Background: Implementation of multifaceted interventions typically involves many diverse elements working together in interrelated ways, including intervention components, implementation strategies, and features of local context. Given this real-world complexity, implementation researchers may be interested in a new mathematical, cross-case method called Coincidence Analysis (CNA) that has been designed explicitly to support causal inference, answer research questions about combinations of conditions that are minimally necessary or sufficient for an outcome, and identify the possible presence of multiple causal paths to an outcome. CNA can be applied as a standalone method or in conjunction with other approaches and can reveal new empirical findings related to implementation that might otherwise have gone undetected.Methods: We applied CNA to a publicly available dataset from Sweden with county-level data on human papillomavirus (HPV) vaccination campaigns and vaccination uptake in 2012 and 2014 and then compared CNA results to the published regression findings.Results: The original regression analysis found vaccination uptake was positively associated only with the availability of vaccines in schools. CNA produced different findings and uncovered an additional solution path: high vaccination rates were achieved by either (1) offering the vaccine in all schools or (2) a combination of offering the vaccine in some schools and media coverage.Conclusions: CNA offers a new comparative approach for researchers seeking to understand how implementation conditions work together and link to outcomes.

To realize potential public health benefits from genetic and genomic innovations, understanding how best to implement the innovations into clinical care is important. The objective of this study was to synthesize data on challenges identified by six diverse projects that are part of a National Human Genome Research Institute (NHGRI)-funded network focused on implementing genomics into practice and strategies to overcome these challenges. We used a multiple-case study approach with each project considered as a case and qualitative methods to elicit and describe themes related to implementation challenges and strategies. We describe challenges and strategies in an implementation framework and typology to enable consistent definitions and cross-case comparisons. Strategies were linked to challenges based on expert review and shared themes. Three challenges were identified by all six projects, and strategies to address these challenges varied across the projects. One common challenge was to increase the relative priority of integrating genomics within the health system electronic health record (EHR). Four projects used data warehousing techniques to accomplish the integration. The second common challenge was to strengthen clinicians’ knowledge and beliefs about genomic medicine. To overcome this challenge, all projects developed educational materials and conducted meetings and outreach focused on genomic education for clinicians. The third challenge was engaging patients in the genomic medicine projects. Strategies to overcome this challenge included use of mass media to spread the word, actively involving patients in implementation (e.g., a patient advisory board), and preparing patients to be active participants in their healthcare decisions. This is the first collaborative evaluation focusing on the description of genomic medicine innovations implemented in multiple real-world clinical settings. Findings suggest that strategies to facilitate integration of genomic data within existing EHRs and educate stakeholders about the value of genomic services are considered important for effective implementation. Future work could build on these findings to evaluate which strategies are optimal under what conditions. This information will be useful for guiding translation of discoveries to clinical care, which, in turn, can provide data to inform continual improvement of genomic innovations and their applications.

We explored whether the effects of a telephone-based osteoarthritis (OA) self-management support intervention differed by race and health literacy. Participants included 515 veterans with hip and/or knee OA. Linear mixed models assessed differential effects of the intervention compared with health education (HE) and usual care (UC) on pain (Arthritis Impact Measurement Scales-2 [AIMS2] and Visual Analogue Scale), function (AIMS2 mobility and walking/bending), affect (AIMS2) and arthritis self-efficacy by: (i) race (white/non-white), (ii) health literacy (high/low) and (iii) race by health literacy. AIMS2 mobility improved more among non-whites than whites in the intervention compared with HE and UC (P = 0.02 and 0.008). AIMS2 pain improved more among participants with low than high literacy in the intervention compared with HE (P = 0.05). However, we found a differential effect of the intervention on AIMS2 pain compared with UC according to the combination of race and health literacy (P = 0.05); non-whites with low literacy in the intervention had the greatest improvement in pain. This telephone-based OA intervention may be particularly beneficial for patients with OA who are racial/ethnic minorities and have low health literacy. These results warrant further research designed specifically to assess whether this type of intervention can reduce OA disparities.

Family caregivers often serve as unpaid members of the home and community-based care workforce for people with serious illness; as key partners in the home-clinic continuum, they should be included...

In trials, hospital walking programs have been shown to improve functional ability after discharge, but little evidence exists about their effectiveness under routine practice conditions. To evaluate the effect of implementation of a supervised walking program known as STRIDE (AssiSTed EaRly MobIlity for HospitalizeD VEterans) on discharge to a skilled-nursing facility (SNF), length of stay (LOS), and inpatient falls. Stepped-wedge, cluster randomized trial. (ClinicalTrials.gov: NCT03300336). 8 Veterans Affairs hospitals from 20 August 2017 to 19 August 2019. Analyses included hospitalizations involving patients aged 60 years or older who were community dwelling and admitted for 2 or more days to a participating medicine ward. Hospitals were randomly assigned in 2 stratified blocks to a launch date for STRIDE. All hospitals received implementation support according to the Replicating Effective Programs framework. The prespecified primary outcomes were discharge to a SNF and hospital LOS, and having 1 or more inpatient falls was exploratory. Generalized linear mixed models were fit to account for clustering of patients within hospitals and included patient-level covariates. Patients in pre-STRIDE time periods (n = 6722) were similar to post-STRIDE time periods (n = 6141). The proportion of patients with any documented walk during a potentially eligible hospitalization ranged from 0.6% to 22.7% per hospital. The estimated rates of discharge to a SNF were 13% pre-STRIDE and 8% post-STRIDE. In adjusted models, odds of discharge to a SNF were lower among eligible patients hospitalized in post-STRIDE time periods (odds ratio [OR], 0.6 [95% CI, 0.5 to 0.8]) compared with pre-STRIDE. Findings were robust to sensitivity analyses. There were no differences in LOS (rate ratio, 1.0 [CI, 0.9 to 1.1]) or having an inpatient fall (OR, 0.8 [CI, 0.5 to 1.1]). Direct program reach was low. Although the reach was limited and variable, hospitalizations occurring during the STRIDE hospital walking program implementation period had lower odds of discharge to a SNF, with no change in hospital LOS or inpatient falls. U.S. Department of Veterans Affairs Quality Enhancement Research Initiative (Optimizing Function and Independence QUERI).