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How can patient journey in surgical wards of a referral hospital be improved?


F Rezaei
M.H. Yarmohammadian
Y Molavi Taleghani
F Ghorat
B Alizadeh
M Vejdani

Abstract

Background: We studied the patient journey in surgical wards in order to find an effective and efficient way of scheduling in surgical wards.

Methods: We applied Root cause analysis (RCA) model within three months in a referral hospital. After understanding root causes of the events occurred through a focus discussion group, required interventions were proposed according to literatures, experiences, and preference of the stakeholders. Possible interventions were also analyzed based on its ability to reduce contributing factors in the events and the belief of process-owner that if interventions can be implemented.

Results: The results were provided for five main steps: 1) the most important root cause was “not prioritizing patients and pre-scheduling the number of surgical procedures in the days before”. 2) Constraints indicated that workforce weren't allocated proportionally to the number of surgical operations in varying shift lengths, increased numbers of on-calls physicians increased related costs, the admission of patients in VIP wards have been getting a high priority, and surgeon compensation based on fee for service method was challenging. 3) The current situation of allocating three rooms on average for each physician can be changed depending on numbers of surgeries. 4) Proposed interventions are establishing a computer registration system, reforming payment methods, setting up an electronic waiting list, development of scheduling guidelines, and Applying MIP model.

Conclusions: Implementing of scheduling reforms requires a comprehensive action plan system and predefined functional indicators. These should be achieved with considering comments of all clinical and technical groups to ensure the feasibility of an operating room schedule.

Keywords: patient journey, surgery, scheduling, Root cause analysis (RCA), patient transfer


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print ISSN: 1112-9867