the full population (n=1250 in each treatment group) Probability of erroneously finding no effect on hospitalizations 70% 41% 16% Studying only the subgroup with effects Subgroup size in each treatment group Probability of erroneously finding no effect on hospitalizations 34% 16% 7% Lower the proportion of target group in which effects are concentrated higher the likelihood of missing true effects Example is for tests of program effects on hospitalizations when true effect is.15 hospitalizations per person per year, for different proportions in which program effects are concentrated, using full sample or only the affected subgroup. 5

6 Common Targeting Dimensions Chronic Conditions (specific diseases, number) Prior utilization Indexes (e.g., HCC scores, PRHA scores) Functioning indicators Type of residence (community, institution) Local market factors Attitudinal factors Exclusions? 6

7 Care Coordination Interventions with Effects Limited to Specific Subgroups Transitional care models Care Management Plus model GRACE model Guided Care (early results) Medicare Coordinated Care Demonstration (MCCD) 7

8 Subgroups with Impacts Inpatients (transitional care models) Diabetics (Care Management Plus) Patients at high risk of hospitalization (GRACE) Patients with HCC scores above 1.2 (Guided Care) Patients with high risk conditions and recent hospitalization or any chronic condition and repeated hospitalizations (MCCD) 8

9 Subgroups Examined in MCCD Study Subgroup 1. Those with conditions with high rates of hospitalization (CHF, CAD, or COPD) 2. More severe cases: in group 1 AND had a hospitalization in preenrollment year 3. Group 2 plus frequent flyers : [2+ hospitalizations in past 2 years, any chronic condition] Results Significant but modest effects on hospitalizations for 3 sites Substantially larger effects for 2 of the 3 sites (14% of Medicare population) 4 programs had significant effects, similar in magnitude to group 2 (18% of Medicare population; 38% of Medicare costs) SOURCE: Brown, Peikes, Peterson, Schore, Razafindrakato. Effects of Care Coordination on Hospitalization and Health Care Expenditutures Among High-Risk Medicare Beneficiaries: 11 Randomized Trials. Manuscript under review. 9

10 Policy Implications For Medicare Medical homes are not likely to succeed in saving money if they do not focus on high risk subgroups Accountable Care Organizations also need to focus their efforts on high risk patients For Dual Eligibles Creating SNPs for duals is not sufficient targeting Different interventions and payment structures are required for different subgroups of duals 10

11 Information and Acknowledgements For more information, please contact Randall Brown at: Funding sources: Changes in Health Care Financing and Organization (Robert Wood Johnson Foundation) Medicare Coordinated Care Practice Research Network Grant (CMS) Evaluation of the Medicare Coordinated Care Demonstration (CMS) 11 Mathematica is a registered trademark of Mathematica Policy Research.