scholarly journals Authorized Shared Electronic Medical Record System with Proxy Re-Encryption and Blockchain Technology

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7765
Author(s):  
Weizhe Chen ◽  
Shunzhi Zhu ◽  
Jianmin Li ◽  
Jiaxin Wu ◽  
Chin-Ling Chen ◽  
...  
Keyword(s):  
Access Control ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Data Privacy ◽  
Data Access ◽  
Electronic Medical Record System ◽  
Record System ◽  
Medical Record System

With the popularity of the internet 5G network, the network constructions of hospitals have also rapidly developed. Operations management in the healthcare system is becoming paperless, for example, via a shared electronic medical record (EMR) system. A shared electronic medical record system plays an important role in reducing diagnosis costs and improving diagnostic accuracy. In the traditional electronic medical record system, centralized database storage is typically used. Once there is a problem with the data storage, it could cause data privacy disclosure and security risks. Blockchain is tamper-proof and data traceable. It can ensure the security and correctness of data. Proxy re-encryption technology can ensure the safe sharing and transmission of relatively sensitive data. Based on the above situation, we propose an electronic medical record system based on consortium blockchain and proxy re-encryption to solve the problem of EMR security sharing. Electronic equipment in this process is connected to the blockchain network, and the security of data access is ensured through the automatic execution of blockchain chaincodes; the attribute-based access control method ensures fine-grained access to the data and improves the system security. Compared with the existing electronic medical records based on cloud storage, the system not only realizes the sharing of electronic medical records, but it also has advantages in privacy protection, access control, data security, etc.

scholarly journals HealthyBlock: Blockchain-Based IT Architecture for Electronic Medical Records Resilient to Connectivity Failures

2020 ◽  
Vol 17 (19) ◽  
pp. 7132
Author(s):  
Omar Gutiérrez ◽  
Giordy Romero ◽  
Luis Pérez ◽  
Augusto Salazar ◽  
Marina Charris ◽  
...  
Keyword(s):  
Medical Record ◽  
Electronic Medical Record ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Medical Information ◽  
High Efficiency ◽  
Electronic Medical Record System ◽  
Security And Privacy ◽  
Record System ◽  
Treatment And Prevention

The current information systems for the registration and control of electronic medical records (EMR) present a series of problems in terms of the fragmentation, security, and privacy of medical information, since each health institution, laboratory, doctor, etc. has its own database and manages its own information, without the intervention of patients. This situation does not favor effective treatment and prevention of diseases for the population, due to potential information loss, misinformation, or data leaks related to a patient, which in turn may imply a direct risk for the individual and high public health costs for governments. One of the proposed solutions to this problem has been the creation of electronic medical record (EMR) systems using blockchain networks; however, most of them do not take into account the occurrence of connectivity failures, such as those found in various developing countries, which can lead to failures in the integrity of the system data. To address these problems, HealthyBlock is presented in this paper as an architecture based on blockchain networks, which proposes a unified electronic medical record system that considers different clinical providers, with resilience in data integrity during connectivity failure and with usability, security, and privacy characteristics. On the basis of the HealthyBlock architecture, a prototype was implemented for the care of patients in a network of hospitals. The results of the evaluation showed high efficiency in keeping the EMRs of patients unified, updated, and secure, regardless of the network clinical provider they consult.

Impact of Wireless Electronic Medical Record System on the Quality of Patient Documentation by Emergency Field Responders during a Disaster Mass-Casualty Exercise

2011 ◽  
Vol 26 (4) ◽  
pp. 268-275 ◽  
Author(s):  
Theodore C. Chan ◽  
William G. Griswold ◽  
Colleen Buono ◽  
David Kirsh ◽  
Joachim Lyon ◽  
...  
Keyword(s):  
Medical Record ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Electronic Medical Record System ◽  
Mass Casualty ◽  
Record System ◽  
Medical Record System ◽  
Patient Documentation ◽  
Field Exercise

AbstractIntroduction: The use of wireless, electronic, medical records and communications in the prehospital and disaster field is increasing.Objective: This study examines the role of wireless, electronic, medical records and communications technologies on the quality of patient documentation by emergency field responders during a mass-casualty exercise.Methods: A controlled, side-to-side comparison of the quality of the field responder patient documentation between responders utilizing National Institutes of Health-funded, wireless, electronic, field, medical record system prototype (“Wireless Internet Information System for medicAl Response to Disasters” or WIISARD) versus those utilizing conventional, paper-based methods during a mass-casualty field exercise. Medical data, including basic victim identification information, acuity status, triage information using Simple Triage and Rapid Treatment (START), decontamination status, and disposition, were collected for simulated patients from all paper and electronic logs used during the exercise. The data were compared for quality of documentation and record completeness comparing WIISARD-enabled field responders and those using conventional paper methods. Statistical analysis was performed with Fisher’s Exact Testing of Proportions with differences and 95% confidence intervals reported.Results: One hundred simulated disaster victim volunteers participated in the exercise, 50 assigned to WIISARD and 50 to the conventional pathway. Of those victims who completed the exercise and were transported to area hospitals, medical documentation of victim START components and triage acuity were significantly better for WIISARD compared to controls (overall acuity was documented for 100% vs 89.5%, respectively, difference = 10.5% [95%CI = 0.5–24.1%]). Similarly, tracking of decontamination status also was higher for the WIISARD group (decontamination status documented for 59.0% vs 0%, respectively, difference = 9.0% [95%CI = 40.9–72.0%]). Documentation of disposition and destination of victims was not different statistically (92.3% vs. 89.5%, respectively, difference = 2.8% [95%CI = -11.3–17.3%]).Conclusions: In a simulated, mass-casualty field exercise, documentation and tracking of victim status including acuity was significantly improved when using a wireless, field electronic medical record system compared to the use of conventional paper methods.

scholarly journals Forecast of Outpatient Visits to a Tertiary Eyecare Network in India Using the EyeSmart Electronic Medical Record System

Healthcare ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 749
Author(s):  
Gumpili Sai Prashanthi ◽  
Nareen Molugu ◽  
Priyanka Kammari ◽  
Ranganath Vadapalli ◽  
Anthony Vipin Das
Keyword(s):  
Medical Record ◽  
Electronic Medical Record ◽  
Time Series Data ◽  
Resource Planning ◽  
Healthcare Services ◽  
Electronic Medical Record System ◽  
Series Data ◽  
Record System ◽  
Outpatient Visits ◽  
Medical Record System

India is home to 1.3 billion people. The geography and the magnitude of the population present unique challenges in the delivery of healthcare services. The implementation of electronic health records and tools for conducting predictive modeling enables opportunities to explore time series data like patient inflow to the hospital. This study aims to analyze expected outpatient visits to the tertiary eyecare network in India using datasets from a domestically developed electronic medical record system (eyeSmart™) implemented across a large multitier ophthalmology network in India. Demographic information of 3,384,157 patient visits was obtained from eyeSmart EMR from August 2010 to December 2017 across the L.V. Prasad Eye Institute network. Age, gender, date of visit and time status of the patients were selected for analysis. The datapoints for each parameter from the patient visits were modeled using the seasonal autoregressive integrated moving average (SARIMA) modeling. SARIMA (0,0,1)(0,1,7)7 provided the best fit for predicting total outpatient visits. This study describes the prediction method of forecasting outpatient visits to a large eyecare network in India. The results of our model hold the potential to be used to support the decisions of resource planning in the delivery of eyecare services to patients.

scholarly journals A simple electronic medical record system designed for research

JAMIA Open ◽  
2021 ◽  
Vol 4 (3) ◽  
Author(s):  
Andrew J King ◽  
Luca Calzoni ◽  
Mohammadamin Tajgardoon ◽  
Gregory F Cooper ◽  
Gilles Clermont ◽  
...  
Keyword(s):  
Medical Record ◽  
Electronic Medical Record ◽  
User Interfaces ◽  
Information Seeking ◽  
Vital Signs ◽  
Electronic Medical Record System ◽  
Record System ◽  
Laboratory Test Results ◽  
Medical Record System ◽  
Open Source Software Package

Abstract With the extensive deployment of electronic medical record (EMR) systems, EMR usability remains a significant source of frustration to clinicians. There is a significant research need for software that emulates EMR systems and enables investigators to conduct laboratory-based human–computer interaction studies. We developed an open-source software package that implements the display functions of an EMR system. The user interface emphasizes the temporal display of vital signs, medication administrations, and laboratory test results. It is well suited to support research about clinician information-seeking behaviors and adaptive user interfaces in terms of measures that include task accuracy, time to completion, and cognitive load. The Simple EMR System is freely available to the research community and is on GitHub.

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