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Analyses of electronic medical databases often compare clinical practice to guideline recommendations. These analyses have a limited ability to simultaneously evaluate many interconnected medical decisions. We aimed to overcome this limitation with an alternative method and apply it to the diagnostic workup of HIV, where misuse can contribute to HIV transmission, delay care, and incur unnecessary costs. We used graph theory to assess patterns of HIV diagnostic testing in a national healthcare system. We modeled the HIV diagnostic testing guidelines as a directed graph. Each node in the graph represented a test, and the edges pointed from one test to the next in chronological order. We then graphed each patient's HIV testing. This set of patient-level graphs was aggregated into a single graph. Finally, we compared the two graphs, the first representing the recommended approach to HIV diagnostic testing and the second representing the observed patterns of HIV testing, to assess for clinical practice deviations. The HIV diagnostic testing of 1.643 million patients provided 8.790 million HIV diagnostic test results for analysis. Significant deviations from recommended practice were found including the use of HIV resistance tests (n = 3,007) and HIV nucleic acid tests (n = 16,567) instead of the recommended HIV screen. We developed a method that modeled a complex medical scenario as a directed graph. When applied to HIV diagnostic testing, we identified deviations in clinical practice from guideline recommendations. The model enabled the identification of intervention targets and prompted systemwide policy changes to enhance HIV detection.

Background While few countries and healthcare systems are on track to meet the World Health Organization’s hepatitis C virus (HCV) elimination goals, the US Veterans Health Administration (VHA) has been a leader in these efforts. We aimed to determine which implementation strategies were associated with successful national viral elimination implementation within the VHA. Methods We conducted a five-year, longitudinal cohort study of the VHA Hepatic Innovation Team (HIT) Collaborative between October 2015 and September 2019. Participants from 130 VHA medical centers treating HCV were sent annual electronic surveys about their use of 73 implementation strategies, organized into nine clusters as described by the Expert Recommendations for Implementing Change taxonomy. Descriptive and nonparametric analyses assessed strategy use over time, strategy attribution to the HIT, and strategy associations with site HCV treatment volume and rate of adoption, following the Theory of Diffusion of Innovations. Results Between 58 and 109 medical centers provided responses in each year, including 127 (98%) responding at least once, and 54 (42%) responding in all four implementation years. A median of 13–27 strategies were endorsed per year, and 8–36 individual strategies were significantly associated with treatment volume per year. Data warehousing, tailoring, and patient-facing strategies were most commonly endorsed. One strategy—“identify early adopters to learn from their experiences”—was significantly associated with HCV treatment volume in each year. Peak implementation year was associated with revising professional roles, providing local technical assistance, using data warehousing (i.e., dashboard population management), and identifying and preparing champions. Many of the strategies were driven by a national learning collaborative, which was instrumental in successful HCV elimination. Conclusions VHA’s tremendous success in rapidly treating nearly all Veterans with HCV can provide a roadmap for other HCV elimination initiatives.

Background Hepatitis C virus (HCV) is a common and highly morbid illness. New medications that have much higher cure rates have become the new evidence-based practice in the field. Understanding the implementation of these new medications nationally provides an opportunity to advance the understanding of the role of implementation strategies in clinical outcomes on a large scale. The Expert Recommendations for Implementing Change (ERIC) study defined discrete implementation strategies and clustered these strategies into groups. The present evaluation assessed the use of these strategies and clusters in the context of HCV treatment across the US Department of Veterans Affairs (VA), Veterans Health Administration, the largest provider of HCV care nationally. Methods A 73-item survey was developed and sent to all VA sites treating HCV via electronic survey, to assess whether or not a site used each ERIC-defined implementation strategy related to employing the new HCV medication in 2014. VA national data regarding the number of Veterans starting on the new HCV medications at each site were collected. The associations between treatment starts and number and type of implementation strategies were assessed. Results A total of 80 (62%) sites responded. Respondents endorsed an average of 25 ± 14 strategies. The number of treatment starts was positively correlated with the total number of strategies endorsed ( r  = 0.43, p  < 0.001). Quartile of treatment starts was significantly associated with the number of strategies endorsed ( p  < 0.01), with the top quartile endorsing a median of 33 strategies, compared to 15 strategies in the lowest quartile. There were significant differences in the types of strategies endorsed by sites in the highest and lowest quartiles of treatment starts. Four of the 10 top strategies for sites in the top quartile had significant correlations with treatment starts compared to only 1 of the 10 top strategies in the bottom quartile sites. Overall, only 3 of the top 15 most frequently used strategies were associated with treatment. Conclusions These results suggest that sites that used a greater number of implementation strategies were able to deliver more evidence-based treatment in HCV. The current assessment also demonstrates the feasibility of electronic self-reporting to evaluate ERIC strategies on a large scale. These results provide initial evidence for the clinical relevance of the ERIC strategies in a real-world implementation setting on a large scale. This is an initial step in identifying which strategies are associated with the uptake of evidence-based practices in nationwide healthcare systems.

The Veterans Health Administration (VA) cares for over 80,000 Veterans with cirrhosis annually. Given the importance of understanding patient reported outcomes in this complex population, we aimed to assess the associations between attitudes towards care, disease knowledge, and health related quality of life (HRQoL) in a national sample. In this cross-sectional study, we mailed paper surveys to a random sample of Veterans with cirrhosis, oversampling those with decompensated disease. Surveys included the Veterans RAND 12-Item Health Survey (measuring HRQoL) and questions about demographics, characteristics of care, satisfaction with care (\"attitudes towards care\"), and symptoms of cirrhosis. Those who reported being \"unsure\" about whether they had decompensation events were defined as \"unsure about cirrhosis symptoms\" (\"disease knowledge\"). We used multivariable regression models to assess the factors associated with HRQoL. Of 1374 surveys, 551 (40%) completed surveys were included for analysis. Most Veterans (63%) were \"satisfied\" or \"very satisfied\" with VA liver care. Patients often self-reported being unsure about whether they had experienced hepatic decompensation events (34%). Overall average physical (PCS) and mental (MCS) component scores of HRQoL were 30±11 and 41±12. In multivariable regression models, hepatic decompensation (PCS:[beta] = -3.8, MCS:[beta] = -2.2), medical comorbidities ([beta] = --2.0, [beta] = -1.7), and being unsure about cirrhosis symptoms ([beta] = -1.9, [beta] = -3.3) were associated with worse HRQoL, while age ([beta] = 0.1, [beta] = 0.2) and satisfaction with care ([beta] = 0.6; [beta] = 1.6) were associated with significantly better HRQoL. Hepatic decompensation, lower satisfaction with care, and being unsure about cirrhosis symptoms were associated with reduced QOL scores in this national cohort.

Background While guidelines recommend twice-yearly liver cancer (hepatocellular carcinoma, HCC) surveillance for people with cirrhosis, adherence to these guidelines remains variable. We aimed to empirically identify and apply successful implementation strategies through Getting to Implementation (GTI), a manualized facilitation approach. Methods A hybrid type III, stepped-wedge, cluster-randomized trial was conducted at 12 underperforming Veterans Health Administration (VA) sites between October 2020 and October 2022. GTI included a stepwise approach to guide sites to detail their current state, set implementation goals, identify implementation barriers, select implementation strategies, make a work plan, conduct an evaluation, and sustain their work. Outcomes were defined using the Reach , Effectiveness , Adoption , Implementation , and Maintenance (RE-AIM) framework. Results Facilitators supported site teams with an average of 20±6 facilitation hours over a 12-month period. Ten of 12 sites (83%) adopted GTI and applied a median of five strategies (e.g., dashboard use, small tests of change, direct patient outreach). Reach , the primary outcome, increased from mean 29.1% to mean 38.8% at-risk Veterans receiving HCC surveillance from pre- to post-intervention, and further increasing to 41.3% in the sustainment period. In both unadjusted and adjusted models, the odds of HCC surveillance were significantly higher during intervention (adjusted odds ratio, aOR=1.67, 95% CI:1.59, 1.75) and during sustainment (aOR=1.69, 95% CI:1.60, 1.78) compared with baseline, and with difference between active and sustainment periods, indicating sustained improvement after active facilitation ended. Conclusions GTI sustainably improved HCC surveillance, suggesting that applying data-driven implementation strategies within a manualized facilitation approach can improve care. Clinical Trial Registration ClinicalTrials.gov , NCT04178096

The Veterans Health Administration (VA) cares for over 80,000 Veterans with cirrhosis annually. Given the importance of understanding patient reported outcomes in this complex population, we aimed to assess the associations between attitudes towards care, disease knowledge, and health related quality of life (HRQoL) in a national sample. In this cross-sectional study, we mailed paper surveys to a random sample of Veterans with cirrhosis, oversampling those with decompensated disease. Surveys included the Veterans RAND 12-Item Health Survey (measuring HRQoL) and questions about demographics, characteristics of care, satisfaction with care (\"attitudes towards care\"), and symptoms of cirrhosis. Those who reported being \"unsure\" about whether they had decompensation events were defined as \"unsure about cirrhosis symptoms\" (\"disease knowledge\"). We used multivariable regression models to assess the factors associated with HRQoL. Of 1374 surveys, 551 (40%) completed surveys were included for analysis. Most Veterans (63%) were \"satisfied\" or \"very satisfied\" with VA liver care. Patients often self-reported being unsure about whether they had experienced hepatic decompensation events (34%). Overall average physical (PCS) and mental (MCS) component scores of HRQoL were 30±11 and 41±12. In multivariable regression models, hepatic decompensation (PCS:[beta] = -3.8, MCS:[beta] = -2.2), medical comorbidities ([beta] = --2.0, [beta] = -1.7), and being unsure about cirrhosis symptoms ([beta] = -1.9, [beta] = -3.3) were associated with worse HRQoL, while age ([beta] = 0.1, [beta] = 0.2) and satisfaction with care ([beta] = 0.6; [beta] = 1.6) were associated with significantly better HRQoL. Hepatic decompensation, lower satisfaction with care, and being unsure about cirrhosis symptoms were associated with reduced QOL scores in this national cohort.

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.

Background To increase the uptake of evidence-based treatments for hepatitis C (HCV), the Department of Veterans Affairs (VA) established the Hepatitis Innovation Team (HIT) Collaborative. Teams of providers were tasked with choosing implementation strategies to improve HCV care. The aim of the current evaluation was to assess how site-level implementation strategies were associated with HCV treatment initiation and how the use of implementation strategies and their association with HCV treatment changed over time. Methods A key HCV provider at each VA site ( N  = 130) was asked in two consecutive fiscal years (FYs) to complete an online survey examining the use of 73 implementation strategies organized into nine clusters as described by the Expert Recommendations for Implementing Change (ERIC) study. The number of Veterans initiating treatment for HCV, or “treatment starts,” at each site was captured using national data. Providers reported whether the use of each implementation strategy was due to the HIT Collaborative. Results Of 130 sites, 80 (62%) responded in Year 1 (FY15) and 105 (81%) responded in Year 2 (FY16). Respondents endorsed a median of 27 (IQR19–38) strategies in Year 2. The strategies significantly more likely to be chosen in Year 2 included tailoring strategies to deliver HCV care, promoting adaptability, sharing knowledge between sites, and using mass media. The total number of treatment starts was significantly positively correlated with total number of strategies endorsed in both years. In Years 1 and 2, respectively, 28 and 26 strategies were significantly associated with treatment starts; 12 strategies overlapped both years, 16 were unique to Year 1, and 14 were unique to Year 2. Strategies significantly associated with treatment starts shifted between Years 1 and 2. Pre-implementation strategies in the “training/educating,” “interactive assistance,” and “building stakeholder interrelationships” clusters were more likely to be significantly associated with treatment starts in Year 1, while strategies in the “evaluative and iterative” and “adapting and tailoring” clusters were more likely to be associated with treatment starts in Year 2. Approximately half of all strategies were attributed to the HIT Collaborative. Conclusions These results suggest that measuring implementation strategies over time is a useful way to catalog implementation of an evidence-based practice over time and across settings.

Analyses of electronic medical databases often compare clinical practice to guideline recommendations. These analyses have a limited ability to simultaneously evaluate many interconnected medical decisions. We aimed to overcome this limitation with an alternative method and apply it to the diagnostic workup of HIV, where misuse can contribute to HIV transmission, delay care, and incur unnecessary costs. We used graph theory to assess patterns of HIV diagnostic testing in a national healthcare system. We modeled the HIV diagnostic testing guidelines as a directed graph. Each node in the graph represented a test, and the edges pointed from one test to the next in chronological order. We then graphed each patient's HIV testing. This set of patient-level graphs was aggregated into a single graph. Finally, we compared the two graphs, the first representing the recommended approach to HIV diagnostic testing and the second representing the observed patterns of HIV testing, to assess for clinical practice deviations. The HIV diagnostic testing of 1.643 million patients provided 8.790 million HIV diagnostic test results for analysis. Significant deviations from recommended practice were found including the use of HIV resistance tests (n = 3,007) and HIV nucleic acid tests (n = 16,567) instead of the recommended HIV screen. We developed a method that modeled a complex medical scenario as a directed graph. When applied to HIV diagnostic testing, we identified deviations in clinical practice from guideline recommendations. The model enabled the identification of intervention targets and prompted systemwide policy changes to enhance HIV detection.

Analyses of electronic medical databases often compare clinical practice to guideline recommendations. These analyses have a limited ability to simultaneously evaluate many interconnected medical decisions. We aimed to overcome this limitation with an alternative method and apply it to the diagnostic workup of HIV, where misuse can contribute to HIV transmission, delay care, and incur unnecessary costs. We used graph theory to assess patterns of HIV diagnostic testing in a national healthcare system. We modeled the HIV diagnostic testing guidelines as a directed graph. Each node in the graph represented a test, and the edges pointed from one test to the next in chronological order. We then graphed each patient's HIV testing. This set of patient-level graphs was aggregated into a single graph. Finally, we compared the two graphs, the first representing the recommended approach to HIV diagnostic testing and the second representing the observed patterns of HIV testing, to assess for clinical practice deviations. The HIV diagnostic testing of 1.643 million patients provided 8.790 million HIV diagnostic test results for analysis. Significant deviations from recommended practice were found including the use of HIV resistance tests (n = 3,007) and HIV nucleic acid tests (n = 16,567) instead of the recommended HIV screen. We developed a method that modeled a complex medical scenario as a directed graph. When applied to HIV diagnostic testing, we identified deviations in clinical practice from guideline recommendations. The model enabled the identification of intervention targets and prompted systemwide policy changes to enhance HIV detection.