It’s an important question if you’re an insurer, employer, or hospital system and you’re planning to buy a lot of it.
At the 2018 American Diabetes Association conference, we presented two posters showing how you can use GlucosePATH to determine a fair price to pay for two new Type 2 Diabetes medicines - Semaglutide (Ozempic) and Ertugliflozin (Steglatro) - for your specific patients, based on the cost and performance of every other Type 2 Diabetes medicine in your inventory.
For this project, the GlucosePATH software evaluated more than 1.5 billion treatment options using a 191-patient population of Type 2 Diabetes patients at a regional hospital. The GlucosePATH software considered how many times each patient would be prescribed the new medications, at price points that varied from $0 to $1,000.
At each price point, the software evaluated five factors for each treatment regimen:
With this analysis, the software was able to estimate the retail price of both semaglutide and ertugliflozin to within $25, before those medicines entered the market.
The chronic, progressive nature of Type 2 Diabetes often requires multi-drug treatment regimens. In these cases, the patient and physician must balance A1c control, side effects, and regimen complexity against the higher costs of multi-drug treatments.
In this poster presentation from the 2017 American Diabetes Association conference, we used the GlucosePATH software to show how the patient’s insurance coverage and monthly medication budget affect:
We also showed how the GlucosePATH software would adapt its treatment recommendations for the same population of patients under four different types of insurance coverage:
The presentation concludes with a case study showing how a self-insured regional employer with approximately 600 employees with Type 2 Diabetes can save more than $1 million annually on medication costs by using the GlucosePATH software for treatment recommendations.
Providers and patients are increasingly asked to manage the cost of therapy. Insurance coverage “tiering” and co-insurance models require the patient to make decisions that include risk, benefit, and cost to the patient and insurer.
The use of medication samples and aggressive manufacturer coupons can disrupt this balance. The patient’s need to reduce their out-of-pocket costs can conflict with the system’s carefully-negotiated formulary. Providers are caught in between beneficence and distributive justice.
For this 2017 American Association of Clinical Endocrinologists poster presentation, we use the GlucosePATH software to show how different insurance plans and manufacturer coupons determine which medication classes are recommended to patients.
In the section titled “Coupons Affect Who Pays For Coverage”, we show the effects of manufacturer coupons on average monthly patient and system costs:
Awarded 1st place at the 2016 American Association of Clinical Endocrinologists Conference poster competition
Providers face an enormous amount of complexity when creating appropriate treatments regimens for patients with Type 2 Diabetes. With over 60 medicines available, there are more than 6 million different ways to create regimens of 1 to 5 medicines. We shouldn’t expect providers to do that in their head.
Another problem facing providers is the complex nature of patient insurance coverage. There are more than 42,000 publicly available insurance plans in the United States, each with their own coverage rules and drug co-pays. We shouldn’t expect providers to know those rules and co-pays, either.
This poster describes how the GlucosePATH software was built to address these two issues of complexity. It presents the results of a retrospective study showing how the software’s treatment suggestions differ from those of primary care physicians, in terms of:
We estimated the software’s recommendations would save the average patient around $764 per year in out-of-pocket costs, while reducing HbA1c and improving weight profiles and side effects.
For years, Len Testa has been using mathematical models to help families answer one of their most challenging questions … Read More
A thousand times today, in offices all over America, hospital patients will be diagnosed with Type 2 Diabetes. When that happens, a healthcare provider has to make a treatment decision of enormous complexity, often with partial information to go on, and in the span of just a few minutes. … Read More
GlucosePATH was developed based on a common interest between a physician and a computer scientist to help patients find affordable and effective treatments for Type 2 Diabetes Mellitus. Through this process, we have found that the powerful computational tools used in the travel and finance industry can be leveraged to help clinicians and patients sort through the thousands of treatment pathways to find individualized solutions.
What started as a weekend project between friends with common values has developed into a powerful, FDA-cleared software platform. GlucosePATH and its surrounding research has been presented in academic and professional settings including: MIT, Cincinnati Children’s Hospital, Health 2.0, American Association of Clinical Endocrinologists, and the American Diabetes Association.