Continuity and Efficiency in Home Care

Introduction

Home care scheduling faces a dual challenge: maximizing continuity of care relationships while operating cost-effectively. Manual scheduling often results in these goals conflicting – fewer unique caregivers per client costs more in travel time, while optimal route planning creates fragmented care relationships.

This research article analyzes a real, optimized two-week schedule from a home care operation in the Stockholm area. By applying scientifically proven methods from Home Health Care Routing and Scheduling Problem (HHCRSP) research, we demonstrate that continuity and efficiency need not be in opposition.

Scientific Background

HHCRSP (Home Health Care Routing and Scheduling Problem) is a complex optimization problem that integrates route planning and scheduling for care personnel. It is an extension of the classical Vehicle Routing Problem (VRP) but with healthcare-specific constraints and objectives.

HHCRSP: Research and Practice

HHCRSP is recognized as a significant variant within the category of Workforce Scheduling and Routing Problems (WSRP) and has been the subject of extensive academic research since the mid-2000s. To optimize continuity, multi-period models are required as the goal of maintaining the same caregiver with the same client necessarily extends over multiple days.

Continuity Metrics

Number of unique caregivers per client (simplest, but doesn't scale with visit frequency)
Continuity of Care Index (CCI) – more sophisticated measure accounting for visit distribution
Kolada N00941 – Swedish standard recommending <11 unique caregivers per client

Methodology

The analysis is based on a real two-week schedule from a home care operation in the Stockholm area, optimized with an AI-driven scheduling platform based on advanced metaheuristics. The schedule reconciles to the second: paid shift time equals visits, travel, waiting and breaks combined.

Data

120 home care recipients
3,227 planned visits
26 caregivers working 274 shifts (day 07–16, evening 16–22)
14-day planning horizon

Key Findings

Continuity: 5.67 unique caregivers

Each client met 5.67 unique caregivers on average over the 14 days – well below the Kolada target of 11 and the national average of 16 (Socialstyrelsen 2021).

Care time: 79.1%

1,335 h 41 min of 1,688 h 24 min available working time, excluding breaks, was spent on client visits.

Travel efficiency: 83.2%

Of the time spent on visits and travel, 83.2% went to visits: 1,335 h 41 min with clients against 270 h 17 min of travel.

The schedule adds up

The 274 shifts gave 1,765 h 24 min of paid time: 1,335 h 41 min of visits, 270 h 17 min of travel, 82 h 26 min of waiting and 77 h of breaks – with nothing unaccounted for.

Compared with the national average of 16 unique caregivers (Socialstyrelsen 2021), that is almost two-thirds fewer – while 79.1% of available working time went to visits.

The results clearly show that continuity and efficiency are not a zero-sum game when intelligent AI optimization is applied.

Discussion

The results have practical implications for all stakeholders in home care:

For Municipalities

Compare travel time against the same source schedule for each scenario
Systematically achieve Kolada N00941 target (<11 unique caregivers)
High care time (79.1% in the analysis) means better resource utilization

For Caregivers

More predictable schedules with fewer ad-hoc changes
Opportunity to build continuous client relationships

For Clients

From the national average of 16 down to fewer than 6 unique caregivers
Research shows continuity leads to better health outcomes

References

Conclusion

AI-based optimization of home care scheduling can deliver high continuity and high efficiency at the same time. A real two-week schedule in the Stockholm area shows 5.67 unique caregivers per client (well below the Kolada target of 11), 79.1% care time and 83.2% travel efficiency – in a schedule whose paid time adds up to the minute.

For municipalities interested in starting a pilot study with AI-optimized scheduling, conducting cost-benefit analysis, or discussing implementation – contact Caire.se.

Continuity and Efficiency in Home Care: AI Optimization