Implementing and Evaluating Genomic Screening Programs in Health Care Systems Proceedings of a Workshop (2018) / Chapter Skim
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6 Improving Health Through the Integration of Genomics-Based Programs: Potential Next Steps
6 Improving Health Through the Integration of Genomics-Based Programs: Potential Next Steps
Pages 87-96
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From page 87... ...
Individual speakers shared their thoughts on actionable next steps that could support the implementation of genomics-based programs in health care systems, and co-chairs Feero and Veenstra captured and summarized key themes that were discussed during the day on topics including evidence generation, data sharing, and genomics-based program design. A MODEL FOR ACCELERATING EVIDENCE GENERATION FOR GENOMIC TECHNOLOGIES IN A LEARNING HEALTH CARE SYSTEM There is limited evidence available on the clinical utility of most genomic tests (Phillips et al., 2017)
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From page 88... ...
The proposed model for rapid generation of clinical utility evidence for genomic tests is not the same as the Centers for Medicare & Medicaid Services's (CMS) Coverage with Evidence Development program, Lu noted, in that the CMS program requires that patients participate in a registry or trial, which is slow with regard to recruitment and subsequent data collection.2 The proposed model is based on a risk-sharing contract between payers and manufacturers so data collection would happen in real time during clinical practice, not through a study or trial, which is the CMS model.
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From page 89... ...
Consortiums (e.g., the IGNITE network described by Orlando in Chapter 4) are working to address this and other challenges, such as the lack of interoperability between EHR systems and other data networks and test results that are not in a readily accessible format.3 Through leveraging 3 For more information on efforts to capture genetic test results in a structured format in the EHR, see DIGITizE, an action collaborative of the Roundtable on Genomics and Precision Health.
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From page 90... ...
. such data networks, Lu concluded, the focus of the model is to capture the missing pieces of genetic test and results data and measure associated patterns of care, clinical outcomes, adverse events, and costs of care in a rapid fashion to generate the clinical and economic utility evidence that is needed to inform clinical practice and policy development.
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From page 91... ...
It should be possible to learn from ongoing clinical genetic testing in the community, he said. However, the data that pertain to the results of genetic tests that are being entered into the EHRs are not discrete (i.e., not in a structured format)
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From page 92... ...
For example, there are a variety of different panels and sequencing approaches that include the BRCA genes, making comparisons challenging. She also said that gathering clinical utility data from a global payment system could be challenging because many items are lumped into one billing code.
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From page 93... ...
He also noted concern about training and the consistency of process outside of the research setting, and he highlighted the opportunity to discuss pointof-care algorithms and tools for helping patients understand the available treatments and courses of action. Another potential topic for Roundtable discussion, Isham suggested, would be practical financing, taking into account the real-world issues that health care systems are struggling with in the current mixed payment environment (i.e., fee-for-service, aggregate payment)
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From page 94... ...
Considerations from Individual Speakers and Presented in Summary Generating Evidence The genomics field is still very much in the evidence-generation stage, Feero said, as opposed to being at the stage of broad implementation of applications with proven benefit. Clinical utility data will be important for facilitating the broader adoption of genomic medicine and the incorporation of genomic data as a routine component of care.
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From page 95... ...
This includes making sure people understand that a negative result does not necessarily mean they do not have a pathogenic variant, especially if there is a strong family history. A multidisciplinary approach is needed, Feero said, and discipline-specific resources and additional support should be given to non-genetics providers to help them improve the care for patients they see who carry potentially harmful genetic variants (as opposed to getting non-genetics providers to adopt the geneticist perspective on the topic)
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From page 96... ...
is lagging and needs attention, he said. When planning the implementation of a genomics program, one should carefully consider the vendor community and how amenable that vendor community will be to genomic testing and genomics data.
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