Reducing Errors and Speeding Calculation through Automation
Armel Cyrille Brou, DCDJ Fellow in Côte d’Ivoire, provided support to the data management team at CMS Private Center Plus, an Ivorian health facility focused on treating patients with HIV/AIDS and STDs. Armel developed an application that reduces the time spent calculating patient program schedules from five minutes to less than 30 seconds.
Background
The Des Chiffres et Des Jeunes (DCDJ) Data Fellowship is a flagship DCDJ program that places technically-trained Ivorian youth into organizations where they encourage and increase the degree to which data is used for decision making. It is a unique opportunity for young people to sharpen data skills while contributing to a strengthened data ecosystem and to data-related resource availability in Côte d’Ivoire. DCDJ is led by Development Gateway and funded by the Data Collaboratives for Local Impact (DCLI) program. The DCDJ Data Fellowship builds young peoples’ skills to strategically catalyze sustainable change, DCDJ leverages local capacity to improve data access, sharing, and availability.
Before joining the DCDJ Fellowship, Armel had been a masters student interested in honing his data science skills and gaining hands-on experience. After the Fellows training, Armel was placed with CMS Private Center Plus.
Problem
While conducting an assessment with the data management team and also the lab, Armel learned that when new patients were admitted, a healthcare worker must calculate the schedule of that patient’s care program. This calculation includes accounting for the patients’ total years of infection and the types of support needed to manage their condition. It is then used to set up a specific appointment, lab test, and medication schedule. Each additional year in treatment adds a layer of complexity to the calculations. For patients with an extended infection history, like those who had been receiving care for 20 years, making the calculation could take over five minutes of busy administrators’ time. Despite being critical to patient care, the information and calculations were also being entered into the system manually, which introduced room for error. It was clear that this calculation was time consuming, and that it could be efficiently automated.
Solution
Armel, with the support of the DCDJ SuperFellows and several other Fellows, worked to create an easy-to-use application that would automatically and accurately calculate the patient program schedules. Built as a simple Excel document, health care providers can enter the date the patient started treatment and the current date, and the application will then calculate all upcoming appointments, lab dates, and needed lab types.
Process
After identifying the calculation problem as a constraint to healthcare administrator productivity, Armel worked with the data management team to support the new tool development process. The team learned the underlying calculations of the program schedule and created Excel functions that would automate them. Then they tested the application with several healthcare providers to confirm its effectiveness. After development, Armel provided staff training to healthcare administrators to ensure the new application was being used effectively. He describes the application as very intuitive and easy to understand and use, so training can be done by existing staff in the future, without having to rely on Armel or other Data Fellows.
Outcomes & Impacts
The application has reduced the number of errors introduced into the patient scheduling process, while also saving the time required for repetitive, manual calculations. Prior to the application, it would take five minutes per program calculation. Now it takes less than 30 seconds. It was clear to Armel that this system was of value to the clinic staff and was being used. When one staff member accidentally deleted the program from the computers at the facility, they quickly called Armel to reinstall it for them.
More effective scheduling also benefits patients. Prior to the new tool, healthcare providers would often only see the patient when they were in need of a medication refill, and would not know to remind patients of upcoming lab appointments. If patients miss their lab appointments, it is difficult for doctors to make informed decisions about patient care – they may be missing data on viral load, viral suppression, and medication. With the automatic calculations, patients and providers both have a much clearer understanding of expectations prior to appointments, and patients benefit from a more comprehensive continuum of care.