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

Cost-Effectiveness Analysis of a Prescription Digital Therapeutic in Type 2 Diabetes

INTRODUCTION

BT-001 (AspyreRx™) prescription digital therapy, a form of personalized cognitive behavioral therapy, has demonstrated clinically meaningful and durable hemoglobin A1c reductions in patients with type 2 diabetes (T2D). The current study examined the cost-effectiveness of BT-001 plus standard of care (SoC) versus SoC alone in T2D over a lifetime horizon from a healthcare payer perspective.

METHODS

We modeled the T2D pathway using an individual patient-level simulation; clinical data were sourced from the intention-to-treat subset of the BT-001 randomized clinical trial (RCT). SoC across both arms included the composition of oral and injectable treatments for T2D. Events were simulated using the United Kingdom Prospective Diabetes Study Outcomes Model 2 risk equation. A 3-month model cycle length was used in the first year, then annual model cycles were used in line with the original risk engine specifications. Patient characteristics informed event equations and Monte Carlo random sampling was used to assess the occurrence of events within each model cycle. Incidence of hypoglycemic events, drug discontinuation, costs, and health utilities and disutility values were sourced from the literature.

RESULTS

From a payer perspective, BT-001 plus SoC versus SoC alone was dominant with a gain in quality-adjusted life years (QALYs) of 0.101 and cost savings of $7343 per patient over the lifetime horizon (i.e., more effective and less costly). BT-001 plus SoC was cost-effective at a willingness-to-pay of $100,000 per QALY (incremental net monetary benefit was $17,443). Savings with BT-001 were primarily driven by a reduction in drug acquisition costs. The reduction in hemoglobin A1c with BT-001 was associated with fewer T2D complications.

CONCLUSIONS

BT-001 plus SoC was estimated to dominate SoC alone over the lifetime horizon from a payer perspective, suggesting that using BT-001 can empower patients to better manage their diabetes with the potential for lifelong advantages.

Design and Early Use of the Nationally Implemented Healthier You National Health Service Digital Diabetes Prevention Programme: Mixed Methods Study

BACKGROUND

The Healthier You National Health Service Digital Diabetes Prevention Programme (NHS-digital-DPP) is a 9-month digital behavior change intervention delivered by 4 independent providers that is implemented nationally across England. No studies have explored the design features included by service providers of digital diabetes prevention programs to promote engagement, and little is known about how participants of nationally implemented digital diabetes prevention programs such as this one make use of them.

OBJECTIVE

This study aimed to understand engagement with the NHS-digital-DPP. The specific objectives were to describe how engagement with the NHS-digital-DPP is promoted via design features and strategies and describe participants' early engagement with the NHS-digital-DPP apps.

METHODS

Mixed methods were used. The qualitative study was a secondary analysis of documents detailing the NHS-digital-DPP intervention design and interviews with program developers (n=6). Data were deductively coded according to an established framework of engagement with digital health interventions. For the quantitative study, anonymous use data collected over 9 months for each provider representing participants' first 30 days of use of the apps were obtained for participants enrolled in the NHS-digital-DPP. Use data fields were categorized into 4 intervention features (Track, Learn, Coach Interactions, and Peer Support). The amount of engagement with the intervention features was calculated for the entire cohort, and the differences between providers were explored statistically.

RESULTS

Data were available for 12,857 participants who enrolled in the NHS-digital-DPP during the data collection phase. Overall, 94.37% (12,133/12,857) of those enrolled engaged with the apps in the first 30 days. The median (IQR) number of days of use was 11 (2-25). Track features were engaged with the most (number of tracking events: median 46, IQR 3-22), and Peer Support features were the least engaged with, a median value of 0 (IQR 0-0). Differences in engagement with features were observed across providers. Qualitative findings offer explanations for the variations, including suggesting the importance of health coaches, reminders, and regular content updates to facilitate early engagement.

CONCLUSIONS

Almost all participants in the NHS-digital-DPP started using the apps. Differences across providers identified by the mixed methods analysis provide the opportunity to identify features that are important for engagement with digital health interventions and could inform the design of other digital behavior change interventions.

Outpatient compared to inpatient thyroidectomy on 30-day postoperative outcomes: a national propensity matched analysis

BACKGROUND

To address the postoperative outcomes between outpatient and inpatient neck surgery involving thyroidectomy procedures.

METHODS

A cohort analysis of surgical patients undergoing primary, elective, total thyroidectomy from multiple United States medical institutions who were registered with the American College of Surgeons National Surgical Quality Improvement Program from 2015 to 2018. The primary outcome was a composite score that included any 30-day postoperative adverse event.

RESULTS

A total of 55,381 patients who underwent a total thyroidectomy were identified comprising of 14,055 inpatient and 41,326 outpatient procedures. A cohort of 13,496 patients who underwent outpatient surgery were propensity matched for covariates with corresponding number of patients who underwent inpatient thyroidectomies. In the propensity matched cohort, the occurrence of any 30-day after surgery complications were greater in the inpatient group, 424 out of 13,496 (3.1%) compared to the outpatient group, 150 out of 13,496 (1.1%), P < 0.001. Moreover, death rates were greater in the inpatient group, 22 out 13,496 (0.16%) compared to the outpatient group, 2 out of 13,496 (0.01%), P < 0.001. Similarly, hospital readmissions occurred with greater frequency in the inpatient group, 438 out of 13,496 (3.2%) compared to the outpatient group, 310 out of 13,496 (2.3%), P < 0.001.

CONCLUSION

Thyroidectomy procedures performed in the outpatient setting had less rates of adverse events, including serious postoperative complications (e.g., surgical site infection, pneumonia, progressive renal insufficiency). In addition, patients who had thyroidectomy in the outpatient setting had less 30-day readmissions and mortality. Surgeons should recognize the benefits of outpatient thyroidectomy when selecting disposition of patients undergoing neck surgery.

Adverse events among persons with TB using in-person vs. electronic directly observed therapy

BACKGROUND: We evaluated patient safety within a randomized crossover trial comparing electronic directly observed therapy (eDOT) to in-person DOT (ipDOT) in persons undergoing TB treatment in New York City, NY, USA.METHODS: Participant symptoms, symptom severity, and clinical management were documented. We assessed adverse event reports (AERs) by DOT method during the two-period crossover. Using Cox proportional-hazards mixed-effects models, we estimated the adjusted hazard ratio (aHR) of participants reporting an adverse event (AE) vs. not reporting an AE.RESULTS: Of 211 participants, 57 (27.0%) reported AEs during the two-period crossover; of these, 54.4% (31/57) were reported while using eDOT vs. 45.6% (26/57) while using ipDOT. Controlling for study group and period, the aHR for eDOT vs. ipDOT was 0.98 (95% CI 0.49-1.93). Although statistically not significant, the wide confidence intervals suggest that a significant association cannot be entirely ruled out. Gastrointestinal symptoms were most frequently reported (42.1%, 24/57). AER types and severity did not differ significantly by DOT method. Days from symptom onset to medical attention was similar across DOT methods (median: 1.0 day, IQR 0.0-2.0). No participants switched DOT methods due to AERs or monitoring concerns.CONCLUSION: Further evaluation to ascertain whether AERs differ when patients use eDOT vs. ipDOT is warranted.

Economic Evaluation Associated With Clinical-Grade Mobile App-Based Digital Therapeutic Interventions: Systematic Review

BACKGROUND

Digital therapeutics (DTx), a class of software-based clinical interventions, are promising new technologies that can potentially prevent, manage, or treat a spectrum of medical disorders and diseases as well as deliver unprecedented portability for patients and scalability for health care providers. Their adoption and implementation were accelerated by the need for remote care during the COVID-19 pandemic, and awareness about their utility has rapidly grown among providers, payers, and regulators. Despite this, relatively little is known about the capacity of DTx to provide economic value in care.

OBJECTIVE

This study aimed to systematically review and summarize the published evidence regarding the cost-effectiveness of clinical-grade mobile app-based DTx and explore the factors affecting such evaluations.

METHODS

A systematic review of economic evaluations of clinical-grade mobile app-based DTx was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. Major electronic databases, including PubMed, Cochrane Library, and Web of Science, were searched for eligible studies published from inception to October 28, 2022. Two independent reviewers evaluated the eligibility of all the retrieved articles for inclusion in the review. Methodological quality and risk of bias were assessed for each included study.

RESULTS

A total of 18 studies were included in this review. Of the 18 studies, 7 (39%) were nonrandomized study-based economic evaluations, 6 (33%) were model-based evaluations, and 5 (28%) were randomized clinical trial-based evaluations. The DTx intervention subject to assessment was found to be cost-effective in 12 (67%) studies, cost saving in 5 (28%) studies, and cost-effective in 1 (6%) study in only 1 of the 3 countries where it was being deployed in the final study. Qualitative deficiencies in methodology and substantial potential for bias, including risks of performance bias and selection bias in participant recruitment, were identified in several included studies.

CONCLUSIONS

This systematic review supports the thesis that DTx interventions offer potential economic benefits. However, DTx economic analyses conducted to date exhibit important methodological shortcomings that must be addressed in future evaluations to reduce the uncertainty surrounding the widespread adoption of DTx interventions.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42022358616; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022358616.

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

OBJECTIVE

To examine changes in cardiovascular disease (CVD) risk outcomes of overweight/obese adults with prediabetes.

METHODS

Using 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.

RESULTS

We 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.

CONCLUSIONS

Our 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.

An Economic Impact Model for Estimating the Value to Health Systems of a Digital Intervention for Diabetes Primary Care: Development and Usefulness Study

Background

Diabetes is associated with significant long-term costs for both patients and health systems. Regular primary care visits aligned with American Diabetes Association guidelines could help mitigate those costs while generating near-term revenue for health systems. Digital interventions prompting primary care visits among unengaged patients could provide significant economic value back to the health system as well as individual patients, but only few economic models have been put forth to understand this value.

Objective

Our objective is to establish a data-based method to estimate the economic impact to a health system of interventions promoting primary care visits for people with diabetes who have been historically unengaged with their care. The model was built with a focus on a specific digital health intervention, Precision Nudging, but can be used to quantify the value of other interventions driving primary care usage among patients with diabetes.

Methods

We developed an economic model to estimate the financial value of a primary care visit of a patient with diabetes to the health system. This model requires segmenting patients with diabetes according to their level of blood sugar control as measured by their most recent hemoglobin A_1c value to understand how frequently they should be visiting a primary care provider. The model also accounts for the payer mix among the population with diabetes, documenting the percentage of insurance coverage through a commercial plan, Medicare, or Medicaid, as these influence the reimbursement rates for the services. Then, the model takes into consideration the population base rates of comorbid conditions for patients with diabetes and the associated current procedural terminology codes to understand what a provider can bill as well as the expected inpatient revenue from a subset of patients likely to require hospitalization based on the national hospitalization rates for people with diabetes. Physician reimbursement is subtracted from the total. Finally, the model also accounts for the level of patient engagement with the intervention to ensure a realistic estimate of the impact.

Results

We present a model to prospectively estimate the economic impact of a digital health intervention to encourage patients with documented diabetes diagnoses to attend primary care visits. The model leverages both publicly available and health system data to calculate the per appointment value (revenue) to the health system. The model offers a method to understand and test the financial impact of Precision Nudging or other primary care–focused diabetes interventions inclusive of costs driven by comorbid conditions.

Conclusions

The proposed economic model can help health systems understand and evaluate the estimated economic benefits of interventions focused on primary care and prevention for patients with diabetes as well as help intervention developers determine pricing for their product.

mHealth prompts within diabetes prevention programs: a scoping review

BACKGROUND

Mobile health (mHealth) prompts (e.g., text messaging, push notifications) are a commonly used technique within behaviour change interventions to prompt or cue a specific behaviour. Such prompts are being increasingly integrated into diabetes prevention programs (DPPs). While mHealth prompts provide a convenient and cost-effective way to reinforce behaviour change, no reviews to date have examined mHealth prompt use within DPPs. This scoping review aims to: (I) understand how mHealth prompts are being used within behaviour change interventions for individuals at risk for developing type 2 diabetes (T2D); and (II) provide recommendations for future mHealth prompt research, design, and application.

METHODS

The scoping review methodology outlined by Arksey and O'Malley were followed. Medline, CINAHL, PsycInfo, Web of Science, and SportDiscus were searched. The search strategy combined keywords relating to T2D risk and mHealth prompts in conjunction with database-controlled vocabulary when available (e.g., MeSH for Medline).

RESULTS

Of the 4,325 publications screened, 44 publications (based on 33 studies) met the inclusion criteria and were included for data extraction. Text messaging was the most widely used mHealth prompt (73%) followed by push notifications (21%). Only 30% of studies discussed the theoretical basis for prompt content and time of day messages were sent, and only 27% provided justification for prompt timing and frequency. Fourteen studies assessed participant satisfaction with mHealth prompts of which only two reported dissatisfaction due to either prompting frequency (hourly) or message content (solely focused on weight). Nine studies assessed behavioural outcomes including weight loss, physical activity, and diabetes incidence, and found mixed effects overall.

CONCLUSIONS

While mHealth prompts were well-received by participants, there are mixed effects on the influence of mHealth prompts on behavioural outcomes and diabetes incidence. More thorough reporting of prompt content development and delivery is needed, and more experimental research is needed to identify optimal content, delivery characteristics, and impact on behavioural and clinical outcomes.

Development and testing of a digital health acceptability model to explain the intention to use a digital diabetes prevention programme

OBJECTIVES

Digitally-delivered diabetes prevention programmes (DPPs) may improve population health by reversing the escalating trend of type 2 diabetes (T2D) incidence. Understanding the factors which determine digital health acceptability is critical to developing effective interventions. This study aimed to develop and test a digital health acceptability model of the factors influencing the intention of adults living in Ireland to use a digital DPP.

DESIGN

A 61-item cross-sectional survey was issued online or in hard copy to a sample of adults.

METHODS

Participants viewed a brochure for a smartphone-based digital DPP. The FINDRISC assessed their risk of developing T2D, and Likert scale items assessed the personal health, social influence, eHealth literacy, and intervention factors of the model. Structural equation modelling was used to assess the relationships between these factors.

RESULT

Three-hundred-and-sixteen eligible participants (M_age  = 36) completed the survey, 42% of which had a slightly elevated T2D risk or higher. Twelve direct factor relationships were statistically significant. Subjective norm had a moderate-to-large impact on T2D risk perceptions. Health status, perceived susceptibility to T2D, eHealth readiness, communicative eHealth literacy and image had significant impacts on use intentions through mediators of perceived ease of use and perceived usefulness. The model explained 65% of the variance in digital DPP use intentions.

CONCLUSION

Personal health beliefs, social influence, and eHealth literacy collectively influence a digital DPP's acceptability. These findings may inform the development of future digital DPPs and other digital health interventions. Future research should test the model with adults that have a higher T2D risk status.

The Effect of 24/7, Digital-First, NHS Primary Care on Acute Hospital Spending: Retrospective Observational Analysis

BACKGROUND

Digital health has the potential to revolutionize health care by improving accessibility, patient experience, outcomes, productivity, safety, and cost efficiency. In England, the NHS (National Health Service) Long Term Plan promised the right to access digital-first primary care by March 31, 2024. However, there are few global, fully digital-first providers and limited research into their effects on cost from a health system perspective.

OBJECTIVE

The aim of this study was to evaluate the impact of highly accessible, digital-first primary care on acute hospital spending.

METHODS

A retrospective, observational analysis compared acute hospital spending on patients registered to a 24/7, digital-first model of NHS primary care with that on patients registered to all other practices in North West London Collaboration of Clinical Commissioning Groups. Acute hospital spending data per practice were obtained under a freedom of information request. Three versions of NHS techniques designed to fairly allocate funding according to need were used to standardize or "weight" the practice populations; hence, there are 3 results for each year. The weighting adjusted the populations for characteristics that impact health care spending, such as age, sex, and deprivation. The total spending was divided by the number of standardized or weighted patients to give the spending per weighted patient, which was used to compare the 2 groups in the NHS financial years (FY) 2018-2019 (FY18/19) and 2019-2020 (FY19/20). FY18/19 costs were adjusted for inflation, so they were comparable with the values of FY19/20.

RESULTS

The NHS spending on acute hospital care for 2.43 million and 2.54 million people (FY18/19 and FY19/20) across 358 practices and 49 primary care networks was £1.6 billion and £1.65 billion (a currency exchange rate of £1=US $1.38 is applicable), respectively. The spending on acute care per weighted patient for Babylon GP at Hand members was 12%, 31%, and 54% (£93, P=.047; £223, P<.001; and £389, P<.001) lower than the regional average in FY18/19 for the 3 weighting methodologies used. In FY19/20, it was 15%, 35%, and 51% (£114, P=.006; £246, P<.001; and £362, P<.001) lower. This amounted to lower costs for the Babylon GP at Hand population of £1.37, £4.40 million, and £11.6 million, respectively, in FY18/19; and £3.26 million, £9.54 million, and £18.8 million, respectively, in FY19/20.

CONCLUSIONS

Patients with access to 24/7, digital-first primary care incurred significantly lower acute hospital costs.