Cutting down cancelations in regional healthcare
Not-for-profit clinics use machine learning from Qlik to enhance patient care and make operational savings.
The situation
Poverty and existing health challenges deter already underserved rural populations from seeking preventative healthcare, making appointment cancellations and no-shows common.
Appalachian Regional Healthcare (ARH) is a not-for-profit healthcare system committed to improving the health and well-being of eastern Kentucky and southern West Virginia residents.
The Company
The Challenge
Because regional poverty results in missed appointments and reduced margins for healthcare providers, making it important to identify at-risk patients — many of whom do not carry traditional health insurance.
The Need
ARH needed a way to analyze varied and unstructured datasets, to equip staff with the right information to reach out to the highest-risk patients with reminders and reassurances.
“We realize that to make headway in serving a disparate population, we have to make the best use of data that we can.”
The Solution
ARH leveraged machine learning and predictive analytics through Qlik AutoML® — a user-friendly, automated machine learning tool that provides data on a variety of barriers to appointment attendance.
The Impact
Nurses and support staff can now predict which patients are most at-risk for missing appointments due to transportation, distance, or local weather issues, then contact them with reminders to minimize cancelations and consequently improve community healthcare.
“Qlik AutoML gets you in the game sooner and gives you the building blocks to create something bigger, faster.”
The Difference
Qlik AutoML not only empowers users to make changes with data, but points them exactly to where those changes need to take place — putting the power of predictive analytics in the hands of business and analyst teams without extensive machine learning or AI expertise.
See how it can help revolutionize your business.