Psychiatric outpatients flow and waiting time improvement using PDSA and RCA techniques - Payesh (Health Monitor)
Volume 15, Issue 4 (July-August 2016)                   Payesh 2016, 15(4): 372-385 | Back to browse issues page

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1- Islamic Azad University, Tehran North Branch, Tehran, Iran
2- Islamic Azad University, Sciences and Research Branch, Tehran, Iran
Abstract:   (3772 Views)
Objective (s): Waits and delays are symptoms of disrupted patient flow that has a negative effect on patient satisfaction, staff retention and referrals. This research aimed to study on psychiatric outpatients’ flow of a medical center in Tehran (name withheld) and their waiting time improvement in the summer of 2014.
Methods: This was a cross-sectional study and convenience sampling method was used. The mean waiting time at each service station was calculated with Minitab software and bottleneck was found. To find the relationship between other variables and waiting time in the bottleneck, linear regression analysis was used. Root causes were identified with Root Cause Analysis (RCA) then preventive measures were proposed and their impact on waiting time was tested by Delphi method which used in the “Do” phase of the cycle of planning, implementation, study and act (PDSA), and action plans were proposed in the “Act” phase to improve waiting times.
Results: Time measurement showed interview station has the highest average waiting time of 27.37 minutes. Linear regression analysis showed that the number of patients waiting, impact the waiting time. In this study the lack of funding, lack of job satisfaction, vague job descriptions and non-compliance with the standard timeframe for meeting patients, were identified as the root causes of long waiting times.
Conclusion: Since the interview station was known as a bottleneck of the process, implementation of strategies such as realistic staff employment, providing opportunities to personal improvement, staff encouragement based on performance evaluation results, making a friendly environment in workplace, will improve waiting time in bottleneck.
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type of study: Descriptive |
Accepted: 2018/03/9 | ePublished ahead of print: 2016/07/20 | Published: 2016/07/15

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