scholarly journals Security and Privacy Concerns Regarding Genetic Data in Mobile Health Record Systems: An Empirical Study from Turkey

2019 ◽  
Author(s):  
Özlem Özkan ◽  
Yeşim Aydin Son ◽  
Arsev Umur Aydinoğlu
Keyword(s):  
Genetic Testing ◽  
Mobile Health ◽  
Genetic Data ◽  
Security And Privacy ◽  
Health Record ◽  
Privacy And Security ◽  
Negative Experience ◽  
Health Records ◽  
Privacy Concerns ◽  
Electronic Health

AbstractWith the increasing use of genetic testing and applications of bioinformatics in healthcare, genetic and genomic data needs to be integrated into electronic health systems. We administered a descriptive survey to 174 participants to elicit their views on the privacy and security of mobile health record systems and inclusion of their genetic data in these systems. A survey was implemented online and on site in two genetic diagnostic centres. Nearly half of the participants or their close family members had undergone genetic testing. Doctors constituted the only profession group that people trusted for the privacy of their health and genetic data; however, people chose to limit even their doctor’s access to their genetic/health records. The majority of the respondents preferred to keep full access for themselves. Several participants had negative experience or preconceptions about electronic health records: the medical reports of 9.7% of the respondents had been used or released without their consent, 15.1% stated that they avoided being tested due to violation risks, and 3.5% asked their doctors to enter a less embarrassing health status in their records. The participants wanted to see some regulations and security measurements before using any system for their health/genetic data. In addition, significantly more participants stating that storing genetic data in a mobile system was riskier compared to other health data. Furthermore, the comparative analysis revealed that being young, being a woman and having higher education were associated with having greater privacy concerns.

scholarly journals Selecting Mobile Health Technologies for Electronic Health Record Integration: Case Study (Preprint)

2020 ◽  
Author(s):  
Ryan Shaw ◽  
Marissa Stroo ◽  
Christopher Fiander ◽  
Katlyn McMillan
Keyword(s):  
Case Report ◽  
Mobile Health ◽  
Wearable Devices ◽  
Environmental Data ◽  
Health Record ◽  
Health Records ◽  
Health Technologies ◽  
Electronic Health ◽  
Selection Of

UNSTRUCTURED Mobile health (mHealth) technologies, such as wearable devices and sensors that can be placed in the home, allow for the capture of physiologic, behavioral, and environmental data from patients between clinic visits. The inclusion of these data in the medical record may benefit patients and providers. Most health systems now have electronic health records (EHRs), and the ability to pull and send data to and from mobile devices via smartphones and other methods is increasing; however, many challenges exist in the evaluation and selection of devices to integrate to meet the needs of diverse patients with a range of clinical needs. We present a case report that describes a method that our health system uses, guided by a telehealth model to evaluate the selection of devices for EHR integration.

scholarly journals Selecting Mobile Health Technologies for Electronic Health Record Integration: Case Study

10.2196/23314 ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. e23314
Author(s):  
Ryan Shaw ◽  
Marissa Stroo ◽  
Christopher Fiander ◽  
Katlyn McMillan
Keyword(s):  
Case Report ◽  
Mobile Health ◽  
Wearable Devices ◽  
Environmental Data ◽  
Health Record ◽  
Health Records ◽  
Health Technologies ◽  
Electronic Health ◽  
Selection Of

Mobile health (mHealth) technologies, such as wearable devices and sensors that can be placed in the home, allow for the capture of physiologic, behavioral, and environmental data from patients between clinic visits. The inclusion of these data in the medical record may benefit patients and providers. Most health systems now have electronic health records (EHRs), and the ability to pull and send data to and from mobile devices via smartphones and other methods is increasing; however, many challenges exist in the evaluation and selection of devices to integrate to meet the needs of diverse patients with a range of clinical needs. We present a case report that describes a method that our health system uses, guided by a telehealth model to evaluate the selection of devices for EHR integration.

scholarly journals Artificial intelligence and multi agent based distributed ledger system for better privacy and security of electronic healthcare records

2020 ◽  
Vol 6 ◽  
pp. e323
Author(s):  
Fahad F. Alruwaili
Keyword(s):  
Artificial Intelligence ◽  
Electronic Health Records ◽  
Privacy Preservation ◽  
Security And Privacy ◽  
Privacy And Security ◽  
Health Records ◽  
Agent Based ◽  
Distributed Ledger ◽  
Multi Agent ◽  
Electronic Health

Background Application of Artificial Intelligence (AI) and the use of agent-based systems in the healthcare system have attracted various researchers to improve the efficiency and utility in the Electronic Health Records (EHR). Nowadays, one of the most important and creative developments is the integration of AI and Blockchain that is, Distributed Ledger Technology (DLT) to enable better and decentralized governance. Privacy and security is a critical piece in EHR implementation and/or adoption. Health records are updated every time a patient visits a doctor as they contain important information about the health and wellbeing of the patient and describes the history of care received during the past and to date. Therefore, such records are critical to research, hospitals, emergency rooms, healthcare laboratories, and even health insurance providers. Methods In this article, a platform employing the AI and the use of multi-agent based systems along with the DLT technology for privacy preservation is proposed. The emphasis of security and privacy is highlighted during the process of collecting, managing and distributing EHR data. Results This article aims to ensure privacy, integrity and security metrics of the electronic health records are met when such copies are not only immutable but also distributed. The findings of this work will help guide the development of further techniques using the combination of AI and multi-agent based systems backed by DLT technology for secure and effective handling EHR data. This proposed architecture uses various AI-based intelligent based agents and blockchain for providing privacy and security in EHR. Future enhancement in this work can be the addition of the biometric based systems for improved security.

scholarly journals Lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ruowang Li ◽  
Rui Duan ◽  
Xinyuan Zhang ◽  
Thomas Lumley ◽  
Sarah Pendergrass ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Genetic Data ◽  
Test Statistics ◽  
Health Records ◽  
Privacy Concerns ◽  
Individual Level ◽  
Multiple Datasets ◽  
Level Data ◽  
Electronic Health ◽  
Identical Test

AbstractIncreasingly, clinical phenotypes with matched genetic data from bio-bank linked electronic health records (EHRs) have been used for pleiotropy analyses. Thus far, pleiotropy analysis using individual-level EHR data has been limited to data from one site. However, it is desirable to integrate EHR data from multiple sites to improve the detection power and generalizability of the results. Due to privacy concerns, individual-level patients’ data are not easily shared across institutions. As a result, we introduce Sum-Share, a method designed to efficiently integrate EHR and genetic data from multiple sites to perform pleiotropy analysis. Sum-Share requires only summary-level data and one round of communication from each site, yet it produces identical test statistics compared with that of pooled individual-level data. Consequently, Sum-Share can achieve lossless integration of multiple datasets. Using real EHR data from eMERGE, Sum-Share is able to identify 1734 potential pleiotropic SNPs for five cardiovascular diseases.

Electronic Health Records Implementation in Jordan: Perceptions of Healthcare Providers and Determinant Factors (Preprint)

2020 ◽  
Author(s):  
Tamadur Shudayfat ◽  
Çağdaş Akyürek ◽  
Noha Al-Shdayfat ◽  
Hatem Alsaqqa
Keyword(s):  
Electronic Health Records ◽  
Electronic Health Record ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Healthcare Providers ◽  
Health Record ◽  
Health Records ◽  
Context Factors ◽  
Electronic Health ◽  
Acceptance Model

BACKGROUND Acceptance of Electronic Health Record systems is considered an essential factor for an effective implementation among the Healthcare providers. In an attempt to understand the healthcare providers’ perceptions on the Electronic Health Record systems implementation and evaluate the factors influencing healthcare providers’ acceptance of Electronic Health Records, the current research examines the effects of individual (user) context factors, and organizational context factors, using Technology Acceptance Model. OBJECTIVE The current research examines the effects of individual (user) context factors, and organizational context factors, using Technology Acceptance Model. METHODS A quantitative cross-sectional survey design was used, in which 319 healthcare providers from five public hospital participated in the present study. Data was collected using a self-administered questionnaire, which was based on the Technology Acceptance Model. RESULTS Jordanian healthcare providers demonstrated positive perceptions of the usefulness and ease of use of Electronic Health Record systems, and subsequently, they accepted the technology. The results indicated that they had a significant effect on the perceived usefulness and perceived ease of use of Electronic Health Record, which in turn was related to positive attitudes towards Electronic Health Record systems as well as the intention to use them. CONCLUSIONS User attributes, organizational competency, management support and training and education are essential variables in predicting healthcare provider’s acceptance toward Electronic Health records. These findings should be considered by healthcare organizations administration to introduce effective system to other healthcare organizations.

scholarly journals MedShard: Electronic Health Record Sharing Using Blockchain Sharding

2021 ◽  
Vol 13 (11) ◽  
pp. 5889
Author(s):  
Faiza Hashim ◽  
Khaled Shuaib ◽  
Farag Sallabi
Keyword(s):  
Healthcare System ◽  
Small Groups ◽  
Network Performance ◽  
Communication Overhead ◽  
Privacy And Security ◽  
Health Records ◽  
Medical Practitioners ◽  
Blockchain Technology ◽  
Simulation Results ◽  
Electronic Health

Electronic health records (EHRs) are important assets of the healthcare system and should be shared among medical practitioners to improve the accuracy and efficiency of diagnosis. Blockchain technology has been investigated and adopted in healthcare as a solution for EHR sharing while preserving privacy and security. Blockchain can revolutionize the healthcare system by providing a decentralized, distributed, immutable, and secure architecture. However, scalability has always been a bottleneck in blockchain networks due to the consensus mechanism and ledger replication to all network participants. Sharding helps address this issue by artificially partitioning the network into small groups termed shards and processing transactions parallelly while running consensus within each shard with a subset of blockchain nodes. Although this technique helps resolve issues related to scalability, cross-shard communication overhead can degrade network performance. This study proposes a transaction-based sharding technique wherein shards are formed on the basis of a patient’s previously visited health entities. Simulation results show that the proposed technique outperforms standard-based healthcare blockchain techniques in terms of the number of appointments processed, consensus latency, and throughput. The proposed technique eliminates cross-shard communication by forming complete shards based on “the need to participate” nodes per patient.

scholarly journals Assessing Users’ Privacy and Security Concerns of Smart Home Technologies

i-com ◽  
2019 ◽  
Vol 18 (3) ◽  
pp. 197-216 ◽  
Author(s):  
Verena Zimmermann ◽  
Paul Gerber ◽  
Karola Marky ◽  
Leon Böck ◽  
Florian Kirchbuchner
Keyword(s):  
Smart Home ◽  
Elderly Care ◽  
Security And Privacy ◽  
Structured Interviews ◽  
Privacy And Security ◽  
Privacy Concerns ◽  
Private Lives ◽  
Societal Level ◽  
Home Users

AbstractSmart Home technologies have the potential to increase the quality of life, home security and facilitate elderly care. Therefore, they require access to a plethora of data about the users’ homes and private lives. Resulting security and privacy concerns form a relevant barrier to adopting this promising technology. Aiming to support end users’ informed decision-making through addressing the concerns we first conducted semi-structured interviews with 42 potential and little-experienced Smart Home users. Their diverse concerns were clustered into four themes that center around attacks on Smart Home data and devices, the perceived loss of control, the trade-off between functionality and security, and user-centric concerns as compared to concerns on a societal level. Second, we discuss measures to address the four themes from an interdisciplinary perspective. The paper concludes with recommendations for addressing user concerns and for supporting developers in designing user-centered Smart Home technologies.

Implementation and evaluation of Stanford Health Care store-and-forward teledermatology consultation workflow built within an existing electronic health record system

2018 ◽  
Vol 26 (3) ◽  
pp. 125-131 ◽  
Author(s):  
Grace E Kim ◽  
Olga K Afanasiev ◽  
Chris O’Dell ◽  
Christopher Sharp ◽  
Justin M Ko
Keyword(s):  
Health Care ◽  
Electronic Health Record ◽  
Primary Care Physicians ◽  
Health Record ◽  
Record System ◽  
Privacy Concerns ◽  
Successful Model ◽  
Dermatology Clinic ◽  
Electronic Health ◽  
Store And Forward

Introduction Teledermatology services that function separately from patients’ primary electronic health record (EHR) can lead to fragmented care, poor provider communication, privacy concerns and billing challenges. This study addresses these challenges by developing PhotoCareMD, a store-and-forward (SAF) teledermatology consultation workflow built entirely within an existing Epic-based EHR. Methods Thirty-six primary care physicians (PCPs) from eight outpatient clinics submitted 215 electronic consults (eConsults) for 211 patients to a Stanford Health Care dermatologist via PhotoCareMD. Comparisons were made with in-person referrals for this same dermatologist prior to initiation of PhotoCareMD. Results Compared to traditional in-person dermatology clinic visits, eConsults decreased the time to diagnosis and treatment from 23 days to 16 hours. The majority (73%) of eConsults were resolved electronically. In-person referrals from PhotoCareMD (27%) had a 50% lower cancellation rate compared with traditional referrals (11% versus 22%). The average in-person visit and documentation was 25 minutes compared with 8 minutes for an eConsult. PhotoCareMD saved 13 additional clinic hours to be made available to the dermatologist over the course of the pilot. At four patients per hour, this opens 52 dermatology clinic slots. Over 96% of patients had a favourable experience and 95% felt this service saved them time. Among PCPs, 100% would recommend PhotoCareMD to their colleagues and 95% said PhotoCareMD was a helpful educational tool. Discussion An internal SAF teledermatology workflow can be effectively implemented to increase access to and quality of dermatologic care. Our workflow can serve as a successful model for other hospitals and specialties.

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