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Title

Administrative and Claims Data Help Predict Patient Mortality in Intensive Care Units by Logistic Regression: A Nationwide Database Study.

Authors

Hsu, Yu-Ting; He, Yi-Ting; Ting, Chien-Kun; Tsou, Mei-Yung; Tang, Gau-Jun; Pu, Christy

Abstract

Background. Increasing attention has been paid to the predictive power of different prognostic scoring systems for decades. In this study, we compared the abilities of three commonly used scoring systems to predict short-term and long-term mortalities, with the intention of building a better prediction model for critically ill patients. We used the data from the National Health Insurance Research Database (NHIRD) in Taiwan, which included information on patient age, comorbidities, and presence of organ failure to build a new prediction model for short-term and long-term mortalities. Methods. We retrospectively collected the medical records of patients in the intensive care unit of a regional hospital in 2012 and linked them to the claims data from the NHIRD. The Acute Physiology and Chronic Health Evaluation II (APACHE II) score, Elixhauser Comorbidity Index (ECI), and Charlson Comorbidity Index (CCI) were compared for their predictive abilities. Multiple logistic regression tests were performed, and the results were presented as receiver operating characteristic curves and C-statistic. Results. The APACHE II score has the best predictive power for inhospital mortality (0.79; C − statistic = 0.77 − 0.83) and 1-year mortality (0.77; C − statistic = 0.74 − 0.79). The ECI and CCI alone have poorer predictive power and need to be combined with other variables to be comparable to the APACHE II score, as predictive tools. Using CCI together with age, sex, and whether or not the patient required mechanical ventilation is estimated to have a C-statistic of 0.773 (95% CI 0.744-0.803) for inhospital mortality, 0.782 (95% CI 0.76-0.81) for 30-day mortality, and 0.78 (95% CI 0.75-0.80) for 1-year mortality. Conclusions. We present a new prognostic model that combines CCI with age, sex, and mechanical ventilation status and can predict mortality, comparable to the APACHE II score.

Subjects

TAIWAN; AGE distribution; APACHE (Disease classification system); COMPARATIVE studies; CONFIDENCE intervals; CRITICALLY ill; INTENSIVE care units; MEDICAL records; NATIONAL health services; PATIENTS; RISK assessment; SEX distribution; COMORBIDITY; LOGISTIC regression analysis; HEALTH insurance reimbursement; BIBLIOGRAPHIC databases; MULTIPLE regression analysis; RETROSPECTIVE studies; RECEIVER operating characteristic curves; HOSPITAL mortality; ACQUISITION of data methodology

Publication

BioMed Research International, 2020, p1

ISSN

2314-6133

Publication type

Academic Journal

DOI

10.1155/2020/9076739

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