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Healthcare processes of laboratory tests for the prediction of mortality in the intensive care unit: a retrospective study based on electronic healthcare records in the USA.

ABSTRACT: OBJECTIVES:Healthcare process carries important prognostic information for patients, but the healthcare processes of laboratory tests have not yet been investigated for patients in the intensive care unit (ICU). The study aimed to investigate the effect of healthcare processes of laboratory tests on hospital mortality, with the hypothesis that the addition of healthcare processes could improve the discrimination for mortality outcome. DESIGN:The study included 12 laboratory tests. There were two dimensions for each laboratory test. One was the pathophysiology value; and the other was the healthcare process variables including the clock hour, the number of measurements and the measurement time from ICU admission. Generalised additive model was employed to investigate the effect of continuous variables on mortality. Generalised linear models with and without healthcare process variables were compared for their discrimination power. SETTING:ICUs in an US-based hospital. PARTICIPANTS:Adult patients included in the critical care big data Medical Information Mart for Intensive Care. PRIMARY AND SECONDARY OUTCOME MEASURES:The hospital mortality was the primary outcome. RESULTS:A total of 52?963 adult patients with complete ICU stay information were included for analysis. The mortality rate was 12.3%. Lower number of tests such as 1-3 times were associated with the lowest mortality for most laboratory tests. However, the hematocrit, glucose and potassium required 6-10 measurements for the first 24?hours to reach the lowest mortality rate. In n of the 12 prediction models involving laboratory tests, the addition of healthcare process variables was associated with significantly increased area under receiver operating characteristics. CONCLUSIONS:The study showed that healthcare processes of laboratory tests were independently associated with hospital mortality. The addition of healthcare processes to the pathophysiology value could increase the discrimination for mortality outcome.

SUBMITTER: Zhang Z

PROVIDER: S-EPMC6597637 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Healthcare processes of laboratory tests for the prediction of mortality in the intensive care unit: a retrospective study based on electronic healthcare records in the USA.

Zhang Zhongheng Z Goyal Hemant H Lange Theis T Hong Yucai Y

BMJ open 20190624 6

<h4>Objectives</h4>Healthcare process carries important prognostic information for patients, but the healthcare processes of laboratory tests have not yet been investigated for patients in the intensive care unit (ICU). The study aimed to investigate the effect of healthcare processes of laboratory tests on hospital mortality, with the hypothesis that the addition of healthcare processes could improve the discrimination for mortality outcome.<h4>Design</h4>The study included 12 laboratory tests. ...[more]

PMID: 31239303

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Project description:BackgroundDespite wide use of severity scoring systems for case-mix determination and benchmarking in the intensive care unit (ICU), the possibility of scoring bias across ethnicities has not been examined. Guidelines on the use of illness severity scores to inform triage decisions for allocation of scarce resources, such as mechanical ventilation, during the current COVID-19 pandemic warrant examination for possible bias in these models. We investigated the performance of the severity scoring systems Acute Physiology and Chronic Health Evaluation IVa (APACHE IVa), Oxford Acute Severity of Illness Score (OASIS), and Sequential Organ Failure Assessment (SOFA) across four ethnicities in two large ICU databases to identify possible ethnicity-based bias.MethodsData from the electronic ICU Collaborative Research Database (eICU-CRD) and the Medical Information Mart for Intensive Care III (MIMIC-III) database, built from patient episodes in the USA from 2014-15 and 2001-12, respectively, were analysed for score performance in Asian, Black, Hispanic, and White people after appropriate exclusions. Hospital mortality was the outcome of interest. Discrimination and calibration were determined for all three scoring systems in all four groups, using area under receiver operating characteristic (AUROC) curve for different ethnicities to assess discrimination, and standardised mortality ratio (SMR) or proxy measures to assess calibration.FindingsWe analysed 166 751 participants (122 919 eICU-CRD and 43 832 MIMIC-III). Although measurements of discrimination were significantly different among the groups (AUROC ranging from 0·86 to 0·89 [p=0·016] with APACHE IVa and from 0·75 to 0·77 [p=0·85] with OASIS), they did not display any discernible systematic patterns of bias. However, measurements of calibration indicated persistent, and in some cases statistically significant, patterns of difference between Hispanic people (SMR 0·73 with APACHE IVa and 0·64 with OASIS) and Black people (0·67 and 0·68) versus Asian people (0·77 and 0·95) and White people (0·76 and 0·81). Although calibrations were imperfect for all groups, the scores consistently showed a pattern of overpredicting mortality for Black people and Hispanic people. Similar results were seen using SOFA scores across the two databases.InterpretationThe systematic differences in calibration across ethnicities suggest that illness severity scores reflect statistical bias in their predictions of mortality.FundingThere was no specific funding for this study.

Dataset Information

Healthcare processes of laboratory tests for the prediction of mortality in the intensive care unit: a retrospective study based on electronic healthcare records in the USA.

Publications

Healthcare processes of laboratory tests for the prediction of mortality in the intensive care unit: a retrospective study based on electronic healthcare records in the USA.

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