Route Optimization for Home Care

    Minimize travel time and maximize care time

    30%less driving distance
    15%more care time
    25%less travel time
    100%AI-optimized
    app.caire.se/schedules/nacka?mode=map
    Caire
    Översikt
    Schema
    Jämför
    Resurser
    Organisation
    SVBE
    7 min2 min9 min
    Namn
    07:00
    07:30
    08:00
    08:30
    09:00
    ALAnna Lind
    JBJohan Berg
    SHSara Holm
    MEMaria Ek
    ESErik Ström
    6m
    8m
    8m
    5m
    5m
    7m
    7m
    9m
    9m
    6m
    Astrid N. · Morgonomsorg
    AL07:00–07:45
    Olof H. · Frukost
    AL07:50–08:15
    Greta B. · Morgonomsorg
    AL08:25–09:00
    Gunnar P. · Morgonomsorg
    JB07:05–07:40
    Vera S. · Frukost
    JB07:50–08:15
    Nils F. · Morgonomsorg
    JB08:20–08:55
    Britta S. · Dusch
    SH07:05–07:40
    Sven A. · Morgonomsorg
    SH07:45–08:25
    Ester L. · Frukost
    SH08:30–08:55
    Karl O. · Morgonomsorg
    ME07:05–07:40
    Margit E. · Frukost
    ME07:45–08:10
    Holger M. · Morgonomsorg
    ME08:20–08:55
    Elsa T. · Morgonomsorg
    ES07:05–07:45
    Rune K. · Frukost
    ES07:50–08:15
    Åke T. · Dusch
    ES08:20–08:55
    Restid i rutten
    −15%261 h → 222 h
    Selected employee route: geography, visits, and calendar context stay visible together.

    Challenges with traditional route planning

    Route planning in home care is a complex task that often requires consideration of many factors simultaneously. Traditional methods struggle with:

    Complex visit patterns

    Varying visit times, specific time windows, different skill requirements, and clients who need to be visited multiple times per day create a difficult puzzle to solve.

    Manual optimization is almost impossible

    Manually planning optimal routes for a team of caregivers who need to visit dozens of clients is mathematically too complex to be solved efficiently by a human.

    Changing conditions

    Traffic conditions, sick leave, emergency visits, and other unforeseen events require quick adjustments that are difficult to make manually in an optimal way.

    High costs of inefficiency

    Inefficient routes result in higher fuel costs, waste of staff time, increased environmental impact, and reduced time for actual care.

    Before vs. After: Time distribution in home care

    CAIRE Route Optimization
    Comparing time distribution before and after implementation

    CAIRE's route optimization technology significantly improves productive care time by reducing travel time, allowing caregivers to spend more time with patients.

    Productive Care
    75%

    Time spent with patients

    +5%
    Travel Time
    18%

    Time spent traveling

    -20%
    Administration
    7%

    Time spent on paperwork

    -10%
    Before vs After Comparison
    Time distribution comparison
    Before CAIRE Implementation
    Time distribution in home care before optimization
    After CAIRE Implementation
    Time distribution in home care after optimization
    Key Benefits
    Improvements from CAIRE implementation

    Increased Care Time

    5% increase in productive care time, allowing caregivers to provide better quality care to patients.

    Reduced Travel Time

    20% reduction in travel time through optimized routing and scheduling.

    By reducing travel time with CAIRE's AI-driven route optimization, the average caregiver can spend 5% more time on actual care – without working more hours. For a home care operation with 50 employees, this equals 20+ extra care hours per day.

    Calculate your potential savings

    Use our calculator to see how much your operation can save with CAIRE's route optimization.

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    Efficiency Gain 3.3 %

    Increase From 65% -> 68.3%
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    Admin Cost Reduction 10 %

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    Optimize your routes with AI

    Contact us to see how our AI-driven route optimization can reduce your driving time and increase care quality.

    Contact us

    Benefits and ROI

    See how route optimization for home care can improve your operations

    Smart geographical optimization

    Analyzes geographical distances and traffic patterns for efficient routes

    Time-based planning

    Optimizes visit times based on client needs and staff schedules

    Balanced workload

    Distributes visits evenly among staff for reduced stress