Anand Iyer, PhD, MBA, is a global digital health leader widely known for his experience and expertise with technology, strategy and regulatory policy. Dr. Iyer is the Chief Strategy Officer at Welldoc. He’s considered a visionary in this field and has played important roles in utilizing his novel thinking and deep expertise globally to move the field and use of digital health forward. He’s a founding member of the board of directors for the Digital Therapeutics Alliance (DTA).
In this Insights interview Dr. Iyer shares his insider’s perspective about the study detailed in on our recently released white paper, Estimating the Economic Impact of a Digital Therapeutic in Type 2 Diabetes.1
What was the main purpose of this study?
Dr. Iyer: Welldoc and IBM Watson Health™, formerly Truven Health Analytics®, set out to answer this question: Could we estimate the economic value, including healthcare expenditures and potential cost savings, of a digital health therapeutic with clinical outcomes? Going in we knew there was limited research in this area. We also knew there was a lack of established methods for translating clinical improvements, in this case reductions in A1c, into cost savings. Historically quantifying these cost savings has been difficult due, in part, to the chaotic nature of real-world data. One of our goals was to establish a defensible methodology by which this type of data could be analyzed for many diseases.
Through our earlier randomized control trials (RCT)2,3, we showed that the use of BlueStar to manage type 2 diabetes can lower A1c levels in the range of 2 points. In this study with Truven we wanted to take the next step–to study how the RCT results translate to healthcare cost savings and bend the cost curve. To answer this we turned to experts at Truven Health Analytics®. This study is part of our ongoing benchmarking in our work with the digital therapeutic BlueStar.
How was the study conducted?
Dr. Iyer: Welldoc provided the starting and ending A1c data from over 3,000 people with type 2 diabetes in our database who had been prescribed BlueStar by their healthcare providers–real world data. Of this population, about one quarter was Medicare eligible. Truven then used their annually updated MarketScan database to search for and use a matched population. Jointly we created a drop matrix to stratify and observe the impact of A1c drops on costs of care by producing a per-person, per-month assessment. The A1c reductions achieved were correlated with fractional cost differences associated with the range of diabetes-related healthcare costs.
What are the key learnings of this study for healthcare payers about cost savings with a Digital Therapeutic in type 2 diabetes?
Dr. Iyer: This analysis offers numerous learnings. For starters, we realized not everyone with diabetes gets their A1c measured according to recommended guidelines. In fact, very few people get their A1c measured four times per year. We also learned A1c is inherently a moving target metric. Related to our methodology, this meant we needed to divide our results into A1c bands (groupings) to enable comparisons between ages and stability and degree of glycemic stability/control and relate this to total costs of care. We learned that on a per-person annual basis cost savings were indeed a function of both the patients’ starting A1c as well as their A1c journey over the year. The precise methodology we used in this study says to others in the digital therapeutics industry who are also attempting to implement digital therapeutics, let’s be precise about our analyses. It also underscores the point that not all A1c drops in people with type 2 diabetes are economically equivalent. Various A1c drops can have different economic impacts on health costs. This, I believe, is a huge finding! Helping a person move, for example, from an A1c of 9% to 8% will produce greater healthcare cost savings than moving an A1c of 8% to 7%.
For healthcare payers our data points more precisely to patients with whom they’ll derive their biggest cost-savings – the biggest bang for their effort. Bottom line: go after people’s who’s A1c is above 9%. This data enables us to help payers look at their population and tell them precisely how much implementing a digital therapeutic, like BlueStar, among their population can bend their cost curve. This precision in turn allows the structuring of true risk- and value-based agreements.
What are the key learnings of this study for healthcare providers?
Dr. Iyer: This study tells us that for high cost patients with type 2 diabetes, implementing the use of a clinically proven digital therapeutic, like BlueStar, can absolutely be a game changer and should be an essential element of treatment pathways. In light of these results I believe that five years from now disease management guidelines will include digital therapeutics as an important element of treatment pathways. With digital therapeutics, health care providers, along with engaged patients, will be able to regularly track progress, provide real time feedback and rapidly progress treatment plans.
Where I believe the healthcare system then needs to advance is to be able to reward everyone, from providers to patients, for delivering improved care and achieving improved outcomes. On the converse providers who don’t integrate validated and guideline recommended digital therapeutics into care plans should be penalized for not taking advantage of these valuable care tools. This will pressure payers and providers to implement them.
As a visionary in digital therapeutics in healthcare, how would you like to see evidence from this white paper applied?
Dr. Iyer: Payers and providers want to get patients most in need of care the best care they can get them. This analysis1 can pave a pathway for value-based reimbursement that is tied to true healthcare outcomes. As leaders in this digital therapeutic space Welldoc would never have been able to conduct this study if we didn’t have confidence in the positive outcomes from our RCT.2,3 This real world data gives us further confidence in our RCT data.
I look at the process this way. Train stop one is the RCTs that showed positive outcomes. Train stop two is real-world data analysis. Train stop three is to confirm, as we did in this study, that our digital therapeutic, BlueStar, generates an economic value.
- WellDoc and Truven. White Paper: Estimating the Economic Impact of a Digital Therapeutic in Type 2 Diabetes: Correlating the A1C Reductions from WellDoc’s BlueStar with Cost Savings in US Payer Populations. Available for viewing and download here.
- Quinn C, Shardell M, Terrin M, et al. Cluster-randomized trial of mobile phone personalized behavioral intervention of blood glucose control. Diabetes Care 2011; 34(9);1933-1943.
- Quinn C, Clough SS, Minor JM, et al. WellDoc™ mobile diabetes management randomized controlled trial: change in clinical and behavioral outcomes and patient and physician satisfaction. Diabetes Technol Ther 2008;10(3);160-168.