Background Personalized feedback is an effective behavior change technique frequently incorporated into mobile health (mHealth) apps. Innovations in data science create opportunities for leveraging the wealth of user data accumulated by mHealth apps to generate personalized health forecasts. One Drop’s digital program is one of the first to implement blood glucose forecasts for people with type 2 diabetes. The impact of these forecasts on behavior and glycemic management has not been evaluated to date. Objective This study sought to evaluate the impact of exposure to blood glucose forecasts on blood glucose logging behavior, average blood glucose, and percentage of glucose points in range. Methods This retrospective cohort study examined people with type 2 diabetes who first began using One Drop to record their blood glucose between 2019 and 2021. Cohorts included those who received blood glucose forecasts and those who did not receive forecasts. The cohorts were compared to evaluate the effect of exposure to blood glucose forecasts on logging activity, average glucose, and percentage of glucose readings in range, after controlling for potential confounding factors. Data were analyzed using analysis of covariance (ANCOVA) and regression analyses. Results Data from a total of 1411 One Drop users with type 2 diabetes and elevated baseline glucose were analyzed. Participants (60.6% male, 795/1311; mean age 50.2 years, SD 11.8) had diabetes for 7.1 years on average (SD 7.9). After controlling for potential confounding factors, blood glucose forecasts were associated with more frequent blood glucose logging (P=.004), lower average blood glucose (P<.001), and a higher percentage of readings in range (P=.03) after 12 weeks. Blood glucose logging partially mediated the relationship between exposure to forecasts and average glucose. Conclusions Individuals who received blood glucose forecasts had significantly lower average glucose, with a greater amount of glucose measurements in a healthy range after 12 weeks compared to those who did not receive forecasts. Glucose logging was identified as a partial mediator of the relationship between forecast exposure and week-12 average glucose, highlighting a potential mechanism through which glucose forecasts exert their effect. When administered as a part of a comprehensive mHealth program, blood glucose forecasts may significantly improve glycemic management among people living with type 2 diabetes.
In the current financial climate, health care institutions and providers experience substantial challenges in achieving the Triple Aim in health care reform (i.e., reducing costs, improving health, improving care). The present study describes the successes and challenges of garnering payment for a population health program, Novel Interventions in Children's Health care (NICH), for youth with both medical and social vulnerability. Using 4 real patient scenarios, this study provides examples of how to use economic data to demonstrate program value to key stakeholders (i.e., insurance providers, hospital administrators) and obtain authorization and payment for services. Health care utilization and cost data were retrieved through retrospective review of patient medical records and hospital financial records. NICH utilized distinct strategies to overcome systemic barriers, demonstrate value, and show need for intervention to key stakeholders. Strategies included highlighting patients': (a) history of utilization, (b) accumulated medical expenditures, (c) projected costs for anticipated procedures, and (d) social risk linked to poor health and high utilization. We describe each effort using real patient scenarios that feature varied medical conditions including Type 1 diabetes, chronic pain, and failure-to-thrive. Economic data can be a useful tool in garnering support for behavioral health interventions. And while these data offer programs like NICH the opportunity to make the case for investing in an alternative intervention, the strategies utilized by NICH to advocate for services can be applied by pediatric psychologists working with youth with medical complexity and social vulnerability. Implications for Impact StatementIn order to increase service access for individuals, families, and medical teams in an ever-changing fiscal environment, psychologists and other behavioral health providers should be prepared to highlight the financial value of their efforts to health care systems and payers. This article provides (a) an example of how a behavioral health program can identify and collect economically relevant data and (b) strategies that use economic data to convince payers to authorize and evaluate the services of such programs. For each of these strategies, we provide real patient scenarios to better illustrate how behavioral health providers can make a compelling case for intervention programs through the strategic presentation of medical, social, and economic data.
Improving diabetes management skills and reducing diabetes-related distress in working adults with type 2 diabetes has implications for work-related outcomes including work productivity. Digital health programs have the potential to positively impact diabetes management and, in turn, improve the productivity of working-age adults.
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