Dataset Information

Determining research knowledge infrastructure for healthcare systems: a qualitative study.

ABSTRACT:

Background

This study examines research knowledge infrastructures (RKIs) found in health systems. An RKI is defined as any instrument (i.e., programs, interventions, tools) implemented in order to facilitate access, dissemination, exchange, and/or use of evidence in healthcare organisations. Based on an environmental scan (17 key informant interviews) and scoping review (26 studies), we found support for a framework that we developed that outlines components that a health system can have in its RKI. The broad domains are climate for research use, research production, activities used to link research to action, and evaluation.The objective of the current study is to profile the RKI of three types of health system organisations--regional health authorities, primary care practices, and hospitals--in two Canadian provinces to determine the current mix of components these organisations have in their RKI, their experience with these components, and their views about future RKI initiatives.

Methods

This study will include semistructured telephone interviews with a purposive sample region of a senior management team member, library/resource centre manager, and a 'knowledge broker' in three regional health authorities, five or six purposively sampled hospitals, and five or six primary care practices in Ontario and Quebec, for a maximum of 71 interviewees. The interviews will explore (a) which RKI components have proven helpful, (b) barriers and facilitators in implementing RKI components, and (c) views about next steps in further development of RKIs.

Discussion

This is the first qualitative examination of potential RKI efforts that can increase the use of research evidence in health system decision making. We anticipate being able to identify broadly applicable insights about important next steps in building effective RKIs. Some of the identified RKI components may increase the use of research evidence by decision makers, which may then lead to more informed decisions.

SUBMITTER: Ellen ME

PROVIDER: S-EPMC3123231 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature

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Publications

Determining research knowledge infrastructure for healthcare systems: a qualitative study.

Ellen Moriah E ME Lavis John N JN Ouimet Mathieu M Grimshaw Jeremy J Bédard Pierre-Olivier PO

Implementation science : IS 20110606

<h4>Background</h4>This study examines research knowledge infrastructures (RKIs) found in health systems. An RKI is defined as any instrument (i.e., programs, interventions, tools) implemented in order to facilitate access, dissemination, exchange, and/or use of evidence in healthcare organisations. Based on an environmental scan (17 key informant interviews) and scoping review (26 studies), we found support for a framework that we developed that outlines components that a health system can have ...[more]

PMID: 21645401

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Project description:BACKGROUND:Health services researchers spend a substantial amount of time performing integration, cleansing, interpretation, and aggregation of raw data from multiple public or private data sources. Often, each researcher (or someone in their team) duplicates this effort for their own project, facing the same challenges and experiencing the same pitfalls discovered by those before them. OBJECTIVE:This paper described a design process for creating a data warehouse that includes the most frequently used databases in health services research. METHODS:The design is based on a conceptual iterative process model framework that utilizes the sociotechnical systems theory approach and includes the capacity for subsequent updates of the existing data sources and the addition of new ones. We introduce the theory and the framework and then explain how they are used to inform the methodology of this study. RESULTS:The application of the iterative process model to the design research process of problem identification and solution design for the Healthcare Research and Analytics Data Infrastructure Solution (HRADIS) is described. Each phase of the iterative model produced end products to inform the implementation of HRADIS. The analysis phase produced the problem statement and requirements documents. The projection phase produced a list of tasks and goals for the ideal system. Finally, the synthesis phase provided the process for a plan to implement HRADIS. HRADIS structures and integrates data dictionaries provided by the data sources, allowing the creation of dimensions and measures for a multidimensional business intelligence system. We discuss how HRADIS is complemented with a set of data mining, analytics, and visualization tools to enable researchers to more efficiently apply multiple methods to a given research project. HRADIS also includes a built-in security and account management framework for data governance purposes to ensure customized authorization depending on user roles and parts of the data the roles are authorized to access. CONCLUSIONS:To address existing inefficiencies during the obtaining, extracting, preprocessing, cleansing, and filtering stages of data processing in health services research, we envision HRADIS as a full-service data warehouse integrating frequently used data sources, processes, and methods along with a variety of data analytics and visualization tools. This paper presents the application of the iterative process model to build such a solution. It also includes a discussion on several prominent issues, lessons learned, reflections and recommendations, and future considerations, as this model was applied.

Project description:IntroductionFinding effective ways to help pregnant women quit smoking and maintain long-term abstinence is a public health priority. Electronic cigarettes (ie, vaping) could be a suitable cessation tool in pregnancy for those who struggle to quit; however, healthcare professionals (HCP) must be informed about these devices to offer appropriate advice. This study used the Capability, Opportunity, Motivation, and Behavior (COM-B) model and Theoretical Domains Framework (TDF) to explore HCP attitudes towards vaping in pregnancy and postpartum; beliefs about the health risks of vaping; perceived barriers and facilitators of vaping in pregnancy; knowledge of current guidelines and policies; and training needs.MethodsInterviews (n = 60) were conducted with midwives (n = 17), health visitors (n = 10), general practitioners (n = 15) and stop smoking specialists (n = 18) across the United Kingdom. Interview transcriptions were analyzed thematically using the framework approach and the COM-B.ResultsDiscussing vaping as a tool for quitting smoking in pregnancy was prevented by a lack of capability (limited knowledge of vaping, lack of training in smoking cessation); lack of opportunity (restricted by organizational policies and guidelines, lack of time and financial issues impacting on training), and negative social influences (sensationalist media and stigma associated with vaping in pregnancy); and lack of motivation (fear of future litigation and comebacks should adverse effects from vaping arise).ConclusionsFactors related to capability, opportunity, and motivation were identified that influence HCPs attitudes and behaviors towards vaping in pregnancy. Gaps in knowledge and training needs were identified, which could inform the development of targeted vaping training.ImplicationsVaping could be suitable in pregnancy for those struggling to quit smoking. However, HCPs must be informed about these devices to offer appropriate advice. These data extend our knowledge of factors influencing HCP attitudes and behaviors towards vaping in pregnancy. Generally, vaping was perceived as safer than cigarettes, but a perceived lack of evidence, health and safety risks, dependency, and regulation issues were concerning. Considering our findings, greater efforts are needed to ensure HCPs are sufficiently informed about vaping and guidelines available. More importance should be placed on training for all HCPs who have contact with pregnant women.

Dataset Information

Determining research knowledge infrastructure for healthcare systems: a qualitative study.

Background

Methods

Discussion

Publications

Determining research knowledge infrastructure for healthcare systems: a qualitative study.

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