Going Beyond Clinical Care to Reduce Health Care Spending: Findings From the J-CHiP Community-based Population Health Management Program Evaluation.

BACKGROUND: Addressing both clinical and nonclinical determinants of health is essential for improving population health outcomes. In 2012, the Johns Hopkins Community Health Partnership (J-CHiP) implemented innovative population health management programs across acute and community environments. The community-based program involved multidisciplinary teams [ie, physicians, care managers (CM), health behavior specialists (HBS), community health workers, neighborhood navigators] and collaboration with community-based organizations to address social determinants. OBJECTIVES: To report the impact of a community-based program on cost and utilization from 2011 to 2016. DESIGN: Difference-in-difference estimates were calculated for an inclusive cohort of J-CHiP participants and matched nonparticipants. The analysis was replicated for participants with a CM and/or HBS to estimate the differential impact with more intensive program services. SUBJECTS: A total of 3268 high-risk Medicaid and Medicare beneficiaries (1634 total J-CHiP participants, 1365 with CM and 678 with HBS). OUTCOME MEASURES: Paid costs and counts of emergency department visits, admissions, and readmissions per member per year. RESULTS: For Medicaid, costs were almost $1200 per member per year lower for participants as a whole, $2000 lower for those with an HBS, and $3000 lower for those with a CM; hospital admission and readmission rates were 9%-26% lower for those with a CM and/or HBS. For Medicare, costs were lower (-$476), but utilization was similar or higher than nonparticipants. None of the observed Medicaid or Medicare differences were statistically significant. CONCLUSIONS: Although not statistically significant, the results indicate a promising innovation for Medicaid beneficiaries. For Medicare, the impact was negligible, indicating the need for further program modification.

Key Design Considerations When Calculating Cost Savings for Population Health Management Programs in an Observational Setting.

OBJECTIVE: To illustrate the impact of key quasi-experimental design elements on cost savings measurement for population health management (PHM) programs. DATA SOURCES: Population health management program records and Medicaid claims and enrollment data from December 2011 through March 2016. STUDY DESIGN: The study uses a difference-in-difference design to compare changes in cost and utilization outcomes between program participants and propensity score-matched nonparticipants. Comparisons of measured savings are made based on (1) stable versus dynamic population enrollment and (2) all eligible versus enrolled-only participant definitions. Options for the operationalization of time are also discussed. DATA COLLECTION/EXTRACTION METHODS: Individual-level Medicaid administrative and claims data and PHM program records are used to match study groups on baseline risk factors and assess changes in costs and utilization. PRINCIPAL FINDINGS: Savings estimates are statistically similar but smaller in magnitude when eliminating variability based on duration of population enrollment and when evaluating program impact on the entire target population. Measurement in calendar time, when possible, simplifies interpretability. CONCLUSION: Program evaluation design elements, including population stability and participant definitions, can influence the estimated magnitude of program savings for the payer and should be considered carefully. Time specifications can also affect interpretability and usefulness.

Caring for children with special healthcare needs in the managed care environment.

Dramatic medical and technological advances over the past 15 years have resulted in the survival into adulthood of children with chronic health conditions. As this population subset has increased, the demand of caring for these children in the managed care arena has become challenging from a clinical, fiscal, and member satisfaction perspective. A disease management program was designed for children, ages birth through age 18, identified as having special needs at the time of birth or at any point throughout childhood related to disease processes such as diabetes, sickle cell disease, genetic aberrations, or the multiple complications of extreme prematurity. Components of the program included identification of the population, coordinated risk assessment, and ongoing case management interventions. Most important, outcome indicators were tracked to demonstrate program effectiveness. The formulation and function of a dedicated disease management database is also discussed.