ArticleNursing research
Comparison of Measures to Predict Mortality and Length of Stay in Hospitalized Patients.
Article in Nursing research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Hospital length of stay prediction tools for all hospital admissions and general medicine populations: systematic review and meta-analysis.Frontiers in medicine · 2023Pooled it
- Good Outcome Following Attempted Resuscitation Score and Clinical Frailty Scale for Estimating Long-Term Mortality: An Ancillary Study of the CLEAR Randomized Clinical Trial.JAMA network open · 2025Trial
- Geographic and Temporal Differences in Sickle Cell Disease Hospitalizations in New York State.JAMA network open · 2026Article
- Factors influencing the length of hospital stay of people experiencing homelessness.Frontiers in public health · 2025Article
- Characteristics and Comorbidities Influencing Mortality Risk Among Hereditary Angioedema Patients.Journal of health economics and outcomes research · 2025Article
- Erratum: Characteristics and Comorbidities Influencing Mortality Risk Among Hereditary Angioedema Patients.Journal of health economics and outcomes research · 2025Article
- Virtual Home Care for Patients With Acute Illness.JAMA network open · 2024Article
- Using machine-learning methods to predict in-hospital mortality through the Elixhauser index: A Medicare data analysis.Research in nursing & health · 2023Article
- Predictivity of the comorbidity indices for geriatric syndromes.BMC geriatrics · 2022Article
- All Patient Refined-Diagnosis Related Groups' (APR-DRGs) Severity of Illness and Risk of Mortality as predictors of in-hospital mortality.Journal of medical systems · 2022Observational
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Authors and funding
7 authors.
Funding
Abstract
backgroundPatient risk adjustment is critical for hospital benchmarking and allocation of healthcare resources. However, considerable heterogeneity exists among measures.
objectivesThe 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.
methodsBinary 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.
resultsAll 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.
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