The objective of this study was to evaluate the impact of quality improvement (QI) and patient safety initiatives and data disaggregation on racial disparities in severe maternal morbidity from hemorrhage (SMM-H).Our hospital began monitoring and reporting on SMM-overall and SMM-H rates in 2018 using administrative data. In March 2019, we began stratifying data by race and ethnicity and noted a disparity in rates, with non-Hispanic Black women having the highest SMM rates. The data was presented as run charts at monthly department meetings. During this time, our hospital implemented several QI and patient safety initiatives around obstetric hemorrhage and used the stratified data to inform guideline development to reduce racial disparity. The initiatives included implementation of a hemorrhage patient safety bundle and in-depth case reviews of adverse patient outcomes with a health equity focus. We then retrospectively analyzed our data. Our outcome of interest was SMM-H prior to data stratification (pre-intervention: June 2018-February 2019) as compared to after data stratification (post-intervention: March 2019-June 2020).During our study time period, there were 13,659 deliveries: 37% Hispanic, 35% White, 20% Black, 7% Asian and 1% Other. Pre-intervention, there was a statistically significant difference between Black and White women for SMM-H rates (p<0.001). This disparity was no longer significant post-intervention (p=0.138). The rate of SMM-H in Black women decreased from 45.5% to 31.6% (p=0.011).Our findings suggest that QI and patient safety efforts that incorporate race and ethnicity data stratification to identify disparities and use the information to target interventions have the potential to reduce disparities in SMM.
Background Strategies to implement evidence-based interventions (EBIs) in children’s mental health services have complex direct and indirect causal impacts on multiple outcomes. Ripple effects are outcomes caused by EBI implementation efforts that are unplanned, unanticipated, and/or more salient to stakeholders other than researchers and implementers. The purpose of the current paper is to provide a compilation of possible ripple effects associated with EBI implementation strategies in children’s mental health services, to be used for implementation planning, research, and quality improvement. Methods Participants were identified via expert nomination and snowball sampling. Online surveys were completed by 81 participants, each representing one of five roles: providers of mental health services to children or youth, researchers, policy makers, caregivers, and youth. A partially directed conventional content analysis with consensus decision making was used to code ripple effects. Results Four hundred and four unique responses were coded into 66 ripple effects and 14 categories. Categories include general knowledge, skills, attitudes, and confidence about using EBIs; general job-related ripple effects; EBI treatment adherence, fidelity, and alignment; gaming the system; equity and stigma; shifting roles, role clarity, and task shifting; economic costs and benefits; EBI treatment availability, access, participation, attendance, barriers, and facilitators; clinical process and treatment quality; client engagement, therapeutic alliance, and client satisfaction; clinical organization structure, relationships in the organization, process, and functioning; youth client and caregiver outcomes; and use of EBI strategies and insights in one’s own life. Conclusions This research advances the field by providing children’s mental health implementers, researchers, funders, policy makers, and consumers with a menu of potential ripple effects. It can be a practical tool to ensure compliance with guidance from Quality Improvement/Quality Assurance, Complexity Science, and Diffusion of Innovation Theory. Future phases will match potential ripple effects with salient children’s mental health implementation strategies for each participant role. Plain Language Summary: This qualitative study of multiple stakeholders in children’s mental health services identifies several possible ripple effects of implementation strategies, opening a new area of study for implementation science. Ripple effects can be positive, negative, or neutral within the full balance of implementation quality and impact. The list of ripple effects will provide implementation scientists, developers, and others with a useful tool during implementation planning and evaluation. This expert-informed methodology can provide a model for other fields for exploring possible ripple effects within implementation science.
Background: Strategies to implement evidence-based interventions (EBIs) in children’s mental health services have complex direct and indirect causal impacts on multiple outcomes. Ripple effects are outcomes that are caused by EBI implementation efforts and are unplanned, unanticipated, and/or more salient to stakeholders other than to researchers and implementers. The purpose of the current paper is to provide a compilation of possible ripple effects associated with EBI implementation strategies in children’s mental health services, to be used for treatment development, implementation planning, research, and quality improvement. Methods: Participants were identified via expert nomination and snowball sampling. Online surveys were completed by 81 participants who contributed ripple effects, each representing one of five roles: providers of mental health services to children or youth, researchers, policy makers, caregivers, and youth. A partially directed conventional content analysis with consensus decision making was used to code ripple effects. Results: Four hundred and four unique responses were coded into 66 ripple effects and 14 categories. Example categories include general knowledge, skills, attitudes, and confidence about using EBIs; general job-related ripple effects; EBI treatment adherence, fidelity, and alignment; gaming the system; equity and stigma; shifting roles, role clarity, and task shifting; economic costs and benefits; EBI treatment availability, access, participation, attendance, barriers, and facilitators; clinical process and treatment quality; client engagement, therapeutic alliance, and client satisfaction; clinical organization structure, relationships in the organization, process, and functioning; youth client and caregiver outcomes; and use of EBI strategies and insights in one’s own life. Conclusions: This research advances the field by providing children’s mental health implementers, researchers, funders, policy makers, and consumers with a menu of potential ripple effects for consideration when evaluating implementation quality and impact. It can be a practical tool to ensure compliance with the guidance of experts from Quality Improvement/Quality Assurance, Complexity Science, Diffusion of Innovation Theory, and the Medical Research Council. Future phases will match potential ripple effects with the most salient children’s mental health implementation strategies for each participant role. Trial Registration: None.
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Background: Strategies to implement evidence-based interventions (EBIs) in children’s mental health services have complex direct and indirect causal impacts on multiple outcomes. Ripple effects as outcomes that are caused by EBI implementation efforts and are indirect, unplanned, unanticipated, and/or more salient to stakeholders other than to researchers and implementers. The purpose of the current paper is to provide a compilation of possible ripple effects associated with EBI implementation strategies in children’s mental health services, to be used for treatment development, implementation planning, research, and quality improvement.Methods: Participants were identified via expert nomination and snowball sampling. Online surveys were completed by 81 participants representing one of five roles: providers of mental health services to children or youth, researchers, policy makers, caregiver, and youth. Participants brainstormed possible ripple effects. A partially directed conventional content analysis with consensus decision making was used to code ripple effects. Results: Four hundred and four unique responses were coded into 66 ripple effects and 14 categories. Example categories include general knowledge, skills, attitudes, and confidence about using EBI’s; general job-related ripple effects; EBI treatment adherence, fidelity, and alignment; gaming the system; equity and stigma; shifting roles, role clarity, and task shifting; economic costs and benefits; EBI treatment availability, access, participation, attendance, barriers, and facilitators; clinical process and treatment quality; client engagement, therapeutic alliance, and client satisfaction; clinical organization structure, relationships in the organization, process, and functioning; youth client and caregiver outcomes; and use of EBI strategies and insights in one’s own life.Conclusions: This research advances the field by providing implementers, researchers, funders, policy makers, and consumers with a “menu” of potential ripple effects for consideration when evaluating the full balance of any implementation effort. It can be a practical tool to ensure compliance with the guidance of experts from Quality Improvement/Quality Assurance, Complexity Science, Diffusion of Innovation Theory, and the Medical Research Council. Future phases will match potential ripple effects with the most salient implementation strategies for each participant role.Trial Registration: None.
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