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work schedules in healthcare organisations is a complex and time-consuming activity that affects healthcare
workers all over the world daily. It's especially difficult because different personnel requirements exist on
different days and shifts, resulting in a variety of constraints (Zhu, Tong, Low, Lau, Chen, & Wang, 2019).
Personnel scheduling, also known as rostering, is the method of creating work schedules for employees so
that a company can meet the demand for its products or services (Ernst, Jiang, Krishnamoorthy, & Sier, 2004).
The majority of healthcare workers do use a manual system to keep track of their schedules. The schedulers
must also be mindful of the doctors who are on call and who are on vacation. An operation may be conducted
without a scheduled anaesthetist due to a scheduling error (Scholiadis, du Toit, & Sevel, 2005). Overestimation
of operational time results in unused operating rooms, whereas underestimation results in unplanned extra work
or case cancellation, all of which may raise costs (Wright, Kooperberg, Bonar, & Bashein, 1996).

3. Methodology

3.1. The Existing System

HCTM uses a manual technique to generate an anaesthetist rostering. The roster is prepared for every month
and week. Mostly, the whole process is done by the roster maker which is the head of the anesthesiology
department.

3.2. The Proposed System

The proposed system is the anaesthetist rostering web application. This web application will prepare the
roster for the anaesthetist into shifts based on workstation demand and requirement. This system generates a
new duty roster every month. The roster maker can manage the workstation demand and next the system can
generate the roster for the anaesthetist.

3.3. Use Case Diagram

The use case diagram for the proposed system as shown in Fig. 1. depicts the actors (anaesthetist and admin)
and their interactions with the system.

Fig. 1. Use Case for anaesthetist rostering web application

E- Proceedings of The 5th International Multi-Conference on Artificial Intelligence Technology (MCAIT 2021) [29]
Artificial Intelligence in the 4th Industrial Revolution