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The Identification of High-Cost Patients
Author(s) -
Tiffany A. Radcliff,
Murray J. Côté,
R. Paul Duncan
Publication year - 2005
Publication title -
hospital topics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.202
H-Index - 21
eISSN - 1939-9278
pISSN - 0018-5868
DOI - 10.3200/htps.83.3.17-24
Subject(s) - identification (biology) , computer science , operations management , medical emergency , survey data collection , actuarial science , business , medicine , statistics , engineering , mathematics , botany , biology
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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