Hepatitis C virus screening at a Veterans Administration Hospital in New York City

Rostata-Pesola, Helen; Olender, Lynda; Leon, Nikki; Aytaman, Ayse; Hoffman, Renee Thibodeau; Pesola, Gene R.

doi:10.1097/jxx.0000000000000393

Cited by 4 publications

(1 citation statement)

References 11 publications

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“…Most dashboards included results from an evaluation of either the dashboard's effect, using the dashboard as a tool for measuring change, or of the dashboard as both intervention and measurement tool (84/118, 71.2%; Table 5). Most evaluations were quantitative, using data from the dashboard or EHR alone (41/118, 34.7%) [23,30,37,44,51,71,72,74,76,78,84,91,98,102,106,107,109,110,117,122,124,[131][132][133]136,[143][144][145]148,151,153,165,180,181,183,189,193,199,200,208], from the dashboard or EHR in combination with survey data (10/118, 8.5%) [34,35,55,64,103,104,115,…”

Section: Discussionmentioning

confidence: 99%

Scoping review of dashboards in health care: why, how, and for whom they have been developed, implemented, and evaluated (Preprint)

Helminski,

Sussman,

Pfeiffer

et al. 2024

Preprint

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BACKGROUND While dashboards are frequently used by health systems to monitor and improve performance, little is known about their characteristics and the processes used to incorporate them into practice. OBJECTIVE This scoping review aimed to explore published literature on health care dashboards to summarize why, how, and for whom they have been developed, implemented, and evaluated. METHODS MEDLINE, EMBASE, Web of Science and the Cochrane Library were searched from inception through July 2020. Studies were included if they described the development or evaluation of a health care dashboard with publication since 2015. Clinical setting, purpose (categorized as clinical, administrative, or both), and end-user were extracted for all studies. Data on dashboard development, design characteristics, implementation strategies, and evaluation were extracted only for studies published from 2018-2020. RESULTS Data was extracted for 199 dashboards described in 193 publications. The most common settings in which dashboards were used were inpatient (n=81/199, 40.7%) and outpatient clinics (n=68/199, 34.2%). Most dashboards had ≥2 stated purposes (n=142/199, 71.4%); of these, 97/199 (48.7%) were administrative, 68/199 (34.2%) were clinical, and 31/199 (15.6%) met both criteria. Most dashboards included front-line clinical staff as end-users (n=154/199, 77.4%). In the 118 dashboards published from 2018-2020, half involved end-users in the design process (n=59/118, 50.0%); fewer described formative usability testing (n=26/118, 22.0%) or use of any theory or framework to guide development, implementation, or evaluation (n=24/118, 20.3%). Dashboards tended to be web-based (n=41/118, 34.7%) or embedded directly into the electronic health record (n=17/118, 14.4%). Common implementation strategies used alongside dashboards included education (n=60/118, 50.8%), audit and feedback (n=59/118, 50.0%), and advisory boards (n=54/118, 45.8%). Evaluations of dashboards (n=84/118, 71.2%) were mostly quantitative (n=60/118, 50.8%), or mixed methods, combining dashboard or health record data with qualitative findings (n=18/118, 15.2%). CONCLUSIONS Dashboards in health care have been used in diverse settings, for multiple purposes and varied end users. The complexity of many dashboards – serving many purposes and end users at once – and the frequent expectation that clinicians will use them underscores the importance of systematic design and evaluation to ensure they are having the intended outcomes. Future work is needed to identify best practices for the development, implementation, and evaluation of health care dashboards. INTERNATIONAL REGISTERED REPORT RR2-10.2196/34894

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Section: Discussionmentioning

confidence: 99%

Scoping review of dashboards in health care: why, how, and for whom they have been developed, implemented, and evaluated (Preprint)

Helminski,

Sussman,

Pfeiffer

et al. 2024

Preprint

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Interventions to enhance testing, linkage to care, and treatment initiation for hepatitis C virus infection: a systematic review and meta-analysis

Cunningham

Wheeler

Hajarizadeh

et al. 2022

The Lancet Gastroenterology & Hepatology

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Maintaining Implementation through Dynamic Adaptations (MIDAS): protocol for a cluster-randomized trial of implementation strategies to optimize and sustain use of evidence-based practices in Veteran Health Administration (VHA) patients

Damschroder

Sussman

Pfeiffer

et al. 2022

Implement Sci Commun

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Background The adoption and sustainment of evidence-based practices (EBPs) is a challenge within many healthcare systems, especially in settings that have already strived but failed to achieve longer-term goals. The Veterans Affairs (VA) Maintaining Implementation through Dynamic Adaptations (MIDAS) Quality Enhancement Research Initiative (QUERI) program was funded as a series of trials to test multi-component implementation strategies to sustain optimal use of three EBPs: (1) a deprescribing approach intended to reduce potentially inappropriate polypharmacy; (2) appropriate dosing and drug selection of direct oral anticoagulants (DOACs); and (3) use of cognitive behavioral therapy as first-line treatment for insomnia before pharmacologic treatment. We describe the design and methods for a harmonized series of cluster-randomized control trials comparing two implementation strategies. Methods For each trial, we will recruit 8–12 clinics (24–36 total). All will have access to relevant clinical data to identify patients who may benefit from the target EBP at that clinic and provider. For each trial, clinics will be randomized to one of two implementation strategies to improve the use of the EBPs: (1) individual-level academic detailing (AD) or (2) AD plus the team-based Learn. Engage. Act. Process. (LEAP) quality improvement (QI) learning program. The primary outcomes will be operationalized across the three trials as a patient-level dichotomous response (yes/no) indicating patients with potentially inappropriate medications (PIMs) among those who may benefit from the EBP. This outcome will be computed using month-by-month administrative data. Primary comparison between the two implementation strategies will be analyzed using generalized estimating equations (GEE) with clinic-level monthly (13 to 36 months) percent of PIMs as the dependent variable. Primary comparative endpoint will be at 18 months post-baseline. Each trial will also be analyzed independently. Discussion MIDAS QUERI trials will focus on fostering sustained use of EBPs that previously had targeted but incomplete implementation. Our implementation approaches are designed to engage frontline clinicians in a dynamic optimization process that integrates the use of actional clinical data and making incremental changes, designed to be feasible within busy clinical settings. Trial registration ClinicalTrials.gov: NCT05065502. Registered October 4, 2021—retrospectively registered.

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Hepatitis C virus screening at a Veterans Administration Hospital in New York City

Cited by 4 publications

References 11 publications

Scoping review of dashboards in health care: why, how, and for whom they have been developed, implemented, and evaluated (Preprint)

Scoping review of dashboards in health care: why, how, and for whom they have been developed, implemented, and evaluated (Preprint)

Interventions to enhance testing, linkage to care, and treatment initiation for hepatitis C virus infection: a systematic review and meta-analysis

Maintaining Implementation through Dynamic Adaptations (MIDAS): protocol for a cluster-randomized trial of implementation strategies to optimize and sustain use of evidence-based practices in Veteran Health Administration (VHA) patients

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