The History of Medical Coding Systems & Languages
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In modern healthcare, medical coding is essential. It provides a framework for ensuring accurate patient care, billing, and health monitoring. Every diagnosis, treatment, and procedure is recorded through a system of codes that, while invisible to most patients, powers nearly every aspect of care delivery. These codes don’t merely fill out paperwork—they are fundamental to communicating medical needs, tracking diseases, and allocating resources across the healthcare system. Today, over 96 percent of US hospitals utilize Electronic Health Records (EHRs) with standardized coding systems (HealthIT 2021).
The accuracy and standardization of medical codes allow providers to track public health trends, monitor disease outbreaks, and compare clinical outcomes on an unprecedented scale. Coding standards, such as the International Classification of Diseases (ICD) by the World Health Organization, focus on diagnoses (the “why”), while Current Procedural Terminology (CPT) codes, managed by the American Medical Association (AMA, specify medical procedures (the “what”).
Together, their users include physicians, nurses, researchers, health information managers and coders, health information technology workers, policymakers, insurers, and patient organizations.
Arriving at interoperable and agreed-upon standards for medical codes was not a simple journey. To learn more about the history of medical coding systems and languages and where they’re heading in the future, read on.
The Pre-History of Medical Coding
The pre-history of medical coding stretches all the way back to the Ebers Papyrus, an ancient Egyptian medical document that is one of the oldest known records of disease descriptions and treatments. While not a coding system in the modern sense, the Ebers Papyrus represents one of many early attempts to systematically describe health conditions and therapies. Other attempts would include the Ancient Greeks’ Hippocratic Corpus and the medical texts of the Islamic Golden Age,
One of the first notable medical records systems—in the modern sense of the term—was the Bills of Mortality in 17th century London, introduced to track the city’s recurring plague outbreaks. These bills provided weekly records of deaths, categorizing them by cause and offering a rudimentary view of disease patterns within the city. While limited in scope, it allowed authorities to see how diseases spread and impacted specific populations, laying the groundwork for more structured methods of population management.
A significant breakthrough came in 1893 with the Bertillon Classification of Causes of Death, often cited as the first structured attempt at international health classification. French statistician Jacques Bertillon’s system introduced a comprehensive, organized list of diseases and causes of death, which cities and countries could adopt to ensure data consistency. This uniformity was crucial for comparing mortality statistics across regions and played a foundational role in modern epidemiology.
The Modern Era: ICD & CPT
Building on the Bertillon Classification of Causes of Death, the World Health Organization (WHO) formalized the first edition of the International Classification of Diseases (ICD) in 1948, setting a precedent for tracking and comparing mortality and morbidity data internationally. In 1975, ICD-9 introduced alphanumeric coding, enhancing the system’s ability to record specific diagnoses and enabling more granular tracking of patient conditions; in 1994, ICD-10 expanded the code range significantly, allowing for greater diagnostics specificity. The latest version, ICD-11, was launched in 2018. It’s designed for digital compatibility, facilitating integration with electronic health records (EHRs) and advancing international data exchange and interoperability.
Developed separately but simultaneously, the Current Procedural Terminology (CPT) was developed in 1966 by the American Medical Association (AMA) to document and standardize medical procedures, primarily for billing purposes in the US. CPT is updated annually, reflecting new medical technologies and practices; today, it includes over 10,000 codes, ensuring it keeps pace with advancements in care. Widely adopted by Medicare, Medicaid, and private insurers, CPT codes play an essential role in healthcare billing and reimbursement, serving as the foundation for the American healthcare system’s procedural tracking.
Digital Innovations in Medical Coding
The digital age has both necessitated and generated significant advancements in medical coding. One such advancement is SNOMED CT. Initially developed in the 1960s as the Systematized Nomenclature of Medicine, SNOMED began as a pathology terminology before evolving into SNOMED Clinical Terms (SNOMED CT) in the early 2000s. Today, SNOMED CT is an internationally recognized, comprehensive coding system that enables precise documentation of clinical details within EHRs, supporting clinical decision-making and patient care across over 80 countries. Its detailed codes allow for enhanced clinical insights, helping healthcare providers manage complex patient data more effectively.
Alongside SNOMED CT, the Logical Observation Identifiers Names and Codes (LOINC) system was created in the 1990s by the Regenstrief Institute to standardize laboratory test names and results globally. LOINC has since become essential for laboratories worldwide, ensuring that test results are comparable and interpretable across different healthcare settings, crucial for patient safety and efficient data exchange.
In tandem with these coding systems, the transformation of health records to digital formats via EHRs has created a link between patient care, billing, and health data analysis. While that link is sometimes referred to as seamless, in reality there are wrinkles—hence the need for interoperability standards, such as Health Level Seven (HL7) and Fast Healthcare Interoperability Resources (FHIR). These frameworks ensure that patient data can be accessed and interpreted consistently, regardless of the system in which it was originally recorded, supporting both individual and public health management.
The Future of Medical Coding Systems & Languages
Today, medical coding plays a pivotal role in epidemiology and public health. The ICD and SNOMED CT systems, for instance, have been used to track outbreaks and assess the global impact of diseases, as seen during the COVID-19 pandemic. Accurate coding data enabled governments and health organizations to monitor COVID-19’s spread, identify hotspots, and respond with informed public health measures. This real-time data-sharing capability illustrates the impact of medical coding on global health security and response readiness. More capabilities will be unlocked in the near future.
Artificial intelligence (AI) and blockchain technology are driving the future of medical coding. AI is being increasingly applied to coding, promising greater accuracy and efficiency by minimizing human error, speeding up coding processes, and reducing administrative burdens. In addition, blockchain technology has the potential to secure patient data within coding systems, offering decentralized security measures that protect sensitive health information from unauthorized access.
The transition to ICD-11 marks another promising development. It’s the first version fully designed for digital use, making it ideal for modern EHR systems and global interoperability. As more countries adopt ICD-11, it’s expected to become the universal standard in health language, streamlining global healthcare data and enhancing care coordination worldwide. At the same time, WHO is exploring collaboration with SNOMED International to link ICD-11 and SNOMED CT, further aiding interoperability (SNOMED International 2024).
As technological advancements unlock new capabilities, medical coding will continue to adapt and innovate, promising even more integration, security, and global collaboration in the future. Through AI, blockchain, and ICD-11’s digital framework, coding systems are set to redefine what’s possible in data-driven healthcare.
