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Barriers and facilitators to implementing cancer prevention clinical decision support in primary care: a qualitative study.

ABSTRACT: BACKGROUND:In the United States, primary care providers (PCPs) routinely balance acute, chronic, and preventive patient care delivery, including cancer prevention and screening, in time-limited visits. Clinical decision support (CDS) may help PCPs prioritize cancer prevention and screening with other patient needs. In a three-arm, pragmatic, clinic-randomized control trial, we are studying cancer prevention CDS in a large, upper Midwestern healthcare system. The web-based, electronic health record (EHR)-linked CDS integrates evidence-based primary and secondary cancer prevention and screening recommendations into an existing cardiovascular risk management CDS system. Our objective with this study was to identify adoption barriers and facilitators before implementation in primary care. METHODS:We conducted semi-structured interviews guided by the Consolidated Framework for Implementation Research (CFIR) with 28 key informants employed by the healthcare organization in either leadership roles or the direct provision of clinical care. Transcribed interviews were analyzed using qualitative content analysis. RESULTS:EHR, CDS workflow, CDS users (providers and patients), training, and organizational barriers and facilitators were identified related to Intervention Characteristics, Outer Setting, Inner Setting, and Characteristics of Individuals CFIR domains. CONCLUSION:Identifying and addressing key informant-identified barriers and facilitators before implementing cancer prevention CDS in primary care may support a successful implementation and sustained use. The CFIR is a useful framework for understanding pre-implementation barriers and facilitators. Based on our findings, the research team developed and instituted specialized training, pilot testing, implementation plans, and post-implementation efforts to maximize identified facilitators and address barriers. TRIAL REGISTRATION:clinicaltrials.gov , NCT02986230 , December 6, 2016.

SUBMITTER: Harry ML

PROVIDER: S-EPMC6668099 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Barriers and facilitators to implementing cancer prevention clinical decision support in primary care: a qualitative study.

Harry Melissa L ML Truitt Anjali R AR Saman Daniel M DM Henzler-Buckingham Hillary A HA Allen Clayton I CI Walton Kayla M KM Ekstrom Heidi L HL O'Connor Patrick J PJ Sperl-Hillen JoAnn M JM Bianco Joseph A JA Elliott Thomas E TE

BMC health services research 20190731 1

<h4>Background</h4>In the United States, primary care providers (PCPs) routinely balance acute, chronic, and preventive patient care delivery, including cancer prevention and screening, in time-limited visits. Clinical decision support (CDS) may help PCPs prioritize cancer prevention and screening with other patient needs. In a three-arm, pragmatic, clinic-randomized control trial, we are studying cancer prevention CDS in a large, upper Midwestern healthcare system. The web-based, electronic hea ...[more]

PMID: 31366355

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Project description:BackgroundDespite the increasing availability of clinical decision support systems (CDSSs) and rising expectation for CDSSs based on artificial intelligence (AI), little is known about the acceptance of AI-based CDSS by physicians and its barriers and facilitators in emergency care settings.ObjectiveWe aimed to evaluate the acceptance, barriers, and facilitators to implementing AI-based CDSSs in the emergency care setting through the opinions of physicians on our newly developed, real-time AI-based CDSS, which alerts ED physicians by predicting aortic dissection based on numeric and text information from medical charts, by using the Unified Theory of Acceptance and Use of Technology (UTAUT; for quantitative evaluation) and the Consolidated Framework for Implementation Research (CFIR; for qualitative evaluation) frameworks.MethodsThis mixed methods study was performed from March to April 2021. Transitional year residents (n=6), emergency medicine residents (n=5), and emergency physicians (n=3) from two community, tertiary care hospitals in Japan were included. We first developed a real-time CDSS for predicting aortic dissection based on numeric and text information from medical charts (eg, chief complaints, medical history, vital signs) with natural language processing. This system was deployed on the internet, and the participants used the system with clinical vignettes of model cases. Participants were then involved in a mixed methods evaluation consisting of a UTAUT-based questionnaire with a 5-point Likert scale (quantitative) and a CFIR-based semistructured interview (qualitative). Cronbach α was calculated as a reliability estimate for UTAUT subconstructs. Interviews were sampled, transcribed, and analyzed using the MaxQDA software. The framework analysis approach was used during the study to determine the relevance of the CFIR constructs.ResultsAll 14 participants completed the questionnaires and interviews. Quantitative analysis revealed generally positive responses for user acceptance with all scores above the neutral score of 3.0. In addition, the mixed methods analysis identified two significant barriers (System Performance, Compatibility) and two major facilitators (Evidence Strength, Design Quality) for implementation of AI-based CDSSs in emergency care settings.ConclusionsOur mixed methods evaluation based on theoretically grounded frameworks revealed the acceptance, barriers, and facilitators of implementation of AI-based CDSS. Although the concern of system failure and overtrusting of the system could be barriers to implementation, the locality of the system and designing an intuitive user interface could likely facilitate the use of optimal AI-based CDSS. Alleviating and resolving these factors should be key to achieving good user acceptance of AI-based CDSS.

Project description:BackgroundThe long-term care setting poses unique challenges and opportunities for effective knowledge translation. The objectives of this review are to (1) synthesize barriers and facilitators to implementing evidence-based guidelines in long-term care, as defined as a home where residents require 24-h nursing care, and 50% of the population is over the age of 65 years; and (2) map barriers and facilitators to the Behaviour Change Wheel framework to inform theory-guided knowledge translation strategies.MethodsFollowing the guidance of the Cochrane Qualitative and Implementation Methods Group Guidance Series and the ENTREQ reporting guidelines, we systematically reviewed the reported experiences of long-term care staff on implementing evidence-based guidelines into practice. MEDLINE Pubmed, EMBASE Ovid, and CINAHL were searched from the earliest date available until May 2021. Two independent reviewers selected primary studies for inclusion if they were conducted in long-term care and reported the perspective or experiences of long-term care staff with implementing an evidence-based practice guideline about health conditions. Appraisal of the included studies was conducted using the Critical Appraisal Skills Programme Checklist and confidence in the findings with the GRADE-CERQual approach.FindingsAfter screening 2680 abstracts, we retrieved 115 full-text articles; 33 of these articles met the inclusion criteria. Barriers included time constraints and inadequate staffing, cost and lack of resources, and lack of teamwork and organizational support. Facilitators included leadership and champions, well-designed strategies, protocols, and resources, and adequate services, resources, and time. The most frequent Behaviour Change Wheel components were physical and social opportunity and psychological capability. We concluded moderate or high confidence in all but one of our review findings.ConclusionsFuture knowledge translation strategies to implement guidelines in long-term care should target physical and social opportunity and psychological capability, and include interventions such as environmental restructuring, training, and education.

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Project description:BackgroundDecision Boxes are summaries of the most important benefits and harms of health interventions provided to clinicians before they meet the patient, to prepare them to help patients make informed and value-based decisions. Our objective is to explore the barriers and facilitators to using Decision Boxes in clinical practice, more precisely factors stemming from (1) the Decision Boxes themselves, (2) the primary healthcare team (PHT), and (3) the primary care practice environment.Methods/designA two-phase mixed methods study will be conducted. Eight Decision Boxes relevant to primary care, and written in both English and in French, will be hosted on a website together with a tutorial to introduce the Decision Box. The Decision Boxes will be delivered as weekly emails over a span of eight weeks to clinicians of PHTs (family physicians, residents and nurses) in five primary care clinics located across two Canadian provinces. Using a web-questionnaire, clinicians will rate each Decision Box with the Information Assessment Method (cognitive impacts, relevance, usefulness, expected benefits) and with a questionnaire based on the Theory of Planned Behavior to study the determinants of clinicians' intention to use what they learned from that Decision Box in their patient encounter (attitude, social norm, perceived behavioral control). Web-log data will be used to monitor clinicians' access to the website. Following the 8-week intervention, we will conduct semi-structured group interviews with clinicians and individual interviews with clinic administrators to explore contextual factors influencing the use of the Decision Boxes. Data collected from questionnaires, focus groups and individual interviews will be combined to identify factors potentially influencing implementation of Decision Boxes in clinical practice by clinicians of PHTs.ConclusionsThis project will allow tailoring of Decision Boxes and their delivery to overcome the specific barriers identified by clinicians of PHTs to improve the implementation of shared decision making in this setting.

Dataset Information

Barriers and facilitators to implementing cancer prevention clinical decision support in primary care: a qualitative study.

Publications

Barriers and facilitators to implementing cancer prevention clinical decision support in primary care: a qualitative study.

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