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“Phenotyping” Hospital Value of Care for Patients with Heart Failure
Author(s) -
Xu Xiao,
Li ShuXia,
Lin Haiqun,
Normand SharonLise T.,
Kim Nancy,
Ott Lesli S.,
Lagu Tara,
Duan Michael,
Kroch Eugene A.,
Krumholz Harlan M.
Publication year - 2014
Publication title -
health services research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.706
H-Index - 121
eISSN - 1475-6773
pISSN - 0017-9124
DOI - 10.1111/1475-6773.12197
Subject(s) - medicine , emergency medicine , multinomial logistic regression , mortality rate , logistic regression , intensive care unit , health care , demography , intensive care medicine , statistics , mathematics , sociology , economics , economic growth
Objective To characterize hospitals based on patterns of their combined financial and clinical outcomes for heart failure hospitalizations longitudinally. Data Source Detailed cost and administrative data on hospitalizations for heart failure from 424 hospitals in the 2005–2011 Premier database. Study Design Using a mixture modeling approach, we identified groups of hospitals with distinct joint trajectories of risk‐standardized cost ( RSC ) per hospitalization and risk‐standardized in‐hospital mortality rate ( RSMR ), and assessed hospital characteristics associated with the distinct patterns using multinomial logistic regression. Principal Findings During 2005–2011, mean hospital RSC decreased from $12,003 to $10,782, while mean hospital RSMR declined from 3.9 to 3.2 percent. We identified five distinct hospital patterns: highest cost and low mortality (3.2 percent of the hospitals), high cost and low mortality (20.4 percent), medium cost and low mortality (34.6 percent), medium cost and high mortality (6.2 percent), and low cost and low mortality (35.6 percent). Longer hospital stay and greater use of intensive care unit and surgical procedures were associated with phenotypes with higher costs or greater mortality. Conclusions Hospitals vary substantially in the joint longitudinal patterns of cost and mortality, suggesting marked difference in value of care. Understanding determinants of the variation will inform strategies for improving the value of hospital care.