Applying Time Series Modeling to Assess the Dynamics and Forecast Monthly Reports of Abuse, Neglect and/or Exploitation Involving a Vulnerable Adult

Background: Application of time series modeling to predict reports related to maltreatment of vulnerable adults can be helpful for efficient and early planning and resource allocation to handle a high volume of investigations. The goal of this study is to apply: (1) autoregressive integrated moving average (ARIMA) time series modeling to fit and forecast monthly maltreatment reports accepted for assessment reported to a state adult protective services (APS) system, and (2) interrupted time series analysis to test whether the implementation of intake call centers have a significant impact in the number of maltreatment reports after the implementation period.

Methods: A time series analysis on monthly APS intake reports was conducted using administrative data from a state APS system in a southeastern US state between January 2014 and June 2018. Monthly APS data were subjected to ARIMA modeling adjusting for the time period when intake hubs were implemented. The coefficient of determination, normalized SBC, AIC, MSE, and Ljung-Box Q-test were used to evaluate the goodness-of-fit of constructed models. The most parsimonious model was selected to predict the monthly APS intakes from July to December 2018. Poisson regression was fit to examine the association of the implementation of the hubs and the number of intake reports received after the implementation periods, adjusting for confounders.

Results: Over 24,000 APS intakes accepted for investigation were identified over a period of four calendar years with an increase in the monthly average of APS intakes between 2014 and 2017. An increase in the number of monthly APS intakes was found after the intake call centers were implemented in 2015 (Phase-1) and 2017 (Phase-2). Of all the models tested, an ARIMA (12), 1, 1 model was found to work best after evaluating all fit measures for both models. For Phase-1, the optimum model predicted an average of 488 APS intake reports between July and December 2018, representing a 9% increase from January - June 2018 (median=445). For Phase-2, the percent increase was 32%.

Conclusions: The implementation of the intake call centers to service APS reports has a significant impact in the number of reports received after the implementation period. ARIMA time series is a valuable tool to predict future reports of maltreatment of vulnerable adults, which could be integrated into routine surveillance practice in social service agencies. Policymakers and program administrators at both the state and federal levels need effective forecasts of future intake reports which could help improve their ability to respond efficiently to a high volume of maltreatment reports as the US aging population continues to increase.