Cost-Effectiveness of the Wellness Incentives and Navigation (WIN) Program

Walter Bruce Vogel; Heather L Morris; Keith Muller; Tianyao Huo; Alice Parish; Dena Stoner; Elizabeth Shenkman

doi:10.1016/j.jval.2020.06.019

Cost-Effectiveness of the Wellness Incentives and Navigation (WIN) Program

Value Health. 2021 Mar;24(3):361-368. doi: 10.1016/j.jval.2020.06.019. Epub 2020 Oct 29.

Authors

Walter Bruce Vogel¹, Heather L Morris², Keith Muller², Tianyao Huo², Alice Parish³, Dena Stoner⁴, Elizabeth Shenkman²

Affiliations

¹ Department of Health Outcomes and Biomedical Informatics, College of Medicine, Clinical and Translational Science Institute, University of Florida, and the Institute for Child Health Policy, Gainesville, FL, USA. Electronic address: bvogel@ufl.edu.
² Department of Health Outcomes and Biomedical Informatics, College of Medicine, Clinical and Translational Science Institute, University of Florida, and the Institute for Child Health Policy, Gainesville, FL, USA.
³ Department of Biostatistics and Bioinformatics, BERD Methods Core, Duke University, Durham, NC, USA.
⁴ Texas Department of State Health Services, Austin, TX, USA.

PMID: 33641770
DOI: 10.1016/j.jval.2020.06.019

Abstract

Objectives: Promoting patient involvement in managing co-occurring physical and mental health conditions is increasingly recognized as critical to improving outcomes and controlling costs in this growing chronically ill population. The main objective of this study was to conduct an economic evaluation of the Wellness Incentives and Navigation (WIN) intervention as part of a longitudinal randomized pragmatic clinical trial for chronically ill Texas Medicaid enrollees with co-occurring physical and mental health conditions.

Methods: The WIN intervention used a personal navigator, motivational interviewing, and a flexible wellness expense account to increase patient activation, that is, the patient's knowledge, skills, and confidence in managing their self-care and co-occurring physical and mental health conditions. Regression models were fit to both participant-level quality-adjusted life years (QALYs) and total costs of care (including the intervention) controlling for demographics, health status, poverty, Medicaid managed care plan, intervention group, and baseline health utility and costs. Incremental costs and QALYs were calculated based on the difference in predicted costs and QALYs under intervention versus usual care and were used to calculate the incremental cost-effectiveness ratios (ICERs). Confidence intervals were calculated using Fieller's method, and sensitivity analyses were performed.

Results: The mean ICER for the intervention compared with usual care was $12 511 (95% CI $8971-$16 842), with a sizable majority of participants (70%) having ICERs below $40 000. The WIN intervention also produced higher QALY increases for participants who were sicker at baseline compared to those who were healthier at baseline.

Conclusion: The WIN intervention shows considerable promise as a cost-effective intervention in this challenging chronically ill population.

Keywords: Medicaid; chronic illness; cost-effectiveness; motivational interviewing; patient activation.

Publication types

Randomized Controlled Trial
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Adult
Cost-Benefit Analysis
Female
Health Knowledge, Attitudes, Practice*
Health Promotion / economics
Health Promotion / organization & administration*
Health Status
Humans
Longitudinal Studies
Male
Medicaid / economics
Medicaid / statistics & numerical data*
Motivational Interviewing / organization & administration
Multiple Chronic Conditions / epidemiology*
Patient Navigation / organization & administration
Quality-Adjusted Life Years
Self Care
Self Concept
Socioeconomic Factors
Texas / epidemiology
United States
Young Adult