Displaying publications 1 - 20 of 60 in total

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  1. Kiah ML, Nabi MS, Zaidan BB, Zaidan AA
    J Med Syst, 2013 Oct;37(5):9971.
    PMID: 24037086 DOI: 10.1007/s10916-013-9971-2
    This study aims to provide security solutions for implementing electronic medical records (EMRs). E-Health organizations could utilize the proposed method and implement recommended solutions in medical/health systems. Majority of the required security features of EMRs were noted. The methods used were tested against each of these security features. In implementing the system, the combination that satisfied all of the security features of EMRs was selected. Secure implementation and management of EMRs facilitate the safeguarding of the confidentiality, integrity, and availability of e-health organization systems. Health practitioners, patients, and visitors can use the information system facilities safely and with confidence anytime and anywhere. After critically reviewing security and data transmission methods, a new hybrid method was proposed to be implemented on EMR systems. This method will enhance the robustness, security, and integration of EMR systems. The hybrid of simple object access protocol/extensible markup language (XML) with advanced encryption standard and secure hash algorithm version 1 has achieved the security requirements of an EMR system with the capability of integrating with other systems through the design of XML messages.
    Matched MeSH terms: Electronic Health Records*
  2. Alhammad A, Yusof MM, Jambari DI
    Expert Rev Med Devices, 2024 Mar;21(3):217-229.
    PMID: 38318674 DOI: 10.1080/17434440.2024.2315024
    INTRODUCTION: Medical device (MD)-integrated (I) electronic medical record (EMR) (MDI-EMR) poses cyber threats that undermine patient safety, and thus, they require effective control mechanisms. We reviewed the related literature, including existing EMR and MD risk assessment approaches, to identify MDI-EMR comprehensive evaluation dimensions and measures.

    AREAS COVERED: We searched multiple databases, including PubMed, Web of Knowledge, Scopus, ACM, Embase, IEEE and Ingenta. We explored various evaluation aspects of MD and EMR to gain a better understanding of their complex integration. We reviewed numerous risk management and assessment frameworks related to MD and EMR security aspects and mitigation controls and then identified their common evaluation aspects. Our review indicated that previous evaluation frameworks assessed MD and EMR independently. To address this gap, we proposed an evaluation framework based on the sociotechnical dimensions of health information systems and risk assessment approaches for MDs to evaluate MDI-EMR integratively.

    EXPERT OPINION: The emergence of MDI-EMR cyber threats requires appropriate evaluation tools to ensure the safe development and application of MDI-EMR. Consequently, our proposed framework will continue to evolve through subsequent validations and refinements. This process aims to establish its applicability in informing stakeholders of the safety level and assessing its effectiveness in mitigating risks for future improvements.

    Matched MeSH terms: Electronic Health Records*
  3. El-Hassan O, Sharif A, Al Redha M, Blair I
    PMID: 29295053
    In the United Arab Emirates (UAE), health services have developed greatly in the past 40 years. To ensure they continue to meet the needs of the population, innovation and change are required including investment in a strong e-Health infrastructure with a single transferrable electronic patient record. In this paper, using the Emirate of Dubai as a case study, we report on the Middle East Electronic Medical Record Adoption Model (EMRAM). Between 2011-2016, the number of participating hospitals has increased from 23 to 33. Currently, while 20/33 of hospitals are at Stage 2 or less, 10/33 have reached Stage 5. Also Dubai's median EMRAM score in 2016 (2.5) was higher than the scores reported from Australia (2.2), New Zealand (2.3), Malaysia (0.06), the Philippines (0.06) and Thailand (0.5). EMRAM has allowed the tracking of the progress being made by healthcare facilities in Dubai towards upgrading their information technology infrastructure and the introduction of electronic medical records.
    Matched MeSH terms: Electronic Health Records*
  4. Ibrahim AA, Ahmad Zamzuri M'I, Ismail R, Ariffin AH, Ismail A, Muhamad Hasani MH, et al.
    Medicine (Baltimore), 2022 Jul 29;101(30):e29627.
    PMID: 35905245 DOI: 10.1097/MD.0000000000029627
    The Teleprimary Care-Oral Health Clinical Information System (TPC-OHCIS) is an updated electronic medical record (EMR) that has been applied in Malaysian primary healthcare. Recognizing the level of patient satisfaction following EMR implementation is crucial for assessing the performance of health care services. Hence, the main objective of this study was to compare the level of patient satisfaction between EMR-based clinics and paper-based clinics. The study was a quasi-experimental design that used a control group and was conducted among patients in 14 public primary healthcare facilities in the Seremban district of Malaysia from May 10, to June 30, 2021. Patient satisfaction was assessed using the validated Short-Form Patient Satisfaction Questionnaire, which consisted of 7 subscales. All data were analyzed using the IBM Statistical Package for Social Sciences version 21. A total of 321 patients consented to participate in this study, and 48.9% of them were from EMR clinics. The mean score for the communication subscale was the highest at 4.08 and 3.96 at EMR-adopted clinics and paper-based record clinics. There were significant differences in general satisfaction and communication subscales, with higher patient satisfaction found in clinics using EMR. With the utilization of EMR, patient satisfaction and communication in delivering healthcare services have improved.
    Matched MeSH terms: Electronic Health Records*
  5. Alsyouf A, Ishak AK, Lutfi A, Alhazmi FN, Al-Okaily M
    Int J Environ Res Public Health, 2022 Sep 05;19(17).
    PMID: 36078837 DOI: 10.3390/ijerph191711125
    This study examines nurses' Continuance Intention (CI) to use electronic health records (EHRs) through a combination of three conceptual frameworks: the Unified Theory of Acceptance and Use of Technology (UTAUT), the theory of expectation-confirmation (ECT), and the Five-Factor Model (FFM). A model is developed to examine and predict the determinants of nurses' CI to use EHRs, including top management support (TMS) and the FFM's five personality domains. Data were collected from a survey of 497 nurses, which were analyzed using partial least squares. No significant relationship was found between TMS and CI. The study revealed that performance expectancy significantly mediated the influences of two different hypotheses of two predictors: agreeableness and openness to testing CI. A significant moderating impact of conscientiousness was found on the relationship between performance expectancy and CI and the relationship between social influence and CI. The findings of this study indicated that rigorous attention to the personality of individual nurses and substantial TMS could improve nurses' CI to use EHRs. A literature gap was filled concerning the mediating effects of performance expectancy on the FFM-CI relationship, and the moderation effects of Conscientiousness on UTAUT constructs and CI are another addition to the literature. The results are expected to assist government agencies, health policymakers, and health institutions all over the globe in their attempts to understand the post-adoption use of EHRs.
    Matched MeSH terms: Electronic Health Records*
  6. Mohd Sulaiman I, Bulgiba A, Abdul Kareem S
    Eval Health Prof, 2023 Mar;46(1):41-47.
    PMID: 36444613 DOI: 10.1177/01632787221142623
    Medical abbreviations can be misinterpreted and endanger patients' lives. This research is the first to investigate the prevalence of abbreviations in Malaysian electronic discharge summaries, where English is widely used, and elicit the risk factors associated with dangerous abbreviations. We randomly sampled and manually annotated 1102 electronic discharge summaries for abbreviations and their senses. Three medical doctors assigned a danger level to ambiguous abbreviations based on their potential to cause patient harm if misinterpreted. The predictors for dangerous abbreviations were determined using binary logistic regression. Abbreviations accounted for 19% (33,824) of total words; 22.6% (7640) of those abbreviations were ambiguous; and 52.3% (115) of the ambiguous abbreviations were labelled dangerous. Increased risk of danger occurs when abbreviations have more than two senses (OR = 2.991; 95% CI 1.586, 5.641), they are medication-related (OR = 6.240; 95% CI 2.674, 14.558), they are disorders (OR = 7.771; 95% CI 2.054, 29.409) and procedures (OR = 3.492; 95% CI 1.376, 8.860). Reduced risk of danger occurs when abbreviations are confined to a single discipline (OR = 0.519; 95% CI 0.278, 0.967). Managing abbreviations through awareness and implementing automated abbreviation detection and expansion would improve the quality of clinical documentation, patient safety, and the information extracted for secondary purposes.
    Matched MeSH terms: Electronic Health Records*
  7. Salleh MIM, Abdullah R, Zakaria N
    BMC Med Inform Decis Mak, 2021 02 25;21(1):75.
    PMID: 33632216 DOI: 10.1186/s12911-021-01447-4
    BACKGROUND: The Ministry of Health of Malaysia has invested significant resources to implement an electronic health record (EHR) system to ensure the full automation of hospitals for coordinated care delivery. Thus, evaluating whether the system has been effectively utilized is necessary, particularly regarding how it predicts the post-implementation primary care providers' performance impact.

    METHODS: Convenience sampling was employed for data collection in three government hospitals for 7 months. A standardized effectiveness survey for EHR systems was administered to primary health care providers (specialists, medical officers, and nurses) as they participated in medical education programs. Empirical data were assessed by employing partial least squares-structural equation modeling for hypothesis testing.

    RESULTS: The results demonstrated that knowledge quality had the highest score for predicting performance and had a large effect size, whereas system compatibility was the most substantial system quality component. The findings indicated that EHR systems supported the clinical tasks and workflows of care providers, which increased system quality, whereas the increased quality of knowledge improved user performance.

    CONCLUSION: Given these findings, knowledge quality and effective use should be incorporated into evaluating EHR system effectiveness in health institutions. Data mining features can be integrated into current systems for efficiently and systematically generating health populations and disease trend analysis, improving clinical knowledge of care providers, and increasing their productivity. The validated survey instrument can be further tested with empirical surveys in other public and private hospitals with different interoperable EHR systems.

    Matched MeSH terms: Electronic Health Records*
  8. Syed-Mohamad SM, Ali SH, Mat-Husin MN
    Health Inf Manag, 2010;39(1):30-5.
    PMID: 20335647
    This paper describes the method used to develop the One Stop Crisis Centre (OSCC) Portal, an open source web-based electronic patient record system (EPR) for the One Stop Crisis Center, Hospital Universiti Sains Malaysia (HUSM) in Kelantan, Malaysia. Features and functionalities of the system are presented to demonstrate the workflow. Use of the OSCC Portal improved data integration and data communication and contributed to improvements in care management. With implementation of the OSCC portal, improved coordination between disciplines and standardisation of data in HUSM were noticed. It is expected that this will in turn result in improved data confidentiality and data integrity. The collected data will also be useful for quality assessment and research. Other low-resource centers with limited computer hardware and access to open-source software could benefit from this endeavour.
    Matched MeSH terms: Electronic Health Records*
  9. Ali A, Ali H, Saeed A, Ahmed Khan A, Tin TT, Assam M, et al.
    Sensors (Basel), 2023 Sep 07;23(18).
    PMID: 37765797 DOI: 10.3390/s23187740
    The rapid advancements in technology have paved the way for innovative solutions in the healthcare domain, aiming to improve scalability and security while enhancing patient care. This abstract introduces a cutting-edge approach, leveraging blockchain technology and hybrid deep learning techniques to revolutionize healthcare systems. Blockchain technology provides a decentralized and transparent framework, enabling secure data storage, sharing, and access control. By integrating blockchain into healthcare systems, data integrity, privacy, and interoperability can be ensured while eliminating the reliance on centralized authorities. In conjunction with blockchain, hybrid deep learning techniques offer powerful capabilities for data analysis and decision making in healthcare. Combining the strengths of deep learning algorithms with traditional machine learning approaches, hybrid deep learning enables accurate and efficient processing of complex healthcare data, including medical records, images, and sensor data. This research proposes a permissions-based blockchain framework for scalable and secure healthcare systems, integrating hybrid deep learning models. The framework ensures that only authorized entities can access and modify sensitive health information, preserving patient privacy while facilitating seamless data sharing and collaboration among healthcare providers. Additionally, the hybrid deep learning models enable real-time analysis of large-scale healthcare data, facilitating timely diagnosis, treatment recommendations, and disease prediction. The integration of blockchain and hybrid deep learning presents numerous benefits, including enhanced scalability, improved security, interoperability, and informed decision making in healthcare systems. However, challenges such as computational complexity, regulatory compliance, and ethical considerations need to be addressed for successful implementation. By harnessing the potential of blockchain and hybrid deep learning, healthcare systems can overcome traditional limitations, promoting efficient and secure data management, personalized patient care, and advancements in medical research. The proposed framework lays the foundation for a future healthcare ecosystem that prioritizes scalability, security, and improved patient outcomes.
    Matched MeSH terms: Electronic Health Records
  10. Zaidan AA, Zaidan BB, Al-Haiqi A, Kiah ML, Hussain M, Abdulnabi M
    J Biomed Inform, 2015 Feb;53:390-404.
    PMID: 25483886 DOI: 10.1016/j.jbi.2014.11.012
    Evaluating and selecting software packages that meet the requirements of an organization are difficult aspects of software engineering process. Selecting the wrong open-source EMR software package can be costly and may adversely affect business processes and functioning of the organization. This study aims to evaluate and select open-source EMR software packages based on multi-criteria decision-making. A hands-on study was performed and a set of open-source EMR software packages were implemented locally on separate virtual machines to examine the systems more closely. Several measures as evaluation basis were specified, and the systems were selected based a set of metric outcomes using Integrated Analytic Hierarchy Process (AHP) and TOPSIS. The experimental results showed that GNUmed and OpenEMR software can provide better basis on ranking score records than other open-source EMR software packages.
    Matched MeSH terms: Electronic Health Records*
  11. Alanazi HO, Zaidan AA, Zaidan BB, Kiah ML, Al-Bakri SH
    J Med Syst, 2015 Jan;39(1):165.
    PMID: 25481568 DOI: 10.1007/s10916-014-0165-3
    This study has two objectives. First, it aims to develop a system with a highly secured approach to transmitting electronic medical records (EMRs), and second, it aims to identify entities that transmit private patient information without permission. The NTRU and the Advanced Encryption Standard (AES) cryptosystems are secured encryption methods. The AES is a tested technology that has already been utilized in several systems to secure sensitive data. The United States government has been using AES since June 2003 to protect sensitive and essential information. Meanwhile, NTRU protects sensitive data against attacks through the use of quantum computers, which can break the RSA cryptosystem and elliptic curve cryptography algorithms. A hybrid of AES and NTRU is developed in this work to improve EMR security. The proposed hybrid cryptography technique is implemented to secure the data transmission process of EMRs. The proposed security solution can provide protection for over 40 years and is resistant to quantum computers. Moreover, the technique provides the necessary evidence required by law to identify disclosure or misuse of patient records. The proposed solution can effectively secure EMR transmission and protect patient rights. It also identifies the source responsible for disclosing confidential patient records. The proposed hybrid technique for securing data managed by institutional websites must be improved in the future.
    Matched MeSH terms: Electronic Health Records/organization & administration*
  12. Kiah ML, Haiqi A, Zaidan BB, Zaidan AA
    Comput Methods Programs Biomed, 2014 Nov;117(2):360-82.
    PMID: 25070757 DOI: 10.1016/j.cmpb.2014.07.002
    The use of open source software in health informatics is increasingly advocated by authors in the literature. Although there is no clear evidence of the superiority of the current open source applications in the healthcare field, the number of available open source applications online is growing and they are gaining greater prominence. This repertoire of open source options is of a great value for any future-planner interested in adopting an electronic medical/health record system, whether selecting an existent application or building a new one. The following questions arise. How do the available open source options compare to each other with respect to functionality, usability and security? Can an implementer of an open source application find sufficient support both as a user and as a developer, and to what extent? Does the available literature provide adequate answers to such questions? This review attempts to shed some light on these aspects.
    Matched MeSH terms: Electronic Health Records/organization & administration*
  13. Yau WC, Phan RC
    J Med Syst, 2013 Dec;37(6):9993.
    PMID: 24194093 DOI: 10.1007/s10916-013-9993-9
    Many authentication schemes have been proposed for telecare medicine information systems (TMIS) to ensure the privacy, integrity, and availability of patient records. These schemes are crucial for TMIS systems because otherwise patients' medical records become susceptible to tampering thus hampering diagnosis or private medical conditions of patients could be disclosed to parties who do not have a right to access such information. Very recently, Hao et al. proposed a chaotic map-based authentication scheme for telecare medicine information systems in a recent issue of Journal of Medical Systems. They claimed that the authentication scheme can withstand various attacks and it is secure to be used in TMIS. In this paper, we show that this authentication scheme is vulnerable to key-compromise impersonation attacks, off-line password guessing attacks upon compromising of a smart card, and parallel session attacks. We also exploit weaknesses in the password change phase of the scheme to mount a denial-of-service attack. Our results show that this scheme cannot be used to provide security in a telecare medicine information system.
    Matched MeSH terms: Electronic Health Records/standards
  14. Hussien HM, Yasin SM, Udzir SNI, Zaidan AA, Zaidan BB
    J Med Syst, 2019 Sep 14;43(10):320.
    PMID: 31522262 DOI: 10.1007/s10916-019-1445-8
    Blockchain in healthcare applications requires robust security and privacy mechanism for high-level authentication, interoperability and medical records sharing to comply with the strict legal requirements of the Health Insurance Portability and Accountability Act of 1996. Blockchain technology in the healthcare industry has received considerable research attention in recent years. This study conducts a review to substantially analyse and map the research landscape of current technologies, mainly the use of blockchain in healthcare applications, into a coherent taxonomy. The present study systematically searches all relevant research articles on blockchain in healthcare applications in three accessible databases, namely, ScienceDirect, IEEE and Web of Science, by using the defined keywords 'blockchain', 'healthcare' and 'electronic health records' and their variations. The final set of collected articles related to the use of blockchain in healthcare application is divided into three categories. The first category includes articles (i.e. 43/58 scientific articles) that attempted to develop and design healthcare applications integrating blockchain, particularly those on new architecture, system designs, framework, scheme, model, platform, approach, protocol and algorithm. The second category includes studies (i.e., 6/58 scientific articles) that attempted to evaluate and analyse the adoption of blockchain in the healthcare system. Finally, the third category comprises review and survey articles (i.e., 6/58 scientific articles) related to the integration of blockchain into healthcare applications. The final articles for review are discussed on the basis of five aspects: (1) year of publication, (2) nationality of authors, (3) publishing house or journal, (4) purpose of using blockchain in health applications and the corresponding contributions and (5) problem types and proposed solutions. Additionally, this study provides identified motivations, open challenges and recommendations on the use of blockchain in healthcare applications. The current research contributes to the literature by providing a detailed review of feasible alternatives and identifying the research gaps. Accordingly, researchers and developers are provided with appealing opportunities to further develop decentralised healthcare applications through a comprehensive discussion of about the importance of blockchain and its integration into various healthcare applications.
    Matched MeSH terms: Electronic Health Records/standards
  15. Jayabalan M, O'Daniel T
    J Med Syst, 2016 Dec;40(12):261.
    PMID: 27722981
    This study presents a systematic literature review of access control for electronic health record systems to protect patient's privacy. Articles from 2006 to 2016 were extracted from the ACM Digital Library, IEEE Xplore Digital Library, Science Direct, MEDLINE, and MetaPress using broad eligibility criteria, and chosen for inclusion based on analysis of ISO22600. Cryptographic standards and methods were left outside the scope of this review. Three broad classes of models are being actively investigated and developed: access control for electronic health records, access control for interoperability, and access control for risk analysis. Traditional role-based access control models are extended with spatial, temporal, probabilistic, dynamic, and semantic aspects to capture contextual information and provide granular access control. Maintenance of audit trails and facilities for overriding normal roles to allow full access in emergency cases are common features. Access privilege frameworks utilizing ontology-based knowledge representation for defining the rules have attracted considerable interest, due to the higher level of abstraction that makes it possible to model domain knowledge and validate access requests efficiently.
    Matched MeSH terms: Electronic Health Records/organization & administration*
  16. Choon SE, Wright AK, Griffiths CEM, Tey KE, Wong KW, Lee YW, et al.
    Br J Dermatol, 2022 Nov;187(5):713-721.
    PMID: 35830199 DOI: 10.1111/bjd.21768
    BACKGROUND: There are no population-based epidemiological data on psoriasis in Southeast Asia, including Malaysia.

    OBJECTIVES: To determine the incidence and prevalence of psoriasis over 11 years in multiethnic Johor Bahru, Malaysia.

    METHODS: A population-based cohort study was made using the Teleprimary Care database between January 2010 and December 2020. Cases of psoriasis, identified by ICD-10 diagnostic codes, were validated by dermatologists. Annual prevalence and incidence were estimated and stratified by age, sex and ethnicity.

    RESULTS: We identified 3932 people with dermatologist-confirmed psoriasis, including 1830 incident cases, among 1 164 724 Malaysians, yielding an 11-year prevalence of 0·34% [95% confidence interval (CI) 0·33-0·35] and incidence of 34·2 per 100 000 person-years (95% CI 32·6-35·8). Rates were higher in Indian patients; the prevalences were 0·54% (0·50-0·58) in Indian, 0·38% (0·36-0·40) in Chinese and 0·29% (0·28-0·30) in Malay patients, and the respective incidences per 100 000 person-years were 52·5 (47·3-57·7), 38·0 (34·1-41·8) and 30·0 (28·2-31·8). Rates were higher in males; the prevalence was 0·39% (0·37-0·41) in males and 0·29% (0·27-0·30) in females, and the respective incidences per 100 000 person-years were 40·7 (38·2-43·2) and 28·3 (26·4-30·3). Between 2010 and 2020, annual psoriasis prevalence and incidence increased steadily from 0·27% to 0·51% and from 27·8 to 60·9 per 100 000 person-years, respectively. Annual rates were consistently higher in male and Indian patients. Overall, psoriasis was significantly more common in males than females [odds ratio (OR) 1·37, 95% CI 1·29-1·46] and in Indian and Chinese patients vs. Malay (OR 1·85, 1·71-2·01 and OR 1·30, 1·20-1·41, respectively). Prevalence increased with age, with the highest rates in the groups aged 50-59 and 60-69 years at 0·67% and 0·66%, respectively. A modest bimodal trend in age of psoriasis onset was observed, with first and second peaks at 20-29 and 50-59 years. Disease onset was significantly earlier in females than males [mean (SD) 36·8 (17·3) vs. 42·0 (17·2) years, P 

    Matched MeSH terms: Electronic Health Records*
  17. Esther Omolara A, Jantan A, Abiodun OI, Arshad H, Dada KV, Emmanuel E
    Health Informatics J, 2020 09;26(3):2083-2104.
    PMID: 31957538 DOI: 10.1177/1460458219894479
    Advancements in electronic health record system allow patients to store and selectively share their medical records as needed with doctors. However, privacy concerns represent one of the major threats facing the electronic health record system. For instance, a cybercriminal may use a brute-force attack to authenticate into a patient's account to steal the patient's personal, medical or genetic details. This threat is amplified given that an individual's genetic content is connected to their family, thus leading to security risks for their family members as well. Several cases of patient's data theft have been reported where cybercriminals authenticated into the patient's account, stole the patient's medical data and assumed the identity of the patients. In some cases, the stolen data were used to access the patient's accounts on other platforms and in other cases, to make fraudulent health insurance claims. Several measures have been suggested to address the security issues in electronic health record systems. Nevertheless, we emphasize that current measures proffer security in the short-term. This work studies the feasibility of using a decoy-based system named HoneyDetails in the security of the electronic health record system. HoneyDetails will serve fictitious medical data to the adversary during his hacking attempt to steal the patient's data. However, the adversary will remain oblivious to the deceit due to the realistic structure of the data. Our findings indicate that the proposed system may serve as a potential measure for safeguarding against patient's information theft.
    Matched MeSH terms: Electronic Health Records
  18. Lim HM, Ng CJ, Abdullah A, Dalmazzo J, Lim WX, Lee KH, et al.
    Front Public Health, 2023;11:1132397.
    PMID: 37228723 DOI: 10.3389/fpubh.2023.1132397
    BACKGROUND: Online health misinformation about statins potentially affects health decision-making on statin use and adherence. We developed an information diary platform (IDP) to measure topic-specific health information exposure where participants record what information they encounter. We evaluated the utility and usability of the smartphone diary from the participants' perspective.

    METHODS: We used a mixed-method design to evaluate how participants used the smartphone diary tool and their perspectives on usability. Participants were high cardiovascular-risk patients recruited from a primary care clinic and used the tool for a week. We measured usability with the System Usability Scale (SUS) questionnaire and interviewed participants to explore utility and usability issues.

    RESULTS: The information diary was available in three languages and tested with 24 participants. The mean SUS score was 69.8 ± 12.9. Five themes related to utility were: IDP functions as a health information diary; supporting discussion of health information with doctors; wanting a feedback function about credible information; increasing awareness of the need to appraise information; and wanting to compare levels of trust with other participants or experts. Four themes related to usability were: ease of learning and use; confusion about selecting the category of information source; capturing offline information by uploading photos; and recording their level of trust.

    CONCLUSION: We found that the smartphone diary can be used as a research instrument to record relevant examples of information exposure. It potentially modifies how people seek and appraise topic-specific health information.

    Matched MeSH terms: Electronic Health Records
  19. Ali A, Al-Rimy BAS, Tin TT, Altamimi SN, Qasem SN, Saeed F
    Sensors (Basel), 2023 Aug 28;23(17).
    PMID: 37687931 DOI: 10.3390/s23177476
    Precision medicine has emerged as a transformative approach to healthcare, aiming to deliver personalized treatments and therapies tailored to individual patients. However, the realization of precision medicine relies heavily on the availability of comprehensive and diverse medical data. In this context, blockchain-enabled federated learning, coupled with electronic medical records (EMRs), presents a groundbreaking solution to unlock revolutionary insights in precision medicine. This abstract explores the potential of blockchain technology to empower precision medicine by enabling secure and decentralized data sharing and analysis. By leveraging blockchain's immutability, transparency, and cryptographic protocols, federated learning can be conducted on distributed EMR datasets without compromising patient privacy. The integration of blockchain technology ensures data integrity, traceability, and consent management, thereby addressing critical concerns associated with data privacy and security. Through the federated learning paradigm, healthcare institutions and research organizations can collaboratively train machine learning models on locally stored EMR data, without the need for data centralization. The blockchain acts as a decentralized ledger, securely recording the training process and aggregating model updates while preserving data privacy at its source. This approach allows the discovery of patterns, correlations, and novel insights across a wide range of medical conditions and patient populations. By unlocking revolutionary insights through blockchain-enabled federated learning and EMRs, precision medicine can revolutionize healthcare delivery. This paradigm shift has the potential to improve diagnosis accuracy, optimize treatment plans, identify subpopulations for clinical trials, and expedite the development of novel therapies. Furthermore, the transparent and auditable nature of blockchain technology enhances trust among stakeholders, enabling greater collaboration, data sharing, and collective intelligence in the pursuit of advancing precision medicine. In conclusion, this abstract highlights the transformative potential of blockchain-enabled federated learning in empowering precision medicine. By unlocking revolutionary insights from diverse and distributed EMR datasets, this approach paves the way for a future where healthcare is personalized, efficient, and tailored to the unique needs of each patient.
    Matched MeSH terms: Electronic Health Records
  20. Rahmat RF, Andreas TSM, Fahmi F, Pasha MF, Alzahrani MY, Budiarto R
    J Healthc Eng, 2019;2019:5810540.
    PMID: 31316743 DOI: 10.1155/2019/5810540
    Compression, in general, aims to reduce file size, with or without decreasing data quality of the original file. Digital Imaging and Communication in Medicine (DICOM) is a medical imaging file standard used to store multiple information such as patient data, imaging procedures, and the image itself. With the rising usage of medical imaging in clinical diagnosis, there is a need for a fast and secure method to share large number of medical images between healthcare practitioners, and compression has always been an option. This work analyses the Huffman coding compression method, one of the lossless compression techniques, as an alternative method to compress a DICOM file in open PACS settings. The idea of the Huffman coding compression method is to provide codeword with less number of bits for the symbol that has a higher value of byte frequency distribution. Experiments using different type of DICOM images are conducted, and the analysis on the performances in terms of compression ratio and compression/decompression time, as well as security, is provided. The experimental results showed that the Huffman coding technique has the capability to compress the DICOM file up to 1 : 3.7010 ratio and up to 72.98% space savings.
    Matched MeSH terms: Electronic Health Records
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