Short-Term VA Health Care Expenditures Following a Health Risk Assessment and Coaching Trial

Journal of General Internal Medicine - Tập 35 - Trang 1452-1457 - 2020
Caroline Sloan1,2, Karen M. Stechuchak1, Maren K. Olsen1,3, Eugene Z. Oddone1,2, Laura J. Damschroder4,5, Matthew L. Maciejewski1,2,6
1Durham Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), , Durham Veterans Affairs Health Care System, Durham, USA
2Division of General Internal Medicine, Department of Medicine, Duke University, Durham, USA
3Department of Biostatistics and Bioinformatics, Duke University, Durham, USA
4Ann Arbor VA HSR&D Center for Clinical Management Research, Ann Arbor, USA
5VA Diabetes QUERI, Ann Arbor, USA
6Department of Population Health Sciences, Duke University, Durham, USA

Tóm tắt

Short-term health care costs following completion of health risk assessments and coaching programs in the VA have not been assessed. To compare VA health care expenditures among veterans who participated in a behavioral intervention trial that randomized patients to complete a HRA followed by health coaching (HRA + coaching) or to complete the HRA without coaching (HRA-alone). Four-hundred seventeen veterans at three Veterans Affairs (VA) Medical Centers or Clinics were randomized to HRA + coaching or HRA-alone. Veterans randomized to HRA-alone (n = 209) were encouraged to discuss HRA results with their primary care team, while veterans randomized to HRA + coaching (n = 208) received two brief telephone-delivered health coaching calls. We included 411 veterans with available cost data. Total VA health expenditures 6 months following trial enrollment were estimated using a generalized linear model with a gamma distribution and log link function. In exploratory analysis, model-based recursive partitioning was used to determine whether the intervention effect on short-term costs differed among any patient subgroups. Most participants were male (85%); mean age was 56, and mean body mass index was 34. From the generalized linear model, 6-month estimated mean total VA expenditures were similar ($8665 for HRA + coaching vs $9900 for HRA-alone, p = 0.25). In exploratory subgroup analysis, among unemployed veterans with good sleep and fair or poor perceived health, mean observed expenditures in the HRA + coaching group were higher than in the HRA-alone group ($12,814 vs $7971). Among unemployed veterans with good sleep and good general health, mean observed expenditures in the HRA + coaching group were lower than in the HRA-alone group ($5082 vs $11,612). Compared to completing and receiving HRA results, working with health coaches to set actionable health behavior change goals following HRA completion did not reduce short-term health expenditures. Clinicaltrials.gov identifier: NCT01828567

Tài liệu tham khảo

Fielding JE. Frequency of health risk assessment activities at U.S. worksites. Am J Prev Med. 1989; 5: 73–81. Aldana SG. Financial impact of health promotion programs: a comprehensive review of the literature. Am J Health Promot AJHP. 2001; 15: 296–320. Haas JS, Baer HJ, Eibensteiner K, et al. A Cluster Randomized Trial of a Personalized Multi-Condition Risk Assessment in Primary Care. Am J Prev Med. 2017; 52: 100–5. Sieck CJ, Dembe AE. A 3-Year Assessment of the Effects of a Self-Administered Health Risk Assessment on Health Care Utilization, Costs, and Health Risks: J Occup Environ Med. 2014; 56: 1284–90. Parkinson MD, Peele PB, Keyser DJ, Liu Y, Doyle S. UPMC MyHealth: managing the health and costs of U.S. healthcare workers. Am J Prev Med. 2014; 47: 403–10. Ozminkowski RJ, Ling D, Goetzel RZ, et al. Long-Term Impact of Johnson & Johnson’s Health & Wellness Program on Health Care Utilization and Expenditures: J Occup Environ Med. 2002; 44: 21–9. Musich S, McCalister T, Wang S, Hawkins K. An Evaluation of the Well at Dell Health Management Program: Health Risk Change and Financial Return on Investment. Am J Health Promot. 2015; 29: 147–57. Fries JF, Bloch DA, Harrington H, Richardson N, Beck R. Two-year results of a randomized controlled trial of a health promotion program in a retiree population: the Bank of America Study. Am J Med. 1993; 94: 455–62. Serxner SA, Gold DB, Grossmeier JJ, Anderson DR. The Relationship Between Health Promotion Program Participation and Medical Costs:: A Dose Response. J Occup Environ Med. 2003; 45: 1196–200. Burton WN, Chen C-Y, Li X, Schultz AB, Kasiarz D, Edington DW. Evaluation of a Comprehensive Employee Wellness Program at an Organization With a Consumer-Directed Health Plan: J Occup Environ Med. 2014; 56: 347–53. Mattke S, Serxner SA, Zakowski SL, Jain AK, Gold DB. Impact of 2 employer-sponsored population health management programs on medical care cost and utilization. Am J Manag Care. 2009; 15: 113–20. Song Z, Baicker K. Effect of a Workplace Wellness Program on Employee Health and Economic Outcomes: A Randomized Clinical Trial. JAMA 2019; 321: 1491–501. Oddone EZ, Gierisch JM, Sanders LL, et al. A Coaching by Telephone Intervention on Engaging Patients to Address Modifiable Cardiovascular Risk Factors: a Randomized Controlled Trial. J Gen Intern Med 2018; 33: 1487–94. Veterans Administration. MyHealtheVet. https://www.myhealth.va.gov/mhv-portal-web/home. Accessed 2/1/2018 Hibbard JH, Mahoney ER, Stockard J, Tusler M. Development and testing of a short form of the patient activation measure. Health Serv Res. 2005; 40: 1918–30. Hibbard JH, Mahoney ER, Stock R, Tusler M. Do increases in patient activation result in improved self-management behaviors? Health Serv Res. 2007; 42: 1443–63. Stewart A, Ware J, Brook R, Davies A. Conceptualization and measurement of physical health for adults in the Health Insurance Study, Vol. II, The RAND Corporation (R-1987/2-HEW), Santa Monica, Calif. 1978. Wilson PW, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998; 97: 1837–47. U.S. Department of Veterans Affairs. VA Informatics and Computing Infrastructure (VINCI), VA HSR HIR 08-204. 2008 https://vaww.VINCI.med.va.gov (accessed Oct 19, 2018). Consumer Price Index (CPI) Databases. U. S. Dep. Labor Bur. Labor Stat. https://www.bls.gov/cpi/data.htm (accessed Dec 17, 2018). Manning WG, Mullahy J. Estimating log models: to transform or not to transform? J Health Econ. 2001; 20: 461–94. Seibold H, Zeileis A, Hothorn T. Model-Based Recursive Partitioning for Subgroup Analyses. Int J Biostat. 2016; 12: 45–63. Hothorn T, Zeileis A. partykit: A Modular Toolkit for Recursive Partytioning in R. J Mach Learn Res. 2015; 16: 3905–9. Schultz AB, Lu C, Barnett TE, et al. Influence of participation in a worksite health-promotion program on disability days. J Occup Environ Med. 2002; 44: 776–80. Singh GK, Daus GP, Allender M, et al. Social Determinants of Health in the United States: Addressing Major Health Inequality Trends for the Nation, 1935-2016. Int J MCH AIDS 2017; 6: 139–64. Besedovsky L, Lange T, Born J. Sleep and immune function. Pflugers Arch. 2012; 463: 121–37. Hoevenaar-Blom MP, Spijkerman AMW, Kromhout D, Verschuren WMM. Sufficient sleep duration contributes to lower cardiovascular disease risk in addition to four traditional lifestyle factors: the MORGEN study. Eur J Prev Cardiol. 2014; 21: 1367–75. Deng H-B, Tam T, Zee BC-Y, et al. Short Sleep Duration Increases Metabolic Impact in Healthy Adults: A Population-Based Cohort Study. Sleep. 2017; 40. https://doi.org/10.1093/sleep/zsx130.