Impacting diabetes self-management in women with gestational diabetes mellitus using short messaging reminders

Quinetta B. Johnson, MD, MPH (Maternal Fetal Medicine Fellow) & Diane C. Berry, PhD, ANP-BC, FAANP, FAAN (Professor)

Journal of the American Association of Nurse Practitioners


Abstract

Background and purpose: Gestational diabetes mellitus (GDM) has been associated with multiple complications, including increase risk of gestational hypertension, cesarean delivery, macrosomia, stillbirth, and preeclampsia. The purpose of this study was to determine the acceptability of text messaging in women with GDM and further refine intervention materials and study procedures (recruitment, enrollment, intervention, retention, and data collection).

Methods: Nineteen women diagnosed with GDM completed a baseline demographic questionnaire followed by 4 weeks of daily text messages that included either a direct reminder to test their blood glucose levels and keep up with their treatment plan or an educational message. A postintervention survey was administered to assess the satisfaction with the messaging program.

Conclusion: The use of daily text messages in the treatment plan of patients diagnosed with GDM seems to be acceptable shown by an overall satisfaction with the messages and a willingness to use the messages in future pregnancies. Half of the participants also felt that the messages helped them to eat healthier.

Implications for practice: This study demonstrated a real opportunity for a low-cost intervention in the management plan of GDM.


Introduction

Diabetes is one of the most common medical complications in pregnancy. It has been estimated that 6–7% of pregnancies are complicated by diabetes, and 90% of those cases are gestational diabetes mellitus (GDM) (Bulletins–Obstetrics, 2013). Gestational diabetes mellitus has been defined as the new onset of glucose intolerance during pregnancy (Bulletins–Obstetrics, 2013). However, due to the increased prevalence of obesity and Type 2 diabetes in women of childbearing age, the American Diabetes Association defines diabetes diagnosed in the first trimester as Type 2 diabetes, and GDM consists of those women diagnosed with diabetes in the second and third trimesters (AssociationA. D, 2015 Prevention C. f. D. C. a, 2015). Gestational diabetes mellitus has been associated with multiple fetal and maternal complications, such as increased risk of gestational hypertension, cesarean delivery, macrosomia, stillbirth, and preeclampsia (Metzger et al., 2008 ;Yogev, Xenakis, & Langer, 2004). Gestational diabetes mellitus also has been shown to increase the risk of women developing Type 2 diabetes in the decades following the incident pregnancy(England et al., 2009 Lee, Hiscock, Wein, Walker, & Permezel, 2007). There have been several randomized control trials that have shown a reduction in obstetrical and fetal complications when GDM is treated, and tight glycemic control is achieved (Crowther et al., 2005 Landon et al., 2009 Mackillop et al., 2014).

Patient adherence is an essential factor affecting GDM management. Once diagnosed with GDM, women must take multiple daily capillary blood glucose measurements, go to frequent clinic appointments, maintain proper gestational weight gain based on their body mass index, and undergo tight glycemic control via diet, exercise, and potentially undergo medical management (Coustan & American Diabetes Association., 2013). Treatment plan adherence is particularly imperative in pregnant women with GDM because of the significant complications that can occur regarding maternal and fetal health. A patient's adherence to a treatment plan is multifactorial, requiring proper education, self-discipline and self-management, and good interactions between patients and providers (Fioravanti, Fico, Salvi, García-Betances, & Arredondo, 2015). Each of these components is a potential area in which appropriate intervention can potentially improve adherence.

Patient empowerment has become a widely recognized approach to patients with diabetes (Funnell et al., 1991 Tang, Funnell, Brown, & Kurlander, 2010). This method is based on the fact that diabetes is a patient-managed disease where they make the final decision regarding their daily self-management and that the patient–provider relationship should be collaborative with the provider's central role being one of support. The use of daily educational text/short message service (SMS) messaging to improve adherence via improved education, self-management, and empowerment may be a cost-effective way to reduce the numerous complications associated with GDM. In the United States, 85% of all adults have cell phones, and 72% of cell phone owners send and receive text/SMS messages (Zickuhr, 2011). Among 18- to 34-year-old women (the group most likely to be childbearing), 95% own a cell phone and 94% send and receive text/SMS messages (Zickuhr, 2011). Previous studies have shown that the use of text/SMS messaging in the treatment of diabetes outside of pregnancy has resulted in clinical improvements with lower glycated hemoglobin (A1c) values (Saffari, Ghanizadeh, & Koenig, 2014). However, there is very limited information regarding the use of text/SMS messaging in the treatment plan of pregnant women with diabetes. With proper messaging and reminders, text messages may be a way to positively affect patients' adherence by improving self-management and fostering healthy interactions between patients and caregivers. However, before we can assess this relationship, we must first know if patients will use this form of communication in this setting.

Materials and methods

This feasibility study was conducted to determine the acceptability of text messaging usage in women with GDM and further refine intervention materials and study procedures (recruitment, enrollment, intervention, retention, and data collection). We recruited women older than 18 years receiving prenatal care at the University of North Carolina Women's Primary Health and Women's Subspecialty clinics. Women were eligible for participation if they were diagnosed with GDM by 2 or more 100-g oral glucose tolerance test values exceeding established thresholds (fasting: 95 mg/dL, 1 hour: 180 mg/dL, 2 hours: 155 mg/dL, 3 hours: 140 mg/dL), owned a cell phone with text messaging functionality, and had the ability to read and write English. Recruitment took place from November 2015 to April 2016.

Women who are diagnosed with GDM in these clinics received diabetes education from a registered nurse and diet counseling from a registered dietitian. Weekly meetings between study personnel and the registered nurse responsible for facilitating the diabetes education at the clinics were done to identify those women who had recently been diagnosed with GDM. Study staff enrolled all participants, who provided written consent, and agreed to complete a baseline questionnaire and a postintervention questionnaire after 4 weeks of receiving the intervention. After completion of the postintervention questionnaire, the participants received a $20 Target gift card. The protocol for this study was approved by the University of North Carolina.

Twenty-seven women were enrolled into the study. Three of these women never signed up for electronic medical record (EPIC) MyChart to receive the survey links, three others received the links but never completed the surveys, and two delivered before completing the initial demographic information. The remaining participants (N = 19) received routine prenatal care, including diabetes teaching and dietician counseling along with the text message intervention. Each participant was informed that all medical questions should be directed to their obstetrician.

Questionnaires

The subjects were asked to complete a 14-item baseline survey consisting of demographic data and questions concerning their current knowledge regarding diabetes and if they had any other comorbidities. The survey was sent to the participants via EPIC MyChart after they were consented to participate in the study.

The postintervention questionnaire link was also sent to the participants via EPIC MyChart after they received all the messages. This survey was used to assess the participant's satisfaction with the messaging program and included questions, such as how many of the messages they read, if they found the messages helpful, and feedback as to how to improve the intervention. Many of the questions on the postintervention survey used a Likert-type scale to assess the participants' agreement with the statements. The options given to these questions were “strongly disagree,” “disagree,” “neither agree nor disagree,” “agree,” and “strongly agree.” Both questionnaires were completed in Qualtrics, and this software was used to complete the statistical analysis.

Intervention

The participants received a total of 30 text messages that included a welcome message, a daily message as either a direct reminder to test their blood glucose levels and keep up with their treatment plan or an educational message and a final message. The educational messages included four areas: blood glucose goals, healthy eating, medication adherence, and exercise. The messages did not refer to the participants by name to maintain confidentiality. The messages were sent through EZ Texting, and each message contained 160 characters or less. The start date for the text messages was within 48 hours of each participant's enrollment.

Results

In general, the sample was educated with a total of 84.2% having greater than a high school education to include 31.6% who completed some college or obtained an associate's degree, 21.1% who completed a bachelor's degree program, and 31.6% who completed graduate or professional school (Table 1). The majority of patients were non-Hispanic White (47.4%) and married (79.0%). A total of 63.2% had medical comorbidities, including depression, hypertension, gastroesophageal reflux, ulcerative colitis, anemia, asthma, seasonal allergies, and hypothyroidism. Before starting the text messaging intervention, nine (47.4%) of the 19 participants felt that they had “good” knowledge regarding diabetes.

 

A total of 18 of 19 participants answered questions on the postintervention survey to assess if the messages helped them to eat healthier, become more active, and remember to check their blood glucose levels and take their medications if needed (Table 2). Over half (66.7%) felt that the messages helped them to remember to check their blood glucose levels. Half of these participants felt that the messages helped them to eat healthier and 38.9% could not agree or disagree with this statement. Seven of the 18 participants felt that the messages helped them to be active. Approximately, one third (33.3%) of these women did not require medication, but of those who did, 66.7% agreed or strongly agreed that the messages helped them to remember 

The majority of all participants (63.2%) agreed or strongly agreed that they would use the messages in future pregnancies if diagnosed with GDM, and 78.9% agreed or strongly agreed that they would recommend the text messaging program to a friend with diabetes in pregnancy. Fifteen (79.0%) women felt that the number of daily messages were “just right.” Over half (52.6%) of participants liked the educational messages, whereas 42.1% liked direct reminders regarding medications and blood glucose checks. Nine participants marked that there was nothing that they disliked regarding the messages; however; five marked that they disliked the lack of personal interaction. A total of 18 (94.7%) participants marked that they read all the messages and 1 (5.3%) marked that they read most of them. In total, 68.4% of participants marked that the messages “fit ok” with their personal treatment plan.

In an attempt to understand ways in which we can improve upon the messages for future studies and clinical usage, the participants were asked to give suggestions to improve messages. First, a couple of participants expressed a desire for more specific information regarding diet and asked in the future “be more specific with diet and activity advice and provide more info on healthy snacks.” Another issue raised was the timing of the messages and included suggestions such as “messages were sent too early in the morning” and “messages would be better timed if they came about 30–45 minutes before a meal.

Discussion

Diabetes is a patient-managed disease, which means that the patient must understand their diagnosis and have buy-in that the benefits of adhering to their treatment plan outweigh opposing factors. The empowerment of patients to make this decision is a widely recognized approach to diabetes management (Funnell et al., 1991 Tang et al., 2010). Gestational diabetes mellitusis an opportune time to encourage women to improve glucose control to improve both maternal and fetal outcomes. Text messaging has been shown to promote improvement in preventive health beliefs and behaviors in pregnancy (Moniz, Meyn, & Beigi, 2015).

This study was unique in that we attempted to understand the acceptability and feasibility of a text messaging intervention in the treatment plan of those diagnosed with GDM. Participants enrolled in the program reported overall satisfaction with the messages, and an overwhelming percentage of participants (63.2%) were willing to use the messages again in future pregnancies complicated by GDM. It was also encouraging that a majority of the women would recommend the program to a friend. Readership of the messages was high, with 94.7% stating they read all the messages.

As previously mentioned, diabetes is a patient-managed disease in which they make the final decision regarding their daily self-management. Participants who used an internet-based telemedicine system in the management of GDM had a significantly higher perception of their ability to bring about changes in their own behavior, as well as the behavior of others to improve their diabetes self-management and psychosocial adaptation to the disease when compared with control subjects (Homko et al., 2007). Previous studies have also shown that the utilization of technology as a means of communication between patients and health care providers reduce medical cost and saves time for both the patient and the clinician (Perez-Ferre et al., 2010).

There is conflicting data regarding the efficacy of technological communication's impact on glucose control. Dalfra, Nicolucci, & Lapolla, 2009 were able to show a benefit in the use of telemedicine and remote submission of glucose values to health care providers (Dalfra et al., 2009). The intervention group in this randomized control trial had better glucose control, lower rates of cesarean delivery and macrosomia, and lower frustration regarding the diagnosis of GDM (Dalfra et al., 2009). However, there have been other studies that show no significant difference in maternal blood glucose values between participants who use such technology and those who do not (Homko et al., 2007 Homko et al., 2012). Therefore, next steps will be to fine-tune and tailor the intervention to better fit the needs of the women and conduct a randomized controlled pilot study in women with GDM. It is imperative that our future study regarding this technology incorporate changes that take into account the suggestions given by the patients in this feasibility study. A program that allows the patient to determine a time frame in which the messages are received is vital for participant satisfaction. It is also vital to determine if this technology not only improves maternal satisfaction but also if it improves maternal and fetal outcomes (Chilelli, Dalfra, & Lapolla, 2014). In the future, if this strategy is efficacious and effective, we may be able to create a system that saves time for patients with GDM by communicating their blood glucose levels to their provider for assistance in medication, dietary, and physical activity titration to improve their glycemic control.

Nurse practitioners and other providers are in a unique position to improve population health management within their practice using technology to provide their patients with helpful information to manage their GDM. Nurse practitioners can provide cost-effective care, help women manage transitions in their lives, provide high-quality care, and improve clinical outcomes to reduce health care costs overall.

This study has revealed a real opportunity for a low-cost intervention in the management plan of a significant and complex disease process. We have shown participants' engagement, satisfaction, and interest in text messages being incorporated in their personal treatment plans for GDM. Next steps include a randomized controlled repeated-measures pilot study to assess if the intervention improves blood glucose levels and obstetrical outcomes, such as birth weight, mode of delivery, cesarean section, macrosomia, and stillbirth statistics. The intervention group will receive tailored text messaging focused on diabetes self-management, and the control group will receive text messages on general pregnancy care. We will include more women from ethnically diverse backgrounds and low-income socioeconomic status. We will measure blood glucose levels and diabetes self-management. At the completion of the pilot study, we will conduct exit interviews with the women in the intervention group to assess what the women liked or disliked about the intervention and text messages and ask for their suggestions on improving the intervention. After completion of the randomized controlled pilot study, we will calculate effect sizes to power a multisite randomized controlled study most likely partnering with the Maternal-Fetal Medicine Units Network with whom the authors currently collaborate with.

Limitations

There are some limitations to consider in interpreting our results. This study was designed as a feasibility study with a small sample size. Therefore, our results are not generalizable and require further investigation. Another limitation of this study is that although we were able to establish that the messages were acceptable to participants, clinical improvements such as improved capillary blood glucose values were not assessed.

Conclusion

In conclusion, the results of this pilot study showed that the text messages were acceptable and feasible in women with GDM. In addition, there was a high level of satisfaction with participants being agreeable to receive the messages in future pregnancies complicated by GDM and their willingness to recommend the messages to friends with GDM. Nurse practitioners and other health care providers caring for patients diagnosed with GDM are in a unique position to help women improve their blood glucose levels through the use of technology, which may be more acceptable to these women. The ultimate impact of improved glucose levels will improve fetal and infant outcomes in women with GDM.


References

Association, A. D. (2015). (2) Classification and diagnosis of diabetes. Diabetes Care, (38 Suppl), S8–S16. doi:10.2337/dc15-S005.

Bulletins–Obstetrics, C. o. P. (2013). Practice Bulletin No. 137: Gestational diabetes mellitus. Obstetrics and Gynecology, 122(2 Pt 1), 406–416.

Chilelli N. C., Dalfra M. G., Lapolla A. (2014). The emerging role of telemedicine in managing glycemic control and psychobehavioral aspects of pregnancy complicated by diabetes. International Journal of Telemedicine and Applications, 2014, 621384.

Coustan D. R., & American Diabetes Association. (2013). Medical management of pregnancycomplicated by diabetes. Online resource pp. 1–307. Retrieved from http://libproxy.lib.unc.edu/login?url=http://www.UNC.eblib.com/EBLWeb/patron/?target=patron&extendedid=P_1222227_0.

Crowther C. A., Hiller J. E., Moss J. R., McPhee A. J., Jeffries W. S., Robinson J. S., & Group, A. C. I. S. i. P. W. A. T. (2005). Effect of treatment of gestational diabetes mellitus on pregnancy outcomes. The New England Journal of Medicine, 352, 2477–2486.

Dalfra M. G., Nicolucci A., Lapolla A. (2009). The effect of telemedicine on outcome and quality of life in pregnant women with diabetes. Journal of Telemedicine and Telecare, 15, 238–242.

England L. J., Dietz P. M., Njoroge T., Callaghan W. M., Bruce C., Buus R. M., Williamson DF. (2009). Preventing type 2 diabetes: Public health implications for women with a history of gestational diabetes mellitus. American Journal of Obstetrics and Gynecology, 200, 365.e361–368.e361.

Fioravanti A., Fico G., Salvi D., García-Betances R. I., Arredondo M. T. (2015). Automatic messaging for improving patients engagement in diabetes management: An exploratory study. Medical & Biological Engineering & Computing, 53, 1285–1294.

Funnell M. M., Anderson R. M., Arnold M. S., Barr P. A., Donnelly M., Johnson P. D., White N. H. (1991). Empowerment: An idea whose time has come in diabetes education. The Diabetes Educator, 17, 37–41.

Homko C. J., Deeb L. C., Rohrbacher K., Mulla W., Mastrogiannis D., Gaughan J., Bove A. A. (2012). Impact of a telemedicine system with automated reminders on outcomes in women with gestational diabetes mellitus. Diabetes Technology & Therapeutics, 14, 624–629.​​​​​​​

Homko C. J., Santamore W. P., Whiteman V., Bower M., Berger P., Geifman-Holtzman O., Bove AA. (2007). Use of an internet-based telemedicine system to manage underserved women with gestational diabetes mellitus. Diabetes Technology & Therapeutics, 9, 297–306.​​​​​​​

Landon M. B., Spong C. Y., Thom E., Carpenter M. W., Ramin S. M., Casey B.,… Network, E. K. S. N. I. o. C. H. a. H. D. M.-F. M. U. (2009). A multicenter, randomized trial of treatment for mild gestational diabetes. The New England Journal of Medicine, 361, 1339–1348.​​​​​​​

Lee A. J., Hiscock R. J., Wein P., Walker S. P., Permezel M. (2007). Gestational diabetes mellitus: Clinical predictors and long-term risk of developing type 2 diabetes: A retrospective cohort study using survival analysis. Diabetes Care, 30, 878–883.​​​​​​​

Mackillop L., Loerup L., Bartlett K., Farmer A., Gibson O. J., Hirst J. E., Tarassenko L. (2014). Development of a real-time smartphone solution for the management of women with or at high risk of gestational diabetes. Journal of Diabetes Science and Technology, 8, 1105–1114.

Metzger B. E., Lowe L. P., Dyer A. R., Trimble E. R., Chaovarindr U., Coustan D. R.,… Group, H. S. C. R. (2008). Hyperglycemia and adverse pregnancy outcomes. The New England Journal of Medicine, 358, 1991–2002.

​​​​​​​Moniz M. H., Meyn L. A., Beigi R. H. (2015). Text messaging to improve preventive health attitudes and behaviors during pregnancy: A prospective cohort analysis. The Journal of Reproductive Medicine, 60, 378–382.​​​​

Perez-Ferre N., Galindo M., Fernandez M. D., Velasco V., de la Cruz M. J., Martin P., Calle-Pascual A. L. (2010). A Telemedicine system based on Internet and short message service as a new approach in the follow-up of patients with gestational diabetes. Diabetes Research and Clinical Practice, 87, e15–e17.​​​​​​​

Prevention, C. f. D. C. a. (2015). Adult Obesity Facts. Available from Centers for Disease Control and Prevention Division of Nutrition, Physical Activity, and Obesity Retrieved May 24, 2016, from Centers for Disease Control and Prevention. Division of Nutrition, Physical Activity, and Obesity. http://www.cdc.gov/obesity/data/adult.html.

Saffari M., Ghanizadeh G., Koenig H. G. (2014). Health education via mobile text messaging for glycemic control in adults with type 2 diabetes: A systematic review and meta-analysis. Primary Care Diabetes, 8, 275–285.​​​​​​​

Tang T. S., Funnell M. M., Brown M. B., Kurlander J. E. (2010). Self-management support in “real-world” settings: An empowerment-based intervention. Patient Education and Counseling, 79, 178–184.​​​​​​​

Yogev Y., Xenakis E. M., Langer O. (2004). The association between preeclampsia and the severity of gestational diabetes: The impact of glycemic control. American Journal of Obstetrics and Gynecology, 191, 1655–1660.​​​​​​​

Zickuhr K. (2011). Generations and their gadgets. Retrieved from Pew Research Center Internet Science Tech RSS website: http://www.pewinternet.org/2011/02/03/generations-and-their-gadgets/

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