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Comparison of Measures to Predict Mortality and Length of Stay in Hospitalized Patients

Liu, Jianfang; Larson, Elaine; Hessels, Amanda; Cohen, Bevin; Zachariah, Philip; Caplan, David; Shang, Jingjing

doi: 10.1097/NNR.0000000000000350
FEATURE ARTICLES
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Background Patient risk adjustment is critical for hospital benchmarking and allocation of healthcare resources. However, considerable heterogeneity exists among measures.

Objectives The performance of five measures was compared to predict mortality and length of stay (LOS) in hospitalized adults using claims data; these include three comorbidity composite scores (Charlson/Deyo age-comorbidity score, V W Elixhauser comorbidity score, and V W Elixhauser age-comorbidity score), 3 M risk of mortality (3 M ROM), and 3 M severity of illness (3 M SOI) subclasses.

Methods Binary logistic and zero-truncated negative binomial regression models were applied to a 2-year retrospective dataset (2013–2014) with 123,641 adult inpatient admissions from a large hospital system in New York City.

Results All five measures demonstrated good to strong model fit for predicting in-hospital mortality, with C-statistics of 0.74 (95% confidence interval [CI] [0.74, 0.75]), 0.80 (95% CI [0.80, 0.81]), 0.81(95% CI [0.81, 0.82]), 0.94 (95% CI [0.93, 0.94]), and 0.90 (95% CI [0.90, 0.91]) for Charlson/Deyo age-comorbidity score, V W Elixhauser comorbidity score, V W Elixhauser age-comorbidity score, 3 M ROM, and 3 M SOI, respectively. The model fit statistics to predict hospital LOS measured by the likelihood ratio index were 0.3%, 1.2%, 1.1%, 6.2%, and 4.3%, respectively.

Discussion The measures tested in this study can guide nurse managers in the assignment of nursing care and coordination of needed patient services and administrators to effectively and efficiently support optimal nursing care.

Jianfang Liu, PhD, is Assistant Professor, School of Nursing, Columbia University, New York, New York.

Elaine Larson, RN, PhD, FAAN, CIC, is Associate Dean for Research and Anna C. Maxwell Professor of Nursing Research, School of Nursing, and Professor of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York.

Amanda Hessels, PhD, MPH, RN, CIC, CPHQ, FAPIC, is Assistant Professor, School of Nursing, Columbia University, New York, New York, and Nurse Scientist, Hackensack Meridian Health, Neptune, New Jersey.

Bevin Cohen, PhD, MPH, RN, is Associate Research Scientist, School of Nursing, Columbia University, New York, New York.

Philip Zachariah, MD, MS, is Assistant Professor, Columbia University Medical Center & New York-Presbyterian Morgan Stanley Children's Hospital.

David Caplan, BS, is Senior Technical Specialist, Division of Quality Analytics, New York-Presbyterian Hospital.

Jingjing Shang, PhD, RN, is Associate Professor, School of Nursing, Columbia University, New York, New York.

Accepted for publication October 3, 2018.

This work was supported by a grant from the Agency for Healthcare Research and Quality (R01 HS02491501).

This study was approved by Columbia University Medical Center's institutional review board (AAK4050).

The authors have no conflicts of interest to report.

Corresponding author: Jianfang Liu, PhD, 560 West 168th Street, New York, NY 10032 (e-mail: jl4029@cumc.columbia.edu).

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