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The American Journal of Managed Care February 2015
A Multidisciplinary Intervention for Reducing Readmissions Among Older Adults in a Patient-Centered Medical Home
Paul M. Stranges, PharmD; Vincent D. Marshall, MS; Paul C. Walker, PharmD; Karen E. Hall, MD, PhD; Diane K. Griffith, LMSW, ACSW; and Tami Remington, PharmD
Quality’s Quarter-Century
Margaret E. O'Kane, MHA, President, National Committee for Quality Assurance
How Pooling Fragmented Healthcare Encounter Data Affects Hospital Profiling
Amresh D. Hanchate, PhD; Arlene S. Ash, PhD; Ann Borzecki, MD, MPH; Hassen Abdulkerim, MS; Kelly L. Stolzmann, MS; Amy K. Rosen, PhD; Aaron S. Fink, MD; Mary Jo V. Pugh, PhD; Priti Shokeen, MS; and Michael Shwartz, PhD
Did Medicare Part D Reduce Disparities?
Julie Zissimopoulos, PhD; Geoffrey F. Joyce, PhD; Lauren M. Scarpati, MA; and Dana P. Goldman, PhD
Health Literacy and Cardiovascular Disease Risk Factors Among the Elderly: A Study From a Patient-Centered Medical Home
Anil Aranha, PhD; Pragnesh Patel, MD; Sidakpal Panaich, MD; and Lavoisier Cardozo, MD
Employers Should Disband Employee Weight Control Programs
Alfred Lewis, JD; Vikram Khanna, MHS; and Shana Montrose, MPH
Race/Ethnicity, Personal Health Record Access, and Quality of Care
Terhilda Garrido, MPH; Michael Kanter, MD; Di Meng, PhD; Marianne Turley, PhD; Jian Wang, MS; Valerie Sue, PhD; Luther Scott, MS
Leveraging Remote Behavioral Health Interventions to Improve Medical Outcomes and Reduce Costs
Reena L. Pande, MD, MSc; Michael Morris; Aimee Peters, LCSW; Claire M. Spettell, PhD; Richard Feifer, MD, MPH; William Gillis, PsyD
Decision Aids for Benign Prostatic Hyperplasia and Prostate Cancer
David Arterburn, MD, MPH; Robert Wellman, MS; Emily O. Westbrook, MHA; Tyler R. Ross, MA; David McCulloch, MD; Matt Handley, MD; Marc Lowe, MD; Chris Cable, MD; Steven B. Zeliadt, PhD; and Richard M. Hoffman, MD, MPH
Faster by a Power of 10: A PLAN for Accelerating National Adoption of Evidence-Based Practices
Natalie D. Erb, MPH; Maulik S. Joshi, DrPH; and Jonathan B. Perlin, MD, PhD, MSHA, FACP, FACMI
Differences in Emergency Colorectal Surgery in Medicaid and Uninsured Patients by Hospital Safety Net Status
Cathy J. Bradley, PhD; Bassam Dahman, PhD; and Lindsay M. Sabik, PhD
The Role of Behavioral Health Services in Accountable Care Organizations
Roger G. Kathol, MD; Kavita Patel, MD, MS; Lee Sacks, MD; Susan Sargent, MBA; and Stephen P. Melek, FSA, MAAA
Currently Reading
Patients Who Self-Monitor Blood Glucose and Their Unused Testing Results
Richard W. Grant, MD, MPH; Elbert S. Huang, MD, MPH; Deborah J. Wexler, MD, MSc; Neda Laiteerapong, MD, MS; E. Margaret Warton, MPH; Howard H. Moffet, MPH; and Andrew J. Karter, PhD
A Systematic Review of Measurement Properties of Instruments Assessing Presenteeism
Maria B. Ospina, PhD; Liz Dennett, MLIS; Arianna Waye, PhD; Philip Jacobs, DPhil; and Angus H. Thompson, PhD
Emergency Department Use: A Reflection of Poor Primary Care Access?
Daniel Weisz, MD, MPA; Michael K. Gusmano, PhD; Grace Wong, MBA, MPH; and John Trombley II, MPP

Patients Who Self-Monitor Blood Glucose and Their Unused Testing Results

Richard W. Grant, MD, MPH; Elbert S. Huang, MD, MPH; Deborah J. Wexler, MD, MSc; Neda Laiteerapong, MD, MS; E. Margaret Warton, MPH; Howard H. Moffet, MPH; and Andrew J. Karter, PhD
This article identifies patient-, provider-, and system-level factors associated with the problem of self-monitoring blood glucose without use of the results.
To investigate the prevalence, predictors, and costs associated with unused results from self-monitoring of blood glucose (SMBG).

Study Design
Observational cohort study.

We studied 7320 patients with type 2 diabetes mellitus who were not prescribed insulin and who reported SMBG. Patients reported whether they used SMBG results to make adjustments to diet, exercise, or medicines; and whether their physician/provider reviewed their SMBG results. We categorized SMBG results as “used” (by patient and/or provider) or “unused” (not used by either patient or provider).

SMBG results were unused by patient and provider in 15.2% of patients. In separate models adjusted for demographic and clinical differences, major predictors of SMBG without patient or physician using the results included a patient reporting that diabetes was not a high priority (relative risk [RR], 1.81; 95% CI, 1.58-2.07); the physician not engaging in shared decision making (RR, 1.66; 95% CI, 1.46-1.90); and no healthcare professional teaching the patient how to adjust diet/medicines based on SMBG results in the past year (RR, 2.27; 95% CI, 2.00-2.57). Patients with unused results were dispensed 171 ± 191 test strips per year at an estimated annual cost of $168.

Nearly 1 in 6 non–insulin-treated patients practiced SMBG without either the patient or physician using the results. This represents a wasteful and ineffective practice for patients and health systems alike. Our results suggest that the decision to initiate and continue SMBG must be made in concert with the patient’s own priorities, and, if prescribed, SMBG requires effective patientprovider communication and patient education.
Am J Manag Care. 2015;21(2):e119-e129
Nearly 1 in 6 non–insulin-treated patients with diabetes self-monitor their blood glucose without either the patient or provider using the results. Key factors associated with unused results include patients not considering diabetes a high priority, physicians not engaging in shared decision making, and care teams not teaching the patient how to adjust diet/medicines based on glucose results.
  • These findings reveal several potential barriers to effective diabetes management.
  • Testing without using the results represents a significant waste of resources.
  • The decision to prescribe glucose self-monitoring should be carefully considered and may need to be reevaluated over time.
Self-monitoring of blood glucose (SMBG) has been advocated as a useful tool to help patients with type 2 diabetes mellitus (T2DM) and their healthcare providers to manage glycemia. For patients injecting insulin, SMBG can provide rapid feedback on glycemic levels and the pattern of results can often help guide insulin regimen adjustment over time. For patients not prescribed insulin, however, the clinical value of SMBG is less certain and remains controversial.1,2 For these patients, the American Diabetes Association (ADA) recommends regular glycated hemoglobin (A1C) testing, lifestyle interventions, and medication dose adjustment to achieve A1C-defined glycemic control. SMBG is suggested as a tool for patient education and self-management with “the frequency and timing … dictated by the particular needs and goals of the patient.”3

Effective clinical use of SMBG among non–insulin-using patients requires that a patient be willing to take an active role in their diabetes care, receive sufficient self-management education to act appropriately on their results, and effectively communicate with healthcare providers about goals and results. Self-monitoring without the patient or physician using the results represents a breakdown in this process. Understanding the factors contributing to this breakdown may provide important insights into barriers to better diabetes care in general, and to more effective prescription of SMBG specifically.

For this analysis, we focused specifically on non–insulintreated patients who self-monitored blood glucose. The purpose of our study was to identify factors associated with “worst case” ineffective SMBG use, defined as SMBG prescription without either the patient or the provider looking at the results. We hypothesized that patient factors (eg, lack of importance placed on diabetes control)4 and provider factors (eg, suboptimal communication)5 could increase the likelihood of self-monitoring without either the patient or provider using the results.


Participants and Setting

The study was conducted within Kaiser Permanente Northern California (KPNC), a nonprofit integrated healthcare delivery system that provides comprehensive medical care to a diverse population of approximately 3.4 million members. Distribution of patient demographic and socioeconomic factors is similar to that of the area population, except at the extremes of the income distribution.6

Survey Procedures and Patient Eligibility

The Diabetes Study of Northern California (DISTANCE) surveyed a race-stratified random sample of members of the KPNC Diabetes Registry.7 The DISTANCE survey assessed a range of social, behavioral, and care-related factors that might influence diabetes outcomes. The survey was in the field from 2005 to 2006 and had a response rate of 62%. (General information and the complete survey are available at

As part of the Diabetes and Aging Study (an ancillary study to DISTANCE), we analyzed adult survey respondents with T2DM not prescribed insulin who reported self-monitoring of blood glucose. Of 16,969 patients with T2DM who were asked SMBG questions, we excluded respondents who had less than 9 months of KPNC membership (n = 73), reported using insulin (n = 3127), had been with their current primary care physician for less than 1 year (n = 2108), had reported not using SMBG (n = 2923), or had missing responses to any of the 3 SMBG use questions (n = 1373). This left 7320 respondents eligible for analysis.

Categorization of Use of SMBG Results

Patient use of SMBG results was based on a “yes” response to either of the following 2 survey questions: “Based on readings from your home glucose tests do you: 1) adjust the dose or timing of diabetes medications? or 2) change when or what you eat or how much you exercise?” Provider use of SMBG results was defined by patient report that “during the past 12 months…your doctor or healthcare provider reviewed your own blood sugar test results” at every visit or most of the visits. We used this question with the logic that if the provider does not look at the results, he or she cannot use them to make changes in therapy. Based on responses to these questions, we categorized SMBG results as “used” (by patient or provider) or “unused” (results not used by patient or provider). In this formulation, unused SMBG test results are those that are not used to guide any changes in patient behavior and are not consistently reviewed (and consequently not used) by their provider.

Patient and Provider Characteristics

The survey included validated measures to assess selfreported patient factors including demographics, health literacy,8 diabetes knowledge,9 depression,10,11 attitudes (eg, “taking care of my diabetes is a high priority for me right now”), and healthcare behaviors such as medication adherence,12 smoking, and physical activity.13 Physical inactivity was defined as less than 3 days of vigorous activity (at least 20 minutes per day) or less than 5 days of moderate intensity activity (at least 30 minutes per day) per week. Provider factors included patient-reported trust in the provider14 and ratings of provider communication (eg, “how often did your personal physician involve you in making decisions about your healthcare as much as you wanted?” to assess shared decision making—a communication style that involves identifying a patient’s priorities and negotiating mutually agreed-upon care plans).15 Patient clinical and other demographic data were derived from administrative and clinical databases and linked to survey responses.7

We grouped characteristics into the following 5 thematic groups: 1) patient demographics; 2) clinical factors (eg, A1C level, diet management only vs treated with oral medications); 3) patient behavioral factors (eg, smoking, physical activity, and whether diabetes self-care was a priority); 4) provider factors (provider demographics, communication skills, and patient trust in provider); and 5) SMBG-specific education (including glucose goals and how to adjust their lifestyle or medications based on SMBG results).

Statistical Methods

We focused our analyses on the differences between patients with used versus unused SMBG results. Differences between respondent categories were compared using χ2 tests, ANOVA, and t tests as indicated. For the 3 variables with the greatest difference in prevalence between patients who used versus did not use SMBG results, we constructed separate Poisson regression models using a log-link function and robust error variance to estimate the relative risk of unused SMBG results after adjusting for patient demographic and clinical variables (including treatment status). Use of modified Poisson models allowed us to estimate relative risks rather than odds ratios, which diverge from relative risk when outcomes are not rare.16 We also created a combined multivariate model to estimate the fully adjusted relative risk of each key variable associated with unused SMBG results. Finally, after setting other model covariates to the overall cohort proportions by covariate categorical level, we used this multivariate model to estimate the population-based risk difference of unused SMBG results between populations with all versus none of the 3 most significant risk variables. SAS version 9.3 (SAS Institute, Inc, Cary, North Carolina) was used for all analyses in the study.

Based on the prevalence of “unused” SMBG results in our cohort, we also estimated the national cost consequences of unused SMBG results as the product of the annual average number of dispensed test strips in the group with unused SMBG results (based on pharmacy dispensing data) and wholesale test strip prices. We chose $0.98 per strip as our test strip cost because this value has been used in the published literature.17 Other potential costs associated with SMBG practice such as glucometers and lancets were not included. The study was approved by the institutional review boards of the Kaiser Foundation Research Institute, University of Chicago, and University of California, San Francisco.


Cohort Characteristics

Among the 7320 patients in our study cohort, mean age was 58.7 ± 9.9 years and mean T2DM duration was 8.3 ± 7.1 years. Based on pharmacy dispensing records, patients were prescribed SMBG test strips for 4.6 ± 2.9 years prior to the survey. Patients had been seeing their primary care physician for 6.1 ± 4.3 years; most (85.2%) were prescribed oral medicines for glycemic control. The distribution of SMBG results, by category, was that 84.8% used the results (36.7% used by both patient and provider; 34.4% by patient only; 13.8% by provider only) and 15.2% were unused by patient or provider.

Patient Demographic, Clinical, and Behavioral Factors

A1C levels were slightly higher among patients with used versus unused SMBG results (7.3% [56 mmol/mol] vs 7.1% [54 mmol/mol]; P <.001). There were several other modest though statistically significant demographic and clinical differences between patient groups (Table 1). Years of SMBG use did not differ between groups (P >.05). Larger differences between patient groups were found in patient attitudes and health behaviors: patients in the unused results group were more than twice as likely to rate diabetes as not being a high priority (17.9% vs 9.1% among patients whose SMBG results were unused vs used; P <.001) and patients with unused results were more likely to be physically inactive (42% vs 35.3%; P <.001).

Physician and Practice Factors

Physicians in this study were on average 44.8 ± 9.1 years old and had graduated from medical school 19.0 ± 9.2 years ago; 45% were women. There were no statistically significant differences in physician demographics between patients in the used versus unused SMBG results categories. However, there were substantive differences in how the 2 patient groups rated their physician’s interactions and communication (Table 2). The physician factor that stood out as markedly different was a lack of shared decision making: patients whose SMBG results were unused were less likely to report that their physician (or primary health provider) practiced shared decision making (55.2% vs 70.4%; P <.001).

Questions specific to SMBG education were framed as asking the patient if they had been taught how to adjust medication, diet, or exercise based on SMBG results in the last 12 months. Virtually all patients reported that a healthcare provider had talked about SMBG in the prior year (98.8%), but substantially fewer patients in the unused SMBG results category reported that a healthcare provider had specifically discussed glucose targets (65.8% vs 76.3% of patients in the unused vs used results group; P <.001) or how to adjust either their diet or medications in response to SMBG results (30% vs 56.5%; P <.001).

Multivariate Models

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