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Using Digital Health Technology to Prevent and Treat Diabetes

2019; Mary Ann Liebert, Inc.; Volume: 21; Issue: S1 Linguagem: Inglês

10.1089/dia.2019.2506

1557-8593

Neal Kaufman, Courtney Ferrin, Darinne Sugrue,

Medication Adherence and Compliance

Diabetes Technology & TherapeuticsVol. 21, No. S1 Original ArticlesFree AccessUsing Digital Health Technology to Prevent and Treat DiabetesNeal Kaufman, Courtney Ferrin, and Darinne SugrueNeal KaufmanFielding School of Public Health, Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CACanary Health, Inc, Los Angeles, CASearch for more papers by this author, Courtney FerrinLoyola Marymount University, Los Angeles, CASearch for more papers by this author, and Darinne SugrueCanary Health, Inc, Los Angeles, CASearch for more papers by this authorPublished Online:20 Feb 2019https://doi.org/10.1089/dia.2019.2506AboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail IntroductionThis article is our annual attempt to highlight the digital approaches successfully being used to improve outcomes for patients with, or at risk for, diabetes. In the past few years a new classification for these efforts has emerged, called digital therapeutics—products that use digital technology to prevent and treat medical conditions.Digital therapeutics can be divided into three types:Digital services aim to modify patient behaviors to improve health outcomes. Ideally, these digital therapeutics use evidence-based approaches and publish studies that show the specific therapeutic can help drive important clinical and economic outcomes.Adjunctive digital therapeutics support the use of traditional therapies such as medications, devices, and monitors. These therapeutics can assist in improving clinical outcomes, but they do so indirectly by enhancing the effectiveness of the traditional therapeutics and typically stop short of claiming an independent therapeutic benefit.Digital drug replacements seek to provide a clinical benefit through the digital technology itself as a replacement for a traditional treatment, and not through any other source. Because of this, digital drug replacements usually require significant scrutiny by way of clinical trial results and review by the Food and Drug Administration before they can be reimbursed in a fee-for-service health-care environment.Of course, these categories are not set in stone. There are already hybrid digital therapeutics in which traditional therapeutics are coupled with an evidence-based digital service to create a new prevention and treatment paradigm.It is hoped these various approaches will be proven to be impactful and will be able to create business models that allow for sustaining their impact at scale.Key Articles Reviewed for the ArticleEvaluation of a diabetes self-management program: claims analysis on comorbid illnesses, health care utilization, and costTurner R, Ma Q, Lorig K, Greenberg J, DeVries AJMed Internet Res 2018;20: e207Mobile Diabetes Intervention Study (MDIS) of patient engagement and impact on blood glucoseQuinn CC, Butler EC, Swasey KK, Shardell MD, Terrin MD, Barr EA, Gruber-Baldini ALJMIR Mhealth Uhealth 2018;6: e31Digital diabetes management application improves glycemic outcomes in people with type 1 and type 2 diabetesOffringa R, Sheng T, Parks L, Clements M, Kerr D, Greenfield MSJ Diabetes Sci Technol 2018;12: 701–708Web-based self-management support for people with type 2 diabetes (HeLPDiabetes) randomised controlled trial in English primary careMurray E, Sweeting M, Dack C, Pal K, Modrow K, Hudda M, Li J, Ross J, Alkhaldi G, Barnard M, Farmer A, Michie S, Yardley L, May C, Parrott S, Stevenson F, Knox M, Patterson DBMJ Open 2017;7: e016009Cost-effectiveness of facilitated access to a self-management websiteLi J, Parrott S, Sweeting M, Farmer A, Ross J, Dack C, Pal K, Yardley L, Barnard M, Hudda M, Alkhaldi G, Murray EJ Med Internet Res 2018;20: e201Comparing the efficacy of a mobile phone-based blood glucose management system with standard clinic care in women with gestational diabetes: randomized controlled trialMackillop L, Hirst JE, Bartlett KJ, Birks JS, Clifton L, Farmer AJ, Gibson O, Kenworthy Y, Levy JC, Loerup L, Rivero-Arias O, Ming WK, Velardo C, Tarassenko LJMIR Mhealth Uhealth 2018;6: e71Use of a connected glucose meter and certified diabetes educator coaching to decrease the likelihood of abnormal blood glucose excursions: The Livongo for Diabetes ProgramDowning J, Bollyky J, Schneider JJ Med Internet Res 2017;19: e234One Drop | Mobile: an evaluation of hemoglobin A1c improvement linked to app engagementOsborn CY, van Ginkel JR, Rodbard D, Heyman M, Marrero DG, Huddleston B, Dachis JJMIR Diabetes 2017;2: e21The impact of a mobile diabetes health intervention on diabetes distress and depression among adults: secondary analysis of a cluster randomized controlled trialQuinn C, Swasey K, Christopher J, Crabbe F, Shardell M, Terrin M, Barr E, Gruber-Baldini AJMIR Mhealth Uhealth 2017;5: e183Effectiveness of text message based, diabetes self-management support programme (SMS4BG)Dobson R, Whittaker R, Jiang Y, Maddison R, Shepherd M, McNamara C, Cutfield R, Khanolkar M, Murphy RBMJ 2018;361: k1959Testing a smartphone app (Young with Diabetes) to improve self-management of diabetes over 12 months: randomized controlled trialCastensøe-Seidenfaden P, Husted GR, Jensen AK, Hommel E, Olsen B, Pedersen-Bjergaard U, Kensing F, Teilmann GJMIR Mhealth Uhealth 2018;6: e141A systematic review of reviews evaluating technology-enabled diabetes self-management education and supportGreenwood DA, Gee PM, Fatkin KJ, Peeples MJ Diabetes Sci Technol 2017;11: 1015–1027Engagement and outcomes in a digital Diabetes Prevention Program: 3-year updateSepah SC, Jiang L, Ellis RJ, McDermott K, Peters ALBMJ Open Diab Res Care 2017;5: e000422A fully automated conversational artificial intelligence for weight loss: longitudinal observational study among overweight and obese adultsStein N, Brooks KJMIR Diabetes 2017;2: e28Peer-based social media features in behavior change interventions systematic reviewElaheebocus SMRA, Weal M, Morrison L, Yardley LJ Med Internet Res 2018;20: e20The use of Facebook in recruiting participants for health research purposes: a systematic reviewWhitaker C, Stevelink S, Fear NJ Med Internet Res 2017;19: e290Serious games for children with chronic diseases: a systematic reviewHoltz BE, Murray K, Park TGames Health J 2018;7: 291–301A team-based online game improves blood glucose control in veterans with type 2 diabetes: a randomized controlled trialKerfoot BP, Gagnon DR, McMahon GT, Orlander JD, Kurgansky KE, Conlin PRDiabetes Care 2017;40: 1218–1225"Active Team" a social and gamified app-based physical activity intervention: randomised controlled trial study protocolEdney S, Plotnikoff R, Vandelanotte C, Olds T, De Bourdeaudhuij I, Ryan J, Maher CBMC Public Health 2017;17: 859Evaluation of a diabetes self-management program: claims analysis on comorbid illnesses, health care utilization, and costTurner R1, Ma Q1, Lorig K2, Greenberg J3, DeVries A11HealthCore, Inc, Wilmington, DE; 2Stanford Patient Education Research Center, Palo Alto, CA; 3National Council on Aging Services, Arlington, VAJ Med Internet Res 2018;20: e207BackgroundDiabetes mellitus is a widespread disease, with an estimated 30.3 million Americans currently living with the disease. The U.S. Department of Health and Human Services laid out national goals through its Healthy People 2020 initiative to enhance the quality of life for individuals who either have or are in jeopardy of developing diabetes mellitus and consequently lower the individual and national economic cost of this chronic disease. Diabetes self-management educational interventions are an essential focal point of this national initiative. The goal of this investigation was to assess the effect of the Better Choices, Better Health – Diabetes (BCBH-D) self-management program on comorbid diseases associated with diabetes mellitus, health-care utilization, and cost.MethodsThis study employed a propensity score matched two-group, pre–post design. Retrospective administrative medical and pharmacy claims data from the HealthCore Integrated Research Environment were used for outcome variables. The intervention group consisted of patients with type 2 diabetes mellitus who were recruited to a diabetes self-management program, while the control group included subjects selected from the HealthCore Integrated Research Environment who had at least two diabetes-related claims (International Classification of Diseases-Ninth Revision, ICD-9 250.xx) within 2 years before October 1, 2011 (the program launch date) but did not participate in BCBH-D. Participants in the control group were matched to cases in a 3:1 propensity score match. Outcome measures included pre- and postintervention all-cause and diabetes-related usage and costs. Cost outcomes were calculated as least-squares means. Repeated measures analyses (generalized estimating equation approach) were conducted for utilization, comorbid conditions, and costs.ResultsProgram users who were identified in HealthCore Integrated Research Environment claims (n=558) were paired to a control group of 1669 participants. After the intervention, the self-management group experienced significant decreases in diabetes mellitus–related comorbid conditions, with a significantly lower postintervention disease burden (mean 1.6 [SD 1.6]) vs the control group (mean 2.1 [SD 1.7]; P=0.001). There was less postintervention all-cause use of medical services in the intervention group than in the control group, with −40/1000 emergency department visits vs +70/1000 (P=0.004) and −5780 outpatient visits per 1000 vs −290/1000 (P=0.001). There was a reduction of U.S. $2207 in unadjusted aggregate all-cause medical cost in the intervention group, vs a reduction of U.S. $338 in the control group (P=0.001). After using structural equation analysis to adjust for other variables, the direct impact of the BCBH-D was determined to be −$815 (P=0.049).ConclusionsBCBH-D program patients experienced a decrease in all-cause health-care usage and expenses, with direct monetary savings of U.S. $815. Given the complicated nature of the diabetic patient population, further studies are required to cross-validate the results.CommentNote: Because two of the authors own (N.K.) or work (N.K., D.S.) for a company that markets the digital therapeutic used in this study, a conflict of interest exists and we have therefore refrained from adding any comments for this article.Mobile Diabetes Intervention Study (MDIS) of patient engagement and impact on blood glucoseQuinn CC1, Butler EC2, Swasey KK1, Shardell MD3, Terrin MD1, Barr EA1, Gruber-Baldini AL11Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD; 2Department of Emergency Medicine, Wellspan York Hospital, York, PA; 3National Institute on Aging, Baltimore, MDJMIR Mhealth Uhealth 2018;6: e31BackgroundSuccessfully treating diabetes includes patient self-management behaviors focused on preventing or delaying complications and comorbid diseases. Based on results from large clinical trials and professional guidelines, diabetes education programs and health providers prescribe daily regimens of glucose monitoring, healthy eating, stress management, medication compliance, and physical activity. Staying consistently committed to these regimens long term is difficult. The use of mobile health to assist patients with lifestyle changes and self-management behaviors is on the rise. The effectiveness of mobile health in improving diabetes outcomes is dependent on patients engaging with the technology, learning its content, and effectively interacting with providers. The goal of this study was to find patient engagement themes in diabetes messaging with care providers and to determine whether differences in engagement in the Mobile Diabetes Intervention Study (MDIS) caused changes in glycated hemoglobin A1c (HbA1c) levels during the course of a 1-year treatment period (1.9% decrease in the parent study).MethodsIn the primary MDIS study, 163 patients were assigned to one of three mobile intervention groups or to a routine care control group based on the cluster randomization assignment of their physicians. The control cohort had no changes from their regular care routine. Participants in all intervention groups received access to a patient portal where they could record their blood glucose levels, prescription changes, self-management data, and blood pressure. Depending on group assignment, participants received differing levels of physician access to patient information. Participants in the intervention group could decide to interact with certified diabetes educators by sending as well as receiving messages through the secure online interface. In this secondary analysis, 4109 patient messages were evaluated using qualitive techniques to identify self-care trends and determine participant engagement. Mixed methods were utilized to find the effect of patient engagement on change in HbA1c over the course of 1 year.ResultsThe self-care behavior themes that elicited the highest participant engagement were glucose monitoring (75/107, 70.1%), medication management (71/107, 66.4%), and risk reduction (71/107, 66.4%). The mean number of messages sent per patient was greatest for glucose monitoring (9.2 [SD 14.0]) and healthy eating (6.9 [SD 13.2]). In comparison with sending no messages, sending any messages regarding glucose monitoring (P=0.03) or medication (P=0.01) was associated with a decrease in HbA1c of 0.62% and 0.72%, respectively. Sending any messages about healthy eating, glucose monitoring, or medication combined resulted in HbA1c falling by 0.54% vs sending no messages related to these themes (P=0.045).ConclusionsThis study helps validate the feasibility of diabetes interventions through mobile platforms. Future studies should work to identify the differences between patients who use mobile interventions and those who do not and to identify customized strategies to increase patient engagement.CommentsThis digital therapeutic study adds to the growing body of literature demonstrating the elements of interventions that tend to work. Interpretation of these findings is limited due to the comparison of not performing a specific activity with performing some or a lot of that activity. A behavior such as sending a message is a relatively small action. The power of small actions may only be seen when done many times. To demonstrate such an effect requires analysis of a continuous variable and not an all-or-nothing finding. It is hoped that subsequent studies are powered to allow further understanding of this critical issue.Digital diabetes management application improves glycemic outcomes in people with type 1 and type 2 diabetesOffringa R1, Sheng T1, Parks L1, Clements M1,2, Kerr D1,3, Greenfield MS11Glooko Inc., Mountain View, CA; 2Children's Mercy Hospital, Kansas City, MO; 3William Sansum Diabetes Center, Santa Barbara, CAJ Diabetes Sci Technol 2018;12: 701–708BackgroundDiabetes is a chronic condition that requires constant self-management. In response, myriad platforms have been created to encourage keeping track of diabetes data with the goal of improving diabetes management. This study examined the real-world advantages of using a mobile diabetes management service by people with type 1 and type 2 diabetes.MethodsA cohort of mobile service users (n=899) and a control cohort (n=900) were formed by randomly assigning participants from a database of diabetes users. Outcomes were modeled utilizing different blended effect generalized linear models, assigning random intercepts for each participant, and modifying the distribution assumption for each result.ResultsParticipants using the mobile platform monitored their blood glucose at an increased frequency (+8.8 tests per month [95% confidence interval 3.4, 14.1], P<0.001) and experienced fewer hyperglycemic events along with lower average glucose levels vs the control group. Additionally, mobile user could anticipate a 3.5% reduction in average blood glucose (−6.4 mg/dL [95% CI −2.0, −10.7], P<0.001) and a 10.7% reduction in hyperglycemia (P<0.001) after 2 months.ConclusionParticipants using the mobile platform tested their blood glucose more frequently and demonstrated greater improvement in blood glucose compared with participants in the control group, who did not use the mobile platform. These results support previous study findings that digital technologies can enhance diabetes care in a real-world setting.CommentsThis study demonstrated that when patients are able to see their blood glucose levels on a mobile phone, they respond to the results and improve their glucose control. The relatively modest improvement can be expected. Patients need more than just easily accessible blood glucose levels to improve their outcomes.Web-based self-management support for people with type 2 diabetes (HeLPDiabetes) randomised controlled trial in English primary careMurray E1, Sweeting M2, Dack C3, Pal K1, Modrow K1, Hudda M4, Li J5, Ross J1, Alkhaldi G1, Barnard M6, Farmer A7, Michie S8, Yardley L7,9, May C10, Parrott S5, Stevenson F1, Knox M1, Patterson D61Research Department of Primary Care and Population Health, University College London, London, UK; 2Department of Public Health and Primary Care, Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK; 3Department of Psychology, University of Bath, Bath, UK; 4Population Health Research Institute, St George's, University of London, London, UK; 5Department of Health Sciences, University of York, York, UK; 6Whittington Health, London, UK; 7Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK; 8Department of Clinical, Educational and Health Psychology, Centre for Behaviour Change, University College London, London, UK; 9Department of Psychology, University of Southampton, Southampton, UK; 10Faculty of Health Sciences, University of Southampton, Southampton, UKBMJ Open 2017;7: e016009BackgroundThe purpose of this study was to determine the viability of using a web-based self-management program to improve glycemic control and reduce diabetes-related distress in patients living with type 2 diabetes.MethodsAdults ≥18 years of age with type 2 diabetes were enrolled from participating general practices. Study subjects were assigned to one of two groups. Both groups continued to receive regular care and were randomized to one of two interventions: (1) Healthy Living for People with Diabetes (HeLP–Diabetes), an interactive, theoretically informed, web-based self-management program; or (2) A simple, text-based website containing basic information only. Primary outcomes were glycated hemoglobin (HbA1c) and diabetes-related distress, evaluated using the Problem Areas in Diabetes (PAID) scale, gathered 3 months and 12 months after randomization, with 12 months as the primary outcome point. Research nurses who were blinded to the group assignment collected clinical data. Participants also answered online self-report questionnaires. The investigation compared groups as randomized (intention to treat) using a linear mixed effects model, adjusted for baseline data with multiple imputation of missing values.ResultsBetween September 2013 and December 2014, 374 subjects were randomized: 185 were assigned to the intervention group, and 189 were assigned to the control group. The last follow-up results, taken at 12 months, for HbA1c were obtained for 318 (85%) members and for PAID, for 337 members (90%). Of these responses, 291 (78%) and 321 (86%) were recorded inside the predefined time frame of 10–14 months postenrollment. HbA1c was lower for members in the intervention cohort compared with the control cohort (mean contrast −0.24%; 95% CI −0.44 to −0.049; P=0.014). No significant overall difference was found between groups in the average PAID score (P=0.21); however, predetermined subgroup investigation of members who had been diagnosed more recently with diabetes demonstrated a positive effect of the intervention in this cohort (P=0.004). No negative effects were observed or reported.ConclusionResults showed that HeLP–Diabetes caused improvement in glycemic control over a year-long period.CommentsThis randomized, controlled trial (RCT) of a digital therapeutic was a very well-done study with an innovative digital therapeutic approach to providing self-management support. Because the participants, all with type 2 diabetes, had relatively good control on entry into the study, an improvement in glucose control was hard to demonstrate. Outcomes likely could have been improved if there had been more social support between participants. The lack of HbA1c improvements in a well-done study with a reasonable intervention reminds us that to demonstrate clinical and economic impact, the study must select for patients who have poor diabetes management and/or higher than average health-care utilization and costs. See the next article for further analysis of the same study.Cost-effectiveness of facilitated access to a self-management websiteLi J1, Parrott S1, Sweeting M2, Farmer A3, Ross J4, Dack C5, Pal K4, Yardley L3,6, Barnard M7, Hudda M8, Alkhaldi G9, Murray E41Mental Health and Addiction Research Group, Department of Health Sciences, University of York, York, UK; 2Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; 3Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK; 4Research Department of Primary Care and Population Health, University College London, London, UK; 5Department of Psychology, University of Bath, Bath, UK; 6Department of Psychology, University of Southampton, Southampton, UK; 7Department of Diabetes and Endocrinology, Whittington Health NHS Trust, London, UK; 8Population Health Research Institute, St. George's University of London, London, UK; 9Community Health Sciences Department, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi ArabiaJ Med Internet Res 2018;20: e201BackgroundActive self-management by individuals with type 2 diabetes improves outcomes and decreases health service costs. Existing evidence for the cost-effectiveness of digital self-management education is limited. The objective of this study was to determine the cost-effectiveness of a type 2 diabetes self-management website compared with usual care.MethodsA cost-effectiveness analysis was conducted using data collected from a 12-month, multicenter, two-arm randomized controlled study. Adults 18 and older with type 2 diabetes and registered with 21 participating primary care centers in England were recruited. Participants were randomized to either usual care with Internet-based technology (HeLP-Diabetes), an interactive web-based self-management program, or to usual care plus a comparator website containing basic information only. The individuals' intervention costs and expanded health-care resource use were collected as well as two health-related quality of life measures: the PAID scale and EQ-5D-3L. These were used to calculate quality-adjusted life years (QALYs).ResultsOverall, 374 participants were chosen, with 185 in the intervention group and 189 in the control group. The initial analysis showed the cost-effectiveness ratios of £58 per unit improvement on PAID scale and £5550 per QALY gained by the Internet-based technology compared to the control group. The final analysis showed less cost-effectiveness and higher uncertainty with incremental cost-effectiveness ratios of $116 per unit improvement on PAID scale and £18,500 per QALY. The cost-effectiveness acceptability curve showed an 87% probability of cost-effectiveness per QALY willingness-to-pay threshold. The analysis measured 363 users would need to use the Internet-based technology to become less costly than usual care.ConclusionUse of HeLP-Diabetes is cost-effective compared with usual care.CommentsThis RCT (same as the previous article) of a digital therapeutic demonstrated cost-effectiveness despite the relatively good diabetes control on entry. Imagine what the results could have been if the study subjects were sicker and costly at baseline. This intervention, with positive clinical and economic results, adds to the growing literature regarding cost-effectiveness and cost savings from digital therapeutics. The particulars of each intervention and the specifics of the participants are critical to the outcomes and to their generalizability. As more studies with a variety of digital approaches emerge and demonstrate impact, the field will be ready to make a major impact on the health and well-being of a large segment of the population—at least we hope so.Comparing the efficacy of a mobile phone-based blood glucose management system with standard clinic care in women with gestational diabetes: randomized controlled trialMackillop L1,2, Hirst JE2, Bartlett KJ1, Birks JS3, Clifton L3, Farmer AJ4, Gibson O5, Kenworthy Y2, Levy JC6, Loerup L5, Rivero-Arias O7, Ming WK8, Velardo C5, Tarassenko L51Oxford University Hospitals NHS Foundation Trust, Headington, UK; 2Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK; 3Centre for Statistics in Medicine, University of Oxford, Oxford, UK; 4Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK; 5Institute of Biomedical Engineering, University of Oxford, Oxford, UK; 6Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; 7National Perinatal Epidemiology Unit, University Of Oxford, Oxford, UK; 8Department of Obstetrics and Gynaecology, Sun Yat-Sen University, Guangzhou, ChinaJMIR Mhealth Uhealth 2018;6: e71BackgroundTreatment of hyperglycemia in women with gestational diabetes mellitus (GDM) improves maternal and neonatal results and requires significant oversight by clinicians. Currently, this is accomplished through biweekly or monthly hospital clinic visits. There are few opportunities for interventions in the time between these appointments.This study was done using a randomized controlled trial to evaluate if the utilization of a smartphone-based, real-time glucose management system to remotely monitor women living with GDM was as successful in controlling blood glucose as regular care practices through clinical visits.MethodsWomen with an irregular oral glucose tolerance test before 34 weeks of pregnancy were randomly assigned to either standard clinic care or standard clinic care plus smartphone-based blood glucose management (GDm-health, the intervention). The main outcome was a change in mean blood glucose in each cohort from enrollment to delivery, calculated with alterations made for the number of blood glucose tests, proportion of preprandial and postprandial readings, and baseline attributes.ResultsA total of 203 women were randomized. Blood glucose information was accessible for 98 women in the intervention cohort and 85 women in the control cohort. No significant difference was observed in rate of change of blood glucose (−0.16 mmol/L in the intervention and −0.14 mmol/L in the control per 28 days, P=0.78). Women in the intervention cohort reported higher overall happiness with care (P=0.049). Preterm birth was less common in the group who received the intervention (5/101, 5.0% vs 13/102, 12.7%; odds ratio 0.36 [95% CI 0.12 to 1.01]). Additionally, cesarean delivery was less common than vaginal delivery in the intervention cohort (27/101, 26.7% vs 47/102, 46.1%; P=0.005). Other glycemic, maternal, and neonatal results were comparable in the two groups. The median time from enrollment in the intervention to delivery was similar (intervention, 54 days; control, 49 days; P=0.23). There were significantly more blood glucose readings in the cohort who received the intervention (mean 3.80 [SD 1.80]) vs mean 2.63 [SD 1.71] readings per day in the intervention and control cohorts, respectively; P<0.001). No significant difference in direct health-care costs was observed between the two cohorts, with a mean cost difference of the intervention compared with control of − £1044 [95% CI − £2186 to £99]. There were no unforeseen negative results.ConclusionDespite the similarity in glycemic control and maternal and neonatal outcomes across the two cohorts, women favored the interventional model of care. Studies should delve deeper into the possible effectiveness of promoting self-management behaviors and healthier lifestyles. Remote, digital blood glucose monitoring may be a scalable, feasible intervention to address the increasing global burden of GDM.CommentsThis RCT of a digital therapeutic in women with gestational diabetes, while only showing modest results, demonstrated that a mobile cell phone–based glucose monitoring system was found by participants to be practical and relatively easy to use. It is not very surprising that the study was not able to demonstrate significant clinical results beyond engagement and blood sugar testing. Also, women received the intervention for an average of <2 months, which might have been too short of a time period to have much of an effect. To be a complete digital therapeutic requires a comprehensive intervention wrapped around the use of blood glucose monitoring. It is hoped that a larger study, with a more robust intervention, would show significant improvements in outcomes.Use of a connected glucose meter and certified diabetes educator coaching to decrease the likelihood of abnormal blood glucose excursions: The Livongo for Diabetes ProgramDowning J1, Bollyky J2,3, Schneider J21Center of Health and Community, University of California, San Francisco, San Francisco, CA; 2Livongo Health, Mountain View, CA; 3Department of Medicine, Stanford University Medical Center, Stanford, CAJ Med Internet Res 2017;19: e234This manusc