Accepted for/Published in: JMIR Formative Research
Date Submitted: Mar 4, 2022
Date Accepted: Sep 12, 2022
An Economic Impact Model to Estimate The Value of a Digital Intervention to Health Systems: A Diabetes Primary Care Example
ABSTRACT
Background:
Diabetes is associated with significant costs for both patients and health systems. Regular primary care visits aligned with American Diabetes Association guidelines could help mitigate those costs. Digital interventions prompting those visits among unengaged patients could provide significant economic value back to the health system as well as individual patients, but few economic models have been put forth to understand this value.
Objective:
This paper presents a data-driven model for estimating the economic impact for a health system of an email and text message intervention that drives appropriate primary care usage among patients with diabetes who have been historically unengaged with their care.
Methods:
We developed a model that segments patients with diabetes according to their level of blood sugar control as measured by their most recent HbA1c value. The model takes into consideration the population base rates of comorbid conditions for patients with diabetes, as well as physician reimbursement rates, inpatient admissions avoided, and historical impact of digital health solutions.
Results:
We present a conceptual model to measure the economic impact of an email and text message-based intervention used with patients with documented diabetes diagnoses and calculate a return on investment for a health care system implementing it for their population. The model offers a method to understand and test the financial impact of a primary care-focused diabetes population inclusive of costs driven by comorbid conditions.
Conclusions:
The proposed economic model can offer a holistic way for health systems to understand the economic benefits delivered by interventions focused on primary care and prevention for patients with diabetes.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.