Technical Review

Number 9 

Closing the Quality Gap: 

A Critical Analysis of 

Quality Improvement Strategies 

Volume 3—Hypertension Care 

Prepared for: 

Agency for Healthcare Research and Quality 

U.S. Department of Health and Human Services 

540 Gaither Road 

Rockville, MD 20850 

www.ahrq.gov 

Contract No. 290-02-0017 

Prepared by: 

Stanford University–UCSF Evidence-based Practice Center 

Series Editors Investigators 

Kaveh G. Shojania, M.D. Judith Walsh, M.D. 

Kathryn M. McDonald, M.M. Vandana Sundaram, M.P.H. 

Robert M. Wachter, M.D. Smita Nayak, M.D. 

Douglas K. Owens, M.D., M.S. Sheryl Davies, M.A. 

Robyn Lewis, M.A. 

Managing Editor Jody Mechanic, R.N. 

Amy J. Markowitz, J.D. Christopher Sharp, M.D. 

Melinda Henne, M.D. 

Bimal Shah, M.D. 

Jo Kay Chan, B.S. 

Mary Kane Goldstein, M.D. 

AHRQ Publication No. 04-0051-3 

January 2005 
This document is in the public domain and may be used and reprinted without permission except 

those copyrighted materials noted for which further reproduction is prohibited without the 

specific permission of copyright holders. 

Suggested Citation: 

Walsh J, McDonald KM, Shojania KG, Sundaram V, Nayak S, Davies S, Lewis R, Mechanic J, 

Sharp C, Henne M, Shah B, Chan JK, Owens DK, Goldstein MK. Hypertension Care. Vol. 3 of: 

Shojania KG, McDonald KM, Wachter RM, Owens DK, editors. Closing The Quality Gap: A 

Critical Analysis of Quality Improvement Strategies. Technical Review 9. (Prepared by the 

Stanford University–UCSF Evidence-based Practice Center, under Contract No. 290-02-0017). 

AHRQ Publication No. 04-0051-3. Rockville, MD: Agency for Healthcare Research and 

Quality. January 2005. 

ii
Preface 

The Agency for Healthcare Research and Quality (AHRQ), through its Evidence-Based Practice 

Centers (EPCs), sponsors the development of evidence reports and technology assessments to 

assist public- and private-sector organizations in their efforts to improve the quality of health 

care in the United States. The reports and assessments provide organizations with 

comprehensive, science-based information on common, costly medical conditions and new 

health care technologies. The EPCs systematically review the relevant scientific literature on 

topics assigned to them by AHRQ and conduct additional analyses when appropriate prior to 

developing their reports and assessments. 

To bring the broadest range of experts into the development of evidence reports and health 

technology assessments, AHRQ encourages the EPCs to form partnerships and enter into 

collaborations with other medical and research organizations. The EPCs work with these partner 

organizations to ensure that the evidence reports and technology assessments they produce will 

become building blocks for health care quality improvement projects throughout the Nation. The 

reports undergo peer review prior to their release. 

AHRQ expects that the EPC evidence reports and technology assessments will inform 

individual health plans, providers, and purchasers as well as the health care system as a whole by 

providing important information to help improve health care quality. 

We welcome written comments on this evidence report. They may be sent to the Task Order 

Officer named below at: Agency for Healthcare Research and Quality, 540 Gaither Road, 

Rockville, MD 20850, or by e-mail to epc@ahrq.gov. 

Carolyn M. Clancy, M.D. Jean R. Slutsky, P.A., M.S.P.H. 

Director Director, Center for Outcomes and Evidence 

Agency for Healthcare Research and Quality Agency for Healthcare Research and Quality 

Kenneth S. Fink, M.D., M.G.A., M.P.H. Marian D. James, M.A., Ph.D. 

Director, EPC Program EPC Program Task Order Officer 

Agency for Healthcare Research and Quality Agency for Healthcare Research and Quality 

The authors of this report are responsible for its content. Statements in the report 

should not be construed as endorsement by the Agency for Healthcare Research and 

Quality or the U.S. Department of Health and Human Services of a particular drug, 

device, test, treatment, or other clinical service. 

iii
iv
Structured Abstract 

Objective: Hypertension affects more than 50 million people in the United States alone. Despite 

clear evidence regarding the beneficial effects of quality treatment for high blood pressure, many 

millions of diagnosed and undiagnosed hypertensives are not receiving the optimal standard of 

care. The difference in patient outcomes achieved with present hypertension treatment methods 

and those thought to be possible using best practice treatment methods is known as a quality gap, 

and such gaps are at least partly responsible for the loss of thousands of lives each year. This 

review was organized to bring a systematic assessment of different quality improvement (QI) 

strategies and their effects to the process of identifying and managing hypertension. 

Search Strategy and Inclusion Criteria: Investigators searched the MEDLINE® database, the 

Cochrane Collaboration’s Effective Practice and Organisation of Care (EPOC) registry, article 

bibliographies, and relevant journals for experimental evaluations of QI interventions aimed at 

improving hypertension screening and management of non-pregnant adults with primary 

hypertension. The reviewers included randomized or quasi-randomized controlled trials, 

controlled before–after studies, and interrupted time series in which at least one reported 

outcome measure included changes in blood pressure, or provider or patient adherence to a 

recommended process of care. 

Data Collection and Analysis: Relevant data were abstracted independently by two reviewers. 

Each QI intervention was classified into one or more of the following components: provider 

education, provider reminders, facilitated relay of clinical information, patient education, 

promotion of self-management, patient reminders, audit and feedback, organizational change, or 

financial incentives. Certain categories were further subdivided into major subtypes (e.g., 

professional meetings for provider education and disease management for organizational 

change). The researchers also evaluated the impact of clinical information systems as a mediator 

for interventions of all types. They compared the different QI strategies in terms of the median 

effects achieved for blood pressure control and for a generalized measure of provider or patient 

adherence. 

Main Results: Sixty-three articles reporting a total of 82 comparisons met the inclusion criteria. 

Studies of hypertension identification were found to be too heterogeneous for quantitative 

analysis. The majority of screening studies were clinic-based (with a few offered at work sites), 

and the most common strategies involved patient and/or provider reminders. These generally 

showed positive results; several studies found that patients were more likely to know their blood 

pressure or attend clinic visits after receiving reminders. Across all studies with a variety of 

strategies, the median reductions in systolic blood pressure (SBP) and diastolic blood pressure 

(DBP) were 4.5 mmHg (interquartile range: 1.5, 11.0) and 2.1 mmHg (interquartile range: -0.2, 

5.0), respectively. The median increase in the proportion of patients in the target SBP range and 

target DBP range was 16.2 percent (interquartile range: 10.3, 32.2), and 6.0 percent (interquartile 

range: 1.5, 17.5), respectively. Studies that focused on improving provider adherence showed a 

range of median reduction of 1.3 percent to a median improvement of 3.3 percent across all QI 

strategies. Overall, patient adherence showed a median improvement of 2.8 percent (interquartile 

range: 1.9, 3.0). 

Conclusion: The findings of this review suggest that QI strategies appear, in general, to be 

associated with the improved identification and control of hypertension. It is not possible to 

v 
discern with complete confidence which specific QI strategies have the greatest effects, since 

most of the studies included more than one QI strategy. All of the assessed strategies may be 

beneficial under some circumstances, and in varying combinations. There may be other useful 

strategies that have not been studied in trials meeting the inclusion criteria for evidence-based 

review; it is not possible to draw conclusions about these strategies.

vi
Contents

Summary ........................................................................................................................................1 

Chapter 1. Introduction ..................................................................................................................9

 Background ..............................................................................................................................9 

 The Quality Gap .......................................................................................................................10 

Evidence-based Guidelines and Quality of Care Measures .....................................................11 

 Guidelines ..........................................................................................................................11 

Quality of Care Measures ..................................................................................................12

 Key Questions ....................................................................................................................13 

Chapter 2. Methods ........................................................................................................................15 

Types of Quality Improvement Strategies ...............................................................................15 

 Scope ........................................................................................................................................ 17 

Literature Search and Review Process .....................................................................................18 

Terminology to Distinguish Studies, Interventions, and Comparisons ...................................18 

 Outcome Measures ...................................................................................................................19 

Measures of Disease Identification and Initial Follow-up .................................................19 

Measures of Disease Control .............................................................................................19 

Measures of Provider Adherence .......................................................................................20 

Measures of Patient Adherence .........................................................................................20 

 Other Outcome Measures ..................................................................................................20 

 Analysis ....................................................................................................................................20 

 Median Effects Calculations ..............................................................................................21 

Study Sample Size and Publication Bias ...........................................................................21 

 Study Design Quality .........................................................................................................22 

 Statistical Analyses ............................................................................................................22 

Chapter 3. Results ..........................................................................................................................23 

Search Yield and Results of Literature Review Process ..........................................................23 

Analysis by Outcome Measures ...............................................................................................23

Effect of Quality Improvement Strategies on Disease Identification and Initial Followup 

 Measures ......................................................................................................................23 

Effect of Quality Improvement Strategies on Measures of Disease Control .....................25 

Effect of Quality Improvement Strategies on Blood Pressure Control ..............................26 

Effect of Quality Improvement Strategies on Provider Adherence ...................................27 

Effect of Quality Improvement on Patient Adherence ......................................................27 

Analysis By Type of Quality Improvement Strategy ..............................................................27 

 Provider Reminders ...........................................................................................................27 

 Facilitated Relay of Clinical Data ......................................................................................28 

 Audit and Feedback ...........................................................................................................28 

 Provider Education .............................................................................................................29 

 Patient Education ...............................................................................................................29 

 Promotion of Self-management .........................................................................................30 

 Patient Reminders ..............................................................................................................30 

vii
 Organizational Change .......................................................................................................30

 Substrategies of Organizational Change ............................................................................31 

 Financial Incentives ...........................................................................................................31 

 Other Analyses .........................................................................................................................31 

 Clinical Information Systems ............................................................................................31 

Analysis of Number of Quality Improvement Strategies on Outcomes ............................32 

Effect of Methodological Features ...........................................................................................33 

Effect of Methodological Features on Blood Pressure Outcomes .....................................33 

Effect of Methodological Features on Provider and Patient Adherence to 

 Recommendations ........................................................................................................34 

Effect of Study Size on Blood Pressure Outcomes ............................................................34 

Chapter 4. Discussion ....................................................................................................................37 

Which QI Strategies Improve Screening for Hypertension? ...................................................37 

Which QI Strategies are Most Effective at Ensuring that Blood Pressure Goals are 

 Achieved and Maintained? ................................................................................................38 

Effect of Specific QI Strategies on Achieving and Maintaining BP Goals .............................38 

Which QI Strategies Improve Provider Adherence with Recommendations for 

 Management of Hypertension? ..........................................................................................40 

Which QI Strategies Improve Patient Adherence with Treatment? .........................................41 

Importance of Organizational Setting for Quality Improvement Interventions .......................41 

 Study Design Effects ..........................................................................................................42 

 Effect of Number of QI Strategies .....................................................................................42 

 Additional Comments ........................................................................................................42 

Limitations of Interpretation of the Data ...........................................................................44 

Recommendations for Future Research on Quality Improvement Implementations .........44 

Chapter 5. Conclusions...................................................................................................................47 

References ......................................................................................................................................49 

Figures

Figure 1. Search strategy and article triage ....................................................................................59 

Tables 

Table 1. Included studies ...............................................................................................................61 

Table 2a. Quality improvement strategies .....................................................................................66 

Table 2b. Quality improvement sub-strategies ..............................................................................67 

Table 3. Number of different quality improvement strategies included in articles .......................68 

Table 4. Quality improvement strategy combinations ...................................................................69 

Table 5. Screening studies .............................................................................................................71 

Table 6a. Effect of quality improvement strategies on blood pressure outcomes .........................76 

Table 6b. Effect of quality improvement strategies on summary adherence outcomes ................78 

Table 7a. Effect of number of quality improvement strategies on blood pressure outcomes ........79 

viii
Table 7b. Effect of number of quality improvement strategies on summary 

adherence outcomes .................................................................................................................80 

Table 8a. Effect of specific quality improvement sub-strategies on blood 

pressure outcomes ....................................................................................................................81 

Table 8b. Effect of specific quality improvement sub-strategies on summary 

adherence outcomes .................................................................................................................82 

Table 9a. Effect of information systems on blood pressure outcomes ..........................................83 

Table 9b. Effect of information systems on summary adherence outcomes .................................84 

Table 10a. Association of methodologic features with decreased blood pressures .......................85 

Table 10b. Association of methodologic features with increased percentage of 

patients in blood pressure target range .....................................................................................86

Table 10c. Association of methodologic features with summary adherence outcomes ................87 

Table 11. Comparison of study design by quality improvement strategy on 

blood pressure outcomes ..........................................................................................................88 

Table 12a. Association of study size with systolic blood pressure outcomes ...............................90 

Table 12b. Association of study size with diastolic blood pressure outcomes ..............................92 

Appendixes 

Appendix A. Medline search for hypertension QI articles 

Appendix B. Hypertension abstraction forms for screening and full-text review 

Appendix C. Articles excluded at the level of full-text review (Stage 3) 

Appendix D. Additional outcomes measures reported in studies reviewed

Appendix E. Articles meeting all inclusion criteria except that intervention exclusively involved 

patient education or promotion of self-management 

Appendix F. Interventions, reported outcomes and main results for each included study 

Appendix G. Median effect for all outcomes 

Appendix H. Calculation of effective sample sizes for trial with clustering

Appendix I. Blood pressure (BP) versus percent of patients achieving BP in target range 

Appendixes and Evidence Tables for this report are provided electronically at 

http://www.ahrq.gov/clinic/tp/hypergap3tp.htm. 

ix
x 
Summary

Introduction 

In early 2003, the Institute of Medicine (IOM) released its report, Priority Areas for National 

Action: Transforming Health Care Quality. The report listed 20 clinical topics for which “best 

practices” were strongly supported by clinical evidence. The report—along with other 

literature—clearly documents the disappointingly low rates at which these practices have been 

implemented in the United States, at an annual cost of many thousands of lives. 

To bring data to bear on the quality improvement opportunities articulated in the IOM’s 2003 

report, the Agency for Healthcare Research and Quality (AHRQ) engaged the Stanford-UCSF 

Evidence-based Practice Center (EPC) to perform a critical analysis of the existing literature on 

quality improvement strategies for a selection of the 20 disease and practice priorities noted in 

the IOM Report. Rather than concentrating on the specific clinical practices that appear to 

improve health outcomes, the focus of this review is on translating research into practice—

identifying those activities that increase the rate at which practices regarded as effective are 

applied to patient care in real world settings. In other words, the authors aim to narrow the 

“quality gap” that is in large part responsible for suboptimal health care practices and outcomes. 

This report focuses on the clinical problem of hypertension. It, like the other reports in the 

series, aims to help readers assess whether the evidence suggests that a quality improvement 

strategy would work in their specific practice or with their specific patient population. The 

question of whether these may be crosscutting practices—that is, the manner in which those that 

have been studied for specific conditions such as hypertension might be applicable to others, 

such as asthma—remains to be seen. We will further address these practices in subsequent 

volumes, as we review the evidence for many of the other conditions highlighted in the 2003 

IOM report.

We defined the quality gap as the difference between health care processes or outcomes 

observed in practice, and those potentially obtainable on the basis of current professional 

knowledge. We defined a quality improvement (QI) strategy as an intervention aimed at reducing 

the quality gap for a group of patients representative of those encountered in routine practice. 

Finally, a quality improvement target is an outcome, process, or structure that the QI strategy 

aims to influence, with the goal of reducing the quality gap. Examples of targets relevant to this 

volume include outcomes such as reductions in blood pressure, or processes such as improved 

provider adherence with medication choices in patients with hypertension. Nine types of QI 

strategies were considered; they are shown (with examples) in Table 1. 

1
Table 1. Taxonomy of QI strategies with examples of substrategies

QI strategy Examples 

Provider reminder systems • Reminders in charts for providers 

• Computer-based reminders for providers 

• Computer-based decision support 

Facilitated relay of clinical data to providers • Transmission of clinical data from outpatient 

specialty clinic to primary care provider by means 

other than medical record, e.g., phone call or fax 

Audit and feedback • Feedback of performance to individual providers 

• Quality indicators and reports

• National/state quality report cards 

• Publicly released performance data 

• Benchmarking – provision of outcomes data from top 

performers for comparison with provider’s own 

data 

Provider education • Workshops and conferences 

• Educational outreach visits (e.g., academic detailing) 

• Distribution of educational materials 

Patient education • Classes 

• Parent and family education

• Patient pamphlets 

• Intensive education strategies promoting selfmanagement of chronic conditions 

Promotion of self-management • Materials and devices to promote self-management 

Patient reminder systems • Postcards or calls to patients

Organizational change • Case Management, Disease Management 

• Total Quality Management, Cycles of Quality 

Improvement 

• Multidisciplinary teams 

• Change from paper to computer-based records 

• Increased staffing 

• Skill mix changes 

Financial incentives, regulation, and policy Provider Directed:

• Financial incentives based on achievement of 

performance goals 

• Alternative reimbursement systems (e.g., fee-forservice, capitated payments) 

• Licensure requirements 

Patient Directed: 

• Co-payments for certain visit types 

• Health insurance premiums, user fees 

Health System Directed: 

• Initiatives by accreditation bodies (e.g., residency 

work hour limits) 

• Changes in reimbursement schemes (e.g., 

capitation, prospective payment, salaried

providers) 

2
Methodology 

Our review involved an exhaustive search strategy of the Medline, Cochrane (including, 

quite importantly, the Cochrane Effective Practice and Organisation of Care (EPOC) Review 

Group registry), and other relevant databases, as well as hand searches of articles and 

bibliographies. We employed standard inclusion/exclusion criteria, definitions and protocols; rereview of exclusion decisions by study personnel, and independent abstractions by two 

reviewers, with conflicts resolved by consensus. In assessing the quality of a given study, we 

used a hierarchy of design (Level 1 studies were randomized controlled trials, Level 2 were 

controlled before–after studies, interrupted time series, and quasi randomized trials, and so on), 

and used the highest quality evidence available to assess the value of each QI strategy. We 

acknowledge that much of the important work in quality improvement is performed “in the 

trenches,” by front-line workers taking advantage of available resources to answer important, 

practical questions using simple designs (e.g., uncontrolled before–after studies). However, in a 

report of this type, we felt it important to strive to find and analyze studies whose research 

methodologies were likeliest to give scientifically correct answers. In analyzing our results, we 

performed quantitative analysis (including the calculation of summary effects, adjustment for 

unit of analysis errors, and meta-regression analysis) when enough studies with similar outcomes 

were available, and studies were sufficiently homogeneous in both design and population.

Hypertension has been defined as systolic blood pressure (SBP) greater than 140 mmHg and 

diastolic blood pressure (DBP) greater than 90 mmHg ( > 140/90), with normal blood pressure 

set at < 120/80. It is estimated that 58.4 million Americans have hypertension, making it the 

most common primary diagnosis in the United States. Hypertension is a major risk factor for 

cardiovascular disease, and high quality evidence (codified in the periodic reports of the Joint 

National Committee on Detection, Evaluation, and Treatment of High Blood Pressure (JNC)) 

supports the premise that treatment of hypertension, most commonly with drug therapy, reduces 

such risks. Even small reductions can have profound effects: a 1990 meta-analysis of 14 

randomized treatment trials found that lowering DBP 5–6 mmHg reduced stroke rates by 42 

percent. The recently issued JNC 7 has emphasized the efficacy of diuretics, recommending 

them as initial therapy for most patients, either alone or in combination with one of the other 

classes of agents (ACE inhibitors, angiotensin receptor antagonists, β-adrenergic receptor 

antagonists, calcium channel antagonists) demonstrated to be beneficial in randomized trials. 

Despite this extraordinary clinical knowledge base and the link between treatment and 

outcomes, there is a profound quality gap in the management of hypertension. In the U.S. in 

1999-2000, 69 percent of people with hypertension were aware of their condition, but only 58 

percent of hypertensives were receiving treatment. Moreover, it is estimated that only 31 percent 

of known hypertensives in the United States have well-controlled blood pressure. Among the 

possible reasons for this gap are the asymptomatic nature of hypertension, the necessity of 

lifelong management for most patients, the frequently changing therapeutic recommendations, 

and the importance of individualizing and titrating treatment. 

We focused on the quality gap in patients with primary hypertension (also called “essential” 

hypertension) in non-pregnant adults. This population makes up more than 90 percent of all 

patients with hypertension. Our quality improvement targets were primarily measures of blood 

pressure screening (i.e., strategies to increase the percentage of patients with high blood pressure 

who are aware of their condition) and control (i.e., fraction of patients with known hypertension 

whose blood pressure is within the range recommended by the JNC and others). We captured 

outcome measures (such as mortality) when they were reported, but they usually were not. We

3
also considered measures of both provider (e.g., adherence to specific medication 

recommendations) and patient (e.g., attending followup appointment) adherence to 

recommendations. 

From our original sample of 3,071 potentially relevant articles, a total of 359 merited full-text 

review. Of these, 110 merited full abstraction. After excluding those consisting solely of a 

patient education strategy (to be reviewed separately in a subsequent volume in the Series), our 

sample consisted of 63 articles reporting a total of 82 comparisons of QI intervention to a control 

group. 

Findings 

Studies of hypertension identification and initial followup were too heterogeneous to be 

analyzed quantitatively. The majority were clinic-based (though a few were offered at work 

sites), and the most common strategies were patient and/or provider reminders. They generally 

showed positive results; several studies found that patients were more likely to know their blood 

pressure or attend clinic visits after receiving reminders. Frequently used strategies included 

patient reminder letters, computer identification of patients with historically poor follow-up (with 

computer-generated reminders to these patients), and the addition of a health promotion nurse to 

identify and followup with high-risk patients. 

The evidence-base behind QI strategies designed to improve blood pressure control was more 

robust, and its results were generally positive. Across all studies (of a variety of strategies), the 

median reduction in SBP was 4.5 mmHg (IQ range: 1.5, 11.0), and median reduction in DBP 

was 2.1 mmHg (IQ range: -0.2, 5.0). Overall, the median increase in the proportion of patients in 

target SBP range and target DBP range in these comparisons was 16.2 percent (IQ range: 10.3, 

32.2), and 6.0 percent (IQ range: 1.5, 17.5), respectively. Note that the QI strategies had a 

somewhat larger effect on SBP than on DBP; the latter was previously considered the more 

important target, but recent research has confirmed the importance of treating systolic 

hypertension. 

Our findings suggest that quality improvement strategies, in general, appear to be associated 

with improved detection and control of hypertension. Since most studies included more than one 

QI strategy (although, unlike in diabetes, multiple interventions did not appear to be associated 

with greater effect sizes in hypertension), it is not possible to discern with complete confidence 

which QI strategies have the greatest effects. All of the strategies assessed--organizational 

change, patient education in combination with several other QI strategies, provider education, 

facilitated relay of clinical data, audit and feedback, promotion of self-management, provider 

reminders, patient reminders, and financial incentives--may be beneficial under some

circumstances, and in varying combinations. Studies that involved organizational change

appeared to have the largest effects on outcomes, although there were some methodologic 

concerns about confounding due to study size. Organizational change may work, at times, 

because the change meshes well with existing structures and resources in a given institution; the 

applicability of these changes to other settings may be limited. Moreover, a given organizational 

change (i.e., the hiring of a nonphysician provider to contact patients) may simply be a marker 

for high levels of administrative support or funding, further limiting the applicability of the 

change itself to other settings. 

Like organizational change, studies including patient education as part of the QI strategy also 

appeared to have relatively large effects, but unfortunately these results also are confounded by 

study size. 

4
Studies that focused on improving provider adherence with recommendations for the 

management of hypertension had less effect (median effects ranged from a 1.3 percent reduction 

to 3.3 percent improvement in adherence across the QI strategies). There are probably several 

reasons for this limited impact, including past controversies in the medical literature over 

treatment goals and therapeutic options, rapidly changing recommendations (best evidenced by a 

new JNC report every few years), practice “inertia,” and environmental influences such as time 

pressures, incentive structures, and resource constraints. 

Conclusions 

Despite the importance and prevalence of both diabetes and hypertension, and the richness of 

their clinical literatures, studies that would help patients, providers, and policymakers choose 

how best to close their quality gaps are somewhat confusing. For each entity, certain strategies 

(such as the use of multifaceted interventions, and perhaps disease management in diabetes, and 

the adoption of organizational change in hypertension) appear to be more effective than others. 

Yet, even in these areas, problems with publication bias, co-interventions, and secular trends 

make sweeping conclusions hazardous. Our review provides a huge collection of research data 

for the interested reader to dissect; undoubtedly, there is information that will be directly 

applicable to a given clinical situation or location. At the synthesis level, however, the most 

striking finding from these systematic reviews is the need for additional, high quality research to 

clarify how best to translate research into practice for these common, highly morbid disorders. 

5
6
Technical Review 
8
Chapter 1. Introduction 

Background 

The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation 

and Treatment of High Blood Pressure (JNC 7), issued in 2003, defines hypertension as a 

systolic blood pressure (SBP) greater than 140 mmHg and diastolic blood pressure (DBP) greater 

than 90 mmHg ( > 140/90), compared with a normal blood pressure of < 120/80. This revised 

threshold represents a marked departure from the former standard for hypertension ( < 140/90).1

A new category—“pre-hypertension”—also was established for patients with a SBP of 120 to139 

mmHg, or a DBP of 80 to 89 mmHg. Hypertension often exhibits no clinical manifestations until 

the onset of organ damage, therefore screening, early detection, and proper disease control are 

critical to good health. The World Health Organization (WHO) credits hypertension with one in 

every eight deaths, making it the third leading cause of death worldwide,2

 and has described high 

blood pressure as “...the most important public health problem in developed countries.”3

 In the 

United States, 28.7 percent of participants in the 1999–2000 National Health and Nutrition 

Examination Survey (NHANES) conducted by the National Center for Health Statistics were 

identified as hypertensive, either because they had elevated blood pressure, or because they were 

being treated with antihypertensive medications. Extrapolating from these findings, it is 

estimated that 58.4 million Americans have the condition. Hypertension is the most common 

primary diagnosis in the United States, and was the principal diagnosis for 35 million office 

visits during 2001.4

 

Hypertension is a major risk factor for cardiovascular disease,5-7

 including coronary heart 

disease (CHD), heart failure, and stroke. The benefits of treating hypertension have been 

established for many years, and treatment standards have evolved continually. A 1990 metaanalysis of 14 randomized treatment trials of hypertensive patients showed that a 5–6 mmHg 

reduction in DBP could translate to a 42 percent reduction in stroke occurances.8 A 1990 

epidemiologic review reported that a lower blood pressure should confer a lower risk of vascular 

disease.9

 Other major trials reported a significant overall decrease in cardiac events following 

treatment for hypertension, including the Systolic Hypertension in the Elderly Program (SHEP) 

(a 27 percent reduction),10 the Swedish Trial in Older Patients with Hypertension (STOP) (a 13 

percent reduction),

11 and the Medical Research Council study (MRC) (a 19 percent reduction).12

While exact projections are difficult to establish, data from the Framingham Heart Study and 

the NHANES II indicate that even small improvements in blood pressure control can have a 

major impact on public health. Lowering the DBP by only 2 mmHg could result in a 6 percent 

reduction in the risk of coronary heart disease, and a 15 percent reduction in the risk of stroke 

and transient ischemic attacks.

13 Moreover, in individuals with a SBP of 140–159 mmHg and/or 

a DBP of 90–99 mmHg, a sustained 12 mm reduction in SBP for a period of 10 years has been 

estimated to prevent one death among every 11 patients treated.1

 

Important advances in hypertension care have occurred in the last ten to fifteen years. 

Previously, hypertension was generally treated only when the DBP exceeded 90 mmHg. But the 

1991 publication of the SHEP study confirmed the benefits of treating isolated systolic 

hypertension.10 More recently, pooled individual data from 61 separate prospective studies 

confirmed the risks associated with an elevated SBP: for individuals aged 40–69, each increase 

of 20 mmHg of SBP (or 10 mmHg DBP) was associated with a two-fold increase in mortality 

9
from both CHD and stroke.14 SBP is a robust indicator of risk of cardiovascular disease in the 

population at large. It is also a stronger predictor of risk than DBP, in those older than age 50.15 

Current guidelines call for treating isolated systolic hypertension according to the same 

principles used in the general care of hypertension.1 The therapeutic focus now is on achieving 

the SBP target goal, as most patients then will reach the DBP goal.1

 Lifestyle modifications and 

drug therapy are recommended for all patients with blood pressures above the normal range. 

The prevalence of hypertension increases with age and tends to be higher among women.16 

And while hypertension affects all races and ethnic groups, certain groups bear a 

disproportionate burden of risk. non-Hispanic blacks have higher rates of hypertension than do 

non-Hispanic whites and Mexican-Americans, while Mexican-Americans have the lowest 

reported rates of controlled hypertension.16 Blacks tend to develop high blood pressure at an 

earlier age, they generally have much higher blood pressures,17 and they have a four times higher 

age-adjusted risk of end-stage renal disease than do whites.18 

Drug therapy for high blood pressure is equally effective among men and women.19 Blacks 

who receive appropriate treatment achieve overall decreases in blood pressure similar to those of 

whites, and also may experience a lower incidence of cardiovascular disease.17, 20, 21 Appropriate 

treatment and control of hypertension also reduces the risk of several associated complications, 

including end-stage renal disease, congestive heart failure, and peripheral vascular disease. The 

target blood pressures are less than 130/80 mmHg for hypertensive patients with diabetes or 

renal disease, and less than 140/90 mmHg for other patients with hypertension. 

This review provides a systematic assessment of the effect of various quality improvement 

(QI) strategies on the screening and treatment of hypertension. 

The Quality Gap 

Despite clear evidence that treating hypertension reduces morbidity and mortality, the 

incidence of stroke, myocardial infarction, and heart failure, hypertension care in the United 

States often fails to comply with evidence-based guidelines.1

 And while 68.9 percent of the 

participants in the 1999–2000 NHANES study were aware of their hypertension, only 58.4 

percent were receiving treatment.16 

These rates are an improvement over those reported from 1991–1998, but they still are not 

optimal. The national wellness program, Healthy People 2010,22 includes four important goals 

for the detection and evaluation of hypertension: 

• Reduce the proportion of U.S. adults with high blood pressure from the current rate of 

28.7 percent,16 to 16 percent.22

• Increase the proportion of hypertensive adults with controlled blood pressure from the 

current rate of 31 percent,16 to 50 percent.22 

• Increase the proportion of adults with high blood pressure who are taking action to help 

control their blood pressure (i.e., losing weight, increasing physical activity, or reducing 

sodium intake) from the current rate of 82 percent,23 to 95 percent.22

• Increase to 95 percent the proportion of adults who have had their blood pressure 

measured in the preceding two years and can state whether their blood pressure is normal 

or high.22

10
Recent findings suggest the nation is approaching this last goal. Data from the National 

Health Interview Survey, collected from 2001–2003, indicate 90 percent of all adults had their 

blood pressure measured in the previous two years and could state whether or not it is high.23 

Evidence-based Guidelines and Quality of Care Measures 

Guidelines 

Many aspects central to high blood pressure detection, evaluation, and treatment have been 

studied and the findings have contributed to the development of one of the most extensive 

guidelines processes available: the JNC Reports.1, 17 These guidelines are developed by the 

National High Blood Pressure Education Program of the National Heart, Lung, and Blood 

Institute, along with a number of coordinating committee member organizations.1

 

Therapy for hypertension is largely pharmaceutical-based, although nonpharmacologic 

therapies and lifestyle modifications such as exercise, sodium restriction, weight loss, and 

modification of alcohol intake are important contributors to blood pressure reduction. Evidencebased guidelines for management of hypertension recommend a wide variety of antihypertensive 

drugs, as well as targets for blood pressure control. The JNC 7 guidelines state “there are 

excellent clinical outcome trial data proving that lowering blood pressure with several classes of 

drugs, including angiotensin converting enzyme (ACE) inhibitors, angiotensin receptor 

antagonists (ARBs), β-adrenergic receptor antagonists (β−blockers), calcium channel antagonists 

(CCBs), and thiazide-type diuretics, will all reduce the complications of hypertension.”

1

Equivalent blood pressure reduction with different antihypertensive agents, however, may not 

confer the same degree of risk reduction.24 A recent analysis of data from 29 randomized trials 

studied the comparative benefits of several different antihypertensive drug classes on risk of 

cardiovascular events.25 This analysis showed a reduction in major cardiovascular events with 

ACE inhibitors, angiotensin receptor antagonists, β-adrenergic receptor antagonists, calcium

channel antagonists, and thiazide-type diuretics, while further determining that larger reductions 

in blood pressure (regardless of which of these medications was used) resulted in larger 

reductions in risk.25 The JNC 7 guidelines further contend that “diuretics have been virtually 

unsurpassed in preventing the cardiovascular complications of hypertension,” and recommends 

 

1

 National Heart, Lung, and Blood Institute, American Academy of Family Physicians, American Academy of Insurance 

Medicine, American Academy of Neurology, American Academy of Ophthalmology, American Academy of Physician

Assistants, American Association of Occupational Health Nurses, American College of Cardiology, American College of Chest 

Physicians, American College of Occupational and Environmental Medicine, American College of Physicians - American 

Society of Internal Medicine, American College of Preventive Medicine, American Dental Association, American Diabetes

Association, American Dietetic Association, American Heart Association, American Hospital Association, American Medical

Association, American Nurses Association, American Optometric Association, American Osteopathic Association, American 

Pharmaceutical Association, American Podiatric Medical Association, American Public Health Association, American Red

Cross, American Society of Health-System Pharmacists, American Society of Hypertension, American Society of Nephrology, 

Association of Black Cardiologists, Citizens for Public Action on High Blood Pressure and Cholesterol, Inc., Hypertension 

Education Foundation, International Society on Hypertension in Blacks, National Black Nurses Association, Inc., National 

Hypertension Association, Inc., National Kidney Foundation, Inc., National Medical Association, National Optometric 

Association, National Stroke Association, NHLBI Ad Hoc Committee on Minority Populations, Society of Geriatric Cardiology, 

Society for Nutrition Education, Federal Agency Representatives, Agency for Healthcare Research and Quality, Centers for

Medicare and Medicaid Services, Department of Veterans Affairs, Health Resources and Services Administration, National 

Center for Health Statistics, National Institute of Diabetes and Digestive and Kidney Diseases

11
that “thiazide-type diuretics should be used as initial therapy for most patients with hypertension, 

either alone or in combination with one of the other classes (ACE inhibitors, ARBs, β−blockers, 

CCBs) demonstrated to be beneficial in randomized controlled outcome trials.”1

 

A complete discussion of the different antihypertensive therapies is beyond the scope of this 

review of quality improvement strategies. Readers are directed to the JNC 7 guidelines and to 

other published resources. The World Health Organization and the Veterans Health 

Administration (VHA), for example, have undertaken independent reviews of the evidence, and 

have developed guidelines that closely resemble the JNC recommendations, with some areas of 

difference.26, 27

Quality of Care Measures 

The recent proliferation of quality measures for the assessment of medical outcomes has 

spawned multiple measures for particular conditions, including hypertension. Although there is 

no consensus regarding a single performance measure for determining hypertension quality of 

care, most national measures have focused on blood pressure control or screening. A multitude 

of blood pressure measures have been used over the years to assess the quality of care, frequently 

involving a percentage of patients with blood pressure exceeding a particular control threshold. 

The Institute of Medicine has stated that control of blood pressure is a valid quality measure, as it 

has been shown to reduce morbidity and mortality.28 Few report cards have used measures other 

than blood pressure control or screening to evaluate quality of care (e.g., whether clinicians

prescribed one of the recommended first-line antihypertensive medications). 

Although blood pressure screening and control have emerged as the consensus choices for 

hypertension quality metrics, variations on these themes have been developed by different 

organizations to reflect their particular goals, purposes, or opinions. Developers of quality 

measures include government agencies, accreditation groups, voluntary health organizations, 

purchasers, health plans, and physician specialty organizations, among others.22, 29–33 Debate 

regarding the most appropriate measures is ongoing, despite a general agreement that ideal 

measures should be easy to obtain, reliable, and valid. A selection of the groups involved in the 

development and/or utilization of hypertension quality measures is described below. 

The Agency for Healthcare Research and Quality (AHRQ) commissioned this report and 

maintains the National Quality Measures Clearinghouse. The Agency is mandated by the U.S. 

Congress to produce the National Healthcare Quality Report (NHQR), based on available quality 

measures.29 AHRQ’s preliminary quality measures for hypertension include the percentage of 

people age 21 and over who have had their blood pressure checked within the past two years, and 

the percentage of people with hypertension who have their blood pressure under control.29

The National Committee for Quality Assurance (NCQA) is the nonprofit accreditation 

organization that developed and maintains the Health Plan Employer Data and Information Set 

(HEDIS®), which contains quality performance measures for health care plans.33 HEDIS is the 

most widely used performance measures set in the managed care industry, and also is used by 

purchasers of health care, regulators, consumers, and health plans. The current HEDIS quality 

measure for hypertension is the percentage of patients with hypertension, age 46 to 85, whose 

blood pressure is controlled (defined as SBP < 140 mmHg and DBP < 90 mmHg). In the year 

2000, for example, 51.5 percent of patients participating in managed care plans that reported 

their HEDIS data had controlled blood pressure.34 This figure represents a significant 

improvement over the 39 percent result obtained in 1999 for the same HEDIS measure.34

12
Moreover, the year 2000 percentage is notably higher than the estimated percentage of known 

hypertensives in the general American population whose blood pressure is under control.34 

The Veterans Health Administration (VHA) utilizes quality measures to evaluate 

hypertension care within its delivery system. These measures include the percentage of patients 

with an active diagnosis of hypertension whose most recent blood pressure recording was less 

than 140/90 mmHg, and the percentage of patients with an active diagnosis of hypertension 

whose most recent blood pressure reading was ≥ 160/100 mmHg, or for whom no blood pressure 

had been recorded during the previous year.35 

Key Questions 

There are several important questions that warrant consideration in the realm of hypertension 

quality improvement. Some of these questions focus on prevention (screening) while others 

relate to the management of a chronic disease (blood pressure control). The reviewers have 

selected the following questions as important foci in the development of this report: 

• Which QI strategies improve the process of screening for hypertension?

• Which QI strategies most effectively ensure that blood pressure goals are achieved and 

maintained? 

• Which QI strategies improve provider adherence to recommended guidelines for 

hypertension management? 

• Which QI strategies improve patient adherence to hypertension treatment? 

Several features of hypertension pose challenges to the development and evaluation of 

quality improvement strategies. First and foremost, hypertension is generally asymptomatic; 

individuals afflicted with hypertension typically do not feel any differently from those who do 

not suffer the condition. In addition, medical treatment for hypertension may cause adverse side 

effects. These factors may make patients less likely to adhere to treatment. Additionally, 

hypertension is most often a chronic condition, requiring lifelong management. Patients whose 

blood pressure is controlled at one point in time may discover it is not well controlled at another 

time. This dilemma may present a challenge to those designing studies to evaluate the impact of 

QI interventions. 

In addition, treatment must be individualized for each patient. While the different classes of 

antihypertensives are effective in lowering blood pressure on a population basis, any individual 

patient may be more or less responsive to a particular medication, and/or may develop particular 

adverse effects. If a patient’s blood pressure already is well controlled through the use of a 

particular drug, changing to a different drug carries with it a possibility that the new drug will 

yield no benefit. The patient also could develop a drug-related adverse effect, requiring dose 

titration or other changes to the treatment regimen. Orthostatic hypotension is another concern, 

particularly in older adults with diminished autonomic responses to maintain blood pressure in 

the standing position. Many patients will require two, three, or more antihypertensive drugs to 

achieve the target blood pressure. Generally speaking, patients with hypertension tend to be older 

and often have other medical disorders requiring drug treatment. This patient population must be 

monitored closely for adverse drug effects and/or drug-drug interactions. Changing guideline 

recommendations and the wide variety of available therapies present further challenges to QI 

13
development and evaluation, given the dynamic nature of physician knowledge and patient 

knowledge concerning hypertension. 

14
Chapter 2: Methods 

Methods common to the reviews of quality improvement strategies for the various topics and 

disorders are presented in first volume of the Closing the Quality Gap series. The authors 

provide additional detail in this section, as it pertains to the review of quality improvement 

strategies for hypertension. 

Types of Quality Improvement Strategies 

A variety of interventions have been tested with the goal of improving the quality of care for 

common clinical conditions. The conceptual framework developed for classifying quality 

improvement strategies has been on the scientific literature (See Closing the Quality Gap, 

Volume 1). These interventions can target organizations, providers, communities, or individual 

patients, and have been evaluated in a wide variety of formats. The reviewers have classified the 

range of interventions into nine broad strategies, according to the following taxonomy (also see, 

Volume 1): 

1. Provider reminders—Information tied to a specific clinical encounter, provided 

verbally, in writing, or by computer, and intended to prompt the clinician to recall 

information (e.g., to make medication adjustments or order appropriate screening tests), 

or to consider performing a specific process of care. The phrase “tied to a specific clinical 

encounter” serves to distinguish reminder systems from audit and feedback, where 

clinicians are typically presented with summaries of their performance relative to a 

process or outcome of care over multiple encounters. 

2. Facilitated relay of clinical data to providers—Clinical information collected directly 

from patients and relayed to the provider where the data are not generally collected 

during a patient visit, or using some format other than the existing local medical record

system (e.g., transmission of a patient’s home blood pressure measurements). The 

researchers expected some overlap with provider reminder systems, but kept these 

strategies separate at the abstraction stage, to allow for the possibility that the data could 

be analyzed subsequently with and without collapsing the two strategies. 

3. Audit and feedback—Any summary of clinical performance of health care providers or 

institutions that is reported either publicly or confidentially, to or about the clinician or 

institution (e.g., the percentage of a provider's patients who have achieved or have not 

achieved some clinical target). Benchmarking refers to the provision of performance data 

from institutions or providers regarded as leaders in the field. The investigators included 

benchmarking as a type of audit and feedback, so long as local data were provided in 

addition to the benchmarks. 

4. Provider education—Any intervention that included one of the following three 

substrategies: educational workshops, meetings (e.g., traditional Continuing Medical 

Education [CME]), and lectures (live or computer-based); educational outreach visits 

(use of a trained person who met with providers in their practice settings to disseminate 

information intended to change the provider's practice); or distribution of educational 

15
materials (e.g., published or printed recommendations for clinical care, including clinical 

practice guidelines, audio-visual materials and/or electronic publications). 

5. Patient education—In-person patient education, either individually or as a part of a 

group or community; distribution of printed or audio-visual educational materials. The 

investigators evaluated those strategies that included patient education as part of a 

multifaceted strategy, but excluded those in which patient education was the sole 

strategy. A future volume in this series will review the topic of patient education with

reference to its effect on a variety of chronic diseases, including hypertension. 

6. Promotion of self-management—Distribution of materials (e.g., devices for blood 

pressure self-monitoring) or access to a resource that enhances the patients' ability to 

manage their condition, provision of clinical data back to the patient, or followup phone 

calls to make recommendations regarding adjustments to care. The reviewers expected 

some strategy overlap with patient education and patient reminders, but kept the 

strategies separate at the abstraction stage to allow for the possibility that the data could 

be analyzed subsequently with and without collapsing the strategies. Those strategies that 

included self-management as part of a multifaceted strategy were analyzed, but those in 

which self-management was the sole strategy were excluded. A future volume in this 

series will address the topic of self-management, along with patient education. 

7. Patient reminders—Any effort directed at encouraging patients to keep appointments or 

adhere to other aspects of self-care.

8. Organizational change—Changes in the structure or delivery of clinical care designed 

to improve its efficiency or comprehensiveness. The investigators included changes such 

as the use of disease management or case management (coordination of assessment, 

treatment, and arrangement for referrals by a person or multidisciplinary team in 

collaboration with or supplementary to the primary care provider), other team or 

personnel changes, use of telemedicine (communication and case discussion between 

distant health professionals), Total Quality Management (TQM) or Continuous Quality 

Improvement (CQI) (i.e., cycles of measurement of quality problems, design of

interventions, implementation, and re-measurement), and changes in medical records 

systems or hospital information systems. Among studies that included organization 

change as one of their QI strategies, three substrategies (disease/case management, 

team/staffing changes, and medical records changes) also were extracted for analysis.

9. Financial, regulatory, or legislative incentives—Interventions providing positive or

negative financial incentives directed at providers (e.g., linked to adherence to some

process of care or achievement of some target patient outcome), positive or negative 

financial incentives directed at patients, system-wide changes in reimbursement (e.g., 

capitation, prospective payment, shift from fee-for-service to salary), changes to provider 

licensure requirements, or changes to institutional accreditation requirements. 

In addition to the aforementioned QI strategies, the reviewers planned initially to abstract 

data on intervention features, such as use of social influence (e.g., local opinion leaders36, 37), 

involvement of top management, designing the intervention based on a theory of behavior or 

organizational change,38–40 and other potential “mediators” of intervention success.41 The 

identified studies, however, rarely explored these and other potentially relevant features of 

intervention design.42 Similarly, few studies considered organizational context43 and local 

16
attitudes and beliefs,44 so these potential predictors of intervention success or failure were 

deleted from the structured questions on the abstraction forms and from the analysis. 

The single “mediator” reported with sufficient frequency and detail was the use of clinical 

information systems, identified as a potential predictor of success in a previous review.45, 46 

Reviewers were asked to indicate whether a clinical information system played a role in the 

design or implementation of the intervention (regardless of QI strategy type). The potential roles 

identified in structured form were: identification and/or group allocation of eligible patients or 

providers; reminders generated by an existing clinical information system; decision support at 

point of care; facilitated communication between providers (e.g., e-mail communications 

between members of a care team); and audit data gathered from a clinical information system to 

facilitate a QI strategy (e.g., audit and feedback, TQM, provider education, financial incentives). 

Scope 

In keeping with the goal of reviewing quality improvement strategies, numerous categories 

of studies were necessarily excluded or included. The investigators defined the scope of the 

project in terms of: hypertension type in the study population; targeted patient subpopulations; 

steps in the pathway to hypertension control; studies excluded for their failure to address QI; 

study design; and year of publication. 

Hypertension type—To review studies that were most applicable to the general population, 

the researchers focused on primary hypertension in non-pregnant adults. Also known as 

"essential" hypertension, primary hypertension comprises at least 90 percent of all cases, and is 

of unknown etiology. Since identifiable secondary causes (such as renal artery stenosis) account 

for only a small number of cases (and management of these cases is less guideline-directed), this 

report focuses on primary hypertension. Studies that failed to specifically state that they omitted 

cases of secondary hypertension from the study population were not excluded. However, as 

management of hypertension in children and in pregnant women differs markedly from 

management of essential hypertension in non-pregnant adults, studies of these subpopulations of 

hypertensives were excluded from this review. 

Targeted patient subpopulations—Many hypertensive patients have comorbidities such as 

diabetes mellitus and cardiovascular disease. These populations were included, as they are a 

sizable segment of the overall hypertensive population in the United States. Studies focused 

primarily on a smaller, specialized subpopulation (e.g., patients with alcoholism) were excluded. 

Steps in the pathway to hypertension control—The causal pathway to hypertension 

control involves numerous steps. Studies that reported solely on interventions related to patient

or provider knowledge at the earliest stages of the pathway were excluded. Patient and provider 

knowledge were considered only in conjunction with reports involving clinically relevant 

outcomes measures, such as blood pressure control. 

Studies excluded for their failure to address QI—The primary QI targets were patient and 

provider adherence to recommendations, and the identification and effective control of 

hypertension (these will be described in full, later in this chapter). Equivalence studies (i.e., two 

patient groups that received either a physician-managed or a nurse-managed intervention to 

determine whether the two were equivalent) were excluded, as were studies that focused solely 

on patient satisfaction, costs, or resource use. In addition, studies of efficacy trials for particular 

17
blood pressure control interventions, and studies designed primarily to assess the efficacy of 

certain medications in lowering blood pressure, particular life-style changes (e.g., salt restriction 

diets, stress reduction) and particular technical innovations (e.g., one home blood pressure 

monitor compared with another) were excluded. The same is true of studies that relied on 

provider self-report as a measure of provider adherence to recommendations. 

Study design. Study designs other than randomized controlled trials (RCT), quasi-RCTs, 

controlled before–after (CBA), or interrupted time series (i.e., studies using a design below Level 

2) were excluded. (For more on study designs, see in Table 2, in Volume 1 of this series.) 

Year of publication—Studies published prior to 1980 were excluded. 

Literature Search and Review Process 

Our search strategy began with a broad electronic search of the MEDLINE® database from

January 1966 to July 2003, which yielded a total of 3070 citations (Figure 1). The search strategy 

is shown in Appendix A. We supplemented these results with a search of the Cochrane 

Collaboration’s Effective Practice and Organisation of Care (EPOC) database,47 which includes 

the results of EMBASE and CINAHL® searches in addition to MEDLINE and extensive hand 

searching. Searching the EPOC database produced an additional 82 articles deemed relevant for 

full abstraction. Manual review of reference lists from retrieved articles, including prior 

systematic reviews and seminal articles24, 48–70 in the field, yielded an additional 13 articles 

(Figure 1). 48, 71–82 Core investigators reviewed all of the resulting abstracts. A total of 359 

articles merited full-text review (performed by two independent reviewers); at this stage, we 

abstracted basic information on study design, quality improvement strategy, and types of 

outcomes (Figure 1, and Appendix B). To meet the criteria for full abstraction, articles were 

required to experimentally assess the effect of a quality improvement strategy on hypertension 

detection, hypertension control, provider adherence, or patient adherence in adults. Articles 

excluded at this review stage appear in Appendix C. 

Terminology to Distinguish Studies, 

Interventions, and Comparisons 

Because the articles we reviewed did not have a uniform structure in the presentation of 

study data, we adopted the following terminology to describe the quality improvement

interventions we reviewed for this volume: 

When a single study led to multiple publications (articles) describing different aspects of the 

study, (e.g., a methods article followed later by a results paper, or several results papers) each 

publication was separately identified, but we reviewed all articles for the same study 

together. 

A single study may include several different study arms (groups of subjects), with different 

QI interventions provided to the subjects in each study arm. These are often reported in a 

single published article. For purposes of analysis, we considered each intervention that was 

18
studied in comparison to a control group as a separate comparison. For example, a single 

study with one control group and three different QI intervention arms receiving different 

interventions (e.g., provider education and organizational change in one arm, patient 

reminder and organizational change in another arm, audit and feedback in a third arm), each 

compared with the control group, was considered (e.g., was listed in the Tables), as three 

comparisons. When an article reported several comparisons, we abstracted the data for each 

comparison separately. 

The intervention described in a particular study may be multifaceted, that is, may involve 

more than one QI strategy. For example, the intervention may consist of a combination of 

provider education and provider reminders. A multifaceted intervention applied to a single 

study arm in comparison with control constituted a single comparison. 

Outcome Measures 

There are several important categories of outcomes relevant to the detection and management 

of hypertension. These include: 

• measures of disease identification 

• measures of disease control 

• measures of provider adherence to recommendations 

• measures of patient adherence to recommendations 

Measures of Disease Identification and Initial Followup 

We reviewed studies of screening for hypertension as a measure of disease identification. 

Screening for high blood pressure can occur in several settings. These include the community, 

the work place, and the clinician’s office. Important outcomes with respect to disease 

identification include: 

• percentage of individuals who had their blood pressure measured 

• percentage of individuals found to have elevated blood pressure 

• percentage of individuals with elevated blood pressure who received follow-up 

• percentage of individuals screened who knew whether or not their blood pressure was 

elevated. 

Measures of Disease Control

We reviewed several measures of disease control outcomes:

• all-cause mortality 

• CVD or CHD mortality 

• mean or median SBP 

• mean or median change in SBP 

• mean or median DBP 

19
• mean or median change in DBP 

• percentage of patients achieving blood pressure within a target blood pressure range 

• percentage of patients with improved blood pressure control 

We also abstracted a description of other measures of disease control used as outcomes in 

individual studies. We considered quality measures related to control of blood pressure to be the 

most important of the frequently used measures by which to evaluate quality improvement 

strategies for hypertension management. Morbidity and mortality measures represent the ideal 

measures, as they are the ultimate outcomes of interest; however, most studies did not report 

them. 

Measures of Provider Adherence 

Several measures of provider adherence were analyzed. We defined providers as the health 

professionals reported in the studies, including physicians, nurses, and pharmacists. We accepted 

the target or recommended practice as reported in the study. It must be noted, however, since 

recommendations have changed over time, some of the targets or recommendations no longer 

comport with current guidelines. Measures evaluated included: 

• adherence to guideline-specified targets for blood pressure 

• adherence to guidelines for the evaluation of patients with hypertension 

• adherence to specific medication recommendations 

• adherence to recommendations to improve patient medication adherence 

• adherence to guidelines for checking and/or recording blood pressure 

• adherence to guidelines for patient counseling or delivering patient education 

Measures of Patient Adherence 

We analyzed the following outcome measures of patient adherence to recommendations: 

• medication adherence (determined by self-report, pill counts, or pharmacy records) 

• adherence to follow-up appointments 

 

Other Outcome Measures 

Additional outcome measures reported in one or more studies that do not fit the categories 

above are shown in Appendix D. 

 

Analysis 

As described in Chapter 2 of this Volume, although we sought to conduct quantitative 

analysis of the included studies, many studies did not provide sufficient information to be 

analyzed in this fashion. Where feasible, we conducted a series of analyses, from descriptive 

summaries to comparative statistical analyses and exploratory regression analyses. 

20
Median Effects Calculations

To take account of differences at baseline between intervention and control groups, we 

computed the outcomes for each study as the net change from pre-intervention to postintervention between study and control groups: 

Net Change = (Post-intervention – Pre-intervention)Study group – (Post-intervention – Pre-intervention )Control group 

Following the method employed in a recent systematic review of strategies for guideline 

implementation,83 the median of the calculated net change for studies reporting the same

outcome was then reported for each analysis, and termed the “median effect.” For example, if a 

study reported the mean SBP for the control and intervention arms before and after the QI 

intervention, we calculated a net change in mmHg. We constructed each outcome measure so 

that a positive result indicated an improvement; for example, a lowering of SBP or an increase in 

the percentage of patients receiving guideline-recommended drugs were recorded as positive 

results. We report the median and inter-quartile (IQ) range for all studies reporting each 

outcome. 

Because many different outcomes were used to measure provider adherence, we were unable 

to perform quantitative analysis of the effect of QI strategies on individual adherence outcomes. 

We therefore developed a summary measure of adherence for each study that reported more than 

one adherence outcome. For example, if a study reported three adherence outcomes that required 

(1) appropriate choice of medication (e.g., diuretics or β-blockers as first-line therapy for 

uncomplicated hypertension), (2) decrease in inappropriate choice of medication (e.g., calcium

channel blocker for patients without specific indication), and (3) appropriate patient education 

(e.g., salt restriction, exercise counseling, smoking cessation), we calculated an effect size for 

each outcome, ranked the effect sizes, and used the outcome with the median effect size as the 

summary adherence measure for that study. 

Study Sample Size and Publication Bias

Publication bias refers to the overestimation of effect size due to preferential reporting of

positive studies, particularly with smaller, poor quality studies,84–90

 and is of particular concern 

for quality improvement studies. Given the lack of a single, well-established analytic method for 

detecting or adjusting for the effects of publication bias,91–93

 conducting a thorough search for 

unpublished research represents the preferred approach to avoiding this potentially large source 

of bias.84, 94, 95 However, in the area of quality improvement, relevant research may be more 

likely to be conducted by personnel charged with quality assurance activities as part of their job 

descriptions, with emphasis placed on measures of success rather than research dissemination. 

Consequently, the incentive to publish evaluations may be particularly low when the result is 

negative. Further, there is not an efficient means to find these studies. 

The difficulty in obtaining unpublished QI trials and the accompanying susceptibility to 

publication bias led us to analyze the studies in terms of sample sizes. Focusing on median 

effects, as described above, rather than average effects, avoids skewing summary measures based 

on one or two outliers with particularly large or small effects. We then examined the median 

effect sizes by different strata of study sample size, e.g., comparing the median effect among 

studies with sample sizes in the lowest quartile versus those in the highest quartile, or the lower 

half compared with the upper half. Strata were defined for studies reporting SBP and DBP 

21
outcomes separately, so that a study was assigned a study size quartile for comparisons with 

other studies reporting the same outcome. 

For studies where the unit of analysis and unit or randomization differed, we also conducted 

analyses of “effective sample size.” Briefly, we adjusted for “clustering” (e.g., providers or 

clinics were randomized and patient outcomes for the providers or clinics used for ascertainment 

of the outcome). We performed this adjustment using estimated values for the intra-cluster 

coefficient (ICC).1, 96 We also addressed the possibility that studies of other sub-optimal design 

might contribute overly-optimistic outcomes by analyzing study design features, as described in 

the next section. 

Study Design Quality 

We reviewed studies for five aspects of study design quality. We considered studies to be of 

higher quality if the design included the following features: randomized allocation of 

intervention, providers blinded to study group assignment, patients blinded to study group 

assignment, unit of analysis same as unit of allocation to treatment, and concealment of 

allocation. We report pooled study outcomes for studies with and without each of these design 

features. 

Statistical Analyses 

Where possible, we performed a simple non-parametric test for differences between median 

effects— the Mann-Whitney rank-sum test.104 Such analyses were possible only for mutually 

exclusive categories, such as randomized versus non-randomized trials, or for all interventions 

with a given QI strategy, compared with those without this strategy. We could not, however, 

compare one strategy to another because of the frequent overlap between types of strategies, with 

the same interventions contributing to multiple median effect sizes. 

22
Chapter 3. Results 

Search Yield and Results of Literature Review Process 

Figure 1 depicts the article search and review process with the results at each step. From a 

literature search that resulted in 3070 citations, 110 articles merited full abstraction (Figure 1). 

Of these, 47 consisted solely of a patient education strategy (Appendix E), and are not reviewed 

here, as this topic will be reported in a future volume of this series. Our study sample consists of 

63 articles73, 105–165 reporting a total of 82 comparisons of QI strategies (Appendix F). Forty-eight 

studies are randomized controlled trials (reporting on 64 different comparisons), six are quasirandomized controlled studies (reporting on seven different comparisons), and nine are 

controlled before-after studies (reporting on 11 different comparisons) (see Table 1 and 

Appendix F). 

The types of quality improvement strategies and substrategies assessed in the articles are 

shown in Tables 2a and 2b. Among individual strategies, organizational change (particularly 

team staffing changes) and patient education (in combination with other interventions) were most 

commonly utilized. Educational interventions for providers were common as well. Most articles 

described interventions consisting of more than one strategy; only 21 percent (17/82) described a 

single strategy (Table 3). The 82 comparisons reported 42 unique combinations of strategies, 

with most of these combinations occurring in only one or two comparisons (Table 4). 

Studies analyzed a mix of outcomes. Ten studies reported disease identification outcomes. 

Most studies reported clinical and process outcomes (Appendix G). Among studies reporting 

clinical outcomes, 60 comparisons had sufficient information to calculate quantitative results. 

Among the 40 comparisons reporting SBP as a measure of disease control, 33 (83 percent) 

reported sufficient information to perform a quantitative analysis. Among the 49 comparisons 

reporting DBP as a measure of disease control, 43 (88 percent) reported sufficient information to 

calculate quantitative results. Among the 23 comparisons reporting proportion of patients 

achieving SBP within a certain range, 14 (61 percent) reported sufficient information to calculate 

quantitative results. Among the 28 comparisons reporting proportion of patients achieving DBP 

within a certain range, 16 (57 percent) supplied sufficient information for quantitative analysis. 

Among the 19 comparisons reporting process outcomes involving provider adherence to 

recommended care, 10 (53 percent) supplied sufficient information for quantitative analysis. 

Among the 28 comparisons reporting outcomes involving patient adherence, only 5 (18 percent) 

supplied sufficient information for quantitative analysis. 

Analysis by Outcome Measures 

Effect of Quality Improvement Strategies on Disease Identification 

and Initial Followup Measures 

A total of 10 studies assessed disease identification and/or initial followup appointments.106,

109, 110, 124, 138, 141, 151, 158, 165, 166 Many of these studies also assessed other outcomes, most

23
commonly disease control. Table 5 summarizes the setting, interventions, and results of these 

studies. Studies of disease identification took place either in a medical setting, for example in a 

clinic, or in the community, for example at a work site, community center, or some other venue 

outside of the health care setting. The majority of these studies (6 of 10) were conducted at a 

clinic. Among the interventions in the clinic setting, the most common QI strategies were patient 

and/or provider reminders. Two studies reported a work site intervention, which included 

identification of hypertensives at the work site, and then a comparison of different followup 

treatment strategies.138, 166 The remaining studies of community-based screening often involved 

public education and appropriate followup of individuals identified as hypertensive. 

Overall, in the studies of disease identification, outcomes measured were varied. Given the 

small number of studies and the heterogeneity of both the interventions and the outcomes, we 

were unable to perform meaningful analyses of pooled data, and therefore do not report summary 

data for screening studies. Most of the interventions led to some improvement in a screening 

related measure (Table 5). 

Of the screening strategies evaluated, some strategies which demonstrated positive results 

included work site screening/followup, use of patient reminder letters, computer identification of 

patients with historically poor followup (combined with computer-generation of physician 

reminders), and the addition of a health promotion nurse to identify and followup with high-risk 

patients. One work site screening study involved 11,196 employees, and compared work site 

screening and referral of hypertensives to a physician (control group) with work site screening, 

referral, and more frequent followup or on-site treatment for hypertensives by a work site 

physician (three intervention groups).166 The study reported higher rates of treatment at the end 

of the study in the intervention groups (96 percent or higher for intervention groups, compared 

with 84 percent for the control). Two studies found positive results with the use of patient letter 

reminders.141, 158 One of these studies involved 5744 patients and evaluated several interventions 

aimed at encouraging patients to have their BP checked, including letter reminders.141 In this 

study, 35.7 percent of patients who received letter reminders subsequently had their blood 

pressure measured, compared with 21.1 percent of patients in the control group.141 The other 

screening study evaluated patient reminder letters that encouraged patients with high blood 

pressure to receive followup, and found that 62 percent of the patients who received the reminder 

letter subsequently had followup, compared with 29 percent in the control group.158 Another 

screening study evaluated the efficacy of an automated computer surveillance system to monitor 

patients with elevated BP and poor followup rates, and which generated reminders to providers 

for all patients not adhering to standard followup procedures.109 This study involved 115 patients, 

and found, over a 6-24 month followup period, that 98 percent of the intervention group had 

followup over this period, and 70 percent had a repeat BP recorded, compared with a 46 percent 

followup rate in the control group, with a 52 percent repeat BP recorded rate.109 One of the 

screening studies evaluated the efficacy of a health promotion nurse to identify and followup 

with high-risk patients (using a computer system to search for high-risk patients).151 This study 

involved 3117 patients, and found that over the course of the five-year study, patients in the 

intervention group increased the frequency with which their BP was recorded from 65 percent to 

93 percent. The control group had a smaller increase in the same measure, from 62 percent to 73 

percent, over the course of the study. 

24
Effect of Quality Improvement Strategies on Measures of 

Disease Control 

Effect of quality improvement strategies on mortality. Six studies reported mortality 

outcomes.20, 105, 110, 118, 131, 165 Two of these studies were large clinical trials, the Multiple Risk 

Factor Intervention Trial (MRFIT), and the Hypertension Detection and Follow-up Program

(HDFP), a major clinical trial.20, 105 The MRFIT study was a primary prevention trial that tested 

the effect of a multifactor intervention program on coronary heart disease mortality in high-risk 

men aged 35-57 years. The “special intervention” (SI) included dietary advice for lowering blood 

cholesterol levels, counseling aimed at cessation for cigarette smokers, and “stepped care” 

treatment for hypertension for those with elevated BP. The SI was compared with usual care in 

the community. The trial included a planned initial followup in February, 1982; at that point, 

coronary heart disease and all-cause mortality rates were similar for SI and usual care. This 

finding was attributed, in part, to the substantially lower than expected death rate in the usual 

care group. After the initial results were reported in 1982, plans were made for additional 

analyses after ten-year followup of the participants. During ten-year followup, there were 317 

deaths among 4019 SI participants (7.9 percent), and 353 deaths among 3993 usual care 

participants (8.8 percent). These rates were also reported as rates per 1000 person-years of 7.55 

per 100 in the intervention group, and 8.48 per 1000 in the control group (P = 0.13). The data 

show a trend toward lower death rate in the SI group, but it was not statistically significant. It is 

not possible to distinguish the effect of the QI strategy components of the intervention from the 

effect of the specific drugs used, nor is it possible to distinguish the effects of blood-pressurelowering from the effects of the cholesterol-lowering and smoking cessation components. 

The HDFP examined a stepped care regimen in which participants were offered a free, 

standardized program of antihypertensive therapy in HDFP centers. Treatment approaches 

included the use of techniques believed to enhance patient adherence. Economic barriers to 

treatment were removed, to the extent possible, with provision of drugs, visits to the centers, 

laboratory tests, and transportation at no cost to the participant. Waiting times were minimized 

by use of additional allied health personnel, and appointments were available at convenient 

hours. Treatment included stepwise increases in medication to bring patients to or below their 

goal DBP. Patients were randomly assigned either to stepped care or usual care. Mortality from

all causes was the primary endpoint of the study. During five-year followup, there were 349 

deaths among 5485 stepped care participants (6.4 percent), and 419 deaths among 5455 usual 

care participants (7.9 percent). These rates were also reported as life table death rates per 100, of 

6.4 per 100 in the intervention group, and 7.7 per 100 in the control group, representing a 16.9 

percent relative risk reduction in mortality in the stepped care group (P < 0.01). The HDFP study 

also reported cardiovascular mortality as a secondary outcome: there were 195/5485 (3.6 

percent) cardiovascular deaths in the stepped care group, and 240/5455 (4.4 percent) 

cardiovascular deaths in the control group (statistical comparison not reported). Because 

mortality was the primary endpoint of the study, and the difference in mortality was statistically 

significant, we can conclude that the stepped care approach, as implemented in the HDFP, was 

effective in lowering mortality risk. It is not possible to distinguish which component of stepped 

care, such as drug choice or QI strategies, was responsible for the benefit. 

Another study reporting mortality rates used multiple QI strategies (provider reminders, 

patient education, patient reminders, and organizational change) in 34 family practices in 

Canada, involving 32,124 patients.110 This study reported similar all-cause and cardiovascular 

mortality in control (1.6 percent, and 0.7 percent, respectively) and intervention (1.5 percent, and 

25
0.7 percent, respectively) groups. This study did not include outcome measures for disease 

control in a format that was quantifiable for inclusion in our disease control analyses. 

The fourth study reporting mortality outcomes, which also reported disease control outcomes 

included in our pooled analyses, was a study of a nurse practitioner intervention in three 

specialist hypertension clinics in Scotland, involving 396 patients.118 The QI strategies included 

patient education, patient reminders, and organizational change. This study reported similar 

mortality rates in the control and intervention groups: 29/198 (15 percent) and 23/198 (12 

percent) all-cause and cardiovascular mortality, respectively, in the control group, and 25/198 

(13 percent) and 17/198 (9 percent) all-cause and cardiovascular mortality, respectively, in the 

intervention group. 

A fifth study provided a special intervention for young, urban, African American men.131 The 

study included an educational intervention for both control and intervention study arms, 

including explanation of BP, goal BP, importance of remaining in care and adhering to 

treatment, referral to a physician if necessary, answers to questions, and a wallet card on which 

to record BP. In addition, men in the special intervention group also received individualized 

counseling, monthly telephone calls, and a home visit. This study reported mortality outcomes as 

one of several reasons for nonattendance at followup visits: 1/101 in usual care group, and 5/103 

in the special intervention group. Mortality outcomes were not a primary outcome measure in 

this small study. 

The sixth study reporting mortality outcomes was the Mayo three-community hypertension 

control program, which included two comparisons.165, 167 This study focused on individuals with 

BP at or above SBP 160 mmHg or DBP 95 mmHg in three different communities. The 

intervention included a special community hypertension clinic. Death rates at five-year followup 

were reported as 12/153 (6.2 percent) and 5/249 (1.8 percent) in the two different control areas, 

and 15/237 (5.4 percent) in the intervention area. Mortality outcomes were not a primary 

outcome measure in this small study. 

Effect of Quality Improvement Strategies on Blood Pressure Control

A total of 33 comparisons assessed reduction in SBP, and 43 comparisons assessed reduction 

in DBP. The vast majority of studies showed improvements in these outcomes associated with 

the QI intervention (Appendix G). The median reduction in SBP was 4.5 mmHg (IQ range: 1.5, 

11.0), and median reduction in DBP was 2.1 mmHg (IQ range: -0.2, 5.0) (Table 6a). Fourteen 

comparisons assessed the effect of the QI strategy on the proportion of patients with blood 

pressure in the target SBP range, and 16 comparisons assessed the effect of the QI strategy on the 

proportion of patients with blood pressure in the target DBP range (Appendix G and Table 6a). 

In these comparisons, the median increase in the proportion of patients in target SBP range and 

DBP range in these comparisons was 16.2 percent (IQ range: 10.3, 32.2), and 6.0 percent (IQ 

range: 1.5, 17.5), respectively. In these studies, QI strategies had a clinically meaningful effect 

on SBP, and on the proportion of patients achieving the target SBP range, and a more modest 

effect on DBP, and the proportion of patients achieving the target DBP range. 

26
Effect of Quality Improvement Strategies on Provider Adherence 

A total of 10 comparisons reported quantitative results of provider adherence to 

recommended practices (Appendix G and Table 6b). Overall, the median increase in percentage 

of providers adhering to recommendations was 3.0 percent (IQ range: 1.0, 5.5). 

Effect of Quality Improvement Strategies on Patient Adherence 

Four studies with five comparisons reported results for patient adherence to medications or 

followup appointments. Overall, there was a median increase in percent of patient adherence of 

2.8 percent (IQ range: 1.9, 3.0) (Appendix G and Table 6b). 

Analysis by Type of Quality Improvement Strategy 

Table 2a lists the number of studies examining each major type of quality improvement 

strategy. For certain QI strategies, there were a large number of important substrategies for 

which meaningful outcomes were reported (Table 2b). Many studies used more than one QI 

strategy. The numbers of studies using each different combination of QI strategies is shown in 

Table 4. Table 6a shows the median effects of QI strategies on blood pressure outcomes, and 

Table 6b shows the effects of individual quality improvement strategies on provider and patient 

adherence outcomes. Since not all comparisons listed in Tables 2a and 2b had sufficient data to 

report all outcomes, the total number of comparisons in the median effect tables may be smaller 

than the total number listed in Tables 2a and 2b. When describing the results of each QI strategy, 

we do not differentiate those that used that particular QI strategy alone, from those that used it in 

conjunction with other strategies. This is because single QI strategies were seldom used alone 

(Table 4), especially in studies with adequate data for reporting median effects (Tables 7a and 

7b). Mann-Whitney tests of significance are noted when P-values were less than 0.05 for 

analyses comparing results from studies with a particular QI strategy to studies without that

particular strategy. This test of significance must be interpreted tentatively, as we conducted 

multiple sub-group analyses. Tables 8a and 8b show the effects of several quality improvement 

substrategies on outcomes. 

Provider Reminders

Nine studies, including a total of 10 comparisons, used provider reminders alone (two 

comparisons), or in combination with other QI strategies (Table 2a and Table 4). Studies that 

used provider reminders, alone or in combination with other QI strategies, found a median 

reduction in SBP of 6.8. mmHg (IQ range: 3.0, 9.4) and a median reduction in DBP of 2.1 

mmHg (IQ range: 0.9, 6.6). There were two comparisons using provider reminders as a QI 

strategy that reported outcomes for SBP in target range; both comparisons were from the same

study, and reported a decrease in this outcome of 3.6 percent (IQ range: -5.7,-1.4) in the 

intervention group compared with the control group.128 This study included three study arms: 

academic detailing, academic detailing plus Continuous Quality Improvement (CQI) teams, and 

27
usual care. Patients whose mean BP measurements over six months were less than 160/90 mmHg 

were classified as controlled. In this study, all study groups showed improvements in percent of 

patients with BP in target range. The usual care control group had a greater improvement than 

the provider reminder (e.g., academic detailing) groups, producing the decrease in median effect 

size. The authors commented that either contamination or a Hawthorne effect may have 

contributed to their generally negative findings, by moving usual care behavior in the direction 

hypothesized by the interventions. 

Three comparisons utilizing provider reminders reported outcomes for provider adherence to 

hypertension treatment recommendations, and had mixed results, with a median effect of 1.3 

percent decrease (Table 6b). Two of these comparisons were in the same study described in the 

preceding paragraph.128, 168 The third study123 used a clinical pharmacist program that included 

provider reminders as part of the QI strategy; this study found an improvement in provider 

adherence to recommended management. No studies using provider reminders reported effects 

on patient adherence outcomes. 

Facilitated Relay of Clinical Data 

Facilitated relay of clinical data was assessed as all (two comparisons), or part of the QI 

strategy in 23 studies, including a total of 31 comparisons (Table 2a and Table 4). Studies that 

used facilitated relay found a median reduction in SBP of 4.5 mmHg (IQ range: 2.2, 11.5), and a 

median increase in the percentage of patients with SBP in the target range of 15.3 percent (IQ 

range: 2.0, 28.4). The median effect for DBP was a reduction of 1 mmHg (IQ range: -1.0, 3.4) 

(Table 6a). There was a median increase in provider adherence of 2 percent (IQ range: -0.4, 3.7, 

seven comparisons), and a median increase in patient adherence of 2.4 percent (IQ range: 0.8, 

5.0, four comparisons) (Table 6b). 

Audit and Feedback 

Ten studies (with 13 comparisons) included audit and feedback alone (one comparison), or in 

combination with other QI strategies (Table 2a and Table 4). In these studies, there were small 

improvements in median SBP of 1.3 mmHg ( IQ range: 0.5, 1.6), median DBP of 0.6 mmHg ( IQ 

range: 0.5, 1.0), percentage of patients with DBP under control (1.8 percent, IQ range: 0.1, 4.3) 

(Table 6a), and median improvement in provider adherence to recommended practice of 2.7 

percent ( IQ range: -0.4, 3.7) (Table 6b). There was a median reduction of 3.6 percent (IQ range: 

-5.7, -1.4) in patients in SBP target range. For SBP and proportion of patients in DBP range 

outcomes, studies with audit and feedback, alone or in combination, showed less of an 

improvement than studies without an audit and feedback component (P = 0.039 for SBP, and P = 

0.036 for DBP range). Seven studies reported provider adherence outcomes with median 

improvement of 2.7 percent (IQ range: -0.4, 3.7) (Table 6b). Only one study reported an effect 

on patient adherence, and this was a net decrease of 2.7 percent (Table 6b).129 This study used a 

multifaceted intervention with a goal of improving physician adherence by tailoring CME to 

deficiencies in physician performance identified by medical record review and a patient survey. 

The study included eight secondary hypotheses, of which one was that patients of physicians 

receiving the intervention were expected to show greater adherence to medication regimens. 

28
Provider Education 

A total of 18 studies (including 22 comparisons) utilized provider education as all (four 

comparisons), or part of the QI strategy (Table 2a and Table 4). Among our included studies, the 

most frequently used provider education strategies were educational workshops, meetings (e.g., 

traditional CME), and/or lectures (live or computer-based), (19 of 22; 86 percent), and 

distribution of educational materials (16 of 22; 73 percent). In studies examining provider 

education, alone or in combination with other QI strategies, there was a median reduction in SBP 

of 2.7 mmHg (IQ range: 1.1, 6.0). There was a median increase of 10.9 percent (IQ range: 1.4, 

13.1) in proportion of patients achieving SBP in the target range (Table 6a). In these studies, the 

median reduction of DBP was 0.7 mmHg (IQ range: -0.3, 3.3), and median increase in 

percentage of patients achieving DBP in the target range was 3.5 percent (IQ range: 1.7, 11.3) 

(Table 6a). For SBP and proportion of patients in SBP range outcomes, studies with provider 

education, alone or in combination with other QI strategies, showed less of an improvement than 

studies without a provider education component (P = 0.037 for SBP and P = 0.012 for SBP 

range). Median improvement in provider adherence with hypertension treatment 

recommendations was 3.3 percent (IQ range: 0.7, 5.0) in these studies (Table 6b). Two studies 

reported the effect of QI strategies that included provider education on patient adherence: one 

reported a decrease in patient adherence of 2.7 percent, and the other an increase of 3.0 percent 

(Table 6b, Appendix G). 

Substrategies of Provider Education 

Because provider education includes so many types of QI strategies, we performed analyses 

of some educational substrategies, including CME, educational outreach, and distribution of 

printed materials (see Tables 8a and 8b). Most studies with provider education included CME, 

and therefore showed similar median effects in blood pressure outcomes as above. Studies 

involving CME as part of the quality improvement strategy also demonstrated similar 

improvements in provider adherence to recommended practices, and in patient adherence to 

medical regimen (see Table 8b). The few studies that included the substrategy of educational 

outreach generally showed improvements for these outcomes, but of lesser magnitude (see 

Tables 8a and 8b). Studies that used distribution of printed materials as part of the QI strategy 

showed a 1.7 mmHg improvement (IQ range: -0.2, 3.4) for SBP, and a 4.2 percent (IQ range: -

2.5, 10.6) increase in the proportion of patients achieving SBP in the target range. However, the 

latter was based on only four studies (Table 8a). Results for DBP improvements were lesser in 

magnitude. 

Patient Education 

A total of 33 studies (including 41 comparisons) included patient education as part of the QI 

strategy (see Table 2a). Patient education was utilized more than any other QI strategy. As 

described above, we included only studies that used patient education in conjunction with at least 

one other QI strategy. Studies that included patient education as part of the QI intervention had a 

median improvement of 8.1 mmHg for SBP (IQ range: 3.3, 11.8) and 3.3 mmHg for DBP (IQ 

range: 0.4, 5.0). These studies also reported improvement in percentage of patients achieving 

both SBP and DBP in the target ranges (19.2 percent, QI range: 10.3, 36.4; and 15.2 percent, IQ 

29
range: 7.3, 21.8 respectively) (see Table 6a, Appendix G). Only two studies that included patient 

education resulted in an increase in patient adherence of 1.9 percent and 2.8 percent (see Table 

6b, Appendix G). Only two studies with patient education QI strategies reported provider 

adherence outcomes; one showed a decrease of 1.3 percent and the other an increase of 2.0 

percent in provider adherence outcomes (see Table 6b, Appendix G).114, 128

 

Promotion of Self-management 

A total of 18 studies (including 20 comparisons) (see Table 2a) included patient selfmanagement as part of the QI strategy. As with patient education, this strategy was only included 

if used in conjunction with other strategies. Studies that used patient self-management, in 

combination with other strategies, showed a median improvement in SBP of 3.6 mmHg (IQ 

range: 2.1, 9.5) and a median improvement in DBP of 2.1 mmHg (IQ range: 0.4, 5.0), and an 

increase in percentage of patients with either SBP in the target range (13.4 percent, one study) or 

DBP in the target range ( median improvement 9.4 percent; IQ range: 1.1, 13.4; five studies) (see 

Table 6a, Appendix G). Only one study assessed the effect of promotion of self-management on 

patient adherence, and this showed a positive effect (see Table 6b, Appendix G). 

Patient Reminders 

A total of 16 studies (including a total of 22 comparisons) included patient reminders as a 

component of the QI strategy, or alone (three comparisons). Studies that used patient reminders, 

alone or in combination, showed a median reduction in SBP of 2.8 mmHg (IQ range: –1.5, 5.1), 

virtually no reduction in DBP (median effect 0.5 mmHg; IQ range: –2.1, 3.4), and increases in 

the overall percentages of patients with SBP and DBP in the target ranges (7.0 percent and 9.4 

percent, IQ range: 1.1, 19.0, respectively). However, only one study reported SBP target range 

results (see Table 6a). No studies using patient reminders reported provider or patient adherence 

outcomes. 

Organizational Change

Organizational change was assessed in 36 studies (including a total of 45 comparisons), 

either alone (six comparisons), or in combination with other strategies. The most common types 

of organizational changes implemented were team staffing changes (e.g., addition of a new 

member to the health care team or a change in existing roles). Overall, studies including 

organizational change as part or all of the QI strategy demonstrated median improvement in SBP 

of 10.1 mmHg (IQ range: 3.9, 14.0), compared with a 2.3 mmHg median improvement for 

studies without an organizational change component (P = 0.007). Given the multiple 

comparisons for the Mann-Whitney significance test, even this low P-value may still be

borderline. Studies including organizational change also showed median improvement in DBP of 

4.4 mmHg (IQ range: -0.50, 6.9), at a potentially significant level, compared with studies that did 

not have an organizational change component (median improvement in DBP of 1.1 mmHg for 

studies without organizational change component; P = 0.04 for comparisons with, versus 

without, organizational change) (see Table 6a). The percentage of patients with SBP in the target 

range had a median improvement of 21.8 percent (IQ range: 9.0, 33.8), and DBP in the target 

30
range had a median improvement of 17.0 percent (IQ range: 4.2, 24.5) (see Table 6a). Studies 

utilizing organizational change had a median improvement in patient adherence by 6.8 percent 

(IQ range: 1.9, 11.6), but provider adherence appeared unaffected (median effect 0.4 percent; IQ 

range: -1.6, 3.3) (see Table 6b). 

Substrategies of Organizational Change 

Because organizational change included several types of QI substrategies, we performed 

additional analyses for some of the commonly used substrategies. These included disease/case 

management, team staffing changes, use of telemedicine, and changes to medical record systems. 

Studies that included disease management/case management showed a median reduction of SBP 

of 14.1 mmHg (IQ range: 11.6, 16.4) and a median increase in the proportion of patients who 

achieved SBP in the target range of 4.2 percent (IQ range: -2.5, 10.3) (see Table 8a). Studies 

including the substrategy of team staffing change showed increases in the proportion of patients 

achieving SBP and DBP in target ranges of 21.8 percent (IQ range: 9.0, 33.8), and 19 percent (IQ 

range: 17.0, 30.0), respectively (see Table 8a). Studies including team staffing changes also 

showed a median increase in patient adherence of 6.8 percent (IQ range: 1.9, 11.6) (see Table 

8b). Studies including telemedicine and changes to medical record systems had less of an effect. 

In these studies, none of the substrategies appeared to demonstrate an effect on provider 

adherence. 

Financial Incentives

Only three studies (including a total of three comparisons) included financial incentives as 

part of the QI strategy. Quantitative analysis was limited due to the small number of studies. One 

study reported a better improvement in the control group, which had a reduction of 13 mmHg 

SBP, relative to the intervention group. In this study, the control group had a higher mean BP at 

baseline, and achieved a post-intervention BP similar to that achieved by the intervention group, 

for an overall greater decrease in SBP in the control group. Three studies assessed the impact of 

financial incentives on DBP reduction: the median effect was 0.0. Two studies assessed the 

impact of financial incentives on the proportion of patients achieving SBP in a certain range, and 

showed an improvement in one study but not the other (see Table 6a and 6b). No studies using 

financial incentives reported outcomes for DBP range, provider or patient adherence. 

Other Analyses 

Clinical Information Systems 

Nineteen studies (reporting 25 comparisons) used information systems in some aspect of the 

quality improvement strategy. Eight studies (reporting 12 comparisons) used them to identify 

eligible participants for study enrollment, eight (reporting 12 comparisons) included a clinical 

reminder based on an existing information system, two (reporting two comparisons) included a 

clinical decision support system, four (reporting five comparisons) included the collection of 

31
audit data based on an information system, and 14 (reporting 16 comparisons) included some

other aspect of an information system. Tables 9a and 9b show the effect sizes of blood pressure 

and adherence outcomes for studies that included various uses of information systems, and 

reported quantitative results adequately for calculating median effects. Studies that included use 

of a clinical information system had a median effect on SBP reduction of 2.2 mmHg (IQ range: 

1.1, 4.2), and on DBP reduction of 0.6 mmHg (IQ range: -1.3, 2.1). The median effect on 

proportion of patients in SBP target range was a decrease of 1.4 percent (IQ range: -3.6, 5.3), and 

in DBP target range was an increase of 1.8 percent (IQ: 0.1, 4.3). These effects were generally 

less than the effects seen in studies without information systems, particularly for the SBP in 

range outcome (Mann Whitney P = 0.03). There was a median effect increase of 2.7 percent (IQ 

range: -0.4, 5.0) in the proportion of providers adherent to recommended practice with the use of 

clinical information systems, and no apparent effect on the proportion of patients adherent to 

recommendations. 

In a number of studies (see Table 9a and 9b), information systems were used only to identify 

eligible participants for the study, and may even have been used for both intervention and control 

groups. When information systems were used this way, they may have contributed to the 

feasibility of the study by facilitating the identification of potential participants, but would not 

have been expected to contribute to improvements in outcome. 

A small numbers of studies reported outcomes for use of information systems to generate 

reminders either to patients or to providers, and results were mixed. Two comparisons (from a 

single study) using a clinical decision support system reported SBP and DBP outcomes, with 

reductions in SBP of 1.0 mmHg in one comparison, and 1.5 mmHg in the other, but an increase 

in DBP of 2.0 mmHg in the first, and a reduction of 0.6 mmHg in the second comparison (Table 

9a). One study, including two comparisons reporting SBP and DBP outcomes used an 

information system to generate audit data. These comparisons also showed mixed results. Three 

studies with four comparisons reported the increase in proportion of patients achieving DBP in 

target range; the median effect was an increase of 3.5 percent (IQ range: 1.0, 5.5). 

The small number of studies using information systems, and the variability in their roles with 

respect to QI strategies, limit the conclusions that can be drawn about this particular intervention. 

Analysis of Number of Quality Improvement Strategies on Outcomes 

The majority of studies employed a combination of QI strategies, rather than a single 

intervention (see Tables 3 and 4). The effect on blood pressure and adherence outcomes as a 

function of the number of QI strategies employed is shown in Tables 7a and 7b. For both SBP 

and DBP reductions, there was no clear pattern of increasing or decreasing effect as the number 

of QI strategies increased. For the SBP outcomes, the Mann-Whitney analysis comparing single 

QI strategies to multifaceted QI strategies (i.e., two or more QI strategies) had a P-value of 0.029 

favoring single QI strategies, which has borderline significance given multiple comparisons. The

results are likely confounded because the studies in the single QI strategy group use primarily 

organizational change strategy (i.e., three of five studies for SBP outcomes, and four of six 

studies for DBP outcomes). When assessing the percentage of patients with SBP in the target 

range, the largest increase was reported in studies employing two QI strategies, but this pattern 

was not present for DBP (Table 7a). There is no clear pattern of effect of number of QI strategies 

on adherence outcomes in our analysis, but again, there are few studies included in this analysis. 

32
Effect of Methodologic Features 

We critically reviewed studies to discern major features in study design or analysis that were 

likely to affect their results. The methodologic features that we considered were random 

allocation of subjects to the intervention, blinding of providers to the treatment status, blinding of 

patients to the treatment status, unit of analysis the same as unit of allocation, and concealment 

of the allocation. These desirable study design features, when present, improve the likelihood 

that the effects observed in the study represent true effects. We assessed the relationship between 

these methodologic features and outcomes, including reported decreases in blood pressure 

(systolic and diastolic), increased percentage of patients with blood pressure in target ranges, 

percentage of providers adhering to recommended practices, and patient adherence to 

recommended practices. 

Effect of Methodologic Features on Blood Pressure Outcomes 

As previously noted, 33 comparisons assessed reduction in SBP, and 43 comparisons 

assessed reduction in DBP. The majority of these were randomized controlled trials (25 of 33 (76 

percent) of the comparisons assessing SBP; 33 of 43 (77 percent) of the comparisons assessing 

DBP (see Table 10a). Neither patients nor providers were blinded in the majority of studies. Unit 

of analysis was the same as the unit of allocation in two-thirds of the comparisons reporting SBP 

and DBP. However, in comparisons reporting target range outcomes, there were proportionally 

less studies with this design feature: only 29 percent of the SBP in target range comparisons, and 

56 percent of the DBP in target range comparisons (see Table 10b). Concealment of allocation 

occurred in the minority of studies with SBP and DBP outcomes, but in the majority of studies 

with target range outcomes. With the exception of concealment of allocation, studies having 

positive design features had better median reduction in SBP; however, the inter-quartile ranges 

had substantial overlap, and Mann-Whitney tests did not show any significant differences by 

design feature. For other blood pressure outcomes, the comparative results by design feature 

were more mixed (e.g., RCT comparisons had lower values than non-RCTs for DBP and DBP in 

target range outcomes, while RCTs examining SBP in target range outcomes had higher values 

for this outcome than non-RCTs ), with no design feature analysis showing significance. 

After stratifying studies by study design (RCT versus non-RCT), we analyzed the effect of 

individual QI strategies on blood pressure outcomes, comparing studies that included a particular 

QI strategy with those that did not include that particular QI strategy (e.g., studies with provider 

education versus studies without a provider education component) (see Table 11). Overall, the 

median reduction in SBP in RCTs was 6.8 mmHg (compared with 4.5 mmHg when both CBAs 

and RCTs are included, or 4.3 mmHg for non-RCTs), and median reduction in DBP was 2.0 

mmHg (compared with 2.1 mmHg when both CBA and RCTs are included, or 2.7 mmHg for 

non-RCTs). In general, analysis of categories of QI strategies according to study type revealed 

zero or minimal change in median reduction in SBP and DBP effects. For example, when 

analyzing RCT studies alone, the effect of organizational change on median reduction in SBP 

was 11.0 mmHg (IQ range: 5.2, 16.2), in contrast with a reduction of 10.1 mmHg (IQ range: 3.9, 

14.0) seen with all study types (19 comparisons). The largest magnitude change for study type 

substratified by QI strategy was for RCT comparisons reporting provider reminders, with a 

median reduction in SBP of 3.0 mmHg (IQ range: -0.8, 6.8), in contrast to a reduction of 6.8 

33
mmHg (IQ range: 3.0, 9.4) seen with all studies. However, there were very few studies (three 

comparisons overall, and two RCTs) reporting the effect of use of provider reminders on 

reduction of SBP.113, 122, 153

 

Visual examination of Table 11 reveals that studies that included either organizational 

change (alone or in combination with other strategies) or patient education (in combination with 

other strategies) consistently report greater improvements in SBP and DBP, regardless of study 

design, as compared with studies without these particular strategies. Studies without patient 

reminders or provider audit and feedback (either alone or in combination) are similarly 

consistent in having greater improvements in SBP and DBP as compared with studies that 

included these strategies. For studies with other strategies, the results are less consistent by both 

outcome and study design. 

Effect of Methodologic Features on Provider and 

Patient Adherence to Recommendations 

Eight studies (10 comparisons) assessed provider adherence to some aspect of recommended 

care of hypertensive patients. The majority of these studies were RCTs (see Table 10c). Studies 

having positive design features had greater improvements in provider adherence to 

recommended practice, but the inter-quartile ranges had substantial overlap, and Mann-Whitney 

tests did not show any significant differences by design feature. Because of the limited number 

of studies, we did not assess QI strategies by design feature for provider adherence outcomes. 

Only four studies (five comparisons) assessed patient adherence. Of these, three were RCTs 

and two were not (see Table 10c). Because of the small numbers of studies, the point estimates 

would have been imprecise, so we did not assess the impact of methodologic quality on patient 

adherence outcomes. 

Effect of Study Size on Blood Pressure Outcomes 

Table 12a reports the association of sample size with SBP outcomes. Results are shown for 

studies that include each QI strategy, followed by studies that do not include that QI strategy. 

The studies with the smaller sample sizes appear to report larger effects on reduction in SBP. 

The Spearman rank correlation of effect size with sample size is 0.43 for SBP (P = 0.01). Table 

12b shows a similar analysis for reduction in DBP. Again, the smaller studies appear to report 

larger effects, although this is not as pronounced. The Spearman rank correlation of effect size 

with sample size for DBP is 0.23 (P = 0.14). To explore possible confounding of sample size 

with study design, we estimated the Spearman rank correlation separately for trials that had the 

desirable study design feature of unit of analysis equal to unit of randomization, and for studies 

that did not have this design feature. For studies without this desirable design feature, the 

Spearman rank correlation of effect size with sample size for SBP was 0.02 (P = 0.53, N = 12), 

indicating no correlation, and -0.36 (P = 0.21, N = 14) for DBP, indicating larger effects for 

larger sample size studies. Since these studies require adjustments to sample size to account for 

patient clustering, the more appropriate Spearman rank correlation comparison is between effect 

size and effective study sample size (Appendix H), which for SBP is 0.01 (P = 0.97), and for 

DBP is 0.07 (P = 0.83), indicating no correlation after adjustments to sample size. In contrast, for 

studies in which the unit of randomization is the same as the unit of analysis, the correlations 

34
between sample size and effect size persisted, with a correlation of 0.58 (P = 0.006, N = 21) for 

SBP, and 0.40 (P = 0.030, N = 29) for DBP. Thus, the studies with differing unit of analysis and 

unit of randomization do not appear to be responsible for the correlations between study size and 

effect size for SBP and DBP; thus analysis by quartile of actual sample size is adequate. Also, 

non-RCT studies did not have a correlation between study size and effect size. 

Correlation analysis for SBP and DBP in target range did not show any significant results, 

though the magnitude of the rank correlation for SBP range was -0.37 (P = 0.21), indicating a 

similar trend toward larger studies having less improvement (lower proportion of patients in 

range compared with smaller studies). 

Visual inspection of Tables 12a and 12b reveal a somewhat consistent pattern for specific QI 

strategies across both blood pressure outcomes, when considering sample size. For example, as 

reported earlier, studies that include organizational change have improvements in SBP of 10.1 

mmHg, and in DBP of 4.4 mmHg, as compared with 2.3 mmHg and 0.6 mmHg, respectively, for 

studies without an organizational change component. For studies reporting SBP outcomes that 

are in the bottom half of study sample size, those that include organizational change (12 

comparisons) show improvements in SBP of 13.5 mmHg, while those that do not include 

organizational change (four comparisons, none of which would fall into the bottom quartile of 

study sample size) show effectively no improvement in SBP (0.1 mmHg). For studies reporting 

SBP outcomes that are in the top half of study sample size, those that include organizational 

change (seven comparisons, including five in the largest study size quartile,) and those that do 

not (10 comparisons, including four in the largest study size quartile), have similar magnitude 

improvements (3.3 mmHg versus 3.6 mmHg). A similar trend of effect sizes eroding with study 

size is seen for DBP, though perhaps to a less striking degree, as the studies with organizational 

change still appear to show greater improvements in DBP as compared with studies without 

organizational change (2.8 mmHg versus 1.6 mmHg). For the largest study size quartile, 

however, the relative magnitudes of DBP outcomes reverse, which occurs for SBP outcomes as 

well. 

35
36
Chapter 4. Discussion 

Hypertension is highly prevalent in the general population, and carries with it serious 

cardiovascular morbidity and mortality risks. The implementation of quality improvement 

strategies aimed at detection and management of this disease has the potential to improve the 

health of millions of Americans. 

Our review of more than 3000 titles, which identified 82 core comparisons relating to the 

general areas of disease screening and management of hypertension, confirms some previous 

findings and extends them, with the addition of recent studies and further analyses.50, 52 Of the 

studies meeting our inclusion criteria, one-third were published in the past five years (1998–

2003). The main questions we sought to answer were which QI strategies could most effectively 

result in improved detection of hypertension, blood pressure control, and improved patient and 

provider adherence. Our findings suggest that quality improvement strategies in general appear

to be associated with improved detection and control of hypertension. Since most studies 

included more than one QI strategy, it is not possible to discern with complete confidence which 

QI strategies have the greatest effects. All of the strategies assessed—organizational change, 

patient education in combination with several other QI strategies, provider education, facilitated 

relay of clinical data, audit and feedback, promotion of self-management, provider reminders, 

patient reminders, and financial incentives—may be beneficial under some circumstances, and in 

varying combinations. Studies with organizational change had the largest effect on outcomes in 

general, a finding which persisted regardless of study design (e.g., RCTs versus CBAs or quasiRCTs). However, after analysis of study sample size, which raised a concern about publication 

bias, these findings are less convincing. Studies including patient education as part of the QI 

strategy also appeared to have relatively larger effects, but these results are also confounded by 

study size, and are additionally uncertain because studies examining patient education alone 

were not reviewed in this report, but rather set aside for a subsequent review in the series. 

Finally, studies with audit and feedback did not show as much improvement in outcomes as 

studies without this strategy, but there were relatively few studies reporting multiple outcomes 

that included this strategy. Although conclusions about specific strategies require caveats, QI 

strategies in general appear beneficial for closing the quality gap in hypertension. 

Which QI Strategies Improve Screening for Hypertension? 

Increasing the percentage of individuals screened for hypertension is a critical national health 

goal. In general, most interventions led to some improvement in the intervention group, such as 

an increased number of individuals screened, an increased number of individuals who knew 

whether or not their blood pressure was elevated, or an increase in those identified as 

hypertensive who received appropriate followup. No single QI strategy had enough screening 

studies to provide pooled results, and therefore discussion of each strategy independently is not 

feasible. 

Screening interventions were generally conducted in one of two environments: in the 

community (outside of medical settings), or at medical clinics. In the community, interventions 

at work sites appeared to be effective.138, 166 In the clinic, several strategies appeared effective. 

37
These include patient reminder letters, computer identification of patients with historically poor 

followup along with computer-generation of provider reminders about these patients, and the 

addition of a health promotion nurse to identify and followup with high-risk patients (Table 5). 

Because there were few studies of screening (10), and because of the heterogeneity of the 

outcomes measured, we were unable to conduct quantitative analyses of the impact of 

screening.†

Which QI Strategies are Most Effective at Ensuring that 

Blood Pressure Goals are Achieved and Maintained? 

Most of the quality improvement strategies we assessed had a positive impact on at least one 

of the blood pressure outcomes measured. The only outcome measures reported frequently 

enough for data analysis were reductions in SBP and DBP, and achieving SBP and DBP in target 

ranges. Most studies used more than one QI strategy. Thus, the following results, presented by 

type of QI strategy, must be interpreted with caution. 

With this important caveat, the largest effect sizes for SBP and DBP reductions were

observed in the strategies of organizational change, provider reminders (either alone or in 

combination with other QI strategies), and patient education (reviewed only in combination with 

other strategies, and often including organizational change). 

For achieving SBP and DBP in target range, most of the strategies appeared to be effective, 

but were often used in combination. The strategies with larger effects include organizational 

change, patient education, promotion of self-management, and facilitated relay of clinical data 

(usually in combination with organizational change as well as other strategies). Audit and 

feedback, patient reminders, and financial incentives showed relatively more modest effects, 

although there were generally fewer studies of these interventions. 

Effect of Specific QI Strategies on Achieving 

And Maintaining BP Goals 

 Studies that included organizational change tended to report larger effects on blood pressure 

outcomes than studies that did not include this QI strategy. Organizational change strategies are 

varied, and some substrategies of organizational change may work better than others. Case 

management and team staffing changes often appeared effective. The vast majority of studies of 

organizational change in hypertension included changes in team members’ roles, additions of 

staff, or other re-organization of work flow for caring for hypertensive patients. 

There are many possible explanations for the success of organizational change with respect 

to achieving blood pressure control. Organizational change typically requires administrative 

 

† The MRFIT and the HDFP trials do not appear in our analysis of screening because these studies performed screening solely to

identify individuals to be enrolled in the disease management portion of those studies, not as an outcome related to the

intervention. We report results from these studies in Appendix F. Another large screening study, the North Karelia Project,169

is omitted from our systematic review because it was conducted before our inclusion date of 1980. 

38
support, which may itself be an important factor in the success of a QI strategy. Many studies of 

organizational change include designation of specific staff to address hypertension, which may 

represent either an increase in staffing or a re-allocation of staff effort to hypertension; in either 

case, it could represent an absolute increase in health professional time allocated to hypertension. 

However, it is also possible that an organizational change could achieve an effective increase in 

attention to hypertension by re-designing work flow without increasing the overall staffing 

devoted to hypertension management. Most studies did not report information that would allow 

us to make this distinction. The finding of the effect of organizational change is consistent with a 

report from an observational study of the Veterans Affairs Health Care System, which found 

moderate improvements in rates of blood pressure control after implementation of systemwide 

reengineering.170, 171 A randomized clinical trial published too recently to be included in our 

analysis confirms the major impact that organizational change may exert on blood pressure 

outcomes. Among 309 inner city African American men, comprehensive interventions in the 

community, by a multidisciplinary team, resulted in 44 percent of the subjects having controlled 

blood pressure (compared with 17 percent at baseline).172

Patient education appeared to be a successful strategy for improving blood pressure control, 

but we evaluated it only when it was used in conjunction with other QI strategies. Therefore, the 

impact of patient education per se may be overestimated in the studies we included. Our findings 

that patient education may be effective in improving blood pressure comport with those of a 

previous meta-analysis.50 However, although patient education produced the largest reduction in 

blood pressure of the various methods studied in one systematic review,52 one particular study 

(which combined a number of interventions along with patient education) accounted for most of 

this finding. Our analysis does not allow for an evaluation of the efficacy of patient education as 

a sole QI strategy for blood pressure control. 

Our findings on provider education differ from the negative findings in one previous, smaller 

review of physician education interventions in the management of hypertension.68 However, in 

our review, provider education was usually accompanied by other QI strategies, so the effect on 

outcomes attributable to provider education or its substrategies is not known. 

Other strategies, such as provider reminders, promotion of patient self-management, and 

audit and feedback, all appear to have relatively modest effects, and, when positive, were often 

coupled with other strategies as part of a multifaceted intervention. Our findings regarding 

promotion of patient self-management on BP control are consistent with those of a previous 

meta-analysis, and a systematic review.50, 52

Our findings regarding audit and feedback are consistent with the conclusions of a recent 

systematic review of that strategy, which states: “when it is effective, the effects are generally 

small to moderate.”173 The studies of audit and feedback in hypertension are a small subset of the 

studies in this review, and highlight the difficulty of interpreting results of specific QI strategies 

for a selected clinical area. While a strategy may be more or less effective in one clinical area 

compared with another, the ability to detect such differences, or lack thereof, are hampered by 

the limited number of studies for any particular strategy, as well as the confounding due to 

multifaceted interventions and study quality. 

39
Which QI Strategies Improve Provider Adherence with 

Recommendations for Management of Hypertension? 

Surprisingly, the median increase in percentage of providers adhering to recommendations 

was relatively small, or even negative, for all QI strategies (median effects ranged from a 1.3 

percent reduction to 3.3 percent improvement in adherence across the QI strategies). Only 

limited conclusions can be drawn, because we found mixed results among the 10 comparisons 

with data on this outcome, and there was significant overlap of studies across QI strategies. We

also note that most of the studies reporting provider adherence outcomes are different from the 

studies that report blood pressure outcomes. Provider adherence included adherence with 

recommended medications, as well as adherence with other recommended practices, such as 

appropriately ordered laboratory tests. It is important to recognize that although guidelines 

recommending specific antihypertensives for treatment of particular comorbidities are evidence 

based,1

 there was not always an evidence base supporting the adherence outcomes we analyzed 

in the studies we reviewed. 

There are a number of possible contributing factors that may explain the finding of the 

limited impact of QI strategies on provider adherence to recommended practice, if in fact this is a 

true effect. Past controversies in the medical literature about the relative importance of DBP 

versus SBP, as well as frequent change to overall targets for hypertension control, may have led 

to some provider confusion about appropriate targets for BP control. The large number of drugs 

available to treat hypertension, and the promotion of certain drugs for certain classes of patients, 

may also lead to some provider confusion. It is also possible that some providers do not agree 

with the guideline recommendations. For example, early trials using the thiazide class of 

diuretics used larger doses that were commonly associated with hypokalemia, a potentially 

serious problem. It is now known that much smaller doses, only rarely associated with 

hypokalemia, are effective in most patients; however, providers may still be reluctant to use them

due to prior adverse effects on their patients. Because medical decision making is prone to 

“availability bias,” a single negative outcome may be remembered vividly, and may exert undue 

impact on future decisions.174 

A systematic review examining barriers to physician adherence to clinical practice guidelines 

identified a number of potential barriers (e.g., lack of awareness, inability to reconcile patient 

preferences with guideline recommendations, lack of resources).175 This review noted that studies 

on improving physician guideline adherence may not be applicable across specialties or practice 

settings, as barriers in one setting may not be present in another.175 Practice “inertia” may also be 

a barrier. The theme of “inertia” of previous practice has been attributed to at least three 

problems: overestimation of care provided; use of “soft” reasons to avoid intensifying therapy; 

and lack of education, training, and practice organization aimed at achieving therapeutic goals.176

The apparently small effect of QI strategies on provider adherence outcomes is a finding that 

deserves future attention, because of the importance of provider behavior in attaining goals of 

improved hypertension outcomes. As described in a systematic review from the National Health 

Service in the United Kingdom,

52 a greater health gain could theoretically be obtained by 

improving professional standards of detection of hypertension and the proportion of patients with 

hypertension receiving treatment, as compared with the expected health gains from

improvements in patient adherence to treatment. Although the applicability of these data to the 

40
United States may be limited, the analysis serves to emphasize the key role of provider 

adherence in improving hypertension outcomes. 

Which QI Strategies Improve Patient 

Adherence with Treatment? 

Use of patient education (in combination with other strategies), organizational change, 

facilitated relay of clinical data, and patient self-management as part of a QI strategy may have 

all improved patient adherence. However, relatively few studies assessed this outcome, and thus 

the evidence base is limited. Our findings that patient education may be effective in improving 

patient adherence are consistent with those of a previous meta-analysis, which found that patient 

education appeared to be effective in improving adherence with medications, and improving 

adherence with appointments.50 We note again that the effect of patient education may be 

overestimated in the included studies, since patient education was never analyzed when it 

appeared as the sole component of an intervention, only when it was considered in combination 

with at least one other QI strategy. 

Importance of Organizational Setting for 

Quality Improvement Interventions 

Implementation of a QI strategy is essentially an attempt to change human behavior, either of 

health professionals or of patients. In studies of QI strategies, the organizational context of the 

study is very likely to have an impact on the effectiveness of the QI strategy. For example, if a 

QI strategy is implemented in a health care system despite objections from most of the 

professional staff, one would expect the likelihood of success to be lower than if the 

implementation enjoys the support of the staff, since it is staff who must carry out the strategy. 

Moreover, whether a given organizational strategy happens to mesh with existing features of an 

organization (such as its values or staffing patterns) may be a more important determinant of 

success than the QI strategy per se. 

We also recognize that over the period of time—more than twenty years—of the studies we 

have included, there have been many changes in health care delivery systems that may affect the 

organizational context for QI implementation. We were not able in this evidence review to 

account for the impact of organizational context, because little information about it is presented 

in the published papers. We do report the setting of each study (see Table 1 and Appendix F), 

and readers who are contemplating implementation of a QI program may consider the similarity 

of the reported settings to their own, and the feasibility of implementation of the strategy in their 

own context. We also provide the actual results of each of the studies meeting the standards for 

inclusion, so that readers may consider the actual results of strategies that they may want to 

replicate. 

41
Study Design Effects

Studies that are less methodologically rigorous may present more impressive-appearing 

findings, because less care was taken to correct for potential biases. Our analysis suggests that 

methodologic features affected some findings for QI strategies for hypertension. We found a 

fairly striking correlation between study size and effect size, particularly for SBP and DBP 

outcomes: larger studies reported less impressive reductions in blood pressures. This pattern did 

not hold for each individual QI strategy, but some individual strategies were used in very few 

studies. In further exploring possible confounding of study size with other study design features 

for the SBP and DBP outcomes, we found that studies in which the unit of randomization was 

the same as the unit of analysis appeared to account for the correlations between study size and 

effect size. 

Our findings regarding the relationship between other study design features and effect size 

were mixed. For example, there was no clear relationship of RCT-study-design with effect size; 

findings differed for different outcomes. 

Effect of Number of QI Strategies 

We did not find a consistent pattern of improved outcomes with an increased number of QI 

strategies, and in fact, found that single QI strategy studies had larger effects compared with 

multifaceted QI strategies. However, our findings should be interpreted with caution because of 

the small number of studies, the large inter-quartile ranges, and possible confounding since most 

of the single QI strategies involved organizational change. Prior reviews have reached 

conflicting conclusions about the relative impact of adding more QI strategies, irrespective of 

their content.45, 83, 173, 177 

Additional Comments 

Multiple risk factors. Many of the quality improvement strategies targeted hypertension as 

one of several risk factors to be controlled (e.g., for cardiovascular disease risk reduction). This 

confounded our ability to draw conclusions about the effect the specific QI strategy component 

had on hypertension, as distinct from the other risk factors. 

Sources of variation in measurements of blood pressure. Many different blood pressure 

thresholds have been used to assess quality of care,178 including percentage of patients with 

blood pressure exceeding a particular control threshold. Guidelines defining control have 

changed over time. This situation has implications with respect to the conclusions that can be 

drawn from studies reporting interventions that showed positive effects on achieving blood 

pressure control. For instance, some QI studies, particularly older studies, used control thresholds 

such as 160/95, whereas many recent studies define the control threshold at 140/90. Some

hypertension quality of care studies used mean blood pressures for a particular patient over a 

number of visits, to determine whether they met control thresholds, whereas others used single 

visit blood pressure readings. The use of varied definitions of control, and different measurement 

techniques to determine control, may result in different judgments of quality of care.178 

Effect of QI interventions on mortality. Few studies reported mortality measures, perhaps 

because most quality improvement studies did not have a long enough study period or large 

enough study populations. For the six studies that did report mortality data, only two reported 

42
mortality as a primary outcome measure. The MRFIT study reported a lower mortality rate at 

ten-year followup that was not statistically significant.105 The HDFP study, however, showed 

reduced mortality of 16.9 percent with stepped care.20 It is not possible to state what portion of 

the mortality benefit was due to the special components of the intervention that might be 

considered QI strategies, and what portion was due to the choices of drug therapy or other 

factors; however, overall, the application of the strategy was effective. With refinements to drug 

therapy since that time, for example the recognition that lower dose thiazide diuretics achieve 

reduction of blood pressure with fewer episodes of hypokalemia, it is possible that application of 

QI strategies such as those used in the stepped care program would be even more effective today. 

On the other hand, at the time that the HDFP study was conducted, the importance of treating 

systolic hypertension was not well-recognized, and the overall targets for BP control were 

higher. It is possible that application of the same strategies today would appear less effective in 

comparison to usual care, because current usual care includes treatments that were not then in 

use.

Relationship of reduction in average BP with improvements in percent of patients 

achieving BP in target range. For some QI strategies, the median effect on SBP or DBP does 

not correlate consistently with the median effect on improving the proportion of patients in SBP 

or DBP target range. For example, for some strategies, the decrease in BP was small, but resulted 

in a substantial increase in the percentage of patients in a target range, and vice versa. The 

relationship of reduction in the average BP with improvement in the percent of patients 

achieving BP in target range depends on several factors, including the baseline average BP, the 

variance in the BPs, and the baseline percent of patients in target range. Depending on the 

distribution of blood pressure and the range chosen as acceptable, a small change in mean BP 

can result in either small or large changes in the percentage of patients in the acceptable range. 

For a more detailed explanation, see Appendix I. 

Potential benefits of clinical information systems. Studies that used a clinical information 

system had mixed effects, including some negative effects, in blood pressure outcomes and 

provider adherence. In light of the high expectations for information technology to improve 

health care, our findings from the studies published to date are disappointing. The potential for 

information technology to improve the quality of health care has been described by the Institute 

of Medicine as “enormous.”179 A systematic review by Balas, et al, of 98 randomized clinical 

trials of computerized information services showed that about 75 percent reported substantial 

improvements.180, 181 Considerable evidence, summarized in systematic reviews, shows that 

automated reminder systems improve provider adherence to clinical practice guidelines.179, 180,

182, 183 Another systematic review of 68 controlled clinical trials assessing the effects of 

computer-based clinical decision support systems (CDSSs) on physician performance and patient 

outcomes found enhanced clinical performance for drug dosing, preventive care, and other 

aspects of medical care, but insufficient evidence regarding improvement in patient outcomes.184

A 1998 systematic review of the use of computers in the management of hypertension showed 

that computers appeared to have a favorable effect on the uptake and followup of patients in 

hypertension management; however, the effect on blood pressure control was less conclusive.145 

We believe that it would be premature to draw conclusions based on the overall effects for 

clinical information systems. In many studies, the information systems used were only to identify 

eligible patients. Many medical centers and clinics are only now adopting electronic medical 

record systems that will permit smooth integration of clinical decision support with clinician 

work flow. In many cases, information technology that has been developed in academic research 

43
centers has yet to be tested in large clinical trials. Decades of research have produced an 

infrastructure in medical informatics to support health care research and quality.185 With further 

development of the infrastructure, new clinical trials will undoubtedly be conducted, and may 

yield different results from the few studies published to date. 

Limitations in Interpretation of the Data 

Conclusions based on pooled data are tentative, and must be interpreted cautiously. Each 

quality improvement study was conducted within a particular set of contexts, including practice 

type, era of guideline recommendations, local attitudes toward guideline implementation, and 

other potentially confounding factors. Nevertheless, although hypertension guidelines have 

changed over time, studies using older guidelines can provide useful evidence about whether or 

not quality improvement strategies work. 

As with all systematic reviews, there is the possibility of missing relevant studies. For 

example, in this instance, studies that focus on a particular quality improvement strategy for 

broad application may have included hypertension, without specifying its inclusion in the title, 

abstract or subject headings, and would therefore be missed by our search strategy.186 

Recommendations for Future Research on 

Quality Improvement Implementations 

Based on our review of published reports of QI strategies for hypertension, we offer several 

suggestions for future QI implementation research: 

Clustering issues. The impact of the randomization choice should be discussed in published 

studies, and steps taken to account appropriately for clustering in the data analysis. Numbers of 

clusters and descriptive statistics of numbers of patients per cluster should be reported. An 

updated Consolidated Standards of Reporting Trials (CONSORT) statement specifically 

addressing cluster-randomized trials is in press.187–189 

Blinding in measurement of study outcome. Providers performing clinical examinations 

may be unconsciously biased by prior expectation of a particular result.190 In a study in which the 

provider who measures the patient’s BP knows that a patient is receiving a QI intervention, the 

outcome measure may be unconsciously biased by an expectation of improvement. When the 

provider is also the individual who delivers the QI intervention, the prior expectation of benefit 

may be even more powerful, and the unconscious bias greater. Reports should specify whether 

the outcomes were measured by individuals who were blinded to the intervention status. 

Pre- and post-intervention measures for both intervention and control group. Baseline 

differences between the intervention and control groups can have major effects on outcome

measures. Reports should report both pre- and post-intervention measurements for both control 

and intervention groups, and should take account of baseline differences in statistical analyses, 

for example, by comparing change from baseline. 

Organizational factors affecting QI interventions. Aspects of the organizational structure 

and setting of the providers’ clinical practice may affect incentives to follow guidelines. For 

example, providers employed in a health care system would be expected to respond differently to 

recommended guidelines when a criterion of their performance standard includes adherence to 

such guidelines, as compared with independent providers, who may electively determine whether 

44
or not to implement guidelines. As another example, when guidelines are recommended by a 

health insurance plan, adherence among providers with a large proportion of patients enrolled in 

that particular plan may differ as compared with providers whose patients are enrolled in many 

different plans. Further examples include extent of administrative support for the QI 

implementation. There is not, however, a clear consensus about how to define or measure such 

organizational factors. Possible factors to report in future studies include, among others:

• Descriptive information about organizational arrangements of providers in the study, for 

example, status as employees or independent practitioners. 

• Descriptions of time constraints on clinical practice. 

• Descriptive information about incentives for providers to follow recommended 

guidelines, for example, use of rates of guideline adherence in credentialing, performance 

review, or other processes. 

• Description of the types and extent of administrative support and involvement of local 

clinical leadership; for instance, reports could include whether the QI strategy was 

implemented with research funds, administrative funds, or both, description of 

administrative support, and, if relevant, how this support was communicated to staff. 

Number of QI activities concurrently implemented. The number of distinct QI 

implementations within a health care clinic or system may affect responses of both providers and 

patients. On one hand, providers or patients who receive many QI interventions may become less 

attentive to the interventions. On the other hand, providers or patients who become accustomed 

to QI interventions may incorporate a new approach to management of disease and may be more 

likely to adhere to guidelines. In order to evaluate the impact of such effects so that such 

questions may be addressed in future research, possible factors to report include: 

• Number of programs in different areas being implemented concurrently in the study 

setting in which the QI strategy is being evaluated 

• Information on the organizational culture regarding attitudes toward guideline 

implementation and QI strategies 

Adverse effects of the QI intervention. As with all effective treatments, QI 

implementations have the potential for unintended adverse consequences. To date, these are 

rarely reported. Additionally, there is as yet no clear consensus as to methods for attributing 

adverse effects to a particular QI implementation, or which potential adverse effects to monitor 

and report. Because of this lack of consensus, studies of QI implementations rarely obtain 

information that would allow reporting of these factors. Candidate factors to consider include: 

• Adverse effects on individual patients that are potentially due to aggressive 

implementation of particular guideline recommendations, for example, for hypertension, 

rates of syncope, falls, and morbidity related to falls (e.g., hip fracture) compared 

between study arms. Such factors might be particularly important to monitor in QI 

implementations that include strong incentives to providers to achieve certain targets for 

BP; and 

• Adverse effects on populations of patients (e.g., the impact of guideline implementation 

for one disease on rates of guideline adherence for other diseases). Studies conducted in 

health care systems with clinical databases may be able to monitor database indicators of 

such rates. Another example might be the potential adverse effect of shifting staff 

resources from one area to another. It is well-recognized in cost-effectiveness analysis 

that it is essential to consider all the costs associated with an intervention, not merely the 

45
immediate costs of providing the intervention initially. Similarly, it may be important to 

consider the effect on an entire health care system of shifting resources within the system. 

Future QI reviews should consider adopting the CONSORT Statement, which provides a 

checklist of items to report in publications of randomized controlled trials.187 The Statement is 

intended to improve the reporting of trials, to enable readers to understand how the trial was 

conducted, and to assess the validity of the results. 

46
Chapter 5. Conclusions 

Our review found that QI strategies result in increased detection of hypertension, and 

improved management, as measured by blood pressure. However, we found only small changes 

in provider and patient adherence due to QI interventions. Studies that included organizational 

change and patient education reported greater improvements in blood pressure control than did 

studies without these strategies, but the evidence is not sufficient to definitively establish the 

superiority of any individual QI strategy relative to others. The reported improvements in blood 

pressure control were smaller in larger studies than in smaller studies, raising a concern that our 

overall measures of the effectiveness of QI strategies may be overestimated because of 

publication bias. 

Closing the quality gap will take sustained effort from the many parties with an interest in 

detection and management of hypertension. Our review documents the varied approaches to QI 

for hypertension that have received careful evaluation. The summary analyses provide a high 

level overview of these QI interventions. Perhaps as importantly, the details of individual studies 

offer a resource that may help guide further QI implementation and evaluation. 

Despite the many studies documented here, the evidence about the usefulness of QI strategies 

in hypertension care is incomplete. There is a strong need for further and more detailed 

evaluation. Future studies will be more useful if they are designed rigorously, describe QI 

interventions carefully, and provide information about the organizational setting in which they 

are performed. 

Each new attempt to close the quality gap in hypertension will likely need to be tailored to 

specific circumstances.42 We hope this report provides a useful starting point for individuals and 

organizations that are trying to improve the detection and management of hypertension, and for 

investigators attempting to further the field of quality improvement. 

“Some observers have suggested that the answer to this problem is to produce a 

seventh version of the Joint National Committee Report on Prevention, Detection, 

Evaluation, and Treatment of High Blood Pressure (JNC). Others counsel that 

what we need is not a new guideline but rather the will to implement what we 

already have, which is extensive. While JNC has been a valuable tool, it cannot be 

the only answer to controlling hypertension because it is an education tool, not an 

action tool. The application of the JNC... is what matters.” 

— Claude Lenfant, Director, NHLBI, from Reflections on 

Hypertension Control Rates. A Message From the Director 

of the National Heart, Lung, and Blood Institute191

47
48
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57

Figure 1. Search strategy and article triage

MEDLINE

59

249 Exclusions

R1: 96 

R2: 4 

R3: 65 

R4: 2 

R5: 29 

R6: 22 

R7: 22 

R8: 9 

Stage 1: title & abstract review by trained research 

assistants 

N = 882 

articles

3070 

citations 

Exclusions 

R1: 2283 

523 Exclusions

R1: 368 

R2: 26 

R3: 80 

R4: 49 

Stage 2: title & abstract review by a core investigator 

Stage 3: full text review by 2 independent reviewers (at 

least one core investigator)

N=359 

articles 

Articles meeting criteria for full

abstraction

N = 110 

Patient education only

N = 47 articles 

to be included in

subsequent review

Provider or 

organizational change ± 

patient education 

N = 63 

articles (reporting 82 

comparisons) included in

current review

Hand Search

EPOC 

82 

citations 

13 

citations 
Figure 1 Legend 

EPOC–Cochrane Effective Practice and Organization of Care database, which is described in Chapter 2, contains the 

results of extensive electronic searches of multiple large bibliographic databases, as well as hand searching of key

journals. The 82 citations indicated above as contributed by EPOC do not include the 134 additional citations in

EPOC already identified by the PubMed search. 

Hand searching conducted for this project involved scanning bibliographies of all articles included at Stage 4 and the 

bibliographies of all systematic reviews and meta-analyses related to QI strategies in hypertension. When no 

systematic review existed for a given topic, we searched the bibliographies of traditional (narrative) review articles, 

editorials, and news items that appeared to describe QI studies involving outpatient hypertension care. 

Reasons for Exclusion

R1—not QI or not an evaluation 

R2—excluded topic: interventions restricted to HTN in pregnancy, Secondary HTN, HTN in children/adolescents, 

preventing HTN in high risk patients, hospital care 

R3—study design below level 2 (i.e. does not meet criteria for RCT, CBA, or ITS) 

R4—unrelated to HTN (e.g., QI article retrieved by broad search but related to a different chronic illness) 

R5—no eligible outcomes 

R6—duplicate article (in some cases the article may have only partially overlapped with another report of the same 

study; in general the earlier or smaller the two publications was excluded, but reviewed with the other article in case it 

contained any additional information). Please refer to Appendix C for a list of these articles. 

R7—study published prior to 1980 

R8—other (outcomes data not available for entire population studied, e.g., only presented in subgroups) 

60
Table 1. Included studies 

Setting Study Period 

(Duration/months) 

Study Design 

(Sample Size) 

QI Strategies 

Employed * 

Outcomes 

Reported † **

22 clinics 

(18 US cities)1

1973-1982 

(99) 

RCT

(8012 patients)

Pt Ed, Org Change Dz: SBP, DBP 

2 hospital-based family

medicine centers 

 (Canada)2

1983-1987 

(60) 

CBA 

(13 providers, 817 

patients) 

Pt Remind, Prvdr Ed, 

Audit & Fdbck, Org 

Change 

DzID: BP Meas 

Cleveland Veterans’ 

Affairs Medical Center 

Ambulatory Clinic 

(Cleveland, OH)3

1992 

(2) 

Quasi-RCT

(2157 patients)

Prvdr Ed, Facil Relay,

Audit & Fdbck 

Prvdr Adhere: Med Rec 

General practice and 

hospital-based 

ambulatory clinic 

(Italy)

4

1994-1996 

(36) 

CBA 

(121 providers, 2253 

patients) 

Prvdr Ed Dz: SBP, DBP, BP 

Range 

Prvdr Adhere: Med Rec 

Pt Adhere: Meds 

Kenmore Center of the 

Harvard Community

Health Plan 

(Boston, MA)5

1975-1977 

(21) 

RCT

(115 patients) 

Prvdr Remind, Info 

System 

DzID: BP Elev FU 

Dz: Other 

Prvdr Adhere: Check BP 

34 family practices 

(Canada)6

1978-1982 

(60) 

RCT

(34 practices, 32124 

patients) 

Pt Ed, Pt Remind, Prvdr 

Remind, Org Change 

DzID: Other 

Dz: SBP, DBP 

Pt Adhere: Meds 

1 ambulatory practice 

center, Temple 

University School of 

Medicine 

(Philadelphia, PA)7

-- 

(3) 

RCT

(171 patients) 

Pt Ed, Self-Mx, Pt 

Remind

Dz: DBP, BP Range 

Pt Adhere: Meds 

20 community pharmacy

sites 

(England)8

1997-1998 

(7) 

Quasi-RCT

(25 pharmacies, 282 

patients) 

Facil Relay, Org Change Dz: BP Range

Pt Adhere: Meds 

1 primary care outpatient 

teaching clinic, The 

Queen’s Medical Center 

(Honolulu, HI)9

-- 

(6) 

Quasi-RCT

(100 patients) 

Pt Ed, Prvdr Remind, 

Facil Relay, Org Change

Dz: SBP, DBP, BP 

Range 

1 hypertension clinic 

(unspecified US city)

10 -- 

(12) 

RCT

(197 patients) 

Pt Ed, Facil Relay, Org 

Change 

Dz: SBP, DBP, BP 

Range 

Prvdr Adhere: Med Rec 

6 community sites 

(Seattle, WA; Dayton, 

OH; Fitchburg or 

Franklin County, MA; 

and Charleston or 

Georgetown County, 

SC)11

1974-1982 

(98) 

RCT

(3958 patients)

Org Change, Financial DzID: BP Elev, BP Elev 

FU 

Dz: SBP, DBP, BP 

Range 

Prvdr Adhere: Med Rec, 

Eval HTN, Pt Counsel 

Pt Adhere: Other 

19 general practices 

(Scotland)12 -- 

(12) 

RCT

(1343 patients)

Pt Ed, Prvdr Ed, Org 

Change 

Dz: BP Range

2 group medical 

practices 

(Taylorville, IL)13

-- 

(6) 

RCT

(55 patients) 

Pt Ed, Prvdr Ed, Facil 

Relay, Org Change, Info 

System 

Dz: SBP, DBP, BP 

Range 

Pt Adhere: Meds 

61
Table 1. Included studies (continued)

3 specialist hypertension 

clinics 

(Scotland)14

-- 

(48) 

CBA 

(396 patients) 

Pt Ed, Pt Remind, Org 

Change 

Dz: SBP, DBP, BP 

Range 

Patient’s 

residence/primary care

clinic15

-- 

(24) 

RCT

(218 patients) 

Pt Ed, Self-Mx, Org 

Change 

Dz: BP Range

2 manufacturing plants 

(unspecified cities, MI)16

1985-1988 

(36) 

RCT

(2 sites, 4341 

patients) 

Pt Ed, Org Change Dz: BP Range

Urban universityaffiliated internal 

medicine clinic

(unspecified US city)

17

-- 

(5) 

Quasi-RCT

(80 patients) 

Pt Ed, Self-Mx, Facil 

Relay, Org Change 

Dz: SBP, DBP, BP 

Range 

62 physician practice 

groups 

(Canada)18

-- 

(12) 

RCT

(62 practices, 198 

patients) 

Prvdr Ed, Prvdr Remind Dz: SBP, DBP, BP 

Range 

Prvdr Adhere: Check BP 

Pt Adhere: Meds 

4 Ford Motor Company

manufacturing plants 

(Southeastern 

Michigan)19

1978-1981 

(36) 

RCT

( 4 worksites, 11196 

patients) 

Pt Ed, Org Change DzID: BP Meas, BP 

Elev, BP Elev FU 

Dz: BP Range

HMO family practice 

clinic, Group Health 

Cooperative of Puget 

Sound 

(Seattle, WA)

20

1986 

(9) 

CBA 

(8 providers, 326 

patients) 

Prvdr Remind, Org 

Change, Info System 

Prvdr Adhere: Med Rec 

4 communities

( Northern California)21

1978-1983 

(64) 

CBA 

( 4 cities, 2364 

patients) 

Pt Ed, Self-Mx, Prvdr Ed DzID: BP Elev, BP Elev 

FU, BP Knew

Dz: SBP, DBP, BP 

Range 

29 greater Boston 

communities 

(Boston, MA)22

-- 

(6) 

RCT

(301 patients) 

Pt Ed, Self-Mx, Facil 

Relay, Info System 

Dz: SBP, DBP 

Pt Adhere: Meds 

1 pharmacy site 

(Portugal)23 2000 

(6) 

RCT

(100 patients) 

Pt Ed, Pt Remind, Facil 

Relay, Org Change 

Dz: SBP, DBP 

Patient’s residence 

(Mexico)24

1998-1999 

(6) 

RCT

(718 patients) 

Pt Ed, Self-Mx, Prvdr 

Ed, Org Change, Info 

System 

Dz: SBP, DBP, BP 

Range 

15 small group practices 

at 4 primary care clinics 

(Seattle, WA)

25

1993-1996 

(30) 

RCT

(78 providers) 

Pt Ed, Prvdr Ed, Prvdr 

Remind, Facil Relay, 

Audit & Fdbck, Org 

Change, Info System 

Dz: BP Range 

Prvdr Adhere: Med Rec 

MDs from 7 counties 

(San Francisco area, 

CA)26

-- 

(12) 

RCT

(82 providers) 

Prvdr Ed, Facil Relay,

Audit & Fdbck, Info 

System 

Dz: BP Range

Prvdr Adhere: Med Rec, 

Target BP 

29 health centers 

(Norway)

27 -- 

(21) 

RCT

(29 practices, 2239) 

Prvdr Ed, Audit & Fdbck, 

Info System 

Dz: SBP, DBP 

62
Table 1. Included studies (continued)

Community site, Johns 

Hopkins Hospital 

catchment area

(Maryland)28

-- 

(12) 

RCT

(204 patients) 

Pt Ed, Self-Mx, Pt 

Remind, Org Change 

Dz: SBP, DBP 

 Pt Adhere: Appt 

General Medical 

Outpatient Clinic at Duke 

University Medical 

Center 

(Durham, NC)29

-- 

(24) 

CBA 

(391 patients) 

Pt Ed, Pt Remind, Org 

Change 

Dz: BP Range

10 VA medical centers, 

1 academic center 

(unspecified US cities)30

-- 

(6) 

RCT

(133 patients) 

Pt Ed, Self-Mx, Pt 

Remind, Facil Relay 

Dz: SBP, DBP 

Pt Adhere: Meds 

17 primary care clinics 

(Saskatchewan, 

Canada)31

-- 

(12) 

RCT

(22 providers) 

Prvdr Ed Prvdr Adhere: Other 

1 hypertension clinic, 

Aldermoor Health Centre 

(Southhampton, UK)32

-- 

(12) 

RCT

(36 patients) 

Org Change Dz: BP Range

5 outpatient general

medicine practices of a 

university-based internal 

medicine training 

program 

(unspecified US city)

33

1998-2000 

(30) 

RCT

(44 providers) 

Audit & Fdbck Prvdr Adhere: Eval HTN 

Worksites 

(Toronto, Canada)34

1977 

(12) 

RCT

(457 patients) 

Org Change Dz: DBP 

38 business locations 

(Toronto, Canada)35

1979 

(12) 

RCT

(194 patients) 

Pt Ed, Self-Mx, Pt 

Remind, Facil Relay, 

Org Change 

Dz: DBP, BP Range 

Pt Adhere: Appt, Meds 

1 industrial worksite 

(Cheboksary, USSR)36

-- 

(60) 

CBA 

(5563 patients)

Org Change DzID: BP Elev 

50 family practices 

(Toronto, Canada)37

-- 

(16) 

RCT

(60 providers, 2833 

patients) 

Pt Remind, Facil Relay,

Info System 

Dz: BP Range

1 general medical clinic 

(unspecified city, GA)38

-- 

(12) 

RCT

(103 patients) 

Pt Ed, Self-Mx, Pt 

Remind, Org Change, 

Financial 

Dz: SBP, DBP, BP 

Range 

4 family practices 

Ottawa Civic Hospital 

(Ottawa, Canada)39

1985-1986 

(18) 

RCT

(4247 families, 5744 

patients) 

Prvdr Remind, Info 

System 

DzID: BP Meas, BP Elev 

Hypertension clinic 

(UK)40

1986-1989 

(48) 

RCT

(831 patients) 

Pt Remind, Facil Relay,

Org Change, Info 

System 

Dz: SBP, DBP, BP 

Range 

Prvdr Adhere: Check BP 

Patient’s residence 

(unspecified city, CO)41

-- 

(6) 

RCT

(36 patients) 

Pt Ed, Self-Mx, Org 

Change 

Dz: SBP, DBP, BP 

Range 

Pt Adhere: Meds 

Patient’s residence 

(Oakland, CA)42

-- 

(12) 

RCT

(204 patients) 

Self-Mx, Facil Relay Dz: SBP, DBP 

27 general practices 

(New Zealand)43

1996-1998 

(24) 

Quasi-RCT

(27 practices, 614 

patients) 

Prvdr Ed, Facil Relay,

Info System 

Dz: SBP, DBP 

63
Table 1. Included studies (continued)

Health care centers 

(Sweden)44

1997-1998 

(11) 

RCT

(40 providers, 46000 

patients) 

Prvdr Ed, Audit & Fdbck, 

Info System 

Prvdr Adhere: Med Rec 

2 pharmacy sites 

(Chicago, IL; 

Kenosha, WI)

45

1993-1995 

(20) 

RCT

(64 patients) 

Pt Ed, Facil Relay, Org 

Change 

Dz: SBP, DBP, BP 

Range 

Pt Adhere: Meds 

University group general 

practice 

(Australia)

46

1992-1994 

(19) 

RCT

(97 patients) 

Pt Ed, Prvdr Remind, 

Org Change 

Dz: Other 

Primary care practices 

(Canada)47

-- 

(18) 

RCT

(25 providers) 

Prvdr Ed Dz: Other 

Hypertension clinic 

Cincinnati General 

Hospital 

(Cincinnati, OH)48

1974 

(6) 

RCT

(100 patients) 

Pt Ed, Org Change Dz: SBP, DBP 

Pt Adhere: Appt, Meds 

1 general practice 

(London, UK)49

1986-1988 

(36) 

RCT

(3117 patients)

Pt Ed, Org Change, Info 

System 

DzID: BP Meas 

State University of New

York Upstate Medical 

University primary care

outpatient clinic

(Syracuse, NY)50

-- 

(11 weeks) 

RCT

(121 patients) 

Self-Mx, Facil Relay, 

Info System 

Dz: Other 

2 primary group 

practices, VA Medical 

Center 

(Richmond, VA)

51

-- 

(--) 

RCT

(2 practices, 320 

patients) 

Prvdr Ed, Prvdr Remind Dz: SBP, DBP, BP 

Range 

Prvdr Adhere: Med Rec 

1 primary care clinic 

(South Africa)52

-- 

(6) 

RCT

(224 patients) 

Pt Ed, Self-Mx, Pt 

Remind

Dz: DBP, BP Range 

Pt Adhere: Meds 

Medicine clinic

University Hospitals 

Clinic, Ohio State 

University

(Columbus, OH)53

-- 

(12) 

RCT

(40 patients) 

Org Change Dz: SBP, DBP, BP 

Range 

Multi-specialty group 

practice 

(Edgecombe county, 

North Carolina)54

1981-1983 

(21) 

CBA 

(8 providers, 460 

patients) 

Pt Remind, Audit & 

Fdbck, Org Change, Info 

System 

Dz: BP Range

Pt Adhere: Appt

4 Kaiser Permanente 

Medical Centers 

(Alameda and Contra 

Costa counties, CA)55

1986 

(12) 

RCT

(430 patients) 

Pt Ed, Self-Mx, Pt 

Remind, Facil Relay 

Dz: SBP, DBP, BP 

Range 

VA medical center walkin screening clinic 

(Durham, NC)56

1979 

(3.5) 

RCT

(74 patients) 

Pt Remind DZID: BP Elev FU 

Dz: DBP 

Pt Adhere: Appt

1 hypertension clinic, VA 

Medical Center

(Philadelphia, PA)57

-- 

(6) 

RCT

(56 patients) 

Org Change Dz: SBP, DBP, BP 

Range 

Pt Adhere: Meds 

64
Table 1. Included studies (continued)

Kenmore Center 

Harvard Community

Health Plan 

(Boston, MA)58

-- 

(15) 

Quasi-RCT

(16 providers) 

Facil Relay, Info System Dz: BP Range

Prvdr Adhere: Eval HTN 

Patient’s residence 

(Ontario, Canada)59

-- 

(2) 

RCT

(31 patients) 

Pt Ed, Self-Mx Dz: Other 

Pt Adhere: Meds 

Duke-Watts family

medicine center 

(Durham, NC)60

-- 

(11) 

RCT

(41 providers, 250 

patients) 

Facil Relay, Audit & 

Fdbck, Info System 

Dz: SBP, DBP, BP 

Range 

14 communities

(various US cities)61

1974-1979 

(60) 

RCT

(10940 patients) 

Pt Ed, Self-Mx, Org 

Change, Financial 

Dz: SBP, DBP, BP 

Range 

Pt Adhere: Meds 

Patient’s residence62

(Detroit, MI) 

-- 

(5) 

RCT

(26 patients) 

Pt Ed, Self-Mx, Facil 

Relay, Org Change, Info 

System 

Dz: SBP, DBP 

Pt Adhere: Other 

3 rural regions

(SE Minnesota)

63

1974-1979 

(72) 

CBA 

(3 regions, 740

patients) 

Pt Ed, Prvdr Ed DZID: BP Elev, BP Elev 

FU 

Dz: SBP, DBP, BP 

Range 

* Audit & Fdbck—audit and feedback to provider; Facil Relay—facilitated relay of information to provider; Financial—financial 

incentives; Info System—clinical information system; Org Change—organizational change; Pt Ed—patient education; Pt Remind—

patient reminder; Prvdr Ed—provider education; Prvdr Remind—provider reminder; Self-Mx—resource for patient selfmanagement. 

†

 Dz: Measure of disease control; SBP—systolic blood pressure; DBP—diastolic blood pressure; BP Range—patients with blood 

pressure within a certain range; Other. 

DzID: Measure of disease identification; BP Elev—patients with elevated blood pressure; BP Elev FU—patients with elevated blood

pressure receiving follow-up; BP Knew—patients who knew blood pressure was elevated; BP Meas—patients who had blood 

pressure measured; Other. 

Prvdr Adhere: provider adherence with recommendations for management of hypertension; Check BP—guidelines for checking or 

recording blood pressure; Eval HTN—guidelines for evaluation of hypertension; Med Rec—specific medication recommendations; 

Pt Counsel—guidelines for patient counseling or delivering patient education; Target BP—guidelines of targets for blood pressure; 

Other. 

Pt Adhere: Patient adherence with treatment; Appt—appointment compliance; Meds—medication compliance; Other. 

** Not all outcomes reported in Table 1 had sufficient information to use in quantitative analysis. 

65
Table 2a. Quality improvement strategies 

QI strategy Randomized Controlled 

Trial 

Non-Randomized

Controlled Trial* 

Total

Provider reminders 7 publications5, 6, 18, 25, 39,

46, 51, 67 

(8 comparisons) 

2 publications9, 20

(2 comparisons) 

9 publications 

(10 comparisons) 

Facilitated relay of 

clinical data 

17 publications10, 13, 22, 23, 

25, 26, 30, 35, 37, 40, 42, 45, 50, 55, 

60, 62, 67–73

(23 comparisons) 

6 publications3, 8, 9, 17, 43, 58, 

64, 65

 (8 comparisons) 

23 publications

(31 comparisons) 

Audit and feedback 6 publications25–27, 33, 44, 60,

67–69

 (9 comparisons) 

4 publications2, 3, 54, 58

(4 comparisons) 

10 publications

(13 comparisons) 

Provider education 12 publications12, 13, 18, 24–

27, 31, 44, 47, 51, 67–69, 74

 (15 comparisons) 

6 publications2–4, 21, 43, 63, 

66

(7 comparisons) 

18 publications

(22 comparisons) 

Patient education† 27 publications1, 6, 7, 10, 12, 

13, 15, 16, 19, 22–25, 28, 30, 35, 38, 

41, 45, 46, 48, 49, 52, 55, 59, 61, 62, 

72, 73, 75–79

(34 comparisons) 

6 publications9, 14, 17, 21, 29, 

63, 66

(7 comparisons) 

33 publications

(41 comparisons) 

Promotion of selfmanagement† 16 publications7, 15, 22, 24, 

28, 30, 35, 38, 41, 42, 50, 52, 55, 59, 

61, 62, 73, 76

(18 comparisons) 

2 publications17, 21

(2 comparisons) 

18 publications

(20 comparisons) 

Patient reminders 12 publications6, 7, 23, 28, 30, 

35, 37, 38, 40, 52, 55, 56, 70, 71, 76, 

80, 81

 (17 comparisons)

4 publications2, 14, 29, 54, 65

(5 comparisons) 

16 publications

(22 comparisons) 

Organizational change 27 publications1, 6, 10–13, 15, 

16, 19, 23–25, 28, 32, 34, 35, 38, 40, 

41, 45, 46, 48, 49, 53, 57, 61, 62, 67, 

72, 73, 75, 77–79, 82

 (35 comparisons) 

9 publications2, 8, 9, 14, 17, 20, 

29, 36, 54, 65

 (10 comparisons) 

36 publications

(45 comparisons) 

Financial incentives 3 publications11, 38, 61

(3 comparisons) 

0 publications 3 publications 

(3 comparisons) 

Total 48 publications

 (64 comparisons) 

15 publications

(18 comparisons) 

63 publications

(82 comparisons) 

* Includes 6 publications (with 7 comparisons) that are quasi-RCTs

3, 8, 9, 17, 43, 58, 64

 and 9 publications (with 11 

comparisons that are controlled before-after studies2, 4, 14, 20, 21, 29, 36, 54, 63, 65, 66

†

 Studies designated as patient education, promotion of self-management, and patient reminders always included 

some other QI strategy involving providers or organizational change. The 46 additional studies reporting interventions 

consisting solely of patient education or promotion of self-management will be reviewed in a subsequent report.

66
 Table 2b. Quality improvement sub-strategies

QI strategy Randomized Controlled 

Trial 

Non-Randomized

Controlled Trial* 

Total

CMEg 9 publications10, 12, 13, 26, 27,

31, 44, 47, 68, 69, 74

 

(11 comparisons) 

6 publications2, 3, 8, 21, 43, 63, 

64, 66

 (8 comparisons) 

15 publications

(19 comparisons) 

Educational outreach 4 publications25, 26, 44, 47, 67,

69

(6 comparisons) 

2 publications3, 21

 (2 comparisons) 

6 publications 

(8 comparisons) 

Distribution of printed 

materials 

10 publications12, 18, 25–27,

31, 44, 47, 51, 67–69, 74

(13 comparisons) 

3 publications2, 3, 21

 (3 comparisons) 

13 publications

(16 comparisons) 

Disease/Case 

management 

8 publications6, 12, 13, 25, 32, 

34, 57, 61, 67, 82

 (10 comparisons) 

1 publications63, 66

 (2 comparisons) 

9 publications 

(12 comparisons) 

Team/Staffing change 25 publications6, 10, 12, 13, 

15, 16, 19, 23–25, 28, 30, 32, 34, 35, 

38, 40, 41, 45, 46, 48, 49, 53, 57, 62, 

67, 72, 73, 75, 77–79, 82

 (33 comparisons) 

8 publications3, 8, 9, 14, 17, 20, 

29, 63, 65, 66

 (10 comparisons) 

33 publications

(43 comparisons) 

Telemedicine 1 publications40 1 publications65

 (1 comparisons) 

1 publications‡

(1 comparisons) 

Change in medical

record system

5 publications5, 6, 25, 32, 40,

67

 (6 comparisons) 

2 publications2, 54, 65

 (3 comparisons) 

7 publications 

(9 comparisons) 

Total 48 

 (64 comparisons) 

15 publications

(18 comparisons) 

63 publications

(82 comparisons) 

* Includes 6 publications (with 7 comparisons) that are quasi-RCTs

3, 8, 9, 17, 43, 58, 64

 and 9 publications (with 11 

comparisons that are controlled before-after studies2, 4, 14, 20, 21, 29, 36, 54, 63, 65, 66

g CME refers to traditional CME in the form of educational workshops or meetings. 

‡ The intervention group remained the same for both comparisons but the control group differed resulting in a 

difference in the study design; the first comparison for this study was a randomized control trial; the second 

comparison for this study had a controlled before-after design. 

67
 Table 3. Number of different quality improvement strategies included in articles 

Number of QI types in Number of comparisons

intervention RCTs Non-RCTs* Total

Single QI type 145, 31–34, 39, 47, 53, 56, 57, 

74, 80–82 34, 36, 64 17 

Multiple (total) 50 15 65

2 QI strategies 211, 11, 16, 18, 19, 27, 37, 42, 

44, 48–51, 56, 59, 60, 70, 71, 75,

77–79

68, 20, 43, 58, 63, 66 27 

3 QI strategies 157, 10, 12, 15, 22, 26, 40, 41, 

45, 46, 52, 68, 69, 72, 76 63, 14, 21, 29, 54, 65 21 

4 QI strategies 106, 13, 23, 24, 28, 30, 55, 61, 

62, 73

32, 9, 17 13 

5 QI strategies 335, 38, 67 0 3

6 QI strategies 125 0 1

 * Includes 6 publications (with 7 comparisons) that are quasi-RCTs3, 8, 9, 17, 43, 58, 64 and 9 publications (with 11 

 comparisons that are controlled before-after studies2, 4, 14, 20, 21, 29, 36, 54, 63, 65, 66

68
Table 4. Quality improvement strategy combinations

IQ Strategy Combination*

Number of 

Comparisons References

PtE, OC 9 1, 16, 19, 48, 49, 75, 77–79

FR, Aud, PvE 4 3, 26, 68, 69

OC 6 32, 34, 36, 53, 57, 82

FR, PtR 3 37, 70, 71

FR, PtE, SMx, OC 4 17, 35, 62, 73

PvE 4 4, 31, 47, 74

FR, PtE, OC 3 10, 45, 72

PtE, SMx, PtR 3 7, 52, 76

Aud, PvE 2 27, 44

PvE, PtE 2 63, 66

FR 2 58, 64

FR, PtR, OC 2 40, 65

FR, SMx 2 42, 50

FR, PtE, SMx, PtR 2 30, 55

PtR 3 56, 80, 81

PvR 2 5, 39

PvR, PvE 2 18, 51

PtE, PtR, OC 2 14, 29

PtE, SMx, OC 2 15, 41

Aud 1 33

Aud, FR 1 60

Aud, PvE, PtR, OC 1 2

Aud, PtR, OC 1 54

PvE, PtE, OC 1 12

PvE, PtE, SMx 1 21

PvE, PtE, SMx, OC 1 24

FR, PvE 1 43

FR, PvE, PtE, OC 1 13

FR, OC 1 8

FR, PtE, PtR, OC 1 23

FR, PtE, SMx 1 22

OC, Fin 1 11

PvR, FR, Aud, PvE, OC 1 67

69
Table 4. Quality improvement strategy combinations (continued)

PvR, FR, Aud, PvE, PtE, OC 1 25

PvR, FR, PtE, OC 1 9

PvR, OC 1 20

PvR, PtE, PtR, OC 1 6

PvR, PtE, OC 1 46

PtE, SMx 1 59

PtE, SMx, PtR, OC 1 28

PtE, SMx, PtR, OC,Fin 1 38

PtE, SMx, OC, Fin 1 61

82

* Aud—audit and feedback to provider; FR—facilitated relay of information to 

provider; Fin—financial incentives; OC—organizational change; PtE—patient 

education; PtR—patient reminder; PvE—provider education; PvR—provider reminder; 

SMx—resource for patient self-management. 

70
Table 5. Screening studies 

Author Screening Intervention Screening 

Setting 

Results Type of Screening

Measure(s) 

Aubin, 19942

non-RCT

(CBA) 

“Operational incentives to 

increase hypertension

screening”: 

Reference guide, 

placed in physician’s 

offices 

Chart aids for the 

recording of BP

measurements

Follow up system and 

protocol

Control group: Usual care 

Clinic 

N = 13 

providers, 

817 patients 

Control group: 

Screening rates decreased 

from 71.9% to 59.8% 

Intervention group: 

Screening rates increased 

from 59.8% to 78.7% 

Note: Control group had high 

screening rate to start with. 

Authors noted that there was a 

medical audit of practices in this 

group at baseline. 

Screening Rate:

Percent of individuals 

who had blood 

pressure measured. 

Control vs. 

Intervention: 

P < 0.001 at 

baseline; 

P < 0.001 at end of 

study

Barnett, 19835

RCT

Automated computer 

surveillance system used 

to monitor patient 

population with elevated

diastolic BP and poor 

follow-up rates. Providers 

received automatic 

computer-generated 

reminders for all patients 

not adhering to standard 

follow-up procedures. 

Control group: Usual care 

Clinic 

N = 115 patients 

6–12 month follow-up period: 

Control group: 

25% follow-up rate; 31% had 

Repeat BP recorded 

Intervention group: 

49% follow-up rate; 49% had 

Repeat BP recorded 

6–24 month follow-up period: 

Control group: 

46% follow-up rate; 52% had 

Repeat BP recorded 

Intervention group: 

98% follow-up rate;70% had 

Repeat BP recorded 

Follow-up Rate

(attempted or 

accomplished): 

Percent of patients 

with elevated

blood pressure

who had follow-up 

P < 0.01 (6–12

months) 

P < 0.01 (6–24

months) 

 

Repeat BP recorded: 

P < 0.05 (6–12

months) 

P < 0.05 (6–24

months) 

71
Table 5. Screening studies (continued)

Bass, 19866

RCT

Medical assistant 

administered hypertension 

screening, education, 

compliance, and follow-up 

activities in family practice 

setting. Medical charts 

were tagged to remind 

providers to measure 

patient’s BP. A “tickler” file 

system tracked patients 

due for follow-up. Patient 

appointments were filed 

on an index card by month 

of visit; the card was 

removed from the file 

when the patient attended 

the appointment. Cards 

remaining at the end of 

the month received followup. 

Patients received post 

card reminders to have BP 

checked. 

Control group: Usual care 

Clinic 

N = 34 

practices, 

32,124 patients 

Control group: 

80% screened at least once; 

57% screened at least twice 

Intervention group: 

90.8% screened at least once; 

70.3% screened at least twice

Note: Authors concluded that 

the higher rates of screening did 

not influence outcomes, 

probably because the family 

doctors were identifying higher

risk groups regardless of 

screening practice. 

Screening Rate:

Percent of patients 

who had blood 

pressure measured; 

Followup Rate: 

Percent of patients 

with elevated blood 

pressure who had 

follow-up 

Intervention versus 

control group patients 

were: 

more likely to have 

lower SBP 

(P < 0.02) 

more likely to be 

more compliant 

(P < 0.05) 

more likely to be 

very satisfied with

care (P < 0.01) 

Foote, 198319

RCT

Worksite hypertension 

screening conducted at 4 

sites. 

Site 1: Screening and 

referral to a physician only 

(Control) 

Site 2: Screening, referral 

to a physician, and 

semiannual follow-up

visits 

Site 3: Screening, referral 

to a physician, and more

frequent follow-ups as 

needed 

Site 4: Screening and onsite treatment by a 

physician. 

Community

(Work site) 

N = 4 worksites, 

11,196 patients 

Screening rates reported for 

Sites 1, 2, 3, and 4 (83%, 75%, 

77%, 66%) 

Percent of employees identified

as hypertensive being treated

before versus after study:

Site 1: 49% to 84% 

Site 2: 49% to 96% 

Site 3: 33% to 96% 

Site 4: 40% to 98% 

Screening Rate:

Percent of patients 

who had blood 

pressure measured; 

Percent of patient 

with hypertension 

who are treated (and 

identified as 

hypertensive) 

Site 1: Significant 

increase in proportion

under treatment (P < 

0.001), but not in 

proportion with

adequate blood 

pressure control. 

Sites 2, 3, and 4: 

Significant increase 

in proportion under 

treatment (P < 0.001) 

and in proportion with 

adequate blood 

pressure control (P < 

0.001). 

No statistical 

comparison between 

control and 

intervention 

72
Table 5. Screening studies (continued)

Markov,198636

non RCT

(CBA) 

Work site hypertension 

screening. Active 

prevention group 

screened annually and 

referred to cardiovascular 

outpatient department for 

further testing and 

treatment. 

Control group: Annual 

screenings; individuals 

with elevated blood 

pressure referred to 

routine care. 

Community

(Work site) 

N = 5,563 

patients 

Control group: 

Effectively treated patients 

increased from 4% to 11.9% 

within 5 years.

Intervention group: 

Effectively treated patients 

increased from 7.3% to 25.2%

within 5 years.

Percent of Effectively

Treated Patients

(i.e., stable decrease 

in DBP below 90 

mmHg, or DBP 

decrease by 10-15%

from initial screening 

to final 5th year of 

screening): 

P < 0.01 for 

change in

proportion of 

effectively treated 

patients in 

intervention group 

P < 0.01 for 

change in

proportion of 

effectively treated 

patients in control 

group 

No statistical 

comparison between 

control and 

intervention 

Robson, 

198949

RCT

Health promotion nurse

assisted physicians in 

recording BP during 

regular appointments. 

Computer system 

allocated patients into 

groups, depending on 

their risk score (based on 

BP measure). Nurse ran 

monthly computer 

searches and followed up 

with high risk patients and 

those without any record 

of risk factors. 

Control group: General

practitioners managed 

patients; recorded blood 

pressure and history of 

smoking in computerized 

record. 

Clinic 

3,117 patients 

Percent patients with BP 

recorded within 5 years: 

Control group: Increased from 

62% to 73%. 

Intervention group: Increased

from 65% to 93%. 

Percent hypertensives with BP

recorded within 1 year at end of 

study:

Control group: 69% 

Intervention group: 97% 

Screening rate

(Percent of patients 

with BP checked 

initially) 

Control versus 

intervention: 

P < 0.001 for 

proportion of 

patients who had 

BP recorded within 

preceding 5 years. 

BP recorded at a 

follow-up time in 

patients identified as 

hypertensive

P < 0.001 for 

proportion of 

patients with HTN 

or who had fewer 

than 3 readings in 

the HTN range but 

had not had BP

recorded within the 

preceding year. 

73
Table 5. Screening studies (continued)

Fortmann, 

199021

non RCT

(CBA) 

Annual cross-sectional 

surveys of randomly

selected households, and 

4 repeated surveys of a 

cohort. Mass media and 

education programs for 

public and health 

professionals in the study

cities. 

Control group: Usual care 

included 2 cities where no

mass media education 

was provided. 

Community

N = 4 cities, 

2,364 patients 

For cohort study – 

Percent of hypertensives aware: 

Control: 58.8% to 64.3% 

Intervention: 42.2% to 55.9% 

Percent of hypertensives under 

treatment: 

Control: 41% to 44.9% 

Intervention: 27.7% to 32.5% 

Percent of 

hypertensives aware 

of HTN

Control versus 

intervention: 

P < 0.01 at 

baseline. 

Results at end of 

study not significant. 

Percent of 

hypertensives under 

treatment: 

P < 0.05 at 

baseline. 

Results at end of 

study not significant. 

McDowell, 

198939

RCT

Patients in 4 family

practices received one of 

the following interventions 

aimed at encouraging 

patients to have their BP 

checked: 

1. Letter reminder 

2. Telephone reminder 

3. Physician reminder 

4. Randomized control 

group 

5. Two additional 

control practices did 

not participate in the 

trial and patients 

were not issued

reminders 

Clinic 

N = 4,247 

families, 5,744 

patients 

Percent of individuals who had 

blood pressure measured: 

Control group: 21.1% 

Letter reminder: 35.7% 

Telephone reminder: 24.1% 

Physician reminder: 30.7%

Control Practices (not 

randomized): 18.6% 

Screening rate

Percent of patients 

without BP checked 

in last year who have 

BP reading within the 

study year: 

P < 0.001 for 

difference between 

the 3 intervention 

groups and the

control group. 

P < 0.001 for 

differences among 

the 3 groups. 

P < 0.001 for 

difference between 

physician 

intervention and 

control. 

Velez, 198556

RCT

Patient and providers 

were randomized to 

receive reminders: 

1. Patient Letter only 

2. Provider Letter only 

3. Both Patient and 

Provider Letter

Control Group: Patients 

informed of their elevated 

blood pressure and the 

need to follow-up with 

their local physician 

Clinic 

N = 74 patients

Percent of patients with elevated 

blood pressure who had followup: 

Control Group: 29% 

Patient Letter: 62% 

Provider Letter: 39% 

Both Letters: 64% 

Note: 60% of patients were 

previously treated for HTN, and 

there were significant 

differences in this rate between 

intervention groups, but 

stratification did not change the 

results significantly.

Percent of patients 

returning to physician 

after high blood 

pressure reading: 

P = 0.012 for main 

effects of patient 

letter. 

P = 0.334 for main 

effects of physician 

letter 

P = 0.72 for 

interaction effects 

of patient letter X 

physician letter 

74
Table 5. Screening studies (continued)

Krishan, 

198163

non-RCT

(CBA) 

Public education via local 

radio and newspapers. 

Providers offered 

educational outreach 

program. 

Community screening. 

Those identified with high 

blood pressure were

offered a stepped care 

approach for the treatment 

of HTN in a special 

community hypertension 

clinic; patients could also 

follow-up with their own

physicians. 

Control group: Usual care 

Community

N = 3 regions, 

740 patients 

2 Control communities were 

compared with Intervention 

community: 

The percentage of patients 

receiving hypertensive 

medications reported at 

baseline and 1st year had no

significant differences 

between communities in first 

two periods, but the 

intervention group had a 

higher rate in the final 5th year

(61.4% and 55.4% in control 

communities versus 68.4% in

intervention community) 

Note: Only patients who 

participated in 5-year follow-up 

survey had data reported. 

Percent of 

hypertensives on 

medications: 

Insignificant 

difference at 

baseline and 1st

year

P = 0.01 for 

intervention 

community versus 

control 

communities at 5 

years

75
Table 6a. Effect of quality improvement strategies on blood pressure outcomes*

Type of QI Median reduction 

in SBP (mmHg) 

[inter-quartile

range] † 

N = number of 

comparisons

Median reduction 

in DBP (mmHg) 

 [inter-quartile

range]

 †

N = number of 

comparisons

Median increase 

in proportion of 

patients 

achieving SBP in 

a certain range

[inter-quartile

range]

 †

N = number of 

comparisons

Median increase 

in proportion of 

patients 

achieving DBP in 

a certain range

[inter-quartile

range]

 †

N = number of 

comparisons

All comparisons 4.5 

[1.5, 11.0] 

N = 331, 4, 9, 10, 13, 14, 

17, 18, 21–24, 27, 28, 30, 

38, 40–43, 45, 51, 53, 55, 

57, 60, 62, 64, 65, 68, 73, 

74, 82

2.1 

[-0.2, 5.0] 

N = 431, 4, 7, 9–11, 13,

14, 17, 18, 21-24, 26-28, 

30, 34, 35, 38, 40–43, 45, 

51–53, 55, 57, 60–66, 68, 

73, 74, 76, 82 

16.2 

[10.3, 32.2] 

N = 144, 8, 12–14, 16, 

19, 21, 25, 45, 53, 67, 72, 

78

6.0 

[1.5, 17.5] 

N = 164, 7, 14, 15, 21, 

26, 29, 38, 54, 58, 60, 61, 

68, 69, 74, 79

Provider reminders 6.8 

[3.0, 9.4] 

N = 39, 18, 51

2.1 

[0.9, 6.6] 

N = 39, 18, 51

-3.6 

[-5.7, -1.4] 

N = 225, 67

NA 

N = 0 

Facilitated relay of 

clinical data 

4.5 

[2.2, 11.5] 

N = 199, 10, 13, 17, 22,

23, 30, 40, 42, 43, 45, 55, 

60, 62, 64, 65, 68, 73, 74

1.1 

[-1.0, 3.4] 

N = 209, 10, 13, 17, 22,

23, 26, 30, 35, 40, 42, 43, 

45, 55, 60, 62, 64, 65, 68, 

73

15.3 

[2.0, 28.4] 

N = 68, 13, 25, 45, 67, 72

2.0 

[1.6, 5.0] 

N = 526, 58, 60, 68, 69

Audit and feedback 1.3 

[0.5, 1.6] 

N = 427, 60, 68, 74

0.6 

[0.5, 1.0] 

N = 426, 27, 60, 68

-3.6 

[-5.7, -1.4] 

N = 225, 67

1.8 

[0.1, 4.3] 

N = 626, 54, 58, 60, 68, 

69

Provider education 2.7 

[1.1, 6.0] 

N = 104, 13, 18, 21, 24,

27, 43, 51, 68, 74

0.7 

[-0.3, 3.3] 

N = 134, 13, 18, 21, 24,

26, 27, 43, 51, 63, 66, 68, 

74

10.9 

[1.4, 13.1] 

N = 64, 12, 13, 21, 25, 67

3.5 

[1.7, 11.3] 

N = 64, 21, 26, 60, 68, 69

Patient education 8.1 

[3.3, 11.8] 

N = 181, 9, 10, 13, 14, 

17, 21–24, 28, 30, 38, 41, 

45, 55, 62, 73

3.3 

[0.4, 5.0] 

N = 251, 7, 9, 10, 13, 14, 

17, 21–24, 28, 30, 35, 38, 

41, 45, 52, 55, 61–63, 66, 

73, 76 

19.2 

[10.3, 36.4] 

N = 1012–14, 16, 19, 21, 

25, 45, 72, 78

15.2 

[7.3, 21.8] 

N = 87, 14, 15, 21, 29, 

38, 61, 79

Promotion of selfmanagement 

3.6 

[2.1, 9.5] 

N = 1217, 21, 22, 24, 28, 

30, 38, 41, 42, 55, 62, 73

2.1 

[0.4, 5.0] 

N = 177, 17, 21, 22, 24,

28, 30, 35, 38, 41, 42, 52, 

55, 61, 62, 73, 76

13.4 

N = 121

9.4 

[1.1, 13.4] 

N = 57, 15, 21, 38, 61

Patient reminders 2.8 

[-1.5, 5.1] 

N = 814, 23, 28, 30, 38, 

40, 55, 65

0.5 

[-2.1, 3.4] 

N = 127, 14, 23, 28, 30,

35, 38, 40, 52, 55, 65, 76 

7.0 

N = 114

9.4 

[1.1, 19.0] 

N = 57, 14, 29, 38, 54

76
Table 6a. Effect of quality improvement strategies on blood pressure outcomes* (continued)

Organizational change 10.1 

[3.9, 14.0] 

N = 191, 9, 10, 13, 14, 

17, 23, 24, 28, 38, 40, 41, 

45, 53, 57, 62, 65, 73, 82

4.4 

[-0.5, 6.9] 

N = 231, 9–11, 13, 14, 

17, 23, 24, 28, 34, 35, 38, 

40, 41, 45, 53, 57, 61, 62, 

65, 73, 82 

21.8 

[9.0, 33.8] 

N = 128, 12–14, 16, 19,

25, 45, 53, 67, 72, 78

17.0 

[4.2, 24.5] 

N = 714, 15, 29, 38, 54, 

61, 69

Financial incentives -13.3 

N = 138

0.0 

[-2.0, 2.5] 

N = 311, 38, 61

NA 

N = 0 

4.2 

[-1.1, 9.4] 

N = 238, 61

 * For reference 25, nurses were given training about ageing, clinical aspects of hypertension, personal interviews, 

health behavior change models, process of negotiation, and ethical aspects of home visits. 

†

 When N=2, square brackets show the actual results of each study rather than interpolated inter-quartile range. 

77
Table 6b. Effect of quality improvement strategies on summary adherence outcomes

Type of QI Median improvement in 

proportion of provider

adherence to recommended 

practice 

[inter-quartile range]

 † 

N = number of comparisons

Median improvement in 

proportion of patient 

adherence

 [inter-quartile range]

 † 

N = number of comparisons

All comparisons 3.0 

[1.0, 5.5] 

N = 103, 4, 10, 20, 25, 26, 44, 58, 67, 69

2.8 

[1.9, 3.0] 

N = 54, 8, 22, 45, 69

Provider reminders -1.3 

[-2.0, 2.9] 

N = 320, 25, 67

NA 

N = 0 

Facilitated relay of clinical data 2.0 

[-0.4, 3.7] 

N = 73, 10, 25, 26, 58, 67, 69

2.4 

[0.8, 5.0] 

N = 48, 22, 45, 69

Audit and feedback 2.7 

[-0.4, 3.7] 

N = 73, 25, 26, 44, 58, 67, 69

-2.7 

N = 169

Provider education 3.3 

[0.7, 5.0] 

N = 73, 4, 25, 26, 44, 67, 69

0.2 

[-2.7, 3.0] 

N = 24, 69

Patient education 0.4 

[-1.3, 2.0] 

N = 210, 25

2.4 

[1.9, 2.8] 

N = 222, 45

Promotion of self-management NA 

N = 0 

2.8 

N = 122

Patient reminder NA 

N = 0 

NA 

N = 0 

Organizational change 0.4 

[-1.6, 3.3] 

N = 410, 20, 25, 67

6.8 

[1.9, 11.6] 

N = 28, 45

Financial incentives NA 

N = 0 

NA 

N = 0 

†

 When N=2, square brackets show the actual results of each study rather than interpolated inter-quartile range. 

78
Table 7a. Effect of number of quality improvement strategies on blood pressure outcomes 

Number of QI 

strategies 

employed in

intervention 

Median reduction in 

SBP (mmHg) 

 [inter-quartile range]*

N = Number of 

comparisons

Median reduction in 

DBP (mmHg) 

 [inter-quartile range]*

N = Number of 

comparisons

Median increase in

proportion of patients

in target SBP range 

[inter-quartile range]*

N = Number of 

comparisons

Median increase in

proportion of patients

in target DBP range 

 [inter-quartile range]*

N = Number of 

comparisons

Single QI 

strategy

10.9 

[4.9, 17.6] 

N = 64, 53, 57, 64, 74, 82

4.8 

[2.5, 10.2] 

N = 74, 34, 53, 57, 64, 74, 82

23.1 

[13.8, 32.4] 

N = 24, 53

14.6 

[5.0, 24.2] 

N = 24, 74

Two QI 

strategies 

1.5 

[1.0, 4.7] 

N = 71, 18, 27, 42, 43, 51, 60

0.3 

[-0.3, 2.1] 

N = 101, 11, 18, 27, 42, 43, 51, 

60, 63, 66

31.5 

[23.4, 38.5] 

N = 48, 16, 19, 78

7.0 

[6.0, 12.0] 

N = 358, 60, 79

Three QI 

strategies 

3.8 

[2.0, 10.1] 

N = 910, 14, 21, 22, 40, 41, 45, 65, 

68

0.7 

[-1.0, 5.0] 

N = 137, 10, 14, 21, 22, 26, 40, 

41, 45, 52, 65, 68, 76

13.4 

[9.7, 31.6] 

N = 512, 14, 21, 45, 72

2.0 

[1.1, 19.0] 

N = 97, 14, 15, 21, 26, 29, 54, 68, 

69

Four QI

strategies 

9.2 

[4.2, 13.4] 

N = 109, 13, 17, 23, 24, 28, 30, 

55, 62, 73

3.7 

[1.1, 8.0] 

N = 119, 13, 17, 23, 24, 28, 30, 

55, 61, 62, 73

12.0 

N = 113

-1.1 

N = 161

Five QI 

strategies 

-13.3 

 

N = 138

-0.6 

[-2.2, 1.1] 

N = 235, 38

-5.7 

N = 167

9.4 

N = 138

Six QI 

strategies 

NA 

N = 0 

NA 

N = 0 

-1.4 

N = 125

NA 

N = 0 

All

comparisons

4.5 

[1.5, 11.0] 

N = 331, 4, 9, 10, 13, 14, 17, 18, 

21–24, 27, 28, 30, 38, 40–43, 45, 51, 

53, 55, 57, 60, 62, 64, 65, 68, 73, 74, 

82

2.1 

[-0.2, 5.0] 

N = 431, 4, 7, 9–11, 13, 14, 17, 

18, 21–24, 26–28, 30, 34, 35, 38, 40–

43, 45, 51–53, 55, 57, 60–66, 68, 73, 

74, 76, 82

16.2 

[10.3, 32.2] 

N = 144, 8, 12–14, 16, 19, 21, 25, 

45, 53, 67, 72, 78

6.0 

[1.5, 17.5] 

N = 164, 7, 14, 15, 21, 26, 29, 38, 

54, 58, 60, 61, 68, 69, 74, 79

* When N=2, square brackets show the actual results of each study rather than interpolated inter-quartile range. 

79
Table 7b. Effect of number of quality improvement strategies on summary adherence outcomes

Number of QI strategies 

employed in intervention 

Median improvement in 

proportion of provider

adherence to recommended 

practice 

 [inter-quartile range]

* 

N = Number of comparisons

Median improvement in 

proportion of patient 

adherence

 [inter-quartile range]*

N = Number of comparisons

Single QI strategy 6.7 

N = 14

3.0 

N = 14

Two QI strategies 2.7 

[1.6, 4.8] 

N = 320, 44, 58

11.6 

N = 18

Three QI strategies 3.7 

[3.0, 4.5] 

N = 43, 10, 26, 69

1.9 

[-0.38, 2.35] 

N = 322, 45, 69

Four QI strategies NA 

N = 0 

NA 

N = 0 

Five QI strategies -2.6 

N = 167

NA 

N = 0 

Six QI strategies -1.3 

N = 125

NA 

N = 0 

All comparisons 3.0 

[1.0, 5.5] 

N = 103, 4, 10, 20, 25, 26, 44, 58, 67, 69

2.8 

[1.9, 3.0] 

N = 54, 8, 22, 45, 69

* When N = 2, square brackets show the actual results of each study rather than interpolated inter-quartile 

range. 

80
Table 8a. Effect of specific quality improvement sub-strategies on blood pressure outcomes 

Type of QI SubStrategy Median reduction in 

SBP (mmHg) 

[inter-quartile

range]*

N = number of 

comparisons

Median reduction in 

DBP (mmHg) 

 [inter-quartile

range]* 

N = number of 

comparisons

Median increase in

proportion of 

patients achieving

SBP in a certain

range

[inter-quartile

range]

*

N = number of 

comparisons

Median increase in

proportion of 

patients achieving

DBP in a certain 

range

[inter-quartile

range]

*

N = number of 

comparisons

Provider education 2.7 

[1.1, 6.0] 

N = 104, 13, 18, 21, 24, 27, 

43, 51, 68, 74

0.7 

[-0.3, 3.3] 

N = 134, 13, 18, 21, 24, 26, 

27, 43, 51, 63, 66, 68, 74

10.9 

[1.4, 13.1] 

N = 54, 12, 13, 21, 25, 67

3.5 

[1.7, 11.3] 

N = 64, 21, 26, 68, 69, 74

CME† 2.9 

[1.4, 5.3] 

N = 810, 13, 21, 27, 43, 64,

68, 74

0.0 

[-1.0, 0.8] 

N = 1110, 13, 21, 26, 27, 43, 

63, 64, 66, 68, 74

12.7 

[11.4, 14.7] 

N = 48, 12, 13, 21

2.0 

[1.6, 5.0] 

N = 521, 26, 68, 69, 74

Educational outreach 3.8 

N = 121

2.2 

[0.7, 3.8] 

N = 221, 26

-1.4 

[-3.6, 6.0] 

N = 321, 25, 67

1.6 

[0.6, 7.5] 

N = 321, 26, 69

Distribution of 

printed materials

1.7 

[-0.2, 3.4] 

N = 618, 21, 27, 51, 68, 74

0.7 

[0.3, 1.6] 

N = 718, 21, 26, 27, 51, 68,

74

4.2 

[-2.5, 10.6] 

N = 412, 21, 25, 67

2.0 

[1.6, 5.0] 

N = 521, 26, 68, 69, 74

Organizational 

change

10.1 

[3.9, 14.0] 

N = 191, 9, 10, 13, 14, 17, 

23, 24, 28, 38, 40, 41, 45, 53, 

57, 62, 65, 73, 82

4.4 

[-0.5, 6.9] 

N = 231, 9–11, 13, 14, 17, 

23, 24, 28, 34, 35, 38, 40, 41, 

45, 53, 57, 61, 62, 65, 73, 82 

21.8 

[9.0, 33.8] 

N = 128, 12–14, 16, 19, 25, 

45, 53, 67, 72, 78

17.0 

[4.2, 24.5] 

N = 714, 15, 29, 38, 54, 61,

69

Disease/Case 

management 

14.1 

[11.6, 16.4] 

N = 313, 57, 82

5.0 

[1.4, 10.2] 

N = 713, 34, 57, 61, 63, 66,

82

4.2 

[-2.5, 10.3] 

N = 412, 13, 25, 67

-1.1 

N = 161

Team/Staffing 

change

10.1 

[3.9, 14.0] 

N = 199, 10, 13, 14, 17, 23, 

24, 28, 30, 38, 40, 41, 45, 53, 

57, 62, 65, 73, 82

3.7 

[-0.8, 6.9] 

N = 239, 10, 13, 14, 17, 23, 

24, 28, 30, 34, 35, 38, 40, 41, 

45, 53, 57, 62, 63, 65, 66, 73, 

82 

21.8 

[9.0, 33.8] 

N = 118, 12–14, 16, 19, 25, 

45, 53, 67, 72, 78

19.0 

[17.0, 30.0] 

N = 514, 15, 29, 38, 79

Telemedicine 3.4 

[2.3, 4.5] 

N = 240, 65

-2.0 

[-1.6, -2.4] 

N = 240, 65

NA 

N = 0 

NA 

N = 0 

Change in medical

record system

3.4 

[2.3, 4.5] 

N = 240, 65

-2.0 

[-1.6, -2.4] 

N = 240, 65

-3.6 

[-5.7, -1.4] 

N = 225, 67

-2.0 

N = 154

* When N = 2, square brackets show the actual results of each study rather than interpolated inter-quartile range. 

†

 CME refers to traditional CME in the form of educational workshops or meetings.

81
Table 8b. Effect of specific quality improvement sub-strategies on summary adherence 

outcomes 

Type of QI Sub-Strategy Median improvement in 

proportion of provider

adherence to recommended 

practice 

 [inter-quartile range]*

N = number of comparisons

Median improvement in 

proportion of patient 

adherence

 [inter-quartile range]*

N = number of comparisons

Provider education 3.3 

[0.7, 5.0] 

N = 73, 4, 25, 26, 44, 67, 69

0.2 

[-2.7, 3.0] 

N = 24, 69

CME† 3.3 

[2.7, 4.0] 

N = 53, 10, 26, 44, 69

4.5 

[-2.7, 11.6] 

N = 28, 69

Educational outreach 3.0 

[-0.3, 3.8] 

N = 63, 25, 26, 44, 67, 69

-2.66 

N = 169

Distribution of printed 

materials 

3.0 

[-0.3, 3.8] 

N = 63, 25, 26, 44, 67, 69

-2.66 

N = 169

Organizational change 0.4 

[-1.6, 3.3] 

N = 310, 20, 25, 67

6.8 

[1.9, 11.6] 

N = 28, 45

Disease/Case 

management 

-2.0 

[-2.6, -1.3] 

N = 225, 67

NA 

N = 0 

Team/Staffing change 2.0 

[-1.3, 3.3] 

N = 53, 10, 20, 25, 67

6.8 

[1.9, 11.6] 

N = 28, 45

Telemedicine NA 

N = 0 

NA 

N = 0 

Change in medical

record system

-2.0 

[-2.6, -1.3] 

N = 225, 67

NA 

N = 0 

* When N = 2, square brackets show the actual results of each study rather than interpolated inter-quartile 

range. 

†

 CME refers to traditional CME in the form of educational workshops or meetings.

82
Table 9a. Effect of information systems on blood pressure outcomes*

Type of Information 

System

Median reduction 

in SBP (mmHg) 

[inter-quartile

range]

 †

N = number of 

comparisons

Median reduction 

in DBP (mmHg) 

 [inter-quartile

range] †

N = number of 

comparisons

Median increase in

proportion of 

patients achieving

SBP in a certain

range

[inter-quartile

range] †

N = number of 

comparisons

Median increase in

proportion of 

patients achieving

DBP in a certain 

range

[inter-quartile

range] †

N = number of 

comparisons

All information 

systems 

2.2 

[1.1, 4.2] 

N = 1013, 22, 24, 27, 40, 

43, 60, 62, 65, 68

0.6 

[-1.3, 2.1] 

N = 1113, 22, 24, 26, 27, 

40, 43, 60, 62, 65, 68

-1.4 

[-3.6, 5.3] 

N = 313, 25, 67

1.8 

[0.1, 4.3] 

N = 626, 54, 58, 60, 68, 69

Identification of

eligible participants 

using information 

systems 

1.2 

[1.0, 1.6] 

N = 427, 43, 60, 68

0.6 

[0, 0.7] 

N = 526, 27, 43, 60, 68

NA 

N=0 

2.0 

[1.6, 5.0] 

N = 526, 58, 60, 68, 69

Reminders generated 

by existing clinical

information system 

2.3 

[1.7, 3.4] 

N = 340, 60, 65

-1.6 

[-2.0, 0.2] 

N = 340, 60, 65

-3.6 

[-5.7, -1.4] 

N = 225, 67

6.0 

[5.0, 7.0] 

N = 258, 60

Decision Support 

System

1.2 

[1.0, 1.5] 

N = 227, 43

-0.7 

[-2.0, 0.6] 

N = 227, 43

NA 

N = 0 

NA 

N = 0 

Audit data gathered

from clinical 

information systems 

1.5 

[1.3, 1.8] 

N = 260, 68

1.0 

[0.5, 1.5] 

N = 260, 68

NA 

N = 0 

3.5 

[1.0, 5.5] 

N = 454, 58, 60, 68

* Some subcategories of information systems strategies are not included in this table. 

†

 When N=2, square brackets show the actual results of each study rather than interpolated inter-quartile range.

83
Table 9b. Effect of information systems on summary adherence outcomes*

Type of Information 

System 

Median improvement in 

proportion of provider adherence

to recommended practice 

 [inter-quartile range]

†

N = number of comparisons

Median improvement in 

proportion of patient adherence

 [inter-quartile range]

†

N = number of comparisons

All Information Systems 2.7 

[-0.4, 5.0] 

N = 720, 25, 26, 44, 58, 67, 69

0.07 

[-2.66, 2.8] 

N = 222, 69

Identification of eligible 

participants using 

information systems 

4.0 

[2.3, 5.0] 

N = 326, 58, 69

-2.66 

N = 169

Reminders generated 

by existing clinical

information system 

-1.3 

[-2.0, -0.4] 

N = 325, 58, 67

NA 

N = 0 

DSS NA 

N = 0 

NA 

N = 0 

Audit data gathered

from clinical 

information systems 

1.7 

[0.6, 2.7] 

N = 244, 58

NA 

N = 0 

* Some subcategories of information systems strategies are not included in this table. 

†

 When N = 2, square brackets show the actual results of each study rather than interpolated inter-quartile 

range.

84
Table 10a. Association of methodologic features* with decreased blood pressures 

Median reduction in SBP (mmHg) 

[inter-quartile range]

†

N = Number of comparisons

Median reduction in DBP (mmHg) 

[inter-quartile range]

†

N = Number of comparisons

 

Design feature 

present 

Design feature 

absent 

Design feature 

present 

Design feature 

absent 

RCT 6.8 

[1.5, 13.0] 

N = 251, 10, 13, 18, 

22–24, 27, 28, 30, 38, 

40–42, 45, 51, 53, 55, 

57, 60, 62, 68, 73, 74, 

82

4. 3 

[3.1, 8.1] 

N = 84, 9, 14, 17, 21, 43, 

64, 65

2.0 

[0.0, 5.0] 

N = 331, 7, 10, 11, 13, 18, 22–

24, 26–28, 30, 34, 35, 38, 40–42,

45, 51-53, 55, 57, 60–62, 68, 73,

74, 76, 82

2.7 

[-0.9, 4.6] 

N = 104, 9, 14, 17, 21, 43, 

63–66

Providers blinded 5.1 

[3.3, 6.8] 

N = 224, 51

4.5 

[1.3, 11.5] 

N = 311, 4, 9, 10, 13, 14, 

17, 18, 21–23, 27, 28, 30, 

38, 40–43, 45, 53, 55, 57, 

60, 62, 64, 65, 68, 73, 74, 

82

2.9 

[2.1, 3.7] 

N = 224, 51

2.0 

[-0.3, 5.0] 

N = 411, 4, 7, 9–11, 13, 14, 

17, 18, 21-23, 27, 28, 30, 34, 

35, 38, 40–43, 45, 52, 53, 55, 

57, 60-66, 68, 73, 74, 76, 82

Patients blinded 6.8 

[1.5, 7.3] 

N = 74, 9, 30, 51, 60, 

68, 74

4.3 

[1.7, 12.5] 

N = 261, 10, 13, 14, 17,

18, 21-24, 27, 28, 38, 40–

43, 45, 53, 55, 57, 62, 64, 

65, 73, 82

1.5 

[0.7, 2.8] 

N = 84, 9, 26, 30, 51, 60, 68, 74

2.1 

[-0.8, 5.0] 

N = 351, 7, 10, 11, 13, 14, 

17, 18, 21–24, 27, 28, 34, 35, 

38, 40–43, 45, 52, 53, 55, 57, 

61-66, 73, 76, 82

 

Unit of analysis same 

as unit of allocation 

7.1 

[2.6, 13.9] 

N = 211, 9, 10, 14, 

22-24, 28, 30, 38, 40-42, 

45, 53, 55, 57, 62, 65, 

73, 82

2.9 

[1.0, 7.0] 

N = 124, 13, 17, 18, 21,

27, 43, 51, 60, 64, 68, 74

3.7 

[0.0, 6.7] 

N = 291, 7, 9-11, 14, 22–24, 

26, 28, 30, 34, 35, 38, 40–42, 45,

52, 53, 55, 57, 61, 62, 65, 73, 76,

82 

0.8 

[-0.5, 2.1] 

N = 144, 13, 17, 18, 21, 27, 

43, 51, 60, 63, 64, 66, 68, 74

Concealment allocation 3.8 

[1.5, 9.6] 

N = 1113, 21, 24, 41, 

43, 60, 62, 64, 68, 73, 

74

6.8 

[1.7, 11.8] 

N = 221, 4, 9, 10, 14, 17, 

18, 22, 23, 27, 28, 30, 38, 

40, 42, 45, 51, 53, 55, 57, 

65, 82

1.5 

[0.0, 4.7] 

N = 1411, 13, 21, 24, 26, 41, 

43, 60-62, 64, 68, 73, 74

2.1 

[-0.3, 5.0] 

N = 291, 4, 7, 9, 10, 14, 17, 

18, 22, 23, 27, 28, 30, 34, 35, 

38, 40, 42, 45, 51-53, 55, 57, 

63, 65, 66, 76, 82

Total (i.e., irrespective 

of design feature 

presence or absence) 

4.5 

[1.5, 11.0] 

N = 331, 4, 9, 10, 13, 14, 17, 18, 21–24, 27, 28, 30, 

38, 40–43, 45, 51, 53, 55, 57, 60, 62, 64, 65, 68, 73, 74,

82

2.1 

[-0.2, 5.0] 

N = 431, 4, 7, 9–11, 13, 14, 17, 18, 21–24, 26–28, 30, 34, 35, 38, 

40–43, 45, 51-53, 55, 57, 60–66, 68, 73, 74, 76, 82

* In this table, all design features whose presence was judged as “unclear” were coded as absent. 

† When N = 2, square brackets show the actual results of each study rather than interpolated inter-quartile range.

85
Table 10b. Association of methodologic features* with increased percentage of patients in blood pressure 

target range 

Median increase in proportion of 

patients in target SBP range 

[inter-quartile range]

†

N = Number of comparisons

Median increase in proportion of patients

in target DBP range 

 [inter-quartile range]

†

N = Number of comparisons

Design feature 

present 

Design feature 

absent 

Design feature 

present 

Design feature 

absent 

RCT 28.3 

[10.3, 36.6] 

N = 1012, 13, 16, 19, 

25, 45, 53, 67, 72, 78

13.6 

[11.8, 15.0] 

N = 44, 8, 14, 21

3.5 

[1.2, 8.8] 

N = 107, 15, 26, 38, 60,

61, 68, 69, 74, 79

16.2 

[7.1, 22.9] 

N = 64, 14, 21, 29, 54, 58

Providers blinded NA 

N = 0 

16.2 

[10.3, 32.2] 

N = 144, 8, 12–14, 16, 19, 

21, 25, 45, 53, 67, 72, 78

NA 

N = 0 

6.0 

[1.5, 17.5] 

N = 164, 7, 14, 15, 21, 26, 

29, 38, 54, 58, 60, 61, 68, 69, 

74, 79

Patients blinded -1.4 

[-3.6, 6.3] 

N = 34, 25, 67

25.0 

[12.7, 35.2] 

N = 118, 12–14, 16, 19,

21, 45, 53, 72, 78

5.0 

[1.8, 6.0] 

N = 74, 25, 58, 60, 68, 69, 

74

13.4 

[1.1, 19.0] 

N = 97, 14, 15, 21, 29, 38, 54,

61, 79

Unit of analysis same as

unit of allocation 

20.7 

[9.0, 31.8] 

N = 412, 14, 45, 53

16.2 

[12.4, 34.8] 

N = 104, 8, 13, 16, 19, 21, 

25, 67, 72, 78

9.4 

[1.1, 19.0] 

N = 97, 14, 15, 26, 29, 38, 

61, 69, 79

5.0 

[3.5, 10.2] 

N = 74, 21, 54, 58, 60, 68, 74

Concealment allocation 13.4 

[9.7, 38.0] 

N = 912, 13, 16, 19,

21, 25, 67, 72, 78

18.6 

[13.8, 31.6] 

N = 54, 8, 14, 45, 53

5.0 

[1.6, 13.4] 

N = 915, 21, 26, 60, 61, 

68, 69, 74, 79

9.4 

[3.1, 21.6] 

N = 74, 7, 14, 29, 38, 54, 58

Total (i.e., irrespective 

of design feature 

presence or absence) 

16.2 

[10.3, 32.2] 

N = 144, 8, 12–14, 16, 19, 21, 25, 45, 53, 67, 72, 78

6.0 

[1.5, 17.5] 

N = 164, 7, 14, 15, 21, 26, 29, 38, 54, 58, 60, 61, 68, 69, 74, 79

* In this table, all design features whose presence was judged as “unclear” were coded as absent. 

† When N = 2, square brackets show the actual results of each study rather than interpolated inter-quartile range. 

86
Table 10c. Association of methodologic features* with summary adherence outcomes

Median improvement in proportion

of provider adherence to 

recommended practice 

 [inter-quartile range]

†

N = Number of comparisons

Median improvement in proportion of

patient adherence

 [inter-quartile range]

†

N = Number of comparisons

Design feature 

present 

Design feature 

absent 

Design feature 

present 

Design feature 

absent 

RCT 2.3 

[-0.5, 3.7] 

N = 610, 25, 26, 44,

67, 69

5.0 

[2.6, 6.8] 

N = 43, 4, 20, 58

1.90 

[-0.38, 2.35] 

N = 322, 45, 69

7.3 

[5.15, 9.45] 

N = 24, 8

Providers blinded NA 

N = 0 

3.0 

[1.0, 5.5] 

N = 103, 4, 10, 20, 25, 26, 

44, 58, 67, 69

NA 

N = 0 

2.8 

[1.9, 3.0] 

N = 54, 8, 22, 45, 69

Patients blinded 3.3 

[0.6, 6.0] 

N = 93, 4, 20, 25, 26, 

44, 58, 67, 69

2.0 

N = 110

0.17 

[-1.25, 1.59] 

N = 24, 69

2.8 

[2.35, 7.2] 

N = 38, 22, 45

Unit of analysis same as

unit of allocation 

4.0 

[3.0, 5.0] 

N = 310, 26, 69

2.7 

[-0.4, 5.0] 

N = 73, 4, 20, 25, 44, 58, 

67

1.9 

[-0.38, 2.35] 

N = 322, 45, 69

7.3 

[5.15, 9.45] 

N = 24, 8

Concealment allocation 3.3 

[-1.3, 4.0] 

N = 53, 25, 26, 67, 69

2.7 

[2.0, 6.7] 

N = 54, 10, 20, 44, 58

-2.66 

N = 169

2.9 

[2.58, 5.15] 

N = 44, 8, 22, 45

Total (i.e., irrespective 

of design feature 

presence or absence) 

3.0 

[1.0, 5.5] 

N = 103, 4, 10, 20, 25, 26, 44, 58, 67, 69

2.8 

[1.9, 3.0] 

N = 54, 8, 22, 45, 69

* In this table, all design features whose presence was judged as “unclear” were coded as absent. 

† When N = 2, square brackets show the actual results of each study rather than interpolated inter-quartile range.

87
Table 11. Comparison of study design by quality improvement strategy on blood pressure outcomes

Median Reduction in SBP (mmHg) 

[inter-quartile range*] 

N = Number of comparisons

Median Improvement in DBP (mmHg) 

[inter-quartile range*] 

N = Number of comparisons

All

Comparisons 

RCT Non-RCT†

 All

Comparisons 

RCT Non-RCT†

 

All QI types 4.5 

[1.5, 11.0] 

N = 33 

6.8 

[1.5, 13.0] 

N = 25 

4.3 

[3.1, 8.1] 

N = 8 

2.1 

[-0.2, 5.0] 

N = 43 

2.0 

[0.0, 5.0] 

N = 33 

2.7 

[-0.9, 4.6] 

N = 10 

Provider 

education 

2.7 

[1.1, 6.0] 

N = 10 

2.0 

[0.3, 5.1] 

N = 7 

3.8 

[2.4, 5.8] 

N = 3 

0.7 

[-0.3, 3.3] 

N = 13 

0.6 

[0.1, 1.3] 

N = 8 

3.3 

[-0.6, 3.8] 

N = 5 

No provider 

education 

8.2 

[2.8, 13.7] 

N = 22 

10.1 

[2.6, 14.1] 

N = 17 

4.5 

[4.0, 9.3] 

N = 5 

2.5 

[-0.1, 6.4] 

N = 30 

2.8 

[0.0, 6.7] 

N = 25 

2.1 

[-1.0, 5.0] 

N = 5 

Provider 

reminders 

6.8 

[3.0, 9.4] 

N = 3 

3.0 

[-0.8, 6.8] 

N = 2 

12.0 

N = 1 

2.1 

[0.9, 6.6] 

N = 3 

0.9 

[-0.3, 2.1] 

N = 2 

11.0 

N = 1 

No provider 

reminders 

4.3 

[1.6, 10.8] 

N = 30 

6.9 

[1.8, 13.5] 

N = 23 

4.0 

[2.4, 6.1] 

N = 7 

2.1 

[-0.2, 5.0] 

N = 40 

2.0 

[0.0, 5.3] 

N = 31 

2.1 

[-1.0, 3.8] 

N = 9 

Facilitated 

relay

5.7 

[2.4, 11.8] 

N = 18 

6.9 

[2.3, 13.0] 

N = 13 

4.5 

[4.0, 9.3] 

N = 5 

1.1 

 [-1.0, 3.4] 

N = 20 

1.6 

[-0.1, 3.9] 

N = 15 

-1.0 

[-1.6, 2.1] 

N = 5 

No facilitated 

relay

3.8 

[-0.9, 8.9] 

N = 15 

5.1 

[-0.8, 11.1] 

N = 12 

3.8 

[1.4, 5.8] 

N = 3 

3.7 

[0.2, 5.0] 

N = 23 

2.9 

[0.1, 5.5] 

N = 18 

3.8 

[3.3, 4.8] 

N = 5 

Patient 

education 

8.1 

[3.3, 11.8] 

N = 18 

8.1 

[3.3, 12.5] 

N = 14 

6.6 

[2.6, 10.0] 

N = 4 

3.3 

[0.4, 5.0] 

N = 25 

2.8 

[-0.3, 5.9] 

N = 19 

3.5 

 [2.4, 4.7] 

N = 6 

No patient 

education 

2.6 

[1.2, 7.3] 

N = 15 

2.3 

[1.2, 10.5] 

N = 11 

4.3 

[3.3, 5.3] 

N = 4 

0.6 

[-0.3, 3.5] 

N = 18 

0.8 

[0.0, 3.5] 

N = 14 

-1.3 

 [-1.7, 0.5] 

N = 4 

Selfmanagement 

3.6 

[2.1, 9.5] 

N = 12 

3.3 

[1.0, 9.3] 

N = 10 

6.6 

[3.8, 9.3] 

N = 2 

2.1 

[0.4, 5.0] 

N = 17 

2.1 

[0.1, 5.9] 

N = 15 

2.9 

 [2.1, 3.8] 

N = 2 

 No selfmanagement 

6.8 

[1.5, 12.0] 

N = 21 

7.1 

[1.7, 13.6] 

N = 15 

4.3 

[1.8, 6.9] 

N = 6 

1.5 

[-0.5, 5.0] 

N = 26 

1.5 

[0.0, 4.9] 

N = 18 

1.3 

 [-1.2, 4.9] 

N = 8 

Patient 

reminders 

2.8 

[-1.5, 5.1] 

N = 8 

2.8 

[-1.7, 6.0] 

N = 6 

1.8 

[-1.0, 4.5] 

N = 2 

0.5 

[-2.1, 3.4] 

N = 12 

0.5 

[-2.3, 2.5] 

N = 10 

1.7 

 [-1.6, 5.0] 

N = 2 

No patient 

reminders 

7.1 

[2.0, 12.0] 

N = 25 

7.1 

[1.7, 13.5] 

N = 19 

5.9 

[3.9, 8.9] 

N = 6 

2.1 

[0.0, 5.0] 

N = 31 

2.1 

[0.3, 5.3] 

N = 23 

2.7 

 [-0.7, 4.1] 

N = 8 

Audit and 

feedback 

1.5 

[1.3, 1.8] 

N = 3 

1.5 

[1.3, 1.8] 

N = 3 

- - - - 

- - - - 

N = 0 

0.5 

[0.5, 1.0] 

N = 4 

0.5 

[0.5, 1.0] 

N = 4 

- - - - 

- - - - 

N = 0 

88
Table 11. Comparison of study design by quality improvement strategy on blood pressure outcomes (continued)

No audit and 

feedback 

6.9 

[2.4, 11.8] 

N = 30 

7.0 

[2.4, 13.7] 

N = 22 

4.3 

[3.1, 8.1] 

N = 8 

2.1 

[-0.5, 5.0] 

N = 39 

2.1 

[-0.1, 5.6] 

N = 29 

2.7 

[-0.9, 4.6] 

N = 10 

Organizational 

change

10.1 

[3.9, 14.0] 

N = 19 

11.0 

[5.2, 16.2] 

N = 15 

6.9 

[3.1, 10.0] 

N = 4 

4.4 

[-0.5, 6.9] 

N = 23 

4.4 

[-0.5, 6.9] 

N = 19 

3.6 

 [1.2, 6.5] 

N = 4 

No 

organizational

change

2.3 

[1.0, 4.0] 

N = 14 

1.8 

[0.6, 3.1] 

N = 10 

3.9 

[3.1, 4.9] 

N = 4 

0.6 

[-0.2, 2.1] 

N = 20 

0.6 

[0.1, 1.9] 

N = 14 

1.4 

 [-0.9, 3.7] 

N = 6 

Financial 

incentives 

-13.3 

N = 1 

-13.3 

N = 1 

- - - - 

- - - - 

- - - - 

0.0 

[-2.0, 2.5] 

N = 3 

0.0 

[-2.0, 2.5] 

N = 3 

- - - - 

- - - - 

N = 0 

No financial 

incentives 

5.6 

[1.9, 11.3] 

N = 32 

6.8 

[1.9, 13.2] 

N = 24 

4.3 

[3.1, 8.1] 

N = 8 

2.1 

[-0.2, 5.0] 

N = 40 

2.1 

 [0.1, 5.5] 

N = 30 

2.7 

[-0.9, 4.6] 

N = 10 

Information 

systems 

2.2 

[1.1, 4.2] 

N = 10 

2.2 

[1.4, 4.7] 

N = 8 

2.8 

[1.9, 3.6] 

N = 2 

0.6 

[-1.3, 2.1] 

N = 11 

0.7 

[0.0, 2.1] 

N = 9 

-1.8 

 [-1.6, -2.0] 

N = 2 

No 

information 

systems 

7.1 

[3.0, 12.5] 

N = 23 

7.1 

[2.6, 13.9] 

N = 17 

5.9 

[3.9, 8.9] 

N = 6 

3.0 

[0.0, 5.2] 

N = 32 

2.5 

[0.0, 5.9] 

N = 24 

3.5 

 [1.4, 4.9] 

N = 8 

* When N = 2, square brackets show the actual results of each study rather than interpolated inter-quartile range. 

† Includes 6 publications (with 7 comparisons) that are quasi-RCTs3, 8, 9, 17, 43, 58, 64 and 9 publications (with 11 comparisons) 

 that are controlled before-after studies.2, 4, 14, 20, 21, 29, 36, 54, 63, 65, 66

89
Table 12a. Association of study size with systolic blood pressure outcomes 

Median Reduction in SBP (mmHg) 

[inter-quartile range]* 

N = Number of comparisons

All Comparisons Comparisons

with sample size 

in lowest

quartile

Comparisons

with sample size 

in lower 2 

quartiles 

Comparisons

with sample size 

in upper 2 

quartiles

Comparisons

with sample size 

in highest 

quartile

All QI types 4.5 

[1.5, 11.0] 

N = 33 

14.0 

[12.3, 19.2] 

N = 8 

11.1 

[5.7, 15.2] 

N = 16 

3.3 

[1.0, 4.5] 

N = 17 

3.3 

 [2.3, 4.5] 

N = 9 

Provider 

education 

2.7 

[1.1, 6.0] 

N = 10 

9.0 

N = 1 

2.0 

[0.5, 5.5] 

N = 3 

3.3 

[1.2, 5.3] 

N = 7 

3.6 

[2.9, 4.8] 

N = 4 

No provider 

education 

7.1 

[2.5, 13.5] 

N = 23 

14.1 

[13.5, 19.8] 

N = 7 

13.0 

[9.3, 18.3] 

N = 13 

3.0 

[0.9, 4.4] 

N = 10 

3.3 

[2.3, 4.5] 

N = 5 

Provider 

reminders 

6.8 

[3.0, 9.4] 

N = 3 

- - - - 

- - - - 

N = 0 

12.0 

N = 1 

3.0 

[-0.8, 6.8] 

N = 2

- - - - 

- - - - 

N = 0 

No provider 

reminders 

4.3 

[1.6, 10.8] 

N = 30 

14.0 

[12.3, 19.2] 

N = 8 

10.1 

[4.5, 16.2] 

N = 15 

3.3 

[1.3, 4.3] 

N = 15

3.3 

[2.3, 4.5] 

N = 9 

Facilitated relay 5.7 

[2.4, 11.8] 

N = 18 

13.5 

[12.0, 16.8] 

N = 4 

10.7 

[7.4, 13.7] 

N = 10 

3.0 

[2.0, 4.1] 

N = 8 

3.3 

[2.8, 3.9] 

N = 3 

No facilitated 

relay

3.8 

[-0.9, 8.9] 

N = 15 

16.4 

[13.1, 19.2] 

N = 4 

12.1 

[1.8, 17.5] 

N = 6 

3.3 

[-0.8, 6.8] 

N = 9 

3.6 

[1.9, 6.3] 

N = 6 

Patient 

education 

8.1 

[3.3, 11.8] 

N = 18 

13.0 

 [10.1, 13.9] 

N = 5 

11.1 

[9.1, 13.7] 

N = 10 

3.3 

[0.1, 4.6] 

N = 8 

3.3 

[3.3, 3.8] 

N = 5 

No patient 

education 

2.6 

[1.2, 7.3] 

N = 15 

18.6 

 [16.4, 19.8] 

N = 3 

8.1 

[1.3, 17.5] 

N = 6 

2.6 

[1.5, 4.5] 

N = 9 

3.4 

[2.1, 5.3] 

N = 4 

Selfmanagement 

3.6 

[2.1, 9.5] 

N = 12 

13.9 

[12.0, 19.8] 

N = 3 

9.7 

[7.5, 13.0] 

N = 6 

3.0 

[1.0, 3.3] 

N = 6 

3.3 

[3.3, 3.6] 

N = 3 

No selfmanagement 

6.8 

[1.5, 12.0] 

N = 21 

14.1 

[13.0, 18.6] 

N = 5 

12.5 

[3.8, 17.3] 

N = 10 

4.0 

[1.2, 7.0] 

N = 11 

3.4 

[1.7, 6.5] 

N = 6 

Patient 

reminders 

2.8 

[-1.5, 5.1] 

N = 8 

- - - - 

- - - - 

N = 0 

6.9 

[-3.2, 12.6] 

N = 3 

2.3 

[-1.0, 3.3] 

N = 5 

2.8 

[1.5, 3.6] 

N = 4 

No patient 

reminders 

7.1 

[2.0, 12.0] 

N = 25 

14.0 

[12.3, 19.2] 

N = 8 

12.0 

[9.0, 14.1] 

N = 13 

3.6 

[1.4, 6.9] 

N = 12 

3.8 

[3.3, 7.1] 

N = 5 

90
Table 12a. Association of study size with systolic blood pressure outcomes (continued)

Audit and 

feedback 

1.5 

[1.3, 1.8] 

N = 3 

- - - - 

- - - - 

N = 0 

1.5 

[1.0, 2.0] 

N = 2 

1.5 

N = 1 

1.5 

N = 1 

No audit and 

feedback 

6.9 

[2.4, 11.8] 

N = 30 

14.0 

[12.3, 19.2] 

N = 8 

12.5 

[9.1, 17.3] 

N = 14 

3.3 

[0.9, 5.1] 

N = 16 

3.6 

[3.1, 5.2] 

N = 8 

Organizational 

change

10.1 

[3.9, 14.0] 

N = 19 

14.0 

[12.3, 19.2] 

N = 8 

13.5 

[9.9, 18.4] 

N = 12 

3.3 

 [0.7, 5.8] 

N = 7 

3.3 

[2.3, 4.5] 

N = 5 

No 

organizational

change

2.3 

[1.0, 4.0] 

N = 14 

- - - - 

- - - - 

N = 0 

1.5 

[0.5, 3.2] 

N = 4 

3.0 

 [1.1, 4.0] 

N = 10 

3.6 

[2.9, 4.8] 

N = 4 

Financial 

incentives 

-13.3 

N = 1 

- - - - 

- - - - 

N = 0 

-13.3 

N = 1 

- - - - 

- - - - 

N = 0 

- - - - 

- - - - 

N = 0 

No financial 

incentives 

5.6 

[1.9, 11.3] 

N = 32 

14.0 

[12.3, 19.2] 

N = 8 

12.0 

[8.0, 16.2] 

N = 15 

3.3 

 [1.0, 4.5] 

N = 17 

3.3 

[2.3, 4.5] 

N = 9 

Information 

systems 

2.2 

[1.1, 4.2] 

N=10 

17.3 

[9.0, 25.7] 

N=2 

5.5 

[1.8, 13.2] 

N=4 

1.9 

 [1.1, 3.1] 

N=6 

2.8 

[2.1, 3.6] 

N=4 

No information 

systems 

7.1 

[3.0, 12.5] 

N=23 

14.0 

[13.2, 17.5] 

N=6 

12.5 

[8.7, 15.2] 

N=12 

3.8 

 [0.9, 7.0] 

N=11 

3.8 

[3.3, 7.1] 

N=5 

* When N = 2, square brackets show the actual results of each study rather than interpolated inter-quartile range.

91
Table 12b. Association of study size with diastolic blood pressure outcomes 

Median Reduction in DBP (mmHg) 

[inter-quartile range]* 

N = Number of comparisons

All Comparisons Comparisons

with sample size 

in lowest

quartile

Comparisons

with sample size 

in lower 2 

quartiles 

Comparisons

with sample size 

in upper 2 

quartiles

Comparisons

with sample size 

in highest 

quartile

All QI types 2.1 

[-0.2, 5.0] 

N = 43 

5.0 

[1.4, 10.7] 

N = 11 

2.1 

[0.0, 7.0] 

N = 21 

1.9 

[-0.9, 3.8] 

N = 22 

3.3 

 [-0.3, 4.1] 

N = 11 

Provider 

education 

0.7 

[-0.3, 3.3] 

N = 13 

-0.2 

[-0.6, 0.3] 

N = 2 

0.3 

[-0.3, 0.8] 

N = 4 

2.1 

[-0.3, 3.7] 

N = 9 

3.5 

[1.3, 3.8] 

N = 6 

No provider 

education 

2.5 

[-0.1, 6.4] 

N = 30 

6.7 

[4.0, 12.5] 

N = 9 

5.0 

[0.6, 9.0] 

N = 17 

1.6 

[-1.0, 4.4] 

N = 13 

0.0 

[-1.6, 4.4] 

N = 5 

Provider 

reminders 

2.1 

[0.9, 6.6] 

N = 3 

------ 

------ 

N = 0 

11.0 

N = 1 

0.9 

[-0.3, 2.1] 

N = 2

- - - - 

- - - - 

N = 0 

No provider 

reminders 

2.1 

[-0.2, 5.0] 

N = 40 

5.0 

[2.1, 10.7] 

N = 11 

2.1 

[0.3, 7.0] 

N = 20 

1.9 

[-1.0, 4.0] 

N = 20

3.3 

[0.3, 4.1] 

N = 11 

Facilitated relay 1.1 

 [-1.0, 3.4] 

N = 20 

2.1 

[1.3, 7.0] 

N = 7 

2.0 

[0.4, 7.5] 

N = 12 

-1.0 

[-1.7, 1.7] 

N = 8 

-2.0 

[-2.4, -1.6] 

N = 2 

 No facilitated

relay

3.7 

[0.2, 5.0] 

N = 23 

10.8 

[6.0, 15.5] 

N = 4 

4.0 

[0.4, 7.0] 

N = 9 

3.5 

[0.1, 4.7] 

N = 14 

3.7 

[0.6, 4.4] 

N = 9 

Patient 

education 

3.3 

[0.4, 5.0] 

N = 25 

5.9 

 [2.8, 8.4] 

N = 6 

5.0 

[0.4, 7.0] 

N = 13 

3.0 

[1.0, 4.0] 

N = 12 

3.7 

[3.4, 4.3] 

N = 6 

No patient 

education 

0.6 

[-0.3, 3.5] 

N = 18 

4.0 

 [2.0, 14.8] 

N = 5 

1.5 

[0.5, 6.7] 

N = 8 

0.1 

[-1.5, 1.8] 

N = 10 

0.0 

[-1.6, 0.6] 

N = 5 

Selfmanagement 

2.1 

[0.4, 5.0] 

N = 17 

7.9 

[5.6, 9.9] 

N = 4 

1.3 

[0.0, 6.9] 

N = 10 

2.8 

[1.8, 3.7] 

N = 7 

3.8 

[3.7, 4.4] 

N = 3 

No selfmanagement 

1.5 

[-0.5, 5.0] 

N = 26 

4.0 

[1.3, 9.9] 

N = 7 

4.0 

[0.8, 9.0] 

N = 11 

0.0 

[-1.0, 3.8] 

N = 15 

0.3 

[-0.9, 3.6] 

N = 8 

Patient 

reminders 

0.5 

[-2.1, 3.4] 

N = 12 

- - - - 

N = 0 

0.5 

[-2.8, 5.4] 

N = 6 

0.0 

[-1.9, 2.5] 

N = 6 

-2.0 

[-2.4, -1.6] 

N = 2 

No patient 

reminders 

2.1 

[0.0, 5.0] 

N = 31 

5.0 

[2.0, 10.7] 

N = 11 

4.0 

[0.8, 10.0] 

N = 15 

2.1 

[-0.4, 4.0] 

N = 16 

3.7 

[0.6, 4.4] 

N = 9 

92
Table 12b. Association of study size with diastolic blood pressure outcomes (continued)

Audit and 

feedback 

0.6 

[0.5, 1.0] 

N = 4 

1.3 

[0.7, 2.0] 

N = 2 

0.7 

[0.3, 1.3] 

N = 3 

0.6 

N = 1 

0.6 

N = 1 

No audit and 

feedback 

2.1 

[-0.5, 5.0] 

N = 39 

6.7 

[4.0, 12.0] 

N = 9 

4.5 

[0.5, 8.5] 

N = 18 

2.1 

[-1.0, 3.8] 

N = 21 

3.5 

[-0.5, 4.3] 

N = 10 

Organizational 

change

4.4 

[-0.5, 6.9] 

N = 23 

6.7 

[4.0, 12.5] 

N = 9 

6.9 

[3.5, 11.4] 

N = 12 

2.8 

 [-1.3, 4.7] 

N = 11 

1.9 

[-1.2, 4.2] 

N = 6 

No 

organizational

change

0.6 

[-0.2, 2.1] 

N = 20 

1.3 

[0.7, 2.0] 

N = 2 

0.6 

[0.0, 1.0] 

N = 9 

1.6 

 [-0.5, 2.7] 

N = 11 

3.3 

[0.6, 3.8] 

N = 5 

Financial 

incentives 

0.0 

[-2.0, 2.5] 

N = 3 

- - - - 

- - - - 

N = 0 

-3.9 

N = 1 

2.5 

[0, 5.0] 

N = 2 

2.5 

[0, 5.0] 

N = 2 

No financial 

incentives 

2.1 

[-0.2, 5.0] 

N = 40 

5.0 

[2.0, 10.7] 

N = 11 

3.0 

[0.5, 7.5] 

N = 20 

1.8 

 [-1.0, 3.7] 

N = 20 

3.3 

[-0.6, 3.8] 

N = 9 

Information 

systems 

0.6 

[-1.3, 2.1] 

N = 11 

1.3 

[0.3, 4.6] 

N = 4 

0.7 

[0.0, 2.0] 

N = 5 

-0.5 

 [-1.9, 1.7] 

N = 6 

-0.5 

[-1.8, 1.4] 

N = 4 

No information 

systems 

3.0 

[0.0, 5.2] 

N = 32 

6.7 

[4.5, 11.9] 

N = 7 

4.5 

[0.5, 7.5] 

N = 16 

2.5 

 [-0.4, 4.5] 

N = 16 

3.8 

[1.6, 4.6] 

N = 7 

* When N = 2, square brackets show the actual results of each study rather than interpolated inter-quartile range.

93
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2000;320(7236):686–90. 

65. McGhee SM, McInnes GT, Hedley AJ, et al. Coordinating and standardizing long-term care: evaluation of the west of 

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66. Krishan I, Davis CS, Nobrega FT,et al. The Mayo three-community hypertension control program. IV. Five-year outcomes

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68. Dickinson, et al. Improving hypertension control: impact of computer feedback and physician education. [Additional 

comparison (2)] Med Care 1981;19:843. 

69. Gullion DS, Tschann JM, Adamson TE, et al. Management of hypertension in private practices: a randomized controlled

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1988;8:239–55. 

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71. Velez R, Anderson L, McFall S, et al. Improving patient follow-up in incidental screening through referral letters. 

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73. Artinian NT, Washington OG, Templin TN. Effects of home telemonitoring and community-based monitoring on blood 

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74. Dickinson, et al. Improving hypertension control: impact of computer feedback and physician education. [Additional 

comparison] Med Care 1981;19:843. 

75. Rehder TL, McCoy LK, Blackwell B, et al. Improving medication compliance by counseling and special prescription 

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76. Saunders LD, Irwig LM, Gear JS, et al. A randomized controlled trial of compliance improving strategies in Soweto 

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77. Pritchard DA, Hyndman J, Taba F. Nutritional counselling in general practice: a cost effective analysis. [Additional 

comparison] J Epidemiol Community Health 1999;53(5):311–6. 

78. Foote A, Erfurt JC. Hypertension control at the work site. Comparison of screening and referral alone, referral and followup, and on-site treatment. [Additional comparison] N Engl J Med 1983;308(14):809–13. 

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80. McDowell I, Newell C, Rosser W. A randomized trial of computerized reminders for blood pressure screening in primary

care. [Additional comparison] Med Care 1989;27(3):297–305. 

97
81. McDowell I, Newell C, Rosser W. A randomized trial of computerized reminders for blood pressure screening in primary

care. [Additional comparison (2)] Med Care 1989;27(3):297–305. 

82. Vivian EM. Improving blood pressure control in a pharmacist-managed hypertension clinic. [Additional comparison] 

Pharmacotherapy 2002;22(12):1533–40. 

98