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Strategies to implement evidence-informed decision making at the organizational level: a rapid systematic review

BMC Health Services Research volume 24, Article number: 405 (2024) Cite this article

Abstract

Background

Achievement of evidence-informed decision making (EIDM) requires the integration of evidence into all practice decisions by identifying and synthesizing evidence, then developing and executing plans to implement and evaluate changes to practice. This rapid systematic review synthesizes evidence for strategies for the implementation of EIDM across organizations, mapping facilitators and barriers to the COM-B (capability, opportunity, motivation, behaviour) model for behaviour change. The review was conducted to support leadership at organizations delivering public health services (health promotion, communicable disease prevention) to drive change toward evidence-informed public health.

Methods

A systematic search was conducted in multiple databases and by reviewing publications of key authors. Articles that describe interventions to drive EIDM within teams, departments, or organizations were eligible for inclusion. For each included article, quality was assessed, and details of the intervention, setting, outcomes, facilitators and barriers were extracted. A convergent integrated approach was undertaken to analyze both quantitative and qualitative findings.

Results

Thirty-seven articles are included. Studies were conducted in primary care, public health, social services, and occupational health settings. Strategies to implement EIDM included the establishment of Knowledge Broker-type roles, building the EIDM capacity of staff, and research or academic partnerships. Facilitators and barriers align with the COM-B model for behaviour change. Facilitators for capability include the development of staff knowledge and skill, establishing specialized roles, and knowledge sharing across the organization, though staff turnover and subsequent knowledge loss was a barrier to capability. For opportunity, facilitators include the development of processes or mechanisms to support new practices, forums for learning and skill development, and protected time, and barriers include competing priorities. Facilitators identified for motivation include supportive organizational culture, expectations for new practices to occur, recognition and positive reinforcement, and strong leadership support. Barriers include negative attitudes toward new practices, and lack of understanding and support from management.

Conclusion

This review provides a comprehensive analysis of facilitators and barriers for the implementation of EIDM in organizations for public health, mapped to the COM-B model for behaviour change. The existing literature for strategies to support EIDM in public health illustrates several facilitators and barriers linked to realizing EIDM. Knowledge of these factors will help senior leadership develop and implement EIDM strategies tailored to their organization, leading to increased likelihood of implementation success.

Review registration

PROSPERO CRD42022318994.

Peer Review reports

Background

There exist expectations that decisions and programs that affect public and population health are informed by the best available evidence from research, local context, and political will [1,2,3]. To achieve evidence-informed public health, it is important that public health organizations engage in and support evidence-informed decision making (EIDM). For this review, “public health organizations” refers to organizations that implement public health programs, including health promotion, injury and disease prevention, population health monitoring, emergency preparedness and response, and other critical functions [4]. EIDM, at an organizational level, involves the integration of evidence into all practice decisions by identifying and synthesizing evidence, then developing and executing plans to implement and evaluate changes to practice [2, 5, 6]. EIDM considers research evidence along with other factors such as context, resources, experience, and patient/community input to influence decision making and program implementation [2, 3, 7, 8]. When implemented, EIDM results in efficient use of scarce resources, encourages stakeholder involvement resulting in more effective programs and decisions, improves transparency and accountability of organizations, improves health outcomes, and reduces harm [3, 7, 8]. Therefore, it is important that EIDM is integrated into organizations serving public health.

Driving organizational change for EIDM is challenging due to the need for multifaceted interventions [9].While there are systematic reviews of the implementation of specific evidence-informed initiatives, reviews of implementation of organization-wide EIDM are lacking. For example, Mathieson et al. and Li et al. examined the barriers and facilitators to the implementation of evidence-informed interventions in community nursing and Paci et al. examined barriers in physiotherapy [10,11,12]. Li et al. found that implementation of evidence-informed practices is associated with an organizational culture for EIDM where staff at all levels value and contribute to EIDM [12]. Similarly, Mathieson et al. and Paci et al. found that organizational context plays an important role in evidence-informed practice implementation along with organizational support and resources [10, 11]. While these reviews identify organizational context, culture and support as crucial for the implementation of a particular evidence-informed practice, they do not identify and describe sufficiently what and how an organization evolves to consistently be evidence-informed for all decisions and programs and services it delivers.

Primary studies have explored how building capacity for staff to find, interpret and synthesize evidence to develop practice and program recommendations may contribute to EIDM [13,14,15,16]. In 2019, Saunders et al. completed an overview of systematic reviews on primary health care professionals’ EIDM competencies and found that implementation of EIDM across studies was low [9]. Participants reported insufficient knowledge and skills to implement EIDM in daily practice despite positive EIDM beliefs and attitudes [9]. In 2014, Sadeghi-Bazargani et al. and in 2018, Barzkar et al. also explored the implementation of EIDM and found similar results, listing inadequate skills and lack of knowledge amongst the most common barriers to EIDM [17, 18].

An underlying current in research for organizational EIDM is a focus on organizational change [13, 14, 19, 20]. To achieve EIDM across an organization, significant organizational change is usually necessary, resulting in substantial impact on the entire organization, as well as for individuals working there. However, while there are reviews of individual capacity for EIDM, there is minimal synthesized evidence describing EIDM capacity at the organizational level. This review seeks to address this research gap by identifying, appraising, and synthesizing research evidence from studies seeking to understand the process of embedding EIDM across an organization, with a focus on public health organizations.

The COM-B model for behaviour change was used as a guide for contextualizing the findings across studies. By integrating causal components of behaviour change, the COM-B model supports the development of interventions that can sustain behaviour change in the long-term. While there are numerous models available to support implementation and organizational change, the COM-B model was chosen, in part, for its simple visual representation of concepts, as well as its contributions to the sustainability of behaviours [21]. This model is designed to guide organizational change initiatives and distill complex systems that influence behaviour into simpler, visual representations. Specifically, this model looks at capability (C), opportunity (O) and motivation (M) as three key influencers of behaviour (B). The capability section of the COM-B model reflects whether the intended audience possess the knowledge and skills for a new behaviour. Opportunity reflects whether there is opportunity for new behaviour to occur, while motivation reflects whether there is sufficient motivation for a new behaviour to occur. All three components interact to create behaviour and behaviours can, in turn, alter capability, motivation and opportunity [21]. Selection of the COM-B model was also driven by authors’ extensive experience supporting public health organizations in implementing EIDM, which observed enablers for EIDM that align well with the COM-B model, such as team-wide capacity-building for EIDM, integration of EIDM into processes, and support from senior leadership [20, 22, 23]. The COM-B model has been used to map findings from systematic reviews examining the barriers and facilitators of various health interventions including nicotine replacement, chlamydia testing and lifestyle management of polycystic ovary syndrome [24,25,26]. This review has a broader focus and maps barriers and facilitators for organization-wide EIDM to the COM-B model.

Overall, EIDM is expected to be a foundation at public health organizations to achieve optimal health of populations. However, the capacity of public health organizations to realize EIDM varies considerably from organization to organization [14, 22, 27,28,29]. This rapid review aims to examine the implementation of EIDM at the organizational level to inform change efforts at Canadian public health organizations. The findings of this review can be applied more broadly and will support public health organizations beyond Canada to implement change efforts to practice in an evidence-informed way.

Methods

Study design

The review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO; Registration CRD42022318994). The review was conducted and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement for reporting systematic reviews and meta-analyses [30]. A rapid review approach was used, since the review was requested to be completed by the National Collaborating Centre for Methods and Tools’ Rapid Evidence Service within a specific timeline, in order to inform an organizational change initiative at a provincial public health organization in Canada [31]. Given the nature of the research question, a mixed methods rapid systematic review approach was taken, with guidance from the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis [32].

Information sources and search strategy

The search was conducted on March 18, 2022. The following databases were searched from 2012 onward: Medline, Embase, Emcare, Global Health Database, PsycINFO, Web of Science. Each database was searched using combinations and variations of the terms “implement*”, “knowledge broker*”, “transform*”, “organizational culture”, “change management”, “evidence-based”, “knowledge translation”, and “knowledge mobilization”. Additionally, publications by key contributors to the field were reviewed. The full search strategy is included in Appendix 1.

Studies were screened using DistillerSR software. Titles and abstracts of retrieved studies were screened by a single reviewer. Full texts of included studies were screened by a second reviewer and reviewed by a third. Screening was not completed in duplicate, consistent with a rapid review protocol [31]. To minimize the risk of bias, a subset of 100 retrieved articles were screened in duplicate at the title and abstract stage to ensure consistency across reviewers. Of this subset, there were four articles with conflicting decisions, which were discussed amongst screeners to clarify inclusion criteria.

Eligibility criteria

English-language, published primary studies with experimental or observational designs were eligible for inclusion. Review papers, such as literature and systematic reviews, were excluded to ensure that details regarding implementation of initiatives were captured without re-interpretation or generalization by review authors. Grey literature was not included. Eligibility criteria are outlined below in terms of a PICO (Population, Intervention, Comparison, Outcome) structure [33].

Population

Studies conducted with public sector health-related service-delivery organizations were eligible for inclusion. This included public health departments and authorities, health care settings and social services. Studies focused on departments or teams within an organization, or on entire organizations, were also eligible for inclusion. Studies conducted in private sectors or academic institutions were excluded to narrow the focus of the review.

Intervention

Interventions designed and implemented to shift teams, departments, or organizations to EIDM in all decisions were eligible for inclusion. These can include initiatives where organizations establish roles or teams to drive organizational change for EIDM, or efforts to build and apply the knowledge and skill of staff for EIDM. These are distinct from implementation strategies for evidence-informed interventions. Eligible interventions were applied to a team, department, or organization to drive change toward evidence use in decision making at all levels of the organizations.

Comparator

Studies that included any comparator or no comparator were included, recognizing that literature was likely to include case reports.

Outcomes

Outcomes measured either quantitatively or qualitatively were considered. These included behaviour change, confidence and skills, patient-level data such as quality indicators, evidence of EIDM embedded in organizational and decision-making processes, changes in organizational culture, and changes to budget allocation. Studies that reported primarily on implementation fidelity were excluded, since studies of implementation fidelity focus on whether an intervention is delivered as intended, rather than drivers for organizational change.

Setting

Studies conducted in the 38 member countries of the Organization for Economic Co-operation and Development (OECD) were included in this review to best align with the Canadian context and to inform organizational change efforts in public health within Canada [34].

Quality assessment

The methodological rigour of included studies was evaluated using the JBI suite of critical appraisal tools [35]. Ratings of low, moderate, or high quality were assigned based on the critical appraisal results. Quality assessment was completed by one reviewer and verified by a second. Conflicts were resolved through discussion or by consulting a third reviewer.

Data extraction

Data extraction was completed by a single reviewer and reviewed by a second. Data on the study design, setting, sector (e.g., public health, primary care, etc.), participants, intervention (e.g., description of learning initiatives, implementation strategies, etc.), outcome measures, and findings were extracted. To minimize the risk of bias, a subset of three included articles underwent data extraction in duplicate to ensure consistency across reviewers. There was good agreement between duplicate extraction, with variations in the format of extracted data but consistency in content.

Data analysis

Quantitative and qualitative data were synthesized simultaneously, using a convergent integrated approach [32]. Quantitative data underwent narrative synthesis, where findings that caused benefit were compared with those that caused harm or no effect [36]. Vote counting based on the direction of effect was used to determine whether most studies found a positive or negative effect [36]. For qualitative findings, studies were grouped according to common strategies. Within these common strategies, findings were reviewed for trends in reported facilitators and barriers. These trends were deductively mapped to the COM-B model for behaviour change [37].

Due to the heterogeneity in study outcomes, the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) [38] approach was not used for this review. Overall certainty of evidence was determined based on the risk of bias of included study designs and study quality.

Results

Database searching retrieved 7067 records. After removing duplicates, 4174 records were screened by title and abstract, resulting in 1370 reports for full text review. Of those 1370 records, 35 articles were included. Scanning the publication lists of key authors retrieved 187 records, of which eight were retrieved for full text review and two were included, for a total of 37 articles included in this review. See Fig. 1 for a PRISMA flow chart illustrating the article search and selection process.

Fig. 1
figure 1

PRISMA 2020 flow chart

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Study characteristics

The overall characteristics of included studies are summarized in Table 1. Of 37 included studies, most were conducted in primary care settings (n = 16) and public health settings (n = 16), with some in social services (n = 3), child and youth mental health (n = 1), and occupational health (n = 1). Most studies were conducted in the USA (n = 17), followed by Canada (n = 12), Australia (n = 5), and Europe (n = 3).

Table 1 Included studies of organization-wide implementation of EIDM
Full size table

Study designs included case reports (n = 18), single group pre-/post-test studies (n = 10), qualitative studies (n = 7), and randomized controlled trials (RCTs) (n = 2). Both RCTs evaluated the implementation of organizational EIDM.

Studies reported quantitative (n = 11), qualitative (n = 20), or both quantitative and qualitative results (n = 6). For the studies that reported quantitative results, measures included EIDM implementation, EIDM-related beliefs and behaviours, organizational priorities for EIDM, and patient care quality indicators. Quantitative measures were heterogenous and did not allow meta-analysis. Qualitative findings were generated through formal qualitative analysis (n = 19) or descriptive case reports (n = 7). Most qualitative results included facilitators and barriers to implementation (n = 16).

Study quality

The critical appraisal checklist used to assess each study is indicated in Table 1. Single group, pre-/post-test studies were evaluated according to the JBI Checklist for Quasi-experimental Studies [35].

A lack of control groups contributed to the risk of bias. Most included studies were rated Moderate or High quality according to their respective quality assessment tools. Full quality assessments for each article are included in Appendix 2. Therefore, the overall methodological quality for this body of literature was rated as Moderate.

Strategies for implementing organization-wide EIDM

Due to the heterogeneity of study designs, interventions, and outcomes, it was not possible to determine which EIDM implementation strategies are more effective compared to others. Implementation strategies included the establishment of Knowledge Broker-type roles, building the EIDM capacity of staff, and research or academic partnerships. These strategies are listed in Table 2.

Table 2 Strategies for implementation of organization-wide EIDM
Full size table

Evaluation of strategies implemented by studies in this review was often qualitative and described facilitators and barriers, rather than quantitatively measuring effectiveness. However, it is possible to explore EIDM implementation strategies and factors that appear to contribute to or inhibit success. The most common strategy implemented in included studies was the establishment of Knowledge Broker-type roles [20, 41, 44, 47, 48, 51, 52, 54,55,56,57, 59, 60, 62,63,64,65,66,67, 69, 71, 72]. Studies described roles differently (e.g., “Evidence-based Practice Facilitator”, “Evidence Facilitator”, “EIDM Mentor”). These roles all served to support EIDM across organizations through knowledge sharing, evidence synthesis, implementation, and other EIDM-related activities. In some studies, new staff were hired to Knowledge Broker roles, or developed among existing staff, while in others, Knowledge Brokers were contracted from external organizations. Knowledge Broker strategies were mostly implemented in parallel with other EIDM implementation strategies, such as capacity building for staff, integrating EIDM into decision-making processes and development of leadership to support EIDM. When these strategies were evaluated quantitatively for organizational capacity, culture and implementation of EIDM, most studies found positive results, such as increased scores for organizational climates supporting EIDM, improved attitudes toward EIDM, or the integration of EIDM into processes [44, 52, 54, 62, 66, 67, 71, 72], although some studies found no change [55, 60] following implementation of Knowledge Broker roles. Qualitatively, most studies described facilitators and barriers to EIDM, either through formal qualitative analysis or case report [14, 20, 39,40,41,42,43, 45, 47, 48, 52, 55, 57, 59,60,61, 64, 65, 68]. Facilitators included organizational culture with supportive leadership and staff buy-in, expectations to use evidence to inform decisions, accessible knowledge, and integration of EIDM into processes and templates. Barriers included limited time and competing priorities, staff turnover, and lack of understanding and support from management.

Ten included studies focused primarily on building EIDM capacity of existing staff at the organization, often at multiple levels (e.g., front-line service providers, managers, and leadership) [13, 14, 39, 40, 42, 43, 46, 49, 50, 58, 61]. Capacity building was typically done through EIDM-focused workshops, often with ongoing follow up support from workshop facilitators. While studies often measured changes in individual knowledge and skill for EIDM for workshop participants, organizational change for EIDM was reported qualitatively, either through formal qualitative analysis or through a case report. Facilitators for EIDM in these ten studies included organizational culture with supportive leadership and staff buy-in, dedicated staff roles to support EIDM, opportunities to meet and discuss EIDM (e.g., communities of practice, journal clubs), knowledge sharing across the organization, expectations to use evidence to inform decisions, accessible knowledge, and integration of EIDM into processes and templates. Barriers included limited time and competing priorities, staff turnover, and negative attitudes toward EIDM.

Research or academic partnerships and networks were the main strategy described in three case reports [45, 53, 68]. These involved establishing collaborations, either through universities or non-governmental health organizations, that provided direct EIDM support. These strategies were not evaluated quantitatively but described facilitators and barriers to effective cross-sector collaborations. Facilitators for EIDM included supportive leadership and management, dedicated staff roles to support EIDM, EIDM knowledge and skill development for staff, and regular communication between partners. Barriers included limited time and competing priorities, preference for experiential over research evidence, and negative attitudes toward EIDM.

Overall, studies described successes in implementing EIDM across organizations, citing several common key facilitators and barriers. To instigate behaviour change, strategies must address capability for change, which may be achieved by building staff capacity, establishing dedicated support roles, improving access to evidence, and sharing knowledge across the organization. Strategies must also enable opportunities for change, which may be supported through forums for EIDM learning and practice, protecting time for EIDM, integrating EIDM into new or existing roles, and adding EIDM to processes and templates. Behaviour change also requires motivation, which may be built through a supportive organizational culture, expectations to use EIDM, recognition and positive reinforcement, and strong support from leadership.

Key considerations for implementing EIDM

Many of the facilitators and barriers to EIDM are common across strategies explored by the studies included in this review. To conceptualize these factors, they were mapped to the COM-B model for behaviour change [21] in Fig. 2.

Fig. 2
figure 2

COM-B Model for behaviour change with facilitators and barriers for implementation of organization-wide EIDM

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Within the capability component of the COM-B model, staff knowledge and skill development were included as a facilitator. Studies included in this review demonstrated that knowledge and skill for EIDM supported the use of evidence in decision making [13, 14, 39, 40, 42, 43, 46, 49, 50, 58, 61]. The establishment of specialized or dedicated roles for EIDM, such as Knowledge Broker roles, was included in the capability component of the COM-B model, since Knowledge Broker roles support the capacity of organizations and their staff to use evidence-informed approaches [20, 41, 44, 47, 48, 51, 52, 54,55,56,57, 59, 60, 62,63,64,65,66,67, 69, 71, 72]. Finally, knowledge sharing across organizations was described as a facilitator for EIDM by several of the studies that built staff capacity for EIDM or established Knowledge Broker roles [13, 48, 49, 51, 52, 54, 56, 59, 61, 65]. Barriers to the capability for EIDM behaviours include staff turnover and subsequent knowledge loss [14, 20, 56]. Staff turnover is especially challenging for interventions that involve staff in dedicated Knowledge Broker roles and interventions that build the knowledge and skill for staff to engage in evidence use [14, 20, 56]. In some cases, individuals who are trained in the Knowledge Broker role are then promoted to new roles or management and have fewer opportunities to apply their Knowledge Broker skills [20].

The opportunity portion of the COM-B model reflects whether there is opportunity for new behaviour to occur. The development of processes and mechanisms that support new practices can act as a reminder for staff, and may include re-design of planning or decision-making templates to capture supporting evidence, or adding EIDM-related items to agendas for regular meetings [41, 47, 53, 60]. Forums for learning and skill development provide staff with opportunities to gain knowledge and practice newly acquired skills in group settings, such as communities of practice or journal clubs [48, 56, 61, 65]. Finally, protected time to apply EIDM was found to be a facilitator for opportunity in the COM-B model [20, 47, 57, 59, 65], while competing priorities were found to be a barrier [20, 39, 40, 52, 55, 57, 60, 64, 65].

The final influencer in the COM-B model, motivation, reflects whether there is sufficient motivation for a new behaviour to occur. Facilitators include supportive organizational culture [14, 20, 43, 47, 57, 59], expectations for new practices to occur [20, 40], recognition and positive reinforcement [52, 59, 60, 65], and strong leadership support [14, 20, 39, 40, 43, 47, 56, 59, 65, 68]. Barriers to motivation included a lack of understanding or support from management [20], and negative attitudes toward change [20, 52, 59, 68].

Discussion

Strategies to implement EIDM across organizations include establishing specialized roles, providing staff education and training, developing processes or mechanisms to support new practices, and demonstrating leadership support. Facilitators and barriers for these strategies align with the COM-B model for behaviour change, which outlines capability, opportunity, and motivation as influencers of behaviour (Fig. 2). The COM-B model provides a comprehensive framework for the factors that influence behaviour change and has provided a valuable structure for examining barriers and facilitators to behaviour change in public health and related fields [73,74,75,76].

The capability section of the COM-B model reflects whether the intended audience possess the knowledge and skill for a new behaviour. Findings from this review establish facilitators for EIDM implementation capability, including the development of staff knowledge and skill, establishing specialized roles, and knowledge sharing across the organization. The development of staff knowledge and skill for EIDM are a necessary component to ensure EIDM in practice, however, literature has found that the organization-wide impact of conducting only individual-level knowledge and skill development is limited [77,78,79]. While knowledge and skill development are a necessary component to EIDM practice, they must be supported by other components to have an impact beyond the individual. Other strategies that support the use of newly gained knowledge and skills include the establishment of specialized roles for EIDM. Another strategy to support the use of EIDM is the establishment of dedicated staff roles, such as Knowledge Brokers. Knowledge Broker roles have been used across diverse contexts and show promise in supporting organization-wide EIDM implementation [20, 22, 23, 67, 80,81,82,83]. One facilitator for Knowledge Broker roles was knowledge sharing across the organization. Factors that influence the success of staff in Knowledge Broker roles align with those mapped to opportunity and motivation in the COM-B model, including the integration of EIDM into processes, knowledge sharing, and supportive organizational culture [20, 22, 47, 67, 84, 85]. Knowledge Brokers can also help facilitate knowledge sharing across the organization, which was another facilitator mapped to the capability level of the model [20, 47, 84, 85]. Knowledge sharing refers to the shared learning, knowledge products and resources for EIDM. At large public health organizations, it can be challenging to facilitate knowledge sharing between teams and departments [86, 87]. Integrating technology can help; there have been some advances driven by the COVID-19 pandemic, such as the development of knowledge sharing platforms [88,89,90,91]. Public health organizations seeking to implement EIDM should invest in their knowledge sharing infrastructure.

At the capability level of the COM-B model, staff turnover was a barrier to EIDM implementation. Organizations that implement these strategies should be cognizant of the potential for knowledge loss due to staff turnover when selecting staff for Knowledge Broker roles or capacity building opportunities.

Facilitators for organizational EIDM opportunity include the development of processes or mechanisms to support new practices, forums for learning and skill development, and protected time. The use of reminders for organizational behaviour change and implementation of clinical practice guidelines has been shown to be an effective strategy across many contexts [92,93,94,95]. Organizations seeking to implement EIDM should consider revising current templates and processes to support their initiatives. Another facilitator included forums for shared learning and skill development. Other literature shows that these forums can be effective in developing knowledge and skill and should foster an environment of learning without fear of reprisal [96, 97]. Finally, protected time for EIDM was a facilitator and competing priorities were a barrier. In public health practice, staff are often challenged with high workloads, so that EIDM may be viewed as an additional burden rather than a means to improve practice [98, 99]. For an EIDM approach to be practiced, staff must be provided with sufficient time to apply and practice skills. Organizations should consider involving middle management who oversee staff time allocations, rather than only senior leadership, to help ensure that staff are provided with the time they need and that expectations are adjusted accordingly [20, 23].

At the motivation level of the COM-B model, supportive organizational culture was mapped as a facilitator. The influence of organizational culture on evidence-informed practice at health organizations has been explored in a previous systematic review by Li et al. [100]. This systematic review of organizational contextual factors that influence evidence-based practice included 37 studies conducted in healthcare-related settings. Findings align with facilitators identified above, especially leadership support, which was found to impact evidence-based practice as well as all other factors that influence evidence-based practice [100]. The review also found that monitoring and feedback contributed to implementation of evidence-based practice, which aligns with recognition and positive reinforcement in the COM-B model above [100]. Notably, another factor that was mapped to the COM-B model was the expectation for new practices to occur, which was not explicitly identified as an influence on practice [100]. While Li et al. acknowledge that leadership that neglects to hold staff accountable are detrimental to implementation of EIDM, this accountability and clear expectations for change practice were a stronger finding in this current rapid systematic review.

The need for leadership support aligns with opportunity, since it is often management that determines the allocation of staff time for EIDM [20, 23]. Attitudes and the belief that EIDM is associated with positive outcomes is a key factor in overall competence for EIDM [101]. Efforts to address negative attitudes within staff, especially at the leadership level, may improve implementation of EIDM.

While this review provides a comprehensive overview of interventions to support EIDM in public health and related organizations, it does have some limitations. Given the heterogeneity of included studies, it was not possible to discern which implementation strategies for EIDM are more effective compared to others. Knowledge Broker roles, building capacity for EIDM, and research-academic partnerships were all shown to contribute to EIDM, but study findings do not support one strategy as superior to others. Given the highly contextual nature of these interventions, it is likely that the relative effectiveness of different interventions depends on the organization’s unique set of characteristics. Evaluation is also critical to determine if change efforts are successful or need to be adjusted. It is possible that a combination of strategies would maximize the likelihood that diverse needs of staff are met. Rigorous studies to evaluate this hypothesis are needed.

Most studies included in this review are non-randomized studies of interventions. Given the importance of context in organizational change, randomized controlled trial designs may not be well-suited to evaluate studies of EIDM implementation [102]. High-quality single-group studies, such as prospective cohort analytic studies evaluated with validated measures or qualitative descriptive analyses of case studies with thorough descriptions of interventions and context, may be more appropriate designs for designing future initiatives in this field. However, arguments have been made for the use of randomized trial designs in implementation research [103]. Foy et al. advocate for overcoming contextual barriers by using innovative trial designs, such as the multiphase optimization strategy approach, where a series of trials identify the most promising single or combined intervention components, or the sequential multiple assignment randomized trial approach, where early results inform tailoring of adaptive interventions [103]. These designs may be a promising approach to conducting trials within highly contextual settings. Another viewpoint is that perhaps it may not be essential to determine if one strategy is superior to another, but rather that strategies build a larger, multi-strategy approach to implementation [104]. There may be greater benefit to determining the conditions under which various strategies are effective [104].

A limitation in this review’s methodology is that the review was completed following a rapid review protocol to ensure timely completion. Modifications of a systematic review approach included the use of a single reviewer for screening and using an unblinded reviewer to check quality assessment and data extraction. This may have contributed to some bias within the review, due to the reviewers’ interpretations of studies. To minimize this bias, there were efforts to calibrate screening, quality assessment and data extraction using a subset of studies.

This review provides a synthesis of strategies for the organization-wide implementation of EIDM, and an in-depth analysis of their facilitators and barriers in public health organizations. Facilitators and barriers mapped to the COM-B model for behaviour change can be used by organizational leadership to drive organizational change toward EIDM.

Conclusion

This rapid systematic review explored the implementation of EIDM at the organizational level of public health and related organizations. Despite the similarity of these implementation challenges, studies used distinct strategies for implementation, including the establishment of dedicated roles to support EIDM, building staff capacities, research or academic partnerships, and integrating evidence into processes or mechanisms. Facilitators and barriers mapped to the COM-B model provide key guidance for driving organizational change to evidence-informed approaches for all decisions.

Availability of data and materials

All data generated or analysed during this study are included in this published article and its supplementary information files.

Abbreviations

EIDM:

Evidence-informed Decision Making

EBP:

Evidence-based Practice

EIP:

Evidence-informed Practice

GRADE:

Grading of Recommendations, Assessment, Development and Evaluations

JBI:

Joanna Briggs Institute

KT:

Knowledge Translation

RCT:

Randomized Controlled Trial

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Acknowledgements

The authors would like to acknowledge the NCCMT’s Rapid Evidence Service, particularly Alyssa Kostopoulos, Sophie Neumann and Selin Akaraci, for their contributions to this review.

Funding

The National Collaborating Centre for Methods and Tools is hosted by McMaster University and funded by the Public Health Agency of Canada. The views expressed herein do not necessarily represent the views of the Public Health Agency of Canada. The funder had no role in the design of the study, collection, analysis, or interpretation of data or in writing the manuscript.

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  1. National Collaborating Centre for Methods and Tools, McMaster University, McMaster Innovation Park, 175 Longwood Rd S, Suite 210a, Hamilton, ON, L8P 0A1, Canada

    Emily C. Clark, Trish Burnett, Rebecca Blair, Robyn L. Traynor, Leah Hagerman & Maureen Dobbins

  2. School of Nursing, McMaster University, Health Sciences Centre, 2J20, 1280 Main St W, Hamilton, ON, L8S 4K1, Canada

    Maureen Dobbins

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Contributions

E.C.C. and M.D. designed the study. E.C.C., L.H., R.B., R.L.T., and T.B. completed screening, quality assessment and data extraction. E.C. and M.D. analyzed study results. E.C.C. and T.B. wrote the manuscript in consultation with M.D. All authors read and approved the final manuscript.

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Correspondence to Maureen Dobbins.

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Clark, E.C., Burnett, T., Blair, R. et al. Strategies to implement evidence-informed decision making at the organizational level: a rapid systematic review. BMC Health Serv Res 24, 405 (2024). https://doi.org/10.1186/s12913-024-10841-3

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