Evidence-based Synthesis Program 

Self-Monitoring of Blood Glucose in 

Patients with Type 2 Diabetes 

Mellitus: Meta Analysis of 

Effectiveness

Department of Veterans Affairs

Health Services Research & Development Service

September 2007

Investigators:

Paul Shekelle, MD, PhD 

Director

 

Brett Munjas, BA

Project Manager/Literature Database Manager

Maria Romanova, MD

Ali Towfigh, MD

Physician Reviewers

Jane Weinreb, MD

Content Expert

Annie Zhou, MS

Marika Suttorp, MS

Statisticians

Prepared for: 

Department of Veterans Affairs

Veterans Health Administration

Health Services Research & Development Service

Washington, DC 20420 

Prepared by:

Greater Los Angeles Veterans Affairs Healthcare 

System/Southern California/RAND Evidence-based 

Practice Center 

Los Angeles, CA
HSR&D Evidence Synthesis Program – ii 

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PREFACE 

VA’s Health Services Research and Development Service (HSR&D) works to improve the cost, 

quality, and outcomes of health care for our nation’s veterans. Collaborating with VA leaders, 

managers, and policy makers, HSR&D focuses on important health care topics that are likely to have 

significant impact on quality improvement efforts. One significant collaborative effort is HSR&D’s 

Evidence-based Synthesis Program (ESP). Through this program, HSR&D provides timely and 

accurate evidence syntheses on targeted health care topics. These products will be disseminated 

broadly throughout VA and will: inform VA clinical policy, develop clinical practice guidelines, set 

directions for future research to address gaps in knowledge, identify the evidence to support VA 

performance measures, and rationalize drug formulary decisions. 

HSR&D provided funding for the two Evidence Based Practice Centers (EPCs) supported by the 

Agency for Healthcare Research and Quality (AHRQ) that also had an active and publicly 

acknowledged VA affiliation—Southern California EPC and Portland, OR EPC—so they could 

develop evidence syntheses on requested topics for dissemination to VA policymakers. A planning 

committee with representation from HSR&D, Patient Care Services, Office of Quality and 

Performance, and the VISN Clinical Management Officers, has been established to identify priority 

topics and to insure the quality of final reports. 

Comments on this evidence report are welcome and can be sent to Susan Schiffner, ESP Program 

Manager, at Susan.Schiffner@va.gov. 
HSR&D Evidence Synthesis Program – v 

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TABLE OF CONTENTS 

INTRODUCTION.............................................................................................................................................................. 1

BACKGROUND....................................................................................................................................................................... 1

METHODS ......................................................................................................................................................................... 2

TOPIC DEVELOPMENT ........................................................................................................................................................... 2

SEARCH STRATEGY............................................................................................................................................................... 2

STUDY SELECTION ................................................................................................................................................................ 3

DATA ABSTRACTION............................................................................................................................................................. 4

QUALITY ASSESSMENT.......................................................................................................................................................... 4

DATA SYNTHESIS.................................................................................................................................................................. 4

RATING THE BODY OF EVIDENCE........................................................................................................................................... 5

PEER REVIEW........................................................................................................................................................................ 6

RESULTS ........................................................................................................................................................................... 7

LITERATURE FLOW ............................................................................................................................................................... 7

DESCRIPTION OF THE EFFICACY EVIDENCE........................................................................................................................... 7

KEY QUESTION #1: IS REGULAR SELF-MONITORING OF BLOOD GLUCOSE EFFECTIVE IN ACHIEVING TARGET A1C LEVELS FOR 

PATIENTS WITH TYPE 2 DIABETES? ...................................................................................................................................... 14

KEY QUESTION #2: IS REGULAR SELF-MONITORING OF BLOOD GLUCOSE EFFECTIVE IN MAINTAINING TARGET A1C LEVELS 

FOR PATIENTS WITH TYPE 2 DIABETES? ............................................................................................................................... 19

KEY QUESTION 3: DOES REGULAR SELF-MONITORING OF BLOOD GLUCOSE REDUCE THE FREQUENCY OF HYPOGLYCEMIA IN 

PATIENTS WITH TYPE 2 DIABETES? ...................................................................................................................................... 19

KEY QUESTION 4: IS THERE EVIDENCE THAT DIFFERENT FREQUENCIES OF TESTING RESULT IN DIFFERENCES IN 

IMPROVEMENTS IN A1C?..................................................................................................................................................... 20

SUMMARY AND DISCUSSION.................................................................................................................................... 21

LIMITATIONS....................................................................................................................................................................... 21

CONCLUSIONS..................................................................................................................................................................... 22

FUTURE RESEARCH .................................................................................................................................................... 24

REFERENCE LIST......................................................................................................................................................... 25

APPENDIX A. DATA COLLECTION FORMS........................................................................................................... 28

APPENDIX B. PEER REVIEW COMMENTS TABLE .............................................................................................. 51

APPENDIX C. EVIDENCE TABLE.............................................................................................................................. 56

In-Text Figure and Tables

TABLE 1. COMPARISON OF RCTS WE INCLUDED IN OUR REVIEW WITH THOSE INCLUDED IN THREE RECENT SYSTEMATIC 

REVIEWS...................................................................................................................................................................... 8

FIGURE 1. SELF-MONITORING OF BLOOD GLUCOSE LITERATURE FLOW ............................................................................... 9

TABLE 2. COMPONENTS OF EACH ARM OF THE 10 RCTS..................................................................................................... 10

FIGURE 2. ANALYSIS OF MEAN DIFFERENCE BETWEEN CONTROL AND SMBG GROUP AT FOLLOW-UP.............................. 15

FIGURE 3. ANALYSIS OF DIFFERENCE OF DIFFERENCES BETWEEN CONTROL AND SMBG GROUP AT FOLLOW-UP ............. 16

FIGURE 4. PUBLICATION BIAS FOR THE 10 RCTS................................................................................................................ 17

TABLE 3. STUDIES OF SELF-MONITORING OF BLOOD GLUCOSE IN VETERANS .................................................................... 18
HSR&D Evidence Synthesis Program – 1 

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INTRODUCTION 

Background 

According to the World Health Organization, at least 180 million people worldwide suffer from 

diabetes. 1 Though prevalent throughout the world, diabetes is more common (especially type 2) 

in more developed countries like the United States. The National Diabetes Information 

Clearinghouse estimates that diabetes costs $132 billion in the United States alone every year. 2

Given these estimates along with the projection that the worldwide incidence of diabetes will 

double in the next 20 years, 1

 intensified research into better management of this chronic disease 

is paramount. 

 

Tighter control of blood glucose is advocated as a means to reduce microvascular and 

macrovascular complications. 3

 VA has performance measures assessing the proportion of 

patients meeting certain A1c goals, currently 7% and 9%. Theoretically, self-monitoring of 

blood glucose (SMBG) can improve compliance with recommendations on diet and exercise and 

medication regimens. The American Diabetes Association has recommended that the optimal 

frequency of SMBG for patients with type 2 diabetes should be adequate to facilitate reaching 

glucose goals. This hypothesis is based on the expectation that life style changes are facilitated 

by SMBG. Under these conditions, we should expect an improvement of glycemic control 

SMBG may decrease patient management costs, and because of the high prevalence of type 2 

diabetes, efforts to establish the efficacy of SMBG in type 2 diabetes mellitus are of greater 

relevance. Methods to achieve improved glycemic control, and therefore a higher proportion of 

patients meeting target A1c levels, include diet, exercise, and medication. However, evidence 

supporting the use of SMBG for diabetics not requiring insulin is not as clear. 

The purpose of this review is to analyze the literature to answer four key questions given to us by 

VA: 1) Is regular self-monitoring of blood glucose effective in achieving target A1c levels for 

patients with type 2 diabetes?; 2) Is regular self-monitoring of blood glucose effective in 

maintaining target A1c levels for patients with type 2 diabetes?; 3) Does regular self-monitoring 

of blood glucose reduce the frequency of hypoglycemia in patients with type 2 diabetes?; 4) Is 

there evidence that different frequencies of testing result in differences in improvements in A1c? 
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METHODS 

Topic Development 

This project was nominated by Dr. Chester B. Good, from the VA Pharmacy service for the 

Evidence Synthesis Project. Key questions were discussed and finalized during a conference call 

that included the Steering Committee of the Evidence Synthesis Project and the VA Greater Los 

Angeles project site director. The final key questions are: 

1. Is regular SMBG effective in achieving target A1c levels for patients with type 2 diabetes? 

2. Is regular SMBG effective in maintaining target A1c levels for patients with type 2 diabetes? 

3. Does regular SMBG reduce the frequency of hypoglycemia in patients with type 2 diabetes? 

4. Is there evidence that different frequencies of testing result in differences in improvements in 

A1c? 

Search Strategy 

This topic has been the subject of several previous reviews. 

Faas et al. (1997) 4 This review covered the years 1976-1996 and identified 11 studies from two 

Medline searches that met the inclusion criteria. Studies were excluded if they were not RCTs 

and if the patients were exclusively using insulin. 

Coster et al. (2000) 5 This review covered the years 1990-1999 and originally identified 18 

possibly relevant studies. Non-randomized studies were excluded. The review included eight 

randomized controlled trials. Two additional randomized trials were excluded; one because it 

used fructosamine as an outcome and the other because it used cluster randomization. 

Welschen et al. (2005) 6 This review covered the years 1966 to 2004. A total of 36 articles were 

retrieved for further review of which five trials were included in the review. A total of six 

articles, one in press during the time of the initial search, were examined. Included trials looked 

at the effectiveness of SMBG compared with usual care in patients with type 2 diabetes who 

were not using insulin at the start of the trial and studies comparing SMBG and urine glucose 

monitoring. 

Balk et al. (2006, draft report for AHRQ) 7 At the time we received this draft report by the 

Tufts-NEMC EPC it had only been distributed for the purpose of peer review and discussion at 

the Medicare Coverage Advisory committee meeting and had not yet been disseminated by the 

Agency for Healthcare Research and Quality. This review, dated August 16, 2006, identified 

five RCTs that evaluated SMBG with A1c as the outcome. Reasons for exclusion from this 

review were wrong population (type 1 diabetes), sample size too small (for inclusion n≥100 in 

the intervention arm), follow-up time too short (for non-clinical outcomes follow-up time had to 

be greater than or equal to three months), intervention or outcome not of interest, design (crosssectional or retrospective), or the trial contained no primary data or duplicate data. 

Jansen (2006) 8

 This review covered the years 1966-2005. The review included studies that 

evaluated SMBG versus no self-monitoring, SMBG versus self-monitoring of urine glucose and 

SMBG with regular feedback versus monitoring without feedback. The review identified 27 
HSR&D Evidence Synthesis Program – 3 

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studies that underwent quality assessment, from which 14 trials were excluded due to the 

outcome they assessed, type of diabetes included or the intervention was not clearly described. 

The Balk et al. 7 review was not available to us at the start of this project. We judged the search 

strategy and inclusion/exclusion criteria of the review by Welschen et al. 6 to be comprehensive 

and therefore acceptable as the basis for our own review. We updated this search by searching 

PubMed from the end date of the prior search to October, 2006 and performed an update search 

in July 2007. 

The search strategy is listed below: 

DATABASE SEARCHED & TIME PERIOD COVERED: 

 PUBMED – 2004-2006 

LIMITERS: 

SEARCH STRATEGY: 

Randomized Controlled Trail AND 

Diabetes Mellitus, Type 2 AND 

Blood Glucose self-monitoring 

NUMBER OF ITEMS RETRIEVED: 23 

In addition to our PubMed search and screening references from prior reviews, we also 

performed reference mining of retrieved articles. 

Study Selection 

Two trained researchers reviewed the list of titles and selected articles for further review. The 

team of researchers consisted of two general internists, one with a special interest in diabetes. 

Each article retrieved was reviewed with a brief screening form (see Appendix A) that collected 

data on efficacy or effectiveness of SMBG alone or as part of a multi-component intervention, 

A1c and hypoglycemia reported as outcomes, the report of frequency of SMBG, duration of 

follow-up, study design, and whether or not the subjects in the study were Veterans. To be 

included in our evidence report, a study had to measure the efficacy or effectiveness of SMBG 

alone or as part of a multi-component intervention and have a follow up duration greater than or 

equal to 12 weeks (chosen because of the use of A1c as the outcome measure). Eligible study 

designs for efficacy included controlled clinical trials, RCTs, and systematic reviews/metaanalyses. Observational studies, case reports, non-systematic reviews, letters to the editor and 

other similar contributions were excluded as evidence of efficacy. To assess effectiveness, we 

required that studies assess SMBG in a Veteran population and VA healthcare delivery setting. 

RCTs and observational studies were eligible. 
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Data Abstraction 

Data were independently abstracted by two general internists trained in critical reading of the 

literature, with consensus resolution. The following data were abstracted from included trials: 

design; randomization and appropriateness; blinding and appropriateness; withdrawals and 

dropouts described; sample size enrolled and followed-up; characteristics of the population 

including percent women and race; mean, median, and range of age; mean, median and range of 

BMI; mean, median and range of duration of diabetes; reported co-morbidities; sample size and 

intervention/exposure data for each arm of the study (intervention/exposure data included 

components of the intervention, total number of visits, frequency of SMBG, number of days per 

week monitored, duration of treatment, co-therapies); outcomes measured; intervals in which the 

outcomes were measured; adverse events. Data abstraction forms are provided in Appendix A. 

The mean A1c level and standard deviation was collected by treatment arm for each reported 

follow-up point. For trials that reported a mean outcome but no standard deviation, we estimated 

the standard deviation by taking the unweighted mean standard deviation across all other trials 

that reported standard deviations for the A1c level. 9

Quality assessment 

To assess internal validity of diagnostic studies, we used the Delphi criteria10 (see Appendix A). 

We abstracted data on treatment allocation; was the method of randomization performed and was 

the treatment allocation concealed; were the groups similar at baseline regarding the most 

important prognostic indicators; were the eligibility criteria specified; was the outcome assessor 

blinded; was the care provider blinded; was the patient blinded; were point estimates and 

measures of variability presented for the primary outcome measures; did the analysis include an 

intention-to-treat analysis. Our own work 11 supports using a threshold of four for distinguishing 

“high” versus “low” quality studies. 

Data Synthesis 

Of the articles that were determined to be clinically eligible, duration of follow-up and frequency 

of SMBG were reviewed across studies to see if they were comparable. 

Since the outcome of interest was the same across all trials, a mean difference was calculated for 

each time point that reported statistical data. The mean difference is the difference between the 

follow-up mean A1c level for the SMBG group and the follow-up mean A1c level for the control 

group. A negative mean difference indicates that the SMBG group has a lower mean A1c score 

than the control group. For our main analysis, we did not control for the baseline mean A1c for 

each group (a difference of differences estimate) since there is evidence that this approach is 

susceptible to bias. 12 We presented results controlling for the baseline as a sensitivity analysis. 

A pooled estimate was calculated by follow-up time, in the following categories: 3- 6months, 6-

11 months, and 12 months or greater. The pooled estimate was calculated using the 

DerSimonian & Laird13 random effects model. In addition, we calculated a pooled estimate 

stratified by high and low quality trials. 
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Meta-regressions14 were performed to individually examine the effect of treatment frequency, 

quality score, and the baseline A1c mean on the mean difference. For trials with more than one 

follow-up time, the long term estimates were used. 

Test of heterogeneity were performed using Cochran’s Q15 and the I2 statistic. 16 A significant Q 

statistic or I2 values close to 100% represent very high degrees of heterogeneity. Publication bias 

was examined using the Begg rank correlation and Egger regression asymmetry test. All analyses 

were conducted in Stata 9.2. 17

Rating the body of evidence 

We assessed the overall quality of evidence for outcomes using a method developed by the 

Grade Working Group, which classified the grade of evidence across outcomes according to the 

following criteria: 18

o High = Further research is very unlikely to change our confidence on the estimate of 

effect. 

o Moderate = Further research is likely to have an important impact on our confidence 

in the estimate of effect and may change the estimate. 

o Low = Further research is very likely to have an important impact on our confidence 

in the estimate of effect and is likely to change the estimate. 

o Very Low = Any estimate of effect is very uncertain. 

GRADE also suggests using the following scheme for assigning the “grade” or strength of 

evidence: 

Criteria for assigning grade of evidence 

Type of evidence 

Randomized trial = high 

Observational study = low 

Any other evidence = very low

Decrease grade if: 

• Serious (-1) or very serious (-2) limitation to study quality 

• Important inconsistency (-1) 

• Some (-1) or major (-2) uncertainty about directness 

• Imprecise or sparse data (-1) 

• High probability of reporting bias (-1) 

Increase grade if: 

• Strong evidence of association-significant relative risk of > 2 (< 0.5) 

based on consistent evidence from two or more observational studies, 

with no plausible confounders (+1) 

• Very strong evidence of association-significant relative risk of > 5 

(< 0.2) based on direct evidence with no major threats to validity (+2) 

• Evidence of a dose response gradient (+1) 

• All plausible confounders would have reduced the effect (+1) 
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For this report, we used both this explicit scoring scheme and the global implicit judgment about 

“confidence” in the result. Where the two disagreed, we went with the lower of the two 

classifications. 

Peer Review

A draft version of this report was sent to three peer reviewers. Their comments and our responses 

are presented in Appendix B. 
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RESULTS 

Literature Flow 

In total, we examined 52 titles. Seventeen articles were identified from prior systematic reviews. 

The electronic update search identified 23 articles. An additional 11 articles were identified 

through reference mining. One was identified by a content expert. 

Of the titles identified through our electronic literature search, 14 were rejected as not relevant to 

the project. This left 38 from all sources. Ten articles were excluded at abstract review. In 

January 2006 we received the Balk and colleagues draft report of a review of SMBG in type 2 

diabetes. 7

 

We performed an update search in July of 2007 that resulted in two additional articles, one of 

which was excluded since it did not test SMBG. In total we reviewed 30 articles. 

We compared trials identified for our review with those identified in the three recent systematic 

reviews (Table 1). Our review included 10 trials, compared to six in the review by Welschen and 

colleagues, 6

 seven in the review by Balk and colleagues, 7 and 13 in the review by Jansen. 8

Jansen included studies of self-monitoring of urine glucose that we did not, and we included 

studies rejected by Balk and/or by Welschen for a variety of reasons, detailed in Table 1. 

Initial screening of the articles resulted in 14 RCTs that measured the effect of SMBG compared 

to a group not receiving SMBG and monitored A1c levels with at least three months of followup. Four were excluded; one because the trial presented duplicate data, the other three because 

the trials compared a control group of SMBG to an intervention group of SMBG plus other 

components. (Figure 1) We identified five observational studies that assessed the effectiveness 

of SMBG in diabetic Veterans. 

Description of the Efficacy Evidence 

The 10 RCTs ranged in size from 29 to 988 subjects. All patients had type 2 diabetes, the mean 

duration of which was three to 13 years. All trials but one included only patients treated without 

insulin, the one exception being a trial from Bangladesh that included patients on oral 

hypoglycemic agents or insulin and not specifying how many of each type. The average age of 

patients was between 50 and 66. Almost all trials included counseling/education with SMBG in 

the intervention group, but other components of the intervention were varied (Table 2). 

All trials measured A1c as an outcome; five trials assessed this at six months, three trials 

assessed this at three months, and five trials assessed this at one year or more. The quality of 

trials varied; most trials scored positively on less then half of the criteria on the Delphi list. 10

Details of each trial are presented in the Evidence Table (Appendix C). We now present a brief 

synopsis of each trial. 
HSR&D Evidence Synthesis Program – 8 

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Table 1. Comparison of RCTs we included in our review with those included in three 

recent systematic reviews. 

 

Welschen 

(2005) 6

Balk (2006) 7

Jansen 

(2006) 8

Our 

Review 

Comments 

Wing RR, Epstein LH, Nowalk MP et al. Does self-monitoring of blood 

glucose levels improve dietary compliance for obese patients with type II 

diabetes? Am J Med. 1986 Nove; 81(5):830-6. 19

 X X 

Fontbonne A, Billault B, Acosta M et al. Is glucose self-monitoring beneficial 

in non-insulin-treated diabetic patients? Results of a randomized 

comparative trial. Diabete Metab. 1989 Sept-1989 Oct 31; 15(5):255-60. 20

X X X X 

Estey AL, Tan MH, Mann K. Follow-up intervention: its effect on compliance 

behavior to a diabetes regimen. Diabetes Educ. 1990 Jul-1990 Aug 31; 

16(4):291-5. 21

 X Excluded in our review because it 

evaluated SMBG vs. SMBG plus 

other components. 

Allen BT, DeLong ER, Feussner JR. Impact of glucose self-monitoring on 

non-insulin-treated patients with type II diabetes mellitus: Randomized 

controlled trial comparing blood and urine testing. Diabetes Care. 1990 

Oct; 13(10):1044-50. 22

X X Excluded in our review due to the 

comparison of SMBG to selfmonitoring of urine glucose (SMUG). 

Rutten G, van Eijk J, de Noebl E, et al. Feasibility and effects of a diabetes 

type II protocol with blood glucose self-monitoring in general practice. 

Fam Pract. 1990 Dec; 7(4):273-8. 23

 X X X 

Muchmore DB, Springer J, Miller M. Self-monitoring of blood glucose in 

overweight type 2 diabetic patients. Acta Diabetol. 1994 Dec; 31(4):215-

09 24

X X X 

Jaber LA, Halapy H, Fernet M, et al. Evaluation of a pharmaceutical care 

model on diabetes management. Ann Pharmacother. 1996 Mar; 

30(2):238-43. 25

 X X 

Miles P. Everett J, Murphy J et al. Comparison of blood or urine testing by 

patients with newly diagnosed non-insulin dependent diabetes: patient 

survey after randomized crossover trial. BMJ. 1997 Aug 9; 

315(7104):348-9. 26

X X Excluded in our study because it 

tested SMBG versus self-monitoring 

of urine glucose. 

Kibriya, MG, Ali L, Banik NG, et al. Home monitoring of blood glucose 

(HMBG) in Type-2 diabetes mellitus in a developing country. Diabetes 

Res Clin Pract. 1999 Dec; 46(3):253-7. 27

 X X 

Brown SA, Garcia AA, Kouzekanani K at al. Culturally competent diabetes 

self-management education for Mexican Americans: the Starr County 

boarder health initiative. Diabetes Care. 2002 Feb; 25(2):259-68. 28

X Excluded as the primary focus of the 

study was delivering culturally 

competent diabetes self management 

education. 

Schwedes U, Siebolds M, Mertes G. Meal-related structured self-monitoring 

of blood glucose: effect on diabetes control in non-insulin-treated type 2 

diabetic patients. Diabetes Care. 2002 Nov; 25(11):1928-32. 29

X X X X 

Guerci B, Drouin P, Grange V, et al. Self-monitoring of blood glucose 

significantly improves metabolic control in patients with type 2 diabetes 

mellitus: the Auto-Surveillance Intervention Active (ASIA) study. 

Diabetes Metab. 2003 Dec; 29(6):587-94. 30

X X X X 

Kwon HS, Cho JH, Him HS et al. Establishment of blood glucose monitoring 

system using the internet. Diabetes Care. 2004 Feb; 27(2):478-83. 31 X Excluded because control group also used SMBG. 

Davidson MB, Castellanos M, Kain D et al. The effect of self-monitoring of 

blood glucose concentrations on glycated hemoglobin levels in diabetic 

patients not taking insulin: a blinded, randomized trail. Am J Med. 2005 

Apr; 118(4):422-5. 32

X X X X 

Farmer A, Wade A, Goyder E, et al. Impact of self monitoring of blood 

glucose in the management of patients with non-insulin treated diabetes: 

open parallel group randomized trial. BMJ. 200733

 X 
HSR&D Evidence Synthesis Program – 9 

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Figure 1. Self-monitoring of Blood Glucose Literature Flow 

Articles identified from prior systematic reviews 

n= 17 

Total number of titles identified for title review 

n= 52 

Total number of titles considered possibly relevant and articles ordered 

n= 38 

10 excluded at abstract review 

Total number of articles reviewed 

n= 30 

Systematic reviews: n=5 

Observational studies: n=8 

Letter/editorial: n=1 

Update search, 10/06 

n= 23 

RCTs measuring the effect 

of SMBG compared to no 

SMBG with A1c as an 

outcome 

n= 10 

Excluded: 

Duplicate data: n=1 

SMBG in control & 

intervention group: n=3 

No A1c as outcome: n=2 

Reference mining 

n= 11 

Update search, 7/07 

n=2 

1 excluded at abstract review 

AHRQ Systematic Review - 

Draft Report 

Content Expert 

n= 1 
HSR&D Evidence Synthesis Program – 10 

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Wing RR et al. (1986) 19 This study assessed the usefulness of SMBG in improvement of dietary compliance 

for obese patients with type 2 diabetes. Authors from the University of Pittsburgh School of Medicine enrolled 

50 patients (mean weight 98 kg, 78% women) with adult-onset diabetes who were treated with oral 

hypoglycemic agents and insulin. All patients received weekly behavioral weight control counseling for the first 

three months, then monthly for six months, and twice more until week 62. Monetary stimulation was used. The 

intervention group was asked to monitor blood glucose on average 5.4 times a week to provide feedback of 

dietary modifications. Patients’ compliance with the diet and SMBG were monitored. Medication adjustments 

were made in similar mode in both groups according to study protocol. Five patients were excluded from the 

analyses with reasons explained by the authors. By week 12 there was a slight improvement of glycemic control 

in both groups (A1c values: SMBG group: 10.19% to 9.68%, control group: 10.86% to 10%). No statistically 

significant difference between groups was observed in glycosylated hemoglobin measurements by the one-year 

follow up. Both groups lost a significant amount of weight (6.1 kg). Patients with a high level of compliance to 

either SMBG or weight loss lost twice the amount of weight compared to poorly compliant patients. A large and 

not significantly different number of patients in both groups had their medications or insulin dose decreased 

during the study. 

Table 2. Components of each arm of the 10 RCTs. 

Study Arm SMBG Counseling/ 

Education 

Dietician Exercise Carbohydrate 

Counting 

Financial 

Incentive 

(weight) 

Financial 

Incentive 

(SMBG) 

Patient 

Control 

Wing RR et al., Control X X X 

198619 Intervention X X X X 

Fontebonne A et Control X 

al., 198920

Intervention X X 

Rutten G et al., Control X 

199023 Intervention X 

Muchmore DB et Control X X 

al., 199424 Intervention X X X X 

Jaber LA et al., Control 

199625 Intervention X X X 

Kibriya MG et al., Control X 

199927 Intervention X X 

Schwedes U et Control X 

al., 200229 Intervention X X 

Guerci B et al. Control X 

200330 Intervention X X 

Davidson MB et Control X X 

al., 200532 Intervention X X X 

Control 

Intervention1 X 

Farmer A et al. 

200733

Intervention2 X X 
HSR&D Evidence Synthesis Program – 11 

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Fontbonne A et al. (1989) 20 This is a French study of 208 non-insulin treated patients with 

long-term and poorly controlled diabetes (mean duration=13 years, mean A1c=8.3%). Patients 

were randomized into three groups (SMBG, urinary glucose monitoring and control), and seen 

by their respective physicians every two months with either A1c results or SMBG measurements. 

At each visit medication and/or dietary modification was allowed. Forty-four patients were lost 

to follow-up. A1c values at the end of six months were not significantly different between the 

three groups. However, the degree of compliance to SMBG appeared to relate to outcome; the 

more blood strips used, the larger the decrease in A1c values. 

Rutten G et al. (1990) 23 This study from the Netherlands looked at the feasibility and effect of a 

diabetes type 2 protocol with SMBG in general practice. One hundred forty-nine patients (66 in 

intervention and 83 in control groups) from eight practices were studied over 12 months. Ten 

patients were excluded from each group with reasons explained for all. Some patients in the 

treatment group tested their fasting glucose and reported it on a monthly basis. In case of 

elevated readings, they were referred to a study doctor, where the protocol was followed and 

medications were possibly changed. The protocol included weight reduction counseling and 

medication changes with up to two oral hypoglycemic agents used. Other patients from the 

treatment group did not check their blood glucose, but had it measured during quarter-annual 

visits with a doctor. At the end of the study, the treatment group decreased A1c values from 

9.7% to 9.2%, whereas the control group increased from 8.9% to 9.4%. 

Muchmore DB et al. (1994) 24 This study tested the hypothesis that combined use of SMBG and 

dietary carbohydrate counting is beneficial in managing type 2 diabetes. The Scripps Clinic 

enrolled 29 overweight patients (BMI=34, 61% women) with diet or treated with oral 

hypoglycemics diabetes. Six were excluded for reasons not described. Patients participated in a 

28-week behavioral weight loss program, with emphasis on glycemic response to carbohydrate 

intake and exercise. Medication adjustment was not included in the study protocol, but it was 

done for a similar amount of patients in both groups by their own physicians. Although A1c 

improved more in the intervention group than in the control group (a decrease of 1.54% vs. 

0.84% absolute), the difference was not statistically significant. Quality-of-life measures were 

similar in both groups. Weight loss was equivalent (~6 kg) in both groups by week 44. 

Jaber LA et al. (1996) 25 This study was performed in a university-affiliated internal medicine 

outpatient clinic. It enrolled 45 obese African-American patients with non-insulin dependent 

diabetes mellitus (NIDDM). All patients were treated with sulfonylurea agents. The mean age of 

the patients was 62, 70% were women, the mean BMI was 33, and mean duration of diabetes 

was six years. During four months of follow-up, the intervention group received diabetic 

education, medication counseling, instructions on dietary regulation, exercise, and SMBG, as 

well as evaluation and adjustment of their hypoglycemic regimen by the pharmacist. Patients 

were instructed to monitor blood glucose eight times a week. The control group was followed by 

their physicians. Six patients withdrew or dropped out from the study with reasons explained by 

the authors. The intervention group patients had on average 2.2 changes in drug therapy, with an 

increase in oral hypoglycemics dose on most visits. The final A1c value in the intervention group 

decreased from 11.5% to 9.2%, and in the control group it decreased from 12.2% to 12.1%. This 

difference between groups was statistically significant. Quality-of-life analyses revealed no 

significant differences in any of the domains tested between or within groups. No significant 

changes were noted within or between groups in blood pressure, body weight, serum lipid 

measurements and renal function parameters. 
HSR&D Evidence Synthesis Program – 12 

Home Glucose Monitoring 

Kibriya MG et al. (1999) 27 Physicians of the Bangladesh Institute of Research and 

Rehabilitation in Diabetes Endocrine and Metabolic disorders (BIRDEM) recruited 64 type 2 

diabetic patients of “higher-middle class to rich socio-economic class and having completed 

secondary school certificate level education” to participate in this randomized study and 

followed them for 18 months. Their aim was to evaluate the cost effectiveness of SMBG in the 

management of type 2 diabetes in developing countries. All patients received education on diet 

and how to adjust insulin or oral antidiabetic medications. Patients in the SMBG group were 

advised to check their blood glucose two to three times a day every two weeks and adjust their 

medications accordingly if fasting values were >6.0 mmol/L. They were also asked to visit the 

physician at three month intervals for blood glucose and A1c measurements. Patients in the 

control group visited the physician at one month intervals and had their antidiabetic regimen 

modified if needed, based on fasting blood glucose measurements at the monthly visits and A1c 

values at each three month visit. Cost analysis was performed using conveyance cost, patient 

wage loss, costs of test strips, glucometer, laboratory tests, and manpower. For the control group, 

results demonstrated a decrease of 0.43% in A1c after 18 months which was statistically 

significant. Statistical comparisons between groups were not reported. The SMBG group 

demonstrated a 1.37% drop in A1c after 18 months which was also significant. Cost analysis 

revealed comparable results for both groups ($134.55 for the control group vs. $134.75 for the 

SMBG group). Conclusions were that SMBG with proper diabetes education is a cost effective 

strategy in the management of type 2 diabetes. 

Schwedes U et al. (2002) 29 This study was a randomized multicenter trial that recruited 

subjects in Germany and Austria and followed them for six months. A total of 250 patients were 

randomized within blocks of eight to one of two groups: one group used SMBG, kept a blood 

glucose/eating diary, and received standardized counseling; the control group received only 

nonstandardized counseling on diet and lifestyle. Two hundred and twenty three patients were 

included in the final analysis. Patients in the SMBG group were instructed to measure blood 

glucose six times a day (pre-and postprandially) on two days per week, and to document eating 

habits and state of well-being. Patients were seen every four weeks. Results showed a 

statistically significant difference in A1c reduction between the two groups. The control group 

had a 0.54% reduction of A1c compared to a 1.0% reduction in the SMBG group. 

Guerci B et al. (2003) 30 The Auto-Surveillance Intervention Active (ASIA) study out of France 

followed 689 patients for six months. Patients were randomized to receive either a conventional 

laboratory work-up based solely on A1c measurements every 12 weeks (control group) or 

conventional laboratory work-up and SMBG at a frequency of at least six times a week 

(intervention group). Both groups received counseling on diet and exercise from their general 

practitioners during five visits throughout the course of the study. At the three month visit, 

practitioners could modify treatments of their patients based on their A1c value measured at that 

time. All but three of the patients were on at least one oral antidiabetic drug. Among those, the 

most widely prescribed drugs were sulfonylureas and biguanides. Results demonstrated a 0.28% 

absolute greater drop in A1c in the SMBG group as compared to the control group at the end of 

the study, which was statistically significant. This difference was most pronounced at three 

months, with a steady state reached in the last three months of the study. The authors concluded 

that SMBG was associated with better quality of metabolic control than usual recommendations 

alone in patients with type 2 diabetes. They noted that since no specific instruction for adjusting 

behavior to the results of SMBG was given to the patients. 
HSR&D Evidence Synthesis Program – 13 

Home Glucose Monitoring 

Davidson MB et al.(2005) 32 This randomized controlled trial followed 88 patients for six 

months. Patients in the treatment group were instructed to measure pre- and post-prandial blood 

glucose levels six days a week. Patients in both groups received dietitian counseling five times 

during the study. A nurse, who was blinded to whether the patient was in the treatment group or 

not, followed a detailed algorithm to make her therapeutic decisions. Her goals were to lower 

fasting glucose concentrations to <130mg/dL by stepwise increases in metformin or a 

sulfonylurea agent every two weeks, and to achieve an A1c value <7.5%. If the goal A1c was not 

achieved, a thiazolidinedione was added. Results demonstrated a significant drop in A1c levels 

of both groups, but no statistically significant difference between the two groups. 

Farmer A et al.(2007)33 This trial randomized 453 patients seen at 48 general practices in 

London into three groups (usual care, SMBG, SMBG plus training to use results for self care). 

Patients were included if they had type 2 diabetes, were at least 25 years old at diagnosis, were 

managed with diet or oral hypoglycemics, had an A1c level greater than or equal to 6.2% at the 

initial visit, and were able to independently perform daily living activities. Patients in the control 

group (n=152) received standardized usual care and were seen for A1c measurements once every 

three months for 12 months. Patients in the less intensive SMBG group (n=150) were instructed 

to monitor three times a day on two days of every week. In addition to being instructed about 

self-monitoring, patients in the more intensive SMBG group (n=151) were trained to use the 

results for self care. Patients in the more intensive group were not instructed to measure blood 

glucose a set number of times per week, but rather to “explore the effect of different activities... 

on their blood glucose level.” From diaries kept by the patients, those in the more intensive 

group tested their blood sugar on average six times per week early in the study, but by the end of 

the 12 months this had decreased to an average of five times per week. Patients in the less 

intensive group tested their blood sugar on average about five times per week throughout the 

trial. At three, six, nine, and 12 months no statistically significant differences in A1c levels were 

found between the three groups.
HSR&D Evidence Synthesis Program – 14 

Home Glucose Monitoring 

Key Question #1: Is regular self-monitoring of blood glucose effective in 

achieving target A1c levels for patients with type 2 diabetes?

Studies of Efficacy 

Achieving Target A1c Levels 

We identified a single trial that assessed the effect of SMBG (plus counseling and education) in 

149 patients in general practice in the Netherlands at meeting target A1c levels. 23 In this study 

the target A1c level was 8.0%. Prior to the intervention 45 and 41 patients in the in control and 

intervention arms, respectively, had an A1c values greater than 8%. After the intervention, one 

patient (2%) and two patients (5%) in the control and intervention arms had A1c values of less 

than 8% (p=0.6). 

Thus there is little evidence to draw a conclusion about the efficacy of SMBG at achieving target 

A1c levels. We judged the strength of this evidence as very low. [GRADE: Very Low = Any 

estimate of effect is very uncertain.] 

Improving Glycemic Control

While not directly answering this question but certainly relevant to it, is the effect of SMBG on 

the mean A1c level. All 10 trials reported this outcome. We grouped trials based on the duration 

of the intervention. The individual and pooled results are shown in Figure 2. 

We identified three trials that reported A1c outcomes at three months. 19,25,33 The three trials 

reported variable results. 19,25 We did not pool the results of these three trials because their results 

were too heterogeneous, with an I2

 statistic of 67%. 

We identified five trials that reported outcomes at about six months. 20,29,30,32,33 Only one trial 

reported a statistically significant improvement in A1c30, although a second trial also yielded a 

statistically significant result after adjusting for baseline difference29. The random effects pooled 

estimate of effect of these five trials was a change in mean A1c value of -0.21% (95% CI: -

0.38%, -0.04%). The I2 statistic for heterogeneity was 0. 

We identified five trials that reported outcomes at about one year or longer. 19,23,24,27,33 No study 

reported a statistically significant difference between groups in the mean A1c value, although 

two studies reported statistically significant benefits after adjusting for baseline differences in 

A1c values. 23,27 The random effects pooled estimate of the effect of these five trials was a 

change in A1c value of -0.15%(95% CI: -0.36%, 0.06%). The I2 statistic for heterogeneity was 0. 

We performed several additional analyses. First we compared studies scores, four or more 

Delphi items positively (which we called “High quality”) with those scoring less than four items 

positively (“Low quality”). The pooled results showed no statistically significant differences 

between high and low quality studies. 
HSR&D Evidence Synthesis Program – 15 

Home Glucose Monitoring 

Figure 2. Analysis of Mean Difference between Control and SMBG Group at Followup 

We repeated our primary analysis using as the outcome the difference in A1c levels between 

groups adjusted for baseline A1c levels (whether or not to do such adjusting in the results of an 

RCT is controversial). When analyzed this way there was much greater heterogeneity between 

studies, with I2 statistics of 49% and 75% for studies with six month and 12 month outcomes 

respectively. However, despite this our primary pooled results were remarkably similar: a 

modest and statistically significant effect on A1c at six months of 0.19 (compared to a pooled 

result of 0.21 in the main analysis); and a nonsignificant effect at 12 months. In the difference of 

difference analysis, high quality studies reported lower estimates of effect than low quality 

studies, an observation seen in other conditions.34 This re-analysis supported our primary 

analysis (Figure 3). 

Meta-regression on baseline values of A1c level showed differential effectiveness (p value for 

difference = 0.05), with higher baseline values of A1c being associated with lesser efficacy of 

SMBG. Each 1% increase in A1c was associated with a 0.3% decrease in efficacy of SMBG. 

Thus, indirect evidence suggests that SMBG results in a smaller percent change in A1c for 

patients with higher baseline values of A1c. 

We attempted to identify other components of the intervention or characteristics of the patients 

associated with greater effectiveness. The trials did not have sufficient similarity in intervention 

components to permit a meta-regression analysis (See Figure 2). Almost all studies included 

SMBG and counseling/education, making an assessment of the effect of one without the other 

impossible, and other intervention components were too sparsely distributed to support metaEffect size

 Favors Treatment Favors Control

 -6 -5 -4 -3 -2 -1 0 1 2

Study Effect size (95% CI)

 One year or longer Kibriya MG et al., 1999 27 -0.01 (-0.75, 0.73)

 Muchmore DB et al., 1994 24 -0.85 (-2.40, 0.70)

 Rutten G et al., 1990 23 -0.20 (-0.67, 0.27)

 Wing RR et al., 1986 19 62 weeks -0.25 (-1.58, 1.08)

 Farmer et al., 200733 More intensive self monitoring -0.13 (-0.38, 0.12)

 Farmer et al., 200733 Less intensive self monitoring -0.21 (-0.45, 0.03)

 Subtotal -0.15 (-0.36, 0.06)*

 Six months

 Davidson MB, et al., 2005 32 -0.10 (-0.75, 0.55)

 Guerci B et al., 200333 0 -0.30 (-0.60,0.00)

 Schwedes U et al., 

200229 -0.34 (-0.71, 0.03)

 Fontbonne A et al., 199020 -0.14 (-0.70, 0.42)

 Farmer et al., 200733 More intensive self monitoring -0.05 (-0.38, 0.28)

 Farmer et al., 200733 Less intensive self monitoring -0.08 (-0.41, 0.25)

 Subtotal -0.21 (-0.38,-0.04)*

 Three months

 Jaber LA et al., 1996 25 -2.90 (-4.74,-1.06)

 Wing RR et al., 19861912 weeks -0.32 (-1.53, 0.89)

 Farmer et al., 200733 More intensive self monitoring -0.05 (-0.41, 0.31)

 Farmer et al., 200733 Less intensive self monitoring -0.14 (-0.51, 0.23)

 High Quality Articles -0.23 (-0.89, 0.43) Low Quality Articles -0.23 (-0.53, 0.08)

 *Subtotal does not include “Farmer et al., 2007 [#1039] Less intensively self monitoring” arm. 
HSR&D Evidence Synthesis Program – 16 

Home Glucose Monitoring 

regression. Meta-regression using the quality assessment (as either a continuous variable or 

dichotomous at a threshold value of four) also did not demonstrative differences between results. 

An analysis of the frequency of SMBG testing is discussed in Key Question #4. 

The funnel plot for publication bias is shown in Figure 4. Neither Begg’s test nor Eggar’s test 

yielded evidence of unexplained heterogeneity. 

Therefore, we found that adding SMBG along with education, counseling, (and some times other 

components) results in a statistically significant decrease in A1c level of an absolute 0.21% at six 

months. Results at three months and one year are more variable, although there is a suggestion 

that this benefit may continue out to at least one year (absolute reducation = -0.15%, 95% CI: 

-0.36, 0.06). Indirect evidence suggests SMBG maybe less efficacious in subjects with higher 

baseline A1c values. 

We judged the strength of evidence for this outcome as moderate, because individual trials did 

not in general report significant results and interventions were heterogeneous. [GRADE: 

Moderate= Further research is likely to have an important impact on our confidence in the 

estimate of effect and may change the estimate.] 

Figure 3. Analysis of Difference of Differences between Control and SMBG Group at 

Follow-up 

 Effect size

Favors Treatment Favors Control

 -6 -5 -4 -3 -2 -1 0 1 2

 Study Effect size (95% CI)

 One year or longer Kibriya MG, et al., 1999 27 -0.99 (-1.78,-0.20)

 Muchmore DB et al., 1994 

24 -0.69 (-2.01, 0.63)

 Rutten G et al., 1990 23 -1.00 (-1.57,-0.44)

 Wing RR et al., 1986 19 62 weeks 0.42 (-0.54, 1.38)

 Farmer et al., 2007 33 More intensive self monitoring 0.17 (-0.19, 0.55)

 Farmer et al., 2007 33 Less intensive self monitoring 0.14 (-0.22, 0.50)

 Subtotal -0.28 (-0.78, 0.22)*

 Six months

 Davidson MB, et al., 2005 32 -0.20 (-0.98, 0.58)

 Guerci B, et al., 2003 30 -0.40 (-0.63,-0.17)

 Schwedes U, et al., 2002 29 -0.46 (-0.79,-0.13)

 Fontbonne A et al., 1990 20 0.14 (-0.56, 0.84)

 Farmer et al., 2007 33 More intensive self monitoring 0.09 (-0.26, 0.44)

 Farmer et al., 2007 33 Less intensive self monitoring 0.00 (-0.35, 0.35)

 Subtotal -0.19 (-0.41, 0.04)*

 Three months

 Jaber LA et al., 1996 25 -2.20 (-3.96,-0.44)

 Wing RR et al., 1986 19 12 weeks 0.35 (-1.34, 2.04)

 Farmer et al., 2007 33 More intensive self monitoring 0.09 (-0.55, 0.73)

 Farmer et al., 2007 33 Less intensive self monitoring 0.06 (-0.58, 0.70)

 High Quality Articles -0.09 (-1.01, 0.83) Low Quality Articles -0.56 (-0.99,-0.12)

 *Subtotal does not include “Farmer et al., 2007 [#1039] Less intensively self monitoring” arm. 
HSR&D Evidence Synthesis Program – 17 

Home Glucose Monitoring 

Figure 4. Publication Bias for the 10 RCTs 

Begg's funnel plot with pseudo 95% confidence limits

WMD

s.e. of: WMD

0 .5 1

-4

-2

0

2

Studies of Effectiveness in Veterans 

We identified six publications assessing the value of SMBG specifically in Veterans. One 

publication was an RCT comparing SMBG with urine glucose monitoring, 22and did not include a 

comparison with Veterans who did no monitoring. The other five studies were observational in 

design, mostly retrospective chart reviews that sought to compare a variety of outcomes between 

Veteran patients receiving supplies for SMBG with those not receiving such supplies. 35-39 Details of 

all studies are in Table 3. 

All studies reported that there was no difference in A1c levels between groups. Although most 

studies attempted to try and control for baseline differences between patients, the observational study 

design cannot inform what the A1c values of Veteran patients currently using SMBG would be if 

they did not receive SMBG supplies. It is possible, for example, that Veterans are selected by their 

clinicians for receipt of SMBG because they are more difficult to control. 

Therefore, the results of the effectiveness studies do not negate the efficacy evidence from RCTs that 

the addition of SMBG and education can result in a decrease in A1c levels of about 0.3% absolute at 

six months and up to one year. However, these studies do raise the question of whether Veteran 

patients are receiving the full possible benefits of SMBG. For example, the RCTs reporting benefit 

also all included counseling and education. If this is necessary for SMBG to have an effect, one 

explanation of the difference in the results between the RCTs and the observational studies in 

veterans is that there is inadequate counseling and education of the Veterans. 
HSR&D Evidence Synthesis Program – 18 

Home Glucose Monitoring 

We judge the strength of evidence for this outcome as very low because these are observational 

studies with serious limitations in study quality. [GRADE: Very Low = Any estimate of effect is 

very uncertain.] 

Table 3. Studies of Self-monitoring of Blood Glucose in Veterans 

Author/year Study Design Patients SMBG Duration of 

Follow-up 

Results 

Malik RL et al. 

(1989) 36

Prospective 

cohort 

16 male Veterans Mean 

age=62 years 

Mean duration of 

DM=8.9years 

Mean A1c=11.0 

“Daily test and 

adjustment diary” to 

record SMBG test results 

and diet changes 

(average=10 tests/week); 

3 4-hour diabetes 

educational seminars 

12 weeks Improvement in A1c 

from 11.0 ± 2.9% to 

9.9 ± 2.4%, Results 

reported as not 

statistically 

significant. 

Newman WP, et 

al. (1990) 35

Retrospectiv

e cohort 

21 Veterans who selfmonitored glucose, 17 

Veterans who did not 

Mean duration of 

DM=17 & 11 years 

respectively 

All patients performing 

self-monitoring were 

cared for and taught by 

the same physician 

3 years No difference in 

groups in A1c values 

over time. 

Allen BT, et al. 

(1990) 22

RCT 61 Veterans with DM 

without prior SMBG 

Mean age=58 years 

Mean A1c=12.0 

SMBG versus urine 

glucose monitoring 

6 months No difference in 

groups in A1c values 

at the end of the 

study (each had 2.0 

decrease compared 

to baseline). 

Klein CE, et al. 

(1993) 37

Retrospectiv

e cohort 

chart review 

229 Veterans, 97%men 

Mean age=62 years 

Mean duration of 

DM=10 years 

181 patients performed 

SMBG 

12 months No difference in 

mean A1c level 

between patients 

using SMBG versus 

those using urine 

glucose monitoring. 

Rindone JP, et 

al. (1997) 38

Retrospectiv

e cohort 

chart review 

115 Veterans 

Mean age=68 years 

58 Veterans received 

Chemstrips 

2 years No difference in 

mean A1c levels 

over 2 years between 

Veterans receiving 

Chemstrips and those 

not receiving 

Chemstrips. 

Wen L, et al. 

(2004) 39

Retrospectiv

e cohort 

chart & 

administrativ

e data 

review 

976 Veterans with DM 

on oral hypoglycemics, 

97% men 

Mean age varied by 

group between 59 & 66 

years 

A1c levels varied 

between 6.6 and 7.25 

161 Veterans received no 

Chemstrips, 75 Veterans 

received Chemstrips in 1 

year only, 138 Veterans 

received Chemstrips in 2 

years only, and 602 

Veterans received 

Chemstrips in all 3 years 

3 years No association 

between use of 

Chemstrips and 

mean A1c levels. 

DM=Diabetes Mellitus
HSR&D Evidence Synthesis Program – 19 

Home Glucose Monitoring 

Key Question #2: Is regular self-monitoring of blood glucose effective in 

maintaining target A1c levels for patients with type 2 diabetes? 

We did not identify any trials that directly assessed this question. Therefore, we draw no 

conclusion. [GRADE: Very Low = Any estimate of effect is very uncertain.] 

Key Question 3: Does regular self-monitoring of blood glucose reduce the 

frequency of hypoglycemia in patients with type 2 diabetes?

We identified four trials that reported hypoglycemia as an outcome. More details of these trials 

were presented previously. A brief synopsis of each study follows, with respect to the 

hypoglycemia outcomes. 

Jaber LA et al. (1996) 25 There were 17 reported hypoglycemic reactions in the intervention 

group and two in the control group. All were rated as mild to moderate, and successfully selftreated. The authors report: "High rate of reported hypoglycemia is partly inherent to the study 

design and execution. Intervention group patients were repeatedly instructed to and trained on 

recognition and documentation of hypoglycemia. They were also questioned about the 

occurrence of these reactions at every clinic visit. Subjects in the control group were not given 

any specific instructions regarding hypoglycemia and data on its occurrence were collected at the 

end of the study where capture of this information may have been hindered by the duration of the 

elapsed time". 

Kibriya MG et al. (1999) 27 In this trial the patients in the SMBG group were instructed to 

perform testing every two weeks, and adjust the dose of anti-diabetic medication accordingly. 

Control group patients were seen by their doctors on a monthly basis, and had their anti-diabetic 

treatment modified if needed. During 18 months of follow-up, ten patients in the SMBG 

intervention group had a total of 17 episodes of hypoglycemia, and five patients from the control 

group had seven similar episodes. Two patients from the SMBG group needed hospitalization for 

hyperglycemia compared to none in the control group. 

Guerci B et al. (2003) 30 During this trial 78 patients reported at least one episode of 

hypoglycemia, either symptomatic or asymptomatic: 53(10%) patients in the SMBG group and 

25(5%) patients in the control group. These proportions were significantly different due to 

asymptomatic hypoglycemia alone (P=0.001). There was no serious episode of hypoglycemia 

reported. 

Farmer A et al. (2007)33 This trial classified hypoglycemia as grade 2 (mild symptoms 

requiring minor intervention), grade 3 (moderate symptoms requiring immediate third party 

intervention), and grade 4 (unconscious). Fourteen patients in the control group had at least one 

grade 2 hypoglycemia episode, compared to 33 patients in the less intensive intervention group 

and 43 patients in the more intensive intervention group and 43 patients in the more intensive 
HSR&D Evidence Synthesis Program – 20 

Home Glucose Monitoring 

intervention group (p<0.001). One patient in the control group had a grade 3 hypoglycemic 

episode. 

Thus, the limited evidence available indicates that SMBG increases the frequency of recognized 

hypoglycemia. This is due to an increase in asymptomatic low blood sugar readings, and also an 

increase in mild-to-moderate symptomatic episodes. There is scant evidence about the effect of 

SMBG on more clinically significant hypoglycemia. We judge the strength of evidence for 

SMBG increasing asymptomatic and mildly symptomatic hypoglycemia as moderate. [Moderate 

= Further research is likely to have an important impact on our confidence in the estimate of 

effect and may change the estimate.] 

Key Question 4: Is there evidence that different frequencies of testing 

result in differences in improvements in A1c? 

We did not identify any study that explicitly tested the effect of different frequency of SMBG on 

outcomes. This could have been accomplished either as an RCT (randomizing patients to 

differing frequencies and comparing outcomes) or as an analysis of outcomes within a cohort of 

patients using SMBG. We therefore were compelled to use an indirect method to examine this 

question. The indirect method compares the outcomes of studies that vary in the frequency of 

reported use of SMBG. Indirect methods have only a limited ability to control for other study 

level differences. 

We used meta-regression to assess the effect of the reported frequency of SMBG use in the 

RCTs (measured as times/week) on differences in A1c level compared to control. No association 

was found (p=0.99). Therefore we draw no conclusion about the effect of frequency of SMBG 

monitoring on A1c values, and judge the strength of the evidence to be very low. [GRADE: Very 

Low = Any estimate of effect is very uncertain.] 
SUMMARY AND DISCUSSION 

In this chapter, we describe the limitations of our review and meta-analysis and then present our 

conclusions. We also discuss the implications of our findings for future research. 

Limitations 

Publication Bias 

Our literature search procedures were extensive and included all articles identified in prior 

reviews plus additional articles. Our formal tests for publication bias did not indicate the 

presence of possible publication bias but such tests do not exclude the possibility that such bias 

exists. Therefore, readers are cautioned about this possibility. 

Study Quality 

An important limitation common to systematic reviews is the quality of the original studies. 

Recent attempts to define elements of study design and execution that are related to bias have 

shown that in many cases, such efforts are not reproducible and do not distinguish study results 

based on bias. Therefore, the current approach is to avoid rejecting studies or using quality 

criteria to adjust the meta-analysis results. We did use the Delphi list10 as a descriptive measure 

of quality. As there is a lack of empirical evidence regarding study characteristics and their 

relationship to bias, we did not attempt to use other criteria. Other aspects of the design and 

execution of a trial may be related to bias, but we do not yet have good measures of these 

elements. The sensitivity analysis of our main result did not yield any suggestion that the quality 

of the trials influenced our findings in a significant way. 

Heterogeneity 

While there were some differences in the population being assessed and the number of times and 

timing of SMBG recommended, the most important heterogeneity in this review was the 

differing intervention components added to SMBG and the difference in the recommendations 

for frequency of SMBG testing, provider interaction or algorithm to adjust medications, and 

intensity of education. While the statistical test for heterogeneity was not significant for six 

months and 12 month outcomes, this test has low power and does not preclude substantial 

heterogeneity among studies. There were too few studies to be able to support meta-regression to 

assess the relative effectiveness of these differences. 

Applicability of Findings 

Green & Glasgow40 provide a framework for evaluating the relevance, generalization, and 

applicability of research. Their framework includes assessing the participation rate, the intended 

target population, the representativeness of the setting, the representativeness of the individuals, 

and evaluating information about implementation and assessment of outcomes. As these data are 

rarely reported in the studies we reviewed, conclusions about applicability are necessarily weak. 

Furthermore, none of the trials assessed VA patients or VA core delivery systems. The 

observational studies done in VA did not report results compatible with SMBG being an 

effective intervention; however RCTs are generally preferred to observational studies when 

making estimates of efficacy and effectiveness. 
Conclusions 

With the above limitations in mind, we reached the conclusions displayed below. 

KEY QUESTION #1: Is regular SMBG effective in achieving target A1c levels for 

patients with type 2 diabetes?

Studies of Efficacy 

Achieving Target A1c Levels 

There is little evidence to draw a conclusion about the effect of SMBG at achieving target A1c 

levels. We judged the strength of this evidence as very low. [GRADE: Very Low = Any 

estimate of effect is very uncertain.] 

Improving Glycemic Control 

We found that adding SMBG along with education, counseling, (and some times other 

components) results in a statistically significant decrease in A1c level of an absolute 0.21% at six 

months. Results at three months and one year are more variable, although there is a suggestion 

that this benefit may continue out to at least one year. 

We judged the strength of evidence for this outcome as moderate, because individual trials did 

not in general report significant results and interventions were heterogeneous. [GRADE: 

Moderate= Further research is likely to have an important impact on our confidence in the 

estimate of effect and may change the estimate.] 

Studies of Effectiveness in Veterans 

Five observational studies of SMBG effectiveness in Veteran populations did not report 

statistically significant improvements in glycemic control. The results of the studies with 

Veterans do not negate the evidence from RCTs that the addition of SMBG and education can 

result in a decrease in A1c levels of about 0.3% absolute at six months and up to one year. 

However, these studies do raise the question of whether veteran patients are receiving the full 

possible benefits of SMBG. [GRADE: Very Low = Any estimate of effect is very uncertain.] 

KEY QUESTION #2: Is regular SMBG effective in maintaining target A1c levels 

for patients with type 2 diabetes? 

We did not identify any trials that directly assessed this question. Therefore, we draw no 

conclusion. [GRADE: Very Low = Any estimate of effect is very uncertain.] 

KEY QUESTION #3: Does regular SMBG reduce the frequency of hypoglycemia 

in patients with type 2 diabetes? 

The limited evidence available indicates that SMBG increases the frequency of recognized 

hypoglycemia. This is due to an increase in asymptomatic low blood sugar readings, and also an 

increase in mild-to-moderate symptomatic episodes. There is scant evidence about the effect of 

SMBG on more clinically significant hypoglycemia. We judge the strength of evidence for 
SMBG increasing asymptomatic and mildly symptomatic hypoglycemia as moderate. [Moderate 

= Further research is likely to have an important impact on our confidence in the estimate of 

effect and may change the estimate.] 

KEY QUESTION #4: Is there evidence that different frequencies of testing result 

in differences in improvements in A1c? 

We used meta-regression to assess the effect of the reported frequency of SMBG use in the 

RCTs (measures as times/week) on differences in A1c level compared to control. No association 

was found (p=0.99). Therefore we draw no conclusion about the effect of frequency of SMBG 

monitoring on A1c values, and judge the strength of the evidence to be very low. [GRADE: Very 

Low = Any estimate of effect is very uncertain.] 
FUTURE RESEARCH 

Our review of existing data support the short term beneficial effect of SMBG on A1c levels in 

the context of a clinical trial. Although improvement in A1c is modest, it is approximately 

equivalent to that achieved with diabetes education interventions. 41Whether the benefit extends 

beyond six months is questionable. 

However, observational studies in the VA do not report differences in A1c levels between 

Veterans using or not using SMBG supplies. This raises the question about implementation: 

more research is needed to understand if implementation of SMBG in a typical VA clinic setting 

is sufficient for Veterans to receive the full benefit reported in clinical trials. 

In particular, it would be worthwhile to conduct studies in VA of “enhanced” SMBG versus 

usual care SMBG, with “enhanced” computer-based or nurse case-management or being Health 

Buddy or My Healthe Vet facilitated implementation of SMBG. This would more closely 

approximate the study question of interest today. New studies would also be able to account for 

improvements in SMBG technology (meters, strips, etc.) over time. 

Additionally, data are needed about the cost-effectiveness of SMBG in a VA setting. 

The evidence is insufficient to draw conclusions about which components of SMBG (additionaleducation, algorithms or other techniques to adjust medication) and frequency of testing are most 

associated with better results. More research is needed, and again we note that it should consider 

incorporation of methods for enhancing SMBG effectiveness. Additionally the impact of SMBG 

on medication adherence should be evaluated. 
REFERENCE LIST 

1. WHO media centre. Diabetes. 2006. 2001. 

2. National Diabetes Information Clearinghouse. National Diabetes Statistics. 2005. 2007. 

3. Stratton IM, Adler AI, Neil HA, Matthews DR, Manley SE, Cull CA, et al. Association of 

glycaemia with macrovascular and microvascular complications of type 2 diabetes 

(UKPDS 35): prospective observational study. BMJ 2000; 321:405-12. 

4. Faas A, Schellevis FG, Van Eijk JT. The efficacy of self-monitoring of blood glucose in 

NIDDM subjects. A criteria-based literature review. Diabetes Care 1997; 20:1482-6. 

5. Coster S, Gulliford MC, Seed PT, Powrie JK, Swaminathan R. Self-monitoring in Type 2 

diabetes mellitus: a meta-analysis. Diabet Med 2000; 17:755-61. 

6. Welschen LM, Bloemendal E, Nijpels G, Dekker JM, Heine RJ, Stalman WA, et al. Selfmonitoring of blood glucose in patients with type 2 diabetes who are not using insulin: 

a systematic review. Diabetes Care 2005; 28:1510-7. 

7. Balk E, Teplinsky E, Trikalinos T, Chew P, Chung M, Pittas A. 20 Date of Publication>; 

Maryland: Agency for Healthcare Research and Quality. 

8. Jansen JP. Self-monitoring of glucose in type 2 diabetes mellitus: a Bayesian metaanalysis of direct and indirect comparisons. Curr Med Res Opin 2006; 22:671-81. 

9. Furukawa TA, Barbui C, Cipriani A, Brambilla P, Watanabe N. Imputing missing standard 

deviations in meta-analyses can provide accurate results. J Clin Epidemiol 2006; 59:7- 

10. Verhagen AP, de Vet HC, de Bie RA, Kessels AG, Boers M, Bouter LM, et al. The 

Delphi list: a criteria list for quality assessment of randomized clinical trials for 

conducting systematic reviews developed by Delphi consensus. J Clin Epidemiol 1998; 

51:1235-41. 

11. Suttorp M, Shekelle P, van Tulder M, Morton S, Bouter L. Cochran Back Group Quality 

Item and Bias in Back Pain Trials. Abstract. 

12. Ray JW, Shadish WR. How interchangeable are different estimators of effect size? J 

Consult Clin Psychol 1996; 64:1316-25. 

13. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials 1986; 7:177-

88. 

14. Berkey CS, Hoaglin DC, Mosteller F, Colditz GA. A random-effects regression model for 

meta-analysis. Stat Med 1995; 14:395-411. 

15. Hedges LV, Olkin I. Statistical Methods for Meta-Analysis. San Diego, CA: Academic 

Press Inc, 1985. 

16. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in metaanalyses. BMJ 2003; 327:557-60. 

17. Stata Statistical Software Manual [computer program]. 2006; ed. 
18. Atkins D, Best D, Briss PA, Eccles M, Falck-Ytter Y, Flottorp S, et al. Grading quality of 

evidence and strength of recommendations. BMJ 2004; 328:1490 

19. Wing RR, Epstein LH, Nowalk MP, Scott N, Koeske R, Hagg S. Does self-monitoring of 

blood glucose levels improve dietary compliance for obese patients with type II 

diabetes? Am J Med 1986; 81:830-6. 

20. Fontbonne A, Billault B, Acosta M, Percheron C, Varenne P, Besse A, et al. Is glucose 

self-monitoring beneficial in non-insulin-treated diabetic patients? Results of a 

randomized comparative trial. Diabete Metab 1989; 15:255-60. 

21. Estey AL, Tan MH, Mann K. Follow-up intervention: its effect on compliance behavior to 

a diabetes regimen. Diabetes Educ 1990; 16:291-5. 

22. Allen BT, DeLong ER, Feussner JR. Impact of glucose self-monitoring on non-insulintreated patients with type II diabetes mellitus. Randomized controlled trial comparing 

blood and urine testing. Diabetes Care 1990; 13:1044-50. 

23. Rutten G, van Eijk J, de Nobel E, Beek M, van der Velden H. Feasibility and effects of a 

diabetes type II protocol with blood glucose self-monitoring in general practice. Fam 

Pract 1990; 7:273-8. 

24. Muchmore DB, Springer J, Miller M. Self-monitoring of blood glucose in overweight type 

2 diabetic patients. Acta Diabetol 1994; 31:215-9. 

25. Jaber LA, Halapy H, Fernet M, Tummalapalli S, Diwakaran H. Evaluation of a 

pharmaceutical care model on diabetes management. Ann Pharmacother 1996; 

30:238-43. 

26. Miles P, Everett J, Murphy J, Kerr D. Comparison of blood or urine testing by patients 

with newly diagnosed non-insulin dependent diabetes: patient survey after randomised 

crossover trial. BMJ 1997; 315:348-9. 

27. Kibriya MG, Ali L, Banik NG, Khan AK. Home monitoring of blood glucose (HMBG) in 

Type-2 diabetes mellitus in a developing country. Diabetes Res Clin Pract 1999; 

46:253-7. 

28. Brown SA, Garcia AA, Kouzekanani K, Hanis CL. Culturally competent diabetes selfmanagement education for Mexican Americans: the Starr County border health 

initiative. Diabetes Care 2002; 25:259-68. 

29. Schwedes U, Siebolds M, Mertes G. Meal-related structured self-monitoring of blood 

glucose: effect on diabetes control in non-insulin-treated type 2 diabetic patients. 

Diabetes Care 2002; 25:1928-32. 

30. Guerci B, Drouin P, Grange V, Bougneres P, Fontaine P, Kerlan V, et al. Self-monitoring 

of blood glucose significantly improves metabolic control in patients with type 2 

diabetes mellitus: the Auto-Surveillance Intervention Active (ASIA) study. Diabetes 

Metab 2003; 29:587-94. 

31. Kwon HS, Cho JH, Kim HS, Song BR, Ko SH, Lee JM, et al. Establishment of blood 

glucose monitoring system using the internet. Diabetes Care 2004; 27:478-83. 
32. Davidson MB, Castellanos M, Kain D, Duran P. The effect of self monitoring of blood 

glucose concentrations on glycated hemoglobin levels in diabetic patients not taking 

insulin: a blinded, randomized trial. Am J Med 2005; 118:422-5. 

33. Farmer A, Wade A, Goyder E, Yudkin P, French D, Craven A, et al. Impact of self 

monitoring of blood glucose in the management of patients with non-insulin treated 

diabetes: open parallel group randomised trial. BMJ 2007; 

34. Moher D, Pham B, Jones A, Cook DJ, Jadad AR, Moher M, et al. Does quality of reports 

of randomised trials affect estimates of intervention efficacy reported in meta-analyses? 

Lancet 1998; 352:609-13. 

35. Newman WP, Laqua D, Engelbrecht D. Impact of glucose self-monitoring on 

glycohemoglobin values in a veteran population. Arch Intern Med 1990; 150:107-10. 

36. Malik RL, Horwitz DL, McNabb WL, Takaki ET, Hawkins HA, Keys AG, et al. 

Adjustment of caloric intake based on self-monitoring in noninsulin-dependent diabetes 

mellitus: development and feasibility. J Am Diet Assoc 1989; 89:960-1. 

37. Klein CE, Oboler SK, Prochazka A, Oboler S, Frank M, Glugla M, et al. Home blood 

glucose monitoring: effectiveness in a general population of patients who have noninsulin-dependent diabetes mellitus. J Gen Intern Med 1993; 8:597-601. 

38. Rindone JP, Austin M, Luchesi J. Effect of home blood glucose monitoring on the 

management of patients with non-insulin dependent diabetes mellitus in the primary 

care setting. Am J Manag Care 1997; 3:1335-8. 

39. Williams GC, McGregor H, Zeldman A, Freedman ZR, Deci EL, Elder D. Promoting 

glycemic control through diabetes self-management: evaluating a patient activation 

intervention. Patient Educ Couns 2005; 56:28-34. 

40. Green LW, Glasgow RE. Evaluating the relevance, generalization, and applicability of 

research: issues in external validation and translation methodology. Eval Health Prof 

2006; 29:126-53. 

41. Norris SL, Lau J, Smith SJ, Schmid CH, Engelgau MM. Self-management education for 

adults with type 2 diabetes: a meta-analysis of the effect on glycemic control. Diabetes 

Care 2002; 25:1159-71.