CarePoint Home Health Case Study

The Challenge

Home health scheduling looks simple on paper: assign nurses to patients, give them addresses, let them drive. In practice, it is one of the most complex routing problems any business can face. Every patient has a specific time window dictated by medical needs, caregiver availability, or insurance requirements. Every visit has a different duration depending on the service type. And every nurse has a full day of these constraints stacked back-to-back across a metro area that stretches 50 miles in any direction.

Diane Kowalski managed all of this from a shared Google Sheet.

As clinical coordinator at CarePoint Home Health, Diane was responsible for building daily schedules for 22 practitioners serving 150–180 patients across the greater Atlanta metro. The agency’s EHR system handled patient records and billing, but its routing capabilities were limited to basic address lookup. For the actual sequencing of visits, Diane relied on her own judgment, a color-coded spreadsheet, and Google Maps open in a dozen browser tabs.

The constraints were relentless. Patient A needed wound care between 8 and 10am, before her dialysis transport arrived. Patient B required physical therapy between 2 and 4pm, after her caregiver’s shift started. Patient C needed a 45-minute visit. Patient D needed 90 minutes. Diane juggled these variables across 22 schedules every single morning, starting at 5:30am and rarely finishing before 9:30am.

The schedules she produced were the best a person could manage. They were not, however, physically possible.

• Impossible timing: A 10am appointment followed by a 10:30am appointment 25 minutes away was a routine occurrence. Diane accounted for visit duration but couldn’t mentally calculate drive time across 22 simultaneous routes. Nurses left patients mid-visit or arrived late to the next one.
• No location visibility: When nurses ran behind, patients called the front desk. The receptionist had no way to check where the nurse was or provide an estimated arrival. Each “where’s my nurse?” call took 10–15 minutes to resolve through phone calls and texts.
• Payer audit flags: Missed and late appointments triggered compliance issues. Home health payers track visit completion rates closely, and CarePoint was averaging 8–12 missed or late visits per week. Several had been flagged in quarterly audits.
• Nurse burnout: Practitioners routinely drove 45–60 minutes between patients because assignments were based on patient-nurse familiarity rather than geography. Nurses who should have been providing care were spending their energy in traffic.

One incident in particular made the problem impossible to ignore. A nurse was scheduled for a comprehensive assessment at a patient’s home, a 90-minute visit that started at 9am. Her next appointment was at 10:45am, 28 minutes away. The assessment ran to its full 90 minutes, as assessments always do. The nurse arrived at her second patient’s home at 11:15, thirty minutes late. That patient had already called the office twice, and the visit overlapped with the patient’s scheduled medication delivery. The patient’s daughter filed a formal complaint, and the incident landed on the desk of CarePoint’s compliance officer.

Diane knew the scheduling method was the problem. She started looking for a system that could handle 22 simultaneous routes with time windows, variable visit durations, and realistic drive times.

The Solution

Diane found Upper after searching for route optimization software designed for multi-driver operations with time constraints. She ran a trial using the previous week’s patient schedule, importing addresses, visit durations, and time windows for all 22 practitioners. The results changed her morning immediately.

Upper generated optimized routes that respected every constraint: no overlapping appointments, realistic drive times between visits, and balanced workloads across all 22 nurses. The schedules that took Diane four hours to build manually were ready in minutes.

Scheduling 22 Practitioners with Realistic Drive Times

The most immediate change was the elimination of physically impossible schedules. Upper’s route optimization accounts for drive time between stops, not just visit duration and time windows. When a wound care visit is scheduled for 45 minutes and the next patient is 20 minutes away, the system builds that gap into the route automatically.

Diane configured service times by visit type: 30 minutes for blood draws, 45 minutes for wound care, 60 minutes for physical therapy sessions, and 90 minutes for comprehensive assessments. Upper used these durations alongside real drive time estimates to build schedules where every appointment was reachable.

The difference showed up on day one. Not a single nurse called in to report a timing conflict during the first week. By the end of the first month, missed and late appointments had dropped from an average of 10 per week to fewer than one.

Real-Time Visibility Across the Entire Care Team

Before Upper, Diane’s only way to locate a nurse was to call or text them. With 22 practitioners spread across Atlanta, that process consumed hours of her day and left patients waiting for answers.

Upper’s live GPS tracking gave Diane a single dashboard view of every nurse’s location in real time. When a patient called asking about their nurse’s arrival, the receptionist could check the dashboard and provide an accurate estimate in seconds instead of making a round of phone calls.

The tracking data also revealed inefficiencies that weren’t visible before. Two nurses assigned to overlapping areas were driving past each other’s patients multiple times per day. After Diane restructured their territories using Upper’s route data, both nurses cut their daily drive time by over 40 minutes.

Keeping Patients Informed with Arrival Notifications

Patient communication had been a persistent pain point. When nurses ran late, patients and their families had no way to know whether to keep waiting or reschedule. The front desk fielded dozens of calls each day asking for updates they couldn’t provide.

Upper’s customer notification system sent automated emails to patients when their nurse was en route, including an estimated arrival window. The notifications reduced inbound calls to the front desk by more than half and gave patients the information they needed without anyone picking up a phone.

For compliance purposes, Diane also began exporting daily route reports that documented planned versus actual visit times. The reports provided the audit trail CarePoint’s compliance officer had been requesting for months.

The Impact

The transformation at CarePoint wasn’t just operational. It affected clinical outcomes, staff morale, and the agency’s financial performance. Nurses who had been spending their energy fighting traffic and impossible schedules were now arriving at each visit on time, focused, and less stressed. Patients noticed the difference.

Within the first quarter of using Upper, CarePoint’s patient satisfaction scores improved by 22% in their quarterly survey. The payer audit flags that had been accumulating due to missed visits dropped to zero. Diane’s morning routine went from a 4-hour scheduling marathon to a 45-minute process that produced better results than her best manual effort ever had.

The capacity gains were significant. With drive times cut nearly in half, each nurse gained time for one to two additional visits per day. Across 22 practitioners, that recovered capacity translated to approximately $15,000 per month in additional revenue without adding a single new hire.

Performance Metrics

Diane now spends her mornings reviewing optimized schedules and handling exceptions rather than building routes from scratch. The system that once consumed half her workday runs in the background, producing schedules that her team trusts and her patients depend on.