Security and privacy consideration for the deployment of electronic health records: a qualitative study covering Greece and Oman

2021 ◽  
pp. 1-17
Author(s):  
Ourania Koutzampasopoulou Xanthidou ◽  
Dimitrios Xanthidis ◽  
Christos Manolas ◽  
Han-I Wang
Keyword(s):  
Qualitative Study ◽  
Electronic Health Records ◽  
Security And Privacy ◽  
Health Records ◽  
Electronic Health

scholarly journals Secure Exchange of Medical Data Using a Novel Real-Time Biometric-Based Protection and Recognition Method

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2013
Author(s):  
Shams Ud Din ◽  
Zahoor Jan ◽  
Muhammad Sajjad ◽  
Maqbool Hussain ◽  
Rahman Ali ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Real Time ◽  
Signal To Noise Ratio ◽  
Security And Privacy ◽  
The Internet ◽  
Healthcare Organizations ◽  
Health Records ◽  
Clinical Notes ◽  
Electronic Health ◽  
Value Decomposition

Security and privacy are essential requirements, and their fulfillment is considered one of the most challenging tasks for healthcare organizations to manage patient data using electronic health records. Electronic health records (clinical notes, images, and documents) become more vulnerable to breaching patients’ privacy when shared with an external organization in the current arena of the internet of medical things (IoMT). Various watermarking techniques were introduced in the medical field to secure patients’ data. Most of the existing techniques focus on an image or document’s imperceptibility without considering the watermark(logo). In this research, a novel technique of watermarking is introduced, which supersedes the shortcomings of existing approaches. It guarantees the imperceptibility of the image/document and takes care of watermark(biometric), which is further passed through a process of recognition for claiming ownership. It extracts suitable frequencies from the transform domain using specialized filters to increase the robustness level. The extracted frequencies are modified by adding the biomedical information while considering the strength factor according to the human visual system. The watermarked frequencies are further decomposed through a singular value decomposition technique to increase payload capacity up to (256 × 256). Experimental results over a variety of medical and official images demonstrate the average peak signal-to-noise ratio (PSNR 54.43), and the normal correlation (N.C.) value is 1. PSNR and N.C. of the watermark were calculated after attacks. The proposed technique is working in real-time for embedding, extraction, and recognition of biometrics over the internet, and its uses can be realized in various platforms of IoMT technologies.

scholarly journals Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study

2018 ◽  
Vol 25 (2) ◽  
pp. 109-125 ◽  
Author(s):  
Mark Chun Moon ◽  
Rebecca Hills ◽  
George Demiris
Keyword(s):  
United States ◽  
Qualitative Study ◽  
Electronic Health Records ◽  
Hospital Setting ◽  
The United States ◽  
Theory Approach ◽  
Health Records ◽  
High Performing ◽  
Advisory Groups ◽  
Electronic Health

BackgroundLittle is known about optimisation of electronic health records (EHRs) systems in the hospital setting while adoption of EHR systems continues in the United States.ObjectiveTo understand optimisation processes of EHR systems undertaken in leading healthcare organisations in the United States.MethodsInformed by a grounded theory approach, a qualitative study was undertaken that involved 11 in-depth interviews and a focus group with the EHR experts from the high performing healthcare organisations across the United States.ResultsThe study describes EHR optimisation processes characterised by prioritising exponentially increasing requests with predominant focus on improving efficiency of EHR, building optimisation teams or advisory groups and standardisation. The study discusses 16 types of optimisation that interdependently produced 16 results along with identifying 11 barriers and 20 facilitators to optimisation.ConclusionsThe study describes overall experiences of optimising EHRs in select high performing healthcare organisations in the US. The findings highlight the importance of optimising the EHR after, and even before, go-live and dedicating resources exclusively for optimisation.

scholarly journals Barriers and facilitators to data quality of electronic health records used for clinical research in China: a qualitative study

BMJ Open ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. e029314 ◽  
Author(s):  
Kaiwen Ni ◽  
Hongling Chu ◽  
Lin Zeng ◽  
Nan Li ◽  
Yiming Zhao
Keyword(s):  
Qualitative Study ◽  
Electronic Health Records ◽  
Clinical Research ◽  
Data Quality ◽  
Healthcare Professionals ◽  
Barriers And Facilitators ◽  
Health Records ◽  
Improve Data Quality ◽  
Electronic Health

ObjectivesThere is an increasing trend in the use of electronic health records (EHRs) for clinical research. However, more knowledge is needed on how to assure and improve data quality. This study aimed to explore healthcare professionals’ experiences and perceptions of barriers and facilitators of data quality of EHR-based studies in the Chinese context.SettingFour tertiary hospitals in Beijing, China.ParticipantsNineteen healthcare professionals with experience in using EHR data for clinical research participated in the study.MethodsA qualitative study based on face-to-face semistructured interviews was conducted from March to July 2018. The interviews were audiorecorded and transcribed verbatim. Data analysis was performed using the inductive thematic analysis approach.ResultsThe main themes included factors related to healthcare systems, clinical documentation, EHR systems and researchers. The perceived barriers to data quality included heavy workload, staff rotations, lack of detailed information for specific research, variations in terminology, limited retrieval capabilities, large amounts of unstructured data, challenges with patient identification and matching, problems with data extraction and unfamiliar with data quality assessment. To improve data quality, suggestions from participants included: better staff training, providing monetary incentives, performing daily data verification, improving software functionality and coding structures as well as enhancing multidisciplinary cooperation.ConclusionsThese results provide a basis to begin to address current barriers and ultimately to improve validity and generalisability of research findings in China.

scholarly journals Approaches to Recording Drug Allergies in Electronic Health Records: Qualitative Study

PLoS ONE ◽  
2014 ◽  
Vol 9 (4) ◽  
pp. e93047 ◽  
Author(s):  
Bernard Fernando ◽  
Zoe Morrison ◽  
Dipak Kalra ◽  
Kathrin Cresswell ◽  
Aziz Sheikh
Keyword(s):  
Qualitative Study ◽  
Electronic Health Records ◽  
Health Records ◽  
Electronic Health

scholarly journals Home Healthcare Clinicians’ Perspectives on Electronic Health Records: A Qualitative Study

2021 ◽  
Author(s):  
Mollie Hobensack ◽  
Marietta Ojo ◽  
Kathryn Bowles ◽  
Margaret McDonald ◽  
Jiyoun Song ◽  
...  
Keyword(s):  
Qualitative Study ◽  
Electronic Health Records ◽  
Thematic Analysis ◽  
Qualitative Interviews ◽  
Home Healthcare ◽  
Patient Risk ◽  
Health Records ◽  
Risk Detection ◽  
Electronic Health ◽  
Northeastern Usa

Clinicians’ perspectives on the electronic health records (EHR) in home healthcare (HHC) are understudied. To explore this topic, qualitative interviews were conducted with 15 HHC clinicians in the Northeastern USA. Thematic analysis was conducted to identify key themes emerging from the interviews. While some EHR benefits were recognized, overall satisfaction with the EHR was low. The results suggest EHR limitations are tied to poor usability, restrictions, and redundancy in documentation leading to increased documentation workload. Clinicians have recommendations to mitigate these limitations via additional EHR functions and better patient risk detection. Future stakeholders should consider the results of this study when developing and updating the EHR in HHC.

scholarly journals Morton Filter-Based Security Mechanism for Healthcare System in Cloud Computing

Healthcare ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1551
Author(s):  
Sugandh Bhatia ◽  
Jyoteesh Malhotra
Keyword(s):  
Electronic Health Records ◽  
Data Structures ◽  
Cloud Security ◽  
Healthcare Systems ◽  
Security And Privacy ◽  
Load Factor ◽  
Security Mechanism ◽  
Health Records ◽  
Reliability Factor ◽  
Electronic Health

Electronic health records contain the patient’s sensitive information. If these data are acquired by a malicious user, it will not only cause the pilferage of the patient’s personal data but also affect the diagnosis and treatment. One of the most challenging tasks in cloud-based healthcare systems is to provide security and privacy to electronic health records. Various probabilistic data structures and watermarking techniques were used in the cloud-based healthcare systems to secure patient’s data. Most of the existing studies focus on cuckoo and bloom filters, without considering their throughputs. In this research, a novel cloud security mechanism is introduced, which supersedes the shortcomings of existing approaches. The proposed solution enhances security with methods such as fragile watermark, least significant bit replacement watermarking, class reliability factor, and Morton filters included in the formation of the security mechanism. A Morton filter is an approximate set membership data structure (ASMDS) that proves many improvements to other data structures, such as cuckoo, bloom, semi-sorting cuckoo, and rank and select quotient filters. The Morton filter improves security; it supports insertions, deletions, and lookups operations and improves their respective throughputs by 0.9× to 15.5×, 1.3× to 1.6×, and 1.3× to 2.5×, when compared to cuckoo filters. We used Hadoop version 0.20.3, and the platform was Red Hat Enterprise Linux 6; we executed five experiments, and the average of the results has been taken. The results of the simulation work show that our proposed security mechanism provides an effective solution for secure data storage in cloud-based healthcare systems, with a load factor of 0.9. Furthermore, to aid cloud security in healthcare systems, we presented the motivation, objectives, related works, major research gaps, and materials and methods; we, thus, presented and implemented a cloud security mechanism, in the form of an algorithm and a set of results and conclusions.

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