Do payor-based outreach programs reduce medical cost and utilization?

Medicare care management congestive heart failure continuity of care health policy high-risk patients predictive analytics

Journal

Health economics
ISSN: 1099-1050
Titre abrégé: Health Econ
Pays: England
ID NLM: 9306780

Informations de publication

Date de publication:
06 2020
Historique:
received: 09 02 2019
revised: 17 12 2019
accepted: 29 01 2020
pubmed: 13 2 2020
medline: 19 8 2021
entrez: 13 2 2020
Statut: ppublish

Résumé

There is growing interest in using predictive analytics to drive interventions that reduce avoidable healthcare utilization. This study evaluates the impact of such an intervention utilizing claims from 2013 to 2017 for high-risk Medicare Advantage patients with congestive heart failure. A predictive algorithm using clinical and nonclinical information produced a risk score ranking for health plan members in 10 separate waves between July 2013 and May 2015. Each wave was followed by an outreach intervention. The varying capacity for outreach across waves created a set of arbitrary intervention treatment cutoff points, separating treated and untreated members with very similar predicted risk scores. We estimate a difference-in-differences model to identify the effects of the intervention program among patients with a high score on care utilization. We find that enrollment in the intervention decreased the probability and number of hospitalizations (by 43% and 50%, respectively) and emergency room visits (10% and 14%, respectively), reduced the time until a primary care visit (8.2 days), and reduced total medical cost by $716 per month in the first 6 months following outreach.

Identifiants

pubmed: 32048411
doi: 10.1002/hec.4010
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

671-682

Informations de copyright

© 2020 John Wiley & Sons, Ltd.

Références

Agency for Healthcare Research and Quality (2015). Care Management: Implications for Medical Practice, Health Policy, and Health Service Research. Rockville, MD.
Agency for Healthcare Research and Quality. Preventable hospitalizations: A window into primary and preventive care, 2000. AHRQ Publication No. 04-0056; 2004. http://archive.ahrq.gov/data/hcup/factbk5/factbk5.pdf. Accessed August 27, 2017.
Amjad, H., Carmichael, D., Austin, A. M., Chang, C. H., & Bynum, J. P. (2016). Continuity of care and health care utilization in older adults with dementia in fee-for-service Medicare. JAMA Internal Medicine, 176(9), 1371-1378. https://doi.org/10.1001/jamainternmed.2016.3553
Angrist, J. D., & Pischke, J.-S. (2008). Mostly harmless econometrics: An empiricist's companion. Princeton, NJ: Princeton University Press.
Autor, D. H. (2003). Outsourcing at will: The contribution of unjust dismissal doctrine to the growth of employment outsourcing. Journal of Labor Economics, 21(1), 1-42. https://doi.org/10.1086/344122
Bates, D. W., Saria, S., Ohno-Machado, L., Shah, A., & Escobar, G. (2014). Big data in health care: Using analytics to identify and manage high-risk and high-cost patients. Health Affairs, 33(7), 1123-1131. https://doi.org/10.1377/hlthaff.2014.0041
Bertrand, M., Duflo, E., & Mullainathan, S. (2004). How much should we trust differences-in-differences estimates? The Quarterly Journal of Economics, 119(1), 249-275. https://doi.org/10.1162/003355304772839588
Bott, D. M., Kapp, M. C., Johnson, L. B., & Magno, L. M. (2009). Disease management for chronically ill beneficiaries in traditional Medicare. Health Affairs, 28(1), 86-98. https://doi.org/10.1377/hlthaff.28.1.86
Brown, R. S., Peikes, D., Peterson, G., Schore, J., & Razafindrakoto, C. M. (2012). Six features of Medicare coordinated care demonstration programs that cut hospital admissions of high-risk patients. Health Affairs, 31(6), 1156-1166. https://doi.org/10.1377/hlthaff.2012.0393
Courtemanche, C., Marton, J., Ukert, B., Yelowitz, A., & Zapata, D. (2017). Early impacts of the Affordable Care Act on health insurance coverage in Medicaid expansion and non-expansion states. Journal of Policy Analysis and Management, 36(1), 178-210. https://doi.org/10.1002/pam.21961
David, G., Smith-McLallen, A., & Ukert, B. (2019). The effect of predictive analytics-driven interventions on healthcare utilization. Journal of Health Economics, 64, 68-79. https://doi.org/10.1016/j.jhealeco.2019.02.002
DeBusk, R. F., Houston Miller, N., Parker, K. M., Bandura, A., Kraemer, H. C., Cher, D. J., … Greenwald, G. (2004). Care management for low-risk patients with heart failure: A randomized, controlled trial. Annals of Internal Medicine, 141(8), 606-613. https://doi.org/10.7326/0003-4819-141-8-200410190-00008
Kansagara, D., Englander, H., Salanitro, A., Kagen, D., Theobald, C., Freeman, M., & Kripalani, S. (2011). Risk prediction models for hospital readmission: A systematic review. JAMA, 306(15), 1688-1698. https://doi.org/10.1001/jama.2011.1515
Kawamoto, K., Houlihan, C. A., Balas, E. A., & Lobach, D. F. (2005). Improving clinical practice using clinical decision support systems: A systematic review of trials to identify features critical to success. BMJ, 330(7494), 765. https://doi.org/10.1136/bmj.38398.500764.8F
McWilliams, J. M., & Schwartz, A. L. (2017). Focusing on high-cost patients: The key to addressing high costs? The New England Journal of Medicine, 376(9), 807-809. https://doi.org/10.1056/NEJMp1612779
National Institute for Health Care Management Foundation Data Brief July 2012. https://www.nihcm.org/pdf/DataBrief3%20Final.pdf
Naylor, M. D., Brooten, D. A., Campbell, R. L., Maislin, G., McCauley, K. M., & Schwartz, J. S. (2004). Transitional care of older adults hospitalized with heart failure: A randomized, controlled trial. Journal of the American Geriatrics Society, 52, 675-684. https://doi.org/10.1111/j.1532-5415.2004.52202.x
Nyweide, D. J., & Bynum, J. P. (2017). Relationship between continuity of ambulatory care and risk of emergency department episodes among older adults. Annals of Emergency Medicine, 69(4), 407-415. https://doi.org/10.1016/j.annemergmed.2016.06.027
Peikes, D., Chen, A., Schore, J., & Brown, R. (2009). Effects of care coordination on hospitalization, quality of care, and health care expenditures among Medicare beneficiaries: 15 randomized trials. JAMA, 301(6), 603-618. https://doi.org/10.1001/jama.2009.126
Rich, M. W., Beckman, V., Wittenberg, C., Leven, C. L., Freedland, K. E., & Carney, R. M. (1995). Multidisciplinary intervention to prevent the readmissions of elderly patients with congestive heart failure. The New England Journal of Medicine, 333, 1190-1195. https://doi.org/10.1056/NEJM199511023331806
Segal, M., Rollins, E., Hodges, K., & Roozeboom, M. (2014). Medicare-Medicaid eligible beneficiaries and potentially avoidable hospitalizations. Medicare & Medicaid Research Review, 4(1), E1-E13. https://doi.org/10.5600/mmrr.004.01.b01
Wang, T. J., Massaro, J. M., Levy, D., Vasan, R. S., Wolf, P. A., D'agostino, R. B., … Benjamin, E. J. (2003). A risk score for predicting stroke or death in individuals with new-onset atrial fibrillation in the community: The Framingham Heart Study. JAMA, 290(8), 1049-1056. https://doi.org/10.1001/jama.290.8.1049
Wright, A., Henkin, S., Feblowitz, J., McCoy, A. B., Bates, D. W., & Sittig, D. F. (2013). Early results of the meaningful use program for electronic health records. New England Journal of Medicine, 368(8), 779-780. https://doi.org/10.1056/NEJMc1213481

Auteurs

Benjamin Ukert (B)

Department of Health Policy and Management, Texas A&M University College Station, Texas.

Guy David (G)

Department of Health Care Management, University of Pennsylvania, Philadelphia, Pennsylvania.

Aaron Smith-McLallen (A)

Informatics, Independence Blue Cross, Philadelphia, Pennsylvania.

Ravi Chawla (R)

Informatics, Independence Blue Cross, Philadelphia, Pennsylvania.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH