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Jurczuk M, Thakar R, Carroll FE, Phillips L, van der Meulen J, Gurol-Urganci I, Sevdalis N. Design and management considerations for control groups in hybrid effectiveness-implementation trials: Narrative review & case studies. FRONTIERS IN HEALTH SERVICES 2023; 3:1059015. [PMID: 36926502 PMCID: PMC10012616 DOI: 10.3389/frhs.2023.1059015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 02/06/2023] [Indexed: 03/12/2023]
Abstract
Hybrid effectiveness-implementation studies allow researchers to combine study of a clinical intervention's effectiveness with study of its implementation with the aim of accelerating the translation of evidence into practice. However, there currently exists limited guidance on how to design and manage such hybrid studies. This is particularly true for studies that include a comparison/control arm that, by design, receives less implementation support than the intervention arm. Lack of such guidance can present a challenge for researchers both in setting up but also in effectively managing participating sites in such trials. This paper uses a narrative review of the literature (Phase 1 of the research) and comparative case study of three studies (Phase 2 of the research) to identify common themes related to study design and management. Based on these, we comment and reflect on: (1) the balance that needs to be struck between fidelity to the study design and tailoring to emerging requests from participating sites as part of the research process, and (2) the modifications to the implementation strategies being evaluated. Hybrid trial teams should carefully consider the impact of design selection, trial management decisions, and any modifications to implementation processes and/or support on the delivery of a controlled evaluation. The rationale for these choices should be systematically reported to fill the gap in the literature.
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Affiliation(s)
- Magdalena Jurczuk
- Centre for Quality Improvement and Clinical Audit, Royal College of Obstetricians and Gynaecologists, London, United Kingdom
| | - Ranee Thakar
- Obstetrics & Gynaecology, Croydon University Hospitals NHS Trust, London, United Kingdom
| | - Fran E Carroll
- Centre for Quality Improvement and Clinical Audit, Royal College of Obstetricians and Gynaecologists, London, United Kingdom
| | - Lizzie Phillips
- Centre for Quality Improvement and Clinical Audit, Royal College of Obstetricians and Gynaecologists, London, United Kingdom.,Maternity Services, University Hospital Plymouth NHS Trust, Plymouth, United Kingdom
| | - Jan van der Meulen
- Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Ipek Gurol-Urganci
- Centre for Quality Improvement and Clinical Audit, Royal College of Obstetricians and Gynaecologists, London, United Kingdom.,Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Nick Sevdalis
- Centre for Implementation Science, Health Service and Population Research Department, King's College London, London, United Kingdom
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Rule A, Melnick ER, Apathy NC. Using event logs to observe interactions with electronic health records: an updated scoping review shows increasing use of vendor-derived measures. J Am Med Inform Assoc 2022; 30:144-154. [PMID: 36173361 PMCID: PMC9748581 DOI: 10.1093/jamia/ocac177] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 09/15/2022] [Accepted: 09/19/2022] [Indexed: 01/24/2023] Open
Abstract
OBJECTIVE The aim of this article is to compare the aims, measures, methods, limitations, and scope of studies that employ vendor-derived and investigator-derived measures of electronic health record (EHR) use, and to assess measure consistency across studies. MATERIALS AND METHODS We searched PubMed for articles published between July 2019 and December 2021 that employed measures of EHR use derived from EHR event logs. We coded the aims, measures, methods, limitations, and scope of each article and compared articles employing vendor-derived and investigator-derived measures. RESULTS One hundred and two articles met inclusion criteria; 40 employed vendor-derived measures, 61 employed investigator-derived measures, and 1 employed both. Studies employing vendor-derived measures were more likely than those employing investigator-derived measures to observe EHR use only in ambulatory settings (83% vs 48%, P = .002) and only by physicians or advanced practice providers (100% vs 54% of studies, P < .001). Studies employing vendor-derived measures were also more likely to measure durations of EHR use (P < .001 for 6 different activities), but definitions of measures such as time outside scheduled hours varied widely. Eight articles reported measure validation. The reported limitations of vendor-derived measures included measure transparency and availability for certain clinical settings and roles. DISCUSSION Vendor-derived measures are increasingly used to study EHR use, but only by certain clinical roles. Although poorly validated and variously defined, both vendor- and investigator-derived measures of EHR time are widely reported. CONCLUSION The number of studies using event logs to observe EHR use continues to grow, but with inconsistent measure definitions and significant differences between studies that employ vendor-derived and investigator-derived measures.
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Affiliation(s)
- Adam Rule
- Corresponding Author: Adam Rule, PhD, Information School,
University of Wisconsin–Madison, 4217 Helen C. White Hall, 600 North Park Street, Madison,
Wisconsin 53706-1403, USA;
| | - Edward R Melnick
- Emergency Medicine, Yale School of Medicine, New Haven,
Connecticut, USA
- Biostatistics (Health Informatics), Yale School of Public
Health, New Haven, Connecticut, USA
| | - Nate C Apathy
- MedStar Health National Center for Human Factors in Healthcare, MedStar
Health Research Institute, District of Columbia, Washington, USA
- Regenstrief Institute, Indianapolis, Indiana, USA
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Nathalie H, Steele V, Miguel M, Laura M, Brigit H, Andrea B, Cohen Deborah J, DeVoe Jennifer E. Effectiveness of an insurance enrollment support tool on insurance rates and cancer prevention in community health centers: a quasi-experimental study. BMC Health Serv Res 2021; 21:1186. [PMID: 34717616 PMCID: PMC8557589 DOI: 10.1186/s12913-021-07195-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 10/19/2021] [Indexed: 11/21/2022] Open
Abstract
Background Following the ACA, millions of people gained Medicaid insurance. Most electronic health record (EHR) tools to date provide clinical-decision support and tracking of clinical biomarkers, we developed an EHR tool to support community health center (CHC) staff in assisting patients with health insurance enrollment documents and tracking insurance application steps. The objective of this study was to test the effectiveness of the health insurance support tool in (1) assisting uninsured patients gaining insurance coverage, (2) ensuring insurance continuity for patients with Medicaid insurance (preventing coverage gaps between visits); and (3) improving receipt of cancer preventive care. Methods In this quasi-experimental study, twenty-three clinics received the intervention (EHR-based insurance support tool) and were matched to 23 comparison clinics. CHCs were recruited from the OCHIN network. EHR data were linked to Medicaid enrollment data. The primary outcomes were rates of uninsured and Medicaid visits. The secondary outcomes were receipt of recommended breast, cervical, and colorectal cancer screenings. A comparative interrupted time-series using Poisson generalized estimated equation (GEE) modeling was performed to evaluate the effectiveness of the EHR-based tool on the primary and secondary outcomes. Results Immediately following implementation of the enrollment tool, the uninsured visit rate decreased by 21.0% (Adjusted Rate Ratio [RR] = 0.790, 95% CI = 0.621–1.005, p = .055) while Medicaid-insured visits increased by 4.5% (ARR = 1.045, 95% CI = 1.013–1.079) in the intervention group relative to comparison group. Cervical cancer preventive ratio increased 5.0% (ARR = 1.050, 95% CI = 1.009–1.093) immediately following implementation of the enrollment tool in the intervention group relative to comparison group. Among patients with a tool use, 81% were enrolled in Medicaid 12 months after tool use. For the 19% who were never enrolled in Medicaid following tool use, most were uninsured (44%) at the time of tool use. Conclusions A health insurance support tool embedded within the EHR can effectively support clinic staff in assisting patients in maintaining their Medicaid coverage. Such tools may also have an indirect impact on evidence-based practice interventions, such as cancer screening. Trial registration This study was retrospectively registered on February 4th, 2015 with Clinicaltrials.gov (#NCT02355262). The registry record can be found at https://www.clinicaltrials.gov/ct2/show/NCT02355262.
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Affiliation(s)
- Huguet Nathalie
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA.
| | - Valenzuela Steele
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
| | - Marino Miguel
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA.,Division of Biostatistics, School of Public Health, Oregon Health & Science University - Portland State University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
| | - Moreno Laura
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
| | - Hatch Brigit
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA.,Research Department, OCHIN Inc, 1881 SW Naito Pkwy, Portland, OR, 97201, USA
| | - Baron Andrea
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
| | - J Cohen Deborah
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
| | - E DeVoe Jennifer
- Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
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Penney LS, Damush TM, Rattray NA, Miech EJ, Baird SA, Homoya BJ, Myers LJ, Bravata DM. Multi-tiered external facilitation: the role of feedback loops and tailored interventions in supporting change in a stepped-wedge implementation trial. Implement Sci Commun 2021; 2:82. [PMID: 34315540 PMCID: PMC8317410 DOI: 10.1186/s43058-021-00180-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 06/29/2021] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Facilitation is a complex, relational implementation strategy that guides change processes. Facilitators engage in multiple activities and tailor efforts to local contexts. How this work is coordinated and shared among multiple, external actors and the contextual factors that prompt and moderate facilitators to tailor activities have not been well-described. METHODS We conducted a mixed methods evaluation of a trial to improve the quality of transient ischemic attack care. Six sites in the Veterans Health Administration received external facilitation (EF) before and during a 1-year active implementation period. We examined how EF was employed and activated. Data analysis included prospective logs of facilitator correspondence with sites (160 site-directed episodes), stakeholder interviews (a total of 78 interviews, involving 42 unique individuals), and collaborative call debriefs (n=22) spanning implementation stages. Logs were descriptively analyzed across facilitators, sites, time periods, and activity types. Interview transcripts were coded for content related to EF and themes were identified. Debriefs were reviewed to identify instances of and utilization of EF during site critical junctures. RESULTS Multi-tiered EF was supported by two groups (site-facing quality improvement [QI] facilitators and the implementation support team) that were connected by feedback loops. Each site received an average of 24 episodes of site-directed EF; most of the EF was delivered by the QI nurse. For each site, site-directed EF frequently involved networking (45%), preparation and planning (44%), process monitoring (44%), and/or education (36%). EF less commonly involved audit and feedback (20%), brainstorming solutions (16%), and/or stakeholder engagement (5%). However, site-directed EF varied widely across sites and time periods in terms of these facilitation types. Site participants recognized the responsiveness of the QI nurse and valued her problem-solving, feedback, and accountability support. External facilitators used monitoring and dialogue to intervene by facilitating redirection during challenging periods of uncertainty about project direction and feasibility for sites. External facilitators, in collaboration with the implementation support team, successfully used strategies tailored to diverse local contexts, including networking, providing data, and brainstorming solutions. CONCLUSIONS Multi-tiered facilitation capitalizing on emergent feedback loops allowed for tailored, site-directed facilitation. Critical juncture cases illustrate the complexity of EF and the need to often try multiple strategies in combination to facilitate implementation progress. TRIAL REGISTRATION The Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) is a registered trial ( NCT02769338 ), May 11, 2016-prospectively registered.
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Affiliation(s)
- Lauren S. Penney
- grid.280682.60000 0004 0420 5695VA HSR&D Elizabeth Dole Center of Excellence for Veteran and Caregiver Research, South Texas Veterans Health Care System, San Antonio, TX USA ,grid.267309.90000 0001 0629 5880School of Medicine, University of Texas Health at San Antonio, San Antonio, TX USA
| | - Teresa M. Damush
- grid.280828.80000 0000 9681 3540VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, Indianapolis, IN USA ,grid.448342.d0000 0001 2287 2027Regenstrief Institute, Inc., Indianapolis, IN USA ,grid.257413.60000 0001 2287 3919Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN USA
| | - Nicholas A. Rattray
- grid.280828.80000 0000 9681 3540VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, Indianapolis, IN USA ,grid.448342.d0000 0001 2287 2027Regenstrief Institute, Inc., Indianapolis, IN USA ,grid.257413.60000 0001 2287 3919Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN USA ,grid.257413.60000 0001 2287 3919Department of Anthropology, Indiana University-Purdue University, Indianapolis, IN USA
| | - Edward J. Miech
- grid.280828.80000 0000 9681 3540VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, Indianapolis, IN USA ,grid.448342.d0000 0001 2287 2027Regenstrief Institute, Inc., Indianapolis, IN USA ,grid.257413.60000 0001 2287 3919Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN USA
| | - Sean A. Baird
- grid.280828.80000 0000 9681 3540VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, Indianapolis, IN USA
| | - Barbara J. Homoya
- grid.280828.80000 0000 9681 3540VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, Indianapolis, IN USA
| | - Laura J. Myers
- grid.280828.80000 0000 9681 3540VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, Indianapolis, IN USA
| | - Dawn M. Bravata
- grid.280828.80000 0000 9681 3540VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, Indianapolis, IN USA ,grid.448342.d0000 0001 2287 2027Regenstrief Institute, Inc., Indianapolis, IN USA ,grid.257413.60000 0001 2287 3919Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN USA ,grid.257413.60000 0001 2287 3919Department of Neurology, Indiana University School of Medicine, Indianapolis, IN USA
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Clinic factors associated with utilization of a pregnancy-intention screening tool in community health centers. Contraception 2021; 103:336-341. [PMID: 33592233 DOI: 10.1016/j.contraception.2021.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 02/04/2021] [Accepted: 02/09/2021] [Indexed: 11/23/2022]
Abstract
OBJECTIVE Routine pregnancy-intention screening in the primary care setting is a promising practice to help patients achieve their reproductive goals. We aim to describe the utilization of a pregnancy-intention screening tool integrated in the electronic health record (EHR) of a national network of community health centers (CHCs) and identify clinic-level factors associated with tool use. STUDY DESIGN We conducted a clinic-level retrospective observational study to assess tool utilization during the first 3 years after the tool was made available in the EHR (November 2015 to October 2018). We describe characteristics of clinics with higher tool utilization (≥90th percentile) versus lower utilization (<90th percentile) and the types of providers who used the tool. We then employ negative binomial regression to identify independent clinic-level factors associated with tool utilization. RESULTS Across 194 clinics in our study sample which served 289,754 eligible female patients, the tool was used for 113,116 (39%). Medical assistants performed 60.3% of screenings and clinicians performed 11.2%. CHCs with higher tool utilization rates were more likely to be located in rural settings (RR 1.75, 95% CI 1.07-2.87) and serve patient populations with higher proportions of women (RR 1.32, 95% CI 1.24-1.41) and lower proportions of patients with non-English language preference (RR 0.92, 95% CI 0.89-0.95). CONCLUSIONS Many health centers utilized pregnancy-intention screening after an EHR-based tool was made available, though overall screening rates were low. IMPLICATIONS Additional study of implementation strategies and effectiveness of pregnancy-intention screening tools is needed. Implementation of future pregnancy-intention screening interventions must be tailored to address clinic-level barriers and facilitators to screening.
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