A leading provider of acute care in hospitals wanted to improve the pay rate of medical bills under the patients' responsibility. With several available patient engagement options available, they needed quantitative detailed information on which combination of engagement actions, under which timing scenario, would most effectively encourage payment, while adhering to the value of respect for the patient and their distinct circumstances.
Elder Research developed and validated predictive models that identified the best patient engagement combination to maximize their propensity to make a medical bill payment within 30 days. Multiple data sources (e.g. claims data, patient demographics, payment data, and medical diagnosis data) were joined with past patient engagement action records (outbound calls, emails, statement messages, text messages, discounts, payment plans, etc.). These were used to model how all possible engagement plans would improve the propensity to make a payment, given the patient's history and circumstances. This revealed the treatment plans that would be good, better, or best to meet the client's objectives.
The models have been delivered to the client with specific guidelines on implementation scenarios and objective methods of measuring the ongoing effectiveness of the deployed model.