Online Program

Real-Time Client Attrition Prediction in the Nurse Family Partnership Home Visiting Program (309889)

Keywords: machine learning, risk predictions, retention, healthcare

Nurse Family Partnership (NFP) is a community health nursing intervention for low income, first time mothers consisting of in-home visits from Registered Nurses from pregnancy through the child’s second birthday. Studies show that clients who remain in the program longer receive the greatest benefit from NFP, making retention a critical determinant of participant outcomes. In seeking to increase program completion (currently at 33%), NFP partnered with Data Clinic, the data for good initiative of Two Sigma, to identify predictors of attrition and develop a real-time flag to help nurses identify clients at risk of dropping out. Using program implementation data and de-identified client information, we predict the risk of client attrition for each client for each week in their program. Results are consistent with prior studies: mothers who are African-American, younger, and have not yet completed high school are at higher risk of attrition, while mothers who complete more of their most recent visits and those who have more social support tend to have lower risk of attrition. We are currently working on a pilot study to evaluate the impact of providing this information on retention.