Comparative Effectiveness of Implementation Strategies for Blood Pressure Control in Hypertensive Patients

Hypertension is a major public health challenge because of its high prevalence and associated cardiovascular disease and premature death (1, 2). Randomized clinical trials have shown that pharmaceutical treatment and lifestyle modifications reduce blood pressure (BP) and risk for cardiovascular disease (3, 4). Despite the proven effectiveness of these interventions, only 13.8% of adults with hypertension and 37.1% of patients with treated hypertension worldwide had their BP controlled in 2010 (1). Barriers to hypertension control have been identified at the health care system, health care provider, and patient levels (5). Such barriers include limited health care resources, lack of performance standards, and limited reimbursement for health coaching at the system level; lack of adherence to clinical guidelines at the provider level; and lack of adherence to prescribed medications and lifestyle modifications at the patient level (5). Implementation strategies to overcome the barriers to BP control, such as home BP monitoring, health coaching, provider training, and team-based care, have been tested in randomized trials (6, 7). Most trials, however, have relatively small sample sizes and limited statistical power to reliably estimate intervention effects. Two previous reviews of implementation strategies for BP reduction included studies published up to 2003 and 2008 (6, 7). They showed that, compared with usual care, many implementation strategies, including team change and home BP monitoring, significantly improved BP control (6, 7). However, the effects of various implementation strategies on BP control were not directly compared in these meta-analyses. In addition, many implementation strategy trials have been published since 2008. In this meta-analysis, we aim to assess the comparative effectiveness of various implementation strategies on BP reduction in patients with hypertension by direct comparison. This information could be used by government and nongovernment organizations to select the most effective implementation strategies for hypertension control in communities. Methods We developed and followed a protocol for all steps of the review and meta-analysis (Supplement). Data Sources and Searches We searched MEDLINE and Embase from inception to 11 September 2017 with search terms hypertension and blood pressure and an extensive list of terms related to provider education, team-based care, patient education, provider feedback and guideline adherence, and home BP monitoring (Supplement Tables 1 and 2) (69). The search was restricted to clinical trials in human adults and had no language restrictions. Additional studies were identified by manual review of references cited in reviews, meta-analyses, and original articles. Finally, we searched ClinicalTrials.gov (September 2017), using the same terms as in the MEDLINE search, to find additional trials and assess publication bias by identifying completed trials without published results. Supplement. Supplementary Material Study Selection A study was eligible for inclusion if 1) it was a randomized controlled trial; 2) participants were adults with hypertension, defined as average systolic BP of at least 140 mm Hg, average diastolic BP of at least 90 mm Hg, or use of antihypertensive medication; 3) net change in systolic or diastolic BP was a main trial outcome; 4) the trial intervention targeted barriers to hypertension control at 1 or more of the patient, provider, and health care system levels; 5) the control group received usual care or minimal education; 6) the trial lasted at least 6 months; 7) variance of BP changes (or data to calculate it) was reported; and 8) clustering was accounted for in the analysis if the trial was cluster randomized. Two investigators independently screened abstracts for initial eligibility and reviewed full texts of eligible studies. Disagreements were resolved by consensus. Data Extraction and Quality Assessment Two investigators independently extracted data using a standardized form. Extracted data included study design, participant characteristics, intervention descriptions, and study results. Data from the 2 investigators were compared, and discrepancies were resolved by consensus. For trials reporting results at more than 1 time point, the report closest to the end of the intervention was selected. Trials were divided into 8 implementation strategy categories based on intervention descriptions (Table 1). Categories were created on the basis of prior literature and availability of trials meeting our inclusion criteria (6, 7). Two categories address only patient-level barriers to BP control: health coaching and home BP monitoring; 3 categories target only provider-level barriers: provider training, audit and feedback, and electronic decision-support systems; and 3 categories are multilevel strategies: multilevel strategies without team-based care, team-based care with physicians titrating medications, and team-based care with nonphysician providers titrating medications. Table 1. Descriptions of Implementation Strategy Categories* Health coaching strategies could be delivered in person or by telephone at several individual or group sessions during the intervention. The strategies were patient-centered, with a component of behavioral self-monitoring. A health coach (case manager, nurse, medical assistant, or community health worker) and patients worked together using self-discovery or active learning processes to improve medication adherence and lifestyle modification (10). Provider-level strategies aimed to improve the BP management performance of health care professionals primarily responsible for hypertensive patient care. Multilevel implementation strategies were aimed at overcoming barriers to hypertension control at 2 or more levels among patients, providers, health care systems, and communities. Team-based care was characterized by interprofessional collaboration, a patient-centered approach, and an integrated care process (12). In this meta-analysis, implementation strategies for team-based care involved task shifting or task sharing from primary care physicians to nurses, pharmacists, or community health workers. Team-based care was divided into 2 categories depending on whether the nonphysician provider could titrate medications. Multilevel strategies without team-based care included any intervention targeting more than 1 level of barriers to BP control but did not include team-based care, such as patient health coaching combined with provider training. Multicomponent strategies were those that combined more than 1 approach regardless of barrier level. We included trials if their control groups were either usual care or minimal education. Usual care was defined as hypertension management by patients' normal care providers with no trial intervention. Minimal education included the provision of educational materials or a brief educational session to either patients or providers. To assess quality, we modified the Cochrane Risk of Bias Tool to make it applicable to cluster trials in implementation research (13). We focused on the following domains: random sequence generation, objective outcome assessment (blinding of BP observers or use of automatic BP cuffs), incomplete outcome data, and selective outcome reporting. Participant recruitment bias was also considered for cluster randomized trials, and funding sources were recorded for all trials. Two reviewers independently assessed risk of bias at the trial level. Data Synthesis and Analysis The Supplemental Methods section of the Supplement describes the analysis and sample code in detail. For each trial, the net change in mean BP and associated SE were calculated from available data and defined as the difference (intervention minus control) in the changes of mean values (follow-up minus baseline). If BP was measured at several time points during follow-up, the measurements taken closest to the end of the intervention were used. In addition, the changes in mean BP and associated SEs in each randomized group were calculated separately for comparing effects among implementation strategies. Random-effects models using the SidikJonkman residual heterogeneity estimator with the KnappHartung small-sample adjustment were used to calculate pooled mean differences within implementation categories using inverse variance weighting (1416). In some trials, several intervention groups were compared with the same reference group. In these cases, robust variance estimation was used to account for nonindependent estimates (17). Heterogeneity was evaluated using the Cochran Q test and quantified with the I 2 index, and the 95% CI was calculated using the test-based method (18). Publication bias was assessed using the Begg rank correlation test and the Egger weighted linear regression test for implementation strategies with at least 10 studies because of low statistical power with small sample sizes. When possible publication bias was observed, the trim-and-fill method was used to estimate the number of missing studies not published, augment the data to make the funnel plot more symmetrical, and calculate a summary estimate based on the augmented data (19). Generalized estimating equations (with an exchangeable correlation matrix between estimates within a study) were used to compare BP reductions associated with each implementation strategy after important covariate adjustment and for pairwise comparisons between implementation strategies. Indicator variables were used for each implementation strategy category, with the common control group as the reference. Weights for these models were exported from a random-effects meta-analysis, including all changes in mean BP and associated SEs from all treatment groups. As such, these weights take into account within- and between-trial variance. Each trial was treated as a cluster to maintain randomized comparisons, and the following trial-leve