Relative importance of clinical and sociodemographic factors in association with post‐operative in‐hospital deaths in colorectal cancer patients in New South Wales: An artificial neural network approach

Abstract

Rationale, Aims and Objectives: Co-morbidities in colorectal cancer patients complicate hospital care, and their relative importance to post-operative deaths is largely unknown. This study was conducted to examine a range of clinical and sociodemographic factors in relation to post-operative in-hospital deaths in colorectal cancer patients and identify whether these contributions would vary by severity of co-morbidities. Methods: In this multicentre retrospective cohort study, we used the complete census of New South Wales inpatient data to select colorectal cancer patients admitted to public hospitals for acute surgical care, who underwent procedures on the digestive system during the period of July 2001 to June 2014. The primary outcome was inhospital death at the end of acute care. Multilayer perceptron and back-propagation artificial neural networks (ANNs) were used to quantify the relative importance of a wide range of clinical and sociodemographic factors in relation to post-operative deaths, stratified by severity of co-morbidities based on Charlson co-morbidity index. Results: Of 6288 colorectal cancer patients, approximately 58.3% (n = 3669) had moderate to severe co-morbidities. A total of 464 (7.4%) died in hospitals. The performance for ANN models was superior to logistic models. Co-morbid musculoskeletal and mental disorders, adverse events in health care, and socioeconomic factors including rural residence and private insurance status contributed to post-operative deaths in hospitals. Conclusion: Identification of relative importance of factors contributing to inhospital deaths in colorectal cancer patients using ANN may help to enhance patient-centred strategies to meet complex needs during acute surgical care and prevent post-operative in-hospital deaths.