Use of Latent Class Analysis and k-Means Clustering to Identify Complex Patient Profiles-Reference-Cited by-同舟云学术

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Use of Latent Class Analysis and k-Means Clustering to Identify Complex Patient Profiles

Published:2020-12-11 Issue:12 Volume:3 Page:e2029068
ISSN:2574-3805
Container-title:JAMA Network Open
language:en
Short-container-title:JAMA Netw Open

Author:

Grant Richard W.¹,McCloskey Jodi¹,Hatfield Meghan¹,Uratsu Connie¹,Ralston James D.²,Bayliss Elizabeth³,Kennedy Chris J.¹⁴

Affiliation:

1. Division of Research, Kaiser Permanente Northern California, Oakland

2. Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle

3. Institute for Health Research, Kaiser Permanente Colorado, Aurora

4. Division of Epidemiology and Biostatistics, University of California, Berkeley, Berkeley

Publisher

American Medical Association (AMA)

Subject

General Medicine

Link

https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2774074/grant_2020_oi_200927_1607110903.52002.pdf

Reference49 articles.

1. Effects of care coordination on hospitalization, quality of care, and health care expenditures among Medicare beneficiaries: 15 randomized trials.;Peikes;JAMA,2009

2. The effect of guided care teams on the use of health services: results from a cluster-randomized controlled trial.;Boult;Arch Intern Med,2011

3. A systematic review of care management interventions targeting multimorbidity and high care utilization.;Baker;BMC Health Serv Res,2018

4. Effectiveness of intensive primary care interventions: a systematic review.;Edwards;J Gen Intern Med,2017

5. Association between care management and outcomes among patients with complex needs in Medicare accountable care organizations.;Ouayogodé;JAMA Netw Open,2019

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