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Glucometer Use and Glycemic Control Among Hispanic Patients With Diabetes in Southern Florida

      Abstract

      Background

      Self-monitoring of blood glucose (SMBG) has been deemed a critical component of diabetes care in the United States. To be effective, patients must have some diabetes knowledge, glucometer proficiency, and an ability to take appropriate actions when certain readings are obtained. However, most patients take no action in response to out-of-range glucometer readings, and in many populations, SMBG practices are not associated with improved glycemic control. Thus, SMBG utilization is being reconsidered in other countries. Nonetheless, SMBG behaviors are increasingly recommended in the United States, where the Hispanic population represents the fastest-growing minority group and is disproportionately affected by suboptimal diabetes outcomes. Because a growing number of interventions aim to reduce diabetes disparities by improving glycemic control among minorities, it is essential to determine whether efforts should focus on SMBG practices. We present data on SMBG behaviors and glycemic control among participants from the Miami Healthy Heart Initiative (MHHI), a National Institutes of Health/National Heart, Lung, and Blood Institute–sponsored trial assessing a community health worker (CHW) intervention among Hispanic patients with poorly controlled diabetes.

      Objective

      This study examined the effects of a CHW intervention on SMBG practices, glycosylated hemoglobin (HbA1c), and knowledge of appropriate responses to glucometer readings among Hispanic patients with diabetes.

      Methods

      This study was an ancillary investigation within MHHI, a randomized, controlled trial in 300 Hispanic patients. Participants were intervention-group members who received 12 months of CHW support. Assessments were administered at baseline and poststudy to determine potential barriers to optimal health. Items from validated instruments were used to determine knowledge of appropriate responses to different glucose readings. These data were linked to HbA1c values. Means and frequencies were used to describe population characteristics and glucometer proficiency. Paired-sample t tests examined potential differences in HbA1c outcomes and SMBG practices. Qualitative data were collected from the CHWs who worked with study participants.

      Results

      Our population was diverse, representing several countries. Mean HbA1c improved significantly, from 10% to 8.8% (P ≤ 0.001). SMBG practices did not change. At baseline, 96% of patients reported owning a glucometer and 94% reported knowing how to use it. However, quantitative assessments and qualitative data suggested that participants had suboptimal knowledge regarding actions that could cause an out-of-range reading or how to respond to certain readings.

      Conclusions

      SMBG behaviors were not associated with glycemic control in our sample. We conclude that a CHW intervention may improve glycemic control without improving SMBG practices. Future interventions may reconsider whether efforts should be directed toward improving SMBG behaviors.

      Key words

      Introduction

      In the United States, self-monitoring of blood glucose (SMBG) has been deemed as a crucial component of diabetes care.
      American Diabetes Association
      Clinical practice recommendations 1997.
      To be effective, SMBG requires patients to have some baseline diabetes knowledge, glucometer proficiency, and an ability to take appropriate actions when certain readings are obtained. Thus, the practice of SMBG alone does not improve glycemic control, as improved outcomes are dependent on the actions taken in response to measured glucose values. Although some studies have found that individuals who practice SMBG achieve improved HbA1c values,
      • Karter A.J.
      • Ackerson L.M.
      • Darbinian J.A.
      • et al.
      Self-monitoring of blood glucose levels and glycemic control: the Northern California Kaiser Permanente Diabetes registry.
      • Welschen L.M.
      • Bloemendal E.
      • Nijpels G.
      • et al.
      Self-monitoring of blood glucose in patients with type 2 diabetes who are not using insulin: a systematic review.
      much of the recent literature has concluded that SMBG behaviors are not associated with improved outcomes.
      • Malanda U.L.
      • Welschen L.M.
      • Riphagen II,
      • et al.
      Self-monitoring of blood glucose in patients with type 2 diabetes mellitus who are not using insulin.
      • 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 randomised trial.
      • Kolb H.
      • Kempf K.
      • Martin S.
      • et al.
      On what evidence-base do we recommend self-monitoring of blood glucose?.
      • O’Kane M.J.
      • Bunting B.
      • Copeland M.
      • Coates V.E.
      Efficacy of self-monitoring of blood glucose in patients with newly diagnosed type 2 diabetes (ESMON study): Randomised controlled trial.
      • Davidson M.B.
      Counterpoint: self-monitoring of blood glucose in type 2 diabetic patients not receiving insulin: a waste of money.
      • Farmer A.J.
      • Perera R.
      • Ward A.
      • et al.
      Meta-analysis of individual patient data in randomised trials of self monitoring of blood glucose in people with non-insulin treated type 2 diabetes.
      In fact, a recent article by Malanda et al,
      • Malanda U.
      • Bot S.
      • Nijpels G.
      Self-monitoring of blood glucose in noninsulin-using type 2 diabetic patients: it is time to face the evidence.
      based on several diabetes studies, reported that SMBG in type 2 diabetic patients is a “waste of money.” Additional research also found that SMBG behaviors did not lead to improved glycemic control, even among individuals with type 1 diabetes and those with gestational diabetes.
      • Kolb H.
      • Kempf K.
      • Martin S.
      • et al.
      On what evidence-base do we recommend self-monitoring of blood glucose?.
      This position is supported by the editor-in-chief of Diabetes Care, who wrote, “The use of SMBG is associated with huge costs, which should be redirected to effective strategies to improve health.”
      • Malanda U.
      • Bot S.
      • Nijpels G.
      Self-monitoring of blood glucose in noninsulin-using type 2 diabetic patients: it is time to face the evidence.
      In light of this research, the practice of SMBG is being reconsidered in other countries. For example, providers in the United Kingdom no longer routinely recommend glucose monitoring to patients who do not take insulin, and a recent report from the National Health Service in the United Kingdom found that SMBG was associated with only minimal improvements in glycemic control.
      • Heller S.
      • et al.
      A report prepared by an NHS Diabetes Working Group
      Self-monitoring of blood glucose in noninsulin-treated type 2 diabetes.
      • Clar C.
      • Barnard K.
      • Cummins E.
      • et al.
      Self-monitoring of blood glucose in type 2 diabetes: systematic review.
      Even in the United States, studies have found that most patients take no action in response to out-of-range glucometer readings.
      • Polonsky W.H.
      • Fisher L.
      • Hessler D.
      • Edelman S.V.
      A survey of blood glucose monitoring in patients with type 2 diabetes: are recommendations from health care professionals being followed?.
      Despite this evidence, the practice of SMBG has become increasingly common in the United States, where minority populations are disproportionately affected by diabetes.

      US Dept of Health and Human Services. National healthcare disparities report. 2012. AHRQ publication no. 13-0003. http://www.ahrq.gov/research/findings/nhqrdr/nhdr12/nhdr12_prov.pdf. Accessed December 23, 2013.

      The Hispanic population is the fastest-growing minority group in the United States, and by 2050 it is projected that 1 in 3 persons in the United States will be Hispanic.

      US Census Bureau. An older and more diverse nation by midcentury. http://quickfacts.census.gov. Accessed September 3, 2013.

      In addition both the incidence and prevalence of diabetes are twice as high in the Hispanic population compared with non-Hispanic whites.

      National Alliance for Hispanic Health. The State of Diabetes Among Hispanics. http://www.hispanichealth.org/assets/pdf/StateofDiabetes2010.pdf. Accessed September 3, 2013.

      Because Hispanic patients have diabetes disparities and the value of SMBG practices in this population has not been established, it is of major public health importance to determine whether practicing SMBG leads to improved glycemic control in this population.

      US Census Bureau. An older and more diverse nation by midcentury. http://quickfacts.census.gov. Accessed September 3, 2013.

      Health and Human Service Fact sheet. Minority health Disparities at a Glance. Retrieved from: http://minorityhealth.hhs.gov/templates/content.aspx?ID=2139

      Because a growing number of interventions are designed to address diabetes disparities among Hispanic patients,
      • Sarkisian C.A.
      • Brown A.F.
      • Norris K.C.
      • et al.
      A systematic review of diabetes self-care interventions for older, African American, or Hispanic adults.
      it is also worthwhile to assess whether protocols should focus on improving SMBG behaviors or should redirect efforts toward more efficacious strategies associated with improved glycemic control.
      In this study, we examined the effects of a community health worker (CHW) intervention on SMBG practices and glycemic control. Participants in our trial were enrolled into the intervention group of the Miami Health Heart Initiative (MHHI), a randomized, controlled trial testing the impact of a 12-month CHW intervention among 300 Hispanic patients with poorly controlled diabetes. The overall goal of MHHI is to reduce cardiovascular risk by improving diabetes management, and primary outcomes are changes in low-density lipoprotein cholesterol (LDL-C), systolic blood pressure, and hemoglobin (Hb) A1c. The study described herein is an ancillary investigation within MHHI, conducted to determine the effects of the CHW intervention on HbA1c, SMBG utilization, and knowledge of appropriate actions to take in response to out-of-range glucometer readings.

      Methods

      In this study, we examined data on 117 of 150 patients randomized to the intervention arm of MHHI, in whom CHWs were able to conduct both prestudy and poststudy assessments. The main study protocol, as well as the CHW interviews, were approved by the institutional review boards at the University of Miami and Jackson Memorial Hospital, Miami, Florida. Eligible participants had at least 1 laboratory result of HbA1c ≥ 8 during the prior 12 months and had accessed diabetes care at Jackson Memorial Hospital. At baseline and poststudy, all participants had undergone phlebotomy and a structured 90-minute research interview before being randomized to a CHW-intervention group or to a control group. Individuals randomized to the intervention received 12 months of CHW support that included accompaniment to medical and social services appointments, and peer education focused on SMBG practices, medication adherence, and life style behaviors.

      Quantitative Measures

      Demographic characteristics were collected by the parent study (MHHI). Within 1 month of randomization, patients in the CHW arm began receiving home visits to establish an individualized plan of care. Each home visit conducted by CHWs was tracked throughout the intervention. During the initial home visits, CHWs administered a structured questionnaire to determine barriers to, enablers of, and facilitators of optimal health. Included in this assessment were measures of SMBG utilization and knowledge of appropriate actions to take in response to out-of-range glucometer readings. CHWs read each item from the assessments to each participant and recorded each response on a paper form. These data were reviewed for accuracy by a research assistant before they were entered into a password-protected database (IBM SPSS Statistics, IBM Corporation, Armonk, New York). On completion of data entry, the database was also reviewed for accuracy by a different research assistant.
      Our CHW intake included 3 items on glucometer utilization. The first 2 were from the Stanford Patient Education Research Center Diabetes Questionnaire.
      • Lorig K.R.
      • Ritter P.L.
      • Jacquez A.
      Outcomes of border health Spanish/English chronic disease self-management programs.
      These items were: (1) “Do you have a glucometer?” (yes/no); and (2) “How many days in the last week did you test your blood sugar level?” (0–7 days). To help CHWs to prioritize patient-education needs, we also added 1 question: (3) “Do you understand how to use your glucometer?” (yes/no).
      Items about behaviors that may cause an out-of-range reading and how to respond to certain glucometer readings were obtained from the Michigan Diabetes Knowledge Scale, which is a widely used and validated 23-item instrument.
      • Fitzgerald J.T.
      • Anderson R.M.
      • Funnell M.M.
      • et al.
      The reliability and validity of a brief diabetes knowledge test.
      It is also available in Spanish from the Michigan Diabetes Research Training Center. Although participants completed the entire instrument, in this study, we analyzed 4 specific items that queried knowledge about appropriate responses to glucometer readings that are too high or too low and knowledge of behaviors that may cause an out-of-range reading.
      Questionnaire data were then linked to HbA1c values from intervention participants. Glycemic control (HbA1c) at baseline was obtained from the electronic medical records that were used to determine patients’ eligibility. Poststudy glycemic control was obtained from the exit procedures conducted in the parent study.

      Qualitative Measures

      In addition to survey and glycemic control data described earlier, we collected qualitative data from CHWs who worked with intervention participants. Based on their training and extensive experience working with study patients, we considered the CHWs to be key informants. All CHWs were Hispanic and were considered to be respected peers in their community. Before working with participants, CHWs were trained by the University of Miami’s Diabetes Research Institute to help public health patients to develop disease-management skills. In addition, the Area Health Education Center trained the CHWs to navigate the public health system, overcome barriers to health care access, and obtain social services resources that support optimal health outcomes.
      In February 2012, 3 interviews with CHWs were conducted, audio-recorded, and transcribed. These interviews were conducted as small group sessions in which researchers asked CHWs specific questions about patients participating in the intervention. The goal of these interviews was to better understand specific issues that CHWs perceived as barriers to the success of intervention participants. Approximately 10 open-ended questions were posed during each 90-minute interview. Because a literature review did not yield any relevant tools to assess patient barriers from the CHW’s perspective, the questions used were adopted from multiple previous studies that had identified common challenges experienced by CHWs.
      • Teng L.
      • Robertson Blackmore E.
      • Stewart D.E.
      Healthcare worker′s perceptions of barriers to care by immigrant women with postpartum depression: an exploratory qualitative study.
      • Simmons D.
      • Lillis S.
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      Discordance in perceptions of barriers to diabetes care between patients and primary care and secondary care.
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      • Batts-Turner M.
      • Gary T.L.
      • et al.
      Training community health workers as diabetes educators for urban African Americans: Value added using participatory methods.
      • Cherrington A.
      • Ayala G.X.
      • Amick H.
      • et al.
      Implementing the community health worker model within diabetes management: challenges and lessons learned from programs across the United States.
      • Wilkinson D.
      Tuberculosis and health sector reform: experience of integrating tuberculosis services into the district health system in rural South Africa.
      After the small group interview sessions, researchers followed up with individual CHWs when additional details were needed to clarify the audio-recorded content.

      Data Analysis

      A trained research assistant entered information obtained by the CHWs from the paper forms into the password-protected electronic database (SPSS). Data entry was reviewed for accuracy by another research assistant. We used medians and frequencies to describe the study population, SMBG utilization, and knowledge of behaviors that can cause an out-of-range glucometer reading, as well as how to respond to different glucometer readings. Glycemic control was dichotomized (Table I), and those with HbA1c ≥8% were considered as having poor control. These data were analyzed using IBM SPSS Statistics version 21. To examine whether pre- and poststudy differences in HbA1c and SMBG practice were significant (P ≤ 0.05), paired-sample t tests were conducted.
      Table IBaseline demographic characteristics (N = 117).
      CharacteristicValue
      Age, y
       Mean55.50
       Median55.00
       Range37–68
      Sex, no. (%)
       Male53 (45.30)
       Female64 (54.70)
      Years living with diabetes
       Mean11.46
       Median10.00
      Education, no. (%)
       Less than high school32 (27.35)
       High school level54 (46.15)
       College level or higher31 (26.50)
      HbA1c, no. (%)
       <8%34 (29.06)
       ≥8%83 (70.94)
      HbA1c = hemoglobin A1c.
      Key informant interviews with CHWs were transcribed verbatim and reviewed for accuracy by the researchers who conducted the interviews. The transcripts were then read aloud and coded (labels were assigned to pieces of the transcript that focused on a specific topic, eg, test strips). Researchers’ personal observations about associations were also recorded throughout the coding process. The coded segments were then read and grouped together as themes and subthemes. As consistent with the standards of qualitative research,
      • Saldana J.
      The Coding Manual for Qualitative Research.
      all points of difference in coding results were discussed among researchers until a consensus was achieved.

      Results

      Study Population Characteristics

      The demographic characteristics of the 117 patients at baseline are shown in Table I. Slightly more than half of the sample (54.70%) was female and 73.50% had a high school diploma or higher education. The Hispanic population enrolled into the parent study was very heterogeneous, with 28.00% self-reporting as being Cuban and others coming from a large variety of countries, including Puerto Rico, Mexico, the Dominican Republic, Ecuador, Columbia, Guatemala, Peru, Brazil, Argentina, Venezuela, and Honduras, with none of these other groups representing >10.00% of our sample. Participants received a mean of 8 CHW visits during the 12-month intervention.

      SMBG Behaviors and HbA1c

      Pre- and poststudy SMBG behaviors and HbA1c are shown in Table II. At baseline, nearly all of the patients reported owning a glucometer (95.72%) and knowing how to use it (93.80%). The percentage of the population that reported practicing SMBG ≥6 d/wk increased slightly, and those who practiced SMBG ≤5 d/wk decreased slightly, between baseline and poststudy. There was a significant reduction in HbA1c between the time patients were deemed eligible for the study and the time of their exit interview (P < 0.001).
      Table IISMBG behaviors and HbA1c. Values are % of patient unless otherwise specified.
      ParameterValue
      3-Item Glucometer Questionnaire
       Do you own a glucometer? (yes)95.72
       Do you know how to use it? (yes)93.80
       Days past week did SMBG?
        Prestudy
         0–223.08
         5–Mar13.67
         ≥663.25
        Poststudy
         0–220.41
         5–Mar11.22
         ≥668.37
      HbA1c,
      Significant at P ≤ 0.001.
      mean (SD)
       Prestudy10.04 (1.7)
       Poststudy8.80 (1.9)
      Mar = xxx; SMBG = self-monitoring of blood glucose.
      low asterisk Significant at P ≤ 0.001.

      Knowledge of How to Respond to Out-of-Range Glucose Values (Michigan Diabetes Knowledge Scale)

      Table III shows that at baseline, participants had suboptimal knowledge regarding behaviors that could cause an out-of-range reading and how to respond to a glucometer reading that was too high or too low. For example, just over half knew that a diet soft drink should not be used to treat low blood glucose. Thirty-four percent did not know that high glucose may be caused by low insulin. More than 60% were unaware that heavy exercise could cause an insulin reaction. Although minor improvements were observed, there were no significant differences at poststudy.
      Table IIIKnowledge of how to respond to out-of-range glucometer readings N = 117
      QuestionAnswer Choices% Correct Prestudy% Correct Poststudy
      Which should not be used to treat low blood glucose?3 hard candies; 1/2 cup orange juice; 1 cup diet soft drink; 1 cup skim milk55.65%64.13%
      Low glucose may be caused by:Too much insulin; too little insulin; too much food; too little exercise78.94%79.35%
      High glucose may be caused by:Not enough insulin; skipping meals; delaying your snack; large ketones in your urine66.07%70.65%
      Which of the following will most likely cause an insulin reaction?Heavy exercise; infection; overeating; not taking your insulin38.93%57.61%

      Interviews With CHWs

      Two key themes emerged regarding patients’ glucometer use: lack of knowledge and lack of adequate financial resources. Low glucometer knowledge was reflected in CHW estimates that as many as 75% of participants did not know they needed to calibrate (or code) their glucometer to ensure an accurate reading when they received new test strips. Therefore, many patients had never calibrated their glucometer and did not know how to perform this function. Furthermore, CHWs estimated that most participants did not know how to use advanced glucometer functions (ie, reviewing weekly or monthly logs). Lack of knowledge regarding appropriate actions to take in response to a high or low glucometer reading was also common: “Most of my patients tell me they do nothing when they have a high or low glucometer reading. They just wait for it to pass,” said one CHW.
      The CHWs also discussed how limited financial resources reduced the likelihood of a patient′s obtaining enough test strips to adhere to providers’ recommendations: “Doctors don’t usually prescribe enough strips for patients to test as instructed. And even when they are prescribed enough strips, the public insurance only allows patients to receive a limited number, which is never enough for a full month. So unless they pay out-of-pocket, patients run out of test strips every month,” said another CHW.
      Further reflecting the impact of limited income, CHWs also pointed out that many patients share glucometers with family members.

      Discussion

      Our primary aim was to assess the impact of a CHW intervention on SMBG behaviors and glycemic control in a diverse population of Hispanic patients with poorly controlled diabetes. We found that after 12 months of an intense peer education and support intervention, HbA1c improved, but SMBG behaviors did not. In addition, we identified serious gaps between patients’ self-reports of glucometer proficiency and actual SMBG practices. Furthermore, we found that many patients did not know what behaviors can cause an out-of-range reading or how to respond to a reading that indicates that insulin is too high or too low. We believe this is one of the first articles to describe the effects of a CHW intervention on glucometer use and HbA1c outcomes among a heterogeneous population of Hispanic patients living in the United States. To our knowledge, this is also the first time both survey and qualitative data have been used to evaluate SMBG practices and barriers among Hispanic patients.
      Our findings are consistent with those from previous studies that found CHWs can improve diabetes outcomes among Hispanic populations.

      Centers for Disease Control and Prevention, Division of Diabetes Translation and Division of Adult and Community Health. Community health workers/promotores de salud: critical connections in communities. http://www.cdc.gov/diabetes/projects/comm.htm. Accessed September 3, 2013.

      Although prior research has focused on homogenous Hispanic groups, such as those from Mexico or Costa Rica, those studies also have found that culturally competent diabetes education can improve diabetes management.
      • Firestone D.N.
      • Jiménez-Briceño L.
      • Reimann J.O.
      • et al.
      Predictors of diabetes-specific knowledge and treatment satisfaction among Costa Ricans.
      • Brown S.A.
      • Garcia A.A.
      • Kouzekanani K.
      • Hanis C.L.
      Culturally competent diabetes self-management education for Mexican Americans: The Starr County Border Health Initiative.
      The results of those studies, combined with ours, provides substantial support for CHW interventions addressing diabetes disparities among minority populations.
      The data indicating that many of our participants do not take action in response to an out-of-range glucometer reading are also consistent with previous research. A recent, large-scale survey in type 2 diabetic patients in the United States found that 56% of patients did nothing at all in response to an out-of-range blood glucose reading.
      • Polonsky W.H.
      • Fisher L.
      • Hessler D.
      • Edelman S.V.
      A survey of blood glucose monitoring in patients with type 2 diabetes: are recommendations from health care professionals being followed?.
      Moreover, a substantial number of participants in a recent study from Scotland reported either taking no action or checking their glucose levels at a later time.
      • Evans J.M.
      • Mackison D.
      • Swanson V.
      • et al.
      Self-monitoring among non-insulin treated patients with type 2 diabetes mellitus: patients’ behavioural responses to readings and associations with glycaemic control.
      Similar to our results, those studies also showed a lack of association between glucometer utilization and glycemic control.
      • Evans J.M.
      • Mackison D.
      • Swanson V.
      • et al.
      Self-monitoring among non-insulin treated patients with type 2 diabetes mellitus: patients’ behavioural responses to readings and associations with glycaemic control.
      As other studies have also documented, limited financial resources impeded SMBG behaviors among our participants. Although most of our patients reported glucose monitoring ≥6 d/wk, many physicians recommend that poorly controlled diabetic patients practice SMBG 3 or 4 times per day.
      • Bejamin E.M.
      Self-monitoring of blood glucose: the basics.
      Adhering to these recommendations would require between 90 and 120 test strips per month. The retail cost for 100 test strips is ~$50. This cost is a substantial, well-documented barrier that low-income patients face when the public health system does not provide enough strips.
      • Nyomba B.L.
      • Berard L.
      • Murphy L.J.
      The cost of self-monitoring of blood glucose is an important factor limiting glycemic control in diabetic patients.
      • Adams A.S.
      • Mah C.
      • Soumerai S.B.
      • et al.
      Barriers to self-monitoring of blood glucose among adults with diabetes in an HMO: a cross sectional study.
      Until this barrier is resolved, it is not likely that many patients will practice SMBG as directed.
      Our results add to the growing body of evidence that shows that SMBG behaviors are of little value in achieving improved glycemic control. The extraordinary cost of practicing SMBG
      • Davidson M.B.
      Counterpoint: self-monitoring of blood glucose in type 2 diabetic patients not receiving insulin: a waste of money.
      is widely acknowledged, and many experts believe that these funds could be redirected to more effective therapies.
      • Malanda U.
      • Bot S.
      • Nijpels G.
      Self-monitoring of blood glucose in noninsulin-using type 2 diabetic patients: it is time to face the evidence.
      Given the limited resources available to care for public health patients, it is essential to consider alternative, potentially more efficacious strategies that could be supported if SMBG practices were reconsidered in the United States.
      Our findings have important implications for clinical practice. Approximately $152 billion of federal funds are used to support diabetes care for low-income populations in the United States.

      American Diabetes Association. Economic cost of diabetes in the US in 2012. Diabetes Care. http://www.diabetes.org/advocate/resources/cost-of-diabetes.html. Accessed December 20, 2013.

      A routine part of this care involves providing patients with a glucometer and test strips on an ongoing basis. Given the high proportion of low-income Hispanic patients with poorly controlled diabetes, clinicians caring for this population must identify efficient, cost-effective strategies to improve disease-management skills. Our outcomes suggest that issuing a glucometer and test strips is not likely to lead to improved glycemic control. The American Diabetes Association recommends that all patients with type 2 diabetes complete diabetes self-management education (DSME) at least once after diagnosis.
      • Haas L.
      • Maryniuk M.
      • Beck J.
      • et al.
      National standards for diabetes self-management education and support.
      Our study was limited because we did not assess whether patients completed DSME before enrollment. Therefore, we were unable to determine whether patients who previously completed DSME practiced SMBG more effectively than did those without DSME. Although our study team did not include any American Diabetes Association–endorsed DSME providers, CHWs did implement Su corazón, su vida: Manual del promotor y promotora de salud (Your Heart, Your Life: A Lay Health Educator’s Manual),
      National Heart, Lung and Blood Institute
      Your heart, your life: the promoter and promoter of health manual [in Spanish].
      a culturally relevant cardiovascular disease risk–reduction curriculum, with all intervention participants.
      Su corazón, su vida includes most of the core topics commonly discussed in effective DSME programs and is endorsed for CHW implementation by the National Heart, Lung and Blood Institute. Because the goal of this curriculum is to help CHWs to reduce cardiovascular risk among Hispanic patients with diabetes, this educational program was aligned with the major goal of the parent study, which was to reduce the risk for cardiovascular disease among poorly controlled diabetic patients. Although all participants received this education, our results show that knowledge of appropriate actions to take in response to different glucometer values did not change and that SMBG behaviors remained relatively constant between pre- and poststudy assessments.
      Our study was also limited by the fact that all patients, whether or not they used insulin, were analyzed as 1 group. However, it was not possible to stratify patients based on insulin use because some patients had been prescribed insulin but were nonadherent, and others previously took insulin until they achieved an HbA1c level that no longer warranted medication. During the study, some insulin-naive participants became insulin dependent as a result of improved health care access facilitated by their CHW. Future studies would benefit from eliciting a comprehensive history of insulin use before assessing SMBG utilization.
      This study was also limited by the eligibility criteria of the MHHI parent study, which required patients to have at least 1 laboratory result of HbA1c ≥ 8 during the prior 12 months. Because HbA1c is a general measure of glucose levels for the previous 3 months, it may have been more appropriate to determine eligibility based on more recent HbA1c measures. However, our sample was composed of poorly controlled diabetic patients who did not access health care regularly. Thus, for most patients, it was not feasible to obtain HbA1c values from the previous 3 months. Nonetheless, this limitation may have introduced substantial variation in baseline HbA1c levels.
      Another limitation in our study was that we did not collect the same SMBG-behavior data from the control group and therefore had no way of comparing the effects of intervention with those in an untreated population. Future research on SMBG would benefit from collecting comparison data. We also did not administer an instrument that specifically queried glucometer acceptability and knowledge of appropriate responses to various glucometer readings. Although the Michigan Diabetes Knowledge Scale did include 4 items that reflected some of this knowledge, and although our qualitative data enhanced our understanding of barriers to practicing SMBG, it is possible that our findings would have been more meaningful had we specifically asked participants whether they understood the appropriate action to take based on various glucometer readings.
      Our study is one of the first to use a mixed-methods approach to describe glucometer use and HbA1c outcomes among a diverse group of Hispanic patients who participated in a CHW intervention. Our findings demonstrate that a CHW intervention can improve glycemic control among minority patients with limited health care access. We conclude that it is not necessary for patients to improve SMBG utilization to achieve better HbA1c. Future studies aiming to improve glycemic control among minorities with diabetes may reconsider whether SMBG education should be included. Our results suggest that advocating SMBG practices among patients without the knowledge of how to respond to blood glucose readings or without the resources to obtain enough test strips may not lead to better outcomes. As public health care in the United States is undergoing reform to ensure accessibility for the masses, it is important to consider that in countries where health care is federally funded, the practice of SMBG among patients who do not take insulin is no longer encouraged because it has not been associated with measureable improvements.

      Scottish Intercollegiate Guidelines Network (SIGN). Management of diabetes. A national clinical guideline 116. http://www.sign.ac.uk/pdf/sign116.pdf. Accessed December 23, 2013.

      • Reynolds R.M.
      • Webb D.J.
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      It is estimated that a Hispanic child born today has a 50% lifetime risk for diabetes.
      • Cowie C.C.
      • Rust K.F.
      • Ford E.S.
      • et al.
      Full accounting of diabetes and pre-diabetes in the U.S. population in 1988–1994 and 2005–2006.
      Thus, it is critically important to identify methods that effectively prevent, reduce, and manage diabetes among this rapidly growing population. Data such as these are crucial in developing targeted interventions that use methods known to improve glycemic control and overall diabetes health.

      Conclusions

      SMBG behaviors were not associated with glycemic control in our sample. We conclude that a CHW intervention may improve glycemic control without improving SMBG practices. Future interventions may reconsider whether efforts should be directed toward improving SMBG behaviors.

      Conflicts of Interest

      This study was supported by NIH/NHLBI award no. R01 HL083857. The authors have indicated that they have no conflicts of interest with regard to the content of this article.

      Acknowledgments

      The authors extend their deepest gratitude to Dr. Olveen Carrasquillo, who provided support and guidance in the preparation of the manuscript. This study was supported by an award from NIH/NHLBI R01 HL083857.
      Dr. Kenya was responsible for the study design, writing, and data interpretation. Dr. Lebron contributed to the data collection, literature reviews, writing, and data interpretation. Dr. Reyes-Arrechea assisted with the data collection, literature reviews, figure creation, and data interpretation. Dr. Li provided statistical analysis guidance and data interpretation.

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