In recent years, most hospitals have implemented Electronic Health Records to manage and integrate a wide range of medical information, including diagnostics, medication admission and laboratory test results. Certain laboratory variables may serve as indicators of a patient's clinical deterioration, making laboratory data a valuable tool for identifying high-risk patients. This work introduces a framework for predicting imminent health outcomes (IHO) of multimorbidity patients using laboratory test data. Our cohort includes 322,316 multimorbidity patients that performed laboratory tests in a large teaching hospital between January 2007 and August 2021. Two Imminent Health Outcomes predictive tools were developed. The first considers all patients in the dataset. The second was developed using a subset of patients with Heart Failure (HF) as the main comorbidity (5% of the entire dataset), considering that HF is a highly prevalent syndrome in multimorbidity patients. This predictive model achieved a reasonable predictive performance (AUROC = 0.718, 95% CI 0.708-0.756, and AUPRC = 0.663, 95% CI 0.630-0.701). C-reactive protein and NT-proBNP are the lab tests that most positively contribute to the prediction of IHO. The IHO predictive tool has the potential to help the medical team identify patients at high-risk of an imminent adverse event, highlighting the laboratory variables that are most contributing to the deterioration of the patient.

The authors have declared no competing interest.

This work was developed by the IntelligentCare project LISBOA-01-0247-FEDER-045948 that is co-financed by the ERDF/LISBOA2020 and by FCT under CMU-Portugal and by FCT under projects UIDB/50021/2020, UIDB/00408/2020, UIDP/00408/2020.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Ethics committee/IRB of Hospital da Luz Lisboa gave ethical approval for this work

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