Addressing Common Barriers to Clinical NGS Testing

Genomic tests that use next generation sequencing (NGS) technology are on the rise, and there’s a growing trend for hospitals to insource these tests to improve turnaround time and reduce costs. However, these tests can be challenging to implement. Challenges include lack of bioinformatics expertise, the cost and expense of deploying a new test, and reimbursement, to name a few.

But the challenges aren’t insurmountable. In our experience, rooted in launching one of the very first clinical NGS testing labs at Washington University in St. Louis, and our work helping many institutions operationalize their testing programs, we’ve taken note of some key strategies that lead to successful implementation:

• Think holistically and align with the strategic goals of your institution.
• Take a multi-disciplinary, design-focused approach for test menu, assay design, and overall workflow.
• Take a focused approach and scale when ready.
• Don’t underestimate the bioinformatics knowledge required.
• Ensure you have a good validation plan.
• Evaluate tools and strategies that help address the “interpretation bottleneck.”
• Pay attention to the details of reimbursement.
• Bring it together with a focus on people, education, and collaboration.

Think holistically and align with the strategic goals of your institution

Surprisingly, many of the challenges associated with launching a clinical NGS test have nothing to do with the technology and everything to do with project management and strategic planning. Taking a business-minded, strategic approach is consistent with the institutional decision making and project strategy put forth in a study of early adopters of clinical NGS.¹

According to Nikoletta Sidiropoulos, MD, Associate Professor and Director of Molecular Pathology at The University of Vermont Medical Center, who took a leadership role on her institution’s precision medicine program, “We fundamentally believe that genomically-informed clinical care involves strategic integration of the best genomic technology, with people and processes beyond the laboratory to realize the promise of precision medicine for each unique patient.”²

For Sidiropoulos and her team, looking beyond the laboratory first meant identifying internal stakeholders that could support the precision medicine vision. They spent 6 months performing a thorough evaluation and through that process, were able to identify stakeholders, secure funding resources, and put together a detailed, 5-year plan for the program. What came out of that evaluation program was also a clear indication of the clinical areas of the institution that would partner in the precision medicine program.

Sidiropoulos adds that a strong focus on strategic planning for the genomic medicine department also played a key role in the success of their program. For instance, they did a lot of forward thinking about how to use the data generated to the biggest benefit of the patient and their organization. In their case this meant building a biobank, aligning with research efforts, and integrating with phenotypic data to improve outcomes for patients. One of the overarching tenets also became to increase education about the use of genomics in patient care, throughout their institution and also with patients.

Learn more about the strategic approach taken by Sidiropoulos and her team.

Take a multi-disciplinary, design-focused approach for test menu, assay design, and overall workflow.

Do you want to spend time and money implementing and validating a test that your physicians won’t order?  Of course not. For that reason, building a test menu, assays, and clinical workflows call for you to think like a designer. Good designers don’t build products and simply hope that consumers will create demand. They start with understanding their customers and their demands and designing a product--an experience, actually--that consumers want to use.

A best practice is to work with the send-out department of your existing in-house laboratory. What tests are they currently sending out? Are there opportunities to do these same tests in-house for less money and with a quicker turnaround time? Are there additional tests that physicians would like to order?

For the design of the assay, it often helps to start with the end in mind. What do physicians want to see in a final report?  Their answer will help dictate much of the assay design. Designing with their needs will make it much more likely that they feel a sense of ownership and will order the test for their patients.

Beyond test menu and assay design, it’s also important to think about the overall workflow -- that of the physician ordering the test and that of the data. From the physician’s perspective, the test should be easy to order and the resulting report should be easy to retrieve, interpret, and share with the patient. And as for the test results and raw data, where do they get curated after a test is run? Will you integrate test results with an electronic medical record system (EMR) or in a biobank for linking of variants with clinical outcome and drug response? Will raw data get stored in a data warehouse? It’s important to think through the entire process.

According to Tony Magliocco, MD, FRCPC, FCAP, Senior Member and Chair of the Department of Anatomic Pathology at Moffitt Cancer Center, he and his team feed test and raw data into an enterprise data warehouse along with information from the electronic medical record, other send-out tests, and their Total Cancer Care program such that researchers and health informaticians can access them to understand mutation frequency, link data to outcomes or trials, and so forth.³

Learn more about the approach to data and test results taken by Magliocco and his team.

Sidiropoulos, in her reflection on the building of the University of Vermont Medical Center program, strongly suggests developing care pathways that address alternative workflows such as reflex testing. Reflex testing can introduce additional complexities in terms of reimbursement and the overall workflow in terms of how results are shared with patients.

The patient must figure into the design of the workflow as well. They are often very sick, scared, and anxious about when they will receive their test results. Sidiropoulos describes a situation in which patients were coming to the doctor, expecting to go home with a care plan--which provides a bit of relief to their diagnosis--only to be told that the results from their molecular test weren’t back yet. Ultimately, Sidiropoulos and her team addressed this issue by feeding workflow information, such as test order date and turnaround, into the electronic medical record. As a result, patient appointments were scheduled based on those dates, and patients had some sense of relief that when they left the doctor’s office after an appointment to discuss test results, they would leave with a care plan.  

Lastly, it’s important to include a host of others in the design process as well. Bioinformatician, lab technician, health informatics, LIMS, and IT staff should all have a seat at the table when it comes to test menu, assay design, and overall workflow.

Take a focused approach and scale when ready.

An arsenal of good strategies aside, launching a clinical NGS test or test menu is a considerable amount of work. For this reason, it’s prudent for laboratories to start with a limited scope. Some strategies we’ve seen work well include identification of pilot projects, reduced scope of reporting, or use of a distributed approach.

When launching a test menu, consider strategic selection of pilot projects. Each institution likely has Physician Health Organizations (PHO) with areas of scientific/research interest that provide ideal opportunities to start with smaller projects. For some institutions, it’s cardiology, but for many others, there are growing oncology programs. Starting with a more finite area or test enables institutions to get online more quickly and determine early on the feasibility of adding additional tests.  

At PierianDx, another strategy we see employed is to design or use an assay that interrogates a larger number of genes but initially only report on a restricted few. Taking this approach limits the number of resources needed for bioinformatics pipeline validation and enables the test to go online sooner. For institutions that take this approach, they can then often move to a report including the full set of genes once they become comfortable with test volumes.

Yet another way to launch tests without incurring too much risk to your ongoing testing operation is to use a distributive model. The CAP distributive model, which allows for laboratories to outsource any component of their test to an accredited laboratory, is an ideal way to launch tests quickly when your laboratory might not have all of the resources or full expertise to do so.

Learn more about the CAP distributive model.

Don’t underestimate the bioinformatics
knowledge required.

Generating high-quality sequencing data is imperative for any clinical NGS test. And it’s well-accepted in the industry that different sequencing platforms, assays, and chemistry types produce data with certain idiosyncratic results. Additionally, the process of sequence alignment can introduce errors.⁴ For these reasons, it’s important to not underestimate the amount of bioinformatics expertise required.

There are now good resources for at least learning more about the scope of bioinformatics work required. A list of the guidelines and resources we recommend can be found below.

While it may seem trite to offer resources for such a complicated endeavor, they are a good place to start if you don’t have an understanding of the process or know what questions to ask.

If you have the luxury of an in-house bioinformatics staff or the resources to hire one, then they can oversee this work. If not, it’s necessary to consider vendors who can provide this expertise or outsource this portion altogether. As mentioned earlier, this can be part of a larger plan to distribute work for which you don’t have resources. One of our customers, Dartmouth-Hitchcock, outsources the bioinformatics and initial interpretation portion of their test, which has enabled them to achieve a great amount of uniformity and standardization in their results and ultimately in their reporting.⁵

Ensure you have a good validation plan.

It’s not uncommon for laboratories to take longer than 9 months to validate a test. Ensuring that you have a robust validation in plan in place can dramatically reduce this time, save money, and prevent the inevitable remorse that can come when newer technologies are introduced: “My test is obsolete, and I haven’t even finished validating it!”

The AMP article mentioned earlier “Standards and Guidelines for Validating Next-Generation Sequencing Bioinformatics Pipelines,” enumerates 17 guidelines for validation and is an excellent place to start. In all, your plan should address both the analytic and diagnostic phases of validation and at the very least address these parameters:

• Analytical Sensitivity (including lower limit of detection)
• Analytical Specificity
• Precision/Reproducibility
• Clinical Sensitivity and Specificity
• Reportable Range
• Reference Range
• Sequencing Quality Metrics (Run-Level Metrics)
• Coverage Metrics (Per Exon)

Learn more about the approach we use at PierianDx for validation.

Evaluate tools and strategies that help address the “interpretation bottleneck.”

The recent explosion of NGS testing has revealed just how cumbersome it can be to assign biological significance to a sequenced sample, so much so that generating the sequenced data is now considered the easy part!

For addressing what has become known as the “interpretation bottleneck,” many laboratories are realizing the need for tools that enable them to streamline their process. When interpreting variants, it’s not uncommon for a variant analyst to need multiple monitors to juggle the spreadsheets, genomic databases, genome browser, and guidelines documents necessary for classification of variants. It’s time-consuming and ultimately not scalable.

The shift to larger assays and in vitro diagnostics, and the resulting increased number of variant types, is causing institutions to evaluate new interpretation strategies as well. These newer tests not only require more sophisticated interpretation strategies but point to the need for robust genomic databases that support these new assays, are updated frequently, and use an artificial intelligence mechanism to infer classifications based on previous cases.

And because variant interpretation is a complex and evolving process, classification of variants can change over time when new information surfaces. Some laboratories automatically re-analyze variants at designated time intervals, as there is recent data to suggest an increase in diagnostic yield from doing so.⁶ At the very least, we recommend developing internal policies that address the need for variant re-analysis.

We provide a review of the AMP guidelines for interpretation and reporting of sequence variants in cancer, along with practical strategies for employing, in our webinar.

Pay attention to the details of reimbursement.

Although the industry has experienced a partial victory with the national coverage decision in May of 2018, there are occasional setbacks, as in the Palmetto decision to limit coverage of BRC1 and BRC2 testing for hereditary cancer risk.⁷ In other words, the landscape of coverage is still evolving. However, there are some strategies that laboratories can adopt to improve reimbursement.

For starters, if your laboratory has the budgetary means, you can hire staff who are well-versed in the complexities of reimbursement and the prior authorization process. This strategy worked well for Sidiropoulos and the University of Vermont. They hired somebody to do prior authorization for all of their genomic tests. For her part, Sidiropoulos developed a strong working relationships with area payors, such as BlueCross BlueShield, to handle coverage of their tests.

The prospect of not getting reimbursed is a risky one for many laboratories. However, one of our customers, Eric Loo, Assistant Professor, Pathology and Lab Medicine, from Dartmouth-Hitchcock puts it this way: “Even by not getting reimbursed, it still makes sense to offer the tests in-house, rather than send-out, because we lose less money.”⁵ He adds that their in-house testing operation conducts a large number of tests, such as those for infectious disease, that are routinely reimbursed and that these balance the costs for tests that aren’t.

But hiring new staff isn’t always practical and when you are first building your testing operations, you might not want to incur the additional risk of non-reimbursable tests. In a recent webinar, we collaborated with Boston Healthcare, which specializes in reimbursement, to provide a toolkit for organizations to use to improve their reimbursement strategies and outcomes.

In addition to having a high-quality, actionable test, the key to successful commercialization is developing an approach that clearly communicates the clinical and economic value story. And to do this, you need an arsenal of communication tools, such as a brief payor coverage presentation and a longer dossier or payor monograph that includes aggregated evidential data of  both the clinical and non-clinical values of the assay. And while it’s also important to compile the health economic data about how payors will benefit, it’s the clinical impact data that payors most want to understand.

The experts at Boston Healthcare also indicate the importance of getting to know the payors in your area and developing strong relationships with them. Each will have different factors that are important to them and the sooner you understand what these are, the sooner you can give them what they want. For instance, aligning with them on a coding approach can be helpful. So can developing an approach for supporting denied claims. Taking a top down approach with payors and engaging with key decision makers also makes sense. Likewise, a bottom-up approach, in which you work at the grassroots level to ensure each test request is supported by the appropriate documentation is also key.  

Boston Healthcare also stresses the education component. According to Joe Ferrara, President, he states that education across the healthcare institution is vital, emphasizing the relationship between pathologists and oncologists. As the number of tests and resulting therapeutics proliferate, it’s going to be important for these two specialties to work very closely together to ensure pathologists have a clear understanding of what oncologists are after and oncologists understand things like reflex testing and the testing selection decision making that's going on at the pathology level.⁸

Learn more about building reimbursement strategies from our webinar with Boston Healthcare. 

Bring it together with a focus on people, education, and collaboration.

The molecular sequencing techniques and data analysis technologies in use today are highly sophisticated and are benefitting from the latest in artificial intelligence. Yet there is no substitute for the expertise and wisdom that people can provide. If you hire or partner with the right people, collaborate within your institution to develop tests that physicians want to use for their patients, and focus on educational outreach of staff, payors, and patients, then you have a solid foundation for building your in-house clinical NGS testing program.

Our network of customers who successfully offer these tests to patients on a daily basis provide us with a healthy dose of reality about what it’s like to implement clinical NGS. But more importantly, working with them provides us with an unending amount of wisdom and knowledge, and we are here to share that knowledge with you. For questions about the process of offering clinical NGS, please contact us.

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Works Cited

1. Crawford JM, Bry L, Pfeifer J, et al. The business of genomic testing: a survey of early adopters. Nature News. https://www.nature.com/articles/gim201460. Published July 10, 2014. Accessed January 25, 2019.
2. PierianDx. A Strategic Approach to Implementing Genomic Testing in Clinical Oncology. https://www.pieriandx.com/strategic-approach-genomic-testing. Accessed January 24, 2019.
3. Pieriandx.com. (2019). Building a Best-in-Class Precision Medicine Program. [online] Available at: https://www.pieriandx.com/building-a-best-in-class-precision-med-program. Accessed 24 Jan. 2019.
4. Kulkarni S, Pfeifer JD. Clinical Genomics. Amsterdam: Academic Press; 2015.
5. PierianDx. Bringing NGS Testing In House. https://www.pieriandx.com/bringing-ngs-testing-in-house. Accessed January 24, 2019.
6. Wright CF, Mcrae JF, Clayton S, et al. Making new genetic diagnoses with old data: iterative reanalysis and reporting from genome-wide data in 1,133 families with developmental disorders. Genetics in Medicine. 2018;20(10):1216-1223. doi:10.1038/gim.2017.246.
7. Ray T. Labs, Advocacy Groups Push Back on Medicare Policy Shift on NGS Testing for Hereditary Cancer Risk. GenomeWeb. https://www.genomeweb.com/cancer/labs-advocacy-groups-push-back-medicare-policy-shift-ngs-testing-hereditary-cancer-risk. Published January 22, 2019. Accessed January 22, 2019.
8. PierianDx. Navigating the Reimbursement Landscape for Clinical NGS Diagnostics. https://www.pieriandx.com/navigating-the-reimbursement-landscape. Accessed January 22, 2019.