Technology, Case Practice, and Turnover: The Case of Virginia

Background and Purpose: After exploring worker support needs through focus groups and exit surveys, Virginia (VA) elected to implement job modernization technology interventions statewide. In concert with the QIC-WD, VA is gathering in-depth data about staff, their perspectives about, and usage of technology in 18 of its localities. These localities encompass a workforce of approximately 450 of the state’s 2200 frontline staff working within the state-supervised, county-administered child welfare system. Rollout of these interventions occurred in multiple phases: transcription services implementation occurred between November 2017 - January 2018 and mobility technology (iPads) rolled out between October 2019 – January 2020. The goal of the interventions are to provide work supports that reduce administrative burdens, enhance flexibility of when and where work is accomplished, and free staff to devote more time to engage families, i.e., conduct more social work.

Methods. Many methods are being used to understand intervention implementation and factors associated with turnover. Analyses used data from: 1) a baseline and annual follow up staff survey with psychological and child welfare practices scales; 2) a diary study capturing worker’s habits, perspectives, and reactions to the new technology, pre- and post-onset of COVID; 3) case-level administrative data reflecting documentation practices over time; and 4) turnover data. Descriptive analyses, generalized linear models, and Cox regression analyses were employed to explore associations between factors and outcomes of interest.

Results. Findings and lessons learned to date include staff perceptions about and adoption of technological interventions, staff characteristics and the likelihood, degree, and manner of technological adoption, and factors associated with turnover. Early findings have indicated that while transcription services were not uniformly embraced, they were associated with improvement in the timeliness of casework documentation and increased flexibility for staff, including the ability to complete administrative tasks while out of the office. Usage analyses related to mobility indicated that staff using iPads are associated with more extensive documentation of visits than those who do not use the iPads. Surveys administered post-rollout of mobility, and pre- and during COVID, indicate staff on average felt the devices saved them time, and were grateful for the resource when COVID hit. The iPads were also a key means for the state agency to communicate with staff about COVID-related policy and practice changes, and provided an efficient and comprehensive means to roll-out additional features to support staff in the pandemic, including HIPPA-compliant virtual meeting technology. An examination of data from 967 caseworkers hired statewide since 2010 identified factors associated with turnover rates and time to turnover. Preliminary findings indicate that non-white staff appear less likely to leave the agency and are likely to stay longer on the job before leaving, while controlling for age at hire date and year of hire. Further, not surprisingly, turnover rates vary by region.

Conclusion. This workforce intervention and outcome research has numerous implications for implementing technological advances and can inform decisions about hiring, training, and/or supervising staff, roll-out of remote work supports, especially in a pandemic environment, and the administration of child welfare agencies.