Digital Diabetes Prevention Program Research Articles

Feasibility of Fit24, a Digital Diabetes Prevention Program for Hispanic Adolescents: Qualitative Evaluation Study.

Digital health interventions are promising for reaching and engaging high-risk youth in disease prevention opportunities; however, few digital prevention interventions have been developed for Hispanic youth, limiting our knowledge of these strategies among this population. This study qualitatively assessed the feasibility and acceptability of Fit24, a 12-week goal-setting intervention that uses a Fitbit watch (Fitbit Inc) and theoretically grounded SMS text messages to promote physical activity and sleep among Hispanic adolescents (aged between 14 and 16 years) with obesity. After completing the intervention, a subsample of youth (N=15) participated in an in-depth interview. We categorized the themes into dimensions based on participant perspectives using the Practical, Robust Implementation, and Sustainability Model (PRISM) framework. Participants shared positive perceptions of wearing the Fitbit and receiving SMS text messages. Youth were highly engaged in monitoring their behaviors and perceived increased activity and sleep. Almost all youth organically received social support from a peer or family member and suggested the use of a group chat or team challenge for integrating peers into future interventions. However, most youth also expressed the need to take personal responsibility for the change in their behavior. Barriers that impacted the feasibility of the study included the skin-irritating material on the Fitbit watch band and environmental barriers (eg, lack of resources and school schedules), that limited participation in activity suggestions. Additionally, sync issues with the Fitbit limited the transmission of data, leading to inaccurate feedback. Fit24 is a promising approach for engaging Hispanic youth in a diabetes prevention program. Strategies are needed to address technical issues with the Fitbit and environmental issues such as message timing. While integrating peer social support may be desired by some, peer support strategies should be mindful of youth's desire to foster personal motivation for behavior change. Findings from this study will inform future diabetes prevention trials of Fit24 and other digital health interventions for high-risk pediatric populations.

Effects of Early-Program Physical Activity Lessons on Daily Active Minutes in a Digital Diabetes Prevention Program

ABSTRACT Background Reducing sedentary behavior and increasing physical activity have important benefits for type 2 diabetes prevention and risk reduction. Purpose To evaluate the immediate impact of completing educational lessons about physical activity within a fully digital diabetes prevention program (DPP) on the daily activity levels of participants with overweight or obesity and at risk for type 2 diabetes. Methods This study compared the pre-post change in daily active minutes of participants between two groups, 1. Completers, or participants who completed physical activity lessons 2 and 3 of the DPP and 2. Starters, or a propensity-matched control group who initiated the program but did not complete lessons 2 and 3 within the first month. Results We observed a significant difference in the change in daily active minutes between groups (U = 636742.5, p ≤ .0001). Completers increased their daily active minutes between baseline and the end of the first month (Mean = 7.1 minutes, SE = 0.7) while Starters decreased (Mean = –25.4 minutes; SE = 1.0). Discussion Targeted educational lessons about physical activity coupled with self-monitoring and automated coaching promoted daily physical activity among participants in a digital DPP. Translation to Health Education Practice Health educators may use digitally delivered educational lessons about physical activity to facilitate immediate changes in daily active behaviors.

Leveraging Machine Learning to Develop Digital Engagement Phenotypes of Users in a Digital Diabetes Prevention Program: Evaluation Study

Background Digital diabetes prevention programs (dDPPs) are effective “digital prescriptions” but have high attrition rates and program noncompletion. To address this, we developed a personalized automatic messaging system (PAMS) that leverages SMS text messaging and data integration into clinical workflows to increase dDPP engagement via enhanced patient-provider communication. Preliminary data showed positive results. However, further investigation is needed to determine how to optimize the tailoring of support technology such as PAMS based on a user’s preferences to boost their dDPP engagement. Objective This study evaluates leveraging machine learning (ML) to develop digital engagement phenotypes of dDPP users and assess ML’s accuracy in predicting engagement with dDPP activities. This research will be used in a PAMS optimization process to improve PAMS personalization by incorporating engagement prediction and digital phenotyping. This study aims (1) to prove the feasibility of using dDPP user-collected data to build an ML model that predicts engagement and contributes to identifying digital engagement phenotypes, (2) to describe methods for developing ML models with dDPP data sets and present preliminary results, and (3) to present preliminary data on user profiling based on ML model outputs. Methods Using the gradient-boosted forest model, we predicted engagement in 4 dDPP individual activities (physical activity, lessons, social activity, and weigh-ins) and general activity (engagement in any activity) based on previous short- and long-term activity in the app. The area under the receiver operating characteristic curve, the area under the precision-recall curve, and the Brier score metrics determined the performance of the model. Shapley values reflected the feature importance of the models and determined what variables informed user profiling through latent profile analysis. Results We developed 2 models using weekly and daily DPP data sets (328,821 and 704,242 records, respectively), which yielded predictive accuracies above 90%. Although both models were highly accurate, the daily model better fitted our research plan because it predicted daily changes in individual activities, which was crucial for creating the “digital phenotypes.” To better understand the variables contributing to the model predictor, we calculated the Shapley values for both models to identify the features with the highest contribution to model fit; engagement with any activity in the dDPP in the last 7 days had the most predictive power. We profiled users with latent profile analysis after 2 weeks of engagement (Bayesian information criterion=−3222.46) with the dDPP and identified 6 profiles of users, including those with high engagement, minimal engagement, and attrition. Conclusions Preliminary results demonstrate that applying ML methods with predicting power is an acceptable mechanism to tailor and optimize messaging interventions to support patient engagement and adherence to digital prescriptions. The results enable future optimization of our existing messaging platform and expansion of this methodology to other clinical domains. Trial Registration ClinicalTrials.gov NCT04773834; https://www.clinicaltrials.gov/ct2/show/NCT04773834 International Registered Report Identifier (IRRID) RR2-10.2196/26750

Weight loss and lifestyle change among high-risk individuals enrolled in a digital diabetes prevention program: A longitudinal study of private and public health insurance members in Western New York

Weight loss is critical to reduce diabetes risk. Diabetes Prevention Programs (DPPs) are effective for weight loss, although less is known about digital DPPs.This study explores the association between Brook+, a 52-week digital DPP, and weight loss. This longitudinal observational study uses a sample of 5,516 private, Medicare, and Medicaid health insurancemembers from Western New York enrolled into Brook+ between December 2020 and December 2022. We used multivariable generalized linear regression models to estimate the association between completion of the Brook+ program,overall and stratified by health insurance type,and 5% weight loss using odds ratios (OR) and 95% confidence intervals (CI), adjusted for age and gender. We also estimated average weight loss from baseline associated with high engagement with the program using adjusted linear regression models. In the pooled sample, those who completed the Brook + program had 21% increased odds of 5% weight loss (OR = 1.21 95% CI: (1.02 – 1.44)). Among users enrolled in private, Medicare, and Medicaid health insurance, program completion was associated with 21%, 33%, and 13% increased odds of 5% weight loss, compared to those who did not complete Brook+. Interacting with health coaches, increased physical activity, and meal logging were all significant predictors of weight loss. Our results suggest that digital DPPs are promising for large-scale diabetes prevention via weight loss and lifestyle change.

Cost-effectiveness analysis of a digital Diabetes Prevention Program (dDPP) in prediabetic patients.

To assess the cost-effectiveness of a digital Diabetes Prevention Program (dDPP) in preventing type 2 diabetes mellitus among prediabetic patients from a health system perspective over a 10-year time horizon. A Markov cohort model was constructed to assess the cost-effectiveness of dDPP compared to a small group education (SGE) intervention. Transition probabilities for the first year of the model were derived from two clinical trials on dDPP. Transition probabilities for longer-term effects were derived from meta-analyses on lifestyle and Diabetes Prevention Program interventions. Cost and health utilities were derived from published literature. Partial completion of interventions was incorporated to provide a robust prediction of a real-world deployment. Parameter uncertainties were assessed using univariate and probabilistic sensitivity analyses. Cost-effectiveness was measured by an incremental cost-effectiveness ratio (ICER) between dDPP and SGE from a health system perspective over a 10-year time horizon. The dDPP dominated the SGE at the $50,000, $100,000, and $150,000 willingness-to-pay thresholds per quality-adjusted life years (QALYs). The base case analysis at the $100,000 willingness-to-pay threshold (WTP) revealed a dominated ICER, with the SGE costing $1332 more and accruing an average of 0.04 fewer QALYs. Probabilistic sensitivity analysis showed that the dDPP was preferred in 64.4% of simulations across the $100,000 WTP thresholds. The findings comparing a dDPP to an SGE suggest that a dDPP can be cost-effective for patients with a high risk of developing type 2 diabetes.

Weight Loss in a Digital Diabetes Prevention Program for People in Health Professional Shortage and Rural Areas.

Individuals with prediabetes living in hard-to-reach and underserved areas experience barriers to accessing traditional in-person preventive health services. The National Diabetes Prevention Program (DPP) is a preventive health care program designed to reduce the risk of developing type 2 diabetes. Although there have been increasing numbers of remote DPPs accessible, there are little data on the clinical outcomes of digital DPPs for members living in hard-to-reach and underserved areas. This study assessed whether living in a designated Health Professional Shortage Area (HPSA) and a rural versus urban area impacted the weight loss of N = 7266 members of a fully digital program called Lark DPP. Secondary analyses included between-group comparisons of program retention and member characteristics, demographics, and socioeconomics. Percent weight loss did not differ by HPSA (P = 0.16) or rural/urban status (P = 0.15), despite greater potential barriers for members residing in HPSAs (eg, highest starting body mass index, lowest income, lowest education). Mean percent weight loss for members residing in an HPSA and rural area was mean (M) = 4.75%, standard error (SE) = 0.09; for members in a non-HPSA, rural area M = 4.96%, SE = 0.16; for members in an HPSA, urban area M = 4.55%, SE = 0.13; and for members in a non-HPSA, urban area M = 4.77%, SE = 0.13. Members of a fully digital DPP achieved weight loss that did not differ by HPSA or urban/rural designation. Fully digital programs offer a solution to reduce the risk of type 2 diabetes in areas where residents may not otherwise have access to diabetes prevention services.

Weight loss and modeled cost savings in a digital diabetes prevention program.

Participation in the National Diabetes Prevention Program (DPP) can improve individual health through reduced risk of type 2 diabetes and save the healthcare system substantial medical costs associated with a diagnosis of type 2 diabetes and its associated complications. There is less evidence of outcomes and cost savings associated with a fully digital delivery of the DPP. This study assessed 13,593 members who provided an initial digital weight and subsequently achieved various weight loss and engagement outcomes during their participation in a digital DPP. Analyzed data included both complete observations and missing observations imputed using maximum likelihood estimation. Findings include members' behavioral correlates of weight loss and a literature-based cost-savings estimate associated with achieving three mutually exclusive weight loss or engagement benchmarks: ≥5% weight loss, >2% but <5% weight loss, and completion of ≥4 educational lessons. 11,976 members (88%) provided a weight after 2months of participation, enabling calculation of their weight nadir. Considering complete data, 97% of members maintained or lost weight. Using the imputed data for these calculations, 32.0% of members achieved ≥5%, 32.4% achieved >2% but <5%, 32.0% maintained ±2%, and 3.6% gained weight. Members who lost the most weight achieved their weight nadir furthest into the program (mean day=189, SE=1.4) and had the longest active engagement (mean days=268, SE=1.4), particularly compared to members who gained weight (mean nadir day=119, SE=3.7; active engagement mean days=199, SE=4.9) (both p≤0.0001). Modeled 1-year cost-savings estimates ranged from $11,229,160 to $12,960,875. Members of a fully digital DPP achieved clinical and engagement outcomes during their participation in the program that confer important health benefits and cost savings.

Using Digital Health Technology to Prevent and Treat Diabetes.

Using Digital Health Technology to Prevent and Treat Diabetes.

Effects of a digital diabetes prevention program on cardiovascular risk among individuals with prediabetes

ObjectiveTo examine changes in cardiovascular disease (CVD) risk outcomes of overweight/obese adults with prediabetes. MethodsUsing data from a randomized control trial of digital diabetes prevention program (d‐DPP) with 599 participants. We applied the atherosclerotic CVD (ASCVD) risk calculator to predict 10-year CVD risk for d‐DPP and small education (comparison) groups. Between-group risk changes at 4 and 12 months were compared using a repeated measures linear mixed-effect model. We examined within-group differences in proportion of participants over time for specific CVD risk factors using generalized estimating equations. ResultsWe found no differences between baseline 10-year ASCVD risk. Relative to the comparison group, the d‐DPP group experienced greater reductions in predicted 10-year ASCVD risk at each follow-up visit and a significant group difference at 4 months (−0.96%; 95% confidence interval: −1.58%, −0.34%) (but not at 12 months). Additionally, we observed that the d‐DPP group experienced a decreased proportion of individuals with hyperlipidemia (18% and 16% from baseline to 4 and 12 months), high-risk total cholesterol (8% from baseline to 12 months), and being insufficiently active (26% and 22% from baseline to 4 and 12 months at follow-up time points. ConclusionsOur findings suggest that a digitally adapted DPP may promote the prevention of cardiometabolic disease among overweight/obese individuals with prediabetes. However, given the lack of maintenance of effect on ASCVD risk at 12 months, there may also be a need for additional interventions to sustain the effect detected at 4 months.

How the Behavior Change Content of a Nationally Implemented Digital Diabetes Prevention Program Is Understood and Used by Participants: Qualitative Study of Fidelity of Receipt and Enactment.

The National Health Service Digital Diabetes Prevention Programme (NHS-DDPP) is a program for adults in England at risk of developing type 2 diabetes mellitus (T2DM). It is based on NHS England specifications that stipulate specific behavior change techniques (BCTs), that is, active ingredients to produce behavior change to target diet and physical activity. Now rolled out nationally, the NHS-DDPP is being delivered by 4 independent providers as a 9-month intervention via apps, educational material, and remote health coaching. To optimize effectiveness, participants need to be able to understand and use behavior change content (eg, goal setting and problem solving) of an intervention delivered to them digitally. Previous research has shown that people benefit from support to aid the understanding and use of BCTs. The objectives of this qualitative study were to evaluate how participants in the NHS-DDPP understand and use BCT content, investigate how participants describe the role of health coaches in supporting their behavior change, and examine how the understanding and use of behavior change content of the NHS-DDPP varies across providers. In total, 45 service users were interviewed twice by telephone at 2 to 4 months into, and at the end of, the program. Topics included participants' understanding and use of key BCTs to support self-regulation (eg, goal setting) and the support they received via the program. Transcripts were analyzed thematically, informed by the framework method. Participants described their understanding and use of some behavior change content of the program as straightforward: use of BCTs (eg, self-monitoring of behavior) delivered digitally via provider apps. Participants valued the role of health coaches in supporting their behavior change through the emotional support they offered and their direct role in delivery and application of some BCTs (eg, problem solving) to their specific circumstances. Participants expressed frustration over the lack of monitoring or feedback regarding their T2DM risk within the program. Variations in the understanding and use of behavior change content of the NHS-DDPP were present across provider programs. Health coaches' support in delivery of key components of the program seems to be pivotal. To improve the understanding and use of BCTs in digital interventions, it is important to consider routes of delivery that offer additional interactive human support. Understanding of some self-regulatory BCTs may benefit from this support more than others; thus, identifying the optimal mode of delivery for behavior change content is a priority for future research. The NHS-DDPP could be improved by explicitly setting out the need for health coaches to support understanding of some self-regulatory BCT content such as problem solving in the service specification and amending the discharge process so that knowledge of any change in T2DM risk is available to participants.

Cost Savings and Reduced Health Care Utilization Associated with Participation in a Digital Diabetes Prevention Program in an Adult Workforce Population.

BackgroundThough in-person delivery of the Diabetes Prevention Program (DPP) has demonstrated medical cost savings, the economic impact of digital programs is not as well understood.ObjectiveThis study examines the impact of a digital DPP program on reducing all-cause health care costs and utilization among 2027 adult participants at 12 months.MethodsA longitudinal, observational analysis of health care claims data was conducted on a workforce population who participated in a digital diabetes prevention program. Differences in utilization and costs from the year prior to program delivery through 1 year after enrollment were calculated using medical claims data for digital DPP participants compared to a propensity matched cohort in a differences-in-differences model.ResultsAt 1 year, the digital DPP population had a reduction in all-cause health care spend of US$1169 per participant relative to the comparison group (P = 0.01), with US$699 of that savings coming from reduced inpatient spend (P = 0.001). Cost savings were driven by fewer hospital admissions and shorter length of stay (P < 0.001). No other significant results in cost differences were detected. There was a trend toward savings extending into the second year, but the savings did not reach statistical significance.ConclusionsThese results demonstrated significant short-term health care cost savings at 1 year associated with digital DPP program delivery.

Mental health diagnosis attenuates weight loss among older adults in a digital diabetes prevention program.

Diabetes Prevention Programs (DPP) are effective at reducing diabetes incidence via clinically significant weight loss. Co-morbid mental health condition(s) may reduce the effect of DPP administered in-person and telephonically but this has not been assessed for digital DPP. This report examines the moderating effect of mental health diagnosis on weight change among individuals who enrolled in digital DPP (enrollees) at 12 and 24months. Secondary analysis of prospective, electronic health record data from a study of digital DPP among adults (N=3904) aged 65-75 with prediabetes (HbA1c 5.7%-6.4%) and obesity (BMI ≥30kg/m2). Mental health diagnosis only moderated the effect of digital DPP on weight change during the first 7months (p=0.003) and the effect attenuated at 12 and 24months. Results were unchanged after adjusting for psychotropic medication use. Among those without a mental health diagnosis, digital DPP enrollees lost more weight than non-enrollees: -4.17kg (95% CI, -5.22 to -3.13) at 12months and -1.88kg (95% CI, -3.00 to -0.76) at 24months, whereas among individuals with a mental health diagnosis, there was no difference in weight loss between enrollees and non-enrollees at 12 and 24months (-1.25kg [95% CI, -2.77 to 0.26] and 0.02kg [95% CI, -1.69-1.73], respectively). Digital DPP appears less effective for weight loss among individuals with a mental health condition, similar to prior findings for in-person and telephonic modalities. Findings suggest a need for tailoring DPP to address mental health conditions.

Costs and Cost-Effectiveness of Implementing a Digital Diabetes Prevention Program in a Large, Integrated Health System.

BackgroundThe Diabetes Prevention Program (DPP) has been translated into digital formats. We report an economic evaluation of a digital DPP implemented in a large, integrated health care system. MethodsPatients (n = 4148) were invited to participate in digital DPP based on clinical characteristics (HbA1c 5.7%-6.4% and body mass index ≥ 30 kg/m2) assessed using electronic medical record data. Using a propensity score we matched (1:1) enrolled and not enrolled patients for a total of 784. We identified high-risk patients (ie, above the 50th percentile of risk; n = 202) by calculating each patient's 2-year of developing diabetes. We report the cost of the intervention and the costs of medical care over 12- and 24-month follow-up, and the incremental cost-effectiveness ratio as the cost per additional kilogram weight loss at 24 months. ResultsAt 12 months, enrolled patients had lower total costs ($6,926, 95% CI $5,681-$8,171) than not enrolled patients ($7,538, 95% CI $6,293-$8,783). This pattern attenuated slightly at 24 months (enrolled = $16,255, 95% CI $14,097-$18,412; not enrolled = $16,688, 95% CI $14,531-$18,846). We found an incremental cost-effectiveness ratio of $81.92 per additional kilogram weight loss. For high-risk patients, the digital DPP group had, on average, lower costs and greater weight loss. We found a 55% chance of the digital DPP program being cost-effective at a willingness-to-pay of $150 per additional kilogram of weight loss; at the same willingness-to-pay, there is a 60% chance in the high-risk subgroup. Limitations include the nonrandomized design and potential volunteer bias. ConclusionDigital DPP had a favorable cost-effectiveness profile compared to other lifestyle interventions.

Impact of a Digital Diabetes Prevention Program on Estimated 8-Year Risk of Diabetes in a Workforce Population.

We asked whether the estimated 8-year risk of diabetes could be reduced within the first 2 years of a digital Diabetes Prevention Program (dDPP) in a workforce population. Employees and spouses were eligible if they had prediabetes-range fasting glucose or hemoglobin A 1c and body mass index ≥25 kg/m 2 . Diabetes risk was assessed using the Framingham diabetes risk score in the year before and the 2 years after dDPP initiation. Among participants completing at least nine dDPP lessons ( n = 286), diabetes risk decreased 5.3% the year after dDPP initiation, after a 5.4% increase the year before initiation (difference in differences, -10.6%; 95% confidence interval, -13.4% to -7.9%; P &lt; 0.001), with risk maintained at reduced levels after the second year of the program. This dDPP reduced the estimated 8-year risk of diabetes over the first 2 years of the program.

Discovering Engagement Personas in a Digital Diabetes Prevention Program.

Digital health technologies are shaping the future of preventive health care. We present a quantitative approach for discovering and characterizing engagement personas: longitudinal engagement patterns in a fully digital diabetes prevention program. We used a two-step approach to discovering engagement personas among n = 1613 users: (1) A univariate clustering method using two unsupervised k-means clustering algorithms on app- and program-feature use separately and (2) A bivariate clustering method that involved comparing cluster labels for each member across app- and program-feature univariate clusters. The univariate analyses revealed five app-feature clusters and four program-feature clusters. The bivariate analysis revealed five unique combinations of these clusters, called engagement personas, which represented 76% of users. These engagement personas differed in both member demographics and weight loss. Exploring engagement personas is beneficial to inform strategies for personalizing the program experience and optimizing engagement in a variety of digital health interventions.

Fidelity to Program Specification of the National Health Service Digital Diabetes Prevention Program Behavior Change Technique Content and Underpinning Theory: Document Analysis.

BackgroundThe National Health Service (NHS) Diabetes Prevention Program is a behavior change intervention for adults in England who are identified as being at high risk of developing type 2 diabetes. The face-to-face service was launched in 2016, followed by a digital service (NHS Digital Diabetes Prevention Program [NHS-DDPP]) in 2019. A total of 4 service providers were commissioned to deliver the NHS-DDPP and were required to deliver the digital service in line with a program specification detailing the key intervention content. The fidelity of the behavior change content in the digital service (ie, the extent to which the program is delivered as intended) is currently unknown. Digital interventions may allow higher fidelity as staff do not have to be trained to deliver all intervention content. Assessing fidelity of the intervention design is particularly important to establish the planned behavior change content in the NHS-DDPP and the extent to which this adheres to the program specification. This is the first known independent assessment of design fidelity in a large-scale digital behavior change intervention.ObjectiveThis study aims to assess the fidelity of the behavior change content in each of the 4 NHS-DDPP providers’ intervention designs to the full program specification.MethodsWe conducted a document review of each provider’s NHS-DDPP intervention design, along with interviews with program developers employed by the 4 digital providers (n=6). Providers’ intervention design documents and interview transcripts were coded for behavior change techniques (BCTs; ie, the active ingredients of the intervention) using the Behavior Change Technique Taxonomy version 1 and underpinning theory using the Theory Coding Scheme framework. The BCTs identified in each digital provider’s intervention design were compared with the 19 BCTs included in the program specification.ResultsOf the 19 BCTs specified in the program specification, the 4 providers planned to deliver 16 (84%), 17 (89%), 16 (84%), and 16 (84%) BCTs, respectively. An additional 41 unspecified BCTs were included in at least one of the 4 digital providers’ intervention designs. By contrast, inconsistent use of the underpinning theory was apparent across providers, and none of the providers had produced a logic model to explain how their programs were expected to work. All providers linked some of their planned BCTs to theoretical constructs; however, justification for the inclusion of other BCTs was not described.ConclusionsThe fidelity of BCT content in the NHS-DDPP was higher than that previously documented for the face-to-face service. Thus, if service users engage with the NHS-DDPP, this should increase the effectiveness of the program. However, given that a clear theoretical underpinning supports the translation of BCTs in intervention designs to intervention delivery, the absence of a logic model describing the constructs to be targeted by specific BCTs is potentially problematic.

Evaluating the Implementation of a Digital Diabetes Prevention Program in an Integrated Health Care Delivery System Among Older Adults: Results of a Natural Experiment.

The purpose of this natural experiment study was to assess the effectiveness of a 12-month digital Diabetes Prevention Program (DPP) for adults aged 65-75 years with prediabetes and obesity within a large, integrated health care system. Adjusting for propensity scores and covariates, patients who enrolled and participated in the digital DPP had a mean weight loss of 8.6 lb over 12 months and 5.7 lb by 24 months, compared with a steady, minimal weight loss of 1.3 lb over 12 months and 2.8 lb by 24 months among patients not enrolled. There was a significant difference in mean change in A1C between enrolled and nonenrolled patients over 12 months (-0.10%), but not by 24 months (-0.06%). Digital DPP appears to be an effective weight loss option and potential diabetes prevention intervention for older adults at high risk for type 2 diabetes.

Evaluating the Implementation of Digital and In-Person Diabetes Prevention Program in a Large, Integrated Health System: Natural Experiment Study Design.

Implementation of a Diabetes Prevention Program (DPP) in both in-person and digital health-care settings has been increasing. The purpose of this article is to describe the protocol of a mixed-methods, natural experiment study designed to evaluate the implementation of DPP in a large, integrated health system. Kaiser Permanente Northwest patients who were 19 to 75 years with prediabetes (hemoglobin A1c or glycated hemoglobin, 5.7-6.4) and obesity (body mass index ≥ 30 kg/m2) were invited, via the Kaiser Permanente Northwest patient portal, to participate in the digital (n = 4124) and in-person (n = 2669) DPP during 2016 through 2018. Primary (weight) and secondary (hemoglobin A1c or glycated hemoglobin level) outcome data will be obtained from electronic health records. A cost-effectiveness analysis as well as qualitative interviews with patients (enrolled and not enrolled in the DPP) and stakeholders will be conducted to examine further implementation, acceptability, and sustainability. The mixed-methods, natural experiment design we will use to evaluate Kaiser Permanente Northwest's implementation of the digital and in-person DPP builds on existing evidence related to the effectiveness of these two DPP delivery modes and will contribute new knowledge related to best practices for implementing and sustaining the DPP within large health systems over the long term.

Reach of a Fully Digital Diabetes Prevention Program in Health Professional Shortage Areas.

The National Diabetes Prevention Program (NDPP) offers lifestyle change education to adults at risk for diabetes across the United States, but its reach is curbed due, in part, to limitations of traditional in-person programs. Diabetes Prevention Programs (DPPs) that are fully digital may increase reach by overcoming these barriers. The aim of this research was to examine the reach of Lark's DPP, a fully digital artificial-intelligence-powered DPP. This study assessed geographic features and demographic characteristics of a sample of Lark DPP commercial health plan members with complete data (N = 16,327) and compared several demographic features with a large composite sample of members from DPPs across the nation (NDPP; N = 143,489) and a National Health Interview Survey (NHIS) sample of prediabetic adults in the United States (NHIS; N = 2118). Examination of the Lark DPP sample revealed that 24.4% of members lived in rural areas, 30.8% lived in whole county health professional shortage areas, and only 7.6% of members lived in a zip code with an in-person DPP. When comparing the Lark sample with the NDPP and NHIS samples, Lark DPP enrollees tended to be younger and have a higher body mass index (BMI) (p's < 0.001). Lark provides convenient access to a DPP for individuals living in hard-to-reach areas who may face barriers to participating in in-person or telephonic DPPs or who prefer a digital program. Compared with the NDPP sample, Lark is also reaching younger and higher BMI users, who are traditionally difficult to enroll and have a high need for intervention.

Effects of a Digital Diabetes Prevention Program: An RCT

In light of the need to expand the reach and access of clinically proven digital Diabetes Prevention Programs (d-DPPs) and the need for rigorous evidence of effectiveness, the purpose of this study was to determine the effectiveness of a digital Diabetes Prevention Program for improving weight, HbA1c, and cardiovascular risk factors among people with prediabetes compared to enhanced standard care plus waitlist control. This was a single-blind RCT among participants at risk of developing type 2 diabetes and included 12 months of follow-up. A total of 599 volunteer patients with prediabetes were recruited primarily through electronic medical records and primary care practices. Participants were randomized to either a d-DPP (n=299) or a single-session small-group diabetes-prevention education class (n=300) focused on action planning for weight loss. The d-DPPs consisted of 52 weekly sessions, lifestyle coaching, virtual peer support, and behavior tracking tools. The primary outcome was a change in HbA1c from baseline to 12 months using intent-to-treat analyses. On the basis of multiple comparisons of endpoints, 95% CIs are presented and 2-sided p<0.025 was required for statistical significance. Secondary outcomes included body weight and cardiovascular disease risk factors. Among 599 randomized participants (mean age=55.4 years, 61.4% women), 483 (80%) completed the study. The d-DPPs produced significantly greater reductions in HbA1c (0.08%, 95% CI= -0.12, -0.03) and percentage change in body weight (-5.5% vs -2.1%, p<0.001) at 12 months. A greater proportion of the d-DPPs group achieved a clinically significant weight loss ≥5% (43% vs 21%, p<0.001), and more participants shifted from prediabetes to normal HbA1c range (58% vs 48%, p=0.04). Engagement in d-DPPs was significantly related to improved HbA1c and weight loss. This d-DPPs demonstrated clinical effectiveness and has significant potential for widespread dissemination and impact, particularly considering the growing demand for telemedicine in preventive healthcare services. This study is registered at www. gov (ClinicalTrials.gov Identifier: NCT03312764).