Too long for comfort: Tackling consultation wait time at a hospital emergency department

In early 2019, Alan Jay, an executive in the Quality, Safety and Risk Management (QSRM) department of Gloria Hospital, a full-service hospital that specialised in children and women healthcare, had been requested to gather insights and seek improvements to the pre-consultation waits at the hospital’...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: ANG, Marcus, HU, Arthur Ruey Heng, LAM, Sean Shao Wei
التنسيق: text
اللغة:English
منشور في: Institutional Knowledge at Singapore Management University 2020
الموضوعات:
الوصول للمادة أونلاين:https://ink.library.smu.edu.sg/cases_coll_all/357
https://smu.sharepoint.com/sites/admin/CMP/cases/SMU-20-BATCH%20%5BPDF-Pic%5D/SMU-20-0027%20%5BGloria%20H%5D/SMU-20-0027%20%5BGloria%20H%5D.pdf
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المؤسسة: Singapore Management University
اللغة: English
الوصف
الملخص:In early 2019, Alan Jay, an executive in the Quality, Safety and Risk Management (QSRM) department of Gloria Hospital, a full-service hospital that specialised in children and women healthcare, had been requested to gather insights and seek improvements to the pre-consultation waits at the hospital’s Children’s Emergency (CE) department. After an initial study, minor schedule adjustments were put into place, with many shifts starting one hour in advance to reduce snowballing of patients awaiting consultation. However, post-implementation data suggested that the patient load to capacity ratios remained uneven across each day of the week. Subsequently, a team of operations professors and students were assembled to join Jay in a second phase of the Children’s Emergency Consultation Queue (CECQ) project, started April 2019, to better understand the actual waiting time of patients at the CE. This case can be used in undergraduate and graduate classes to illustrate the effectiveness of mathematical programming in a healthcare setting, and appreciate the balance between an operations approach and a service approach. Students are expected to derive a suitable model to determine a scheduling policy. The case reinforces the students’ skills in data processing, mathematical modelling, and numerical computation.