Gai Elhanan, M.D., M.A. Chief Medical Information Officer. Jane A. Burke BSMT (ASCP) Clinical Data Specialist

Transcription

1 Gai Elhanan, M.D., M.A. Chief Medical Information Officer Jane A. Burke BSMT (ASCP) Clinical Data Specialist 1 P a g e H a l f p e n n y T e c h n o l o g i e s LOINC White Paper

2 Laboratories should include LOINC codes in their outbound HL7 messages so that clinical and research clients can easily integrate these results into their clinical and research repositories. 1 Recently, a group of senators sent a letter to the Centers for Medicare and Medicaid Services (CMS) requesting a re-evaluation and reboot of the Meaningful Use (MU) program citing, among other things, concerns regarding the program s ability to achieve meaningful interoperability. For lab data, there is a solution. LOINC: The Cornerstone for Interoperability The cornerstone of interoperability is the use of standardized data structure and coding schemes. Since clinical laboratory data comprise the bulk of an individual s medical record and are essential for healthcare decision making, one would expect it to be prominently featured in all interoperability discussions. In the realm of clinical laboratory data exchange, specifically for lab results, two standards come to mind immediately: 1.) The Laboratory Reporting Initiative (LRI) as a structure standard 2.) LOINC as a coding standard. While both are mentioned in MU regulations and the accompanying Office of National Coordinator (ONC) standards documents, they are not widely recognized as critical for interoperability progress but they are! 2 P a g e H a l f p e n n y T e c h n o l o g i e s LOINC White Paper

3 The Evolution of LOINC LOINC originated in the mid-90s. It is being used nationally and internationally and while it has enjoyed wider adoption with large academic medical centers and healthcare systems with advanced health information systems (HISs) adoption in the ambulatory setting has been a challenge. Aside from Quest, LabCorp and a handful of other reference labs, a historic lack of clear drivers hindered wider adoption other than sporadic use for the healthcare effectiveness data and information set (HEDIS) reporting. Over the years, labs were left to their own devices resulting in a myriad of protocols, coding schemes and integration methodologies, epitomized by the ubiquitous faxed requisition and result forms. However, this era is rapidly coming to a close, and the sooner C-suite and lab personnel internalize it, the better they will be able to cope with impending changes to the business of conducting clinical laboratory testing. the ever progressing MU initiative all require normalized data for their advanced analytics and population-based initiatives to realize the promise of shared savings and efficient care. Supporting Shared Savings Models, Care Coordination and the Actionable Exchange of Lab Data The focus of the current healthcare revolution is on coordinated care and actionable, sharable data. We cannot reach that goal if the bulk of the data, i.e. lab data, is not coded and delivered in an agreed upon standard. For lab results, LOINC is that standard. The Accountable Care Organizations (ACOs) that are sprouting all around the country and already serving millions of patients; the various bundled payment initiatives; and the ever progressing MU initiative all require normalized data for their advanced analytics and population-based initiatives to realize the promise of shared savings and efficient care. Nevertheless, most laboratories, at this time, are not active participants that fall under the mandate of the MU regulations. 3 P a g e H a l f p e n n y T e c h n o l o g i e s LOINC White Paper

4 Electronic laboratory interfaces can significantly increase the value of ambulatory electronic health record (EHR) systems by providing laboratory results data automatically and in a computable form. However, many ambulatory EHRs cannot implement electronic laboratory interfaces despite the existence of messaging standards, such as Health Level 7, version 2 (HL7). 2 LOINC Defined So what is LOINC? What is it good for? And why should the clinical lab world accelerate adoption of LOINC even without a clear regulatory mandate? As indicated earlier, the Laboratory Observation Identifier Names and Codes (LOINC) system was created in 1994 at the Regenstrief Institute, associated with Indiana University. Initially focused on laboratory observations (all laboratory categories and Veterinary Medicine), it has also expanded to include other clinical observations made on patients. LOINC has been endorsed by the American Clinical Laboratory Association (ACLA) and the College of American Pathologists (CAP). It has been adopted for test reporting by large commercial labs such as Quest, LabCorp, Mayo Medical Laboratories, and MDS Labs; large HMOs including Kaiser Permanente and Aetna; governmental organizations including the CDC, DOD, VA, and NLM. Internationally, LOINC has been adopted as a national standard in many countries, including the United States, and has been translated into many languages. Interoperability has two cornerstones: 1. standardized structure 2. standardized content LOINC was created to solve the problem of laboratory data interoperability by promoting standardized content. To date, most labs use proprietary order and results codes. In the past, when results were manually transported or faxed, standardization was not an issue. However, in our emerging electronic healthcare setting without content standardization there is no interoperability. Different systems will not be able to understand each other, data cannot be aggregated, and analytics cannot be performed. 4 P a g e H a l f p e n n y T e c h n o l o g i e s LOINC White Paper

5 Along with a unique numeric LOINC code, each LOINC test result or observation has a formal five or six part fully specified name: COMPONENT The name of the component or analyte measured (example: Sodium) PROPERTY Unit of measure (example: mg/dl, %, number, etc.) TIME ASPECT Interval of time (example: 24 hour collection or point in time) SYSTEM Type of specimen (example: urine, blood, etc.) TYPE OF SCALE The scale of measure: Quantitative, Ordinal, Nominal or Narrative TYPE OF METHOD The methodology used to perform the test (Optional, used where relevant) Currently, LOINC is the de facto standard for laboratory result observations, but it is yet to achieve a similar status for laboratory orders. The New Standard for Lab Results AND Lab Orders Currently there are nearly 50,000 LOINC laboratory observation codes. They offer extensive coverage for: Chemistry Hematology Serology Microbiology Toxicology Drugs Cell Counts Antibiotic Susceptibilities Molecular Genetics Other Domains While many of the LOINC codes identify an orderable lab test, including panels, the majority of the LOINC codes are for result observations (test results). Currently, LOINC is the de facto standard for laboratory result observations, but it is yet to achieve a similar status for laboratory orders. 5 P a g e H a l f p e n n y T e c h n o l o g i e s LOINC White Paper

6 LOINC is not a theoretical exercise. The changes taking place throughout our healthcare delivery system make it a reality and a necessity. Meaningful Use and LOINC Most clinical labs don t realize the possibilities and potential of supporting their community providers with LOINC mapped lab results while some willingly ignore this need until compelled to do so. Such an approach is shortsighted. MU regulations already require LOINC for reportable lab results and as part of the new LRI HL7 format. Although, at this time these requirements primarily affect a small portion of hospital labs, CMS is gradually increasing the pressure for further adoption through the ever increasing demand for actionable lab data from providers. It is not inconceivable that future MU rules will mandate the use of LOINC on a much broader basis. LOINC mapping is not easy nor is it a one-time effort: 1 It requires resources, expertise, and dedication to an ongoing effort. 2 Test dictionaries must be brought up-to-date and then LOINC mapped and loaded into their respective laboratory information systems (LISs). 3 Some labs may even find that their legacy LIS cannot accommodate LOINC codes. 4 Tests, lab equipment and kits continually change and necessitate constant updates to previous LOINC mappings. 5 All require expensive and disruptive updates and resource allocation at a time when resources are being stretched in many directions. 6 Additionally, the expertise required for LOINC mapping may be beyond the skill level available in most small hospital and independent labs. The Key to Success for Independent and Hospital Labs LOINC is not a theoretical exercise. The changes taking place throughout our healthcare delivery system make it a reality and a necessity. It is only a question as to when government regulations will mandate it in a manner that will force all labs to comply. Until then, only indirect pressure by providers and provider organizations will gradually force a change. MU users, ACOs, and bundled payment organizations already begin to steer business to labs that can support electronic delivery of normalized results. This will only be amplified by the threat of reduced testing volume as a result of realizing efficiencies due to coordination of care. Since LabCorp, Quest and a handful of other capable laboratories already support such needs, independent and hospital labs will find it ever more difficult to compete with them and survive. 6 P a g e H a l f p e n n y T e c h n o l o g i e s LOINC White Paper

7 50,000 LOINC Codes vs. 2,000 CPT4 Codes LOINC is large and complex. As mentioned previously, the laboratory observation section encompasses almost 50,000 codes. Compare that with the 2,000 or less orderable Current Procedural Terminology (CPT) codes. In some respects, the magnitude of transitioning to LOINC is similar to or greater than the transition between ICD-9 CM to ICD-10-CM. While the ICD coding system increases by a factor of six to seven, the LOINC to CPT ratio is 25. LOINC is just so more granular than the CPT coding systems could ever be and therefore, it is not a surprise that CPT codes cannot support the data analytics needs of modern healthcare. Consider the example below, a single CPT code maps to numerous different types of urine chloride tests and tests results: point-in-time tests, 24-hour collection tests, tests with different units of measure, etc. While the CPT code might do, from an administrative and billing perspective -- from a clinical perspective, it falls far short of providing the necessary information that will allow accurate test to test comparison or data aggregation. Therefore, it is not a surprise that modern healthcare demands a much more detailed clinical observations coding system for use within clinical information systems for analytics and actionable and sharable data. If there is anything to be learned from the current state of the ICD transition, it is that leaving it to the last possible moment is the worst possible alternative. The transition to LOINC does not carry the wide, systemic effect as the ICD transition does; and clinical laboratories are traditionally not at the top in resource allocation. In the future, labs can expect even more barriers to enabling their internal staff the time needed to transition to LOINC code use. Therefore, the prudent approach by hospital and independent labs is to be proactive and prepare while there is still time. The laboratory observation section encompasses almost 50,000 codes. Compare that with the 2,000 or less orderable Current Procedural Terminology (CPT) codes 7 P a g e H a l f p e n n y T e c h n o l o g i e s LOINC White Paper

8 Some third-party vendors offer services for the initial dictionary build, LOINC mapping, ongoing maintenance, as well as, middleware solutions that can bridge the gap in current capabilities of existing LISs. Asking the Right Questions Labs should examine their systems and their ability to support community physicians increasing demand for sharable and actionable data: Does the lab have an up-to-date test dictionary? Without this it will be impossible to provide the required coded output. Furthermore, future MU regulations are expected to require the use of the electronic directory of services (edos) standard to publish those services for consumption by physician EHRs. To what level is the current dictionary LOINC mapped? Is any current LOINC mapping up-to-date? Does the lab have the skill set and dedicated time to conduct such mapping? Can the lab keep maintaining it? What is plan B? Is the current LIS version capable of holding LOINC codes? Many legacy LISs still in use lack the design to actually accommodate LOINC codes. If this is the case, what is the plan? LIS upgrades or replacements are expensive and disruptive. Find a LOINC Mapping Expert For those that conclude that they do not have the skill set and/or the infrastructure to support LOINC, alternatives do exist and should be examined. Test dictionary builds and LOINC mapping are specialty skills that require lab and LIS expertise as well as LOINC expertise. Most LIS vendors do not offer such services to support their software systems and most labs are left to fend for themselves. However, some third-party vendors offer services for the initial dictionary build, LOINC mapping, ongoing maintenance, as well as, middleware solutions that can bridge the gap in current capabilities of existing LISs. Being able to positively answer the above questions or, at least, have a roadmap to achieve them within the first year of the start of MU stage 2 (2014), will prepare the lab for the realities of providing clinical services to physicians in the era of accountable care. For more information, on LOINC Mapping and Test Dictionary builds, please contact Halfpenny Technologies at or visit us online at 8 P a g e H a l f p e n n y T e c h n o l o g i e s LOINC White Paper

9 Footnotes 1 Clement J McDonald, Stanley M Huff, Jeffrey G Suico, Gilbert Hill, Dennis Leavelle, Raymond Aller, Arden Forrey, Kathy Mercer, Georges DeMoor, John Hook, Warren Williams, James Case, and Pat Maloney (2003); LOINC, a universal standard for identifying laboratory observations: a 5-year update Clin Chem 49(4): Walter V Sujansky, J M Overhage, Sophia Chang, Jonah Frohlich, and Samuel A Faus (2009) The development of a highly constrained health level 7 implementation guide to facilitate electronic laboratory reporting to ambulatory electronic health record systems. J Am Med Inform Assoc 16(3): About the Authors Gai Elhanan, M.D., M.A., Chief Medical Information Officer A veteran physician with more than 12 years of experience in internal medicine and infectious diseases, Dr. Elhanan has more than 15 years of experience with healthcare information systems; research, design, development and implementation in clinical and administrative environments. Dr. Elhanan received his medical informatics M.A. from Columbia University, NY, and completed a post-doctoral fellowship at the medical informatics department, New York Presbyterian Medical Center with broad skill set in the informatics field as well as unique knowledge in the field of sematic networks and medical/healthcare ontologies. Dr. Elhanan is an experienced healthcare software industry manager and leader for the development and implementation of innovative software solutions. He served as chief of healthcare informatics at 3M Health Information Systems, Medical Necessity and Compliance, and holds a Research Professor position at the department of computer science, New Jersey Institute of Technology where he researched auditing methodologies and improvements for large-scale healthcare terminologies. Jane A. Burke, BSMT (ASCP), Clinical Data Specialist Jane has been working as a laboratory professional for more than 30 years. She possesses a wide array of invaluable strengths that include meticulous problem solving ability, quality assurance and quality control, proficiency testing, procedure documentation for CLIA requirements, and leadership of staff. Under her direction, the laboratory twice received the COLA Laboratory of Excellence Award. She also served as the Manager of LIS for a three year period and was responsible for software, hardware, and system security as well as file definition and instrument interfaces. Halfpenny Technologies was pleased to gain the benefit of Jane s breadth of knowledge when she began with the company in June, She manages all LOINC mapping projects and is HTI s internal LOINC mapping expert. She has experience in dictionary builds, interface testing and project management. She is particularly adept at analyzing and reviewing processes, assessing complex rules and creating clear documentation that enables test dictionaries to be built to the highest standards. Jane has a B.S. in Medical Technology from West Virginia University. 9 P a g e H a l f p e n n y T e c h n o l o g i e s LOINC White Paper