The analysis and evaluation of the patient transportation program

Abstract

This study aims to evaluate and analyze the performance of the Patient Transportation Program using retrospective data from May 2023 to September 2024. The findings revealed a total of 205,371 transportation requests, but after data cleansing to remove duplicates and system test entries, 194,071 valid requests remained, accounting for 94.54% of the total requests. The analysis identified several issues in recording timestamp data at various moments, including 82,730 instances (40.8%) of initiating transport before patient pickup and 7,708 instances (3.8%) of completing service before the start. Additionally, 3,859 instances (1.89%) of scheduling after order acceptance were noted, primarily due to delayed data entry and system inefficiencies.

The workload analysis showed that afternoon shifts had the highest workload, averaging 19 tasks per staff member per shift, followed by night shifts at 17 tasks and morning shifts at 16 tasks per staff member per shift. Regarding patient satisfaction, 97.1% of the feedback gave a score of 0, possibly due to the inconvenience of the feedback process. Simplifying the evaluation process through QR codes or mobile applications could improve response rates and service quality.

The use of real-time data entry technology and in-depth data analysis (Big Data Analytics) can significantly improve resource allocation and decision-making accuracy, enhancing the overall efficiency of the Patient Transportation Program.

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