Strengthening the System Supporting Perinatal People with Substance Use Disorder in the Midwest Using Group Model Building.

INTRODUCTION: Providing comprehensive, evidence-based care to perinatal people with substance use disorders (SUD) requires multi-stakeholder collaboration and alignment. The National Maternal and Child Health Workforce Development Center facilitated a system-strengthening process with the Midwest substance use in pregnancy (SUPper) club, a regional collaborative of health care providers, state public health agencies, and community-rooted organizations. METHODS: Facilitators led a 2 day group model building (GMB) workshop with 20 participants and two semi-structured interviews. Workshop participants were invited to complete an evaluation. RESULTS: Two primary trends were identified as priorities for change: (1) Birthing people's perception/experience of stigma and (2) The Midwest SUPper Club's reach and influence. Three causal loop diagrams (CLDs) were created to capture the interconnected dynamics of the Midwest perinatal SUD system: (1) the influence of stigma on maternal and infant health outcomes, (2) the role of clinic, organizational, and state policies, and (3) the impact of workforce education and evidence-based practices on care. From the CLDs, four priorities for action emerged: (1) align and promote shared mental models across stakeholders, (2) expand education and training opportunities for the perinatal SUD workforce, (3) strengthen systems infrastructure to support care navigation for patients and providers, and (4) collaboratively identify evidence-based practices that meet regional needs. All evaluation respondents reported that the workshop supported the development of a shared mental model. DISCUSSION: The GMB process strengthened collaboration and advanced strategic planning for the SUPper Club. GMB can be further utilized among diverse stakeholders across MCH systems to create shared mental models and accelerate collaborative planning efforts.

Tools for Supporting the MCH Workforce in Addressing Complex Challenges: A Scoping Review of System Dynamics Modeling in Maternal and Child Health.

OBJECTIVES: System Dynamics (SD) is a promising decision support modeling approach for growing shared understanding of complex maternal and child health (MCH) trends. We sought to inventory published applications of SD to MCH topics and introduce the MCH workforce to these approaches through examples to support further iteration and use. METHODS: We conducted a systematic search (1958-2018) for applications of SD to MCH topics and characterized identified articles, following PRISMA guidelines. Pairs of experts abstracted information on SD approach and MCH relevance. RESULTS: We identified 101 articles describing applications of SD to MCH topics. APPROACH: 27 articles present qualitative diagrams, 10 introduce concept models that begin to quantify dynamics, and 67 present more fully tested/analyzed models. PURPOSE: The most common purposes described were to increase understanding (n = 55) and support strategic planning (n = 26). While the majority of studies (n = 53) did not involve stakeholders, 40 included what we considered to be a high level of stakeholder engagement - a strength of SD for MCH. TOPICS: The two Healthy People 2020 topics addressed most frequently were early and middle childhood (n = 30) and access to health services (n = 26). The most commonly addressed SDG goals were "End disease epidemics" (n = 26) and "End preventable deaths" (n = 26). CONCLUSIONS FOR PRACTICE: While several excellent examples of the application of SD in MCH were found, SD is still underutilized in MCH. Because SD is particularly well-suited to studying and addressing complex challenges with stakeholders, its expanded use by the MCH workforce could inform an understanding of contemporary MCH challenges.

Insights from system dynamics applications in addiction research: A scoping review.

BACKGROUND AND AIMS: Substance misuse and use disorders are dynamic and complex problems, situated within systems of interacting social, environmental, and neurobiological factors. System dynamics (SD) methods broaden, test, and improve understanding of complex systems and can help inform effective action. We sought to systematically review the use of SD tools in addiction-related research. METHODS: Following PRISMA guidelines, we searched several databases from 1958 to 2019. We included studies focused on addiction-related screening and diagnosis, treatment, and return to use, as well as studies focused on earlier stages that may begin a path to addiction (e.g., experimentation, misuse onset). RESULTS: We extracted information from 59 articles with a median publication year of 2014. In addition to using SD to understand the underlying complexity driving addiction-related trends, other commonly cited reasons for use of SD included assessing impacts of potential actions (n = 35), predicting future trends (n = 28), and supporting strategic planning processes (n = 22). Most studies included simulation models (n = 43); however, some presented insights from qualitative SD diagrams (n = 9) and concept models (n = 6). The majority of studies focused on stages leading to potential addiction: initiation/ experimentation (n = 42) and misuse onset (n = 38). One-third (n = 20) engaged persons with lived experience or other stakeholders during the modeling process. CONCLUSIONS: Addiction-related SD research has increased over the last few decades with applications varying in several ways, from model purpose and types of data used to stakeholder involvement. Future applications should consider the benefits of stakeholder engagement throughout the modeling process and expanding models to include concomitant substance use.

A systematic review of the methodological quality of economic evaluations in genetic screening and testing for monogenic disorders.

PURPOSE: Understanding the value of genetic screening and testing for monogenic disorders requires high-quality, methodologically robust economic evaluations. This systematic review sought to assess the methodological quality among such studies and examined opportunities for improvement. METHODS: We searched PubMed, Cochrane, Embase, and Web of Science for economic evaluations of genetic screening/testing (2013-2019). Methodological rigor and adherence to best practices were systematically assessed using the British Medical Journal checklist. RESULTS: Across the 47 identified studies, there were substantial variations in modeling approaches, reporting detail, and sophistication. Models ranged from simple decision trees to individual-level microsimulations that compared between 2 and >20 alternative interventions. Many studies failed to report sufficient detail to enable replication or did not justify modeling assumptions, especially for costing methods and utility values. Meta-analyses, systematic reviews, or calibration were rarely used to derive parameter estimates. Nearly all studies conducted some sensitivity analysis, and more sophisticated studies implemented probabilistic sensitivity/uncertainty analysis, threshold analysis, and value of information analysis. CONCLUSION: We describe a heterogeneous body of work and present recommendations and exemplar studies across the methodological domains of (1) perspective, scope, and parameter selection; (2) use of uncertainty/sensitivity analyses; and (3) reporting transparency for improvement in the economic evaluation of genetic screening/testing.