Rikhotso M. 1, Kalema B. M. 2, Seaba T. R. 3
| 1 Tshwane University of Technology, South Africa 2 University of Mpumalanga, South Africa 3 Nelson Mandela University, South Africa |
Abstract
Background and Aim of Study: The increasing use of information technologies in healthcare has enhanced communication between its stakeholders and has also reduced health cost. As a result, data interoperability has become a priority which has increased the need to assess whether health information systems (HIS) used are interoperable enough to support this call. The aim of the study: to assess the data interoperability of the HIS used in the South African public healthcare.
Material and Methods: Based on the conceptual model with the constructs of core, policy, societal, engagement as well as acceptance and use readiness and parameters of functional, syntactic and semantic interoperability, a measuring instrument in the form of closed-ended questionnaire was designed. Statistical data was collected from Information Technology personnel in three district hospitals of Gauteng Province in South Africa.
Results: Hypotheses 1, 3 5, 6a and 6c predicted the influence of core readiness, societal readiness, use readiness functional interoperability and semantic interoperability on HIS data interoperability readiness respectively and were all accepted. Hypothesis 2, 4 6b predicted the influence of policy readiness, engagement readiness and syntactic interoperability on HIS data interoperability readiness and were all rejected.
Conclusions: The developed model can be used to enhance research on data interoperability that is a major challenge in the use of information technology in healthcare. The sharing of information among different levels of medical personnel is essential for healthcare quality, efficiency, and safety of care provided to a patient. To enable this, systems should be able to connect and exchange information with each other without limitation. Such also enables better workflows, reduce ambiguity, and allows data transfer among systems and healthcare stakeholders.
Keywords
health information systems, interoperability assessment, interoperability parameters, readiness assessment, South African healthcare
References
Achieng, M., & Ruhode, E. (2023). Context-based factors that influence healthcare information system implementation in resource-constrained public hospitals. African Journal of Science, Technology, Innovation and Development, 15(5), 580–589. https://doi.org/10.1080/20421338.2022.2157786
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage. https://www.ucg.ac.me/skladiste/blog_609332/objava_105202/fajlovi/Creswell.pdf
De Mello, B. H., Rigo, S. J., da Costa, C. A., da Rosa Righi, R., Donida, B., Bez, M. R., & Schunke, L. C. (2022). Semantic interoperability in health records standards: A systematic literature review. Health and Technology, 12(2), 255–272. https://doi.org/10.1007/s12553-022-00639-w
Dixon, B. E., Rahurkar, S., & Apathy, N. C. (2020). Interoperability and health information exchange for public health. In Magnuson, J., & Dixon, B. (Eds.), Public Health Informatics and Information Systems. Health Informatics (pp. 307–324). Springer, Cham. https://doi.org/10.1007/978-3-030-41215-9_18
Ennis-Cole, D. L., Cullum, P. M., & Iwundu, C. (2018). Physicians as operational leaders: Cost, curriculum, technology, and organizational challenges. TechTrends, 62, 239–249. https://doi.org/10.1007/s11528-018-0273-x
Kgasi, M. R., & Kalema, B. M. (2014). Assessment E-health readiness for rural South African areas. Journal of Industrial and Intelligent Information, 2(2), 131–135. https://doi.org/10.12720/jiii.2.2.131-135
Kouroubali, A., Papastilianou, A., & Katehakis, D. G. (2019). Preliminary assessment of the Interoperability maturity of healthcare digital services vs public services of other sectors. Studies in Health Technology and Informatics, 264, 654–658. https://doi.org/10.3233/SHTI190304
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610. https://doi.org/10.1177/001316447003000308
Kante, M., & Ndayizigamiye, P. (2021). Internet of medical things, policies and geriatrics: An analysis of the national digital health strategy for South Africa 2019-2024 from the policy triangle framework perspective. Scientific African, 12, Article e00759. https://doi.org/10.1016/j.sciaf.2021.e00759
Khubone, T., Tlou, B., & Mashamba-Thompson, T .P. (2020). Electronic health information systems to improve disease diagnosis and management at point-of-care in low and middle income countries: A narrative review. Diagnostics, 10(5), Article 327. https://doi.org/10.3390/diagnostics10050327
Lehne, M., Sass, J., Essenwanger, A., Schepers, J., & Thun, S. (2019). Why digital medicine depends on interoperability. NPJ Digital Medicine, 2(1), Article 79. https://doi.org/10.1038/s41746-019-0158-1
Mbunge, E., Batani, J., Gaobotse, G., & Muchemwa, B. (2022). Virtual healthcare services and digital health technologies deployed during coronavirus disease 2019 (COVID-19) pandemic in South Africa: A systematic review. Global Health Journal, 6(2), 102–113. https://doi.org/10.016/j.glohj.2022.03.001
Naidoo, V., Suleman, F., & Bangalee, V. (2023). Policy developer’s perceptions on the implementation of National Health Insurance in South Africa: A qualitative study. Journal of Pharmaceutical Policy and Practice, 16(1). https://doi.org/10.1186/s40545-023-00564-x
Nilsen, E. R., Stendal, K., & Gullslett, M. K. (2020). Implementation of eHealth Technology in community health care: The complexity of stakeholder involvement. BMC Health Services Research, 20, Article 395. https://doi.org/10.1186/s12913-020-05287-2
Ogundeji, Y. K., Ohiri, K., & Agidani, A. (2019). A checklist for designing health insurance programmes – A proposed guidelines for Nigerian states. Health Research Policy and Systems, 17, Article 81. https://doi.org/10.1186/s12961-019-0480-8
Parasuraman, A. (2000). Technology Readiness Index (TRI) a multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4), 307–320. https://doi.org/10.1177/109467050024001
Peng, C., & Goswami, P. (2019). Meaningful integration of data from heterogeneous health services and home environment based on ontology. Sensors, 19(8), Article 1747. https://doi.org/10.3390/s19081747
Pypenko, I. S., & Melnyk, Yu. B. (2021). Principles of digitalisation of the state economy. International Journal of Education and Science, 4(1), 42–50. https://doi.org/10.26697/ijes.2021.1.5
Richemond, D., & Huggins-Jordan, T. D. (2023) The impact of health information systems on patient outcomes. Open Access Library Journal, 10(8). https://doi.org/10.4236/oalib.1110518
Savage, M., & Savage, L. C. (2020). Doctors routinely share health data electronically under HIPAA, and sharing with patients and patients third-party health apps is consistent: Interoperability and privacy analysis. Journal of Medical Internet Research, 22(9), Article e19818. https://doi.org/10.2196/19818
Szarfman, A., Levine, J. G., & Tonning, J. M. (2022) Recommendations for achieving interoperable and shareable medical data in the USA. Communications Medicine 2, Article 86. https://doi.org/10.1038/s43856-022-00148-x
Tsegaye, T., & Flowerday, S. (2021). A system architecture for ensuring interoperability in a South African national electronic health record system. South African Computer Journal, 33(1), 79–110. https://dx.doi.org/10.18489/sacj.v33i1.838
Torab-Miandoab, A., Samad-Soltani, T., Jodati, A., & Rezaei-Hachesu, P. (2023). Interoperability of heterogeneous health information systems: A systematic literature review. BMC Medical Informatics and Decision Making, 23(1), Article 18. https://doi.org/10.1186/s12911-023-02115-5
Udekwe, E., Iwu, C. G., de la Harpe, A. C., & Daramola, J. O. (2021). A systematic literature review of Human Resource Information System (HRIS) usage in the health system of South Africa. International Journal of Research in Business and Social Science, 10(7), 87–115. https://doi.org/10.20525/ijrbs.v10i7.1424
Yusif, S., Hafeez-Baig, A., & Soar, J. (2020). An exploratory study of the readiness of public healthcare facilities in developing countries to adopt health information technology (HIT)/e-Health: The case of Ghana. Journal of Healthcare Informatics Research, 4, 189–214. https://doi.org/10.1007/s41666-020-00070-8
Rikhotso Matimu – https://orcid.org/0009-0001-9665-664X; MComp, Tshwane University of Technology, Pretoria, South Africa.
Kalema Billy Mathias – https://orcid.org/0000-0002-2405-9088; Doctor of Philosophy in Computer Science, Professor, University of Mpumalanga, Mbombela, South Africa.
Seaba Tshinakaho Relebogile (Corresponding Author) – https://orcid.org/0000-0002-5773-887X;
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APA
Rikhotso, M., Kalema, B. M., & Seaba, T. R. (2024). Data interoperability assessment model for health information system in South African public healthcare. International Journal of Science Annals, 7(2), 1–9. https://doi.org/10.26697/ijsa.2024.2.4
Harvard
Rikhotso, M., Kalema, B. M., & Seaba, T. R. "Data interoperability assessment model for health information system in South African public healthcare." International Journal of Science Annals, [online] 7(2), pp. 1–9. viewed 25 December 2024, https://culturehealth.org/ijsa_archive/ijsa.2024.2.4.pdfVancouver
Rikhotso M., Kalema B. M., & Seaba T. R. Data interoperability assessment model for health information system in South African public healthcare. International Journal of Science Annals [Internet]. 2024 [cited 25 December 2024]; 7(2): 1–9. Available from: https://culturehealth.org/ijsa_archive/ijsa.2024.2.4.pdf https://doi.org/10.26697/ijsa.2024.2.4
