ArticleBMC health services research2008
Performance of in-hospital mortality prediction models for acute hospitalization: hospital standardized mortality ratio in Japan.
Article in BMC health services research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 27 citations in OpenAlex.
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- Hospital mortality in older patients in the Brazilian Unified Health System, Southeast region.Revista de saude publica · 2018Observational
- Use of risk-adjusted CUSUM charts to monitor 30-day mortality in Danish hospitals.Clinical epidemiology · 2018Article
- Hierarchical Genetic Algorithm and Fuzzy Radial Basis Function Networks for Factors Influencing Hospital Length of Stay Outliers.Healthcare informatics research · 2017Article
- Surgical risk model for acute diffuse peritonitis based on a Japanese nationwide database: an initial report on the surgical and 30-day mortality.Surgery today · 2015Article
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- Predicting the cumulative risk of death during hospitalization by modeling weekend, weekday and diurnal mortality risks.BMC health services research · 2014Article
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- A simple insightful approach to investigating a hospital standardised mortality ratio: an illustrative case-study.PloS one · 2013Article
- Efficacy of a numerical value of a fixed-effect estimator in stochastic frontier analysis as an indicator of hospital production structure.BMC health services research · 2012Article
- Derivation and validation of a risk adjustment model for predicting seven day mortality in emergency medical admissions: mixed prospective and retrospective cohort study.BMJ (Clinical research ed.) · 2012Article
- Assessment of hospital performance with a case-mix standardized mortality model using an existing administrative database in Japan.BMC health services research · 2010Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveIn-hospital mortality is an important performance measure for quality improvement, although it requires proper risk adjustment. We set out to develop in-hospital mortality prediction models for acute hospitalization using a nation-wide electronic administrative record system in Japan.
methodsAdministrative records of 224,207 patients (patients discharged from 82 hospitals in Japan between July 1, 2002 and October 31, 2002) were randomly split into preliminary (179,156 records) and test (45,051 records) groups. Study variables included Major Diagnostic Category, age, gender, ambulance use, admission status, length of hospital stay, comorbidity, and in-hospital mortality. ICD-10 codes were converted to calculate comorbidity scores based on Quan's methodology. Multivariate logistic regression analysis was then performed using in-hospital mortality as a dependent variable. C-indexes were calculated across risk groups in order to evaluate model performances.
resultsIn-hospital mortality rates were 2.68% and 2.76% for the preliminary and test datasets, respectively. C-index values were 0.869 for the model that excluded length of stay and 0.841 for the model that included length of stay.
conclusionRisk models developed in this study included a set of variables easily accessible from administrative data, and still successfully exhibited a high degree of prediction accuracy. These models can be used to estimate in-hospital mortality rates of various diagnoses and procedures.
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