Impact of Primary Care Intensive Management on High-Risk Veterans' Costs and Utilization
Authors: John H. Wasson
Journal: Annals of Internal Medicine (2018)

Letters2 October 2018Impact of Primary Care Intensive Management on High-Risk Veterans' Costs and UtilizationJohn H. Wasson, MDJohn H. Wasson, MDGeisel School of Medicine at Dartmouth, Hanover, New Hampshire (J.H.W.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/L18-0460 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail TO THE EDITOR:A growing list of studies, including Yoon and colleagues' multicenter trial (1), do not support the hypothesis that providing intensive management to patients at high risk for costly health care will save money. Moreover, recognition that computer-based designations of being at risk for costly care (also decorously called predictive analytics) vary considerably, furnish no specific guidance, and are inaccurate is increasing. Most patients in the small, at-risk subgroup will not use such care, whereas care becomes relatively rationed for most patients not designated as such—including those who may require it (2, 3). Nevertheless, health care executives embrace ...References1. Yoon J, Chang E, Rubenstein LV, Park A, Zulman DM, Stockdale S, et al. Impact of primary care intensive management on high-risk veterans' costs and utilization: a randomized quality improvement trial. Ann Intern Med. 2018;168:846-54. [PMID: 29868706]. doi:10.7326/M17-3039 LinkGoogle Scholar2. Wasson JH, Soloway L, Moore LG, Labrec P, Ho L. Development of a care guidance index based on what matters to patients. Qual Life Res. 2018;27:51-8. [PMID: 28401418] doi:10.1007/s11136-017-1573-x CrossrefMedlineGoogle Scholar3. Wasson JH, Ho L, Soloway L, Moore LG. Validation of the What Matters Index: a brief, patient-reported index that guides care for chronic conditions and can substitute for computer-generated risk models. PLoS One. 2018;13:e0192475. [PMID: 29470544] doi:10.1371/journal.pone.0192475 CrossrefMedlineGoogle Scholar4. Society of Actuaries. 2017 Predictive Analytics in Healthcare Trend Forecast. Schaumburg, IL: Society of Actuaries; 2017. Accessed at www.soa.org/Files/programs/predictive-analytics/2017-health-care-trend.pdf on 26 August 2018. Google Scholar5. HowsYourHealth.org. Quick health check-up. 2018. Accessed at https://howsyourhealth.org on 26 August 2018. Google Scholar Author, Article, and Disclosure InformationAffiliations: Geisel School of Medicine at Dartmouth, Hanover, New Hampshire (J.H.W.)Disclosures: The author has disclosed no conflicts of interest. The form can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=L18-0460. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoImpact of Primary Care Intensive Management on High-Risk Veterans' Costs and Utilization Jean Yoon , Evelyn Chang , Lisa V. Rubenstein , Angel Park , Donna M. Zulman , Susan Stockdale , Michael K. Ong , David Atkins , Gordon Schectman , and Steven M. Asch Impact of Primary Care Intensive Management on High-Risk Veterans' Costs and Utilization Jean Yoon , Evelyn Chang , Lisa V. Rubenstein , Donna M. Zulman , and Steven M. Asch Impact of Primary Care Intensive Management on High-Risk Veterans' Costs and Utilization Katherine Rediger and D.R. Bailey Miles Impact of Primary Care Intensive Management on High-Risk Veterans' Costs and Utilization Eran Bellin Metrics Cited byInsights From Organized Crime for Disorganized Health Care 2 October 2018Volume 169, Issue 7Page: 514KeywordsAnxietyComputersConflicts of interestDepressionDisclosureForecastingHealth careHealth care utilizationMedical services ePublished: 2 October 2018 Issue Published: 2 October 2018 Copyright & PermissionsCopyright © 2018 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...