Health Information Management Professionals' Interest and Perception of Clinical Coding Practice: A Systematic Review
Keywords:
Health Information Management, Clinical Coding, Medical Coding, computer-assisted coding, Career Interest, Health Information ProfessionalsAbstract
This paper synthesises available peer-reviewed and grey literature on HIM professionals' interest in, and perceptions of clinical coding practice. A structured literature search was conducted using academic search engines and indexed databases, supplemented by targeted grey-literature searches. Findings were narratively synthesised using thematic analysis, and are reported with American Psychological Association (APA, 7th edition) in-text citations and references. Eleven studies and reviews meeting the inclusion focus were identified, spanning Iran, Portugal, Australia, the United Kingdom, Canada, Nigeria, and Malaysia. Four dominant themes emerged: (1) HIM professionals generally perceive clinical coding as important for patient care, funding, and research, but view the coding process itself as burdensome; documentation quality, terminology ambiguity, and time pressure are the most consistently reported perceived barriers to accurate coding; interest in coding as a specialisation is shaped by training exposure, confidence with technology and classification systems, perceived career progression, and workload/remuneration; and attitudes toward computer-assisted coding and artificial intelligence are cautiously positive, tempered by concerns about deskilling and job security. The study concluded that HIM professionals across diverse settings value clinical coding's importance but experience it as cognitively demanding and under-supported by training, documentation quality, and organisational systems. Strengthening pre-service exposure to coding, structured mentorship, clinician–coder collaboration, and thoughtfully implemented coding technologies could improve both interest in and perception of coding practice.
References
Adeleke, I. T., et al. (2015). Information technology skills and training needs of health information management professionals in Nigeria: A nationwide study. Health Information Management Journal, 44, 30–38.
Alonso, V., Santos, J. V., Pinto, M., et al. (2020a). Health records as the basis of clinical coding: Is the quality adequate? A qualitative study of medical coders' perceptions. Health Information Management Journal. https://doi.org/10.1177/183335831982635
Alonso, V., Santos, J. V., Pinto, M., et al. (2020b). Problems and barriers during the process of clinical coding: A focus group study of coders' perceptions. Journal of Medical Systems, 44, Article 62. https://doi.org/10.1007/s10916-020-1532-x
Campbell, S., & Giadresco, K. (2020). Computer-assisted clinical coding: A narrative review of the literature on its benefits, limitations, implementation and impact on clinical coding professionals. Health Information Management Journal, 49(1), 5–18. https://doi.org/10.1177/1833358319851305
Davies, A., Ahmed, H., Thomas-Wood, T., & Wood, F. (2024). Primary healthcare professionals' approach to clinical coding: A qualitative interview study in Wales. British Journal of General Practice, 75(750), e43–e49. https://doi.org/10.3399/BJGP.2024.0036
Factors affecting clinical coding errors. (2022). Shiraz E-Medical Journal. https://brieflands.com/articles/semj-122161
Hosseini, S., et al. (2021). Factors affecting the quality of diagnosis coding data with a triangulation view: A qualitative study. The International Journal of Health Planning and Management. https://doi.org/10.1002/hpm.3254
Kimiafar, K., Hemmati, F., Banaye Yazdipour, A., & Sarbaz, M. (2018). Views of health information management staff on the medical coding software in Mashhad, Iran. Studies in Health Technology and Informatics, 247, 471–475.
Lucyk, K., Tang, K., & Quan, H. (n.d.). Barriers to data quality resulting from the process of coding health information to administrative data: A qualitative study. BMC Health Services Research.
Maharajan, M. K., & Rajiah, K. (2026). Unravelling career preferences: Exploring health science students' perspectives on healthcare analytics. Cogent Education/Cogent OA. https://doi.org/10.1080/2331186X.2026.2642463
Santos, S., Murphy, G., Baxter, K., & Robinson, K. M. (2008). Organisational factors affecting the quality of hospital clinical coding. Health Information Management Journal, 37(1), 25–37. https://doi.org/10.1177/183335830803700103
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