This 2023 article describes an algorithm to optimise home healthcare scheduling, claiming a 41% efficiency gain compared to current practice (manual planning without a quantitative basis).
A model-based evolutionary algorithm for home health care scheduling
Levels of planning
Strategic
- (Districting) Decide on the geographical coverage area of a home healthcare organisation
- (Home healthcare location problem) Decide where to locate home healthcare facilities across the geographical territory
Tactical
- (Dimensioning) Match the size and composition of the home care teams with local demand
- (Shift scheduling) Decide on shift patterns (start and end times, breaks, etc.) and assigning the number and type of care workers to each shift
Operational
- (Nurse rostering problem/operator assignment problem) Assigning care appointments to available working shifts or specific care workers
- (HHCRSP) Determine the timing and order in which care tasks should be carried out
Factors that can be optimised
Different studies have tried to optimise planning but each focus on different parts and none take all relevant factors into account:
- Focus op employee preferences rather than client preferences
- Focus on balancing workload between caregivers
- Focus on minimising number of caregivers that visit a patient