Mechanism to Visualize Workload of Doctor & Ward for Resource Planning

This abstract has open access
Abstract Description
Abstract ID :
HAC777
Submission Type
Proposed Topic (Most preferred): :
Staff Engagement and Empowerment (motivating staff / teamwork / work revamp tackling manpower issue / staff wellness / OSH / retention)
Authors (including presenting author) :
Cheung E(1), Fong WC(2), Cheung YF(2), Yao S(2), Leung C(2), Cheng WY(2), Law MY(2), Lam I(2), Mak C(3), Cheng W(3), Lee H(3), Tsang K(3)
Affiliation :
(1)Queen Elizabeth Hospital, (2)Department of Medicine, Queen Elizabeth Hospital, (3)IT Department, Kowloon Central Cluster
Introduction :
The patient volume of QEH Medical Department is among the highest in HA. An effective manpower allocation to improve doctors and wards’ efficiency is critical. In 2022-23, the Ward e-Whiteboard and Doctor Dashboard systems were launched to facilitate supervisors, doctors and wards for such purpose.
Objectives :
1) Enable supervisor to identify pressure areas and overloaded doctors required workload re-allocation, 2) facilitate doctor to access patient list under care with key parameters for patient care prioritization, and 3) enable nurses to access real-time bed situation in ward and identify patients required attention.
Methodology :
The 2 systems were piloted in 2 medical wards in Oct 2022 and rollout to 24 medical wards by Apr 2023. For each ward, the Ward e-Whiteboard was setup in TV to show the occupied bed/patient list grouped under respective doctor in charge. Indicators like new case, pending discharge, etc are included for patients required attention. For individual doctor, the i-Pad based Doctor Dashboard would show the patient list under care. Essential patient parameters including diagnosis, ventilator status, an AI-predicted status in coming 24 hours, etc are included for doctor to prioritize patient care and ward round order. Supervisor’s dashboard is showing the workload distribution among individual doctor/team/ward by new case number, patients required special attention, average length of stay and other workload indicators. Besides, the concerned workload information can be visualized graphically to show the trend over time.
Result & Outcome :
By year end 2023, total 49,574 episodes were handled by the systems and review was conducted with respective users. Supervisors agreed the dashboard enabling them to master the patient distribution and condition to arrange manpower for first round, second round & holiday round plus prioritization of new case admission after 2pm. It also helps to identify overloaded wards and doctors. Individual doctor agreed the system facilitates them assessing patient list off-site in consolidated view regardless of patient location. It also provides a hint for their work priority. In ward, the Ward e-Whiteboard is a useful communication platform to identify patients required attention. It is useful for departmental meeting to facilitate discussion and planning. In future, the data exchange with other HA systems would enhance the systems’ usefulness.
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