On process mining in health care

With the increasing demand for health care, hospitals are looking for ways to optimize their care processes in order to increase efficiency, while guaranteeing the quality of the care. Process modeling is a crucial step for process improvement, since it provides a process model that can be analyzed and optimized. Process mining is a recent promising methodology to discover process models based on data from event logs. However, early applications of process mining to health care has produced overly complex models, which have been attributed to the complexity of the health care domain. In this paper, we argue that existing process mining methods fail to identify good process models, even for well-defined clinical processes. We identify a number of reasons for this shortcoming and discuss a few directions for extending process mining methods in order to make them more suitable for the clinical domain

Prognostic immunohistochemical biomarkers of chemotherapy efficacy in biliary tract cancer: A systematic review and meta-analysis

Introduction: Chemotherapy is the mainstay of systemic treatment of biliary tract cancer (BTC). However, the treatment response to chemotherapy varies between patients. Currently, no prognostic biomarkers for chemotherapy efficacy have been considered for use in clinical practice. A systematic review was conducted to evaluate the prognostic value of immunohistochemical biomarkers for chemotherapy in patients with resected as well as with advanced BTC. Method: Medline and EMBASE databases were searched up to March 2017 for studies that evaluated biomarker expression by immunohistochemistry in resected or advanced BTC patients treated with chemotherapy. The primary endpoints were overall survival (OS) and disease or progression free survival (DFS or PFS). Result: Twenty-six studies, including a total of 1348 patients and 26 different biomarkers, met the inclusion criteria and were included in this review. The most frequently studied prognostic biomarkers in BTC were the human Equilibrative Nucleoside Transporter 1 (hENT1), Ribonucleotide Reductase M1 (RRM1), and excision repair cross-complementation 1 (ERCC1). In the meta-analysis of patients treated with gemcitabine-based chemotherapy, high hENT1 expression was associated with longer OS (HR 0.43, 95% CI: 0.28 to 0.64) and DFS/PFS (HR 0.45, 95% CI: 0.33 to 0.61). Conclusion: hENT1 is a promising prognostic biomarker for gemcitabine-based chemotherapy in resected as well as in advanced BTC and should be further validated for the selection of patients for chemotherapy