Health Services Research最新文献

{"title":"Quality improvement lessons learned from National Implementation of the \"Patient Safety Events in Community Care: Reporting, Investigation, and Improvement Guidebook\".","authors":"Jennifer L Sullivan, Marlena H Shin, Jeffrey Chan, Michael Shwartz, Edward J Miech, Ann M Borzecki, Edward Yackel, Sachin Yende, Amy K Rosen","doi":"10.1111/1475-6773.14317","DOIUrl":"10.1111/1475-6773.14317","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate nationwide implementation of a Guidebook designed to standardize safety practices across VA-delivered and VA-purchased care (i.e., Community Care) and identify lessons learned and strategies to improve them.</p><p><strong>Data sources and study setting: </strong>Qualitative data collected from key informants at 18 geographically diverse VA facilities across 17 Veterans Integrated Services Networks (VISNs).</p><p><strong>Study design: </strong>We conducted semi-structured interviews from 2019 to 2022 with VISN Patient Safety Officers (PSOs) and VA facility patient safety and quality managers (PSMs and QMs) and VA Facility Community Care (CC) staff to assess lessons learned by examining organizational contextual factors affecting Guidebook implementation based on the Consolidated Framework for Implementation Research (CFIR).</p><p><strong>Data collection/extraction methods: </strong>Interviews were conducted virtually with 45 facility staff and 10 VISN PSOs. Using directed content analysis, we identified CFIR factors affecting implementation. These factors were mapped to the Expert Recommendations for Implementing Change (ERIC) strategy compilation to identify lessons learned that could be useful to our operational partners in improving implementation processes. We met frequently with our partners to discuss findings and plan next steps.</p><p><strong>Principal findings: </strong>Six CFIR constructs were identified as both facilitators and barriers to Guidebook implementation: (1) planning for implementation; (2) engaging key knowledge holders; (3) available resources; (4) networks and communications; (5) culture; and (6) external policies. The two CFIR constructs that were only barriers included: (1) cosmopolitanism and (2) executing implementation.</p><p><strong>Conclusions: </strong>Our findings suggest several important lessons: (1) engage all collaborators involved in implementation; (2) ensure end-users have opportunities to provide feedback; (3) describe collaborators' purpose and roles/responsibilities clearly at the start; (4) communicate information widely and repeatedly; and (5) identify how multiple high priorities can be synergistic. This evaluation will help our partners and key VA leadership to determine next steps and future strategies for improving Guidebook implementation through collaboration with VA staff.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540575/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140892939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptations and early adoption of a family caregiver intervention in the Veterans Affairs Health Care System: A multimethod pragmatic approach for national scaling.","authors":"Amanda C Blok, Connor Drake, Kasey Decosimo, Leah L Zullig, Jaime M Hughes, Nina R Sperber, Swetha Kota, Emily Franzosa, Cynthia J Coffman, Megan Shepherd-Banigan, Trisha Chadduck, Kelli D Allen, Susan N Hastings, Courtney H Van Houtven","doi":"10.1111/1475-6773.14360","DOIUrl":"10.1111/1475-6773.14360","url":null,"abstract":"<p><strong>Objective: </strong>To examine the relationship between site-level adaptation and early adoption of Caregivers Finding Important Resources, Support, and Training (FIRST) training during national implementation across diverse Veteran Health Administration (VA) medical centers.</p><p><strong>Data sources and study setting: </strong>We enrolled and evaluated 25 VA medical centers (VAMCs). Along with administrative data on site characteristics, we examined site-reported data on adaptations and intervention adoption, defined as ≥4 training classes delivered to ≥5 caregivers at 6 months from April through October 2022.</p><p><strong>Study design: </strong>A type III hybrid implementation-effectiveness cluster randomized controlled trial, randomized VAMCs 1:1 to receive foundational (low-touch) implementation support (n = 12) or the addition of enhanced (high-touch) implementation support (n = 13).</p><p><strong>Data collection/extraction methods: </strong>At key implementation phases, VAMCs were asked to report adaptations including content, contextual modifications (format, setting, personnel, and population), and training of providers. We describe site-level adaptations by arm and by organizational characteristics that included VAMC complexity level, staffing, rurality, and organizational readiness to change. We used qualitative comparative analysis to identify unique adaptations that contributed to intervention adoption at 6 months.</p><p><strong>Principal findings: </strong>VAMCs randomized to receive enhanced support reported slightly more adaptations than those randomized to foundational support. At 6 months, VAMCs with two or more adaptations adopted Caregivers FIRST at a higher rate than those with fewer adaptations (90% vs. 44%). Staffing adaptations (e.g., who delivered the intervention), format and content (e.g., modified delivery pace), and referring provider training were unique adaptations to adopting sites.</p><p><strong>Conclusions: </strong>Site-level adaptations were diverse and occurred more frequently in sites with early adoption of Caregivers FIRST. Future research should identify best practices of supporting and monitoring intervention adaptation. Understanding the role of adaptation in early adoption success could assist other healthcare systems in implementing interventions for caregivers.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540588/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141876759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A structured approach to modifying an implementation package while scaling up a complex evidence-based practice.","authors":"Kristina M Cordasco, Sonya E Gabrielian, Jenny Barnard, Taylor Harris, Erin P Finley","doi":"10.1111/1475-6773.14313","DOIUrl":"10.1111/1475-6773.14313","url":null,"abstract":"<p><strong>Objective: </strong>To describe a structured, iterative, data-driven approach for modifying implementation strategies for a complex evidence-based practice during a nationwide scale-up initiative.</p><p><strong>Data sources and study setting: </strong>We scaled-up implementation of Critical Time Intervention (CTI)-an evidence-based case management model-across 32 diverse community-based Veterans Affairs (VA) \"Grant and Per Diem\" case management (GPD-CM) agencies that serve homeless-experienced Veterans transitioning to independent living. Primary data were collected using qualitative methods.</p><p><strong>Study design: </strong>We embarked on a scale-up initiative while conducting a pragmatic randomized evaluation using a roll-out design, comparing two versions of a CTI implementation package tailored to VA's GPD-CM program. We iteratively assessed contextual factors and implementation outcomes (e.g., acceptability); findings informed package modifications that were characterized using the Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies.</p><p><strong>Data collection methods: </strong>We conducted semi-structured interviews with Veterans, GPD-CM staff, and liaising VA clinicians; periodic reflections with liaising VA clinicians and implementation team members; and drew upon detailed meeting notes. We used rapid qualitative methods and content analysis to integrate data and characterize modifications.</p><p><strong>Principal findings: </strong>After each scale-up wave-in response to variations in agency-level characteristics- we made iterative modifications to the implementation package to increase CTI adoption and fidelity across the diverse contexts of our scale-up sites. Modifications included adding, deleting, integrating, and altering the package; core package components were preserved.</p><p><strong>Conclusions: </strong>Implementation packages for complex evidence-based practices undergoing scale-up in diverse contexts may benefit from iterative modifications to optimize practice adoption with fidelity. We offer a structured, pragmatic approach for iteratively identifying data-driven, midstream implementation package adjustments, for use in both VA and non-VA scale-up initiatives. Our project demonstrates the importance of assessing for and making modifications in a scale-up initiative, as well as the trade-offs of projects having simultaneous formative and summative evaluation aims.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540582/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140946492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness of a virtual quality improvement training program to improve reach of weight management programs within a large health system.","authors":"Laura J Damschroder, Richard Evans, H Myra Kim, Jeremy Sussman, Michelle B Freitag, Claire H Robinson, Jennifer A Burns, Nicholas R Yankey, Julie C Lowery","doi":"10.1111/1475-6773.14344","DOIUrl":"10.1111/1475-6773.14344","url":null,"abstract":"<p><strong>Objective: </strong>To test effectiveness of the LEAP (Learn Engage Act Process) Program on engaging frontline Veteran Health Administration (VHA) medical center teams in continuous quality improvement (QI), a core capability for learning health systems.</p><p><strong>Data sources and study setting: </strong>Data sources included VHA electronic health record (EHR) data, surveys, and LEAP coaching field notes.</p><p><strong>Study design: </strong>A staggered difference-in-differences study was conducted. Fifty-five facilities participated in LEAP across eight randomly assigned clusters of 6-8 facilities per cluster over 2 years. Non-participating facilities were used as controls. A MOVE! weight management program team completed a Plan-Do-Study-Act cycle of change supported by learning curriculum, coaching, and virtual collaboratives in LEAP facilities. Primary outcome was program reach to Veterans. A mixed-effects model compared pre- versus post-LEAP periods for LEAP versus control facilities. LEAP adherence, satisfaction, and cost to deliver LEAP were evaluated.</p><p><strong>Data collection/extraction methods: </strong>Thirty months of facility-level EHR MOVE! enrollment data were included in analyses. LEAP Satisfaction and QI skills were elicited via surveys at baseline and 6-month post-LEAP.</p><p><strong>Principal findings: </strong>Fifty-five facilities were randomly assigned to eight time-period-based clusters to receive LEAP (71% completed LEAP) and 82 non-participating facilities were randomly assigned as controls. Reach in LEAP and control facilities was comparable in the 12-month pre-LEAP period (p = 0.07). Though LEAP facilities experienced slower decline in reach in the 12-month post-LEAP period compared with controls (p < 0.001), this is likely due to unexplained fluctuations in controls. For LEAP facilities, satisfaction was high (all mean ratings >4 on a 5-point scale), self-reported use of QI methods increased significantly (p-values <0.05) 6 months post-LEAP, and delivery cost was $4024 per facility-based team.</p><p><strong>Conclusion: </strong>Control facilities experienced declining reach in the 12-month post-LEAP period, but LEAP facilities did not, plus they reported higher engagement in QI, an essential capability for learning health systems.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540586/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141762774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tracking implementation strategies in real-world settings: VA Office of Rural Health enterprise-wide initiative portfolio.","authors":"Heather Schacht Reisinger, Sheila Barron, Erin Balkenende, Melissa Steffen, Kenda Steffensmeier, Chris Richards, Dan Ball, Emily E Chasco, Jennifer Van Tiem, Nicole L Johnson, DeShauna Jones, Julia E Friberg, Rachael Kenney, Jane Moeckli, Kanika Arora, Borsika Rabin","doi":"10.1111/1475-6773.14377","DOIUrl":"10.1111/1475-6773.14377","url":null,"abstract":"<p><strong>Objective: </strong>To use a practical approach to examining the use of Expert Recommendations for Implementing Change (ERIC) strategies by Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) dimensions for rural health innovations using annual reports on a diverse array of initiatives.</p><p><strong>Data sources and study setting: </strong>The Veterans Affairs (VA) Office of Rural Health (ORH) funds initiatives designed to support the implementation and spread of innovations and evidence-based programs and practices to improve the health of rural Veterans. This study draws on the annual evaluation reports submitted for fiscal years 2020-2022 from 30 of these enterprise-wide initiatives (EWIs).</p><p><strong>Study design: </strong>Content analysis was guided by the RE-AIM framework conducted by the Center for the Evaluation of Enterprise-Wide Initiatives (CEEWI), a Quality Enhancement Research Initiative (QUERI)-ORH partnered evaluation initiative.</p><p><strong>Data collection and extraction methods: </strong>CEEWI analysts conducted a content analysis of EWI annual evaluation reports submitted to ORH. Analysis included cataloguing reported implementation strategies by Reach, Adoption, Implementation, and Maintenance (RE-AIM) dimensions (i.e., identifying strategies that were used to support each dimension) and labeling strategies using ERIC taxonomy. Descriptive statistics were conducted to summarize data.</p><p><strong>Principal findings: </strong>A total of 875 implementation strategies were catalogued in 73 reports. Across these strategies, 66 unique ERIC strategies were reported. EWIs applied an average of 12 implementation strategies (range 3-22). The top three ERIC clusters across all 3 years were Develop stakeholder relationships (21%), Use evaluative/iterative strategies (20%), and Train/educate stakeholders (19%). Most strategies were reported within the Implementation dimension. Strategy use among EWIs meeting the rurality benchmark were also compared.</p><p><strong>Conclusions: </strong>Combining the dimensions from the RE-AIM framework and the ERIC strategies allows for understanding the use of implementation strategies across each RE-AIM dimension. This analysis will support ORH efforts to spread and sustain rural health innovations and evidence-based programs and practices through targeted implementation strategies.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540587/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142121214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Primary care mental health integration to improve early treatment engagement for veterans who screen positive for depression.","authors":"Lucinda B Leung, Karen Chu, Danielle E Rose, Susan E Stockdale, Edward P Post, Jennifer S Funderburk, Lisa V Rubenstein","doi":"10.1111/1475-6773.14354","DOIUrl":"10.1111/1475-6773.14354","url":null,"abstract":"<p><strong>Objective: </strong>To examine the relationship between the penetration (or reach) of a national program aiming to integrate mental health clinicians into all primary care clinics (PC-MHI) and rates of guideline-concordant follow-up and treatment among clinic patients newly identified with depression in the Veterans Health Administration (VA).</p><p><strong>Data sources/study setting: </strong>15,155 screen-positive patients 607,730 patients with 2-item Patient Health Questionnaire scores in 82 primary care clinics, 2015-2019.</p><p><strong>Study design: </strong>In this retrospective cohort study, we used established depression care quality measures to assess primary care patients who (a) newly screened positive (score ≥3) and (b) were identified with depression by clinicians via diagnosis and/or medication (n = 15,155; 15,650 patient-years). Timely follow-up included ≥3 mental health, ≥3 psychotherapy, or ≥3 primary care visits for depression. Minimally appropriate treatment included ≥4 mental health visits, ≥3 psychotherapy, or ≥60 days of medication. In multivariate regressions, we examined whether higher rates of PC-MHI penetration in clinic (proportion of total primary care patients in a clinic who saw any PC-MHI clinician) were associated with greater depression care quality among cohort patients, adjusting for year, healthcare system, and patient and clinic characteristics.</p><p><strong>Data collection/extraction methods: </strong>Electronic health record data from 82 VA clinics across three states.</p><p><strong>Principal findings: </strong>A median of 9% of all primary care patients were seen by any PC-MHI clinician annually. In fully adjusted models, greater PC-MHI penetration was associated with timely depression follow-up within 84 days (∆P = 0.5; SE = 0.1; p < 0.001) and 180 days (∆P = 0.3; SE = 0.1; p = 0.01) of a positive depression screen. Completion of at least minimal treatment within 12 months was high (77%), on average, and not associated with PC-MHI penetration.</p><p><strong>Conclusions: </strong>Greater PC-MHI program penetration was associated with early depression treatment engagement at 84-/180-days among clinic patients newly identified with depression, with no effect on already high rates of completion of minimally sufficient treatment within the year.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540560/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142019635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Engaging healthcare teams to increase access to medications for opioid use disorder.","authors":"Rebecca S Oberman, Alexis K Huynh, Kelsey Cummings, Adam Resnick, Stephanie L Taylor, Alicia A Bergman, Evelyn T Chang","doi":"10.1111/1475-6773.14371","DOIUrl":"10.1111/1475-6773.14371","url":null,"abstract":"<p><strong>Objective: </strong>To assess the effectiveness of evidence-based quality improvement (EBQI) as an implementation strategy to expand the use of medications for opioid use disorder (MOUD) within nonspecialty settings.</p><p><strong>Data sources and study setting: </strong>We studied eight facilities in one Veteran Health Administration (VHA) region from October 2015 to September 2022 using administrative data.</p><p><strong>Study design: </strong>Initially a pilot, we sequentially engaged seven of eight facilities from April 2018 to September 2022 using EBQI, consisting of multilevel stakeholder engagement, technical support, practice facilitation, and data feedback. We established facility-level interdisciplinary quality improvement (QI) teams and a regional-level cross-facility collaborative. We used a nonrandomized stepped wedge design with repeated cross sections to accommodate the phased implementation. Using aggregate facility-level data from October 2015 to September 2022, we analyzed changes in patients receiving MOUD using hierarchical multiple logistic regression.</p><p><strong>Data collection/extraction methods: </strong>Eligible patients had an opioid use disorder (OUD) diagnosis from an outpatient or inpatient visit in the previous year. Receiving MOUD was defined as having been prescribed an opioid agonist or antagonist treatment or a visit to an opioid substitution clinic.</p><p><strong>Principal findings: </strong>The probability of patients with OUD receiving MOUD improved significantly over time for all eight facilities (average marginal effect [AME]: 0.0057, 95% CI: 0.0044, 0.0070) due to ongoing VHA initiatives, with the probability of receiving MOUD increasing by 0.577 percentage points, on average, each quarter, totaling 16 percentage points during the evaluation period. The seven facilities engaging in EBQI experienced, on average, an additional 5.25 percentage point increase in the probability of receiving MOUD (AME: 0.0525, 95%CI: 0.0280, 0.0769). EBQI duration was not associated with changes.</p><p><strong>Conclusions: </strong>EBQI was effective for expanding access to MOUD in nonspecialty settings, resulting in increases in patients receiving MOUD exceeding those associated with temporal trends. Additional research is needed due to recent MOUD expansion legislation.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540584/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142156752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Connecting unstably housed veterans living in rural areas to health care: Perspectives from Health Care Navigators.","authors":"Kalea Jones, Meagan Cusack, Gala True, Taylor E Harris, Jill S Roncarati, Christel Antonellis, Tatiana Brecht, Ann Elizabeth Montgomery","doi":"10.1111/1475-6773.14316","DOIUrl":"10.1111/1475-6773.14316","url":null,"abstract":"<p><strong>Objective: </strong>To understand existing care practices and policies, and potential enhancements, to improve the effectiveness of the US Department of Veterans Affairs (VA) Supportive Services for Veteran Families (SSVF) Health Care Navigators (HCN) in linking Veterans experiencing housing instability in rural areas with health care services.</p><p><strong>Data sources and study setting: </strong>We used primary data collected during semistructured interviews with HCNs (n = 21) serving rural areas across the United States during Spring 2022.</p><p><strong>Study design: </strong>We applied the Consolidated Framework for Implementation Research (CFIR) 2009 and the Social Ecological Model (SEM) to the collection and analysis of qualitative data to understand how HCNs administer services within SSVF and the larger community.</p><p><strong>Data collection/extraction methods: </strong>We used rapid qualitative methods to summarize and analyze data. Templated matrix summaries identified facilitators and barriers to linking Veterans with health care services and policy and practice implications.</p><p><strong>Principal findings: </strong>Using CFIR 2009, we identified contextual factors affecting successful implementation of HCN services within SSVF; we offer a crosswalk between CFIR 2009 and the version updated in 2022. Framing facilitators and barriers within the SEM provided insight into whether implementation strategies should be addressed at a community, interpersonal, or intrapersonal level within the SEM. Facilitators included sufficient knowledge, training, and mentorship opportunities for HCNs and their capacity to collaborate within their organization and with other community-based organizations. Barriers included lack of local technology and housing resources, inadequate understanding of Veterans' service eligibilities and pathways to access those services, and deficient collaboration with the VA.</p><p><strong>Conclusions: </strong>Understanding facilitators and barriers experienced by HCN when linking unstably housed Veterans in rural areas with health care services can inform future strategies, including policy changes such as increased training to support HCNs' understanding of eligibility, benefits, and entitlements as well as improving communication and collaboration between VA and community partners.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540570/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140900416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-world impacts from a decade of Quality Enhancement Research Initiative-partnered projects to translate the Diabetes Prevention Program in the Veterans Health Administration.","authors":"Laura J Damschroder, Alison Hamilton, Melissa M Farmer, Bevanne Bean-Mayberry, Caroline Richardson, Catherine Chanfreau, Rebecca S Oberman, Rachel Lesser, Jackie Lewis, Sue D Raffa, Micheal G Goldstein, Sally Haskell, Erin Finley, Tannaz Moin","doi":"10.1111/1475-6773.14349","DOIUrl":"10.1111/1475-6773.14349","url":null,"abstract":"<p><strong>Objectives: </strong>To describe the impacts of four Veterans Health Administration (VA) Quality Enhancement Research Initiative (QUERI) projects implementing an evidence-based lifestyle intervention known as the Diabetes Prevention Program (DPP).</p><p><strong>Data sources and study setting: </strong>2012-2024 VA administrative and survey data.</p><p><strong>Study design: </strong>This is a summary of findings and impacts from four effectiveness-implementation projects focused on in-person and/or online DPP across VA sites.</p><p><strong>Data collection/extraction methods: </strong>Patient demographics, participation data, and key findings and impacts were summarized across reports from the VA Diabetes-Mellitus Quality Enhancement Research Initiative (QUERI-DM) Diabetes Prevention Program (VA DPP) Trial, QUERI-DM Online DPP Trial, the Enhancing Mental and Physical Health of Women through Engagement and Retention (EMPOWER) QUERI DPP Project, and EMPOWER 2.0 QUERI Program.</p><p><strong>Principal findings: </strong>Between 2012 and 2024, four VA QUERI studies enrolled 963 Veterans in DPP across 16 VA sites. All participants had overweight/obesity with one additional risk factor for type 2 diabetes (i.e., prediabetes, elevated risk score, or history of gestational diabetes) and 56% (N = 536) were women. In addition to enhancing the reach of and engagement in diabetes prevention services among Veterans, these projects resulted in three key impacts as follows: (1) informing the national redesign of VA MOVE! including recommendations to increase the number of MOVE! sessions and revise guidelines across 150+ VA sites, (2) enhancing the national evidence base to support online DPP delivery options with citations in national care guidelines outside VA, and (3) demonstrating the importance of gender-tailoring of preventive care services by and for women Veterans to enhance engagement in preventive services.</p><p><strong>Conclusions: </strong>Over the past decade, the evolution of VA QUERI DPP projects increased the reach of and engagement in diabetes prevention services among Veterans, including women Veterans who have been harder to engage in lifestyle change programs in VA, and resulted in three key impacts informing type 2 diabetes and obesity prevention efforts within and outside of VA.</p>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540559/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141536028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aligning quality improvement, research, and health system goals using the QUERI priority-setting process: A step forward in creating a learning health system.","authors":"Kara L Beck, Amy M Kilbourne, Stefanie I Gidmark, Melissa Z Braganza","doi":"10.1111/1475-6773.14388","DOIUrl":"10.1111/1475-6773.14388","url":null,"abstract":"","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540569/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142332735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}