40 research outputs found
Participatory System Dynamics in Implementation Science Practice: A Scoping Review
Objective: The objective of this scoping review is to 1) document PSD use in implementation science projects, 2) quantify PSD use across EPIS implementation stages (Exploration, Preparation, Implementation, and Sustainment) (EPIS), 3) quantify PSD implementation outcomes, and 4) measure fidelity and of PSD model across studies.
Introduction: Like Implementation Science, Participatory Systems Dynamics seeks to examine the complex, contextual determinants of implementation. While implementation science seeks to understand these determinants, it often does not simulate them dynamically. Therefore, this scoping review seeks to understand the applications of PSD in IS projects and how this method can complement implementation work.
Inclusion criteria: Studies published between 2000 to 2023 were included if they used a participatory systems dynamics approach to elucidate an implementation challenge. We included studies that matched the validated synonyms for this work. We excluded studies that were international, non-English language, or were not peer-reviewed (e.g., commentary or literature review).
Methods: PubMed and PsychInfo will be queried in June 2022 for PSD and IS terms and their synonyms. Synonym included in the search terms include “Group model building”, “community based systems dynamics”, “quality improvement” and “improvement science”. Abstract screening and full text screening were completed with two coders for consensus, and data extraction was completed by the first author
Coincidence analysis: a new method for causal inference in implementation science
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.publishedVersio
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An electronic family health history tool to identify and manage patients at increased risk for colorectal cancer: protocol for a randomized controlled trial.
BackgroundColorectal cancer is the fourth most commonly diagnosed cancer in the United States. Approximately 3-10% of the population has an increased risk for colorectal cancer due to family history and warrants more frequent or intensive screening. Yet, < 50% of that high-risk population receives guideline-concordant care. Systematic collection of family health history and decision support may improve guideline-concordant screening for patients at increased risk of colorectal cancer. We seek to test the effectiveness of a web-based, systematic family health history collection tool and decision support platform (MeTree) to improve risk assessment and appropriate management of colorectal cancer risk among patients in the Department of Veterans Affairs primary care practices.MethodsIn this ongoing randomized controlled trial, primary care providers at the Durham Veterans Affairs Health Care System and the Madison VA Medical Center are randomized to immediate intervention or wait-list control. Veterans are eligible if assigned to enrolled providers, have an upcoming primary care appointment, and have no conditions that would place them at increased risk for colorectal cancer (such as personal history, adenomatous polyps, or inflammatory bowel disease). Those with a recent lower endoscopy (e.g. colonoscopy, sigmoidoscopy) are excluded. Immediate intervention patients put their family health history information into a web-based platform, MeTree, which provides both patient- and provider-facing decision support reports. Wait-list control patients access MeTree 12 months post-consent. The primary outcome is the risk-concordant colorectal cancer screening referral rate obtained via chart review. Secondary outcomes include patient completion of risk management recommendations (e.g. colonoscopy) and referral for genetic consultation. We will also conduct an economic analysis and an assessment of providers' experience with MeTree clinical decision support recommendations to inform future implementation efforts if the intervention is found to be effective.DiscussionThis trial will assess the feasibility and effectiveness of patient-collected family health history linked to decision support to promote risk-appropriate screening in a large healthcare system such as the Department of Veterans Affairs.Trial registrationClinicalTrials.gov, NCT02247336 . Registered on 25 September 2014
Developing a Common Framework for Evaluating the Implementation of Genomic Medicine Interventions in Clinical Care: The IGNITE Network’s Common Measures Working Group
Purpose
Implementation research provides a structure for evaluating the clinical integration of genomic medicine interventions. This paper describes the Implementing GeNomics In PracTicE (IGNITE) Network’s efforts to promote: 1) a broader understanding of genomic medicine implementation research; and 2) the sharing of knowledge generated in the network.
Methods
To facilitate this goal the IGNITE Network Common Measures Working Group (CMG) members adopted the Consolidated Framework for Implementation Research (CFIR) to guide their approach to: identifying constructs and measures relevant to evaluating genomic medicine as a whole, standardizing data collection across projects, and combining data in a centralized resource for cross network analyses.
Results
CMG identified ten high-priority CFIR constructs as important for genomic medicine. Of those, eight didn’t have standardized measurement instruments. Therefore, we developed four survey tools to address this gap. In addition, we identified seven high-priority constructs related to patients, families, and communities that did not map to CFIR constructs. Both sets of constructs were combined to create a draft genomic medicine implementation model.
Conclusion
We developed processes to identify constructs deemed valuable for genomic medicine implementation and codified them in a model. These resources are freely available to facilitate knowledge generation and sharing across the field
Family caregiver use and value of support services in the VA Program of comprehensive assistance for family caregivers
Context: The US Congress in 2010 established the Program of Comprehensive Assistance for Family Caregivers (PCAFC) in the Department of Veterans Affairs’ (VA) healthcare system, expanding services for family caregivers of eligible veterans with injuries sustained or aggravated in the line of duty on or after 11 September 2001. The program includes a Caregiver Support Coordinator, stipends for caregivers, education/training, and additional services. Objective: The primary goal of this study was to examine the types of services that family caregivers of veterans use and value, how services are used and any limitations family caregivers’ experienced. Given that few interventions assess caregiver satisfaction with services, there is a gap in the existing literature addressing these outcomes. Methods: We assessed how caregivers use and value services with a national, web-based survey (N=1,407 caregivers) and semi-structured phone interviews (N=50 caregivers). Findings: Caregivers rated all services as helpful and especially valued financial support to be with the veteran, training in skills for symptom management, and assistance with navigating the healthcare system. A majority reported more confidence in caregiving, knowing about resources for caregiving and feeling better prepared to support the veteran’s progress and healthcare engagement. However, only a minority reported awareness of the full range of PCAFC services. Limitations: There was a low response rate to the survey, which may have implications for generalisability to the whole population of caregivers accessing PCAFC. Additionally, we rely on self-report rather than objective measures of service use and outcomes. Implications: This is the first in-depth examination of experiences of caregivers of using the innovative PCAFC model of support. It acknowledges the important role of caregivers in health and long-term (social) care delivery and can be used to inform development of strategies outside the VA healthcare system to recognise caregivers. Findings suggest that a system-wide program to effectively include caregivers as part of the care team should include mechanisms to help connect caregivers with an array of resources, options from which to find those which best fit their personal needs and preferences