Background: The Electronic Health Record Sharing System (eHRSS) is an electronic platform for two-way communication between the public and private sectors in Hong Kong. The authorised healthcare professionals (HCProfs) could access and upload patients' health records on the eHR Viewer in the eHRSS. This study aims to evaluate the usage of eHR viewer among the HCProfs from the private sector by 1) examining the correlation of various factors and the data access of eHR viewer; 2) investigating the trend on data access and upload to eHR viewer by time period and domain.
Methods: A total of 3972 HCProfs from private hospitals, group practice, and solo practice were included in the study. Regression analysis was performed to identify the correlation between various factors and the data access to eHR viewer. Trends on accessing and data uploading to eHR viewer by time period and domains were evaluated. Trends on data uploading to eHR viewer by time period and domains were presented in the line chart as well.
Findings: All types of HCProfs had a higher likelihood of accessing the eHR viewer as compared to those from private hospitals. HCProfs with specialities (apart from anaesthesia) had a higher possibility of accessing the eHR viewer than general practitioners without specialities. HCProfs participating in the Public-Private Partnership (PPP) Programme and the eHealth System (Subsidies) (eHS(S)) were more likely to access the eHR viewer. The overall trend of accessing eHR viewer was rising notably from 2016 to 2022, every domain showed rising trends, especially the laboratory domain with a 5-times increase between 2016 and 2022.
Conclusion: HCProfs with speciality were more likely to access the eHR viewer (except anaesthesiology), compared with the general practitioners. Participation in the PPP programmes and eHS(S) also increased the access rate of the eHR viewer. Besides, the use of eHR viewer (accessing and data uploading) would be influenced by social policy and the epidemic. Future research should focus on the impact of government programmes on eHRSS adoption.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.ijmedinf.2023.105137 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Artificial Intelligence-Based Diagnostic Support System for Patent Ductus Arteriosus in Premature Infants.
J Clin Med
April 2024
Department of Computer Science, Yonsei University, 50 Yonsei-ro, Seoul 03722, Republic of Korea.
: Patent ductus arteriosus (PDA) is a prevalent congenital heart defect in premature infants, associated with significant morbidity and mortality. Accurate and timely diagnosis of PDA is crucial, given the vulnerability of this population. : We introduce an artificial intelligence (AI)-based PDA diagnostic support system designed to assist medical professionals in diagnosing PDA in premature infants.
View Article and Find Full Text PDFDICOM® integrated EEG data: A first clinical implementation of the new DICOM standard for neurophysiology data.
Clin Neurophysiol
November 2023
Department of Neurology, Clinic Hietzing, Vienna, Austria; Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, Vienna, Austria; Medical Faculty, Sigmund Freud University, Vienna, Austria.
Objective: Demonstrating a pilot implementation of the Digital Imaging and Communication in Medicine (DICOM) neurophysiology standard published in 2020.
Methods: An automated workflow for converting EEG data from a proprietary vendor EEG format to standardized and interoperable DICOM format was developed and tested.
Results: Retrieval of proprietary EEG data, associated videos, annotations and metadata from the vendor EEG archive and their subsequent conversion to DICOM EEG was possible without changes to the departmental workflow.
Usage of electronic health record (eHR) viewer among healthcare professionals (HCProfs): A territory-wide study of 3972 participants.
Int J Med Inform
September 2023
JC School of Public Health and Primary Care, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong Special Administrative Region; Centre for Health Education and Health Promotion, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; School of Public Health, Peking Union Medical College, Beijing, China; School of Public Health, Peking University, Beijing, China. Electronic address:
Background: The Electronic Health Record Sharing System (eHRSS) is an electronic platform for two-way communication between the public and private sectors in Hong Kong. The authorised healthcare professionals (HCProfs) could access and upload patients' health records on the eHR Viewer in the eHRSS. This study aims to evaluate the usage of eHR viewer among the HCProfs from the private sector by 1) examining the correlation of various factors and the data access of eHR viewer; 2) investigating the trend on data access and upload to eHR viewer by time period and domain.
View Article and Find Full Text PDFWhat Goes Up, Must Come Down: A State-of-the-Art Electronic Health Record Downtime and Uptime Procedure in a Metropolitan Health Setting.
Appl Clin Inform
May 2023
Biomedical Informatics and Digital Health, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.
Background: Electronic health records (EHRs) are used at most hospitals around the world, and downtime events are inevitable and common. Downtime represents a risky time for patients because patient information and critical EHR functionality are unavailable. Many institutions have used EHRs for years, with health professionals less likely to be familiar or comfortable with paper-based processes, resulting in an increased risk of errors during downtimes.
View Article and Find Full Text PDFA Structured Analysis to study the Role of Machine Learning and Deep Learning in The Healthcare Sector with Big Data Analytics.
Arch Comput Methods Eng
March 2023
Center of Excellence in Weather & Climate Analytics, Atmospheric Sciences Research Center (ASRC), University at Albany (UAlbany), State University of New York (SUNY), Albany, New York 12226 USA.
Machine and deep learning are used worldwide. Machine Learning (ML) and Deep Learning (DL) are playing an increasingly important role in the healthcare sector, particularly when combined with big data analytics. Some of the ways that ML and DL are being used in healthcare include Predictive Analytics, Medical Image Analysis, Drug Discovery, Personalized Medicine, and Electronic Health Records (EHR) Analysis.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!