IEEE Access · 2020 · 27 citations · 14 references
ComputingHealth InformaticsInformation SystemsElectronic Health RecordsHealth Information SystemsHealthcare Information SystemsHospital Information SystemsPetri NetsProcess MiningProcess ModelingWorkflow AnalysisWorkflow ManagementHospital Electronic Health RecordsHospital Workflow ManagementPetri Net AnalysisProcess Conformance CheckingProcess Mining In HealthcareSystem Event Log AnalysisWorkflow MiningWorkflow Modeling
Open Source Electronic Medical Records (EMR) and Electronic Health Records (EHR) are widely used in healthcare institutions because it is mostly free and customizable. Generally, EMRs and EHRs are used in healthcare institutions because their adoption reduces costs and improves patient outcomes through increased efficiency. During the adoption of EMRs/EHRs, whether open-source or closed-source, the number one concern of healthcare institutions is their workflow. When adopting any open-source software, there is a lot to consider, “Free does not mean you have to compromise on utility.” Process mining helps to discover and analyze the actual process executions of an information system (IS). In this paper, we use process mining to check the conformance of the workflow of Open-Source EMRs (workflow from event logs of an EMR) and the workflow of hospitals (workflow of hospitals based on domain knowledge). We modeled the workflow of hospital processes using business process modeling notation (BPMN) and converted it into a Petri net. Event log extracted from an Open-Source EMR (OpenEMR) was preprocessed for process conformance checking in ProM Framework. We check the conformance of log and model using alignment and replay. We display the results based on four metrics (fitness, precision, simplicity, and generalization). Then, we filter logs to check the conformance of Role-based access controls. Our conformance checking results showed that processes in Open-Source EMR align with the processes executed by hospitals.
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Process mining techniques: an application to stroke care.
Ronny S. Mans, Helen Schonenberg, Giorgio Leonardi et al. · PubMed · 2008 · 153 citations
Liaqat Ali, Ce Zhu, Noorbakhsh Amiri Golilarz et al. · IEEE Access · 2019 · 125 citations · Full text