Publication Details
ESTHER ASARE
- NUGS-Anhui
- Information Security And Engineering (Phd)
- Anhui University Of Science And Technology
An Approach for Mining Multiple types of Silent Transitions in Business Process 14 Feb 2022
2021 IEEE Access
An Optimization Approach for Mining of Process Models with Infrequent Behaviors Integrating Data Flow and Control Flow 07 Sep 2021
scientific Programming
Discovery of effective infrequent sequences based on maximum probability path maximum probability path 07 Sep 2021
Taylor and Francis
IEEE
07 Sep 2021 | 15:38
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 ofEMRs/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.