A Data-Driven Approach to Support the Understanding and Improvement of Patients' Journeys: A Case Study Using Electronic Health Records of an Emergency Department.

OBJECTIVES: Given the increasing availability of electronic health records, it has become increasingly feasible to adopt data-driven approaches to capture a deep understanding of the patient journeys. Nevertheless, simply using data-driven techniques to depict the patient journeys without an integrated modeling and analysis approach is proving to be of little benefit for improving patients' experiences. Indeed, a model of the journey patterns is necessary to support the improvement process. METHODS: We presented a 3-phase methodology that integrates a process mining-based understanding of patient journeys with a stochastic graphical modeling approach to derive and analyze the analytical expressions of some important performance indicators of an emergency department including mean and variance of patients' length of stay (LOS). RESULTS: Analytical expressions were derived and discussed for mean and variance of LOS times and discharge and admission probabilities. LOS differed significantly depending on whether a patient was admitted to the hospital or discharged. Moreover, multiparameter sensitivity equations are obtained to identify which activities contribute the most in reducing the LOS at given operating conditions so decision makers can prioritize their improvement initiatives. CONCLUSIONS: Data-driven based approaches for understanding the patient journeys coupled with appropriate modeling techniques yield a promising tool to support improving patients' experiences. The modeling techniques should be easy to implement and not only should be capable of deriving some key performance indicators of interest but also guide decision makers in their improvement initiatives.

Process Mining-Based Method of Designing and Optimizing the Layouts of Emergency Departments in Hospitals.

OBJECTIVE: This article proposes an approach to help designers analyze complex care processes and identify the optimal layout of an emergency department (ED) considering several objectives simultaneously. These objectives include minimizing the distances traveled by patients, maximizing design preferences, and minimizing the relocation costs. BACKGROUND: Rising demand for healthcare services leads to increasing demand for new hospital buildings as well as renovating existing ones. Operations management techniques have been successfully applied in both manufacturing and service industries to design more efficient layouts. However, high complexity of healthcare processes makes it challenging to apply these techniques in healthcare environments. METHOD: Process mining techniques were applied to address the problem of complexity and to enhance healthcare process analysis. Process-related information, such as information about the clinical pathways, was extracted from the information system of an ED. A goal programming approach was then employed to find a single layout that would simultaneously satisfy several objectives. RESULTS: The layout identified using the proposed method improved the distances traveled by noncritical and critical patients by 42.2% and 47.6%, respectively, and minimized the relocation costs. CONCLUSION: This study has shown that an efficient placement of the clinical units yields remarkable improvements in the distances traveled by patients.