New LOINC Codes for reporting pharmacogenomics results can enable evidence-based clinical decision making

The Regenstrief Institute Inc. and Clinical Pharmacogenetics Implementation Consortium (CPIC™) are working together to create LOINC codes for reporting pharmacogenomic laboratory results in a standard format.

The LOINC terminology, which is owned and developed by the Regenstrief Institute, enables interoperability between laboratory information systems, electronic health record (EHR) systems, and other clinical information systems from different vendors and institutions.

CPIC is a shared project between Pharmacogenomics Knowledge base (PharmGKB) and the Pharmacogenomics Research Network that provides peer-reviewed guidelines that help translate genetic laboratory test results into actionable prescribing decisions for specific drugs.

“Today, LOINC is used in more than 170 countries so that clinical systems can share, aggregate, and understand the health data they receive from many sources” said Daniel Vreeman, P.T., D.P.T, M.Sc., associate director of terminology services at the Regenstrief Institute and associate research professor of medicine at the Indiana University School of Medicine. "We are delighted to work with CPIC to expand LOINC’s coverage of pharmacogenomic laboratory results, which provide key data for personalizing drug treatment decisions."

LOINC codes also make it possible for these information systems to understand the data and provide effective decision support to the clinicians using them.

"The lack of common, coded identifiers for genetic lab test results is one of the biggest barriers to the integration of genomic test results into EHR systems and the subsequent use of those results in clinical decision support rules", said Robert Freimuth, Ph.D, Assistant Professor of Biomedical Informatics at Mayo Clinic College of Medicine and co-Chair of the CPIC Informatics Working Group.  "The codes produced by the collaboration between LOINC and CPIC represent a significant step forward in our ability to provide genome-guided therapy at the bedside."

One of the early adopters of the standardized terminologies proposed by CPIC is the DIGITizE Action Collaborative (DIGITizE AC), an activity of the Institute of Medicine’s (IOM) Roundtable on Translating Genomic-Based Research for Health. The DIGITizE AC is working on increasing support for clinical genomics within EHR systems. On December 1, 2015, DIGITizE AC published its first implementation guide, Establishing Connectivity and Pharmacogenomic Clinical Decision Support Rules to Protect Patients Carrying HLA-B*57:01 and TPMT Variants: An Implementation Guide, which is based on CPIC guidelines for HLA-B and TPMT.

Each CPIC guideline makes recommendations to clinicians on how to assign phenotypes to clinical genotypes and on how to prescribe medications based on genotype/phenotype. The new DIGITizE AC implementation guide specifies how system developers and healthcare organizations can implement clinical decision support rules that are based on CPIC guidelines and LOINC-coded pharmacogenomic laboratory test results.

The terms describing pharmacogenetic test results were developed by CPIC through a community-based standardization project. Those terms were assigned LOINC codes and are now included in the most recent LOINC release (version 2.54, released December 21, 2015).

About the Regenstrief Institute and LOINC

The Regenstrief Institute is a distinguished medical research organization dedicated to improving the quality and effectiveness of health care. The institute is the home of internationally recognized centers of excellence in biomedical and public health informatics, aging, and health services and health systems research. Institute investigators are faculty members of the Indiana University School of Medicine, other schools at Indiana University-Purdue University Indianapolis, or Purdue University.

LOINC was initiated in 1994 by the Regenstrief Institute and developed by Regenstrief and the LOINC committee because there was a growing trend to send clinical data electronically from laboratories and other data producers to hospitals, physician's offices, and payers who use the data for clinical care and management purposes. LOINC was created to provide a common language (set of identifiers, names, and codes) for clinical and laboratory observations. The current version of LOINC includes more than 78,000 terms, including laboratory tests, clinical measures like vital signs and anthropomorphic measures, clinical document titles, standardized survey instruments and more.

Regenstrief Institute

About CPIC

The Clinical Pharmacogenetics Implementation Consortium  (CPIC™) was formed as a shared project between PharmGKB and the Pharmacogenomics Research Network (PGRN) in 2009. The goal of CPIC is to accelerate proper use of pharmacogenomic tests in the clinic.  CPIC addresses what has been one of the major barriers to clinical implementation of pharmacogenetic tests:  the lack of freely available, peer-reviewed, updatable, and detailed gene/drug clinical practice guidelines. CPIC creates, curates, and updates guidelines that enable the translation of genetic laboratory test results into actionable prescribing decisions for specific drugs.

Priority is given to gene/drug groupings for which the evidence for actionable prescribing is strongest. Following peer-review, CPIC guidelines are simultaneously published in a leading journal and publicly posted. CPIC guidelines help clinicians understand how to use available genetic test results to guide prescribing and do not focus on whether to order genetic tests. Each CPIC guideline adheres to a standard format that includes which variants define alleles, assignment of function to alleles, translation of diplotypes into phenotypes, prescribing recommendations (graded according to strength), graded evidence to support prescribing recommendations, allele frequencies world-wide, and algorithms and example language for clinical decision support.

CPIC is funded by NIGMS and NHGRI, of the National Institutes of Health (NIH).

CPIC