Cloud-based Electronic Health Records Research Articles

Secure Cloud-Based Electronic Health Records: Cross-Patient Block-Level Deduplication with Blockchain Auditing.

In today's data-driven world, the exponential growth of digital information poses significant challenges in data management. In recent years, the adoption of cloud-based Electronic Health Records (EHR) sharing schemes has yielded numerous advantages like improved accessibility, availability, and enhanced interoperability. However, the centralized nature of cloud storage presents challenges in terms of information storage, privacy protection, and security. Despite several approaches that have been presented to ensure secure deduplication of similar EHRs, the validation of data integrity without a third-party auditor (TPA) remains a persistent task. Because involving a TPA raises concerns about the confidentiality and privacy of crucial healthcare information. To tackle this challenge, a novel cloud storage auditing technique is proposed that incorporates cross-patient block-level deduplication while upholding strong privacy protection, ensuring that EHR is not compromised. Here, we introduced blockchain technology to achieve integrity verification, thus eliminating the need for a TPA by providing a decentralized and transparent mechanism. Additionally, an index for all EHRs has been generated to facilitate block-level duplicate checks and employ a novel strategy to prevent adversaries from acquiring original information saved in the cloud storage. The security of the proposed approach is established against factorization attacks and decrypt exponent attacks. The performance evaluation demonstrates the superior efficiency of the proposed scheme in terms of file authenticator generation, challenge creation, and proof verification to other existing client-side deduplication approaches.

Leveraging semantic context to establish access controls for secure cloud-based electronic health records

With the continuous growth of cloud-based Electronic Health Record (EHR) systems and medical data, medical organizations are particularly concerned about storing patient data to provide fast services while adhering to privacy and security concerns. Existing EHR systems often face challenges in handling heterogeneous data and maintaining good performance with data growth. These systems mostly use relational databases or partially store data in a knowledge graph, making it challenging to handle big data and allowing flexible schema expansion. Hence, there is a need to address these problems. This paper provides a solution by proposing a novel graph-based EHR system integrating Attribute-Based Encryption and Semantic Web Technologies to ensure fine-grained EHR field-level security of patient records. Our approach leverages semantic context to query through a knowledge graph that stores encrypted medical data in the nodes, making it possible to handle heterogeneous data while ensuring optimal performance and preserving patient privacy.

Securing Mobile Cloud-Based Electronic Health Records: A Blockchain-Powered Cryptographic Solution with Enhanced Privacy and Efficiency

Securing Mobile Cloud-Based Electronic Health Records: A Blockchain-Powered Cryptographic Solution with Enhanced Privacy and Efficiency

Benefits of Using a Free Cloud-Based Electronic Health Record for Simulation in a Baccalaureate Nursing Program.

The rising cost of simulated electronic health record (EHR) software for students in a baccalaureate nursing program was risking student success. The need for faculty to decrease this financial burden on students was apparent. Simulation faculty created a free and cloud-based simulated EHR. High-fidelity features of the simulated EHR include barcode scanning capabilities and real-time diagnostic results. Students report that the simulated EHR is easy to navigate and they are particularly satisfied with the free cost. The EHR template, which can be customized for each simulated patient, and is now being used inside the classroom as an active learning strategy.

BJWT-EHR: A novel JWT based Blockchain System for Electronic Health Records

Since most transactions in the world now take place digitally, it is crucial to maintain data integrity, share data securely, and provide quick access to it. Our reliance on computers in our daily lives is growing, and new data will inevitably be generated to meet this need. Providing for safe data exchange is becoming increasingly crucial every day. Maintaining and safeguarding the security of this data is crucial. Recently, the term "blockchain" has been used extensively for data security. A decentralized digital ledger called blockchain is in charge of preserving data integrity and facilitating safe data sharing. Blockchain transfers data by the principle of transparency, records data one way, and prevents reverse engineering. According to reports, blockchain is the general term for the technology that promotes common data sharing of these recorded data and reduces access times, essential for preserving data security. There are several risks to patients' privacy when information from medical records is stolen or altered. The damage caused by malicious people with this information causes serious harm to both the patient and the financing institution. Therefore, cloud-based EHR (electronic health records) is becoming a focal point in many areas. Storing patient data, ensuring data accuracy, protecting data confidentiality, and ensuring fast data transmission in the cloud system is a significant concerns in the healthcare industry. In this study, the layered architecture structure is also addressed in addition to the blockchain for sharing health data with the help of cloud service providers while providing data access control and auditing for EHR records. To enter this layered architectural system, new solutions are proposed by applying JWT (JSON web token) and hashing function of patient information. This proposed method manages and controls the patient's health records electronically. Therefore, these technologies used in the blockchain platform open new doors to more secure and sustainable solutions.

Blockchain-Enabled Fine-Grained Searchable Encryption With Cloud–Edge Computing for Electronic Health Records Sharing

The integration of Internet of Things (IoT) with cloud-edge computing in cyber-physical systems has revolutionized the way healthcare enterprises manage electronic health records (EHRs). With more healthcare enterprises outsourcing encrypted EHRs to the cloud, searchable encryption is utilized to retrieve encrypted data, especially attribute-based searchable encryption (ABSE) can achieve fine-grained access control. However, ABSE usually requires a lot of computation, which imposes a serious burden on resource-limited devices. Moreover, ensuring fairness in data access is crucial in the healthcare domain, where both data users and owners may have conflicting interests. In order to overcome these problems, this paper proposes a searchable encryption scheme with fine-grained access control for cloud-based EHRs sharing assisted by blockchain. It transfers computing tasks to edge servers and enables users to control who has access to their EHRs. The adoption of blockchain and smart contracts guarantees data integrity and transaction fairness. Moreover, a consensus algorithm is designed for the higher efficiency of the proposed scheme. Finally, security analysis proves the proposed scheme resists adaptive chosen keyword attacks (CKA). Performance analysis further confirms it has more functionalities and is efficient for smart healthcare.

Blockchain based secure medical data outsourcing with data deduplication in cloud environment

With the rapid growth of cloud computing, an increasing number of individuals and businesses are opting to store their vast data on the cloud in order to cut data maintenance costs and obtain more easy access. The cloud-based Electronic Health Records (EHR) sharing scheme has provided many benefits in recent years, but the centralization of the cloud raises challenges to privacy protection and data security. Blockchain technology is viewed as a possible solution to these challenges because of its unique properties of unforgeability, anonymity, and verifiability. Therefore, a blockchain based secure data outsourcing scheme is proposed in this paper. In the proposed scheme, each activity on outsourcing EHRs is recorded as a transaction on the public blockchain, authenticity is ensured by registration, and secure data access is ensured by keyword search. Initially, the EHR is encrypted by the proposed Enhanced Map Chaotic Encryption (EMCE) algorithm to ensure confidentiality. Then, data de-duplication is performed by the proposed Tri-Level Chunk Hashing (TL-CH) technique to eliminated duplicate records and reduce the storage space. Finally, the integrity of outsourced EHRs is validated by the Third-Party Auditor (TPA). The performance and security analysis show that the proposed scheme can provide solid security against various attacks, and the storage space is reduced.

Association of Serum Vitamin D level and COVID-19 infection: A Case-control Study.

Vitamin D is considered a potent modulator of the immune system, albeit its role in COVID-19 infection is a matter of debate. The present study aimed to estimate the association between serum vitamin D levels and COVID-19 among people in Qatar. This case-control study, approved by the Institutional Review Board of Primary Health Care Corporation (PHCC) Qatar, retrospectively evaluated the principal public healthcare sector population data repository retrieved from the cloud-based Electronic Health Record (EHR) software-Cerner, during April 2020-2021. The health records of all adult patients aged >18 years who had undergone the reverse transcription-polymerase chain reaction (RT-PCR) test and whose medical records had documented serum 25-hydroxyvitamin D [25 (OH)D] levels were analyzed. A total of 924,173 EHRs were extracted, of which 62,451 EHR comprised of 16,446 (26.3%) COVID-19 patients and 46,005 (73.7%) negative-control group patients met the inclusion criteria. The odds ratio (OR) among different categories of vitamin D deficiency (VDD) revealed that people with mild/moderate VDD were 1.18 times (95% CI 1.126-1.258) and those with severe VDD were 1.90 times (95% CI 1.116-1.251) more likely to have COVID-19 infection when compared to the people with optimal serum vitamin D level. On applying multiple logistic regression, the odds of having COVID-19 infection were found to be 1.27 times (95% CI 1.184-1.371) higher among those with mild/moderate VDD and 1.32 times (95% CI 1.206-1.405) higher among those with severe VDD when compared to people with optimal vitamin D level (p<0.001). Our findings demonstrated a significant association between the suboptimal serum vitamin D level and COVID-19 infection. Further studies are required to determine the effects of VDD on the severity and outcomes of COVID-19 infections.

Emergence of Healthcare 4.0 and Blockchain into Secure Cloud-based Electronic Health Records Systems: Solutions, Challenges, and Future Roadmap

Emergence of Healthcare 4.0 and Blockchain into Secure Cloud-based Electronic Health Records Systems: Solutions, Challenges, and Future Roadmap

Cloud architecture for electronic health record systems interoperability

BACKGROUND: Current Electronic Health Record (EHR) systems are built using different data representation and information models, which makes difficult achieving information exchange. OBJECTIVE: Our aim was to propose a scalable architecture that allows the integration of information from different EHR systems. METHODS: A cloud-based EHR interoperable architecture is proposed through the standardization and integration of patient electronic health records. The data is stored in a cloud repository with high availability features. Stakeholders can retrieve the patient EHR by requesting only to the integrated data repository. The OpenEHR two-level approach is applied according to the HL7-FHIR standards. We validated our architecture by comparing it with 5 different works (CHISTAR, ARIEN, DIRAYA, LLPHR and INEHRIS) using a set of selected axes and a scoring method. RESULTS: The problem was reduced to a single point of communication between each EHR system and the integrated data repository. By combining cloud computing paradigm with selected health informatics standards, we obtained a generic and scalable architecture that complies 100% with interoperability requisites according to the evaluation framework applied. CONCLUSIONS: The architecture allowed the integration of several EHR systems, adapting them with the use of standards and ensuring the availability thanks to cloud computing features.

Privacy Preservation and Access Control for Sharing Electronic Health Records Using Blockchain Technology

Sharing of Electronic Health Records (EHRs) is of significant importance in health care. Lately, a cloud-based electronic health record sharing scheme has been used extensively to share patient records among various healthcare organizations. However, cloud centralization may compromise patients&#8217; privacy and security. Due to the special features of blockchain, it is important to see this technology as a promising solution to resolve these issues. This article proposes a privacy-preserving, secure EHR sharing and access control framework based on blockchain technology. The proposal aims to implement EHR blockchain technology and ensure that electronic records are stored safely by specifying user access permissions. We emulate the cryptographic primitives and use smart contracts to describe the relationships between the EHR owner and EHR user through the proposed system on the Ethereum blockchain. We assess the proposal results based on encryption and decryption time and the costs of the smart contract. The encryption and decryption times are proportional to the size of the EHR, which varies from 128 KB to 128 MB. When it comes to encryption, the smallest EHR takes 0.0012 s to encrypt, while the largest EHR, which is 128 MB, takes 1.4149 s. On the other hand, a 128 KB EHR takes 0.0013 s to decrypt, whereas a 128 MB EHR requires 1.6284 s. As a result, performance evaluation and security analysis confirm that the proposal is secure for practical application.

Cloud-based electronic health record sharing and access controlling blockchain architecture using data de-identification method

Cloud-based electronic health record sharing and access controlling blockchain architecture using data de-identification method

A New Approach for Secure Cloud-Based Electronic Health Record and its Experimental Testbed

The tremendous development of the Internet of Things (IoT) technology in the last decades has fostered advancement in automatic medical assistive devices to support the existing Electronic Health Record (EHR) system. As an integral part of the EHR electronic model, public cloud servers store medical data. Unfortunately, public cloud servers are prone to security and privacy breach. This paper introduces a novel non-cryptographic approach to preserve electrocardiograph (ECG) data confidentiality and integrity in the EHR environment. The main objective of the proposed anonymization algorithm is to obscure the patient’s cardiac information during transmission and to protect information stored in the cloud database. Although we focus on ECG data, generalization to other types of clinical data can be derived using the proposed method. Performance evaluation of the proposed scheme showed that the algorithm conceals both fiducial and non-fiducial features of the data. Therefore, confidentiality feature is preserved. This paper examined confidentiality of the anonymized data using the Percentage Residual Difference (PRD) and investigated the integrity of the reconstructed data in terms of cross-correlation. Security analysis carried out using the PRD, brute force attack, and performance comparison between the proposed algorithm and existing methods. Evaluation showed that the proposed scheme offers a secure non-cryptographic model for transmission and storing clinical data in the cloud. Moreover, in terms of processing time, the proposed algorithm is ten times faster than the existing wavelet packet method when processing long ECG data, 65,536 sample points. In a real-time experimental testbed, the implemented proposed system was successful.

Delegated Authorization Framework for EHR Services Using Attribute-Based Encryption

Medical organizations find it challenging to adopt cloud-based Electronic Health Records (EHR) services due to the risk of data breaches and the resulting compromise of patient data. Existing authorization models follow a patient-centric approach for EHR management, where the responsibility of authorizing data access is handled at the patients end. This creates a significant overhead for the patient who must authorize every access of their health record. This is not practical given that multiple personnel are typically involved in providing care and that the patient may not always be in a state to provide this authorization. Hence there is a need to develop a proper authorization delegation mechanism for safe, secure and easy to use cloud-based EHR Service management. We present a novel, centralized, attribute-based authorization mechanism that uses Attribute Based Encryption (ABE) and allows for delegated secure access of patient records. This mechanism transfers the service management overhead from the patient to the medical organization and allows easy delegation of cloud-based EHRs access authority to medical providers.

Integrated Care: A PTSD diagnostic mechanism for a refugee reception centre

IntroductionWithin the 65 million displaced people, many are dealing with post-traumatic stress disorder (PTSD). According to the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV), PTSD derives from witnessing of violence and crime. Among the symptoms are avoidance of trauma-related stimuli, negative thoughts and alterations in arousal and reactivity. PTSD seriously affects functionality and transition to the new society and therefore, thorough screening is highly recommended. Assessment solely through a PTSD-related questionnaire cannot be satisfactory to reveal the difficulties faced and the intervention needed. A possible way to provide a holistic approach in dealing with PTSD, is to conduct a battery of tests in combination with simple technological aids.Theory/Methods Assessment and treatment of PTSD requires the coordination of a multi-disciplinary group that is usually lacking in refugee reception centres. The suggested set of assessments does not require application by a clinician and may serve as a solid base upon which to build the treatment plan. The aim is to explore whether the use of a battery of tests along with a smart band and a Galvanic Skin Response (GSR) sensor will provide more accurate diagnostic results, allowing a thorough assessment of the mental, functional and occupational state for refugees living in reception centers and thus, multi-disciplinary intervention planning. The Davidson Trauma Scale (DTS), the Stressful Life Events Screening Questionnaire and the Canadian Occupational Performance Measure (COPM) will be applied to adult refugees residing at Kofinou Reception Center in Cyprus. Occupational therapy students supervised by a professional will apply the tests to approximately 100 participants. This will be a within-subjects design, meant to empower the diagnostic phase of intervention. In Stage A: Participants will be wearing a wrist band for one week to record the number of steps, hours of sleep (deep / light) and heart rate. In Stage B: A Questionnaire application will be conducted, while participants will be wearing a GSR sensor to determine their relative stress levels. Results will be uploaded on a cloud-based Electronic Health Record (HER) to be further processed by a multidisciplinary group.Results / DiscussionsTreatment for PTSD involves psychotherapy, medication and occupational therapy, each of which requires a thorough assessment beforehand to design a client-centered intervention strategy. Treatment may focus on dealing with negative thoughts, learning ways to cope with symptoms, minimizing depression, anxiety, or misuse of alcohol or drugs and engaging in meaningful occupations.ConclusionsCombining a battery of tests along with introducing smart wearable technologies will provide a thorough assessment and further intervention for refugees living in reception centers. This is a critical process given the vast number of refugees arriving on a daily basis in Cyprus and Greece .Suggestions for future research Application of the assessment battery by non-clinicians may be one of the next steps. Furthermore, Machine Learning / Artificial Intelligence techniques may be used to process results stored on the cloud in order to provide early stage indications of PTSD.

25649 Comorbidities among children with hidradenitis suppurativa

Comorbidities among adults with hidradenitis suppurativa (HS) have been extensively explored, but there are limited data regarding comorbidities among children with HS. The objective of this study was to determine the prevalence of comorbidities among pediatric patients with HS using an aggregated, deidentified patient database. Pediatric patients (<18 years old) with HS were identified in Explorys, a cloud-based electronic health record database composed of over 360 hospitals. Pediatric patients between 5 and <18 years old were used as controls, as all children with HS were ≥5 years old.

Digitized Maternal Early Warning and Response Telehealth System

Introduction: In this article, we describe a pilot telehealth project for identifying women at risk of developing serious complications early and for instituting timely, appropriate, and up-to-date management even in situations with limited resources and skilled obstetric services. Maternal mortality remains unacceptably high, with less than two-thirds of the signatories to the 2015 Millennium Development Goals achieving the outlined 75% reduction in maternal mortality ratio (MMR) from 1990 to 2015. Looking forward to 2030, the Sustainable Development Goals (SDGs) lay out a target of reducing the MMR in every country to below 70 per 100,000 live births. This will require progress in low-and-middle-income countries at a rate much greater than that seen over the past 15 years. Given that 94% of the global maternal deaths occur in low- and-middle-income countries, a solution to meet the unique challenges of these countries will be necessary to achieve the SDG. The Women’s Obstetrical Neonatal Death and Reduction (WONDER) telehealth system described here offers a potential telehealth solution to reduce mortality and morbidity rates in resource-limited environments by early identification of risk indicators and initiation of care. Materials and methods: The WONDER system consists of a cloud-based electronic health record with a Clinical Decision Support tool and a color-coded alert system. The Clinical Decision Support tool is based upon Maternal Early Warning Signs and provides real-time assistance to caregivers via relevant national treatment guidelines. This system uses inexpensive computing hardware, displays, and cell-phone technology. This system was tested in a 2-year pilot study in India. A total of 15,184 patients were monitored during labor and the postpartum period. Results: Within limitations of the study, the incidence of in-hospital eclampsia was reduced by 91.7%, and in 95% of cases, timely treatment was started within an hour of identifying the abnormality in vital signs. Maternal mortality was reduced by 50.1% over local benchmark figures. Conclusions: The WONDER system identified at-risk patients, directed skilled care to those patients at risk for complications, and helped to institute effective, timely treatment, demonstrating a potential solution for women in resource-limited locations.

Applying Blockchain Technology to Security-Related Aspects of Electronic Healthcare Record Infrastructure

The centralised architecture employed by electronic health records (EHRs) may constitute a single point of failure. From the perspective of availability, an alternative cloud-based EHR infrastructure is effective and efficient. However, this increased availability has created challenges related to the security and privacy of patients’ medical records. The sensitive nature of EHRs attracts the attention of cyber-criminals. There has been a rise in the number of data breaches related to EHRs. The infrastructure used by EHRs does not assure the privacy and security of patients’ medical records. Features of blockchain platforms, such as decentralisation, immutability, auditability, and transparency, may provide a viable means of augmenting or improving services related to the security of EHRs. This study presents a series of experimental data flow configurations to test the application of blockchain technology to aspects of EHRs. The insights gained from these experiments are founded on a theoretical base to provide recommendations for applying blockchain technology to services related to the security of EHR infrastructure. These recommendations may be employed by developers when redesigning existing EHR systems or deploying new EHR systems.

Sijilli: A Scalable Model of Cloud-Based Electronic Health Records for Migrating Populations in Low-Resource Settings.

The world is witnessing an alarming rate of displacement and migration, with more than 70.8 million forcibly displaced individuals, including 26 million refugees. These populations are known to have increased vulnerability and susceptibility to mental and physical health problems due to the migration journey. Access of these individuals to health services, whether during their trajectory of displacement or in refugee-hosting countries, remains limited and challenging due to multiple factors, including language and cultural barriers and unavailability of the refugees’ health records. Cloud-based electronic health records (EHRs) are considered among the top five health technologies integrated in humanitarian crisis preparedness and response during times of conflict. This viewpoint describes the design and implementation of a scalable and innovative cloud-based EHR named Sijilli, which targets refugees in low-resource settings. This paper discusses this solution compared with other similar practices, shedding light on its potential for scalability.

Abstract A63: Overcoming challenges in health care with machine learning: Innovation from retinoblastoma

Abstract Introduction: As retinoblastoma is a rare pediatric cancer (1/17,000 live births) with little evidence to justify treatment choices, we built a cloud-based retinoblastoma-specific electronic health record database for point-of-care data to support clinical and research collaboration and provide a quantitative analysis of prescribed treatments. Methods: Disease-specific Electronic Patient Illustrated Clinical Timeline (DEPICT HEALTH) is online, cloud-based, interactive, with point-of-care timelines and corresponding retinal/tumor drawings, with standardized scoring of tumor number, size, and locations. Results: DEPICT HEALTH records are contributed by the entire care team and used in quantitative treatment analyses. DEPICT HEALTH effectively communicates disease and treatment information to the patients’ circle of care and their parents, independent of language. The Retinoblastoma Activity Index (RAI) quantifies the active tumor (colored yellow) by counting the yellow pixels in the DEPICT HEALTH digital drawings. The drawings represent tumor at every encounter based on the collective opinion of the care team, and the RAI will quantitate tumor response to treatment. Two clinical trials were initiated using DEPICT HEALTH and RAI for eligibility and short- and long-term outcomes. Conclusion: Using RAI to score tumor response provides RECIST (response evaluation criteria in solid tumors) for retinoblastoma research, a standard of measurement that has never before been available. Machine learning methods will ultimately analyze point-of-care data to predict patient outcomes and assist with clinical decision making. DEPICT HEALTH provides an unbiased view of the efficacy of treatments, with potential to allow global point-of-care data to be widely available for research, essentially an “n” of “ALL.” Citation Format: Isabella Janusonis, Tran Truong, Justin Liu, Mei Chen, Brenda Gallie. Overcoming challenges in health care with machine learning: Innovation from retinoblastoma [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr A63.