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Self-Monitoring of Blood Glucose: Practical Aspects

March 2010
Journal of Diabetes Science and Technology 4(2):435-9

DOI:10.1177/193229681000400225

Source
PubMed

Authors:

Wake Forest University

Self-monitoring of blood glucose (SMBG) should be part of a regular management plan for patients with diabetes. Self-monitoring of blood glucose provides information regarding an individual's dynamic blood glucose profile. This information can help with the appropriate scheduling of food, activity, and medication. It is also required for understanding of the timing of blood glucose variations. Lack of regular SMBG predicts hospitalization for diabetes-related complications. Self-monitoring of blood glucose is an essential tool for people with diabetes who are taking insulin or for those who experience fluctuations in their blood glucose levels, especially hypoglycemia. Application of practical aspects that aid in easy management of SMBG makes the task of checking blood glucose more achievable. For patients taking insulin and adjusting their dose, SMBG is needed for self-management. For others receiving oral medication, profiling glucose trends and the confirmation of high or low blood glucose can be a useful addendum to successful management.

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435

Self-Monitoring of Blood Glucose: Practical Aspects

Julienne K. Kirk, Pharm.D., C.D.E., and Jane Stegner, R.D., C.D.E.

Author Afliations: Department of Family and Community Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina

Abbreviations: (ADA) American Diabetes Association, (CGMS) continuous glucose monitoring system, (DCCT) Diabetes Control

and Complications Trial, (A1C) hemoglobin A1c, (SMBG) self-monitoring of blood glucose, (T2DM) type 2 diabetes mellitus

Keywords: diabetes, glucose monitoring, lancing, self-monitoring of blood glucose

Corresponding Author: Julienne K. Kirk, Pharm.D., C.D.E., Department of Family and Community Medicine, Wake Forest University School

of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157-1084; email address jkirk@wfubmc.edu

Journal of Diabetes Science and Technology

Volume 4, Issue 2, March 2010

Abstract

Self-monitoring of blood glucose (SMBG) should be part of a regular management plan for patients with

diabetes. Self-monitoring of blood glucose provides information regarding an individual’s dynamic blood

glucose prole. This information can help with the appropriate scheduling of food, activity, and medication.

It is also required for understanding of the timing of blood glucose variations. Lack of regular SMBG predicts

hospitalization for diabetes-related complications. Self-monitoring of blood glucose is an essential tool

for people with diabetes who are taking insulin or for those who experience uctuations in their blood glucose

levels, especially hypoglycemia. Application of practical aspects that aid in easy management of SMBG makes the

task of checking blood glucose more achievable. For patients taking insulin and adjusting their dose, SMBG is

needed for self-management. For others receiving oral medication, proling glucose trends and the conrmation

of high or low blood glucose can be a useful addendum to successful management.

J Diabetes Sci Technol 2010;4(2):435-439

CLINICAL APPLICATIONS

Introduction

Self-monitoring of blood glucose (SMBG) can be a

useful tool in the management of diabetes mellitus.

Patients with diabetes often measure their blood glucose

to detect hypoglycemia and to adjust insulin dose as

needed. Others utilize SMBG to help establish a prole

of blood glucose levels and response to nutrition and

pharmacotherapy. The American Diabetes Association

(ADA) initially established guidelines for SMBG in 1987,

and current recommendations suggest regular SMBG in

persons with diabetes based on each patient’s needs.1,2

Records of SMBG can also be used during consultation

with diabetes health care providers to titrate blood glucose-

lowering agents and to guide physical activity and food

intake.

One objective of Healthy People 2010 is to increase the

number of adults with any type of diabetes who

perform SMBG at least once daily.3 Data from the

Behavioral Risk Factor Surveillance System, representing

25 of 38 states in the United States, reported this to

be 63.4% among all adults with diabetes and 86.7%

among those treated with insulin.4 For patients with

type 1 diabetes mellitus, it is recommended that patients

measure their blood glucose at least three times daily.2

The effectiveness of SMBG has been established for

insulin-treated patients.

There is debate over optimal frequency and timing of

SMBG for those with type 2 diabetes mellitus (T2DM)

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Self-Monitoring of Blood Glucose: Practical Aspects Kirk

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J Diabetes Sci Technol Vol 4, Issue 2, March 2010

not taking insulin. Some health practitioners are skeptical

about the effectiveness of SMBG as a self-management tool.

However, lack of regular SMBG predicts hospitalization

for diabetes-related complications.5 Self-monitoring of

blood glucose has also been shown to signicantly decrease

hemoglobin A1c (A1C).6,7 The ADA recommends using

SMBG as a guide to successful therapy and to achieve

postprandial glucose targets.2

Self-monitoring of blood glucose by persons with diabetes

is an integral part of intensive glycemic treatment and is

widely believed to improve the control of blood glucose

levels and health outcomes. The results of the Diabetes

Control and Complications Trial (DCCT) among persons

with type 1 diabetes mellitus showed that intensive

glycemic control signicantly slowed the progression of

diabetes complications.8 The DCCT protocol required

SMBG at least four times each day and multiple

injections of insulin. Furthermore, the United Kingdom

Prospective Diabetes Study found that a reduction in A1C

was associated with a decreased risk of microvascular

complications in persons with T2DM.9

Specic Goals of Blood Glucose and

Documentation

The target for A1C is less than 7%; this correlates with

an average blood glucose of approximately 150 mg/dl.

Specically, the ADA recommends that preprandial plasma

glucose values range from 70 to 130 mg/dl, and peak

postprandial levels are targeted at <180 mg/dl.2 The use

of SMBG by a person with diabetes can be helpful in

developing a longitudinal glucose prole and as an aid

in making day-to-day decisions. Standards of Medical Care

in Diabetes 2010 also recognizes that there is increased

risk for diabetes at a fasting plasma glucose of 100 to

125 mg/dl or a 2-hour postprandial glucose that is 140

to 199 mg/dl as well as a A1C level that is 5.7% to 6.4%.2

Furthermore, the new standards also recognize the use

of a A1C ≥6.5% as an option for diagnosis of diabetes if

the test is performed by a laboratory using a certied

methodology.2

It is advisable to have the patient record their SMBG values

in a log book. Information about food intake, medication,

and exercise can be important for interpreting the SMBG

results. Keeping a log will also encourage the patient

to acknowledge their SMBG and to contemplate the

potential adjustments they can make with activity and

nutrition. Accurate data are imperative for the health

team to adjust medication, problem solve, and recommend

lifestyle (activity, stress, nutrition) modications for the

patient.

Steps for Self-Monitoring of Blood

Glucose

There are several necessary steps to assure accurate

data from SMBG. To assess a patient’s understanding

of SMBG knowledge, an explanation of the practical

aspects of the procedure is imperative. Table 1 contains

points to consider for successful SMBG and lists several

important steps that should be instituted for SMBG.10–13

Specically, proper use of the strips and general

procedures for meter handling must be understood

appropriately in order to obtain useful data. Since there

are a multitude of meters available on the market, the

information in Table 1 applies to general aspects of

SMBG and user manuals for each individual meter can

be consulted for specic functions, error messages, and

setting date and time. For some meters, the accuracy

can be affected by interfering substances (medication),

temperature, hematocrit level, and user technique.14

In addition, the accuracy of SMBG meters available

has been recommended to produce results within a

20% margin of error.13 Recognition of meter accuracy

variability is important, as many patients will retest

SMBG, obtaining different results that can create concern.

Table 1.

Strip and Meter Handling for Self-Monitoring of

Blood Glucose10–12

Meter and test strips should be handled with clean, dry hands.

Test strips are for single use and unique for each meter.

Test strips must be kept in the original canister, as any moisture

can affect the integrity of the strip, and the containers should be

kept closed. Check for expiration date.

Strips can be tested for accuracy with control solution provided

initially with each meter and should be checked for expiration

date. The control glucose range for the strips appears on the

canister.

Some meters require coding with each canister. Many of the

newer meters do not require coding.

The amount of blood required is usually ver y small.

Many meters easily pull the blood drop into the end of the strip.

Inadequate sample can be a source of error.

Keep meter and supplies in a cool, dry area, not in the car or in

sunlight.

Bring meter into ofce visits with diabetes educator or primary

care provider to test the accuracy comparatively.

Lancing procedures for SMBG require the patient to

fully understand the appropriate steps for successful

blood obtainment (Table 2).15,16 Most SMBG meters come

with some type of lancing device. It will be important

for the patient to demonstrate how to adjust the depth

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Self-Monitoring of Blood Glucose: Practical Aspects Kirk

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J Diabetes Sci Technol Vol 4, Issue 2, March 2010

Blood sample size can also be a factor for many individuals,

especially if there is lancing difculty or lack of blood

ow. Sample size requirement for some meters is as small

as 0.3 μl. Newer SMBG devices deliver results very quickly,

averaging around ve seconds or less. For the vision

impaired, the size of the screen will need to be evaluated

with a variety of digital output reading font sizes and

information that is available. Some meters contain very

sophisticated features such as food/medication/activity

tracking, premeal and postmeal SMBG “tagging,” and

low blood glucose alerts. The option of using a talking

meter that provides verbal guidance on each step in the

SMBG process is also available. A comprehensive guide to

SMBG devices including size, weight, sample size required,

alternative site testing approval, memory features, warranty,

and other meter aspects are available annually at the

beginning of each year in a resource guide published by

the ADA.13

Cost is a major factor for many patients and often times

becomes the primary factor for SMBG meter selection.

Insurance coverage varies widely in the amount of

copay required and whether a deductible has to be met

rst before a percentage of the supplies are covered.

Some insurance companies will only cover a specic

SMBG meter and supplies, giving the patient no

alternative unless they want to pay for a different device

out of pocket. For many insurance coverage plans,

mail order can be an option to cover the meter, strips,

and lancets as durable medical equipment and will not

factor in under the patient’s prescription benet coverage.

Documented medical necessity can help reimbursement

for exceptions.

Management of Self-Monitoring of Blood

Glucose

Management of SMBG depends on the patient’s level

of diabetes education and/or a person’s general ability

to understand the necessary basic steps for SMBG.

The application of SMBG results for self-management is

necessary for successful diabetes outcomes.17 Goal setting

from a health care and patient team approach can also

be useful as action items for SMBG results. For example,

if the results of SMBG show a consistent pattern of high

fasting glucose levels, then medications that target liver

output of glucose might be helpful. Postprandial glucose

levels (two hours after eating) provide information

regarding the impact of food intake on blood sugar.

Diet modication or medication (some orals or mealtime

insulin) may be useful therapies.

of the lancing device to avoid bruising while effectively

acquiring an adequate blood sample. Alternative sites

other than the nger can be used with many meters;

however, blood sample obtainment can often be

challenging without instruction. There are also lancing

tools that have multiple lancets that are inserted into a

device that rotates a cylinder and provides an alternative

to handling individual sharps.

Table 2.

Lancing Procedure for Self-Monitoring of Blood

Glucose13,15

Site preparation: Clean area with warm, soapy water and dry.

Food residue can be a source of false high blood sugar values.

Lancet devices to obtain blood can vary and all use a lancet to

prick the skin. Thin, sharp lancets are more comfortable. Lancets

should not be reused or cleaned, as they quickly become dull.

Depth set ting on the lancet device controls the penetration of

the stick and can be adjusted for best comfort and size of blood

sample. Most meters require very small samples—less than a

small teardrop.

Lancet should be applied rmly to the clean, dry nger, but not

with force.

Sides of the nger should be used, as there is less pain.

Use of the third, fourth, and fth digits may be preferable to

spare index nger and thumb.

Alternate test sites (upper arms and thighs) are approved for

many meter s. Finger tips or the outer palm are preferred and are

more accurate.

Obtainment of blood sample should be a gentle “milking” from

the base of the nger to the lanced tip. Pressure directly on the

site of lancing is not recommended.

Disposal of lancets and SMBG testing supplies should be done

according to local laws for sharps. In many locations, a hard

plastic container with a screw top can be disposed of in the

household trash.

Choosing a Self-Monitoring of Blood

Glucose Device

There are several considerations for pairing a meter

with each patient. Assessment of the patient’s ability to

follow the necessary steps to successfully obtain a SMBG

reading will be essential. Dexterity is a very important

factor to consider. Some meters facilitate the use of

strips that are contained with multiple use containers

or “drums” that load much like a roll of lm into a

camera. Other meters contain multiple blood glucose

strips that are in the form of a circulating wheel that

rotates and eliminates the need to handle individual test

strips. Many SMBG meters have strips that “wick” the

blood sample into the end of the strip, allowing visual

inspection to assure an appropriate sample is obtained.

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Self-Monitoring of Blood Glucose: Practical Aspects Kirk

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J Diabetes Sci Technol Vol 4, Issue 2, March 2010

The role of physical activity and diet will be needed to

assess how to appropriately adjust self-management.

Treatment should be outlined to include goal setting

for self-care behavior.18 Specic schedules for SMBG

will vary for each patient. Short periods of intense SMBG,

before and after each meal and at bedtime, will provide

data to identify glucose patterns. This can be an

important adjunct to A1C to distinguish between

fasting, preprandial hyperglycemia, and postprandial

hyperglycemia. Alternatively, patients may use a staggered

schedule of checking at various times of day throughout

the week. For example, the use of a preprandial

and two-hour postprandial SMBG gives the patient

immediate feedback on their food choices for that meal.

Postprandial spikes may be an independent risk factor

for diabetes complications, even when glycemic control

appears to be satisfactory.19 Useful tips for health

care providers and patients are outlined in Table 3.

Careful consideration should be given to assessing the

patient’s ability to comprehend and retain the procedure of

SMBG that can often be technical. Attention to literacy

and numeracy skills will be an equally important step

in successful SMBG.20 Patient demonstration of SMBG to

the diabetes educator or health care provider is critical.

patient and the health care provider should be agreed upon

to assure periodic assessment of SMBG timing, accuracy

of testing, and goals. For example, when medicine dose is

being adjusted, more frequent SMBG may be needed to

assure response to therapy. Once therapy is established,

SMBG can often be altered to accommodate patient

schedules. Targeting blood glucose uctuations around

meals or increased activity can provide useful information.

There is also the option of a continuous glucose

monitoring system (CGMS). Through a sensor that is

inserted subcutaneously, the patient wears the CGMS for

an extended period of time (usually 3 days) to capture

blood glucose levels day and night.13 While CGMS is

an ideal option to monitor blood glucose spikes and

potential lows, insurance coverage is variable, and

interpretation of the data will be necessary by a qualied

individual (diabetologist, certied diabetes educator, or

endocrinologist).

Other Summary Points

Diabetes requires self-management and adherence to

treatment guidelines such as those recommended by the

ADA; among these is regular SMBG to monitor success

with the diabetes treatment plan. The cost-effectiveness

of SMBG has also been questioned, and insurance

coverage or affordability of glucose test strips must be

considered.21 Some research has shown that providing

SMBG devices at no charge can improve the rate of

testing.22 Self-monitoring of blood glucose can serve

an important role in improving patient knowledge of

glucose levels and the effects of different behaviors on

blood glucose outcomes.

Acknowledgment:

The authors thank Carol Hildebrandt for her expertise in editing this

manuscript.

Disclosures:

Julienne K. Kirk is a diabetes educator/speaker for Novo Nordisk

and Lilly. Jane Stegner is a contracted trainer for Abbott, Animas,

and Roche.

References:

1. Consensus statement on self-monitoring of blood glucose. Diabetes

Care. 1987;10(1):95–9.

2. American Diabetes Association. Standards of medical care in

diabetes 2010. Diabetes Care. 2010;33(Suppl 1):S11–61.

3. U.S. Department of Health and Human Services. Healthy people

2010: objectives for improving health. Ofce of Disease Prevention

and Health Promotion; 2000.

Table 3.

Tips for Successful Self-Monitoring of Blood

Glucose Teaching

Use simple and specic steps at the patient’s level of

comprehension.

Be sure the patient can demonstrate the steps for SMBG.

Give your patient written recommendations for frequency and

times of testing and desired results.

Obser ve SMBG procedure at follow-up visits.

Ask the patient to assess the relationship of SMBG with exercise,

food, medications, and stress.

Specif y which SMBG values are most problematic (especially

low blood glucose) and discuss solutions with the patient.

Acknowledge the patient for goals achieved with SMBG.

Tools, such as SMBG, can help patients with glucose

regulation. The ADA recommends that patients receive

initial instruction for SMBG and routine follow-up to use

data obtained to adjust therapy.2 The frequency of SMBG

testing should be clearly outlined with emphasis on testing

during illness, preprandial and/or postprandial, and

during times of potential low blood sugar. Patients who

use carbohydrate counting to adjust insulin doses and

postprandial glucose will need SMBG goals set that may be

more intensive than for persons who are maintained with

good control using oral medications. A dialogue between the

439

Self-Monitoring of Blood Glucose: Practical Aspects Kirk

www.jou rnalofdst.org

J Diabetes Sci Technol Vol 4, Issue 2, March 2010

20. Cavanaugh K, Wallston KA, Gebretsadik T, Shintani A,

Huizinga MM, Davis D, Gregory RP, Malone R, Pignone M,

DeWalt D, Elasy TA, Rothman RL. Addressing literacy and

numeracy to improve diabetes care: two randomized controlled

trials. Diabetes Care. 2009;32(12):2149–55.

21. Klonoff DC, Schwartz DM. An economic analysis of interventions

for diabetes. Diabetes Care. 2000;23(3):390–404.

22. Soumerai SB, Mah C, Zhang F, Adams A, Barton M, Fajtova V,

Ross-Degnan D. Effects of health maintenance organization

coverage of self-monitoring devices on diabetes self-care and

glycemic control. Arch Intern Med. 2004;164(6):645–52.

4. Centers for Disease Control and Prevention. Blood glucose daily

self-monitoring: rate of daily self-monitoring among adults with

diabetes aged 18 years and older, 1997–2006. http://www.cdc.gov/

DataStatistics/2007/bloodglucose/. Accessed September 17, 2009.

5. Burge MR. Lack of compliance with home blood glucose monitoring

predicts hospitalization in diabetes. Diabetes Care. 2001;24(8):1502–3.

6. Welschen LM, Bloemendal E, Nijpels G, Dekker JM, Heine RJ,

Stalman WA, Bouter LM. Self-monitoring of blood glucose

in patients with type 2 diabetes who are not using insulin:

a systematic review. Diabetes Care. 2005;28(6):1510–7.

7. Poolsup N, Suksomboon N, Rattanasookchit S. Meta-Analysis

of the benets of self-monitoring of blood glucose on glycemic

control in type 2 diabetes patients: an update. Diabetes Technol

Ther. 2009;11(12):775–84.

8. American Association of Diabetes Educators. Intensive diabetes

management: implications of the DCCT and UKPDS. Diabetes

Educ. 2002;28(5):735–40.

9. UK Prospective Diabetes Study (UKPDS) Group. Intensive blood-

glucose control with sulphonylureas or insulin compared with

conventional treatment and risk of complications in patients with

type 2 diabetes (UKPDS 33). Lancet. 1998;352(9131):837–53.

10. Peragallo-Dittko V. Monitoring. In: Diabetes management therapies,

a core curriculum for diabetes education. 5th ed. Franz MJ, ed.

Chicago, IL: American Association of Diabetes Educators, 2003:189–212.

11. Havas S, Mayeld J, American Academy of Family Physicians Panel

on Self-Monitoring of Blood Glucose. Self-control: a physician’s

guide to blood glucose monitoring in the management of diabetes.

An American family physician monograph. Leawood: American

Academy of Family Physicians; 2004.

12. Austin MM, Haas L, Johnson T, Parkin CG, Parkin CL, Spollett G,

Volpone MT. Self-monitoring of blood glucose: benets and utilization.

Diabetes Educ. 2006;32(6):835–6, 844–7.

13. Bunker K, American Diabetes Association. 2010 Consumer Guide.

Blood glucose meters. Diabetes Forecast. 2010;63(1):32–41.

14. Hirsch IB, Bode BW, Childs BP, Close KL, Fisher WA, Gavin JR,

Ginsberg BH, Raine CH, Verderese CA. Self-monitoring of blood

glucose (SMBG) in insulin- and non-insulin-using adults with

diabetes: consensus recommendations for improving SMBG accuracy,

utilization, and research. Diabetes Technol Ther. 2008;10(6):419–39.

15. American Diabetes Association. 2009 Resource Guide. Home

glucose monitoring: at the center of your diabetes care plan is a

small, lightweight device that provides lifesaving knowledge at

your ngertips—literally. Diabetes Forecast. 2009;62(1):53– 65.

16. American Association Diabetes Educators. Position statement:

educating providers and persons with diabetes to prevent the

transmission of bloodborne infections and avoid injuries from

sharps. http://www.diabeteseducator.org/export/sites/aade/_resources/pdf/

EducProvidersBloodborneInfetions.pdf. Accessed September 30, 2009.

17. Klonoff DC, Bergenstal R, Blonde L, Boren SA, Church TS,

Gaffaney J, Jovanovic L, Kendall DM, Kollman C, Kovatchev BP,

Leippert C, Owens DR, Polonsky WH, Reach G, Renard E,

Riddell MC, Rubin RR, Schnell O, Siminiero LM, Vigersky RA,

Wilson DM, Wollitzer AO. Consensus report of the coalition for

clinical research—self-monitoring of blood glucose. J Diabetes Sci

Technol. 2008;2(6):1030–53.

18. Funnell MM, Brown TL, Childs BP, Haas LB, Hosey GM, Jensen B,

Maryniuk M, Peyrot M, Piette JD, Reader D, Siminerio LM, Weinger K,

Weiss MA. National standards for diabetes self-management

education. Diabetes Care. 2010;33(Suppl 1):S89–96.

19. Parkin CG, Davidson JA. Values of self-monitoring blood glucose

pattern analysis in improving diabetes outcomes. J Diabetes Sci

Technol. 2009;3(3):500–8.

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Background: Diabetes-related distress (DD) significantly impacts self-management and quality of life (QoL) in individuals with type 1 diabetes (T1D). While previous research has established a strong link between DD and glycemic control in type 2 diabetes, the relationship remains less consistent in T1D. Additionally, continuous glucose monitoring (CGM) has been shown to improve glycemic outcomes, yet its effects on self-management and QoL are still debated. This study aimed to examine the relationship between DD, self-management efficacy (SME), and QoL in T1D, incorporating both physiological and behavioral indicators. Furthermore, differences between CGM-users and non-users were investigated. Methods: A cross-sectional study including 108 T1D patients was conducted. Participants completed several validated self-report measures, including the Diabetes Distress Scale (DDS), Diabetes Self-Management Questionnaire (DSMQ), and Audit of Diabetes-Dependent Quality of Life (ADDQoL-19). HbA1c levels and CGM usage were retrieved from medical records. Structural equation modeling (SEM) was used to examine the relationships between DD, self-management, and QoL. Results: Distress level (DDS) had a significant negative effect on SME (β = −0.47, p < 0.001), suggesting that higher distress levels are associated with lower self-management. In contrast, SME showed no significant impact on quality of life (β = 0.03, p = 0.779). However, the relationship between quality of life and distress was significant and negative (β = −0.37, p < 0.001), meaning that higher distress levels are linked to a lower quality of life. No significant differences in DD, SME, HbA1c, or QoL were found among CGM users and non-users. Conclusions: DD significantly impacts self-management and QoL in individuals with T1D. Therefore, incorporating PROs on DD and on behavioral aspects of self-management alongside HbA1c levels in clinical care is essential for optimizing treatment plans and improving physical health outcomes. While CGM technology facilitates glucose regulation, it does not inherently improve QoL, which is more closely linked to distress.

Enhancing Health Equity and Patient Engagement in Diabetes Care: Technology-Aided Continuous Glucose Monitoring Pilot Implementation Project

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Federally Qualified Health Centers (FQHCs) provide service to medically underserved areas and communities, providing care to over 32 million patients annually. The burden of diabetes is increasing, but often, the vulnerable communities served by FQHCs lag in the management of the disease due to limited resources and related social determinants of health. With the increasing adoption of technologies in health care delivery, digital tools for continuous glucose monitoring (CGM) are being used to improve disease management and increase patient engagement. In this viewpoint, we share insights on the implementation of a CGM program at an FQHC, the Community-University Health Care Center (CUHCC) in Minneapolis, Minnesota. Our intent is to improve diabetes management through better monitoring of glucose and to ensure that the CGM program enables our organization’s overarching digital strategy. Given the resource limitations of our population, we provided Libre Pro devices to uninsured patients through grants to improve health care equity. We used an interdisciplinary approach involving pharmacists, nurses, and clinicians and used hemoglobin A1c (HbA1c) levels as a measure of diabetes management. We assessed the CGM program and noted key aspects to guide future implementation and scalability. We recruited 148 participants with a mean age of 54 years; 39.8% (59/148) self-identified their race as non-White, 9.5% (14/148) self-identified their ethnicity as Hispanic or Latino, and one-third (53/148, 35.8%) were uninsured. Participants had diverse language preferences, with Spanish (54/148, 36.5%), English (52/148, 35.1%), Somali (21/148, 14.2%), and other languages (21/148, 14.2%). Their clinical characteristics included an average BMI of 29.91 kg/m2 and a mean baseline HbA1c level of 9.73%. Results indicate that the CGM program reduced HbA1c levels significantly from baseline to first follow-up (P<.001) and second follow-up (P<.001), but no significant difference between the first and second follow-up (P=.94). We share key lessons learned on cultural and language barriers, the digital divide, technical issues, and interoperability needs. These key lessons are generalizable for improving implementation at FQHCs and refining digital strategies for future scalability.

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Full-text available

Sep 2024

Diabetes mellitus (DM) is a prevalent disorder with an urgent need for continuous, precise, and on-site biomarker monitoring devices. The continuous monitoring of DM biomarkers from different biological matrices will become routine in the future, thanks to the promising biosensor design. Lately, employing different nanomaterials in biosensor receptor parts has had a great impact on smart DM monitoring. Among them, gold nanostructures (AuNSs) have arisen as highly potential materials in fabricating precise DM biosensors due to their unique properties. The present study provides an update on the applications of AuNSs in biosensors for detecting glucose as well as other DM biomarkers, such as glycated hemoglobin (HbA1c), glycated albumin (GA), insulin, insulin antibodies, uric acid, lactate, and glutamic acid decarboxylase antibodies (GADA), with a focus on the most important factors in biosensor performance such as sensitivity, selectivity, response time, and stability. Specified values of limit of detection (LOD), linear concentrations, reproducibility%, recovery%, and assay time were used to compare studies. In conclusion, AuNSs, owing to the wide electrochemical potential window and low electrical resistivity, are valuable tools in biosensor design, alongside other biological reagents and/or nanomaterials.

Diabetes Self-Care Behaviors in Singapore and Their Associations With Patients’ Characteristics and Health Literacy

Article

Sep 2024

Purpose: The purpose of this study was to examine the relationship between self-management behaviors (eg, healthy eating, being active, medication taking, glucose monitoring, feet check), sociodemographic factors, disease-related characteristics, and health literacy among patients with type 2 diabetes in Singapore. Methods: Data were analyzed from a nationwide survey conducted between 2019 and 2020 (n = 387). Self-management behaviors were assessed using the Dietary Approaches to Stop Hypertension questionnaire, the Global Physical Activity Questionnaire, and a diabetes care questionnaire. A linear regression model was generated to examine the association of healthy eating with the variables of interest (sociodemographic factors, disease-related characteristics, and health literacy), and logistic regression models were generated to investigate the significant correlates of the remaining self-care behaviors. Results: Regression models showed that the 5 self-care behaviors have different correlates. Nonetheless, compared to individuals aged 50 to 64 years, those aged 65 years and above were less likely to be active, adhere to their medication prescription, and check their feet. Individuals with a higher number of diabetes-related complications were less likely to be sufficiently active but more likely to monitor their glucose level and check their feet. Moreover, individuals with poor health literacy were more likely to eat healthily and be sufficiently active. Conclusions: Programs related to self-care behaviors can be tailored to specific demographics to improve their uptake in the population. Furthermore, encouraging comprehensive self-care behaviors in those aged 65 years and above is crucial for effective diabetes management.

Physiological Signal Based Blood Glucose Prediction in Diabetics and Non-Diabetics

Conference Paper

Nov 2024

Effective blood glucose regulation is essential for both diabetic and non-diabetic individuals. Finger-prick methods are inconvenient and painful, while continuous glucose monitoring (CGM) systems are costly and require frequent sensor replacements. This paper proposes an innovative approach for continuous real-time blood glucose level estimation using non-invasive physiological signals and ensemble regression techniques. We observed significant differences in the predictive power of individual features and overall model performance between the diabetic and the non-diabetic groups. The best model for the diabetic group achieved better performance (R 2 = 0.50) compared to the best model for the non-diabetic group (R 2 = 0.27). However, when evaluated for clinical accuracy, the non-diabetic models outperformed the diabetic models. The best non-diabetic model had 100% of predictions in the clinically acceptable zones of the Clarke Error Grids (CEG), while the best diabetic model had only 91%. The between-group differences in model performance are likely due to the variations in underlying glucose dynamics between diabetic and non-diabetic individuals. Our findings highlight the necessity of collecting and sharing large multimodal datasets from both diabetic and non-diabetic populations, as well as evaluating glucose prediction models from both mathematical and clinical accuracy.

Advancements in Surface Plasmon Resonance Sensors for Real-Time Detection of Chemical Analytes: Sensing Materials and Applications

Article

Full-text available

Jan 2025

Chemicals are being used in various fields with the development of industry, but the importance of human safety from chemicals is emerging. Instead of the traditional detection methods of analyzing...

Sonographic Determination of the Pancreatic Duct Diameter among Healthy Individuals in Gaborone, Southeast District, Botswana

Article

Jun 2024

Uko Ogba

The pancreatic duct is an intrapancreatic restricted tube that connects the pancreas to the common bile duct. The pancreatic duct transports pancreatic juice to the common bile duct for digesting. Pancreatic duct diameter is an important index in assessing pancreatic duct pathology as well as the pancreas. Duct obstruction may lead to dilatation due to cancer of the pancreas, pancreatitis, cholelithiasis or duodenal pathology. Recent studies have established a direct relationship between dilatation of the pancreatic duct and cancer of the pancreas. The objective of this study is to determine the pancreatic duct diameter in apparently healthy individuals in Gaborone and its relationship with anthropometric variables. Sonographic determination of the pancreatic duct diameter is very important for providing an objective evaluation of the pancreas and the nature and extent of disease if pathologic. Establishment of a baseline reference value for the pancreatic duct diameter is therefore important for providing a normogram in healthy individuals in Gaborone, Botswana. A total of 384 randomly selected individuals and 330 pancreatic duct diameter measurements were used for the study between July 2020 and May 2021. Optimum sonographic scanning technique described by Taylor et al was utilized in measuring the pancreatic duct diameter in this study. The mean pancreatic duct diameter was: 2.40±0.58mm for the head, 2.10±0.50mm for the body and 1.84±0.54mm for the tail. The mean pancreatic duct diameter for the present study was 2.11±0.50mm. The pancreatic duct diameter increased with age from 45years, indicating statistically significant relationship (P-value=0.0492). There was no significant statistical difference in the overall mean pancreatic duct diameter between male and female (p > 0.05). The present study has established that the pancreatic duct diameter for adults in Gaborone is 2.11±0.50mm and could be used in clinical setting as baseline reference value. The normogram also will be a valuable tool in age related pancreatic duct pathologies.

Health Literacy and Numeracy in Self-monitoring of Capillary Glycemia: A Systematic Review of Mixed Methods

Article

Full-text available

Jan 2025
Curr Diabetes Rev

Objective The aim of this study was to synthesize scientific evidence on the influence of health literacy and numerical knowledge on self-monitoring of capillary blood glucose. Methods Adhering to the PRISMA guidelines and the principles of the Joanna Briggs Institute, a comprehensive search was conducted across multiple databases, including CINAHL, Cochrane, Embase, LILACS, PubMed, Scopus, Web of Science, Google Scholar, OPENGREY, and NDLTD. The review included studies published in any language that examined the relationship between HL, numeracy, and SMBG. Results A total of 12 studies met the inclusion criteria. These studies utilized various assessment tools, such as the Brief Test of Functional Health Literacy in Adults (B-TOFHLA) and the Diabetes Numeracy Test (DNT-15), to evaluate health literacy and numeracy levels. The findings revealed a significant association between adequate HL and numeracy and improved SMBG practices. Specifically, individuals with sufficient health literacy were more likely to monitor their blood glucose levels regularly and make appropriate treatment adjustments based on their readings. Conclusion The results indicated that numeracy skills and health literacy are critical determinants of effective SMBG, influencing the frequency and accuracy of self-care practices in diabetes management. These findings highlight the urgent need for educational interventions tailored to enhance these skills, which could lead to improved health outcomes for individuals with diabetes.

Continuous glucose monitoring for self-management of diabetes in people living with type 2 diabetes mellitus on basal insulin therapy: A microsimulation model and cost-effectiveness analysis from a US perspective with relevance to Medicaid

Article

Aug 2024

Background: Reducing the risks of complications is a primary goal of diabetes management, with effective glycemic control a key factor. Glucose monitoring using continuous glucose monitoring (CGM) technology is an important part of diabetes self-management, helping patients reach and maintain targeted glucose and glycated hemoglobin (HbA1c) levels. Although clinical guidelines recommended CGM use, coverage by Medicaid is limited, likely because of cost concerns. Objective: To assess the cost-effectiveness of FreeStyle Libre CGM systems, compared with capillary-based self-monitoring of blood glucose (SMBG), in US individuals with type 2 diabetes mellitus using basal insulin. Methods: A patient-level microsimulation model was used to compare CGM with SMBG for a population of 10,000 patients. A 10-year horizon was used, with an annual discount rate of 3.0% for costs and utilities. Model population characteristics were based on US national epidemiology data. Patient outcomes were based on published clinical trials and real-world studies. Annual costs, reflective of 2023 values, included CGM and SMBG acquisition costs and the costs of treating diabetic ketoacidosis, severe hypoglycemia, and diabetes complications. The effect of CGM was modeled as a persistent 1.1% reduction in HbA1c relative to SMBG based on US real-world evidence. Disutilities were based on published clinical trials and other relevant literature. The primary outcome was cost per quality-adjusted life-year (QALY) gained. Sensitivity analyses were performed to test the validity of the model results when accounting for a plausible variation of inputs. Results: In the base case analysis, CGM was dominant to SMBG, providing more QALYs (6.18 vs 5.97) at a lower cost (

70,137 vs

71,809) over the 10-year time horizon. A

10,456 increase in glucose monitoring costs was offset by a

12,127 reduction in treatment costs. Cost savings reflected avoidance of acute diabetic events (savings owing to reductions in severe hypoglycemia and diabetic ketoacidosis were

271 and

2,159, respectively) and a reduced cumulative incidence of diabetes complications, particularly renal failure (saving

5,292), myocardial infarction (saving

1,996), and congestive heart failure (saving

1,061). Scenario analyses were consistent with the base case results, and the incremental cost-effectiveness ratio for CGM vs SMBG ranged from dominant to cost-effective. In probabilistic analysis, CGM was 100% likely to be cost-effective at a willingness-to-pay threshold of

50,000/QALY. Conclusions: CGM is cost-effective compared with SMBG for US patients with type 2 diabetes mellitus receiving basal insulin therapy. This suggests that state Medicaid programs could benefit from broader coverage of CGM.

Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33)

Article

Full-text available

Sep 1998

Background Improved blood-glucose control decreases the progression of diabetic microvascular disease, but the effect on macrovascular complications is unknown. There is concern that sulphonylureas may increase cardiovascular mortality in patients with type 2 diabetes and that high insulin concentrations may enhance atheroma formation. We compared the effects of intensive blood-glucose control with either sulphonylurea or insulin and conventional treatment on the risk of microvascular and macrovascular complications in patients with type 2 diabetes in a randomised controlled trial. Methods 3867 newly diagnosed patients with type 2 diabetes, median age 54 years (IQR 48-60 years), who after 3 months' diet treatment had a mean of two fasting plasma glucose (FPG) concentrations of 6.1-15.0 mmol/L were randomly assigned intensive policy with a sulphonylurea (chlorpropamide, glibenclamide, or. glipizide) or with insulin, or conventional policy with diet. The aim in the intensive group was FPG less than 6 mmol/L. in the conventional group, the aim was the best achievable FPG with diet atone; drugs were added only if there were hyperglycaemic symptoms or FPG greater than 15 mmol/L. Three aggregate endpoints were used to assess differences between conventional and intensive treatment: any diabetes-related endpoint (sudden death, death from hyperglycaemia or hypoglycaemia, fatal or non-fatal myocardial infarction, angina, heart failure, stroke, renal failure, amputation [of at least one digit], vitreous haemorrhage, retinopathy requiring photocoagulation, blindness in one eye,or cataract extraction); diabetes-related death (death from myocardial infarction, stroke, peripheral vascular disease, renal disease, hyperglycaemia or hypoglycaemia, and sudden death); all-cause mortality. Single clinical endpoints and surrogate subclinical endpoints were also assessed. All analyses were by intention to treat and frequency of hypoglycaemia was also analysed by actual therapy. Findings Over 10 years, haemoglobin A(1c) (HbA(1c)) was 7.0% (6.2-8.2) in the intensive group compared with 7.9% (6.9-8.8) in the conventional group-an 11% reduction. There was no difference in HbA(1c) among agents in the intensive group. Compared with the conventional group, the risk in the intensive group was 12% lower (95% CI 1-21, p=0.029) for any diabetes-related endpoint; 10% lower (-11 to 27, p=0.34) for any diabetes-related death; and 6% lower (-10 to 20, p=0.44) for all-cause mortality. Most of the risk reduction in the any diabetes-related aggregate endpoint was due to a 25% risk reduction (7-40, p=0.0099) in microvascular endpoints, including the need for retinal photocoagulation. There was no difference for any of the three aggregate endpoints the three intensive agents (chlorpropamide, glibenclamide, or insulin). Patients in the intensive group had more hypoglycaemic episodes than those in the conventional group on both types of analysis (both p<0.0001). The rates of major hypoglycaemic episodes per year were 0.7% with conventional treatment, 1.0% with chlorpropamide, 1.4% with glibenclamide, and 1.8% with insulin. Weight gain was significantly higher in the intensive group (mean 2.9 kg) than in the conventional group (p<0.001), and patients assigned insulin had a greater gain in weight (4.0 kg) than those assigned chlorpropamide (2.6 kg) or glibenclamide (1.7 kg). Interpretation Intensive blood-glucose control by either sulphonylureas or insulin substantially decreases the risk of microvascular complications, but not macrovascular disease, in patients with type 2 diabetes. None of the individual drugs had an adverse effect on cardiovascular outcomes. All intensive treatment increased the risk of hypoglycaemia.

National Standards for Diabetes Self-Management Education and Support

Article

Full-text available

Sep 2012

By the most recent estimates, 18.8 million people in the U.S. have been diagnosed with diabetes and an additional 7 million are believed to be living with undiagnosed diabetes. At the same time, 79 million people are estimated to have blood glucose levels in the range of prediabetes or categories of increased risk for diabetes. Thus, more than 100 million Americans are at risk for developing the devastating complications of diabetes (1). Diabetes self-management education (DSME) is a critical element of care for all people with diabetes and those at risk for developing the disease. It is necessary in order to prevent or delay the complications of diabetes (2–6) and has elements related to lifestyle changes that are also essential for individuals with prediabetes as part of efforts to prevent the disease (7,8). The National Standards for Diabetes Self-Management Education are designed to define quality DSME and support and to assist diabetes educators in providing evidence-based education and self-management support. The Standards are applicable to educators in solo practice as well as those in large multicenter programs—and everyone in between. There are many good models for the provision of diabetes education and support. The Standards do not endorse any one approach, but rather seek to delineate the commonalities among effective and excellent self-management education strategies. These are the standards used in the field for recognition and accreditation. They also serve as a guide for nonaccredited and nonrecognized providers and programs. Because of the dynamic nature of health care and diabetes-related research, the Standards are reviewed and revised approximately every 5 years by key stakeholders and experts within the diabetes education community. In the fall of 2011, a Task Force was jointly convened by the American Association of Diabetes Educators (AADE) and the American Diabetes Association …

National Standards for Diabetes Self-Management Education

Article

Full-text available

Jan 2010

National Standards for Diabetes Self-Management Education

Article

Full-text available

Jan 2011

Value of Self-Monitoring Blood Glucose Pattern Analysis in Improving Diabetes Outcomes

Article

Full-text available

May 2009

Self-monitoring of blood glucose (SMBG) is an important adjunct to hemoglobin A1c (HbA1c) testing. This action can distinguish between fasting, preprandial, and postprandial hyperglycemia; detect glycemic excursions; identify and monitor resolution of hypoglycemia; and provide immediate feedback to patients about the effect of food choices, activity, and medication on glycemic control. Pattern analysis is a systematic approach to identifying glycemic patterns within SMBG data and then taking appropriate action based upon those results. The use of pattern analysis involves: (1) establishing pre- and postprandial glucose targets; (2) obtaining data on glucose levels, carbohydrate intake, medication administration (type, dosages, timing), activity levels and physical/emotional stress; (3) analyzing data to identify patterns of glycemic excursions, assessing any influential factors, and implementing appropriate action(s); and (4) performing ongoing SMBG to assess the impact of any therapeutic changes made. Computer-based and paper-based data collection and management tools can be developed to perform pattern analysis for identifying patterns in SMBG data. This approach to interpreting SMBG data facilitates rational therapeutic adjustments in response to this information. Pattern analysis of SMBG data can be of equal or greater value than measurement of HbA1c levels.

Consensus Report of the Coalition for Clinical Research--Self-Monitoring of Blood Glucose

Article

Full-text available

Nov 2008

The Coalition for Clinical Research—Self-Monitoring of Blood Glucose Scientific Board, a group of nine academic clinicians and scientists from the United States and Europe, convened in San Francisco, California, on June 11–12, 2008, to discuss the appropriate uses of self-monitoring of blood glucose (SMBG) and the measures necessary to accurately assess the potential benefit of this practice in noninsulin-treated type 2 diabetes mellitus (T2DM). Thirteen consultants from the United States, Europe, and Canada from academia, practice, and government also participated and contributed based on their fields of expertise. These experts represent a range of disciplines that include adult endocrinology, pediatric endocrinology, health education, mathematics, statistics, psychology, nutrition, exercise physiology, and nursing. This coalition was organized by Diabetes Technology Management, Inc. Among the participants, there was consensus that:

Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33)

Article

Jan 1998

Group UPDS

2010 Consumer Guide. Blood glucose meters

Article

Jan 2010

K. Bunker

Intensive diabetes management: implications of the DCCT and UKPDS

Article

Sep 2002

Meta-Analysis of the Benefits of Self-Monitoring of Blood Glucose on Glycemic Control in Type 2 Diabetes Patients: An Update

Article

Dec 2009
DIABETES TECHNOL THE

Our systematic review and meta-analysis of the benefit of self-monitoring of blood glucose (SMBG) in improving glycemic control in type 2 diabetes was published in 2008. With the few studies that have emerged afterward, we undertook subsequent meta-analysis of the available evidence to update the results. Clinical trials of SMBG were identified through electronic searches (MEDLINE, EMBASE, and The Cochrane Library) up to and including June 2009. Studies were included if they met the following inclusion criteria: (1) randomized controlled trial comparing SMBG versus non-SMBG in type 2 diabetes patients not using insulin and (2) hemoglobin A1c (HbA(1c)) reported as an outcome measure. The efficacy was estimated with the mean difference in the changes of HbA(1c) from baseline to final assessment between the SMBG and the non-SMBG groups. SMBG was effective in reducing HbA(1c) in non-insulin-treated type 2 diabetes (pooled mean difference, -0.24%; 95% confidence interval, -0.34% to -0.14%; P < 0.00001). Glycemic control significantly improved among the subgroup of patients whose baseline HbA(1c) was >or=8%. In contrast, no significant effect of SMBG was detected in patients who had HbA(1c) <8%. The available evidence suggests the usefulness of SMBG in improving glycemic control in non-insulin-treated type 2 diabetes as demonstrated by the reduction of HbA(1c) levels. In particular, SMBG proved to be useful in the subgroup of patients whose baseline HbA(1c) was >or=8%.

Self-Monitoring of Blood Glucose: Practical Aspects

Abstract

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