A review on solving the interoperability challenge of health care systems using artificial intelligence

Michael Nyoro; John Kamau; Joyce Gikandi

doi:10.51867/ajernet.6.3.79

Authors

Michael Nyoro Mount Kenya University, Kenya https://orcid.org/0000-0003-0052-5854
John Kamau Mount Kenya University, Kenya
Joyce Gikandi Mount Kenya University, Kenya https://orcid.org/0000-0001-8531-6212

DOI:

https://doi.org/10.51867/ajernet.6.3.79

Keywords:

Automation, Data Consistency, Healthcare Interoperability, Health Information Exchange, National Standards, Patient Care, Socio Technical Systems

Abstract

Tackling the challenge of healthcare interoperability calls for more than just technical fixes; it needs a well-coordinated and collaborative effort that brings together both systems and people. This study, grounded in sociotechnical systems theory, recognizes that successful health information exchange depends not only on technology but also on how people work together around it. The research aimed to pinpoint where current data sharing falls short, explore how well automated tools help standardize and connect health information, and understand how better interoperability affects patient care and health system efficiency. To do this, a mixed methods approach was used: quantitative analysis of healthcare data highlighted where inconsistencies and breakdowns were happening, while interviews and focus groups with healthcare workers and system developers provided deeper insights into what is working and what is not. The results showed that many healthcare facilities still operate on systems that do not talk to each other well, leading to fragmented data and unnecessary delays. But when automation was introduced, tools that translate and link data from different systems made a big difference. Information became more consistent, manual entry errors dropped, and providers gained quicker access to patient records. The study found that to truly improve interoperability, healthcare systems need to invest in integrated solutions that prioritize data consistency, security, and compatibility. It recommends developing national standards for how health data is shared, offering more training to health workers on using digital tools, and building stronger partnerships between healthcare providers, tech developers, and policymakers. When these pieces come together, the result is a more connected, efficient, and patient-centered healthcare system where everyone involved can work smarter and deliver better care.

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