Understanding the performance of the oncology healthcare system

Doctor's hand and modern laptop computer with virtual icon diagram, photo by everythingpossible/Adobe Stock

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Researchers identified a number of key indicators that can be used to analyse elements of the oncology health system from different perspectives, and then used these indicators to create an overarching scorecard for oncology ecosystem performance.

What is the issue?

Healthcare systems are complex and multifaceted, with a wide range of actors interacting within them. While these interactions and networks can lead to innovations that improve outcomes for patients, given their complex nature they are not always well understood or effectively optimised.

In 2019, RAND Europe was first commissioned by the Milken Institute to produce a conceptual framework that conceptualises the healthcare “ecosystem” as a series of domains, as part of their aim to better understand and conceptualise this complex landscape.

How did we help?

Building on the first phase of work, in this study we applied and extended these ecosystem domains to the field of oncology.

Using the framework structure, we developed a set of potential metrics that can be used to assess the performance and effectiveness of health systems in oncology.

What did we find?

The oncology health system is broad, complex, and well-studied. Through interviews and a detailed, highly targeted review of the literature, we identified a number of key indicators that can be used to analyse elements of the system from different perspectives. The result is an overarching scorecard for oncology ecosystem performance, which can be found in the report.

Oncology ecosystem subdomains and the scorecard

Within the set of metrics we developed, there is significant overlap between domains. Some domains, such as Outcomes and Patient-centricity or Market environment and Capacity, are particularly closely connected. As the metrics serve different purposes in different contexts, such overlap can therefore add value.

We observe that some areas of measurement are significantly more mature than others. To improve the availability of data and insights, the following areas would merit further investment in research:

  • Cancer-specific evidence on patient-reported outcomes and experiences
  • Evidence on levels of patient engagement in research and innovation, and the extent to which the innovation process is driven by patient needs and preferences
  • Evidence on innovation and productivity, particularly on innovative outputs and processes, for oncology specifically

Relevant datasets for measurement

In the US, the main sources of freely available datasets for oncology are data from services such as the Medicare and Medicaid programs, the US Food and Drug Administration (FDA) agency’s datasets, patent data available through the US patent and trademark office and the Survey of Federal Funds for Research and Development, and the datasets available through the National Cancer Institute (NCI), the National Center for Health Statistics, and the United States Cancer Statistics provided by the Centers for Disease Control and Prevention (CDC).

Using the scorecard beyond oncology

While the extent that these metrics can be used beyond oncology varies, we were able to identify a number of challenges in this area that are broadly similar to those across the wider healthcare landscape. For example, issues such as the bottlenecks in Research and Innovation (R&I) productivity, particularly in the pharmaceutical industry, pervade across different health conditions.

From a broader ecosystem perspective, the emergence of big data capabilities within oncology means increasing prominence is being given to personalized medicine. The emphasis on interoperability in electronic health record datasets and improvements in the payment systems indicate a potentially disruptive innovation landscape, not only in relation to oncology, but also in relation to wider health innovation.