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Effectiveness of implementation interventions in improving physician adherence to guideline recommendations in heart failure: a systematic review

Background The uptake of guideline recommendations that improve heart failure (HF) outcomes remains suboptimal. We reviewed implementation interventions that improve physician adherence to these recommendations, and identified contextual factors associated with implementation success. Methods We searched databases from January 1990 to November 2017 for studies testing interventions to improve uptake of class I HF guidelines. We used the Cochrane Effective Practice and Organisation of Care and Process Redesign frameworks for data extraction. Primary outcomes included: proportion of eligible patients offered guideline-recommended pharmacotherapy, self-care education, left ventricular function assessment and/or intracardiac devices. We reported clinical outcomes when available. Results We included 38 studies. Provider-level interventions (n=13 studies) included audit and feedback, reminders and education. Organisation-level interventions (n=18) included medical records system changes, multidisciplinary teams, clinical pathways and continuity of care. System-level interventions (n=3) included provider/institutional incentives. Four studies assessed multi-level interventions. We could not perform meta-analyses due to statistical/conceptual heterogeneity. Thirty-two studies reported significant improvements in at least one primary outcome. Clinical pathways, multidisciplinary teams and multifaceted interventions were most consistently successful in increasing physician uptake of guidelines. Among randomised controlled trials (RCT) (n=10), pharmacist and nurse-led interventions improved target dose prescriptions. Eleven studies reported clinical outcomes; significant improvements were reported in three, including a clinical pathway, a multidisciplinary team and a multifaceted intervention. Baseline assessment of barriers, staff training, iterative intervention development, leadership commitment and policy/financial incentives were associated with intervention effectiveness. Most studies (n=20) had medium risk of bias; nine RCTs had low risk of bias. Conclusion Our study is limited by the quality and heterogeneity of the primary studies. Clinical pathways, multidisciplinary teams and multifaceted interventions appear to be most consistent in increasing guideline uptake. However, improvements in process outcomes were rarely accompanied by improvements in clinical outcomes. Our work highlights the need for improved research methodology to reliably assess the effectiveness of implementation interventions.


INTRODUCTION
Heart Failure (HF) has a prevalence of approximately 10% in the elderly, and is a common cause of hospitalization and death in older adults. [1] Patients diagnosed with HF have a 30% risk of mortality at 3 years, and those hospitalized for HF face a substantially higher risk. [1] Evidenceinformed HF treatments can improve clinical outcomes and recommendations surrounding their use are published in clinical practice guidelines. [2,3,4,5] Class I/Level A recommendations are supported by strong evidence, and are associated with reduced hospitalization and mortality; these include assessment of heart function, self-care education, pharmacotherapy, and device therapies. [2] However, studies show that the uptake of these guidelines by physicians into routine clinical practice remains slow and inconsistent. [6,7,8] Implementation interventions are designed to bridge the gap between evidence and practice, and are broadly classified at the provider, organizational, or health systems levels. Interventions may be single or multifaceted.[9] Implementation success also depends on the interventiondevelopment process and organizational context. While previous reviews have evaluated implementation interventions,[10] none, to our knowledge, have evaluated interventions within HF care or identified contextual factors associated with implementation success.
Accordingly, the primary objective of our review was to examine the effectiveness of implementation interventions in increasing physician adherence to the specified HF guideline recommendations. Our secondary objectives were to assess the effect of implementation interventions on clinical outcomes, and to identify process and contextual factors that influence implementation success.

METHODS AND ANALYSIS
The systematic review protocol is registered in the International Prospective Register of Systematic Reviews (PROSPERO: CRD42015017155), and published in a peer-reviewed journal.
[11] The only deviation from the protocol was the inclusion of uncontrolled before-after studies.

Eligibility criteria
We included trials evaluating 1 or more interventions aimed at improving physician adherence to Class I HF guidelines, relative to usual care. Interventions were categorized by level (i.e. provider-, organization-, systems-level) and type (i.e. education, decision-support, financial Outcomes While implementation interventions were targeted towards healthcare providers, outcomes were measured at the level of the patient (e.g. number of patients receiving guideline-appropriate care). Primary outcomes were process indicators, defined as measures that assess guidelineconsistent activities undertaken by a provider.
[12] The primary outcomes included the proportion of eligible HF patients who: were prescribed a guideline-recommended pharmacological treatment such as β-blockers, angiotensin-converting-enzyme inhibitors (ACEIs), angiotensin II receptor blockers (ARBs), or mineralocorticoid receptor antagonists (MRAs); were referred for implantable cardioverter defibrillator (ICD) and/or cardiac resynchronization therapy (CRT) consideration; were provided self-care education at discharge; and/or had their left ventricular ejection fraction (LVEF) quantified. Secondary outcomes were clinical outcomes such as HFrelated hospitalizations, readmissions and mortality. In the absence of HF-specific clinical outcomes, we extracted and reported all-cause clinical outcomes.

Study design
We included randomized controlled trials (RCTs), cohort studies (with comparisons), controlled and uncontrolled before and after studies, and interrupted time series studies.

Study selection
We searched for all English language articles published since 1990 in MEDLINE, EMBASE,  Centre for Reviews and Dissemination Database. Our primary search strategy used the terms: heart failure, guideline adherence, practice guideline, evidence-based medicine, implement (Appendix 1). Our secondary search included terms for each of the different EPOC intervention types and heart failure (Appendix 2). Two authors independently screened titles and abstracts, and then assessed select full-text articles according to the eligibility criteria.

Data extraction and management
Two authors independently extracted details about study design, statistical analysis, intervention, patient and provider characteristics, follow-up, and outcomes using the EPOC Data Collection Checklist.
[9] In addition, the Process Redesign framework was used to extract and synthesize details on the intervention-development process, and relevant contextual factors. [13]

Assessment of risk of bias
In addition to identifying the limitations inherent within specific study designs, two authors independently applied design-specific criteria to assess the internal validity of studies retained for analysis. We used the criteria outlined in the EPOC Data Collection Checklist to evaluate

Data synthesis
We classified the implementation interventions according to the level targeted (provider, organization, and system) and the type of intervention (e.g. education, decision-support, auditand-feedback, financial) using the EPOC Taxonomy.
[9] An abbreviated version of the EPOC Taxonomy is presented in Table 1. We explored the suitability of a meta-analysis of the results within each intervention category by first assessing clinical heterogeneity at face value on the basis of included patient populations, settings (inpatient/outpatient), intervention types, and outcome measures. We then assessed statistical heterogeneity using the I 2 statistic, defining substantial heterogeneity as I 2 >75%. For studies not suitable for meta-analysis, we narratively synthesized results. [17,18] We performed vote counting for each outcome measure in each EPOC intervention category, by noting the number of studies reporting significant improvements compared to those with no significant improvements.

Contextual factors
Context generally refers to the physical, social, political, and economic influences on healthcare practices. [19] We used the Process Redesign framework to systematically evaluate contextual factors that may influence the effectiveness of implementation interventions.
[13] The Process Redesign framework classifies context into categories: outer setting, inner setting, and characteristics of individuals and teams. The inner context refers to the structural characteristics of the clinical setting (e.g. inpatient, outpatient, community-based care, academic status), networks and communications, culture, and climate. The characteristics of individuals and teams more specifically refer to professional roles, responsibilities, and authority within the organization. The outer context refers to factors related to the broader social, political, and economic environment in which the intervention is applied. We considered processes that introduced and adapted the intervention to the organization as part of the intervention, rather than the context. An abbreviated and modified version of the framework is presented in Table 2.  Degree to which intervention steps are developed in advance of implementation and with consideration of various possible scenarios Assessing Formal assessment of the problem or condition to be changed, including needs of users, and barriers and facilitators of change Staging and iteration Whether the implementation is carried out in incremental steps, refined iteratively, or implemented in its entirety within a specified period Access to information, training, and education Staff access to information or education about the intervention Inner Setting (contextual factor) Team and network characteristics Influence, breadth, depth, and role diversity of teams and networks engaged in the Process Redesign Teams, networks, and communications Quality of teams and social networks; formal/informal communication and information exchange within an organization or between organizations Culture Norms, values, and beliefs within a team, unit, or practice that affect views of process redesign and its implementation Mandate Whether adherence to the intervention is expected or mandated Leadership commitment Degree of commitment, involvement, and accountability of leaders and managers to quality improvement and to the specific intervention Human factors Whether features of the physical and technical environment of the practice are designed to optimize human use, accessibility, and uptake in patient care Outer Setting (contextual factor) External networks Degree to which an organization is networked with other organizations engaged in similar types of process redesign activities External pressure Pressure emanating from outside the organization to introduce an intervention External policy and incentives/disincentives Laws, regulations, governmental recommendations, and/or payment schemes that affect the decision to adopt or abandon the process redesign efforts Characteristics of Individuals and Teams (contextual factor) Role Individual's or team's role and responsibilities, and the extent of multiple or shared roles Authority Perceived and actual degree of authority to make decisions and act autonomously Our systematic search produced 2424 unique articles, of which 2299 were excluded on the basis of title and/or abstract review. We assessed 126 full-text articles, of which 35 studies met eligibility criteria. We excluded articles that: were abstracts, protocols, or letters (N=9); did not test implementation interventions (N=20); did not focus on HF patients (N=3); had no comparator group (N=5); or had no outcomes of interest (N=54) (see Figure 1).

Characteristics of included studies
Setting. A majority of the studies were conducted in the USA (N=25), and the remainder in Europe (N=9) and Australia (N=1). Sixteen studies were conducted in inpatient settings, 18 in outpatient settings, and 1 involved care in both settings (Table 3).  Intervention: Cardiologists presented guidelines and discussed cases with colleagues. Educational aids and guideline booklets were supplied to physicians.
Process: Planning/Assessment -Prior to developing the educational intervention, a preliminary survey was conducted to identify specific guideline deviations in practice. Guidelines determined to be of particular concern were made the focus of the intervention. Intervention: Providers received patient-specific feedback on a sample of patients, and attended structured meetings to discuss guidelines and current management, identify problems, and propose solutions for improving patient care. ACEI +5% a , p>0.05 o n l y 12 Process: Planning/Assessment -Optimal intervention design was determined through literature review. Specific barriers to guideline adherence were identified by physicians during peer-review meetings as part of the intervention.

Intervention:
Physician assistants provided physicians with a practice-specific feedback report, identified areas needing improvement, and provided guidance and resources for improvement. Process: Access to information, training, and education -Pre-enrollment, internal medicine housestaff and primary care physicians in the network were presented an outline of the program; pocket cards with inclusion criteria and referral phone numbers were also provided for all nursing stations at the hospital.

Effectiveness of Implementation Interventions
A summary of study outcomes is presented in Table 3. A majority of studies (n=29, 83%) reported significant improvements in at least one primary outcome.
Prescription of indicated medications. Reminders, clinical pathways, changes in medical records systems, and multifaceted interventions were commonly associated with an increase in guideline-recommended prescriptions. In 4 studies that reported prescriptions of more than 1 indicated medication, significant improvements were observed in the prescription of β-blockers and MRAs, but not in the prescription of ACEIs. In these studies, the prescription rates at baseline for ACEIs were substantially higher than those of β-blockers or MRAs, ranging from Clinical pathways. Four of 5 studies on clinical pathways reported a significant increase in the percent of patients prescribed an indicated medication. [43][44][45][46] The single study that reported no reported no significant improvements. The RCT evaluating a clinical pathway [42] significantly increased patient self-care education, [42] and the RCT assessing a multifaceted intervention significantly increased the prescription of some target-dose medications. [31]

Clinical outcomes
While 5 of the 6 studies reporting all-cause mortality successfully improved process outcomes, only 2 reported a significant decrease in mortality: an RCT evaluating a clinical pathway [42] and a before-after study assessing a multifaceted transitional care intervention. [53] While all 6 studies reporting all-cause hospitalization or readmission rates improved process outcomes [30,37,40,43,43,44], significant improvements in the clinical outcomes were only  (Table 3) Six studies reported provision of preliminary training, education, and resources to introduce clinicians to the implementation intervention and encourage utilization; in each case interventions were effective in improving at least 1 process outcome. [ reporting of quality of care data. These contextual factors encouraged organizations to implement interventions to improve guideline adherence. This is in contrast to the lack of success observed when financial interventions were used as the implementation intervention itself.

DISCUSSION
In this systematic review, we assessed the effectiveness of implementation interventions aimed at improving physician adherence to Class I HF guideline recommendations. We synthesized our findings narratively as the variation in study design, intervention, and outcomes across studies precluded meta-analysis. We temper our discussion in accordance with the limitations of a narrative synthesis, to provide an overview of the current literature.
We found that a majority (83%) of 35 studies reported significant improvements in at least 1 process outcome. A process outcome commonly reported across studies and interventions was the proportion of patients prescribed an indicated medication. Electronic medical system interventions were associated with significant improvements in this outcome in 100% of studies The gap between process and clinical outcomes may also be explained by study designs that did not account for background trends or adjust for confounding variables. Finally, it is important to note that improvements in HF clinical outcomes are multifactorial and depend not only on the physician prescribing appropriate medications, but also on the patient's adherence to these medications, as well as follow-up care by other providers.
[30] The studies that showed a trend toward reduction in HF-related readmissions, albeit not significant, are those that addressed more than 1 of these factors. [38,40] Beyond the features of an implementation intervention, the process of its introduction and adaptation to the local setting is critical to its uptake and effectiveness. In particular, a planning period that assesses barriers at baseline and tailors the intervention based on provider feedback, Our findings are consistent with those of related reviews. For example, a review focusing on audit and feedback interventions found that they are largely ineffective unless providers also receive explicit instructions for improvement.  There were a number of limitations to our review. First, the variation in interventions, settings, study designs, and outcome measures precluded meta-analyses, and in turn, our ability to draw substantive conclusions regarding specific implementation strategies and their comparative effectiveness. We chose to use a "vote counting" approach to synthesis. While this method is useful in presenting an initial description of the trends found across studies, it is limited by the fact that it assigns equal weight to studies of varying sample sizes, effect sizes, and significance levels. [68] Another limitation was the methodological quality of the primary studies. Most studies used observational and quasi-experimental study designs. Quasi-experimental and observational designs possess some inherent risks of bias. In uncontrolled before-after studies, which formed the majority of studies in this review, temporal trends or sudden changes make it difficult to attribute the observed effects to the intervention alone. A time-series design increases confidence with which the observed effect can be attributed to the intervention; however, it does not protect against simultaneous events that may influence the intervention effect. Controlled before-after studies can protect against these effects, but cannot match groups on the basis of unknown confounders. We found that most quasi-experimental and observational studies possessed at least a medium risk of bias. Though almost all included RCTs demonstrated low risk of bias, they were largely applied in the evaluation of multidisciplinary team interventions, and less so to the evaluation of other implementation interventions.
A minority of studies in this review (9 of 35 studies) were RCTs, considered the gold standard in establishing a causal link between an intervention and its outcome. Indeed, RCTs are an uncommonly used methodology in implementation studies. In a recent systematic review of implementation interventions for the management of ICU delirium, only 1 of the 21 studies was

Suggestions for future studies
We identify a number of ways in which future research on the effectiveness of implementation interventions may be strengthened. First, there is a need for implementation interventions to be evaluated using more robust study designs that also account for the pragmatic challenges of implementation research. Furthermore, reporting of studies should adhere to standardized guidelines in order to better facilitate comparison between interventions. An example of reporting guidelines is the Quality Improvement Minimum Quality Criteria Set (QI-MQCS), which spans the spectrum of intervention characteristics and contextual factors. [75].
Implementation research in HF may also benefit from more careful consideration of the contextual factors that influence implementation success. Finally, in addition to examining process outcomes, the direct impact of implementation interventions on clinical outcomes should be examined more consistently.

CONCLUSIONS
In this review, the heterogeneity of interventions, study designs, and outcomes limited our ability to draw substantive conclusions regarding the comparative effectiveness of implementation interventions. Trends observed across the included studies suggest that effective implementation interventions include electronic medical records systems, clinical multidisciplinary teams, clinical pathways, and multifaceted interventions that include audit-and-feedback. There is a need for higher quality research to assess the effectiveness of implementation interventions on HF care processes and on clinical outcomes, and for the use standardized reporting guidelines.
Future work in the area should also include a closer examination of the organizational and external implementation context in order to better facilitate targeted application of implementation strategies.     10. 3 or 4 or 5 or 6 or 7 or 8 or 9 11. 1 or 2 12. 10 and 11 13. limit 12 to (english language and yr="1990 -Current") 4 Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale.

4-5
Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.

5-6
Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.

S1
Appendix, S2 Appendix Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).

5-6
Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.

6
Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.

6
Risk of bias in individual studies 12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.

10-11
Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations.
12-25 (Table 3) Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12).

Supp. Tables S3-S7
Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot.

36-38
Limitations 25 Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias).

38-40
Conclusions 26 Provide a general interpretation of the results in the context of other evidence, and implications for future research.

40-41
FUNDING interventions were most consistently successful in increasing physician uptake of guidelines.
Among RCTs (N=10), pharmacist and nurse-led interventions improved target dose prescriptions. Eleven studies reported clinical outcomes; significant improvements were reported in 3, including a clinical pathway, a multidisciplinary team, and a multifaceted intervention.
Baseline assessment of barriers, staff training, iterative intervention development, leadership commitment, and policy/financial incentives were associated with intervention effectiveness.
Most studies (N=20) had medium risk of bias; 9 RCTs had low risk of bias.

Conclusion:
Our study is limited by the quality and heterogeneity of the primary studies.
Clinical pathways, multidisciplinary teams, and multifaceted interventions appear to be most consistent in increasing guideline uptake. However, improvements in process outcomes were rarely accompanied by improvements in clinical outcomes. Our work highlights the need for improved research methodology to reliably assess the effectiveness of implementation interventions.

STRENGTHS AND LIMITATIONS
• While previous reviews have evaluated implementation interventions, to our knowledge, this review is the first to examine interventions to improve HF care, and to identify contextual factors associated with implementation success.
• We conducted an extensive search of 9 databases and include 38 studies spanning 9 implementation intervention categories.
• A major limitation of our review is that a majority of the studies (N=28) used observational or quasi-experimental designs, which are subject to bias and confounding.
Only 10 studies were RCTs.

INTRODUCTION
Heart Failure (HF) has a prevalence of approximately 10% in the elderly, and is a common cause of hospitalization and death in older adults. [ Accordingly, the primary objective of our review was to examine the effectiveness of implementation interventions in increasing physician adherence to the specified HF guideline recommendations. Our secondary objectives were to assess the effect of implementation interventions on clinical outcomes, and to identify process and contextual factors that influence implementation success.

METHODS AND ANALYSIS
The systematic review protocol is registered in the International Prospective Register of Systematic Reviews (PROSPERO: CRD42015017155), and published in a peer-reviewed journal.
[13] The only deviation from the protocol was the inclusion of uncontrolled before-after studies.

Eligibility criteria
We included trials evaluating 1 or more interventions aimed at improving physician adherence to Class I HF guidelines, relative to usual care. Interventions were categorized by level (i.e. provider-, organization-, systems-level) and type (i.e. education, decision-support, financial Outcomes While implementation interventions were targeted towards healthcare providers, outcomes were measured at the level of the patient (e.g. number of patients receiving guideline-appropriate care). Primary outcomes were process indicators, defined as measures that assess guidelineconsistent activities undertaken by a provider.
[14] The primary outcomes included the proportion of eligible HF patients who: were prescribed a guideline-recommended pharmacological treatment such as β-blockers, angiotensin-converting-enzyme inhibitors (ACEIs), angiotensin II receptor blockers (ARBs), or mineralocorticoid receptor antagonists (MRAs); were referred for implantable cardioverter defibrillator (ICD) and/or cardiac resynchronization therapy (CRT) consideration; were provided self-care education at discharge; and/or had their left ventricular ejection fraction (LVEF) quantified. Secondary outcomes were clinical outcomes such as HFrelated hospitalizations, readmissions and mortality. In the absence of HF-specific clinical outcomes, we extracted and reported all-cause clinical outcomes.

Study design
We included randomized controlled trials (RCTs), cohort studies (with comparisons), controlled and uncontrolled before and after studies, and interrupted time series studies.

Study selection
We

Quality (AHRQ) Evidence-based Practice Centers' Research Reports, and the University of York
Centre for Reviews and Dissemination Database. Our primary search strategy used the terms: heart failure, guideline adherence, practice guideline, evidence-based medicine, implement (Appendix 1). Our secondary search included terms for each of the different EPOC intervention types and heart failure (Appendix 2). Two authors independently screened titles and abstracts, and then assessed select full-text articles according to the eligibility criteria.

Data extraction and management
Two authors independently extracted details about study design, statistical analysis, intervention, patient and provider characteristics, follow-up, and outcomes using the EPOC Data Collection Checklist.
[9] In addition, the Process Redesign framework was used to extract and synthesize details on the intervention-development process, and relevant contextual factors. [15]

Assessment of risk of bias
In addition to identifying the limitations inherent within specific study designs, two authors independently applied design-specific criteria to assess the internal validity of studies retained for analysis. We used the criteria outlined in the EPOC Data Collection Checklist to evaluate 1 criterion was not satisfied, medium risk if 2 to 3 criteria were not satisfied, and high risk if more than 3 criteria were not satisfied.

Data synthesis
We classified the implementation interventions according to the level targeted (provider, organization, and system) and the type of intervention (e.g. education, decision-support, auditand-feedback, financial) using the EPOC Taxonomy.
[9] An abbreviated version of the EPOC Taxonomy is presented in Table 1. We explored the suitability of a meta-analysis of the results within each intervention category by first assessing clinical heterogeneity at face value on the basis of included patient populations, settings (inpatient/outpatient), intervention types, and outcome measures. We then assessed statistical heterogeneity using the I 2 statistic, defining substantial heterogeneity as I 2 >75%. For studies not suitable for meta-analysis, we narratively synthesized results. [19,20] We performed vote counting for each outcome measure in each EPOC intervention category, by noting the number of studies reporting significant improvements compared to those with no significant improvements. Financial reward or penalty for specific action by an institution or group of providers

Contextual factors
Context generally refers to the physical, social, political, and economic influences on healthcare practices. [21] We used the Process Redesign framework to systematically evaluate contextual factors that may influence the effectiveness of implementation interventions.
[15] The Process Redesign framework classifies context into categories: outer setting, inner setting, and characteristics of individuals and teams. The inner context refers to the structural characteristics of the clinical setting (e.g. inpatient, outpatient, community-based care, academic status), networks and communications, culture, and climate. The characteristics of individuals and teams more specifically refer to professional roles, responsibilities, and authority within the organization. The outer context refers to factors related to the broader social, political, and economic environment in which the intervention is applied. We considered processes that introduced and adapted the intervention to the organization as part of the intervention, rather than the context. An abbreviated and modified version of the framework is presented in Table 2.

Construct Description Process of Implementation (applied here as an intervention factor) Planning
Degree to which intervention steps are developed in advance of implementation and with consideration of various possible scenarios Assessing Formal assessment of the problem or condition to be changed, including needs of users, and barriers and facilitators of change Staging and iteration Whether the implementation is carried out in incremental steps, refined iteratively, or implemented in its entirety within a specified period Access to information, training, and education Staff access to information or education about the intervention Inner Setting (contextual factor) Team and network characteristics Influence, breadth, depth, and role diversity of teams and networks engaged in the Process Redesign Teams, networks, and communications Quality of teams and social networks; formal/informal communication and information exchange within an organization or between organizations Culture Norms, values, and beliefs within a team, unit, or practice that affect views of process redesign and its implementation Mandate Whether adherence to the intervention is expected or mandated Leadership commitment Degree of commitment, involvement, and accountability of leaders and managers to quality improvement and to the specific intervention Human factors Whether features of the physical and technical environment of the practice are designed to optimize human use, accessibility, and uptake in patient care Outer Setting (contextual factor) External networks Degree to which an organization is networked with other organizations engaged in similar types of process redesign activities External pressure Pressure emanating from outside the organization to introduce an intervention External policy and incentives/disincentives Laws, regulations, governmental recommendations, and/or payment schemes that affect the decision to adopt or abandon the process redesign efforts

Characteristics of Individuals and Teams (contextual factor) Role
Individual's or team's role and responsibilities, and the extent of multiple or shared roles Authority Perceived and actual degree of authority to make decisions and act autonomously

Identification, screening, and selection of studies
Our systematic search produced 3742 unique articles, of which 3590 were excluded on the basis of title and/or abstract review. We assessed 152 full-text articles, of which 38 studies met eligibility criteria. We excluded articles that: were abstracts, protocols, or letters (N=17); did not test implementation interventions (N=26); did not focus on HF patients (N=4); had no comparator group (N=6); or had no outcomes of interest (N=61) (see Figure 1).  (Table 3).  Intervention: Cardiologists presented guidelines and discussed cases with colleagues. Educational aids and guideline booklets were supplied to physicians.

Control: Usual care; no implementation intervention.
Process: Planning/Assessment -Prior to developing the educational intervention, a preliminary survey was conducted to identify specific guideline deviations in practice. Guidelines determined to be of particular concern were made the focus of the intervention.

Intervention:
Physician assistants provided physicians with a practice-specific feedback report, identified areas needing improvement, and provided guidance and resources for improvement.

Intervention:
Pharmacists were asked to invent methods to improve prescribing practices. Pharmacists received data on facility guideline adherence, along with a list of patients with suboptimal HF therapy.

Control:
Pharmacists were asked to invent methods to improve prescribing practices. Pharmacists received data on facility guideline adherence.

Intervention:
The intervention consisted of a guideline-based clinical decision support tool kit, educational materials, practice-specific data reports, benchmarked quality-of-care reports, and structured educational opportunities.

Effectiveness of Implementation Interventions
A summary of study outcomes is presented in Table 3. A majority of studies (n=32, 84%) reported significant improvements in at least one primary outcome.

Clinical outcomes
While 5 of the 6 studies reporting all-cause mortality successfully improved process outcomes, only 2 reported a significant decrease in mortality: an RCT evaluating a clinical pathway [46] and a before-after study assessing a multifaceted transitional care intervention. implement interventions to improve guideline adherence. This is in contrast to the lack of success observed when financial interventions were used as the implementation intervention itself.

DISCUSSION
In this systematic review, we assessed the effectiveness of implementation interventions aimed at improving physician adherence to Class I HF guideline recommendations. We synthesized our findings narratively as the variation in study design, intervention, and outcomes across studies precluded meta-analysis.
We found that a majority (84%) of 38 studies reported significant improvements in at least 1 process outcome. A process outcome commonly reported across studies and interventions was the proportion of patients prescribed an indicated medication: 12 studies reported on the prescription of ACEIs, [22,27,29,37,38,42,46, In general, improvements in process outcomes as a result of implementation interventions, were rarely accompanied by improvements in clinical outcomes. In some studies, the gap between process and clinical outcomes may be attributed to insufficient statistical power to detect improvements in clinical outcomes.[13,25,33] The gap may also be explained by study designs that did not account for background trends or adjust for confounding variables. Finally, HF clinical outcomes are multifactorial and depend not only on the physician prescribing appropriate medications, but also on the patient's adherence to these medications, and follow-up care by other providers.
[32] The studies that showed a trend toward reduction in HF-related readmissions, albeit not significant, are those that addressed more than 1 of these factors. [40,42] The context in which an implementation intervention is applied can influence its success. [61,66] The limited contextual details available in the included studies made it difficult to identify facilitators of implementation efforts. In general, support of organization leaders, and external policies and incentives for guideline adherence seemed to be associated with guideline uptake. Association's comprehensive Get With The Guidelines (GWTG)-HF program, which used a combination of educational approaches, multidisciplinary teams, and public hospital performance reporting to improve care. [73] The intervention was carefully adapted and introduced at each hospital site through collaborative discussions of barriers and solutions, and iterative plan-do-study-act (PDSA) cycles prior to the intervention phase. [74] There were a number of limitations to our review. First, the variation in interventions, settings, study designs, and outcome measures precluded meta-analyses, and in turn, our ability to draw substantive conclusions regarding specific implementation strategies and their comparative effectiveness. We chose to use a "vote counting" approach to synthesis. While this method is useful in presenting an initial description of the trends found across studies, it is limited by the fact that it assigns equal weight to studies of varying sample sizes, effect sizes, and significance levels. [75] Another were uncontrolled before-after or time-series studies. [77] While randomized trials are robust in methodology, they pose a number of logistical challenges that may make them suboptimal for

Suggestions for future studies
We identify a number of ways in which future research on the effectiveness of implementation interventions may be strengthened. First, there is a need for implementation interventions to be evaluated using more robust study designs that also account for the pragmatic challenges of implementation research. Furthermore, reporting of studies should adhere to standardized guidelines in order to better facilitate comparison between interventions. An example of reporting guidelines is the Quality Improvement Minimum Quality Criteria Set (QI-MQCS), which spans the spectrum of intervention characteristics and contextual factors. [82].

4-5
Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.

5-6
Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.

S1
Appendix, S2 Appendix Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis).

5-6
Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators.

6
Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made.

6
Risk of bias in individual studies 12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.

N/A
Additional analyses 16 Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified.

Study selection
17 Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram.

10
Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations.
12-25 (Table 3) Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome level assessment (see item 12).

Supp. Tables S3-S7
Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot. (Table 3) Synthesis of results 21 Present results of each meta-analysis done, including confidence intervals and measures of consistency.

11-26
28-31 (narr. synth) Risk of bias across studies 22 Present results of any assessment of risk of bias across studies (see Item 15).

N/A
Additional analysis 23 Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression [see Item 16]).

DISCUSSION
Summary of evidence 24 Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).

34-36
Limitations 25 Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias).