Category Archives: Healthcare

Reducing Drop-out Rate in WIC Program

Women, Infants and Children (WIC) program is a Special Supplemental Nutrition Program that provides federal grants to states for supplemental foods, health care referrals, and nutrition education for low-income pregnant, breastfeeding, and non-breastfeeding postpartum women, and to infants and children up to age five who are found to be at nutritional risk. The objective is to meet the nutritional needs of young children and nursing and lactating mothers. This has been shown to improve the health of those involved in the program and to help the children be ready to start school. WIC is one of the U.S.’s most cost effective programs in providing nutrition to young families. WIC serves about half of all infants born in the United States.

The state of Texas wanted help in reducing their drop-out rate. A family may become ineligible due to income level or if the youngest child is older than five. However, if a family is eligible, it is better for the children if they remain in the program. We gave the administrators of the program a dashboard (based on PowerBI) with three views:

  • Current state
  • Past trends
  • Drop-out predictions

Current State

The first view showed a map of Texas with the Local Agencies highlighted. The number of certificates for the five certificate types is shown overall (upper left), by County (lower left), by city (lower center and Local Agency-Clinic. One can click on any of these to zero in on the status of that area. For example, if you click on Houston in the lower center, you get the next view.

Now the information specific to Houston is highlighted.

Past Trends

The next view show a history of the number of Certificates of each type. The default view is for the state as a whole and for the entire period of the data. There are some interesting trends, especially for Category ‘C’ in the lower left panel. Management may already have an explanation for these trends, but it’s helpful to see them over time. Again, one can select a specific city, county, Local Agency or clinic as well as a subset of the date range.

When we select Dallas for the most recent two years we get the next view.

Drop-out Predictions

The final view gives a prediction of who is likely to drop out of the program prior to the Certificate end date. The opening view is for the entire state. A client is considered a “likely” dropout based on the threshold set by the slider bar in the upper right. The user has the ability to change this if desired. For this example, a client is considered a likely dropout if the probability they will drop out is greater than 50%. The list in the lower left is the clients with the highest probability of dropping out, sorted decreasing by dropout probability. (The client ID (CID) has been hidden for confidentiality reasons.) There are some clients listed here with a very high probability of dropping out. The middle lower panel is the number of dropouts by city and lower right by clinic for a given Local Agency.

One way this view would be used by local management is to retrieve the information specific to the City or Clinic. When the highest bar in the lower right graph is clicked the Clinic management will get a list of their clients who are most likely to drop out of the program and they can take appropriate action to encourage them to stay in the program.

These predictions were based on numerous sources of data and were constructed using Machine Learning.