Hailemariam Maji, Rosen Rochelle K, Sneed Rodlescia, Brown Garrett, Clark Kendra J, Mackey Benjamin, Eshetu Hiywote, Wei Jiaxin, Taxman Faye S, Johnson Jennifer E
Charles Stewart Mott Department of Public Health, Michigan State University, 200 East 1 st St Room 366, Flint, MI, USA.
Center for Behavioral and Preventive Medicine, The Miriam Hospital, Providence, RI, USA.
BMC Health Serv Res. 2025 Aug 28;25(1):1138. doi: 10.1186/s12913-025-13385-2.
Data-driven decision-making is an implementation strategy to improve system performance and health outcomes for individuals with substance use and mental health needs interacting with criminal-legal systems. We currently have limited understanding of how agencies define and use data in their decision-making processes. A qualitative study was conducted with agency leaders from jails, probation and parole, and community mental health and substance use service agencies to characterize (1) how respondents defined data and data use, (2) current level of data use for decision-making, (3) data capacity needs, and (4) agency perspectives on best practices and their recommendations.
In-depth interviews were conducted with 68 mental health, substance use, jail, and probation leaders from a representative group of 52 U.S. counties from December 2020-March 2022. Data were analyzed using applied thematic analysis.
Four themes emerged. For defining data and data use, respondents characterized their current level of data use as rudimentary. In terms of current level of data use, individual-level health or legal information needed to coordinate services, and risk prediction scores were used over system measures. Data capacity needs identified as capacity to track and share data across agencies and inadequate data management. In terms of best practices and agency recommendations, participants highlighted the need for data sharing, standardized data management systems, data dashboards, and in-house data expertise.
Findings from this study highlight the limited capacity of counties to implement data-driven decision making in mental health, substance use, and criminal legal settings. Addressing gaps in infrastructure, staffing, and data expertise will require technical assistance and targeted policy incentives. System-level metrics and benchmarks, such as the cascade of care, are essential for evaluating cross-agency performance and improving outcomes for individuals with mental health needs.
数据驱动的决策是一种实施策略，旨在改善与刑事法律系统互动的有物质使用和心理健康需求的个人的系统性能和健康结果。我们目前对各机构如何在其决策过程中定义和使用数据的了解有限。对来自监狱、缓刑和假释机构以及社区心理健康和物质使用服务机构的机构负责人进行了一项定性研究，以描述：（1）受访者如何定义数据和数据使用；（2）当前用于决策的数据使用水平；（3）数据能力需求；（4）机构对最佳实践及其建议的看法。
2020年12月至2022年3月期间，对来自美国52个县的代表性样本中的68名心理健康、物质使用、监狱和缓刑负责人进行了深入访谈。使用应用主题分析法对数据进行了分析。
出现了四个主题。在定义数据和数据使用方面，受访者将他们目前的数据使用水平描述为初级。就当前的数据使用水平而言，协调服务所需的个人层面的健康或法律信息以及风险预测分数比系统指标更常用。确定的数据能力需求包括跨机构跟踪和共享数据的能力以及数据管理不足。在最佳实践和机构建议方面，参与者强调了数据共享、标准化数据管理系统、数据仪表板和内部数据专业知识的必要性。
本研究的结果凸显了各县在心理健康、物质使用和刑事法律环境中实施数据驱动决策的能力有限。解决基础设施、人员配备和数据专业知识方面的差距将需要技术援助和有针对性的政策激励措施。系统层面的指标和基准，如护理级联，对于评估跨机构绩效和改善有心理健康需求的个人的结果至关重要。
