Virtually everyone in the clinical laboratory business is now acquainted with Z-code identifiers. Each unique laboratory test should have a unique tracking code, even if more than one Z-code identifier is reported with a corresponding American Medical Association’s Current Procedural Terminology (CPT) billing code. The uniqueness of each test is determined primarily by the methodology of performing the test, although other factors, such as specimen type, may also be considered.

Z-code identifiers were created and are maintained by McKesson Corporation as the initial step in creating a single national catalog for all commercially available tests that are molecular in nature. This catalog, which is part of the McKesson Diagnostics Exchange, can be viewed by anyone who creates a free user profile at McKessonDEX.com.

Much like NDC codes for drugs, Z-code identifiers enable the consistent identification of that unique test across systems by labs, providers, payers, and policy makers. It allows healthcare stakeholders to make decisions on genetic tests based on their clinical and financial impact, which ultimately reduces disease burden and improves health outcomes.

Approximately 4,500 Z-code identifiers have now been assigned, with a steady stream of applications for new codes in the pipeline. It’s important to understand that, as a tracking code, the Z-code identifier is not validating or credentialing the test accuracy or value. It is simply a unique identifier for each unique test, as documented by the clinical laboratory requesting a code.

The significance of this tracking function can be highlighted by several examples. More than 20 different versions of KRAS testing have been documented with unique Z-code identifier assignments, based on subtle differences in test methodology. A process for confirming the equivalence of each of these test methodologies has not been established. In contrast, if a different clinical laboratory performs the same test in multiple geographical locations, following the same stringent protocol, only a single Z-code identifier is assigned.

The process for initial registration of a test can yield a Z-code identifier assignment within weeks of completing the application. However, this does not mean that a test is ready for “prime time” and immediately available for use. The clinical laboratory applying for a Z-code identifier retains some control over the submitted data and determines whether this data will be made available through the Diagnostics Exchange to other entities (eg, health plans and the AMA/CPT workgroup) for further coding, clinical coverage, and pricing considerations.

How many unique tests will we need to catalog? No one really knows. We do know that the National Institutes of Health has registered more than 16,000 assays, including experimental and investigational purposes, in its Genetic Testing Registry. This registry is limited to human gene tests only, whereas Z-code identifiers may be assigned to any test that is molecular in nature.

Are Z-code identifiers competing with CPT or HCPCS codes? The simple answer is, “No.” Think of Z-code identifiers as tracking codes only for the unique identification of each test. The appropriate CPT or Healthcare Common Procedure Coding System (HCPCS) code is still required on a medical claim for reimbursement purposes. On an 837 electronic claim, the Z-code is reported in the free text claim line comment field and the CPT or HCPCS charge code is reported in the usual procedure code location.

The CPT code set is also evolving to meet the challenge of molecular diagnostic coding. The CPT Editorial Panel recently added “Tier 1” codes, where each CPT code specifies the gene and methodology for commonly ordered tests. They also created “Tier 2” codes for less commonly ordered tests, where nine levels (or families) of codes are defined, based on the testing methodology and similar work effort. Approximately 500 tests are now identified as Tier 1 or Tier 2 tests. But this is just a fraction of the 4,500 Z-code identifiers that have already been assigned.

A crucial component of the process for assigning a CPT code is to establish a clear, evidence- based justification for any code in the CPT set. This is a slower, more methodical process than assigning a Z-code identifier. For emerging technology, it can take some time to develop the objective evidence needed for a CPT code justification. For the special challenges of the new frontier in molecular diagnosis, using Z-code identifiers provides a new pathway for code development. By using incremental steps, a test inventor can now obtain a unique identifier during the clinical evidence justification process. This permits specific communication and publication of data and documentation regarding the new technology during the evidence development phase.

This is significant. Now test inventors can talk specifically about new technology, the evidence needed to establish clinical validity and clinical utility, and pricing, well in advance of documenting requirements for a full-fledged CPT or HCPCS code.

Lastly, the CPT process has acknowledged some of the features of emerging laboratory technology by creating an accelerated protocol for evaluating clinical evidence. This process, named CPT Code- Bridge, will:

		Evaluate test inventor data submitted in the initial application for a Z-code identifier.

		Consider additional research and utilization data as it becomes available.

		Map the Z-code identifier to the appropriate CPT code, with published updates three times a year, instead of annually, as occurs now. Prior to a CodeBridge mapping, a laboratory can still bill an unmapped code using the unlisted molecular diagnostic CPT code, 81479.

Using this approach, clinical laboratories may shorten the time it takes to get a new Z-code identifier from years to months (potentially). The value to payers can be a significant jump-start in evaluating and embracing new technology, and a reduction in administrative costs and hassles. The value to physicians is rapid access to credible, objective information about a test and what it does, when documentation and clinical indications for the new test is published along with the listing.

And most importantly, the value to patients is that they can receive the most appropriate and evidence-based diagnostic tests.

Articles

Virtually everyone in the clinical laboratory business is now acquainted with Z-code identifiers. Each unique laboratory test should have a unique tracking code, even if more than one Z-code identifier is reported with a corresponding American Medical Association's Current Procedural Terminology (CPT) billing code. 

Z-Code Identifiers Give Providers Objective Information About Molecular Tests

Nobody disputes the need for careful, judicious diagnostic testing. But as the number of individual gene tests continues to grow, clinicians are struggling to keep up. On the one hand, using diagnostic markers like KRAS in colon cancer or hormone receptor status in breast cancer to select the most appropriate chemotherapy regimen is essential. It’s the standard of care. On the other hand, the role of many other gene markers is still not fully defined.

One way to keep up with the “what’s what” in molecular diagnostics is to maintain a framework for classifying the tests that a practice uses regularly. Here’s an example of such a framework.

 An ideal screening test is simple to do, sensitive (low false negative rate), specific (low false positive rate), and inexpensive. The goal is to test 100 percent of a targeted population for affected members. The principles of screening are straightforward; putting it into practice, less so. For example, the debates for or against PSA testing for prostate cancer and mammography modalities for breast cancer have not convincingly been resolved.

 An analyte that clearly distinguishes a favorable characteristic for treatment group #1 with a not-so-favorable response that moves a patient into treatment group #2 becomes important when the cost and/or toxicity of treatment group #1 is significant. The emergence of KRAS for colon cancer, and the continuing debate surrounding it, highlight this category.

 BRCA testing to confirm high-risk status for women with strong family history of breast cancer highlights the challenge of a focused screening test that is moderately expensive, and challenging to apply to the entire population. By narrowing the tested cohort to high-risk individuals without sufficient family history may be missed (orphans, only children in small families).

 Similar to predictive risk in a screening population, this category is distinguished by starting with a known problem and attempting to further characterize markers for response. OncotypeDX for breast cancer is probably the best example of a test that uses multiple markers to assess the response to treatment. Twenty-one genes are assayed and ranked via statistical algorithms to create a recurrence score between zero and 100. Higher numbers suggest the need for more aggressive treatment.

 Metabolic markers have emerged in recent years as critical variables to assess in advance of the actual treatment process. Genetic variation in the cytochrome p450 pathways can determine faster or slower drug clearance rates, leading to dosage or treatment interval adjustments in individuals. Although this is the heart of personalized medicine, the term precision medicine is frequently being used in this setting.

 There are several types of testing that assess multiple markers in the same test. Two major subcategories must be distinguished. The first is Multi-Analyte Algorithm Assays (MAAA, CPT Manual, Appendix O), a term chosen by the AMA/CPT Editorial Panel to replace In Vitro Diagnostic Multivariate Index Assay (IVDMIA).

		Oncotype DX testing, mentioned above, can also be classified in this category. Oncotype DX Breast, for example, assays 21 specific genes and, via statistical profiling, assigns a composite risk score based on phenotype outcomes in a reference population. Steadily increasing clinical familiarity with this approach is affirming the usefulness of this prognostic approach, but individual outcomes will still vary from predicted outcomes.

		The second category, multiple analyte testing (against dozens, hundreds, and even thousands of genes) is now available as Next Generation Sequencing (NGS) platforms automate the laboratory component that examines exomes (eg, 21,000 human protein genes) and full genomes. Interpreting the results of new mutations and unexpected, untargeted variations in adjacent genes remains a significant challenge for clinicians moving forward in this field.

The pace of change and innovation in molecular diagnostics testing won’t be slowing anytime soon. The pressure is on providers to make the best clinical decisions in a rapidly changing environment where few tests have sufficient clinical evidence to determine their clinical utility, and where many are lab-developed tests (LDTs) here, protocols and processes can differ significantly. Job one: Classify the tests your practice uses regularly, and keep that framework well maintained. 

Nobody disputes the need for careful, judicious diagnostic testing. But as the number of individual gene tests continues to grow, clinicians are struggling to keep up. On the one hand, using diagnostic markers like KRAS in colon cancer or hormone receptor status in breast cancer to select the most appropriate chemotherapy regimen is essential.

Maintaining a Framework In Molecular Diagnostic Testing

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.

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&mdash;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.

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.

More progress has been made with financial requirements. Z-Code Identifiers, one unique code per test, can be obtained via an online application process whereby the test inventor (ie, the applicant laboratory) provides sufficient data to establish uniqueness, either as an analyte or a methodology. The new identifier becomes a permanent addition to the catalog and, with laboratory permission, becomes available for general use.

Note, however, that applying for and receiving a Z-code is only the first step and does not mean a new test is ready for prime time. Next steps include electronic data submission to support analytic validity, clinical validity, and clinical utility. Once complete, payers can review for coverage and pricing determinations. Moreover, with permission of the applicant laboratory, the American Medical Association CodeBridge review process can consider specific assignment to a suitable current procedural terminology (CPT) charge code. The pathway just described is not specific to any testing category, and further development will extend this approach to panel testing and next-generation sequencing.

The importance of these developments is difficult to overstate for oncology. Evidence is steadily accumulating that exome or whole genome sequencing may generate additional treatment options for up to 25% of patients with suspected genetic disorders; recent case reports suggest similar results for oncology patients whose established first- and second-line therapies have failed. In addition, treatment selection markers (such as hormone receptors for breast, KRAS for colon, and others), prognostic indicators (eg, Oncotype and others), metabolic subtyping for fast/slow metabolizers, and other companion diagnostic parameters are quickly becoming core competencies for clinical practitioners.

The need for a readily accessible, objective, reliable, and current test directory and data management platform is upon us. Creating mechanisms for tools that are sensitive to stakeholder input, flexible for additional user requirements, and interoperable with other knowledge bases is crucial and complex. Achieving industry consensus for these strategies is our new imperative.

	Douglas Moeller, MD, is a member of the advisory board of 

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. 

Douglas Moeller, MD

Articles

Z-Code Identifiers Give Providers Objective Information About Molecular Tests

Maintaining a Framework In Molecular Diagnostic Testing

Expanded Molecular Test Registry and Upgraded Data Systems Needed