Integrating Well-Being Information and the Multidimensional Adaptive Prediction Process to Estimate Individual-Level Future Health Care Expenditure Levels.

Decades of research exist focusing on the utility of self-reported health risk and status data in health care cost predictive models. However, in many of these studies a limited number of self-reported measures were considered. Compounding this issue, prior research evaluated models specified with a single covariate vector and distribution.

Impact of a scalable care transitions program for readmission avoidance.

Objectives: To evaluate the Care Transition Solution (CTS) as a means to improve quality through reduction of preventable hospital readmissions among patients with readmission-sensitive conditions subject to penalties imposed by the Affordable Care Act.

Study Design: A retrospective quasi-experimental evaluation of the impact of the CTS among admitted patients diagnosed with heart failure, acute myocardial infarction, chronic obstructive pulmonary disease, and/or pneumonia (CMS readmission-penalty diagnoses) in 14 acute care hospitals in Texas. The program, designed for scalable delivery, incorporated identification of high readmission-risk patients, assessment of individual needs, medication reconciliation, discharge planning, care coordination, and telephonic postdischarge follow-up.

Exploring robust methods for evaluating treatment and comparison groups in chronic care management programs.

Evaluation of chronic care management (CCM) programs is necessary to determine the behavioral, clinical, and financial value of the programs. Financial outcomes of members who are exposed to interventions (treatment group) typically are compared to those not exposed (comparison group) in a quasi-experimental study design. However, because member assignment is not randomized, outcomes reported from these designs may be biased or inefficient if study groups are not comparable or balanced prior to analysis.