Cost effectiveness of an internet-delivered lifestyle intervention in primary care patients with high cardiovascular risk

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

OBJECTIVES

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Cost-effectiveness analysis of a digital diabetes-prevention programme versus an in-person diabetes-prevention programme in people with prediabetes in the United States

AIM

To assess the cost-effectiveness of a digital diabetes prevention programme (d-DPP) compared with a diabetes prevention programme (DPP) for preventing type 2 diabetes (T2D) in individuals with prediabetes in the United States.

METHODS

A Markov cohort model was constructed, simulating a 10-year period starting at the age of 45 years, with a societal and healthcare sector perspective. The effectiveness of the d-DPP intervention was evaluated using a meta-analysis, with that of the DPP as the comparator. The initial cycle represented the treatment period, and transition probabilities for the post-treatment period were derived from a long-term lifestyle intervention meta-analysis. The onset of T2D complications was estimated using microsimulation. Quality-adjusted life years (QALYs) were calculated based on health utility measured by short form (SF)-12 scores, and a willingness-to-pay threshold of $100 000 per QALY gained was applied.

RESULTS

The d-DPP intervention resulted in cost savings of $3,672 from a societal perspective and $2,990 from a healthcare sector perspective and a gain of 0.08 QALYs compared with the DPP. The dropout rate was identified as a significant factor influencing the results. Probabilistic sensitivity analysis showed that the d-DPP intervention was preferred in 85.8% in the societal perspective and 85.2% in the healthcare sector perspective.

CONCLUSIONS

The d-DPP is a cost-effective alternative to in-person lifestyle interventions for preventing the development of T2D among individuals with prediabetes in the United States.

Factors influencing participation in an online national diabetes prevention programme: A qualitative study with attenders and educators

AIM

To explore factors affecting participation in the pilot of the synchronous online national diabetes prevention programme (NDPP) in Ireland from the perspectives of those who attended and the educators who recruited for and delivered the programme.

METHODS

A qualitative study involving semi-structured interviews and focus groups with NDPP attenders (attended the assessment and at least one session) and educators (dietitians) on the programme. The Framework Method using the Theoretical Domains Framework (TDF) guided the analysis.

RESULTS

Thirteen attenders took part in two online focus groups and five online or phone interviews. Eight educators took part. Four themes which cut across the TDF domains were identified as factors influencing participation; (i) lack of awareness of prediabetes and fear of diabetes, relating to attenders' fear of diabetes and lack of knowledge of prediabetes and diabetes prevention; (ii) perceived need for programme support to change health behaviour, concerning attenders' and educators' recognition of the need for the NDPP; (iii) trust in healthcare professionals (HCPs), relating to trust in HCPs to convey the seriousness of prediabetes and the value of diabetes prevention programmes (DPPs) and (iv) practical and personal ease of joining online, relating to the flexibility and accessibility of the synchronous online group format, the IT skills of attenders and educators and apprehension about group education.

CONCLUSIONS

Raising awareness of prediabetes and the need for prevention programmes should be a priority for health services and HCPs. The synchronous online group format was seen as less daunting to join than a face-to-face programme and may be a useful option to encourage participation.

Cost and cost-effectiveness analysis of a digital diabetes prevention program: results from the PREDICTS trial

Although technology-assisted diabetes prevention programs (DPPs) have been shown to improve glycemic control and weight loss, information are limited regarding relevant costs and their cost-effectiveness. To describe a retrospective within-trial cost and cost-effectiveness analysis (CEA) to compare a digital-based DPP (d-DPP) with small group education (SGE), over a 1-year study period. The costs were summarized into direct medical costs, direct nonmedical costs (i.e., times that participants spent engaging with the interventions), and indirect costs (i.e., lost work productivity costs). The CEA was measured by the incremental cost-effectiveness ratio (ICER). Sensitivity analysis was performed using nonparametric bootstrap analysis. Over 1 year, the direct medical costs, direct nonmedical costs, and indirect costs per participant were $4,556, $1,595, and $6,942 in the d-DPP group versus $4,177, $1,350, and $9,204 in the SGE group. The CEA results showed cost savings from d-DPP relative to SGE based on a societal perspective. Using a private payer perspective for d-DPP, ICERs were $4,739 and $114 to obtain an additional unit reduction in HbA1c (%) and weight (kg), and were $19,955 for an additional unit gain of quality-adjusted life years (QALYs) compared to SGE, respectively. From a societal perspective, bootstrapping results indicated that d-DPP has a 39% and a 69% probability, at a willingness-to-pay of $50,000/QALY and $100,000/QALY, respectively, of being cost-effective. The d-DPP was cost-effective and offers the prospect of high scalability and sustainability due to its program features and delivery modes, which can be easily translated to other settings.

Study protocol: BRInging the Diabetes prevention program to GEriatric Populations

In the Diabetes Prevention Program (DPP) randomized, controlled clinical trial, participants who were  ≥ 60 years of age in the intensive lifestyle (diet and physical activity) intervention had a 71% reduction in incident diabetes over the 3-year trial. However, few of the 26.4 million American adults age ≥65 years with prediabetes are participating in the National DPP. The BRInging the Diabetes prevention program to GEriatric Populations (BRIDGE) randomized trial compares an in-person DPP program Tailored for Older AdulTs (DPP-TOAT) to a DPP-TOAT delivered via group virtual sessions (V-DPP-TOAT) in a randomized, controlled trial design (N = 230). Eligible patients are recruited through electronic health records (EHRs) and randomized to the DPP-TOAT or V-DPP-TOAT arm. The primary effectiveness outcome is 6-month weight loss and the primary implementation outcome is intervention session attendance with a non-inferiority design. Findings will inform best practices in the delivery of an evidence-based intervention.

Health economic evaluation of preventive digital public health interventions using decision-analytic modelling: a systematized review

BACKGROUND

Digital public health (DiPH) provides novel approaches for prevention, potentially leading to long-term health benefits in resource-limited health systems. However, cost-effectiveness of DiPH interventions is unclear. This systematized review investigates the use of decision-analytic modelling in health economic evaluations of DiPH primary prevention and health promotion interventions, focusing on intervention's design, methods used, results, and reporting quality.

METHODS

PubMed, CINAHL, and Web of Science were searched for studies of decision-analytic economic evaluations of digital interventions in primary prevention or health promotion, published up to June 2022. Intervention characteristics and selected items were extracted based on the Consolidated Health Economic Evaluation Reporting Standards (CHEERS). Incremental cost-effectiveness ratios (ICERs) were then extracted and price-adjusted to compare the economic evaluation results. Finally, the included studies' reporting quality was assessed by building a score using CHEERS.

RESULTS

The database search (including search update) produced 2,273 hits. After removing duplicates, 1,434 titles and abstracts were screened. Of the 89 studies meeting the full-text search criteria, 14 were ultimately reviewed. The most common targets were physical activity (five studies) and weight loss (four). Digital applications include text messages, web-based inventions, app-based interventions, e-learning devices, and the promotion of smartphone apps. The mean ICER of the 12 studies using quality-adjusted life years (QALYs) is €20,955 per QALY (min. - €3,949; max. €114,211). The mean of reported CHEERS items per study is 81% (min. 59%; max. 91%).

CONCLUSIONS

This review only includes primary prevention and health promotion, and thus excludes other DiPH fields (e.g. secondary prevention). It also focuses on decision-analytic models, excluding study-based economic evaluations. Standard methods of economic evaluation could be adapted more to the specifics of DiPH by measuring the effectiveness of more current technologies through alternative methods, incorporating a societal perspective, and more clearly defining comparators. Nevertheless, the review demonstrates using common thresholds that the new field of DiPH shows potential for cost-effective preventive interventions.

Digital Health Interventions to Enhance Prevention in Primary Care: Scoping Review

BACKGROUND

Disease prevention is a central aspect of primary care practice and is comprised of primary (eg, vaccinations), secondary (eg, screenings), tertiary (eg, chronic condition monitoring), and quaternary (eg, prevention of overmedicalization) levels. Despite rapid digital transformation of primary care practices, digital health interventions (DHIs) in preventive care have yet to be systematically evaluated.

OBJECTIVE

This review aimed to identify and describe the scope and use of current DHIs for preventive care in primary care settings.

METHODS

A scoping review to identify literature published from 2014 to 2020 was conducted across multiple databases using keywords and Medical Subject Headings terms covering primary care professionals, prevention and care management, and digital health. A subgroup analysis identified relevant studies conducted in US primary care settings, excluding DHIs that use the electronic health record (EHR) as a retrospective data capture tool. Technology descriptions, outcomes (eg, health care performance and implementation science), and study quality as per Oxford levels of evidence were abstracted.

RESULTS

The search yielded 5274 citations, of which 1060 full-text articles were identified. Following a subgroup analysis, 241 articles met the inclusion criteria. Studies primarily examined DHIs among health information technologies, including EHRs (166/241, 68.9%), clinical decision support (88/241, 36.5%), telehealth (88/241, 36.5%), and multiple technologies (154/241, 63.9%). DHIs were predominantly used for tertiary prevention (131/241, 54.4%). Of the core primary care functions, comprehensiveness was addressed most frequently (213/241, 88.4%). DHI users were providers (205/241, 85.1%), patients (111/241, 46.1%), or multiple types (89/241, 36.9%). Reported outcomes were primarily clinical (179/241, 70.1%), and statistically significant improvements were common (192/241, 79.7%). Results were summarized across the following 5 topics for the most novel/distinct DHIs: population-centered, patient-centered, care access expansion, panel-centered (dashboarding), and application-driven DHIs. The quality of the included studies was moderate to low.

CONCLUSIONS

Preventive DHIs in primary care settings demonstrated meaningful improvements in both clinical and nonclinical outcomes, and across user types; however, adoption and implementation in the US were limited primarily to EHR platforms, and users were mainly clinicians receiving alerts regarding care management for their patients. Evaluations of negative results, effects on health disparities, and many other gaps remain to be explored.

Digital Behavior Change Interventions for the Prevention and Management of Type 2 Diabetes: Systematic Market Analysis

BACKGROUND

Advancements in technology offer new opportunities for the prevention and management of type 2 diabetes. Venture capital companies have been investing in digital diabetes companies that offer digital behavior change interventions (DBCIs). However, little is known about the scientific evidence underpinning such interventions or the degree to which these interventions leverage novel technology-driven automated developments such as conversational agents (CAs) or just-in-time adaptive intervention (JITAI) approaches.

OBJECTIVE

Our objectives were to identify the top-funded companies offering DBCIs for type 2 diabetes management and prevention, review the level of scientific evidence underpinning the DBCIs, identify which DBCIs are recognized as evidence-based programs by quality assurance authorities, and examine the degree to which these DBCIs include novel automated approaches such as CAs and JITAI mechanisms.

METHODS

A systematic search was conducted using 2 venture capital databases (Crunchbase Pro and Pitchbook) to identify the top-funded companies offering interventions for type 2 diabetes prevention and management. Scientific publications relating to the identified DBCIs were identified via PubMed, Google Scholar, and the DBCIs' websites, and data regarding intervention effectiveness were extracted. The Diabetes Prevention Recognition Program (DPRP) of the Center for Disease Control and Prevention in the United States was used to identify the recognition status. The DBCIs' publications, websites, and mobile apps were reviewed with regard to the intervention characteristics.

RESULTS

The 16 top-funded companies offering DBCIs for type 2 diabetes received a total funding of US $2.4 billion as of June 15, 2021. Only 4 out of the 50 identified publications associated with these DBCIs were fully powered randomized controlled trials (RCTs). Further, 1 of those 4 RCTs showed a significant difference in glycated hemoglobin A1c (HbA1c) outcomes between the intervention and control groups. However, all the studies reported HbA1c improvements ranging from 0.2% to 1.9% over the course of 12 months. In addition, 6 interventions were fully recognized by the DPRP to deliver evidence-based programs, and 2 interventions had a pending recognition status. Health professionals were included in the majority of DBCIs (13/16, 81%,), whereas only 10% (1/10) of accessible apps involved a CA as part of the intervention delivery. Self-reports represented most of the data sources (74/119, 62%) that could be used to tailor JITAIs.

CONCLUSIONS

Our findings suggest that the level of funding received by companies offering DBCIs for type 2 diabetes prevention and management does not coincide with the level of evidence on the intervention effectiveness. There is considerable variation in the level of evidence underpinning the different DBCIs and an overall need for more rigorous effectiveness trials and transparent reporting by quality assurance authorities. Currently, very few DBCIs use automated approaches such as CAs and JITAIs, limiting the scalability and reach of these solutions.

Counselor Efficiency at Providing Feedback in a Technology-Based Behavioral Weight Loss Intervention: Longitudinal Analysis

BACKGROUND

Feedback for participants' self-monitoring is a crucial and costly component of technology-based weight loss interventions. Detailed examination of interventionist time when reviewing and providing feedback for online self-monitoring data is lacking.

OBJECTIVE

The aim of this study was to longitudinally examine the time counselors spent providing feedback on participant self-monitoring data (ie, diet, physical activity, weight) in a 12-month technology-based weight loss intervention. We hypothesized that counselors would compose feedback for participants more quickly over time.

METHODS

The time the lay counselors (N=10) spent reviewing self-monitoring records and providing feedback to participants via email was longitudinally examined for all counselors across the three years of study implementation. Descriptives were observed for counselor feedback duration across counselors by 12 annual quarters (ie, 3-month periods). Differences in overall duration times by each consecutive annual quarter were analyzed using Wilcoxon-Mann-Whitney tests.

RESULTS

There was a decrease in counselor feedback duration from the first to second quarter (mean 53 to 46 minutes; P<.001), and from the second to third (mean 46 to 30 minutes; P<.001). A trend suggested a decrease from the third to fourth quarter (mean 30 to 26 minutes; P=.053), but no changes were found in subsequent quarters. Consistent with the hypothesis, counselors may be increasing their efficiency in providing feedback; across 12 months, counselors spent less time reviewing participant self-monitoring and composing feedback (decreasing from mean 53 to 26 minutes).

CONCLUSIONS

Counselors used increasingly less time to review online self-monitoring data and compose feedback after the initial 9 months of study implementation. Results inform counselor costs for future technology-based behavioral weight loss interventions. For example, regardless of increasing counselor efficiency, 25-30 minutes per feedback message is a high cost for interventions. One possibility for reducing costs would be generating computer-automated feedback.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02063178; https://clinicaltrials.gov/ct2/show/NCT02063178.

A Systematic Review of Cost-Effectiveness Studies of Interventions With a Personalized Nutrition Component in Adults

OBJECTIVES

Important links between dietary patterns and diseases have been widely applied to establish nutrition interventions. However, knowledge about between-person heterogeneity regarding the benefits of nutrition intervention can be used to personalize the intervention and thereby improve health outcomes and efficiency. We performed a systematic review of cost-effectiveness analyses (CEAs) of interventions with a personalized nutrition (PN) component to assess their methodology and findings.

METHODS

A systematic search (March 2019) was performed in 5 databases: EMBASE, Medline Ovid, Web of Science, Cochrane CENTRAL, and Google Scholar. CEAs involving interventions in adults with a PN component were included; CEAs focusing on clinical nutrition or undernutrition were excluded. The CHEERS checklist was used to assess the quality of CEAs.

RESULTS

We identified 49 eligible studies among 1792 unique records. Substantial variation in methodology was found. Most studies (91%) focused only on psychological concepts of PN such as behavior and preferences. Thirty-four CEAs were trial-based, 13 were modeling studies, and 4 studies were both trial- and model-based. Thirty-two studies used quality-adjusted life year as an outcome measure. Different time horizons, comparators, and modeling assumptions were applied, leading to differences in costs/quality-adjusted life years. Twenty-eight CEAs (49%) concluded that the intervention was cost-effective, and 75% of the incremental cost-utility ratios were cost-effective given a willingness-to-pay threshold of $50 000 per quality-adjusted life year.

CONCLUSIONS

Interventions with PN components are often evaluated using various types of models. However, most PN interventions have been considered cost-effective. More studies should examine the cost-effectiveness of PN interventions that combine psychological and biological concepts of personalization.

Effect of an Online Weight Management Program Integrated With Population Health Management on Weight Change: A Randomized Clinical Trial

IMPORTANCE

Online programs may help with weight loss but have not been widely implemented in routine primary care.

OBJECTIVE

To compare the effectiveness of a combined intervention, including an online weight management program plus population health management, with the online program only and with usual care.

DESIGN, SETTING, AND PARTICIPANTS

Cluster randomized trial with enrollment from July 19, 2016, through August 10, 2017, at 15 primary care practices in the US. Eligible participants had a scheduled primary care visit and were aged 20 to 70 years, had a body mass index between 27 and less than 40, and had a diagnosis of hypertension or type 2 diabetes. Follow-up ended on May 8, 2019.

INTERVENTIONS

Participants in the usual care group (n = 326) were mailed general information about weight management. Participants in the online program only group (n = 216) and the combined intervention group (n = 298) were registered for the online program. The participants in the combined intervention group also received weight-related population health management, which included additional support from nonclinical staff who monitored their progress in the online program and conducted periodic outreach.

MAIN OUTCOMES AND MEASURES

The primary outcome was weight change at 12 months based on measured weights recorded in the electronic health record. Weight change at 18 months was a secondary outcome.

RESULTS

Among the 840 participants who enrolled (mean age, 59.3 years [SD, 8.6 years]; 60% female; 76.8% White), 732 (87.1%) had a recorded weight at 12 months and the missing weights for the remaining participants were imputed. There was a significant difference in weight change at 12 months by group with a mean weight change of -1.2 kg (95% CI, -2.1 to -0.3 kg) in the usual care group, -1.9 kg (95% CI, -2.6 to -1.1 kg) in the online program only group, and -3.1 kg (95% CI, -3.7 to -2.5 kg) in the combined intervention group (P < .001). The difference in weight change between the combined intervention group and the usual care group was -1.9 kg (97.5% CI, -2.9 to -0.9 kg; P < .001) and the difference between the combined intervention group and the online program only group was -1.2 kg (95% CI, -2.2 to -0.3 kg; P = .01). At 18 months, the mean weight change was -1.9 kg (95% CI, -2.8 to -1.0 kg) in the usual care group, -1.1 kg (95% CI, -2.0 to -0.3 kg) in the online program only group, and -2.8 kg (95% CI, -3.5 to -2.0 kg) in the combined intervention group (P < .001).

CONCLUSIONS AND RELEVANCE

Among primary care patients with overweight or obesity and hypertension or type 2 diabetes, combining population health management with an online program resulted in a small but statistically significant greater weight loss at 12 months compared with usual care or the online program only. Further research is needed to understand the generalizability, scalability, and durability of these findings.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02656693.

Evaluation of the scale-up and implementation of mind, exercise, nutrition … do it! (MEND) in British Columbia: a hybrid trial type 3 evaluation

BACKGROUND

The Mind, Exercise, Nutrition … Do it! (MEND) childhood obesity intervention was implemented in British Columbia (B.C.), Canada from April 2013 to June 2017. The study objective was: a) to describe and explore program reach, attendance, satisfaction, acceptability, fidelity, and facilitators and challenges during scale-up and implementation of MEND in B.C. while b) monitoring program effectiveness in improving children's body mass index (BMI) z-score, waist circumference, dietary and physical activity behaviours, and psychological well-being.

METHODS

This prospective, pragmatic implementation evaluation (Hybrid Type 3 design) recruited families with children and adolescents aged 7-13 with a BMI ≥ 85th percentile for age and sex. The 10-week MEND B.C. program was delivered in 27 sites, throughout all five B.C. health regions (Northern, Interior, Island, Fraser, and Vancouver Coastal) over 4 years. Families attended two weekly in-person group sessions aimed to increase physical activity and promote healthy eating. BMI z-score and waist circumference were measured at baseline and follow-up. Dietary and physical activity behaviours and psychological well-being were measured using validated questionnaires. A mixed-method approach was used to collect and analyze the data.

RESULTS

One hundred thirty-six MEND B.C. programs were delivered over 4 years. The program reached 987 eligible participants. 755 (76.5%) children and adolescents completed the program. The average program attendance was 81.5%. Parents reported the program content was easy to understand, culturally suitable, respectful of family's financial situation, and provided adequate information to build a healthy lifestyle. Children achieved significant positive changes across all four evaluation years in BMI z-score (d = - 0.13), nutrition behaviours (d = 0.64), physical activity levels (d = 0.30), hours of screen time per week (d = - 0.38) and emotional distress (d = - 0.21). Challenges to continued program implementation included: recruitment, resource requirement for implementation, and the need to tailor the program locally to be more flexible and culturally relevant.

CONCLUSIONS

The program reached a broad demographic of children and adolescents in B.C. Families were highly satisfied with the program delivery. MEND. B.C. at scale was effective across all four evaluation years in improving BMI z-score, lifestyle behaviours and psychological well-being among children. Future interventions need to explore strategies to enhance program delivery flexibility.

Cost of behavioral weight loss programs implemented in clinical practice: The POWER trial at Johns Hopkins

Obesity presents an important public health problem that affects more than a third of the U.S. adult population and that is associated with increased morbidity, mortality, and costs. Previously, we documented that two primary care-based weight loss interventions were clinically effective. To encourage the implementation of and reimbursement for these interventions, we evaluated their relative cost-effectiveness. We performed a cost analysis of the Practice-based Opportunities for Weight Reduction (POWER) trial, a three-arm trial that enrolled 415 patients with obesity from six primary care practices. Trial participants were randomized to a control arm, an in-person support intervention, or a remote support intervention; in the two intervention arms, behavioral interventions were delivered over 24 months, in two phases. Weight loss was measured at 6, 12, and 24 months. Using timesheets and empirical data, we evaluated the cost of the in-person and remote support interventions from the perspective of a health care system delivering the interventions. A univariate sensitivity analysis was conducted to evaluate uncertainty around model assumptions. All comparisons were tested using independent t-tests. Cost of the in-person intervention was higher at 6 months ($113 per participant per month and $117 per kg lost) than the remote support intervention ($101 per participant per month and $99 per kg lost; p < .001). Costs were also higher for the in-person support intervention at 24 months ($73 per participant per month and $342 per kg lost) than for the remote support intervention ($53 per participant per month and $275 per kg lost; p < .001). In the sensitivity analyses, cost ranged from $274/kg lost to $456/kg lost for the in-person support intervention and from $218/kg to $367/kg lost for the remote support intervention. A primary care weight loss intervention administered remotely was relatively more cost-effective than an in-person intervention. Expanding the scope of reimbursable programs to include other cost-effective interventions could help ensure that a broader range of patients receive the type of support needed.

Cost-Effectiveness of a Weight Loss Intervention: An Adaptation of the Look AHEAD Lifestyle Intervention in the US Military

OBJECTIVE

This study aimed to assess whether a counselor-initiated (CI) adaptation of the Look AHEAD (Action for Health in Diabetes) intensive lifestyle intervention in a military setting was cost-effective relative to a self-paced (SP) adaptation.

METHODS

A cost-effectiveness analysis from a payer perspective was performed alongside a 2014-2017 randomized behavioral weight loss trial among 248 active-duty military personnel stationed at a US Air Force base in Texas. Incremental cost-effectiveness ratios were calculated for weight loss, reductions in waist circumference, and quality-adjusted life-years (QALYs).

RESULTS

After 12 months, the CI adaptation cost more per participant compared with the SP adaptation ($1,081 vs. $120) but achieved greater weight loss (1.86 kg vs. 0.06 kg), greater reductions in waist circumference (1.85 cm vs. 0.48 cm), and more QALYs (0.871 vs. 0.856). The incremental cost-effectiveness ratio for the CI adaptation relative to the SP adaptation was $61,268 per additional QALY. At willingness-to-pay thresholds of $50,000 and $100,000 per QALY, the CI adaptation was 45% and 49% likely to be cost-effective, respectively.

CONCLUSIONS

The CI delivery of the Look AHEAD Intensive Lifestyle Intervention may offer a cost-effective approach to tackle excess weight in the US military.

A Systematic Review of Methods to Predict Weight Trajectories in Health Economic Models of Behavioral Weight-Management Programs: The Potential Role of Psychosocial Factors

Objectives. There is limited evidence on the long-term effectiveness of behavioral weight-management interventions, and thus, when conducting health economic modeling, assumptions are made about weight trajectories. The aims of this review were to examine these assumptions made about weight trajectories, the evidence sources used to justify them, and the impact of assumptions on estimated cost-effectiveness. Given the evidence that some psychosocial variables are associated with weight-loss trajectories, we also aimed to examine the extent to which psychosocial variables have been used to estimate weight trajectories and whether psychosocial variables were measured within cited evidence sources. Methods. A search of databases (Medline, PubMed, Cochrane, NHS Economic Evaluation, Embase, PSYCinfo, CINAHL, EconLit) was conducted using keywords related to overweight, weight-management, and economic evaluation. Economic evaluations of weight-management interventions that included modeling beyond trial data were included. Results. Within the 38 eligible articles, 6 types of assumptions were reported (weight loss maintained, weight loss regained immediately, linear weight regain, subgroup-specific trajectories, exponential decay of effect, maintenance followed by regain). Fifteen articles cited at least 1 evidence source to support the assumption reported. The assumption used affected the assessment of cost-effectiveness in 9 of the 19 studies that tested this in sensitivity analyses. None of the articles reported using psychosocial factors to estimate weight trajectories. However, psychosocial factors were measured in evidence sources cited by 11 health economic models. Conclusions. Given the range of weight trajectories reported and the potential impact on funding decisions, further research is warranted to investigate how psychosocial variables measured in trials can be used within health economic models to simulate heterogeneous weight trajectories and potentially improve the accuracy of cost-effectiveness estimates.

Behavior stages of a physician- and coach-supported cloud-based diabetes prevention program for people with prediabetes

Introduction:

Centers for Disease Control and Prevention Diabetes Prevention Program recognition requires successful program completion by a cohort of at least five people with prediabetes. Such programs have generally been “in-person” and provided by a qualified coach from a recognized program. A cohort of 10 patients with prediabetes was enrolled in a physician’s office to use the cloud-based Type II Diabetes Prevention Module in an effort to achieve recognition. Module use was supported by the physician and a qualified coach. The purpose of this article is to evaluate Module performance relative to behavior stages associated with long-term behavior modification.

Methods:

The Module employs a web application supporting diabetes prevention education and a mobile application that is an electronic diary and virtual coach. A dashboard allows an efficient review of user performance and the ability to send users notifications of support from the user’s coach or physician. The cohort of 10 patients with prediabetes was offered Module use upon diagnosis of prediabetes.

Results:

All 10 patients with prediabetes offered Module use agreed participation. Six have completed educational sessions, made diary entries, and have met the 5% Centers for Disease Control and Prevention Diabetes Prevention Program weight loss target prior to 6 months of Module use. This high success rate (60%) is contrary to behavior stages often associated with long-term behavior modification.

Conclusion:

The strength of the physician–patient relationship appears to allow patients with prediabetes to skip or advance rapidly through behavioral stages in the process of lifestyle modification.

Outcomes of a Digital Health Program With Human Coaching for Diabetes Risk Reduction in a Medicare Population

OBJECTIVE

To examine the outcomes of a Medicare population who participated in a program combining digital health with human coaching for diabetes risk reduction.

METHOD

People at risk for diabetes enrolled in a program combining digital health with human coaching. Participation and health outcomes were examined at 16 weeks and 6 and 12 months.

RESULTS

A total of 501 participants enrolled; 92% completed at least nine of 16 core lessons. Participants averaged 19 of 31 possible opportunities for weekly program engagement. At 12 months, participants lost 7.5% ( SD = 7.8%) of initial body weight; among participants with clinical data, glucose control improved (glycosylated hemoglobin [HbA1c] change = -0.14%, p = .001) and total cholesterol decreased (-7.08 mg/dL, p = .008). Self-reported well-being, depression, and self-care improved ( p < .0001).

DISCUSSION

This Medicare population demonstrated sustained program engagement and improved weight, health, and well-being. The findings support digital programs with human coaching for reducing chronic disease risk among older adults.

A Review of Technology-Assisted Interventions for Diabetes Prevention

PURPOSE OF REVIEW

The high prevalence of prediabetes and success of the diabetes prevention program (DPP) has led to increasing efforts to provide readily accessible, cost-effective DPP interventions to the general public. Technology-assisted DPP interventions are of particular interest since they may be easier to widely distribute and sustain as compared to traditional in-person DPP. The purpose of this article is to provide an overview of currently available technology-assisted DPP interventions.

RECENT FINDINGS

This review focuses on studies that have examined the use of mobile phone text messaging, smartphone/web-based apps, and telehealth programs to help prevent or delay the onset of incident type 2 diabetes. While there is variability in the results of studies focused on technology-assisted DPP and weight loss interventions, there is evidence to suggest that these programs have been associated with clinically meaningful weight loss and can be cost-effective. Patients who are at risk for diabetes can be offered technology-assisted DPP and weight loss interventions to lower their risk of incident diabetes. Further research should determine what specific combination of intervention features would be most successful.

Lessons from Launching the Diabetes Prevention Program in a Large Integrated Health Care Delivery System: A Case Study

There is urgent need for health systems to prevent diabetes. To date, few health systems have implemented the evidence-based Diabetes Prevention Program (DPP), and the few that have mostly partnered with community-based organizations to implement the program. Given the recent decision by the Centers for Medicare & Medicaid Services to reimburse for diabetes prevention, there is likely much interest in how such programs can be implemented within large health systems or how community partnerships can be expanded to support DPP implementation. Beginning in 2010, Montefiore Health System (MHS), a large health care system in the Bronx, NY, partnered with the Young Men's Christian Association (YMCA) of Greater New York to deliver the YMCA's DPP. Over 4 years, 1390 referrals to YMCA's DPP were made; 287 participants attended ≥3 classes, and average weight loss was 3.4%. Because of increased patient demand and internal capacity, MHS assumed responsibility for DPP implementation in May 2015. Fully integrating the program within the health system took 5–6 months, including configuring electronic health record templates/reports, hiring a coordinator, and creating clinical referral workflows/training guides. Billing workflows were designed for risk-based contracts. In the first 11 months of implementation, 1277 referrals were made, and referrals increased over time. Twenty-four class cycles were initiated, and 282 patients began attending classes. Average weight loss among 61 graduates from the Summer/Fall 2015 wave of MDPP classes was 3.8%. Additional opportunities for expansion include training allied health staff, providing patient incentives, increasing master trainer capacity, offering DPP to employees, and securing reimbursement.