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Knowledge, Attitudes, and Challenges of E-Coding Use in Health Information Management: A Case Study of Lagos University Teaching Hospital

Vol. 3 No. 7 (2025): International Journal of Integrative and Modern Medicine:

Idowu Oluwatoyin Margaret (1), Jayeoba Olufunke Felicia (2), Feyisayo Elizabeth Akinjoko (3), Agboola Abimbola Ajoke (4), Adetayo Fatai Adewale (5)

(1) Public Health Dept. Leadcity University,Ibadan Nigeria, Uzbekistan
(2) Department of Health Information, Faculty of Basic Medical Science, Adeleke University, Ede, Uzbekistan
(3) Ladoke Akintola University of Technology, Ogbomoso, Nigeria, Uzbekistan
(4) Primary Health Care Tutor School, University Teaching Hospital Ibadan, Uzbekistan
(5) Federal University of Agriculture, Uzbekistan
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Abstract:

Introduction:


The adoption of electronic health information systems has become increasingly important in improving healthcare delivery and data management. Electronic coding (e-coding), a key component of this transformation, enhances the accuracy of clinical documentation, supports timely billing, and facilitates reliable health data reporting. Despite its benefits, implementation challenges persist, especially in resource-limited settings like Nigeria.


Objectives:


This study aimed to assess the level of knowledge, attitudes, perceived benefits, and challenges related to e-coding among Health Information Management (HIM) personnel at Lagos University Teaching Hospital (LUTH). It also sought to determine the association between knowledge and the actual practice of e-coding.


Method of Analysis:


A descriptive cross-sectional research design was employed. Total enumeration sampling was used to administer structured questionnaires to 150 HIM personnel. Descriptive statistics (frequency, percentage, mean, and standard deviation) were used for data presentation, while Chi-square analysis tested the relationship between knowledge and practice of e-coding.


Result:


Findings revealed that 88% of respondents were aware of e-coding, although only 54% had received formal training. While 78% agreed that e-coding improves documentation accuracy and 82% acknowledged its role in enhancing record accessibility, only 60% expressed confidence in its use. Key challenges included inadequate training (62%), poor infrastructure (58%), and incomplete clinical documentation (50%). A significant association was found between knowledge and e-coding practice (χ² = 9.09, p = 0.0001), confirming that increased knowledge correlates with higher adoption.


Conclusion:


Despite positive perceptions of e-coding, its effective implementation is hindered by infrastructural deficits and a lack of comprehensive training. Enhancing workforce capacity, improving infrastructure, and addressing documentation quality are essential steps toward optimizing e-coding usage in health institutions. Addressing these barriers will be critical in leveraging digital tools to improve healthcare data quality and service delivery in Nigeria.

References

1. Afolabi, M. O., Daropale, V. O., Irinoye, A. I., & Adegoke, A. A. (2020). Health workers’ knowledge and use of electronic medical records in a developing country. Health Information Management Journal, 49(2), 92–102. https://doi.org/10.1177/1833358318799135

2. Al-Muammar, M. N., Alharbi, S. A., & Almalki, M. J. (2023). Electronic medical coding systems and their impact on documentation quality: A systematic review. Health Information Management Journal, 52(1), 27–36.

3. Adewole, A. O., & Oladipo, O. A. (2022). Digital health transformation in Nigeria: Opportunities and challenges for health information professionals. Nigerian Journal of Health Informatics, 14(2), 45–53.

4. Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52(1), 1–26. https://doi.org/10.1146/annurev.psych.52.1.1

5. Bello, M. A., Salawu, R. A., & Yusuf, M. A. (2023). Attitudinal barriers to the adoption of electronic health records among health workers in Nigeria. African Journal of Health Management, 11(1), 22–30.

6. Champion, V. L., & Skinner, C. S. (2008). The health belief model. In K. Glanz, B. K. Rimer, & K. Viswanath (Eds.), Health Behavior and Health Education: Theory, Research, and Practice (4th ed., pp. 45–65). San Francisco: Jossey-Bass.

7. Evans, R. S., Lloyd, J. F., & Pierce, L. A. (2021). Clinical coding, classification, and data quality improvement with electronic health records. Perspectives in Health Information Management, 18(1), 1e.

8. Glanz, K., Rimer, B. K., & Viswanath, K. (2015). Health behavior: Theory, research, and practice (5th ed.). San Francisco: Jossey-Bass.

9. Hasan, M., Lutfiyya, M. N., & Stone, L. A. (2021). Training needs for ICD-11 implementation: A global perspective. BMC Medical Education, 21, 434. https://doi.org/10.1186/s12909-021-02906-8

10. Kim, H., Park, Y., & Lee, J. (2022). Impact of electronic coding systems on clinical documentation and reimbursement accuracy: A systematic review. International Journal of Medical Informatics, 162, 104768. https://doi.org/10.1016/j.ijmedinf.2022.104768

11. Musa, I. A., & Ajayi, T. O. (2020). EHR implementation in Nigerian teaching hospitals: A review of current practices and challenges. Journal of Global Health Technology, 8(3), 101–110.

12. Naylor, M. D., McBride, S., & Link, A. R. (2022). Digital transformation in healthcare: Opportunities and challenges in adopting AI-driven coding systems. Journal of the American Medical Informatics Association, 29(5), 836–843. https://doi.org/10.1093/jamia/ocac030

13. Ojo, O. M., Akintunde, A. A., & Ekundayo, O. M. (2021). Youth involvement in health information systems: A pathway to digital health transformation in Nigeria. Nigerian Journal of Health Sciences, 21(1), 34–41.

14. Okafor, I. J., & Chukwudi, F. O. (2021). Challenges of clinical documentation and coding accuracy in Nigerian tertiary hospitals. Nigerian Health Journal, 21(3), 159–166.

15. Oladele, T. A., Oyewole, K. O., & Adegbite, O. F. (2022). Evaluating the use of electronic health records in medical coding among health information managers in southwestern Nigeria. African Journal of Health Information and Knowledge Management, 17(2), 23–30.

16. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press.

17. World Health Organization. (2021). Global strategy on digital health 2020–2025. World Health Organization. https://www.who.int/publications/i/item/9789240020924

18. World Health Organization. (2023). ICD-11 implementation toolkit. Geneva: WHO Press.