Many in the medical field have a vision of a system of personalized, precision medicine. In this vision, doctors are able to identify treatments for patients based on genetic information that has been linked to treatment efficacy.
Precision medicine is an area of innovation that could help more quickly identify treatments with better outcomes for patients. Because in this paradigm, it is less likely that the patient would be going through trial-and-error cycles of treatment, fewer side effects would be expected.
Advances in the understanding of genetic factors in treatment efficacy have enabled the development of diagnostic tools that allow doctors to identify potential treatment options that were not previously recognized. This information can be used to prescribe targeted, patient-specific treatment regimens. But there is a lot to accomplish before this vision becomes a reality – on the research side and organizationally within the healthcare system.
As these technologies and scientific knowledge have been increasing, rising health care costs have led to the development of new payment approaches meant to reduce cost and protect quality. Value-based purchasing (VBP) is an approach designed to move medicine towards evidence-based treatment options and provide incentives for healthcare practitioners to more closely question the expected effectiveness of treatments that may add costs without adding value.
Under a VBP model, reimbursement decisions for drugs, medical devices and therapies are based on their demonstrated impact on quality measures. In other words, hospital and healthcare providers are paid, in part, based on quality measure results rather than just the cost of treatment. Traditional fee-for-service models are reimbursed based on cost of treatment, which provide counter-incentives that can greatly increase cost.
Proponents believe that VBP models have the potential to lower overall healthcare spending while increasing the quality of care for patients. While it’s hard to argue with these goals, concerns have been expressed about how innovation will fare in a value-based framework. Once the use of precision medicine is well developed and established, its use will be entirely consistent with a value-based purchasing model. So the question is – how do we get there from here? How do we allow this technology to advance during a time in which its value is not yet proven and still being refined? How can we make sure we do not curtail such work – letting the now uncertain understanding override the potential long-term benefit?
A Precision Medicine Study
Battelle conducted a study to look at the decision-making processes around using precision medicine diagnostic tools for cancer treatment. The study identified possible barriers to more fully realizing the potential of these tools for improved patient outcomes.
Although diagnostics to conduct genetic screening for cancer are well developed, they are not yet consistently used. The cost of the diagnostic tools is high and since treatment options do not yet exist for every genetic mutation, the output from the test is not always going to be valuable to the provider. Further, payers generally have been reluctant to reimburse for these tools, preferring instead to reimburse for tools and treatments under current “Standards of Care” that have longer histories of evidence behind them. Most importantly, providers do not always know how to use the results from these tools, and they are often only seen as a “tool of last resort” for patients who have not responded to other forms of treatment.
In order for genetic testing for informing decisions on cancer treatment to become more widely used, costs will need to come down and the perceived value will need to go up. In part, perceived value will depend on the approval of more targeted options matched to specific test results. It also will require analysis assessing the degree to which patients receiving the test have better outcomes than those who do not.
Learn more about the Battelle study.
Value-based payment programs are not intentionally designed to stifle innovation, but their use is based on a static Standard of Care. This restricts the ability for providers to try to adapt the research in emerging areas, like precision medicine. This approach can be adapted to better support development of innovative approaches such as precision medicine, but change would be needed.
Our recommendation is that this adaption should consider these questions:
Are measures aligned with the outcomes analyzed?
Is information available in a timely manner to providers and payers?
Is the analysis of the value of approach decision-driven (not just based on clinical efficacy)?
Are the transition costs incorporated into the payment model?
As the speed of discovery and change accelerates in medicine, the impact of cost-reducing purchasing models will need to be monitored to ensure that patients have access to the best treatments and diagnostic options, and to ensure the long-term potential is not being lost. This will require building a more dynamic system for updating Standards of Care to capture fast-moving science. Care must also be taken to ensure Standards of Care are informed by the best possible evidence.
Our research suggests that developing the analysis and decision-support tools necessary to support new medical advances while meeting the needs of patients, providers and value-based payers is possible, but will be challenging.