Volume 3, Issue 1-1, January 2015, Page: 38-46
Current Clinical Coding Practices and Implementation of ICD-10 in Africa: A Survey of Nigerian Hospitals
Ibrahim Taiwo Adeleke, Department of Health Information, Federal Medical Centre, Bida, Nigeria; Centre for Health & Allied Researches, Bida, Nigeria; Health Informatics Research Initiatives in Nigeria, Bida, Nigeria
Olawole Olusegun Ajayi, Department of Health Records, Lagos University Teaching Hospital, Idi-Araba, Nigeria
Ahmed Bolakale Jimoh, Department of Health Information, Federal Medical Centre, Bida, Nigeria; Health Informatics Research Initiatives in Nigeria, Bida, Nigeria
Abdullateef Adisa Adebisi, Department of Health Information, Federal Medical Centre, Bida, Nigeria; Centre for Health & Allied Researches, Bida, Nigeria; Health Informatics Research Initiatives in Nigeria, Bida, Nigeria
Sunday Akingbola Omokanye, Department of Health Information, Federal Medical Centre, Bida, Nigeria; Centre for Health & Allied Researches, Bida, Nigeria; Health Informatics Research Initiatives in Nigeria, Bida, Nigeria
Mary Kehinde Jegede, Department of Health Information, Federal Medical Centre, Bida, Nigeria; Health Informatics Research Initiatives in Nigeria, Bida, Nigeria
Received: Dec. 19, 2014;       Accepted: Dec. 23, 2014;       Published: Dec. 31, 2014
DOI: 10.11648/j.ajhr.s.2015030101.16      View  4935      Downloads  296
Background: Clinical coding is an integral part of health information management (HIM) practice which provides valuable data for healthcare quality evaluation, health resource allocation, health services research, medical billing, public health programming, Case-Mix/DRG funding. The International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) is a veritable tool for the effectiveness of clinical coding practices. Objective: This present study determined implementation levels of ICD-10 as well as ICD-10-PCS and clinical coding practices in both public and for-profit hospitals in Nigeria. Methods: We used Chi square (χ2) and Cramer’s V (φc) to assess the level of association between type of workplace and implementations of ICD-10 and clinical coding practices. Statistical significance was set at .05. Result: The study discovered nationwide implementation of ICD-10 (179, 88.2%) and fair adoption of its procedure counterpart (79, 38.9%). Most hospitals in Nigeria especially, for-profit facilities (3, 100%) and tertiary healthcare settings (148, 93.1%) employed HIM professionals (214, 91.5%) to manage their clinical coding processes. Conversely, the study observed that challenges confronting clinical coding processes were enormous. Notable among these were absence of automation (70, 34.5%), lack of political will (51, 48.1%), inadequate clinical coders (153, 74.4%) and suboptimal documentation (186, 91.6). Suggestions to improve clinical coding practices ranges from continuing professional coding education (33, 10.3%) to initiation of Nigerian’s modification of ICD such that ICD-10 will become ICD-10-NGM (1, 0.3%). Conclusion: Most healthcare systems in Nigeria have implemented ICD-10 for coding and classification of diagnoses and procedures and the process is being managed by the right workforce (i.e. HIM professionals) which reassures effectiveness. However, lack of political will, inadequate and unmotivated workforce and suboptimal clinical documentation were among challenges confronting the practice in Nigeria. Therefore, this study suggests advocacy and coding education with a view to modifying the orientation of all stakeholders and to sensitize relevant authorities on the benefits of clinical coding practices in order to maximize its outcome and in effect, improve public health in the country.
Automated Coding, Clinical Coding, Clinical Documentation, Data Quality, Discharge Summary, Health Information Technology, Health Information Management Professionals, ICD-10
To cite this article
Ibrahim Taiwo Adeleke, Olawole Olusegun Ajayi, Ahmed Bolakale Jimoh, Abdullateef Adisa Adebisi, Sunday Akingbola Omokanye, Mary Kehinde Jegede, Current Clinical Coding Practices and Implementation of ICD-10 in Africa: A Survey of Nigerian Hospitals, American Journal of Health Research. Special Issue: Health Information Technology in Developing Nations: Challenges and Prospects Health Information Technology . Vol. 3, No. 1-1, 2015, pp. 38-46. doi: 10.11648/j.ajhr.s.2015030101.16
World Health Organization. International Statistical Classification of Diseases and Related Health Problems, Tenth Revision. Volume II. World Health Organization (Geneva: 1993).
World Health Organization. International Classification of Diseases. Available at www.who.int/Intenational_Classification_of _Diseases.htm Accessed on: 22nd December 2011
R. F. Averill, R. L. Mullin, B. A. Steinback, et al. Development of the ICD-10-Procedure Coding System. Centres for Medicare and Medicaid Services 2009. Contract Number: 90-1138, 91-22300, 500-95-0005 and HHSM-500-2004-00011C to 3M Health Information Systems Research Report pp24.
M. H. Stanfill, M. Williams, S. H. Fenton, et al. A systematic literature review of automated clinical coding and classification systems. J Am Med Inform Assoc. 2010; 17(6):646–651.
American Health Information Management Association. Clinical Coding. Available at www.ahima.org/coding Accessed on 5th June 2012.
S. D. Lusignan, S. E. Wells, N. J. Hague, et al. Managers see the problems associated with coding clinical data as a technical issue while clinicians also see cultural barriers. Methods Inf Med 2003; 42:416-22.
S. E. Campbell, M. K. Campbell, J. M. Grimshaw, et al. A systematic review of discharge coding accuracy. Journal of Public Health Medicine. 2001;23(3): 205-211.
S. D. Lusignan. The barriers to clinical coding in general practice: a literature review. informatics for health and social care. 2005;30(2):89-97. doi:10.1080/14639230500298651.
CHKS Ltd. Clinical Coding. Available at www.chks.co.uk/index.php%3Fid%3D33. Accessed on 30th July 2012.
E. K. Huffman. Medical Record Management. 9th Edition as revised by AHIMA. Physicians’ Records Company Berwyn, Illinois; 1990
I. T. Adeleke, A. O. Adekanye, K. A. Onawola, et al. Data quality assessment in healthcare: a 365-day chart review of inpatients’ health records at a Nigeria tertiary hospital. J Am Med Inform Assoc 2012; 19:1039-1042 doi: 10.1136/amiajnl-2012-00823.
A. J. H. Kind, M. A. Smith. Documentation of mandated discharge summary components in transitions from acute to sub-acute care. In: Henriksen K, Battles JB, Keyes MA, et al, eds. Advances in patient safety: new directions and alternative approaches (Vol. 2: Culture and Redesign). Rockville (MD): Agency for Healthcare Research and Quality (US), 2008.
B. J. Petterson. Content and structure of the health record. In: Health Information Management Technology: An Applied Approach. (Second Edition) Johns ML (Ed) (American Health Information Management Association Chicago Illinois 2007 p47-112).
L. So, C. A. Beck, S. Brien, et al. Chart documentation quality and its relationship to the validity of administrative data discharge records. Health Informatics Journal. 2010;16(2):101-113.
W. R. Hersh. Stimulus to define informatics and health information technology, BMC Medical Informatics and Decision Making 2009;9:24.
J. Farhan, S. Al-Jummaa, A. A. Alrajhi, et al. Documentation and coding of medical records in a tertiary care centre: A pilot study. Ann Saudi Med. 2005; 25(1):46-9.
Mahmood K, Shakeel S, Saeedi I, et al. Audit of medical record documentation of patients admitted to a medical unit in a teaching hospital NWFP Pakistan. JPMI 2007 21(2):113-116.
C. Paul, M. P. LaRosa, S. M. Gorden. Use of computer-based records, completeness of documentation and appropriateness of documented clinical decisions. J Am Med Inform Assoc. 1999;6(3):245-251.
W. C. Morris, D. T. Heinze, Warner HR, et al. Assessing the accuracy of automated coding system in Emergency Medicine. 1067-5027/001$5.00 C) 2000 AMIA, Inc.595-599.
L. Lorenzoni, R. D. Cas, U. L. Aparo. The quality of abstracting medical information from the medical record: the impact of training programmes. Int J Qual Health Care. 1999;11(3):209-213. doi: 10.1093/intqhc/11.3.209.
S. V. S. Pakhomov, J. D. Buntrock, C. G. Chute. Automating the assignment of diagnosis codes to patient encounters using example-based and machine learning techniques. J Am Med Inform Assoc. 2006;13(5):516-525. doi: 10.1197/jamia.M2077.
J. A. Langlois, J. S. Buechner, E. A. O’Connor, et al. Improving the e-coding of hospitalizations for injury: Do hospital records contain adequate documentation? Am J of Public Health. 1995;85(9):1261-1265. PMCID: PMC1615600.
R. L. Walker, D. A. Hennessy, H. Johansen, C. Sambell, L. Lix, H. Quan. Implementation of ICD-10 in Canada: how has it impacted coded hospital discharge data. BMC Health Services Research. 2012;12:149.
M. Topaz, L. Shafran-Topaz, K. H. Bowles. ICD-9 to ICD-10: Evolution, revolution, and current debates in the United States. Perspectives in Health Information Management, Spring 2013.
L. Jones. The quality of clinical documentation and subsequent effect on DRG assignment: A report on the findings of the DRG documentation study: Casemix development program. Commonwealth Department of Health, Housing and Community Services, Canberra, 1993. Available at: www.wpro.who.int/publications/docs Accessed on: 9th June 2012.
J. H. Garvin, V. J. M. Watzlaf. Current coding competency compared to the projected. Perspect Health Inf Manag. 2004; 1:2.
J. Ashley (1990/91) The International Classification of Diseases: the structure and content of the tenth revision. Health Trends. 1991; 22(4):135–137.
C. Rooney, C. Griffiths, L. Cook. The implementation of ICD-10 for cause of death coding: some preliminary results from the bridge coding study. Health Statistics Quarterly. 2002;13:31-41.
B. Fox, J. Sheehan. Openness and exactness: mitigating fraud vulnerabilities in the age of EHRs and ICD-10, 2012. Available at: Accessed August 20, 2012.
F. Upton, P. Sessions. Implementation of ICD-10 in USA: the most recent coding system to be used by healthcare providers for reimbursement and other functions. United States of American House Energy and Commerce Committee and House Rules Committee. Available at: www.energycommerce.house.gov/press-release/house-chairmen-upton-sessions-statement-icd-10. Accessed December 16, 2014.
I. T. Adeleke, S. A. Erinle, A. M. Ndana, T. C. Anamah, O. A. Ogundele, D. Aliyu. Health information technology in Nigeria: Stakeholders’ perspectives of nationwide implementations and meaningful use of the emerging technology in the most populous black nation. American Journal of Health Research. Special Issue: Health information technology in developing nations: challenges and prospects health information technology. 2014;3(1-1):17-24. doi: 10.11648/j.ajhr.s.2015030101.13.
I. T. Adeleke, A. H. Lawal, R. A. Adio, A. A. Adebisi. Information technology skills and training needs of health information management professionals in Nigeria: a nationwide study. Health Information Management Journal, 2014. doi.org/10.12826/18333575.2014.0002.Adeleke.
C. I. F. Rooney, S. K. Smith. Health Statistics Quarterly. 2000;08:41-50.
M. Rorsch. Computer-assisted coding: emerging technology today, primary coding technology tomorrow, 2012. Available at: Optum www.optuminsight.com Accessed on: December 15, 2014.
W. C. Moris, D. T. Heinze, H. R. Warner, et al. Assessing the accuracy of an automated coding system in emergency medicine. Proc AMIA Symp. 2000:595-9
C. Bouchet, F. Empereur, F. Kohler. Evaluating a computerized tool for coding patient information. Proc AMIA Symp. 1998:185-9.
S. S. Lloyd, E. Layman. The effects of automated encoders on coding accuracy and coding speed. Top Health Inf Manage. 1997;17(3):72-9.
N. F. Khan, S. E. Harrison, P. W. Rose. Validity of diagnostic coding within the General Practice Research Database: a systematic review. Br J Gen Pract. 2010;60(572):e128-e136.
J. Arthur, R. Nair. Increasing the accuracy of operative coding. Ann R Coll Surg Engl 2004; 86:210-212.
I. T. Adeleke. Knowledge, attitude and practice of clinical coding among HIM professionals at Federal Medical Centre, Bida. B.Sc. project submitted to Houdegbe North Amrican University, Cotonou, Republic of Benin, 2012.
O. O. Adepoju. Knowledge and practice of clinical coding among healthcare providers in three Nigerian tertiary hospitals. B.Sc. project submitted to Houdegbe North Amrican University, Cotonou, Republic of Benin, 2013.
C. Rao, D. Bradshaw, C. D. Mathers. Improving death registration and statistics in developing countries. Lessons from sub-saharan Africa. SAJDem. 9(2):81-99.
J. Cunningham, D. Williamson, K. M. Robinson, R. Carroll, R. Buchanan, L. Paul. The quality of medical record documentation and External cause of fall injury coding in a tertiary teaching hospital. Health Information Management Journal. 2014;43(1):6-15. ISSN 1833-3583 (Print) ISSN 1833-3575 (Online).
K. McKenzie, S. Walker, C. Dixon-Lee, et al. Clinical coding internationally: a comparison of the coding workforce in Australia, America, Canada and England. Available at: www.eprints.qut.edu.au Accessed on July 20, 2012.
F. J. Rodriguez-Vera, Y. Marin, A. Sanchez, et al. Illegible handwriting in medical records. J R Soc. Med. 2002; 95(11): 545-546.
S. Kumar, K. M. Thomas KM. Development of a hospital based menu driven clinician coding tool to implement quality reimbursement process in the U.S.--a cardiologist's diagnoses as an illustration. Technol Health Care 2011; 19(6):423-34.
S. Santos, G. Murphy, K. Baxter, K. M. Robinson. Organisational factors affecting the quality of hospital clinical coding. Health Information Management Journal. 2008;37(1):25-37. ISSN 1833-3583 (Print) ISSN 1833-3575 (Online).
A. Arends-Marquez, N. Knight, D. Thomas-Flowers. ICD-10’s impact reaches far beyond coding: examining the new code sets’ revenue cycle implications. Journal of AHIMA. 2014;85(11):74-76. Available at: www.library.ahima.org/xpedio/groups/public/documents/ahima/bok1_050783.hcsp?dDocName=bok1_050783. Accessed on December 16, 2014.
World Health Organization. Classification of health workers: Mapping occupations to the international standard classification. World Health Organization, Geneva. Available at www.who.int/hrh/statistics/workforce_statistics. Accessed on: 28th May 2012.
M. Leppert. Coder productivity in ICD-10-PCS. ICD-10 Trainer. 2012. http://blogs.hcpro.com/icd-10/2012/10/coder-productivity-in-icd-10-pcs/.
Browse journals by subject