Literature DB >> 16294676

The identification of high-cost patients.

Tiffany A Radcliff1, Murray J Côté, R Paul Duncan.   

Abstract

The authors examine whether retrospective claims data are useful to distinguish future high-cost cases among the uninsured. They rely on internal claims and accounting data for the calendar years from 1999 to 2001 from a representative safety net facility to describe the distribution of costs and any characteristics that distinguish high-cost patients from other uninsured patients. They conclude that administrative data combined with in-depth survey information could be a useful approach for identifying cases for intensive case management.

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Year:  2005        PMID: 16294676     DOI: 10.3200/HTPS.83.3.17-24

Source DB:  PubMed          Journal:  Hosp Top        ISSN: 0018-5868


  5 in total

1.  Comparison of alternative risk adjustment measures for predictive modeling: high risk patient case finding using Taiwan's National Health Insurance claims.

Authors:  Hsien-Yen Chang; Wui-Chiang Lee; Jonathan P Weiner
Journal:  BMC Health Serv Res       Date:  2010-12-20       Impact factor: 2.655

2.  High-cost health care users in Ontario, Canada: demographic, socio-economic, and health status characteristics.

Authors:  Laura C Rosella; Tiffany Fitzpatrick; Walter P Wodchis; Andrew Calzavara; Heather Manson; Vivek Goel
Journal:  BMC Health Serv Res       Date:  2014-10-31       Impact factor: 2.655

3.  Effects of behavioural risk factors on high-cost users of healthcare: a population-based study.

Authors:  Amanda Alberga; Laura Holder; Kathy Kornas; Catherine Bornbaum; Laura Rosella
Journal:  Can J Public Health       Date:  2018-09-19

4.  An in-depth assessment of a diagnosis-based risk adjustment model based on national health insurance claims: the application of the Johns Hopkins Adjusted Clinical Group case-mix system in Taiwan.

Authors:  Hsien-Yen Chang; Jonathan P Weiner
Journal:  BMC Med       Date:  2010-01-18       Impact factor: 8.775

5.  Who Are the High-Cost Users? A Method for Person-Centred Attribution of Health Care Spending.

Authors:  Sara J T Guilcher; Susan E Bronskill; Jun Guan; Walter P Wodchis
Journal:  PLoS One       Date:  2016-03-03       Impact factor: 3.240

  5 in total

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