Expanded Molecular Test Registry and Upgraded Data Systems Needed

Douglas Moeller, MD
Published: Wednesday, Jun 04, 2014
Dr. Douglas Moeller
Douglas Moeller, MD

Medical Director
McKesson Health Solutions
Malvern, PA

Although we’ve known for decades that heredity is a major factor in cancer susceptibility and management, the insights gained in the past decade are still breathtaking. The abundance of novel approaches for assessing risk factors (eg, BRCA and others), screening at-risk populations, profiling family histories, monitoring treatment progress, and detecting fast/slow metabolizers for dosing adjustments is dizzying.

As more of the genome becomes understood, the implications grow more significant. Staying current is nearly impossible for individual practitioners. Two major strategies are required:
  • An even greater focus on team-based care, integrating the expertise of all caregivers, and including the patient and family members in decision making. Patients and family members have access to the Internet, are joining disease-specific advocacy groups (both online and offline), and are becoming more informed each day. Smart practitioners recognize how the patient and family members can be effective members of the care team—no one is more motivated than the patient and his family.
  • Interoperable, secure health information technology (HIT). There’s no other way to eliminate waste and redundancy. And while this has been a common refrain for some time, progress in the HIT field is accelerating. Success stories where HIT provides a seamless experience among multiple providers are now common. Clinical practice sites in the Geisinger Health System and the Veterans Administration are leading the way with ready access to systemwide electronic records, including diagnostic test results and clinical notes. The upfront costs of these systems are now paying dividends with improved efficiency and less redundant testing and treatments.

Current Registry Limited

And yet, despite this progress, new challenges continue to emerge. For example, the National Institutes of Health (NIH) Gene Test Registry, a voluntary, research- based, diagnostic test registry, recently passed the 11,000-individual mark for test registrations—involving human genes only. The registry provides a central location for voluntary submission of genetic test information by providers. The scope includes the test’s purpose, methodology, evidence of the test’s usefulness, and laboratory contacts and credentials. But it has limits—this “human gene only” registry does not include testing for proteome markers, cell surface markers, or infectious disease probes.

We also know there are more than 900 new drugs and vaccines in the pipeline, according to a survey by Pharmaceutical Research and Manufacturers of America (PhRMA) in March 2013. Anticipating the need to evaluate all new agents with value-based evidentiary criteria demands new decision support tools and models. It might be appropriate to mirror the successful data system integration approaches taken by pharmacy benefit management (PBM) systems over the past two decades.

A PBM matches a pharmacy prescription request to a patient’s actual drug coverage benefit, and can provide one or more choices (to the patient via the pharmacist) specifying generic versus brand name, with exact pricing information. Comparable diagnostic benefit managers are now available that request patient-specific diagnostic parameters, access payer-specific medical coverage policies, automate preauthorization protocols (as required), and provide confirmation receipts in minutes, not days.

Better Infrastructure Required

Do we really need a universal catalog for molecular diagnostics? When the cost per test surpasses more than $1000, “Yes.” Not so obvious are the infrastructure requirements to support this approach. The usefulness of a single, universal, commercial test catalog should be apparent. Each test in this catalog must have a unique identifier—and, because it is online, additional look-up attributes can provide ordering clinicians with ample, searchable information about the test methodology, indications, health plan medical and coverage policies, and, ideally, cost.

In more robust systems, both available and under development, pertinent clinical data can now be used to support the clinician or clinical support staff in using patient parameters (eg, age, gender, personal or family history, or specific clinical status indicators) in optimizing the test selection process. Efforts to automatically query electronic medical records for this data are under way but have been hampered by the lack of interoperability standards and patient privacy requirements.


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