Evaluation of the clinical process in a critical care information system using the Lean method: a case study
Yusof Maryati Mohd, Khodambashi Soudabeh, Mokhtar Ariffin Marzuki
BMC Medical Informatics and Decision Making · 2012
doi:10.1186/1472-6947-12-150 (opens in a new tab)
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Abstract
<p>Abstract</p> <p>Background</p> <p>There are numerous applications for Health Information Systems (HIS) that support specific tasks in the clinical workflow. The Lean method has been used increasingly to optimize clinical workflows, by removing waste and shortening the delivery cycle time. There are a limited number of studies on Lean applications related to HIS. Therefore, we applied the Lean method to evaluate the clinical processes related to HIS, in order to evaluate its efficiency in removing waste and optimizing the process flow. This paper presents the evaluation findings of these clinical processes, with regards to a critical care information system (CCIS), known as IntelliVue Clinical Information Portfolio (ICIP), and recommends solutions to the problems that were identified during the study.</p> <p>Methods</p> <p>We conducted a case study under actual clinical settings, to investigate how the Lean method can be used to improve the clinical process. We used observations, interviews, and document analysis, to achieve our stated goal. We also applied two tools from the Lean methodology, namely the Value Stream Mapping and the A3 problem-solving tools. We used eVSM software to plot the Value Stream Map and A3 reports.</p> <p>Results</p> <p>We identified a number of problems related to inefficiency and waste in the clinical process, and proposed an improved process model.</p> <p>Conclusions</p> <p>The case study findings show that the Value Stream Mapping and the A3 reports can be used as tools to identify waste and integrate the process steps more efficiently. We also proposed a standardized and improved clinical process model and suggested an integrated information system that combines database and software applications to reduce waste and data redundancy.</p>
Abstract licence: CC BY-NC-ND
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