Lean Six Sigma Improves Collections Rates – Contributed by Joe Valvona

Lean Six Sigma Improves Collections Rates – Contributed by Joe Valvona

Improving Collections with DOE & Regression Analysis – Contributed by Joe Valvona

When asked to improve the collections rate on outstanding balances for hospital services, Joe used a Design of Experiment strategy to identify better ways to interact with the customer and achieve the
desired result. The design was complex.  The LSS team:

  • Selected three hospitals and three types of patients (inpatient, emergency room patient, and outpatients).
  • Grouped the patients into two or three outstanding balance categories.
  • Developed ten alternative scenarios for interacting with customers. Each scenario was some combination of three variables:  person-to-person calls; letters, and statements asking
    the patient to “please pay.”
  • Used regression analysis to identify the most effective scenarios.

Over 12,000 accounts were tracked for up to four months (when either the outstanding balance was paid or the account was sent to a collection agency). Two different scenarios were implemented (one for
patients with insurance; the other for patients without insurance). The entire experiment, including monitoring the implementation of the selected scenarios, lasted more than 12 months.   Joe is proud of
the results this project achieved:

  • Implementation of the new scenarios required the hiring of additional staff and the purchase of new equipment. During the 12-month realization period, the project netted approximately $2 million dollars in net new revenue.
  • Customers also derived a benefit. Because the in-house collectors were talking to the customers, they were able to help some uninsured persons qualify for Medicaid.