In the context of clinical trials, the meticulous collection and management of data are fundamental to the success and reliability of the research outcomes. The increasing complexity of medical terminology in clinical trials necessitates the use of standardised medical coding systems to ensure uniformity in data interpretation. This data collection process is primarily conducted through Case Record Forms (CRFs) for paper-based studies and electronic Case Record Forms (eCRFs) for digital or web-based trials. These data collection instruments are meticulously designed to capture a wide range of relevant information that is crucial for evaluating the safety and efficacy of clinical interventions. Key elements documented in these forms include Adverse Events (AEs), Medical History (MH), and Concomitant Medications (CM) that participants may be taking concurrently with the study medication. This article provides an overview of the processes involved in medical coding within clinical data management, specifically highlighting the role of established medical dictionaries like the Medical Dictionary for Regulatory Activities (MedDRA) and the World Health Organisation Drug Dictionary Enhanced (WHO-DDE). In the medical coding workflow, the precoding process involves a series of important steps to ensure that the relevant medical coding dictionaries are correctly integrated into the coding tool used for clinical trials. These dictionaries aid in categorising medical terms from reports generated throughout the lifecycle of clinical trials, addressing challenges such as variations in data presentation due to diverse investigator backgrounds. Medical coding typically involves a precoding process, followed by auto-coding where terms matching those in the dictionary are automatically assigned codes. However, discrepancies may arise, necessitating manual coding to address unclear or ambiguous terms. The medical coding team plays a critical role in ensuring accurate coding by collaborating with investigators to clarify ambiguous terms and rectify errors in data recorded on Case Report Forms (CRFs). The MedDRA structure includes multiple hierarchical levels from Low Level Terms (LLTs) to System Organ Classes (SOCs), providing a comprehensive framework for handling diverse medical terms. Common issues faced by coders, including illegible terms, abbreviations, and improper categorisation, are also discussed. By understanding these processes and challenges, medical coders can enhance the reliability of clinical trial data, ultimately contributing to safer and more effective therapeutic outcomes. In conclusion, accurately managing and reducing errors in medical coding and billing is crucial for the accuracy and financial health of an organisation. To minimise these errors, it’s essential to provide thorough training on coding standards, conduct regular audits and monitoring, and enhance knowledge in areas such as medical terminology, anatomy and physiology, medical abbreviations, and diagnoses. While coding and billing mistakes can be avoided, understanding their root causes is key to effectively reducing and managing them.
Author (s) Details
Shubham Kamble
The Royal Gondwana College of Pharmacy, Nagpur, India.
Janhavi Indurkar
Central India College of Pharmacy, Nagpur, India.
Akshay Ramteke
Central India College of Pharmacy, Nagpur, India.
Smita Meshram
Central India College of Pharmacy, Nagpur, India.
Please see the book here:- https://doi.org/10.9734/bpi/msti/v13/5312
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