As the world continues to grapple with the aftermath of the COVID-19 pandemic, Long Covid has emerged as a significant public health challenge. Characterised by persistent symptoms like fatigue, brain fog, shortness of breath, and joint pain lasting weeks, months or even years after an infection, Long Covid affects millions globally. Yet, one major hurdle in understanding and addressing this condition is its under-recording in electronic medical records (EMRs).
Accurate coding of Long Covid in EMRs is essential for studying its epidemiology, improving patient care, and managing its impact on healthcare systems and on societies. Electronic medical records are at the core of modern health systems and have largely replaced the more traditional paper-based records used by healthcare providers for many decades. Electronic medical records are used to track patient diagnoses, treatments, and clinical outcomes. When Long Covid is not properly coded, it becomes difficult to use this data to carry out these tasks. Accurate coding using standardised systems such as SNOMED enables researchers and healthcare providers to:
- Track Prevalence and Trends: Consistent coding allows us to estimate how many people are affected by Long Covid, identify demographic patterns, and monitor changes over time.
- Study Risk Factors and Outcomes: Properly coded data helps researchers pinpoint who is most at risk and how Long Covid impacts long-term health.
- Optimise Healthcare Resources: Understanding the true burden of Long Covid helps health systems allocate resources, plan specialised clinics, and train clinicians.
- Support Policy and Funding: Reliable data informs public health policies and justifies funding for Long Covid research and treatment programs.
Without accurate coding, Long Covid remains under-represented in the data that shapes healthcare decisions.
The Challenges of Coding Long Covid
Despite its importance, coding Long Covid in EMRs faces many challenges:
- Lack of Standardised Coding: The ICD-10 and SNOMED codes exist but their use is inconsistent. Many clinicians may not apply it, either due to unfamiliarity or because symptoms don’t neatly fit into a code’s description.
- Symptom Overlap and Complexity: Long Covid presents with a wide range of symptoms that overlap with other conditions like chronic fatigue syndrome or fibromyalgia. Clinicians may code individual symptoms (e.g., fatigue) rather than linking them to Long Covid, fragmenting the data.
- Confusion with other medical problems. Where patients have other long-term medical problems – such as chronic lung disease or cognitive impairment – new symptoms may be be assumed to be of these conditions rather than from Long Covid.
- Limited Clinician Awareness: In busy clinical settings, Long Covid may not be recognised or prioritised, especially if patients present with vague or multisystem symptoms. Lack of training on Long Covid’s diagnostic criteria exacerbates this issue.
- Under-reporting by Patients: Some patients may not seek care for persistent symptoms, or their concerns may be dismissed, leading to no record of Long Covid in EMRs.
These barriers lead to underestimation of Long Covid’s impact, which in turn limits research and resources needed to improve diagnosis and treatment.
The Consequences of Under-Coding
When Long Covid is not properly documented, the consequences ripple across patients, providers, and systems:
- For Patients: Misdiagnosis or lack of a formal Long Covid diagnosis can delay treatment, leaving patients struggling without validation or access to specialised care.
- For Research: Incomplete data hinders epidemiological studies, making it harder to understand Long Covid’s long-term effects or develop evidence-based treatments.
- For Healthcare Systems: Without clear data, hospitals and clinics can’t plan for the growing demand for Long Covid care, leading to strained resources and inequities in access.
- For Public Health: Policymakers rely on EMR data to justify funding and programs. Under-coding obscures the scale of the problem, potentially stalling progress.
Solutions to Improve Coding
Addressing the under-coding of Long Covid requires a multi-pronged approach:
- Standardised Coding Protocols: Healthcare systems should promote the consistent use of ICD-10 and SNOMED codes. Clear guidelines are also needed for when and how to apply these codes. Future iterations of coding systems could include more specific Long Covid codes to capture its diverse presentations.
- Clinician Training: Educating healthcare providers about Long Covid’s symptoms, diagnostic criteria, and coding practices is essential. Continuing medical education (CME) programs can bridge knowledge gaps and encourage proactive documentation.
- Technology and AI: Natural language processing (NLP) tools can analyse unstructured EMR data, such as clinician notes, to flag potential Long Covid cases that might otherwise go uncoded. Integrating these tools into EMR systems could improve case identification.
- Patient Awareness: Public health campaigns can encourage patients to report persistent symptoms and advocate for themselves, ensuring their conditions are documented.
- Research and Collaboration: Partnerships between health systems, researchers, and policymakers can drive the development of better diagnostic and coding frameworks, informed by real-world data.
Conclusions
The under-recording of Long Covid in electronic medical records is more than a technical issue. It is a barrier to understanding and addressing a condition that affects millions of people globally. Accurate coding is the foundation for robust research, effective patient care, and informed public health strategies. By prioritising standardised coding, clinician education, and innovative technologies, we can shine a light on Long Covid’s true impact and pave the way for better outcomes.
For healthcare providers and clinicians, the message is clear: document Long Covid deliberately and consistently. For patients, it is about advocating for your health and ensuring your symptoms are recorded. And for health systems, it’s about investing in the tools and training needed to make electronic medical records an effective tool in managing Long Covid at patient, healthcare provider and national levels.