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Objective: The aim of this study was to explore barriers and facilitators to implementing enhanced recovery pathways, with a focus on identifying factors that distinguished hospitals achieving greater levels of implementation success. Background: Despite the clinical effectiveness of enhanced recovery pathways, the implementation of these complex interventions varies widely. While there is a growing list of contextual factors that may affect implementation, little is known about which factors distinguish between higher and lower levels of implementation success. Methods: We conducted in-depth interviews with 168 perioperative leaders, clinicians, and staff from 8 US hospitals participating in the Agency for Healthcare Research and Quality Safety Program for Improving Surgical Care and Recovery. Guided by the Consolidated Framework for Implementation Research, we coded interview transcripts and conducted a thematic analysis of implementation barriers and facilitators. We also rated the perceived effect of factors on different levels of implementation success, as measured by hospitals’ adherence with 9 process measures over time. Results: Across all hospitals, factors with a consistently positive effect on implementation included information-sharing practices and the implementation processes of planning and engaging. Consistently negative factors included the complexity of the pathway itself, hospitals’ infrastructure, and the implementation process of “executing” (particularly in altering electronic health record systems). Hospitals with the greatest improvement in process measure adherence were distinguished by clinicians’ positive knowledge and beliefs about pathways and strong leadership support from both clinicians and executives. Conclusion: We draw upon diverse perspectives from across the perioperative continuum of care to qualitatively describe implementation factors most strongly associated with successful implementation of enhanced recovery pathways. [ABSTRACT FROM AUTHOR]

People with serious mental illnesses (SMIs) experience excess mortality, driven in large part by high rates of cardiovascular disease (CVD), with all cardiovascular disease risk factors elevated. Interventions designed to improve the cardiovascular health of people with SMI have been shown to lead to clinically significant improvements in clinical trials; however, the uptake of these interventions into real-life clinical settings remains limited. Implementation strategies, which constitute the "how to" component of changing healthcare practice, are critical to supporting the scale-up of evidence-based interventions that can improve the cardiovascular health of people with SMI. And yet, implementation strategies are often poorly described and rarely justified theoretically in the literature, limiting the ability of researchers and practitioners to tease apart why, what, how, and when implementation strategies lead to improvement. In this Perspective, we describe the implementation strategies that the Johns Hopkins ALACRITY Center for Health and Longevity in Mental Illness is using to scale-up three evidenced-based interventions related to: (1) weight loss; (2) tobacco smoking cessation treatment; and (3) hypertension, dyslipidemia, and diabetes care for people with SMI. Building on concepts from the literature on complex health interventions, we focus on considerations related to the core function of an intervention (i.e., or basic purposes of the change process that the health intervention seeks to facilitate) vs. the form (i.e., implementation strategies or specific activities taken to carry out core functions that are customized to local contexts). By clearly delineating how implementation strategies are operationalized to support the interventions' core functions across these three studies, we aim to build and improve the future evidence base of how to adapt, implement, and evaluate interventions to improve the cardiovascular health of people with SMI. [ABSTRACT FROM AUTHOR]

Background: Despite the potential for electronic health records (EHRs) to improve patient safety and quality of care, the intended benefits of EHRs are not always realized because of implementation-related challenges. Enlisting clinician super users to provide frontline support to employees has been recommended to foster EHR implementation success. In some instances, their enlistment has been associated with implementation success; in other cases, it has not. Little is known about why some super users are more effective than others. The purpose of this study was to identify super users' mechanisms of influence and examine their effects on EHR implementation outcomes. Methods: We conducted a longitudinal (October 2012 - June 2013), comparative case study of super users' behaviors on two medical units of a large, academic hospital implementing a new EHR system. We assessed super users' behaviors by observing 29 clinicians and conducting 24 in-depth interviews. The implementation outcome, clinicians' information systems (IS) proficiency, was assessed using longitudinal survey data collected from 43 clinicians before and after the EHR start-date. We used multivariable linear regression to estimate the relationship between clinicians' IS proficiency and the clinical unit in which they worked. Results: Super users on both units employed behaviors that supported and hindered implementation. Four super user behaviors differed between the two units: proactivity, depth of explanation, framing, and information-sharing. The unit in which super users were more proactive, provided more comprehensive explanations for their actions, used positive framing, and shared information more freely experienced significantly greater improvement in clinicians' IS proficiency (p =0.03). Use of the four behaviors varied as a function of super users' role engagement, which was influenced by how the two units' managers selected super users and shaped the implementation climate. Conclusions: Super users' behaviors in implementing EHRs vary substantively and can have important influence on implementation success. [ABSTRACT FROM AUTHOR]

Implementation of health information technology fails at an alarming rate because intended users often choose not to use it. Implementation theory and frameworks suggest that social networks may influence individuals' use, but empirical study remains limited. Furthermore, neither theory nor research has identified whose beliefs within the network matter most for implementation. We examine the relationship between an individual's system use and the beliefs of his or her peers. We assess the relationship for two peer groups: the entire group of peers and the subset that shares the individual's beliefs about the system. We used data collected from an academic hospital in the United States that had recently implemented a bar code medication administration system, a technology meant to increase medication safety. We administered a survey to nurses (N = 207) in six clinical units approximately 3–5 months (April–June 2013) after the "go-live" of the system to identify peer groups and beliefs about system usefulness. We calculated mean peer belief for the entire peer group and sharedness of belief using a homophily measure. From the hospital's electronic health record system, we obtained nurses' system use during the 3-month data collection period. We used multivariable linear regression to examine relationships. We found no effect of mean peer beliefs on individual system use. However, sharedness of belief about usefulness was positively associated with individual system use. Individuals' own positive belief was only associated with greater system use when shared with peers. Our findings indicate a significant role of social networks in implementation, and specifically that shared beliefs between an individual and his or her peer network may be critical to implementation success, more so than the beliefs across the entire peer group. Reinforcement by the social network appears to dictate whether individuals' own beliefs translate into system use. • First study to examine effects of peer beliefs on health information technology use. • When nurses shared positive beliefs about the technology with peers, use increased. • Reinforcement by peers appears to translate individual's own beliefs into action. [ABSTRACT FROM AUTHOR]