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Standardizing Corneal Transplantation Records Using openEHR: Case Study. | LitMetric

Standardizing Corneal Transplantation Records Using openEHR: Case Study.

JMIR Med Inform

ALGORITMI Research Center, Intelligent Systems Associate Laboratory (LASI), School of Engineering, University of Minho, Guimarães, Portugal.

Published: September 2024

AI Article Synopsis

  • Corneal transplantation is a vital surgical procedure for restoring vision, but existing electronic health records (EHRs) are often inconsistent and fragmented, causing issues in patient data management and safety.
  • This research advocates for the adoption of openEHR structures to standardize records related to corneal transplantation, aiming to improve data quality and sharing among healthcare providers.
  • The study implemented openEHR specifications through collaboration with healthcare professionals, resulting in a streamlined solution that was successfully integrated into a Portuguese hospital, enhancing clinical practices involved in corneal transplantation.

Article Abstract

Background: Corneal transplantation, also known as keratoplasty, is a widely performed surgical procedure that aims to restore vision in patients with corneal damage. The success of corneal transplantation relies on the accurate and timely management of patient information, which can be enhanced using electronic health records (EHRs). However, conventional EHRs are often fragmented and lack standardization, leading to difficulties in information access and sharing, increased medical errors, and decreased patient safety. In the wake of these problems, there is a growing demand for standardized EHRs that can ensure the accuracy and consistency of patient data across health care organizations.

Objective: This paper proposes the use of openEHR structures for standardizing corneal transplantation records. The main objective of this research was to improve the quality and interoperability of EHRs in corneal transplantation, making it easier for health care providers to capture, share, and analyze clinical information.

Methods: A series of sequential steps were carried out in this study to implement standardized clinical records using openEHR specifications. These specifications furnish a methodical approach that ascertains the development of high-quality clinical records. In broad terms, the methodology followed encompasses the conduction of meetings with health care professionals and the modeling of archetypes, templates, forms, decision rules, and work plans.

Results: This research resulted in a tailored solution that streamlines health care delivery and meets the needs of medical professionals involved in the corneal transplantation process while seamlessly aligning with contemporary clinical practices. The proposed solution culminated in the successful integration within a Portuguese hospital of 3 key components of openEHR specifications: forms, Decision Logic Modules, and Work Plans. A statistical analysis of data collected from May 1, 2022, to March 31, 2023, allowed for the perception of the use of the new technologies within the corneal transplantation workflow. Despite the completion rate being only 63.9% (530/830), which can be explained by external factors such as patient health and availability of donor organs, there was an overall improvement in terms of task control and follow-up of the patients' clinical process.

Conclusions: This study shows that the adoption of openEHR structures represents a significant step forward in the standardization and optimization of corneal transplantation records. It offers a detailed demonstration of how to implement openEHR specifications and highlights the different advantages of standardizing EHRs in the field of corneal transplantation. Furthermore, it serves as a valuable reference for researchers and practitioners who are interested in advancing and improving the exploitation of EHRs in health care.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11443176PMC
http://dx.doi.org/10.2196/48407DOI Listing

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