With different starting points, representation formalisms, funding sources, and evolutionary paths, SNOMED CT, LOINC, and RxNorm have evolved over the past few decades into three major clinical terminologies supporting key use cases in clinical practice. Despite their differences, partnerships have been created among their development teams to facilitate interoperability and minimize duplication of effort.
There is now widespread recognition of the powerful potential of electronic health record (EHR) systems to improve the healthcare delivery system. The benefits of EHRs grow even larger when the health data within their purview are seamlessly shared, aggregated, and processed across different providers, settings, and institutions. Yet, the plethora of idiosyncratic conventions for identifying the same clinical content in different information systems is a fundamental barrier to fully leveraging the potential of EHRs. Only by adopting vocabulary standards that provide the lingua franca across these local dialects can computers efficiently move, aggregate, and use health data for decision support, outcomes management, quality reporting, research, and many other purposes. In this regard, the ICF is an important standard for physiotherapists because it provides a framework and standard language for describing health and health-related states. However, physiotherapists and other healthcare professionals capture a wide range of data such as patient histories, clinical findings, tests and measurements, procedures, etc. for which other vocabulary standards such as LOINC and SNOMED CT are crucial for interoperable communication between different electronic systems. In this paper we describe how the ICF and other internationally accepted vocabulary standards could advance physiotherapy practice and research by enabling data sharing and reuse by EHRs. We highlight how these different vocabulary standards fit together within a comprehensive record system, and how EHRs can make use of them, with a particular focus on enhancing decision-making. By incorporating the ICF and other internationally accepted vocabulary standards into our clinical information systems, physiotherapists will be able to leverage the potent capabilities of EHRs and contribute our unique clinical perspective to other healthcare providers within the emerging electronic health information infrastructure.
Summary Objectives We characterized the use of laboratory LOINC® codes in three large institutions, focused on the following questions: 1) How many local codes had been voluntarily mapped to LOINC codes by the each institution? 2) Could additional mappings be found by expert manual review for any local codes that were not initially mapped to LOINC codes by the local institution? and 3) Are there any common characteristics of unmapped local codes that might explain why some local codes were not mapped to LOINC codes by the local institution? Methods With Institutional Review Board (IRB) approval, we obtained deidentified data from three large institutions. We calculated the percentage of local codes that have been mapped to LOINC by personnel at each of the institutions. We also analyzed a sample of unmapped local codes to determine whether any additional LOINC mappings could be made and identify common characteristics that might explain why some local codes did not have mappings. Results Concept type coverage and concept token coverage (volume of instance data covered) of local codes mapped to LOINC codes were 0.44/0.59, 0.78/0.78 and 0.79/0.88 for ARUP, Intermountain, and Regenstrief respectively. After additional expert manual mapping the results showed mapping rates of 0.63/0.72, 0.83/0.80 and 0.88/0.90 respectively. After excluding local codes which were not useful for inter-institutional data exchange, the mapping rates became 0.73/0.79, 0.90/0.99 and 0.93/0.997 respectively. Conclusions Local codes for two institutions could be mapped to LOINC codes with 99% or better concept token coverage, but mapping for a third institution (a reference laboratory) only achieved 79% concept token coverage. Our research supports the conclusions of others that not all local codes should be assigned LOINC codes. There should also be public discussions to develop more precise rules for when LOINC codes should be assigned.
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