X. Cai, O. Perez-Concha, E. Coiera, F. Martin-Sanchez, R. Day, D. Roffe and B. Gallego. (2015). Real-time prediction of mortality, readmission, and length of stay using electronic health record data. J Am Med Inform Assoc.

Abstract: OBJECTIVE: To develop a predictive model for real-time predictions of length of stay, mortality, and readmission for hospitalized patients using electronic health records (EHRs). MATERIALS AND METHODS: A Bayesian Network model was built to estimate the probability of a hospitalized patient being “at home,” in the hospital, or dead for each of the next

O. P. Concha, B. Gallego, K. Hillman, G. P. Delaney and E. Coiera. (2014). Do variations in hospital mortality patterns after weekend admission reflect reduced quality of care or different patient cohorts? A population-based study. BMJ Qual Saf (Vol. 23, pp. 215-22).

Abstract: BACKGROUND: Proposed causes for increased mortality following weekend admission (the ‘weekend effect’) include poorer quality of care and sicker patients. The aim of this study was to analyse the 7 days post-admission time patterns of excess mortality following weekend admission to identify whether distinct patterns exist for patients depending upon the relative contribution of

E. Coiera, Y. Wang, F. Magrabi, O. P. Concha, B. Gallego and W. Runciman. (2014). Predicting the cumulative risk of death during hospitalization by modeling weekend, weekday and diurnal mortality risks. BMC Health Serv Res (Vol. 14, pp. 226).

Abstract: BACKGROUND: Current prognostic models factor in patient and disease specific variables but do not consider cumulative risks of hospitalization over time. We developed risk models of the likelihood of death associated with cumulative exposure to hospitalization, based on time-varying risks of hospitalization over any given day, as well as day of the week. Model