Abstract
To develop a quasi-experimental method for estimating Population Health Management (PHM) program savings that mitigates common sources of confounding, supports regular updates for continued program monitoring, and estimates model precision. Administrative, program, and claims records from January 2005 through June 2009. Data are aggregated by member and month. Study participants include chronically ill adult commercial health plan members. The intervention group consists of members currently enrolled in PHM, stratified by intensity level. Comparison groups include (1) members never enrolled, and (2) PHM participants not currently enrolled. Mixed model smoothing is employed to regress monthly medical costs on time (in months), a history of PHM enrollment, and monthly program enrollment by intensity level. Comparison group trends are used to estimate expected costs for intervention members. Savings are realized when PHM participants' costs are lower than expected. This method mitigates many of the limitations faced using traditional pre-post models for estimating PHM savings in an observational setting, supports replication for ongoing monitoring, and performs basic statistical inference. This method provides payers with a confident basis for making investment decisions.
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