Exploring the impact of innovative healthcare technologies and the role of reimbursement

Contributing lab leaderDr. Chiweon Kim

Despite the hype around startups aiming to "disrupt" healthcare, it's expected that these companies’ innovative technologies will work alongside, rather than replace, fundamental healthcare components like physicians and established standards of care. Unfortunately, not all revolutionary emerging technologies are created equal in healthcare. For novel products to gain acceptance, they need to demonstrate how they will bring value. 

At Roche Experience Days (RED) 2023, Dr. Chiweon Kim, Partner, Kakao Ventures, South Korea, talked about the pitfalls of creating products that won’t move the needle. Rather, he points out that for tools to become more accepted by payers, they need to demonstrate their ability to boost clinical flow, reduce costs, work alongside physicians to reveal what cannot be seen, and improve upon existing standards of care.


Article highlights:

  • Disruptive healthcare technologies are entering the sector at a rapid pace, but will work alongside rather than replace doctors and core healthcare standards.
  • For payer adoption, technologies must demonstrate how they will improve upon established clinical workflows.
  • Cost-saving, physician-enhancing, and care-building technologies have a higher likelihood of easier reimbursement.
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Proving value with new technologies

In general, the clinical workflow is composed of screening, diagnosis (risk classification, confirmation, and companion), treatment, monitoring, re-treatment, and patient outcomes.1 A payer will judge the value of a startup company’s product within this timeline and, more specifically, how the technology will ultimately provide benefit to both the physician and patient. However, “the farther you are from the patient outcome, the harder it is to prove value,” says Dr. Kim.

For example, onboarding a new screening method for the general public might be an extremely innovative tool, but it could be problematic if the prevalence of the disease is extremely low. Because disease occurrence is limited, this novel method could lead to low positive predictive value, in which a positive test result is less likely to accurately indicate the presence of the disease, thus not creating a significant difference in the healthcare field. Another example is developing a new disease monitoring technology. If it is no better than the current standard of care and established guidelines, then adoption of the tool will be difficult. 

Increasing test intervals is also an issue because measuring frequently may not always be possible and may not improve outcomes. An example is the reimbursement history of continuous glucose monitoring (CGM), cleared by the FDA in 1999. However, reimbursement of CGM by Medicare in the U.S. didn't occur for another 18 years.2,3

According to Dr. Kim, before founders continue developing their groundbreaking technology, they must first fully understand the standard of care, complexities of indications, patient populations, and, ultimately, how their product will impact patient outcomes.


Emerging healthcare technologies achieving reimbursement

According to Dr. Kim, payers are reimbursing technologies that hold one of these criteria:

  • Advance clinical flow

  • Decrease costs

  • Unveil what human physicians cannot see

  • Improve care that is already proven


While medical Artificial Intelligence (AI) has the power to improve clinical workflow dramatically, this technology can be challenging to gain reimbursement because it needs to demonstrate its value for patient outcome improvement. The FDA has cleared almost 700 AI-based medical devices.4 However, most of them are mainly assisting physicians. If an AI technology can only improve diagnostic accuracy by a small percentage better than a physician, it is unlikely that the tool will gain reimbursement approval, argues Dr. Kim. To that end, stakeholders must ensure that their product can significantly improve clinical workflow, reducing time and increasing efficiency, thus, directly impacting patients' lives.

AI for breast cancer screening is one example that can improve clinical flow and decrease costs. European countries employ a dual reading of mammogram screening, in which two physicians will separately evaluate the results to conclude the patient. However, with the shortages of physicians, this can be quite challenging. As a result, a type of AI technology is being employed in Sweden and has demonstrated that replacing one of the physicians can dramatically improve breast cancer detection rates, as well as decrease costs and clinical workflow.5

Lastly, products that have proven their ability to improve care are also getting reimbursement. For example, while the Holter monitoring device, a portable electrocardiogram (ECG) system, has demonstrated its value for evaluating various heart conditions, such as arrhythmias, it has not been easy for patients to use. Stakeholders developing novel wearable ECG devices that are simpler and less prone to wear and tear than the Holter device will have an easier time achieving reimbursement since the value of ECG monitoring is already well established.7,8

The future of disruptive healthcare technologies

In his talk, Dr. Kim showed that proving the value of screening and diagnostic technologies can be challenging despite the advanced capabilities of these tools. Healthcare startups should prioritize enhancing patient care and demonstrating value to payers and insurers by aligning their technology with areas where outcomes are measurable. 

Successful technologies should demonstrate how they will improve upon established clinical workflows and existing standards of care to facilitate adoption, emphasizing augmentation rather than replacing the existing roles of physicians. 

If you want to hear more from Dr. Kim about innovation in healthcare reimbursement and how emerging technologies will play a complementary role, click here to watch his full presentation at RED 2023.

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  1. Davis et al. (2019). J Ambul Care Manage, 42(1): 51–65. Article available from [Accessed January 2024]

  2. Didyuk et al. (2021). J Diabetes Sci Technol, 15(3): 676–683. Article available from [Accessed January 2024]

  3. Centers for Medicare & Medicaid Services. Article available from [Accessed January 2024]

  4. U.S. Food and Drug Administration. (2023). Information available from [Accessed January 2024]
  5. Lunit. (2023). Information available from [Accessed January 2024]

  6. HeartFlow, Inc. Information available from [Accessed January 2024]

  7. Cardiogram, Inc. (2023). Article available from [Accessed January 2024]

  8. Zio by iRhythm Technologies, Inc. Information available from [Accessed January 2024]