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McCurdy H, Nobbe A, Scott D, Patton H, Morgan TR, Bajaj JS, Yakovchenko V, Merante M, Gibson S, Lamorte C, Baffy G, Ioannou GN, Taddei TH, Rozenberg-Ben-Dror K, Anwar J, Dominitz JA, Rogal SS. Organizational and Implementation Factors Associated with Cirrhosis Care in the Veterans Health Administration. Dig Dis Sci 2024; 69:2008-2017. [PMID: 38616215 DOI: 10.1007/s10620-024-08409-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 03/25/2024] [Indexed: 04/16/2024]
Abstract
BACKGROUND The Veterans Health Administration provides care to more than 100,000 Veterans with cirrhosis. AIMS This implementation evaluation aimed to understand organizational resources and barriers associated with cirrhosis care. METHODS Clinicians across 145 Department of Veterans Affairs (VA) medical centers (VAMCs) were surveyed in 2022 about implementing guideline-concordant cirrhosis care. VA Corporate Data Warehouse data were used to assess VAMC performance on two national cirrhosis quality measures: HCC surveillance and esophageal variceal surveillance or treatment (EVST). Organizational factors associated with higher performance were identified using linear regression models. RESULTS Responding VAMCs (n = 124, 86%) ranged in resource availability, perceived barriers, and care processes. In multivariable models, factors independently associated with HCC surveillance included on-site interventional radiology and identifying patients overdue for surveillance using a national cirrhosis population management tool ("dashboard"). EVST was significantly associated with dashboard use and on-site gastroenterology services. For larger VAMCs, the average HCC surveillance rate was similar between VAMCs using vs. not using the dashboard (47% vs. 41%), while for smaller and less resourced VAMCs, dashboard use resulted in a 13% rate difference (46% vs. 33%). Likewise, higher EVST rates were more strongly associated with dashboard use in smaller (55% vs. 50%) compared to larger (57% vs. 55%) VAMCs. CONCLUSIONS Resources, barriers, and care processes varied across diverse VAMCs. Smaller VAMCs without specialty care achieved HCC and EVST surveillance rates nearly as high as more complex and resourced VAMCs if they used a population management tool to identify the patients due for cirrhosis care.
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Affiliation(s)
- Heather McCurdy
- Gastroenterology Section, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Anna Nobbe
- Digestive Diseases Section, Cincinnati VA Medical Center, Cincinnati, OH, USA
| | - Dawn Scott
- VA Central Texas Healthcare System, Temple, TX, USA
| | - Heather Patton
- VA San Diego Healthcare System, San Diego, CA, USA
- University of California San Diego, La Jolla, CA, USA
| | - Timothy R Morgan
- VA Long Beach Healthcare System, Long Beach, CA, USA
- Department of Medicine, University of California, Irvine, CA, USA
- National Gastroenterology and Hepatology Program, Department of Veterans Affairs, Veterans Health Administration, Washington, DC, USA
| | - Jasmohan S Bajaj
- Division of Gastroenterology, Hepatology and Nutrition, Virginia Commonwealth University, Richmond, VA, USA
- Division of Gastroenterology, Hepatology and Nutrition, Central Virginia VA Health Care System, Richmond, VA, USA
| | - Vera Yakovchenko
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Monica Merante
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Sandra Gibson
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Carolyn Lamorte
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Gyorgy Baffy
- Section of Gastroenterology, Department of Medicine, VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - George N Ioannou
- VA Puget Sound Health Care System, Seattle, WA, USA
- University of Washington, Seattle, WA, USA
| | - Tamar H Taddei
- VA Connecticut Healthcare System, West Haven, CT, USA
- Yale University, New Haven, CT, USA
| | | | - Jennifer Anwar
- VA Long Beach Healthcare System, Long Beach, CA, USA
- National Gastroenterology and Hepatology Program, Department of Veterans Affairs, Veterans Health Administration, Washington, DC, USA
| | - Jason A Dominitz
- National Gastroenterology and Hepatology Program, Department of Veterans Affairs, Veterans Health Administration, Washington, DC, USA
- VA Puget Sound Health Care System, Seattle, WA, USA
- University of Washington, Seattle, WA, USA
| | - Shari S Rogal
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA.
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Surgery, University of Pittsburgh, Pittsburgh, PA, USA.
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Building 30 Room 2A113, University Drive (151C), Pittsburgh, PA, 15240, USA.
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Garrido MM, Legler A, Strombotne KL, Frakt AB. Differences in adverse outcomes across race and ethnicity among Veterans with similar predicted risks of an overdose or suicide-related event. PAIN MEDICINE (MALDEN, MASS.) 2024; 25:125-130. [PMID: 37738604 DOI: 10.1093/pm/pnad129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 08/16/2023] [Accepted: 09/18/2023] [Indexed: 09/24/2023]
Abstract
OBJECTIVE To evaluate the degree to which differences in incidence of mortality and serious adverse events exist across patient race and ethnicity among Veterans Health Administration (VHA) patients receiving outpatient opioid prescriptions and who have similar predicted risks of adverse outcomes. Patients were assigned scores via the VHA Stratification Tool for Opioid Risk Mitigation (STORM), a model used to predict the risk of experiencing overdose- or suicide-related health care events or death. Individuals with the highest STORM risk scores are targeted for case review. DESIGN Retrospective cohort study of high-risk veterans who received an outpatient prescription opioid between 4/2018-3/2019. SETTING All VHA medical centers. PARTICIPANTS In total, 84 473 patients whose estimated risk scores were between 0.0420 and 0.0609, the risk scores associated with the top 5%-10% of risk in the STORM development sample. METHODS We examined the expected probability of mortality and serious adverse events (SAEs; overdose or suicide-related events) given a patient's risk score and race. RESULTS Given a similar risk score, Black patients were less likely than White patients to have a recorded SAE within 6 months of risk score calculation. Black, Hispanic, and Asian patients were less likely than White patients with similar risk scores to die within 6 months of risk score calculation. Some of the mortality differences were driven by age differences in the composition of racial and ethnic groups in our sample. CONCLUSIONS Our results suggest that relying on the STORM model to identify patients who may benefit from an interdisciplinary case review may identify patients with clinically meaningful differences in outcome risk across race and ethnicity.
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Affiliation(s)
- Melissa M Garrido
- Partnered Evidence-based Policy Resource Center, VA Boston Healthcare System, Boston, MA 02130, United States
- Department of Health Law, Policy and Management, Boston University School of Public Health, Boston, MA 02118, United States
| | - Aaron Legler
- Partnered Evidence-based Policy Resource Center, VA Boston Healthcare System, Boston, MA 02130, United States
| | - Kiersten L Strombotne
- Partnered Evidence-based Policy Resource Center, VA Boston Healthcare System, Boston, MA 02130, United States
- Department of Health Law, Policy and Management, Boston University School of Public Health, Boston, MA 02118, United States
| | - Austin B Frakt
- Partnered Evidence-based Policy Resource Center, VA Boston Healthcare System, Boston, MA 02130, United States
- Department of Health Law, Policy and Management, Boston University School of Public Health, Boston, MA 02118, United States
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Cambridge, MA 02115, United States
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Smith MY, Gaglio B, Anatchkova M. The use of implementation science theories, models, and frameworks in implementation research for medicinal products: A scoping review. Health Res Policy Syst 2024; 22:17. [PMID: 38287407 PMCID: PMC10823700 DOI: 10.1186/s12961-024-01102-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 01/05/2024] [Indexed: 01/31/2024] Open
Abstract
BACKGROUND The uptake, adoption and integration of new medicines and treatment regimens within healthcare delivery can take a decade or more. Increasingly, implementation science (IS) research is being used to bridge this gap between the availability of new therapeutic evidence and its actual application in clinical practice. Little is known, however, about the quality of IS research in this area, including the degree to which theories, models and frameworks (TMFs) are being used. The objective of this study was to conduct a scoping review of the use of TMFs in implementation research involving medicinal products. METHODS A search was conducted for English language abstracts and manuscripts describing the application of TMFs in IS studies for medicinal products. Eligible publications were those published between 1 January 1974 and 12 December 2022. All records were screened at the title and abstract stage; included full-text papers were abstracted using data extraction tables designed for the study. Study quality was appraised using the Implementation Research Development Tool. RESULTS The initial scoping search identified 2697 publications, of which 9 were ultimately eligible for inclusion in the review. Most studies were published after 2020 and varied in their objectives, design and therapeutic area. Most studies had sample sizes of fewer than 50 participants, and all focused on the post-marketing phase of drug development. The TMF most frequently used was the Consolidated Framework for Implementation Research (CFIR). Although most studies applied all TMF domains, TMF use was limited to instrument development and/or qualitative analysis. Quality appraisals indicated the need for engaging patients and other stakeholders in the implementation research, reporting on the cost of implementation strategies, and evaluating the unintended consequences of implementation efforts. CONCLUSIONS We found that few IS studies involving medicinal products reported using TMFs. Those that did encompassed a wide variety of therapeutic indications and medicinal products; all were in the post-marketing phase and involved limited application of the TMFs. Researchers should consider conducting IS in earlier phases of drug development and integrating the TMFs throughout the research process. More consistent and in-depth use of TMFs may help advance research in this area.
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Affiliation(s)
- Meredith Y Smith
- Evidera, Inc., Bethesda, MD, United States of America.
- Department of Regulatory and Quality Sciences, School of Pharmacy, University of Southern California, Los Angeles, CA, United States of America.
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Held U, Forzy T, Signorell A, Deforth M, Burgstaller JM, Wertli MM. Development and internal validation of a prediction model for long-term opioid use-an analysis of insurance claims data. Pain 2024; 165:44-53. [PMID: 37782553 PMCID: PMC10723645 DOI: 10.1097/j.pain.0000000000003023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 06/02/2023] [Accepted: 06/05/2023] [Indexed: 10/04/2023]
Abstract
ABSTRACT In the United States, a public-health crisis of opioid overuse has been observed, and in Europe, prescriptions of opioids are strongly increasing over time. The objective was to develop and validate a multivariable prognostic model to be used at the beginning of an opioid prescription episode, aiming to identify individual patients at high risk for long-term opioid use based on routinely collected data. Predictors including demographics, comorbid diseases, comedication, morphine dose at episode initiation, and prescription practice were collected. The primary outcome was long-term opioid use, defined as opioid use of either >90 days duration and ≥10 claims or >120 days, independent of the number of claims. Traditional generalized linear statistical regression models and machine learning approaches were applied. The area under the curve, calibration plots, and the scaled Brier score assessed model performance. More than four hundred thousand opioid episodes were included. The final risk prediction model had an area under the curve of 0.927 (95% confidence interval 0.924-0.931) in the validation set, and this model had a scaled Brier score of 48.5%. Using a threshold of 10% predicted probability to identify patients at high risk, the overall accuracy of this risk prediction model was 81.6% (95% confidence interval 81.2% to 82.0%). Our study demonstrated that long-term opioid use can be predicted at the initiation of an opioid prescription episode, with satisfactory accuracy using data routinely collected at a large health insurance company. Traditional statistical methods resulted in higher discriminative ability and similarly good calibration as compared with machine learning approaches.
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Affiliation(s)
- Ulrike Held
- Department of Biostatistics at Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Tom Forzy
- Master Program Statistics, ETH Zurich, Zurich, Switzerland
| | - Andri Signorell
- Department of Health Sciences, Helsana, Dübendorf, Switzerland
| | - Manja Deforth
- Department of Biostatistics at Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Jakob M. Burgstaller
- Institute of Primary Care, University and University Hospital Zurich, Zurich, Switzerland
| | - Maria M. Wertli
- Department of Internal Medicine, Cantonal Hospital Baden KSB, Baden, Switzerland
- Department of General Internal Medicine University Hospital Bern, University of Bern, Switzerland
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Smith JD, Norton WE, Mitchell SA, Cronin C, Hassett MJ, Ridgeway JL, Garcia SF, Osarogiagbon RU, Dizon DS, Austin JD, Battestilli W, Richardson JE, Tesch NK, Cella D, Cheville AL, DiMartino LD. The Longitudinal Implementation Strategy Tracking System (LISTS): feasibility, usability, and pilot testing of a novel method. Implement Sci Commun 2023; 4:153. [PMID: 38017582 PMCID: PMC10683230 DOI: 10.1186/s43058-023-00529-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 11/09/2023] [Indexed: 11/30/2023] Open
Abstract
BACKGROUND Systematic approaches are needed to accurately characterize the dynamic use of implementation strategies and how they change over time. We describe the development and preliminary evaluation of the Longitudinal Implementation Strategy Tracking System (LISTS), a novel methodology to document and characterize implementation strategies use over time. METHODS The development and initial evaluation of the LISTS method was conducted within the Improving the Management of SymPtoms during And following Cancer Treatment (IMPACT) Research Consortium (supported by funding provided through the NCI Cancer MoonshotSM). The IMPACT Consortium includes a coordinating center and three hybrid effectiveness-implementation studies testing routine symptom surveillance and integration of symptom management interventions in ambulatory oncology care settings. LISTS was created to increase the precision and reliability of dynamic changes in implementation strategy use over time. It includes three components: (1) a strategy assessment, (2) a data capture platform, and (3) a User's Guide. An iterative process between implementation researchers and practitioners was used to develop, pilot test, and refine the LISTS method prior to evaluating its use in three stepped-wedge trials within the IMPACT Consortium. The LISTS method was used with research and practice teams for approximately 12 months and subsequently we evaluated its feasibility, acceptability, and usability using established instruments and novel questions developed specifically for this study. RESULTS Initial evaluation of LISTS indicates that it is a feasible and acceptable method, with content validity, for characterizing and tracking the use of implementation strategies over time. Users of LISTS highlighted several opportunities for improving the method for use in future and more diverse implementation studies. CONCLUSIONS The LISTS method was developed collaboratively between researchers and practitioners to fill a research gap in systematically tracking implementation strategy use and modifications in research studies and other implementation efforts. Preliminary feedback from LISTS users indicate it is feasible and usable. Potential future developments include additional features, fewer data elements, and interoperability with alternative data entry platforms. LISTS offers a systematic method that encourages the use of common data elements to support data analysis across sites and synthesis across studies. Future research is needed to further adapt, refine, and evaluate the LISTS method in studies with employ diverse study designs and address varying delivery settings, health conditions, and intervention types.
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Affiliation(s)
- Justin D Smith
- Department of Population Health Sciences, School of Medicine, University of Utah, Spencer Fox Eccles, Salt Lake City, UT, USA.
- Departments of Psychiatry and Behavioral Science and Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
| | - Wynne E Norton
- Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD, USA
| | - Sandra A Mitchell
- Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD, USA
| | - Christine Cronin
- Division of Population Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Michael J Hassett
- Departments of Medical Oncology and Quality & Patient Safety, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Jennifer L Ridgeway
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery and Division of Health Care Delivery Research, Mayo Clinic, Rochester, MN, USA
| | - Sofia F Garcia
- Departments of Psychiatry and Behavioral Science and Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Raymond U Osarogiagbon
- Multidisciplinary Thoracic Oncology Program, Thoracic Oncology Research Group, Baptist Cancer Center, Memphis, TN, USA
| | - Don S Dizon
- Division of Hematology-Oncology, Department of Medicine, Legoretta Cancer Center, The Warren Alpert Medical School of Brown University, and Lifespan Cancer Institute, Providence, USA
| | - Jessica D Austin
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Scottsdale, AZ, USA
| | - Whitney Battestilli
- Center for Clinical Research Informatics, RTI International, Durham, NC, USA
| | - Joshua E Richardson
- Center for Health Informatics, RTI International, Research Triangle Park, Fayetteville, NC, USA
| | - Nathan K Tesch
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA
| | - David Cella
- Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine and Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL, USA
| | - Andrea L Cheville
- Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, MN, USA
| | - Lisa D DiMartino
- Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA
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Juckett LA, Bernard KP, Thomas KS. Partnering with social service staff to implement pragmatic clinical trials: an interim analysis of implementation strategies. Trials 2023; 24:739. [PMID: 37978528 PMCID: PMC10656935 DOI: 10.1186/s13063-023-07757-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 10/27/2023] [Indexed: 11/19/2023] Open
Abstract
BACKGROUND With recent growth in the conduct of pragmatic clinical trials, the reliance on frontline staff to contribute to trial-related activities has grown as well. Active partnerships with staff members are often critical to pragmatic trial implementation, but rarely do research teams track and evaluate the specific "implementation strategies" used to support staff's involvement in trial procedures (e.g., participant recruitment). Accordingly, we adapted implementation science methodologies and conducted an interim analysis of the strategies deployed with social service staff involved in one multi-site pragmatic clinical trial. METHODS We used a naturalistic, observational study design to characterize strategies our research team deployed with staff during monthly, virtual meetings. Data were drawn from meeting notes and recordings from the trial's 4-month Preparation phase and 8-month Implementation phase. Strategies were mapped to the Expert Recommendations for Implementing Change taxonomy and categorized into nine implementation clusters. Survey data were also collected from staff to identify the most useful strategies the research team should deploy when onboarding new staff members in the trial's second year. RESULTS A total of 287 strategies were deployed. Strategies in the develop stakeholder interrelationships cluster predominated in both the Preparation (35%) and Implementation (31%) phases, followed by strategies in the use iterative and evaluative approaches cluster, though these were more prevalent during trial Preparation (24%) as compared to trial Implementation (18%). When surveyed on strategy usefulness, strategies in the provide interactive assistance, use financial approaches, and support staff clusters were most useful, per staff responses. CONCLUSIONS While strategies to develop stakeholder interrelationships were used most frequently during trial Preparation and Implementation, program staff perceived strategies that provided technical assistance, supported clinicians, and used financial approaches to be most useful and should be deployed when onboarding new staff members. Research teams are encouraged to adapt and apply implementation strategy tracking methods when partnering with social service staff and deploy practical strategies that support pragmatic trial success given staff needs and preferences. TRIAL REGISTRATION NCT05357261. May 2, 2022.
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Affiliation(s)
- Lisa A Juckett
- School of Health and Rehabilitation Sciences, The Ohio State University, 453 West 10th Avenue, Columbus, OH, USA.
| | | | - Kali S Thomas
- School of Public Health, Brown University, Providence, RI, USA
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McElfresh DC, Chen L, Oliva E, Joyce V, Rose S, Tamang S. A call for better validation of opioid overdose risk algorithms. J Am Med Inform Assoc 2023; 30:1741-1746. [PMID: 37428897 PMCID: PMC10531142 DOI: 10.1093/jamia/ocad110] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 05/11/2023] [Accepted: 07/01/2023] [Indexed: 07/12/2023] Open
Abstract
Clinical decision support (CDS) systems powered by predictive models have the potential to improve the accuracy and efficiency of clinical decision-making. However, without sufficient validation, these systems have the potential to mislead clinicians and harm patients. This is especially true for CDS systems used by opioid prescribers and dispensers, where a flawed prediction can directly harm patients. To prevent these harms, regulators and researchers have proposed guidance for validating predictive models and CDS systems. However, this guidance is not universally followed and is not required by law. We call on CDS developers, deployers, and users to hold these systems to higher standards of clinical and technical validation. We provide a case study on two CDS systems deployed on a national scale in the United States for predicting a patient's risk of adverse opioid-related events: the Stratification Tool for Opioid Risk Mitigation (STORM), used by the Veterans Health Administration, and NarxCare, a commercial system.
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Affiliation(s)
- Duncan C McElfresh
- Department of Health Policy, Stanford University, Stanford, California, USA
- Program Evaluation Resource Center, Office of Mental Health and Suicide Prevention, US Department of Veterans Affairs, Menlo Park, California, USA
| | - Lucia Chen
- Department of Health Policy, Stanford University, Stanford, California, USA
| | - Elizabeth Oliva
- Program Evaluation Resource Center, Office of Mental Health and Suicide Prevention, US Department of Veterans Affairs, Menlo Park, California, USA
| | - Vilija Joyce
- Program Evaluation Resource Center, Office of Mental Health and Suicide Prevention, US Department of Veterans Affairs, Menlo Park, California, USA
- Health Economics Resource Center, US Department of Veterans Affairs, Menlo Park, California, USA
| | - Sherri Rose
- Department of Health Policy, Stanford University, Stanford, California, USA
| | - Suzanne Tamang
- Program Evaluation Resource Center, Office of Mental Health and Suicide Prevention, US Department of Veterans Affairs, Menlo Park, California, USA
- Department of Medicine, Stanford University, Stanford, California, USA
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Kelley AT, Incze MA, Baylis JD, Calder SG, Weiner SJ, Zickmund SL, Jones AL, Vanneman ME, Conroy MB, Gordon AJ, Bridges JF. Patient-centered quality measurement for opioid use disorder: Development of a taxonomy to address gaps in research and practice. Subst Abus 2022; 43:1286-1299. [PMID: 35849749 PMCID: PMC9703846 DOI: 10.1080/08897077.2022.2095082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
Background: Evidence-based treatment is provided infrequently and inconsistently to patients with opioid use disorder (OUD). Treatment guidelines call for high-quality, patient-centered care that meets individual preferences and needs, but it is unclear whether current quality measures address individualized aspects of care and whether measures of patient-centered OUD care are supported by evidence. Methods: We conducted an environmental scan of OUD care quality to (1) evaluate patient-centeredness in current OUD quality measures endorsed by national agencies and in national OUD treatment guidelines; and (2) review literature evidence for patient-centered care in OUD diagnosis and management, including gaps in current guidelines, performance data, and quality measures. We then synthesized these findings to develop a new quality measurement taxonomy that incorporates patient-centered aspects of care and identifies priority areas for future research and quality measure development. Results: Across 31 endorsed OUD quality measures, only two measures of patient experience incorporated patient preferences and needs, while national guidelines emphasized providing patient-centered care. Among 689 articles reviewed, evidence varied for practices of patient-centered care. Many practices were supported by guidelines and substantial evidence, while others lacked evidence despite guideline support. Our synthesis of findings resulted in EQuIITable Care, a taxonomy comprised of six classifications: (1) patient Experience and engagement, (2) Quality of life; (3) Identification of patient risks; (4) Interventions to mitigate patient risks; (5) Treatment; and (6) Care coordination and navigation. Conclusions: Current quality measurement for OUD lacks patient-centeredness. EQuIITable Care for OUD provides a roadmap to develop measures of patient-centered care for OUD.
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Affiliation(s)
- A. Taylor Kelley
- Informatics, Decision-Enhancement and Analytic Sciences (IDEAS) Center, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Vulnerable Veteran Innovative Patient-aligned Care Team (VIP), VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Division of General Internal Medicine, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
- Program for Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Michael A. Incze
- Division of General Internal Medicine, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
- Program for Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Jacob D. Baylis
- Informatics, Decision-Enhancement and Analytic Sciences (IDEAS) Center, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Vulnerable Veteran Innovative Patient-aligned Care Team (VIP), VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Program for Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Spencer G. Calder
- Informatics, Decision-Enhancement and Analytic Sciences (IDEAS) Center, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Vulnerable Veteran Innovative Patient-aligned Care Team (VIP), VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Program for Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Saul J. Weiner
- Center of Innovation for Complex Chronic Healthcare, Jesse Brown VA Chicago Health Care System, Chicago, Illinois, USA
- Division of Academic Internal Medicine and Geriatrics, Department of Medicine, The University of Illinois College of Medicine at Chicago, Chicago, Illinois, USA
| | - Susan L. Zickmund
- Informatics, Decision-Enhancement and Analytic Sciences (IDEAS) Center, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Audrey L. Jones
- Informatics, Decision-Enhancement and Analytic Sciences (IDEAS) Center, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Vulnerable Veteran Innovative Patient-aligned Care Team (VIP), VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Program for Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Megan E. Vanneman
- Informatics, Decision-Enhancement and Analytic Sciences (IDEAS) Center, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Program for Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
- Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Molly B. Conroy
- Division of General Internal Medicine, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Adam J. Gordon
- Informatics, Decision-Enhancement and Analytic Sciences (IDEAS) Center, VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Vulnerable Veteran Innovative Patient-aligned Care Team (VIP), VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Program for Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - John F.P. Bridges
- Department of Biomedical Informatics, The Ohio State University College of Medicine, Columbus, Ohio, USA
- Department of Health, Behavior, and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
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Yakovchenko V, Morgan TR, Miech EJ, Neely B, Lamorte C, Gibson S, Beste LA, McCurdy H, Scott D, Gonzalez R, Park A, Powell BJ, Bajaj JS, Dominitz JA, Chartier M, Ross D, Chinman MJ, Rogal SS. Core implementation strategies for improving cirrhosis care in the Veterans Health Administration. Hepatology 2022; 76:404-417. [PMID: 35124820 PMCID: PMC9288973 DOI: 10.1002/hep.32395] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 01/11/2022] [Accepted: 01/14/2022] [Indexed: 12/28/2022]
Abstract
BACKGROUND AND AIMS The Veterans Health Administration (VHA) provides care for more than 80,000 veterans with cirrhosis. This longitudinal, multimethod evaluation of a cirrhosis care quality improvement program aimed to (1) identify implementation strategies associated with evidence-based, guideline-concordant cirrhosis care over time, and (2) use qualitative interviews to operationalize strategies for a manualized intervention. APPROACH AND RESULTS VHA providers were surveyed annually about the use of 73 implementation strategies to improve cirrhosis care in fiscal years 2018 (FY18) and 2019 (FY19). Implementation strategies linked to guideline-concordant cirrhosis care were identified using bivariate statistics and comparative configurational methods. Semistructured interviews were conducted with 12 facilities in the highest quartile of cirrhosis care to specify the successful implementation strategies and their mechanisms of change. A total of 106 VHA facilities (82%) responded at least once over the 2-year period (FY18, n = 63; FY19, n = 100). Facilities reported using a median of 12 (interquartile range [IQR] 20) implementation strategies in FY18 and 10 (IQR 19) in FY19. Of the 73 strategies, 35 (48%) were positively correlated with provision of evidence-based cirrhosis care. Configurational analysis identified multiple strategy pathways directly linked to more guideline-concordant cirrhosis care. Across both methods, a subset of eight strategies was determined to be core to cirrhosis care improvement and specified using qualitative interviews. CONCLUSIONS In a national cirrhosis care improvement initiative, a multimethod approach identified a core subset of successful implementation strategy combinations. This process of empirically identifying and specifying implementation strategies may be applicable to other implementation challenges in hepatology.
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Affiliation(s)
- Vera Yakovchenko
- Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, Bedford, MA
| | - Timothy R. Morgan
- Gastroenterology Section, VA Long Beach Healthcare System, Long Beach, CA,Division of Gastroenterology, Department of Medicine, University of California, Irvine, CA
| | - Edward J. Miech
- Department of Veterans Affairs, Roudebush VA Medical Center, HSR&D Center for Health Information & Communication, VA PRIS-M QUERI, Indianapolis, IN,Regenstrief Institute, Indianapolis, IN
| | - Brittney Neely
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA
| | - Carolyn Lamorte
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA
| | - Sandra Gibson
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA,Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA
| | - Lauren A. Beste
- Division of General Internal Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, WA,General Medicine Service, VA Puget Sound Health Care System, Seattle, WA
| | | | - Dawn Scott
- Department of Medicine, Central Texas Veterans Healthcare System, Temple, TX
| | - Rachel Gonzalez
- Department of Veterans Affairs, Sierra Pacific Veterans Integrated Service Network, Pharmacy Benefits Management, Mather, CA
| | - Angela Park
- Office of Healthcare Transformation, Department of Veterans Affairs, Washington, DC
| | - Byron J. Powell
- Brown School, Washington University in St. Louis, St. Louis, MO
| | - Jasmohan S. Bajaj
- Division of Gastroenterology, Hepatology, and Nutrition, Virginia Commonwealth University, Richmond, VA,Division of Gastroenterology, Central Virginia Veterans Affairs Healthcare System, Richmond, VA
| | - Jason A. Dominitz
- Gastroenterology Section, Veterans Affairs Puget Sound Health Care System, Seattle, WA,Division of Gastroenterology, Department of Medicine, University of Washington School of Medicine, Seattle, WA
| | - Maggie Chartier
- HIV, Hepatitis, and Related Conditions Programs, Office of Specialty Care Services, Veterans Health Administration, Washington, DC
| | - David Ross
- HIV, Hepatitis, and Related Conditions Programs, Office of Specialty Care Services, Veterans Health Administration, Washington, DC
| | - Matthew J. Chinman
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA,RAND Corporation, Pittsburgh, PA
| | - Shari S. Rogal
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA,Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA,Department of Surgery, University of Pittsburgh, Pittsburgh, PA
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10
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Atkins D, Makridis CA, Alterovitz G, Ramoni R, Clancy C. Developing and Implementing Predictive Models in a Learning Healthcare System: Traditional and Artificial Intelligence Approaches in the Veterans Health Administration. Annu Rev Biomed Data Sci 2022; 5:393-413. [PMID: 35609894 DOI: 10.1146/annurev-biodatasci-122220-110053] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Predicting clinical risk is an important part of healthcare and can inform decisions about treatments, preventive interventions, and provision of extra services. The field of predictive models has been revolutionized over the past two decades by electronic health record data; the ability to link such data with other demographic, socioeconomic, and geographic information; the availability of high-capacity computing; and new machine learning and artificial intelligence methods for extracting insights from complex datasets. These advances have produced a new generation of computerized predictive models, but debate continues about their development, reporting, validation, evaluation, and implementation. In this review we reflect on more than 10 years of experience at the Veterans Health Administration, the largest integrated healthcare system in the United States, in developing, testing, and implementing such models at scale. We report lessons from the implementation of national risk prediction models and suggest an agenda for research. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- David Atkins
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, USA;
| | - Christos A Makridis
- National Artificial Intelligence Institute, Department of Veterans Affairs, Washington, DC, USA
| | - Gil Alterovitz
- National Artificial Intelligence Institute, Department of Veterans Affairs, Washington, DC, USA
| | - Rachel Ramoni
- Office of Research and Development, Department of Veterans Affairs, Washington, DC, USA;
| | - Carolyn Clancy
- Office of Discovery, Education and Affiliate Networks, Department of Veterans Affairs, Washington, DC, USA
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11
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Abstract
This paper is the forty-third consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2020 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonists and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (1), the roles of these opioid peptides and receptors in pain and analgesia in animals (2) and humans (3), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (4), opioid peptide and receptor involvement in tolerance and dependence (5), stress and social status (6), learning and memory (7), eating and drinking (8), drug abuse and alcohol (9), sexual activity and hormones, pregnancy, development and endocrinology (10), mental illness and mood (11), seizures and neurologic disorders (12), electrical-related activity and neurophysiology (13), general activity and locomotion (14), gastrointestinal, renal and hepatic functions (15), cardiovascular responses (16), respiration and thermoregulation (17), and immunological responses (18).
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Affiliation(s)
- Richard J Bodnar
- Department of Psychology and Neuropsychology Doctoral Sub-Program, Queens College, City University of New York, Flushing, NY, 11367, United States.
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12
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McCarthy SA, Chinman M, Rogal SS, Klima G, Hausmann LRM, Mor MK, Shah M, Hale JA, Zhang H, Gordon AJ, Gellad WF. Tracking the randomized rollout of a Veterans Affairs opioid risk management tool: A multi-method implementation evaluation using the Consolidated Framework for Implementation Research (CFIR). IMPLEMENTATION RESEARCH AND PRACTICE 2022; 3:26334895221114665. [PMID: 37091078 PMCID: PMC9924239 DOI: 10.1177/26334895221114665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022] Open
Abstract
Background The Veterans Health Administration (VHA) developed the Stratification Tool for Opioid Risk Mitigation (STORM) dashboard to assist in identifying Veterans at risk for adverse opioid overdose or suicide-related events. In 2018, a policy was implemented requiring VHA facilities to complete case reviews of Veterans identified by STORM as very high risk for adverse events. Nationally, facilities were randomized in STORM implementation to four arms based on required oversight and by the timing of an increase in the number of required case reviews. To help evaluate this policy intervention, we aimed to (1) identify barriers and facilitators to implementing case reviews; (2) assess variation across the four arms; and (3) evaluate associations between facility characteristics and implementation barriers and facilitators. Method Using the Consolidated Framework for Implementation Research (CFIR), we developed a semi-structured interview guide to examine barriers to and facilitators of implementing the STORM policy. A total of 78 staff from 39 purposefully selected facilities were invited to participate in telephone interviews. Interview transcripts were coded and then organized into memos, which were rated using the −2 to + 2 CFIR rating system. Descriptive statistics were used to evaluate the mean ratings on each CFIR construct, the associations between ratings and study arm, and three facility characteristics (size, rurality, and academic detailing) associated with CFIR ratings. We used the mean CFIR rating for each site to determine which constructs differed between the sites with highest and lowest overall CFIR scores, and these constructs were described in detail. Results Two important CFIR constructs emerged as barriers to implementation: Access to knowledge and information and Evaluating and reflecting. Little time to complete the CASE reviews was a pervasive barrier. Sites with higher overall CFIR scores showed three important facilitators: Leadership engagement, Engaging, and Implementation climate. CFIR ratings were not significantly different between the four study arms, nor associated with facility characteristics. Plain Language Summary: The Veterans Health Administration (VHA) created a tool called the Stratification Tool for Opioid Risk Mitigation dashboard. This dashboard shows Veterans at risk for opioid overdose or suicide-related events. In 2018, a national policy required all VHA facilities to complete case reviews for Veterans who were at high risk for these events. To evaluate this policy implementation, 78 staff from 39 facilities were interviewed. The Consolidated Framework for Implementation Research (CFIR) implementation framework was used to create the interview. Interview transcripts were coded and organized into site memos. The site memos were rated using CFIR's −2 to +2 rating system. Ratings did not differ for four study arms related to oversight and timing. Ratings were not associated with facility characteristics. Leadership, engagement and implementation climate were the strongest facilitators for implementation. Lack of time, knowledge, and feedback were important barriers.
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Affiliation(s)
- Sharon A. McCarthy
- Veterans Integrated Service Network 4 Mental Illness Research, Education and Clinical Center, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Matthew Chinman
- Veterans Integrated Service Network 4 Mental Illness Research, Education and Clinical Center, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
- RAND Corporation, Pittsburgh, PA, USA
| | - Shari S. Rogal
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Gloria Klima
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Leslie R. M. Hausmann
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Maria K. Mor
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Mala Shah
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Jennifer A. Hale
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Hongwei Zhang
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Adam J. Gordon
- Informatics, Decision-Enhancement, and Analytic Sciences Center, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- Program for Addiction Research, Clinical Care, Knowledge, and Advocacy (PARCKA), Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Walid F. Gellad
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
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13
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Implementing immediate postpartum contraception: a comparative case study at 11 hospitals. Implement Sci Commun 2021; 2:42. [PMID: 33845922 PMCID: PMC8042857 DOI: 10.1186/s43058-021-00136-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 03/19/2021] [Indexed: 12/27/2022] Open
Abstract
Background Immediate postpartum long-acting reversible contraception (LARC) is an evidence-based practice, but hospitals face significant barriers to its adoption. Our objective was to examine how organizational context (e.g., size, employee attitudes toward the clinical practice) and implementation strategies (i.e., the actions taken to routinize a clinical practice) drive successful implementation of immediate postpartum LARC services, with a goal of informing the design of future implementation interventions. Methods We conducted a comparative case study of the implementation of inpatient postpartum contraceptive care at 11 US maternity hospitals. In 2017–2018, we conducted site visits that included semi-structured key informant interviews informed by the Consolidated Framework for Implementation Research. Qualitative measures of implementation success included stakeholder satisfaction, routinization, and sustainability of immediate postpartum LARC services. Qualitative content analysis and cross-case synthesis explored relationships among organizational context, implementation strategies, and implementation success. Results We completed semi-structured interviews with 78 clinicians, nurses, residents, pharmacy and revenue cycle staff, and hospital administrators. Successful implementation required three essential conditions: effective implementation champions, an enabling financial environment, and hospital administrator engagement. Six other contextual conditions were influential: trust and effective communication, alignment with stakeholders’ professional values, perception of meeting patients’ needs, robust learning climate, compatibility with workflow, and positive attitudes and adequate knowledge about the clinical practice. On average, sites used 18 (range 11-22) strategies. Strategies to optimize the financial environment and train clinicians and staff were commonly used. Strategies to plan and evaluate implementation and to engage patients emerged as promising to address barriers to practice change, yet were often underused. Conclusions Implementation efforts in maternity settings may be more successful if they select strategies to optimize local conditions for success. Our findings elucidate key contextual conditions to target and provide a menu of promising implementation strategies for incorporating recommended contraceptive services into routine maternity practice. Additional prospective research should evaluate whether these strategies effectively optimize local conditions for successful implementation in a variety of settings. Supplementary Information The online version contains supplementary material available at 10.1186/s43058-021-00136-7.
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14
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Gustavson AM, Wisdom JP, Kenny ME, Salameh HA, Ackland PE, Clothier B, Noorbaloochi S, Gordon AJ, Hagedorn HJ. Early impacts of a multi-faceted implementation strategy to increase use of medication treatments for opioid use disorder in the Veterans Health Administration. Implement Sci Commun 2021; 2:20. [PMID: 33588952 PMCID: PMC7885503 DOI: 10.1186/s43058-021-00119-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 01/28/2021] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Despite the risk of negative sequelae from opioid use disorder (OUD) and clinical guidelines for the use of effective medication treatment for OUD (M-OUD), many Veterans Health Administration (VHA) providers and facilities lag in providing M-OUD. An intensive external facilitation intervention may enhance uptake in low-adopting VHA facilities by engaging stakeholders from multiple clinical settings within a facility (e.g., mental health, primary care, pain specialty clinic, substance use disorder clinics). Our study identified pre-intervention determinants of implementation through qualitative interviews, described strategies employed during the first 6 months of intensive external facilitation, and explored patterns of implementation determinants in relation to early outcomes. METHODS Guided by the integrated-Promoting Action on Research Implementation in Health Services (i-PARIHS) framework, we interviewed stakeholders at low-adopting VHA facilities prior to external facilitation, employed a rapid qualitative analytic process, presented findings during facility visits, and collaboratively created facilitation action plans to achieve goals set by the facilities that would increase M-OUD uptake. The primary outcome was the Substance Use Disorder (SUD)-16, which is a VHA facility-level performance metric consisting of the percent of patients receiving M-OUD among those with an OUD diagnosis. We examined the relationship between pre-implementation factors and 6-month SUD-16 outcomes. RESULTS Across eight VHA facilities, we interviewed 68 participants. Implementation determinants included barriers and facilitators across innovation, context, and recipients constructs of i-PARIHS. Each facility selected goals based on the qualitative results. At 6 months, two facilities achieved most goals and two facilities demonstrated progress. The SUD-16 from baseline to 6 months significantly improved in two facilities (8.4% increase (95 % confidence interval [CI] 4.4-12.4) and 9.9% increase (95% CI 3.6-16.2), respectively). Six-month implementation outcomes showed that the extent to which M-OUD aligns with existing clinical practices and values was a primary factor at all facilities, with six of eight facilities perceiving it as both a barrier and facilitator. External health system barriers were most challenging for facilities with the smallest change in SUD-16. CONCLUSIONS Early impacts of a multi-faceted implementation approach demonstrated a strong signal for positively impacting M-OUD prescribing in low-adopting VHA facilities. This signal indicates that external facilitation can influence adoption of M-OUD at the facility level in the early implementation phase. These short-term wins experienced by stakeholders may encourage continued adoption and long-term sustainability M-OUD.
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Affiliation(s)
- Allison M Gustavson
- Veterans Affairs Health Services Research and Development Center for Care Delivery and Outcomes Research, Minneapolis Veterans Affairs Health Care System, 1 Veterans Drive, Mail Code #152, Minneapolis, MN, 55417, USA.
| | | | - Marie E Kenny
- Veterans Affairs Health Services Research and Development Center for Care Delivery and Outcomes Research, Minneapolis Veterans Affairs Health Care System, 1 Veterans Drive, Mail Code #152, Minneapolis, MN, 55417, USA
| | - Hope A Salameh
- Veterans Affairs Health Services Research and Development Center for Care Delivery and Outcomes Research, Minneapolis Veterans Affairs Health Care System, 1 Veterans Drive, Mail Code #152, Minneapolis, MN, 55417, USA
| | - Princess E Ackland
- Veterans Affairs Health Services Research and Development Center for Care Delivery and Outcomes Research, Minneapolis Veterans Affairs Health Care System, 1 Veterans Drive, Mail Code #152, Minneapolis, MN, 55417, USA
- Department of Medicine, University of Minnesota, Minneapolis, USA
| | - Barbara Clothier
- Veterans Affairs Health Services Research and Development Center for Care Delivery and Outcomes Research, Minneapolis Veterans Affairs Health Care System, 1 Veterans Drive, Mail Code #152, Minneapolis, MN, 55417, USA
| | - Siamak Noorbaloochi
- Veterans Affairs Health Services Research and Development Center for Care Delivery and Outcomes Research, Minneapolis Veterans Affairs Health Care System, 1 Veterans Drive, Mail Code #152, Minneapolis, MN, 55417, USA
- Department of Medicine, University of Minnesota, Minneapolis, USA
| | - Adam J Gordon
- Vulnerable Veteran Innovative PACT (VIP) Initiative; Informatics, Decision-Enhancement, and Analytic Sciences Center (IDEAS), VA Salt Lake City Health Care System, 500 Foothill Drive, Salt Lake City, UT, 84148, USA
- Program for Addiction Research, Clinical Care, Knowledge and Advocacy (PARCKA), University of Utah School of Medicine, Salt Lake City, Utah, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Hildi J Hagedorn
- Veterans Affairs Health Services Research and Development Center for Care Delivery and Outcomes Research, Minneapolis Veterans Affairs Health Care System, 1 Veterans Drive, Mail Code #152, Minneapolis, MN, 55417, USA
- Department of Psychiatry, University of Minnesota School of Medicine, Minneapolis, MN, 55455, USA
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15
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Rudd BN, Davis M, Beidas RS. Integrating implementation science in clinical research to maximize public health impact: a call for the reporting and alignment of implementation strategy use with implementation outcomes in clinical research. Implement Sci 2020; 15:103. [PMID: 33239097 PMCID: PMC7690013 DOI: 10.1186/s13012-020-01060-5] [Citation(s) in RCA: 65] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 10/25/2020] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Although comprehensive reporting guidelines for implementation strategy use within implementation research exist, they are rarely used by clinical (i.e., efficacy and effectiveness) researchers. In this debate, we argue that the lack of comprehensive reporting of implementation strategy use and alignment of those strategies with implementation outcomes within clinical research is a missed opportunity to efficiently narrow research-to-practice gaps. MAIN BODY We review ways that comprehensively specifying implementation strategy use can advance science, including enhancing replicability of clinical trials and reducing the time from clinical research to public health impact. We then propose that revisions to frequently used reporting guidelines in clinical research (e.g., CONSORT, TIDieR) are needed, review current methods for reporting implementation strategy use (e.g., utilizing StaRI), provide pragmatic suggestions on how to both prospectively and retrospectively specify implementation strategy use and align these strategies with implementation outcomes within clinical research, and offer a case study of using these methods. CONCLUSIONS The approaches recommended in this article will not only contribute to shared knowledge and language among clinical and implementation researchers but also facilitate the replication of efficacy and effectiveness research. Ultimately, we hope to accelerate translation from clinical to implementation research in order to expedite improvements in public health.
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Affiliation(s)
- Brittany N Rudd
- Institute for Juvenile Research, Department of Psychiatry, University of Illinois at Chicago, 1747 West Roosevelt Road, Chicago, IL, 60608, USA.
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Penn Implementation Science Center, Leonard Davis Institute (PISCE@LDI), Philadelphia, PA, USA.
| | - Molly Davis
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Implementation Science Center, Leonard Davis Institute (PISCE@LDI), Philadelphia, PA, USA
| | - Rinad S Beidas
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Implementation Science Center, Leonard Davis Institute (PISCE@LDI), Philadelphia, PA, USA
- Department of Medical Ethics and Health Policy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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16
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Rogal SS, Yakovchenko V, Morgan T, Bajaj JS, Gonzalez R, Park A, Beste L, Miech EJ, Lamorte C, Neely B, Gibson S, Malone PS, Chartier M, Taddei T, Garcia-Tsao G, Powell BJ, Dominitz JA, Ross D, Chinman MJ. Getting to implementation: a protocol for a Hybrid III stepped wedge cluster randomized evaluation of using data-driven implementation strategies to improve cirrhosis care for Veterans. Implement Sci 2020; 15:92. [PMID: 33087156 PMCID: PMC7579930 DOI: 10.1186/s13012-020-01050-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2020] [Accepted: 10/05/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Cirrhosis is a rapidly increasing cause of global mortality. To improve cirrhosis care, the Veterans Health Administration (VHA) developed the Hepatic Innovation Team (HIT) Collaborative to support VA Medical Centers (VAMCs) to deliver evidence-based cirrhosis care. This randomized HIT program evaluation aims to develop and assess a novel approach for choosing and applying implementation strategies to improve the quality of cirrhosis care. METHODS Evaluation aims are to (1) empirically determine which combinations of implementation strategies are associated with successful implementation of evidence-based practices (EBPs) for Veterans with cirrhosis, (2) manualize these "data-driven" implementation strategies, and (3) assess the effectiveness of data-driven implementation strategies in increasing cirrhosis EBP uptake. Aim 1 will include an online survey of all VAMCs' use of 73 implementations strategies to improve cirrhosis care, as defined by the Expert Recommendations for Implementing Change taxonomy. Traditional statistical as well as configurational comparative methods will both be employed to determine which combinations of implementation strategies are associated with site-level adherence to EBPs for cirrhosis. In aim 2, semi-structured interviews with high-performing VAMCs will be conducted to operationalize successful implementation strategies for cirrhosis care. These data will be used to inform the creation of a step-by-step guide to tailoring and applying the implementation strategies identified in aim 1. In aim 3, this manualized implementation intervention will be assessed using a hybrid type III stepped-wedge cluster randomized design. This evaluation will be conducted in 12 VAMCs, with four VAMCs crossing from control to intervention every 6 months, in order to assess the effectiveness of using data-driven implementation strategies to improve guideline-concordant cirrhosis care. DISCUSSION Successful completion of this innovative evaluation will establish the feasibility of using early evaluation data to inform a manualized, user-friendly implementation intervention for VAMCs with opportunities to improve care. This evaluation will provide implementation support tools that can be applied to enhance the implementation of other evidence-based practices. TRIAL REGISTRATION This project was registered at ClinicalTrials.Gov ( NCT04178096 ) on 4/29/20.
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Affiliation(s)
- Shari S Rogal
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Research Office Building (151R), University Drive C, Pittsburgh, PA, 15240, USA. .,Departments of Medicine and Surgery, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Vera Yakovchenko
- Center for Healthcare Organization and Implementation Research, Edith Nourse Rogers Memorial VA Hospital, Bedford, MA, USA
| | - Timothy Morgan
- Gastroenterology Section, VA Long Beach Healthcare System, Long Beach, CA, USA.,Division of Gastroenterology, Department of Medicine, University of California, Irvine, CA, USA
| | - Jasmohan S Bajaj
- Division of Gastroenterology, Hepatology, and Nutrition, Virginia Commonwealth University, Richmond, VA, USA.,Division of Gastroenterology, Hunter Holmes McGuire VA Medical Center, Richmond, VA, USA
| | - Rachel Gonzalez
- Department of Veterans Affairs, Sierra Pacific Veterans Integrated Service Network, Pharmacy Benefits Management, Mather, CA, USA
| | - Angela Park
- Office of Healthcare Transformation, Veterans Engineering Resource Center, Washington, DC, USA
| | - Lauren Beste
- Division of General Internal Medicine, Department of Medicine, VA Puget Sound Healthcare System, Seattle, WA, USA.,Division of General Internal Medicine, University of Washington, Seattle, WA, USA
| | - Edward J Miech
- Department of Veterans Affairs, Roudebush VA Medical Center, HSR&D Center for Health Information & Communication, VA PRIS-M QUERI, Indianapolis, IN, USA
| | - Carolyn Lamorte
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Research Office Building (151R), University Drive C, Pittsburgh, PA, 15240, USA
| | - Brittney Neely
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Research Office Building (151R), University Drive C, Pittsburgh, PA, 15240, USA
| | - Sandra Gibson
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Research Office Building (151R), University Drive C, Pittsburgh, PA, 15240, USA
| | | | - Maggie Chartier
- HIV, Hepatitis and Related Conditions Programs, Office of Specialty Care Services, Veterans Health Administration, Washington, DC, USA
| | - Tamar Taddei
- VA Connecticut Healthcare System, West Haven, CT, USA.,Department of Medicine, Yale University, West Haven, CT, USA
| | - Guadalupe Garcia-Tsao
- VA Connecticut Healthcare System, West Haven, CT, USA.,Department of Medicine, Yale University, West Haven, CT, USA
| | - Byron J Powell
- Brown School, Washington University in St. Louis, St. Louis, MO, USA
| | - Jason A Dominitz
- Gastroenterology Section, VA Puget Sound Health Care System, Seattle, WA, USA.,Department of Medicine, University of Washington, Seattle, WA, USA
| | - David Ross
- HIV, Hepatitis and Related Conditions Programs, Office of Specialty Care Services, Veterans Health Administration, Washington, DC, USA
| | - Matthew J Chinman
- Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Research Office Building (151R), University Drive C, Pittsburgh, PA, 15240, USA.,RAND Corporation, Pittsburgh, PA, USA
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