A SITUATIONAL METHOD FOR HEALTHCARE BUSINESS PROCESS IMPROVEMENT
dc.contributor.author | Ondimu, K. O. | |
dc.contributor.author | Muketha, Geoffrey M. | |
dc.contributor.author | Lukandu, I. A. | |
dc.contributor.author | Omieno, K. K. | |
dc.date.accessioned | 2019-11-01T14:02:21Z | |
dc.date.available | 2019-11-01T14:02:21Z | |
dc.date.issued | 2018-10 | |
dc.identifier.uri | http://hdl.handle.net/123456789/4361 | |
dc.description.abstract | Healthcare business processes are complex due to the many decisions and procedures captured, are highly dynamic, increasingly multidisciplinary and ad hoc which makes it difficult to achieve any meaningful improvement through control flow improvement. This study aims at developing and validating a method for healthcare business process improvement with extensions of process mining and visual analytics. Situational method engineering is used to develop a method for healthcare business process improvement and validated through simulations using synthetic event-logs. The results show that the throughput for all resource combinations gravitates to 1 hour after a simulation period of two hours in the original KPI. A new KPI with the lower upper bounds at 0.091 hours and medium upper bound 0.132 hours posts an average throughput of 0.94387hours (56.63 minutes) compared to the original 1.11hours (66.6 minutes) when two testers and one Solver (Complex) are added. This demonstrates the effectiveness of the method. It is also proven that deployment of resources on the most common trace has the highest impact on throughput reduction. Further testing of the method using real life or field data is to be carried out in future. | en_US |
dc.language.iso | en | en_US |
dc.subject | Process Mining | en_US |
dc.subject | Visual Analytics | en_US |
dc.subject | Method | en_US |
dc.subject | Simulation | en_US |
dc.subject | Improvement | en_US |
dc.subject | Throughput | en_US |
dc.subject | Healthcare | en_US |
dc.title | A SITUATIONAL METHOD FOR HEALTHCARE BUSINESS PROCESS IMPROVEMENT | en_US |
dc.type | Article | en_US |
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