PURPOSE: This study was a systematic review with a quantitative synthesis of the literature examining the overall effect size of practice facilitation and possible moderating factors. The primary outcome was the change in evidence-based practice behavior calculated as a standardized mean difference. METHODS: In this systematic review, we searched 4 electronic databases and the reference lists of published literature reviews to find practice facilitation studies that identified evidence-based guideline implementation within primary care practices as the outcome. We included randomized and nonrandomized controlled trials and prospective cohort studies published from 1966 to December 2010 in English language only peer-reviewed journals. Reviews of each study were conducted and assessed for quality; data were abstracted, and standardized mean difference estimates and 95% confidence intervals (CIs) were calculated using a random-effects model. Publication bias, influence, subgroup, and meta-regression analyses were also conducted. RESULTS: Twenty-three studies contributed to the analysis for a total of 1,398 participating practices: 697 practice facilitation intervention and 701 control group practices. The degree of variability between studies was consistent with what would be expected to occur by chance alone (I2 = 20%). An overall effect size of 0.56 (95% CI, 0.43-0.68) favored practice facilitation (z = 8.76; P <.001), and publication bias was evident. Primary care practices are 2.76 (95% CI, 2.18-3.43) times more likely to adopt evidence-based guidelines through practice facilitation. Meta-regression analysis indicated that tailoring (P = .05), the intensity of the intervention (P = .03), and the number of intervention practices per facilitator (P = .004) modified evidence-based guideline adoption. CONCLUSION: Practice facilitation has a moderately robust effect on evidence-based guideline adoption within primary care. Implementation fidelity factors, such as tailoring, the number of practices per facilitator, and the intensity of the intervention, have important resource implications.
PURPOSE: This study was a systematic review with a quantitative synthesis of the literature examining the overall effect size of practice facilitation and possible moderating factors. The primary outcome was the change in evidence-based practice behavior calculated as a standardized mean difference. METHODS: In this systematic review, we searched 4 electronic databases and the reference lists of published literature reviews to find practice facilitation studies that identified evidence-based guideline implementation within primary care practices as the outcome. We included randomized and nonrandomized controlled trials and prospective cohort studies published from 1966 to December 2010 in English language only peer-reviewed journals. Reviews of each study were conducted and assessed for quality; data were abstracted, and standardized mean difference estimates and 95% confidence intervals (CIs) were calculated using a random-effects model. Publication bias, influence, subgroup, and meta-regression analyses were also conducted. RESULTS: Twenty-three studies contributed to the analysis for a total of 1,398 participating practices: 697 practice facilitation intervention and 701 control group practices. The degree of variability between studies was consistent with what would be expected to occur by chance alone (I2 = 20%). An overall effect size of 0.56 (95% CI, 0.43-0.68) favored practice facilitation (z = 8.76; P <.001), and publication bias was evident. Primary care practices are 2.76 (95% CI, 2.18-3.43) times more likely to adopt evidence-based guidelines through practice facilitation. Meta-regression analysis indicated that tailoring (P = .05), the intensity of the intervention (P = .03), and the number of intervention practices per facilitator (P = .004) modified evidence-based guideline adoption. CONCLUSION: Practice facilitation has a moderately robust effect on evidence-based guideline adoption within primary care. Implementation fidelity factors, such as tailoring, the number of practices per facilitator, and the intensity of the intervention, have important resource implications.
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