Forecasting the Impact of Licensing Regulatory Scenarios on Scaling-up the Social Work Workforce and Mitigating Harm: Using System Dynamics Simulation Modeling

Background and purpose: During the Utah 2024 legislative session, lawmakers modified various social work licensing policies with the intent of increasing the workforce and improving service quality. We partnered with the government office who authored the policy changes. In the absence of specific empirical data, the office was unable to forecast the impact of the various policy changes they were recommending. The objective of this presentation is to provide a case example of how a system dynamics simulation model can be used to forecast the impact of various social work licensing policy scenarios on the size of the social work workforce and the safety of services.

Methods: We used system dynamics computational simulation modeling to address our objective. We identified two outcomes for the model: the number of new licensees added to the workforce and the number of ethical violations over time. Next, we iteratively designed a computational simulation model incorporating factors from the research literature and theory. Then, we collaborated with state partners to obtain data to operationalize the variables. We ran the following policy scenarios on our two outcomes: 1) dropping one or both licensing exams, 2) modifying the time to take the licensing exams, 3) modifying the supervision hours required to become independently licensed, and 4) modifying the number of practice hours required to become independently licensed (LCSW). Of note, because there is no empirical data connecting passing the exam with safety of practice, we modeled several hypothetical scenarios.

Results: The results of the policy scenarios are as follows: 1) dropping the master’s exam increases the size of the masters social work (CSW) workforce slightly, with a possible increase in ethical violations (depending on assumptions). Dropping the clinical exam reduces the CSW pool and slightly increases the LCSW pool. In this scenario there is a slight decrease in CSW ethical violations, and an increase in the LCSW ethical violations. Dropping both exams increases LCSWs slightly, CSWs are the same, and ethical violations slightly increase among CSWs and LCSWs (depending on assumptions). 2) changing the amount of time to take an exam has essentially no impact on the workforce size or violations. 3) reducing supervision hours from 100 to 75 slightly increases the LCSW workforce with an increase in LCSW ethical violations. Increasing to 200 hours lowers LCSW pool and reduces the ethical violations. 4) reducing the practice hours doesn’t increase the workforce but does increase ethical violations. The workforce increases when you decrease the practice hours and the number of supervision hours.

Conclusions and implications: Using simulation modeling is a useful approach to translate social work research to help law makers see the potential impact of policy changes in a virtual space before they consider making changes in the real world. The results from the various scenarios demonstrate the unintended consequences or trade-offs that can occur within complex policy contexts.