Know who's leaving before they do.
Weekly churn risk scores for every caregiver based on satisfaction trends, overtime patterns, no-shows, tenure, and credential status. Automated alerts with recommended interventions. Data-driven retention that saves $2,500-5,000 per hire.
Home care turnover costs agencies $2,500-5,000 per hire. Most don't see it coming.
The average home care agency loses 60-80% of its caregiver workforce annually. Every departure means recruiting costs, training time, client disruption, and lost revenue from uncovered shifts. Tendara's Retention Predictor turns resignation surprises into preventable events.
System collects behavioral signals
Every clock-in, survey response, overtime hour, no-show, and credential update feeds the model. No extra data entry required — the signals are already in Tendara.
Weekly risk scores calculated
Every caregiver receives a churn risk score from 0-100, updated weekly. Low, moderate, high, and critical tiers let you prioritize your retention efforts where they matter most.
Alerts trigger recommended interventions
When a caregiver crosses into high or critical risk, their coordinator gets an alert with specific recommended actions — schedule adjustment, recognition, check-in conversation, or workload rebalancing.
Six signals that predict caregiver departure
Research shows caregiver turnover correlates with a small set of measurable factors. Tendara tracks all six automatically and combines them into a single risk score with full factor transparency.
Tenure
The first 90 days are the highest-risk window. Caregivers who survive the first quarter are 3x more likely to stay a year. The model weights tenure heavily for new hires.
Satisfaction trend
Pulse survey scores over time — not just the latest number. A caregiver dropping from 4.5 to 3.2 over six weeks is a bigger risk signal than someone who's been steady at 3.5.
Overtime patterns
Consistent overtime correlates with burnout. The model tracks weekly overtime trends — not just whether they hit 40 hours, but how often and how much.
No-show frequency
Increasing no-shows and late arrivals are among the strongest pre-departure signals. The model detects acceleration — a caregiver who went from zero no-shows to two in a month is flagged immediately.
Consecutive days worked
Caregivers who work 10+ consecutive days without a break are significantly more likely to quit within the following month. The system tracks streaks and factors them into risk.
Credential status
Expiring certifications that aren't renewed signal disengagement. The model treats credential lapses as a leading indicator — if they're not investing in their credentials, they may not be investing in the job.
A retention dashboard that tells you what to do — not just what to worry about
Risk scores are useless without action paths. Every high-risk caregiver comes with specific, data-backed intervention recommendations and 12-week trend tracking so you can measure whether your efforts are working.
Risk dashboard with factor breakdown
See your entire caregiver roster ranked by churn risk. Click into any caregiver to see which factors are driving their score — so your intervention matches the actual problem.
Automated high-risk alerts
Coordinators receive notifications when caregivers on their caseload cross into high or critical risk. No manual dashboard checking required — the system comes to you.
Recommended interventions
Based on the dominant risk factors: reduce hours for overtime-driven risk, schedule a check-in for satisfaction drops, rebalance workload for consecutive-day burnout. Specific actions, not generic advice.
12-week trend tracking
Track each caregiver's risk score over a rolling 12-week window. See whether your interventions moved the needle, and identify caregivers whose risk is trending up before they hit critical.
Related Features
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