Solving scheduling challenges through predictive analytics and machine learning
Many health systems struggle with inefficiencies in their clinical offices. Long patient wait times and overburdened nurses are common concerns.
Nurse leaders at Hartford Healthcare’s infusion centers explained during a Nov. 30 webinar how they applied machine learning and predictive analytics to solve common operational and scheduling challenges in the clinical environment, thus increasing patient access, reducing wait times and improving nurse satisfaction.
Engage staff when making 1 changes to scheduling operations
Hartford Healthcare has 10 medical oncology practices and 13 infusion centers across the state of Connecticut. Similar to other infusion centers, Hartford was challenged with a backlog of patient appointments, causing delays in care and unhappy nurses. When Hartford began the process of transforming its scheduling operations to mitigate these issues, a multidisciplinary group of clinicians and staff were included. Among those involved were the program director for infusion services, the IT director for the cancer institute, the infusion nurse manager, frontline nurses and physicians. The team continued to be involved during and after implementation of changes. Additionally, frontline nurses were assigned as champions, training staff and explaining why changes were happening. This has helped ensure buy-in across stakeholders.
Taking patient acuity into 2 account improves nurse satisfaction
A major change Hartford implemented was using LeanTaaS’ iQueue tool to assign nurses infusion patients based on their acuity. Prior to the tool, nurses would be assigned patients without any consideration for their unique needs and treatment. Using iQueue, nurse leaders created a grid of patients’ acuity, assigning patients numbers one through five, with five indicating the highest level of acuity. Now, nurses who are assigned patients with higher levels of acuity are assigned less patients in a day overall, causing fewer delays in care and allowing nurses to take breaks.
Data collection is key to 3 accurate scheduling
In order to create an efficient clinical office schedule, staff must have access to key data points. Hartford Health, with the use of the iQueue tool, is able to see the length of appointments and wait times for patients from check-in to vital sign administration and when the first treatment is administered. This access to data has promoted process improvements. For instance, when the Hartford team noticed that many appointments were extended by 30-minutes, they investigated further, discovering many were lengthened due to injection treatment. To address this, the staff now schedule injection appointments while patients are in the office.
Continuously monitor 4 changes
When a health system makes changes to how it handles appointment scheduling, its essential team members are charged with ensuring compliance of the changes is occurring consistently. It’s easy to fall back into old habits of scheduling. Additionally, team members should investigate why compliance is declining, as shifts in staffing, largely due to physicians moving, could be the cause. This may require changes to scheduling protocols.
Asking physicians to 5 spread-out appointments helps prevent backlog
Similar to most infusion centers, appointments for treatment are typically linked with doctor’s appointments. Hartford leaders noticed there was a bottleneck of physician appointments at 9 a.m., causing a bottleneck of appointments at the infusion center, stressing nurses and delaying patient care. Hartford leaders involved the physicians, asking for volunteers who could schedule appointments earlier in the morning. Some physicians agreed, improving the patient experience and enabling nurses to have a more balanced workload.