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Battelle Health & Analytics Newsletter

Battelle Health & Analytics Newsletter

Does Value-Based Purchasing Restrict Innovation?

Interest in and demand for Value-Based Purchasing (VBP) models is growing. But what happens when VBP runs up against innovative treatment options—such as the use of precision medicine diagnostics to improve knowledge of treatment options? These payment models may create barriers to the success of new medical advances if they are not properly accounted for in the model.

Researchers at Battelle recently examined this issue, using precision medicine as a case study standing in for innovation more broadly. Kara Morgan, a Research Leader on the Battelle Health Analytics team, presented the findings in a “Rapid Fire” session at the Academy Health National Health Policy Conference this January in Washington, D.C.

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, to some degree, based on quality measure results rather than just the cost of treatment, as in more traditional fee-for-service models. The Centers for Medicare & Medicaid Services (CMS) are moving towards implementing VBP, and some private insurers are also moving in this direction.

The overall goal of VBP is to move the practice of medicine towards evidence-based treatment options and provide a real incentive for healthcare practitioners to better evaluate the use of ineffective treatments that add cost without adding value. Proponents believe that VBP models have the potential to lower overall healthcare spending while increasing the quality of care for patients. While it is hard to argue with these goals, concerns have been expressed that VBP could negatively impact medical innovation.

The formative study that Battelle conducted looked at the decision-making processes around using precision medicine diagnostic tools for cancer treatment. It also identified possible barriers to more fully realizing the potential of these tools for improved patient outcomes.

Precision medicine could give cancer patients faster diagnoses and access to treatments with better outcomes and fewer side effects. 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.

However, while the diagnostics to conduct genetic screening for several types of cancer are well developed, they are not yet widely used. The cost of the diagnostic tools is still high and, since treatment options do not yet exist for every cancer mutation, the output from the test is not always going to be valuable. As a result, 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. Currently, precision diagnostics for cancer are often seen as a “tool of last resort” for patients who have not responded to other forms of treatment.

Our research looked at the decision models for patients, providers and payers in making selection or reimbursement decisions for precision medicine tools. We found that existing Standards of Care are strong drivers for decision making for providers and payers—and rightly so for areas of care not undergoing radical change. All three types of decision makers were concerned about the existing evidence behind the tools. However, the groups had different and sometimes conflicting priorities when looking at the decision to use precision medicine tools.

  • Providers were strongly influenced by existing Standards of Care used by colleagues for patients with similar conditions. Their decision to use a precision medicine diagnostic was influenced by their satisfaction level with current Standards of Care, their awareness of the diagnostic options and their confidence that the test would result in usable information. They were also influenced by concerns about cost to the patient.
  • Patients’ views on precision medicine tools were influenced by their perception of the health impact (Am I satisfied with my prognosis under current treatment options? Will using this tool delay treatment? Will it lead to better treatments?) and the risks and benefits of having the information (Will it tell me about potential risks for my children? Are there potential negative impacts of having this information?). They were also concerned with the privacy of their personal genetic information and potential out-of-pocket costs.
  • Payers largely made decisions based on the likelihood that the test would lead to better health outcomes, the relative value compared to alternatives and the absolute cost of the test. Payers tend to ask questions like: “Will the knowledge gained from this test lead to better health outcomes? Will it drive down other treatment costs? Does it work better than alternatives that are already part of the Standard of Care?”

In order for genetic testing for 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 treatment options matched to specific test results. It will also require analysis demonstrating that patients receiving the tests have better outcomes than those who do not.

Currently, the reliance on existing Standards of Care for reimbursement decisions can act as a barrier to the acceptance of new and innovative healthcare options. A more dynamic approach for updating the Standards of Care is needed in order for the transition to these new tools and the benefits to patients to be realized. In time, many of these novel treatments and diagnostics could significantly improve patient outcomes and reduce overall healthcare costs by reducing spending on treatments that will not work for the patient. However, demonstrating these results goes beyond the evidence of clinical efficacy and into a new, emerging area of evidence of “value-to-patient” that includes comparison to alternative treatment options.  

Value-based payment programs are not intentionally designed to stifle innovation, but their construct does assume a somewhat static Standard of Care. This approach can be adapted to better support development of innovative approaches such as precision medicine, but change would be needed. Our recommendations are that this adaption should consider these questions:

  • Are measures are aligned with the outcomes analyzed?
  • Is information available in a timely manner to providers and payers?
  • Is the analysis of the value of the approach decision-driven (i.e., not just based on clinical efficacy)?
  • Are transition costs incorporated into the payment model?

As the speed of discovery and change accelerates in medicine, purchasing models will need to be reviewed to ensure that patients have access to the best treatments and diagnostic options. This will require building a more dynamic system for updating Standards of Care to capture fast-moving science. However, care also must be taken to ensure that Standards of Care are informed by the best possible evidence. Additional work is needed to define the evidence required to update Standards of Care and refine value-based measures so that they fully capture the value of new treatment options. 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.