Written by Julie Bick, Ph.D.
Pharmacogenomic (PGx) testing assesses how an individual’s genetic makeup affects their response to medications, and as such, is proving to be an important step towards personalized medicine [1]. By tailoring drug therapy to the patient’s genetic profile, PGx testing can enhance treatment efficacy, reduce adverse drug reactions, and improve overall patient outcomes. Despite its potential, the widespread adoption and insurance coverage of PGx testing currently remains limited. Many in the healthcare sector have expressed concerns about the lack of robust, high-quality evidence to demonstrate the clinical utility of PGx testing, and while numerous studies highlight the potential benefits, insurers and healthcare providers continue to request clear evidence for its cost-effectiveness as well as benefits to patients [2]. For this to be achieved, PGx will need to be incorporated into widespread clinical trials and PGx-driven recommendations will require standardization through extensive clinical studies, coordinated through academic institutions, healthcare organizations and the drug development industry. Only then will confidence in PGx testing be sufficient to drive legislation requiring its wider adoption in the healthcare industry [3].
In this blog, we explain the changing landscape of insurance coverage for PGx testing and discuss what steps need to be taken to improve access to this simple and yet powerful test.
All health insurance companies work through a process that uses codes known as Current Procedural Terminology (CPT) codes. The ever-changing CPT code lists are maintained by the American Medical Association (AMA), and used to describe medical, surgical, and diagnostic services, including PGx testing (www.ama-assn.org). CPT codes are essential for billing and reimbursement purposes and play a critical role in the adoption and integration of new testing into clinical practice [4]. The CPT code landscape for PGx testing is complex and evolving as new tests and drug-gene interactions are clinically described.
Single gene analysis codes are used for tests that analyze specific genes related to drug metabolism, efficacy, or safety, for specific known drug-gene interactions. Each of these CPT codes corresponds to a particular gene or a small set of genes. Examples include:
CPT Code 81225 for CYP2C19 gene analysis, commonly used to assess response to clopidogrel.
CPT Code 81226 for CYP2D6 gene analysis, often used for drugs such as antidepressants and antipsychotics.
CPT Code 81227 for CYP2C9 gene analysis, relevant for warfarin metabolism and used to guide dosing.
There are also multi-gene panels codes that cover tests that analyze multiple genes simultaneously. Multi-gene panels are becoming more common in PGx because they can provide a comprehensive assessment of a patient's genetic profile related to a variety of drug responses.
Examples of these types of billable tests include
CPT Code 81418 for pharmacogenetic gene panel, 5-50 genes. This code is used when testing involves multiple genes relevant to drug metabolism or response and is most frequently applied when a patient is taking, or is likely to take, multiple medications that are known to be influenced by genetic variants, such as anticoagulants, antidepressants, opioids, and chemotherapy agents. Preauthorization from the patient’s insurance provider is usually necessary, as coverage for PGx testing can vary depending on the payer and the clinical scenario. Patients for whom this type of test is most valuable include those with treatment-resistant depression, chronic pain or multiple chronic conditions requiring medications from various therapeutic classes.
CPT Code 81479 for an unlisted molecular pathology procedure, when no specific CPT code exists for a multi-gene panel. This is often used for comprehensive PGx panels that include several gene-drug interactions which are not covered under CPT Code 81418. When using this code, the physician must document the medical necessity for the test. This includes providing a rationale for why a specific unlisted molecular pathology test is required for the patient’s diagnosis or treatment.
Some CPT codes are designated for PGx tests that use algorithms to interpret the results and predict drug response such as CPT Code 0036U- a unique code for a specific laboratory-developed test (LDT) that evaluates multiple PGx markers using an algorithm to guide psychotropic drug therapy. The test includes 15 common variants in multiple genes including ABCB1, COMT, CYP2C19, CYP2C9, CYP2D6, DRD2, HTR2A, MTHFR, OPRM1 and SLC6A4 and couples with an algorithmic interpretation to provide recommendations on drug selection, dosing, and potential for adverse effects. This code is used when a healthcare provider needs to optimize psychotropic medications for patients with complex psychiatric histories, treatment-resistant conditions, or those who have experienced multiple adverse drug reactions. The physician must document the reasons for the test, such as previous adverse reactions, lack of efficacy with standard treatments, or a complex psychiatric history.
Within the CPT code system there are Tier 1 and Tier 2 Molecular Pathology Codes established by the AMA according to the complexity of the tests. They provide clear and direct coding for specific genetic tests, making them easier to use for billing and documentation.
Tier 1 Codes are used for well-established and clinically significant single-gene tests that are frequently performed. Examples of PGx Tier 1 tests include the CYP2D6 gene (CPT 81226), CYP2C19 (CPT 81235) and F5 (Factor V- Leiden variant) (CPT 81241)
Tier 2 Codes are used for less commonly performed tests or those with less established clinical utility. They are grouped based on the technical effort and resources required for the analysis rather than the specific gene, and include screens for rare genetic conditions, and custom tests. Examples include CPT 81400 covering a level 1 molecular pathology procedure (e.g., identification of a single exon by DNA sequence analysis, analysis of less than 10 amplicons using multiplex PCR in a single run, or a simple restriction digest); and CPT 81405 for a level 6 molecular pathology procedure (e.g., more complex tests involving analysis of 11-25 exons, or a larger number of variants). Understanding the distinction between these tiers is essential for accurate coding, billing, and documentation of molecular diagnostic services.
Proprietary Laboratory Analyses (PLA) codes are specific to laboratory-developed tests (LDTs) offered by a single laboratory or manufacturer. These tests are often unique and can include PGx tests designed to guide drug therapy based on multiple genetic markers. For example, the CPT Code 0173U covers the PLA code for a specific PGx test panel used to predict the risk of adverse drug reactions and to guide medication choice for patients with chronic pain. They are intended to identify specific tests that are not adequately described by existing CPT codes, including Tier 1, Tier 2, and Multianalyte Assays with Algorithmic Analyses (MAAA) codes. PLA codes are created and maintained by the AMA, and laboratories or manufacturers must apply to the AMA to obtain a PLA code for their proprietary test.
It is important to note that the creation of a PLA code does not imply FDA approval or clearance of the test; it is solely for coding and billing purposes. As precision medicine and personalized healthcare continue to advance, PLA codes will become increasingly important in capturing the complexity and uniqueness of these cutting-edge diagnostics.
Under Medicare, there are two branches of coverage that determine if a given test is covered- National Coverage Determinations (NCDs) and Local Coverage Determinations (LCDs). NCD policies are largely determined by The Centers for Medicare and Medicaid Services (CMS) when they deem that a test or service is necessary for the diagnosis or treatment of an illness under the scope of a given Medicare benefit category. Currently, the only NCD for PGx testing is for Warfarin Response (90.1), for which testing is used for drug suitability as well as dosing. This is likely to change very soon given that the FDA has almost 300 medications with PGx-driven dosing guidelines or warnings associated with their use. This means that LCDs are often used to justify PGx testing for these drugs. See Article - Billing and Coding: MolDX: Pharmacogenomics Testing (A57384) (cms.gov) for more information.
Unlike NCDs, LCDs are coverage determinations that can also be made by a Medicare Administrative Contractor (MAC), who then bills through the Medicare claims process. Approval is based on several criteria that include the use or intent to prescribe a drug that has a known gene-drug interaction requiring a PGx test to be prescribed. In some instances, the prescribing physician may need to provide as justification for that drug over others not requiring PGx testing- this may include such things as the patient’s medical history, polypharmacy.
MolDx L38294 refers to a Local Coverage Determination (LCD) issued by the CMS under the MolDx (Molecular Diagnostics Services) program. It sets specific guidelines for the coverage of PGx testing in the context of refractory depression and anxiety and defines when such testing is considered reasonable and necessary for Medicare beneficiaries, based on clinical criteria and the potential to improve patient outcomes.
Understanding the requirements and limitations of L38294 is crucial for providers and laboratories to ensure compliance and appropriate use of PGx testing within the Medicare population. This LCD applies to PGx testing that includes single gene, multi-gene panels and combinatorial tests (a multi-gene panel that incorporates an algorithm to evaluate PK/PD relationships), that are deemed reasonable and necessary for the improved safety in the use of specific medications by avoiding potentially harmful medications dose &/or adverse reactions known to occur with certain genotypes. The program aims to ensure that Medicare only covers molecular diagnostic tests that provide clinically meaningful information that improves patient outcomes. At this time, the coverage it limited to germline tests, performed in clinical testing laboratories. Providers must document the medical necessity of the test, including a history of treatment-resistant depression or anxiety and the failure of at least two prior medication trials. In addition, a clear clinical plan should be in place indicating how the results of the test will be used to alter treatment.
In all instances, reimbursement under Medicare and Medicaid requires that the drug-gene interaction is clinically recognized by either the FDA, CPIC or PharmGKB- all of these agencies curate clinical annotations for gene-drug interactions and assign levels of risk of ADRs and evidence of gene-drug interactions. The three agencies don’t always agree, and this can result in reevaluation of the test reimbursement. CPIC currently has 23 guidelines for the administration or dosing of 46 drugs based on clinically validated drug-gene interactions [5]. CPIC assesses the clinical data and assigns a confidence level based on this.
The 4 levels are outlined below.
Modified from CPIC. http://cpicpgx.org/prioritization/#flowchart . Accessed 7/5/2023
A PGx test is considered to have actionable use when the gene variant information provides guidance for the avoidance of a specific drug therapy or a modification of a therapeutic dose of a drug therapy; this must be based on the FDA drug label, and FDA safety concern or warning for that drug, or a CPIC level A or B gene-drug interaction. Anything out of the scope of these three factors is not currently considered an actionable use for the purposes of LCDs.
In addition, the ordering of a PGx test for a patient with a medical condition can only be completed by the ordering physician who is responsible for the management of the patient’s therapy and is either considering or has already prescribed a medication with an actionable gene-drug interaction, and who fully understands the actionability of the ordered PGx test. Furthermore, that physician is required to have the licensure, qualifications and training to diagnose the patient’s condition and prescribe the medications in accordance with applicable state laws [6].
The drug labeling process by the FDA is a collaborative and detailed procedure that involves multiple stages of review and approval. Drug labels, also known as prescribing information or package inserts, provide critical information on the safe and effective use of medications. The initial approved version is filed as part of the New Drug Application (NDA), but post-marketing surveillance by the FDA can result in changes that include additional warnings, contraindications or dosing recommendations for example. It is important to recognize that drug labels are legal documents that are used to guide the proper use of the drug, help avoid off-label use that could result in safety issues or legal liability, and they serve as the primary resource for physicians and pharmacists. Therefore, the incorporation of PGx testing is slowly gaining traction. The most common use of PGx for drug labeling incorporates genetic testing recommendations- these may provide guidance for dosing to minimize side effects. An example of a PGx-recommendation on a drug label is for the commonly prescribed anticoagulant warfarin; the drug label for warfarin includes recommendations for PGx testing for CYP2C9 and VKORC1 which affect both dosing and the risk of bleeding [7].
For other drugs, testing is strongly recommended when genetic factors could influence drug metabolism, efficacy, or the risk of adverse effects. Examples of this include the drug Clopidogrel (Plavix); the Plavix drug label carries a strong recommendation for PGx profiling of CYP2C19 variants to identify poor metabolizers, who may not adequately convert clopidogrel to its active form, resulting in highly reduced drug efficacy. Similarly, carbamazepine (Tegretol) is a drug used to manage epilepsy and bipolar disorder; PGx testing for the HLA-B*1502 variant is strongly recommended on the drug label due to the increased risk of severe and potentially lethal skin reactions such as Stevens-Johnson Syndrome.
There are also a handful of drugs for which PGx testing is mandatory, because the genetic variant in question significantly alters the risk-benefit profile of the medication. These include Trastuzumab (Herceptin) used to treat HER-2- positive cancers such as HER2-positive breast cancer and Ivacaftor (Kalydeco) for patients with cystic fibrosis due to the patients being carriers of specific mutations in the CFTR gene that respond to the drug. In both instances, pre-genetic screening is used to confirm the response of the patients to the drugs based on their specific genetic profiles. It also identifies patients for whom these drugs will offer no therapeutic benefit.
Another example of required PGx testing is for the prescription of the HIV drug Abacavir (Ziagen); patients with the HLA-B*5701 allele are at a significantly higher risk of severe hypersensitivity to the drug, and alternative antiviral therapeutics are recommended.
With more drug labels incorporating PGx-recommendations, health insurance companies are increasingly recognizing the potential of pharmacogenomic testing to enhance patient care and reduce healthcare costs. Currently, the use of PGx testing in insurance varies by the type of test, the specific health condition, and the potential benefits. Insurers are exploring Value-Based Insurance Design (VBID) models where coverage is aligned with the value of a test or treatment to the patient. If PGx testing is shown to improve outcomes and reduce costs, it is more likely to be covered and encouraged. While coverage is most common for FDA-recommended tests and high-risk medications, insurers are gradually expanding their use of PGx testing in areas like psychiatry, pain management, and chronic disease treatment, as evidence for its benefits grows. However, challenges related to cost, evidence, and standardization still need to be addressed for wider adoption.
More information on the role of drug labeling in PGx testing, please refer to these resources
US Food and Drug Administration Table of Pharmacogenomic Biomarkers in Drug Labeling. [(accessed on 10 November 2020)]; Available online: https://www.fda.gov/drugs/science-and-research-drugs/table-pharmacogenomic-biomarkers-drug-labeling
PharmGKB Drug Label Information and Legend. [(accessed on 10 November 2020)]; Available online: https://www.pharmgkb.org/page/drugLabelLegend
GINA, the Genetic Information Nondiscrimination Act of 2008 prohibits medical insurance companies (through Title I) and employers (through Title II) from discriminating against individuals on the basis of their genetic information, including PGx test results [8]. Title I represents an amendment of the Employee Retirement Income Security Act (ERISA) of 1974, the Public Health Service Act (PHSA) and Internal Revenue Code (IRC), and the Health Insurance Portability and Accountability Act (HIPAA) of 1996. Under Title I, private health insurers, Medicare, Medicaid, the Federal Employees Health Benefits and the Veterans Health Administration may not use genetic information to determine eligibility for coverage, or even set premiums based on this information; this includes genetic information based on family history or genetic information from other family members. The only limitations lie within the US Military’s TRICARE insurance program, since the US Military is permitted to use medical information, including genetic information to make employment decisions.
Title II of GINA prevents employers from requesting or requiring genetic information from employees or from individuals applying for employment and is implemented by the Equal Employment Opportunity Commission (EEOC). However, the GINA federal law does not protect you against genetic discrimination by life insurance, disability insurance or long-term care insurance companies. Some states have laws in this area, such as North Carolina’s prohibition of discrimination based on an individual’s carrying of the sickle cell trait. Other states have gone further, prohibiting genetic discrimination for life-, disability- and long-term care insurance policies. In 2011, California passed a California Genetic Information Nondiscrimination Act (CalGINA) which extends protections from genetic discrimination to state-funded programs, housing and education loans and emergency medical services. As with Title I, Title II does not cover the US Military’s TRICARE insurance, and also does not apply to any employers with fewer than 15 employees.
With respect to employer-offered wellness programs, GINA has some key provisions that mean wellness programs cannot request, require, or purchase genetic information about an employee or their family members. GINA also requires that any health risk assessment or other health screenings as part of these wellness programs are completely voluntary, and any questions about genetic information, including family medical history, must be optional, and the employee must be clearly informed that they are not required to answer them. In order to ensure that employees are not indirectly coerced into revealing genetic information, any employer sponsored wellness program cannot offer financial incentives to employees or penalize them for not participating in genetic testing. However, wellness programs can use aggregate, de-identified data for designing and implementing the program, as long as the data does not reveal individual genetic information or could be used to identify specific individuals.
Most stakeholders in the healthcare industry agree that PGx testing holds immense promise for the future of personalized medicine. However, its widespread adoption is significantly influenced by the role of health insurers in determining access and affordability. In the US, health insurers play a pivotal role in shaping the healthcare landscape, and their policies on PGx testing can either facilitate or hinder its integration into routine clinical practice. By providing coverage and reimbursement for PGx testing, insurers can enable broader access, especially for populations that are traditionally underserved or have limited financial resources. Conversely, restrictive policies can create significant barriers, preventing patients from benefiting from personalized medicine and leaving clinicians with fewer tools to manage complex treatment decisions effectively.
While some PGx tests are well-established and supported by strong clinical evidence, others are still emerging, with varying levels of proven utility. Insurers often require robust clinical evidence of cost-effectiveness and improved health outcomes before they will provide coverage. This cautious approach is understandable, as it aims to ensure that healthcare resources are used effectively. However, it can also stifle innovation and delay the adoption of promising new technologies that could significantly benefit patients.
For PGx testing to become a standard part of healthcare, a collaborative approach is needed. Health insurers, healthcare providers, researchers, and policymakers must work together to establish clear, evidence-based guidelines for the clinical use of PGx. This includes developing standardized testing protocols, investing in large-scale studies to generate compelling evidence of clinical utility, and creating reimbursement models that reflect the long-term value of personalized medicine. Innovative insurance models are being explored, such as value-based care arrangements that reward providers for improved patient outcomes, which may be enhanced through the use of PGx testing. Such models could encourage the adoption of PGx testing where it has the potential to most impact patient care.
The policies of the health insurers will either accelerate the transition to personalized medicine or create barriers that continue to slow its adoption. Only through a collaborative, forward-thinking approach can we ensure that all patients, regardless of their socioeconomic status, have access to the benefits of PGx testing. This is not just a matter of advancing medical science; it is a critical step toward achieving equity and excellence in healthcare for all.
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