Predictive analytics and tailored interventions improve clinical outcomes in older adults: a randomized controlled trial

Author:

Golas Sara BerscheORCID,Nikolova-Simons MarianaORCID,Palacholla Ramya,op den Buijs Jorn,Garberg Gary,Orenstein Allison,Kvedar JosephORCID

Abstract

AbstractThis study explored the potential to improve clinical outcomes in patients at risk of moving to the top segment of the cost acuity pyramid. This randomized controlled trial evaluated the impact of a Stepped-Care approach (predictive analytics + tailored nurse-driven interventions) on healthcare utilization among 370 older adult patients enrolled in a homecare management program and using a Personal Emergency Response System. The Control group (CG) received care as usual, while the Intervention group (IG) received Stepped-Care during a 180-day intervention period. The primary outcome, decrease in emergency encounters, was not statistically significant (15%, p = 0.291). However, compared to the CG, the IG had significant reductions in total 90-day readmissions (68%, p = 0.007), patients with 90-day readmissions (76%, p = 0.011), total 180-day readmissions (53%, p = 0.020), and EMS encounters (49%, p = 0.006). Predictive analytics combined with tailored interventions could potentially improve clinical outcomes in older adults, supporting population health management in home or community settings.

Funder

Philips

Publisher

Springer Science and Business Media LLC

Subject

Health Information Management,Health Informatics,Computer Science Applications,Medicine (miscellaneous)

Reference35 articles.

1. Suzman, R. et al. Health in an ageing world—what do we know? Lancet 385, 484–486 (2015).

2. Ortman, J. M., Velkoff, V. & Hogan, H. An aging nation: the older population in the United States. Econ. Stat. Adm. US Dep. Commer. 1964, 1–28 (2014).

3. For Patients With Multiple Chronic Conditions, Improving Care Will Be A Bipartisan Effort, Health Affairs Blog. https://doi.org/10.1377/hblog20170601.060354/full

4. Centers for Medicare and Medicaid Services (CMC). Chronic conditions among Medicare beneficiaries, Prevalence and Medicare utilization and spending for 21 chronic conditions throughout the years 2007-2017. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Chronic-Conditions/CC_Main

5. Bodenheimer, T., Chen, E. & Bennett, H. D. Confronting the growing burden of chronic disease: can the U.S. health care workforce do the job? Health Aff. 28, 64–74, https://www.healthaffairs.org/doi/full/10.1377/hlthaff.28.1.64 (2009).

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3