Don’t lock genomic data into silos

The floodgates are open: The demand for access to genomic information along the care continuum is sweeping the healthcare industry. Two significant factors are driving the tsunami:

1. The science behind genetic sequencing is lightyears ahead of care delivery and the informatics needed to make full use of it. It’s been a been accelerating as a marquee issue ever since the human genome project was completed 15 years ago.
2. Consumer interest in this field of medicine is unprecedented and gathering steam. Individuals understand the potential value of genetic information that can be unlocked, and that it can greatly impact their health and quality of life.

Now it’s up to those on the front lines – the clinicians and the IT professionals – to ensure the puzzle pieces revealed by science come together in a meaningful picture that’s understood, used and shared during day-to-day encounters with patients.

Genomic data must be shareable

But there’s a significant barrier and, sadly, it’s a familiar one.

The healthcare industry has struggled with interoperability and data sharing – or lack thereof – for decades. Critical patient information is locked in individual or best-of-breed clinical information systems. Care teams can’t access information that could help them come to better diagnoses and treatment plans faster – and which would help them meet the Triple Aim.

We’re on the verge of making the same mistake again. As departments like cardiology and oncology recognize the value of genomics, they begin to investigate stand-alone specialty systems to meet their needs. As the industry has painfully learned, however, that’s an incredibly shortsighted view: Other specialists across the organization can’t tap into the wealth of data the genomic results reveal.

The better option is an enterprise-spanning platform that makes the information accessible for all clinicians.

Unexpected uses, unexpected value

One of our users recently had an “Aha!” moment when leaders recognized that the genomic data they were using for a specific purpose contained insights that could impact a much wider set of clinical challenges. This client initially undertook a pilot project, intending to use pharmacogenomics to help clinicians determine medications most likely to quickly and effectively treat patients with behavioral health issues – to which antidepressants, for example, might an individual patient be genetically resistant.

As clinical leaders interrogated the pharmacogenomic data, however, they discovered how robust it was – and immediately saw applications beyond behavioral health. They are currently reassessing the pilot to ensure they leverage genomic insights beyond the original use case.

We can easily extrapolate this lesson across other examples:

• Researchers who had conducted a clinical study involving more than 10,000 women recently announced that not all breast cancer patients require chemotherapy following surgery. Those who appear not to require post-operative chemotherapy may respond equally on tamoxifen. However, oncologists need detailed pharmacogenomic data to understand if a patient metabolizes tamoxifen well or not – or if other medications may impact efficacy.
• Consider a surgeon in the emergency department seeing a 30-year-old woman with severe abdominal pain. Diagnosing ovarian torsion, the physician might consider an ovarian-sparing surgery. If he had access to genomic information, however, and could see the patient was BRCA-positive (a marker for ovarian cancer risk), he might make a different treatment decision.

Begin with the end game in mind

Before data silos are erected in precision medicine, healthcare leaders need to step back and consider a “practice-specific” rather than “disease-specific” approach to precision medicine. They need to look at the value genomics can deliver across their entire enterprise – for the wide variety of patients they see –  and begin building a precision medicine foundation with the endgame in mind. In a recent blog, for example, Mayo Clinic shared a pertinent example about the value of repurposing pharmacogenomic data.

In addition to implementing a precision medicine strategy that is comprehensive and forms the basis for emerging clinical use cases, health system leaders likewise should ensure it is future proofed. Genomic tests invariably identify mutations and genetic characteristics that scientists don’t understand…yet. But the pace of discovery is incredibly fast. Within a few years, we will undoubtedly know more than we do now.

That means we need to harness, harmonize and store germline, somatic and pharmacogenomic data so clinicians can re-interrogate and re-interpret it across the enterprise and throughout the life of individual patients. What has been uncovered, but not understood, today could hold the key to improving outcomes and lives within a decade.

Finally, healthcare leaders should consider another “lesson learned” from our recent informatics past: If physicians need to leave their workflow, their tendency to access available information plummets. Organizations discovered this when PACS systems and e-prescribe functionalities were siloed – leaving tools that could improve clinical decision making and care quality underutilized. As organizations embark with precision medicine priorities, they need to ensure the information is harmonized and presented within the clinical workflow.

6 steps for success

The question remains:  How do we begin to ensure we don’t make the same mistakes we did in the past by rendering genomic data inaccessible – and thereby marginalizing its value? Six steps can help a healthcare organization get off on the right foot:

• Create a council of clinicians, informaticists and executives to formulate a precision medicine strategy and execution plan.
• Encourage the council to educate itself on the state of genomics and where it intersects most effectively with clinical care.
• Determine organizational priorities and where it will start implementing genomic data (e.g., oncology,  internal medicine).
• Outline the objectives of the precision medicine program – for now and into the future (five years).
• Begin to investigate precision medicine providers within the context of objectives:
  • Can we establish a flexible, scalable platform with this partner?
  • Can the partner solve the informatics challenges of precision medicine (making the data accessible and meaningful across the enterprise)?
  • Will the partner be able to help develop new functionality as the field of precision medicine evolves?
• Educate clinicians, IT professionals, support staff, patients and the community about how the organization is adopting precision medicine for improved care.

Precision medicine is an incredibly promising field. Healthcare leaders have an opportunity to build their infrastructure right this time – with foresight into how valuable genomic data will be to all their stakeholders, now and into the future.

Photo: Getty Images

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