HEDGE: A sustainable framework for energy efficient optimized proof of work in block chain systems

BackgroundClinicians’ use of electronic health record (EHR) systems while multitasking may increase the risk of making errors, but silent EHR system use may lower patient satisfaction. Delaying EHR system use until after patient visits may increase clinicians’ EHR workload, stress, and burnout.ObjectiveWe aimed to describe the perspectives of clinicians, educators, administrators, and researchers about misses and near misses that they felt were related to clinician multitasking while using EHR systems.MethodsThis observational study was a thematic analysis of perspectives elicited from 63 continuing medical education (CME) participants during 2 workshops and 1 interactive lecture about challenges and strategies for relationship-centered communication during clinician EHR system use. The workshop elicited reflection about memorable times when multitasking EHR use was associated with “misses” (errors that were not caught at the time) or “near misses” (mistakes that were caught before leading to errors). We conducted qualitative analysis using an editing analysis style to identify codes and then select representative themes and quotes.ResultsAll workshop participants shared stories of misses or near misses in EHR system ordering and documentation or patient-clinician communication, wondering about “misses we don’t even know about.” Risk factors included the computer’s position, EHR system usability, note content and style, information overload, problematic workflows, systems issues, and provider and patient communication behaviors and expectations. Strategies to reduce multitasking EHR system misses included clinician transparency when needing silent EHR system use (eg, for prescribing), narrating EHR system use, patient activation during EHR system use, adapting visit organization and workflow, improving EHR system design, and improving team support and systems.ConclusionsCME participants shared numerous stories of errors and near misses in EHR tasks and communication that they felt related to EHR multitasking. However, they brainstormed diverse strategies for using EHR systems safely while preserving patient relationships.

Usability problems do not heal by themselves: National survey on physicians’ experiences with EHRs in Finland

This paper presents the impact of the Electronic Health Records (EHRs) systems jointly in the Spanish Primary Public Health System. Different EHRs that exist in each of the Spanish regions are discussed. Moreover, other purpose of this analysis is to identify the current state of knowledge about health information systems adoption in primary care in Spain. For the analysis and study of EHRs systems in Spain we have relied on the use of different sources, mostly items related to the study of EHRs systems in different areas. We will analyze some technical aspects of these and some of their major implications, both positive and negative. Moreover, we have resorted to make direct contact with the organizations that have implemented the EHRs systems. The result of this study leads to a main idea, the need for interoperability between different systems. We will delve into how we have reached this conclusion and that is the key to EHRs systems homogenization of Spanish territory. EHR systems used in different regions of Spain offer the access to medical information as well as provide a clinical analysis of each patient more quickly. The adoption of health information systems is seen world wide as one method to mitigate the widening health care demand and supply gap.

IntroductionThe ability to utilize the electronic health record (EHR) without compromising the doctor-patient relationship (DPR) is an essential skill of all physicians and trainees, yet little time is spent on educating or assessing learners on needed techniques. To address this gap, we developed a conventional OSCE station coupled with a simulated patient chart within the Epic program in order to assess our students' skills utilizing the EHR during a patient encounter.MethodsOf third-year medical students, 119 were given full access to the patient's simulated chart 24 hours in advance of their OSCE to review clinical data. During an in-person OSCE with a standardized patient (SP), students performed a focused history and physical, using the EHR to verify allergies and medications. Students completed an electronic patient note graded by faculty. SPs evaluated the students on communication and interpersonal skills with specific rubric elements. Faculty graded the students' notes to evaluate their expression of clinical reasoning in the assessment and plan.ResultsTraining SPs and faculty to assess students on EHR skills was feasible. After implementation of a comprehensive curriculum focused on EHR and DPR, there was a significant difference on EHR-related communication skills (M = 76.4, SD = 17.6) versus (M = 37, SD = 28.9) before curriculum enhancement t (117.9) = −12.4, p <.001.DiscussionThe EHR OSCE station provided a standardized method of assessing students' EHR skills during a patient encounter. Challenges still exist in the technological requirements to develop and deliver cases in today's EHR platform.

BackgroundWhile machine learning (ML) technologies have shifted from development to real-world deployment over the past decade, US health care providers and hospital administrators have increasingly embraced ML, particularly through its integration with electronic health record (EHR) systems. This evolving landscape underscores the need for empirical evidence on ML adoption and its determinants; however, the relationship between hospital characteristics and ML integration within EHR systems remains insufficiently explored.ObjectiveThis study aimed to examine the current state of ML adoption within EHR systems across US general acute care hospitals and to identify hospital characteristics associated with ML implementation.MethodsWe used linked data between the 2022‐2023 American Hospital Association Annual Survey and the 2023‐2024 American Hospital Association Information Technology Supplement Survey. The sample includes 2562 general and acute care hospitals in the United States with a total of 4055 observations over 2 years. Applying inverse probability weighting to address nonresponse bias, we used descriptive statistics to assess ML adoption patterns and multivariate logistic regression models to identify hospital characteristics associated with ML adoption.ResultsOverall, about 75% of the hospitals had adopted ML functions within their EHR systems in 2023‐2024, and the majority tended to adopt both clinical and operational ML functions simultaneously. The most commonly adopted individual functions were predicting inpatient risks and outpatient follow-ups. ML model evaluation practices, while still limited overall, showed notable improvement. Multivariate regression estimates indicate that hospitals were more likely to adopt any ML if they were not-for-profit (4.4 percentage points, 95% CI 0.6-8.2; P=.02), large hospitals (15 percentage points, 95% CI 9.4-21; P<.001), operated in metropolitan areas (4.3 percentage points, 95% CI 0.8-7.8; P=.02), contracted with leading EHR vendors (20.6 percentage points, 95% CI 17.1-24; P<.001), and affiliated with a health system (26.8 percentage points, 95% CI 22.4-31.3; P<.001). Similar patterns were observed for predicting the adoption of both clinical and operative ML. We also identified specific hospital characteristics associated with the adoption of individual ML functions.ConclusionsML adoption in hospitals is influenced by organizational resources and strategic priorities, raising concerns about potential digital inequities. Limited quality control and evaluation practices highlight the need for stronger regulatory oversight and targeted support for underresourced hospitals. As the integration of ML into EHR systems expands, disparities in both adoption and oversight become increasingly critical. To ensure the equitable, safe, and effective implementation of ML technologies in health care, well-designed policies must address these gaps and promote inclusive innovation across all hospital settings.

4 - Blockchain applications for the healthcare sector: Uses beyond Bitcoin

BackgroundThe recent, rapid development of digital technologies offers new possibilities for more efficient implementation of electronic health record (EHR) and personal health record (PHR) systems. A growing volume of healthcare data has been the hallmark of this digital transformation. The large healthcare datasets' complexity and their dynamic nature pose various challenges related to processing, analysis, storage, security, privacy, data exchange, and usability. Materials and MethodsWe performed a systematic review of systematic reviews to assess technological progress in EHR and PHR systems. We searched MEDLINE, Cochrane, Web of Science, and Scopus for systematic literature reviews on technological advancements that support EHR and PHR systems published between January 1, 2010, and October 06, 2020. ResultsThe searches resulted in a total of 2,448 hits. Of these, we finally selected 23 systematic reviews. Most of the included papers dealt with information extraction tools and natural language processing technology (n = 10), followed by studies that assessed the use of blockchain technology in healthcare (n = 8). Other areas of digital technology research included EHR and PHR systems in austere settings (n = 1), de-identification methods (n = 1), visualization techniques (n = 1), communication tools within EHR and PHR systems (n = 1), and methodologies for defining Clinical Information Models that promoted EHRs and PHRs interoperability (n = 1). ConclusionsTechnological advancements can improve the efficiency in the implementation of EHR and PHR systems in numerous ways. Natural language processing techniques, either rule-based, machine-learning, or deep learning-based, can extract information from clinical narratives and other unstructured data locked in EHRs and PHRs, allowing secondary research (i.e., phenotyping). Moreover, EHRs and PHRs are expected to be the primary beneficiaries of the blockchain technology implementation on Health Information Systems. Governance regulations, lack of trust, poor scalability, security, privacy, low performance, and high cost remain the most critical challenges for implementing these technologies.

Background: In most healthcare facilities, the shift from paper-based medical records to electronic health records (EHRs) has taken place. However, there are issues with credibility, management, and secure data storage with the existing EHR systems. In the healthcare industry, interoperability and user control over personal data are also major challenges. Block chain technology has become a potent tool that can provide immutability, security, and user control over records that are saved; yet, its potential usage in EHR systems is still not well understood. Objectives: This research attempts to close this knowledge gap by developing an EHR framework that is built on blockchain technology and is compatible with many national and international EHR standards, including HL7 and HIPAA. Methods: In order to investigate the state of the art in the field of EHRs, including blockchain-based EHR implementations, a systematic literature review is the study approach used. Results: The report analyzes numerous national and international EHR standards, identifies the interoperability needs based on these standards, and outlines the interoperability challenges in the current blockchain-based EHR frameworks. Without the requirement for centralized systems, the suggested framework can give the healthcare industry safer ways to exchange health information while also offering the features of immutability, security, and user control over stored records. Conclusion: This work contributes to the understanding of Blockchain technology's potential application in EHR frameworks and offers an interoperable Blockchain-based EHR framework that can meet the requirements outlined in multiple national and international EHR standards.

We adjust the Proof of Work (PoW) consensus mechanism used in Bitcoin and Ethereum so that we can build on its strength while also addressing, in part, some of its perceived weaknesses. Notably, our work is motivated by the high energy consumption for mining PoW, and we want to restrict the use of PoW to a configurable, expected size of nodes, as a function of the local blockchain state. The approach we develop for this rests on three pillars: (i) Proof of Kernel Work (PoKW), a means of dynamically reducing the set of nodes that can participate in the solving of PoW puzzles such that an adversary cannot increase his attack surface because of such a reduction; (ii) Practical Adaptation of Existing Technology, a realization of this PoW reduction through an adaptation of existing blockchain and enterprise technology stacks; and (iii) Machine Learning for Adaptive System Resiliency, the use of techniques from artificial intelligence to make our approach adaptive to system, network and attack dynamics. We develop here, in detail, the first pillar and illustrate the second pillar through a real use case, a pilot project done with Porsche on controlling permissions to vehicle and data log accesses. We also discuss pertinent attack vectors for PoKW consensus and their mitigation. Moreover, we sketch how our approach may lead to more democratic PoKW-based blockchain systems for public networks that may inherit the resilience of blockchains based on PoW.

An Electronic Health Record (EHR) system is a computerised medical information system that collects, displays, and stores a patient’s information. It is an evidence base that addresses issues associated with patients’ paper records. Implementing such a system will have a high positive impact on healthcare quality and healthcare services. For example, an EHR is an electronic record that sequentially stores any resident’s health data from nearly the first month of gestation until death, and can bring those records anytime and to any authorised physician. The objectives of this study are to investigate the present status of EHR implementations around the world, and to identify best practice solutions. Additionally, the study focuses on how to adopt best practices in Australia. The methodology of this paper involved an academic research consisting of 250 articles and over 100 websites. All of the information in this paper was obtained through a search strategy—using PubMed, Google Scholar, and Google—of the best practices applied in many countries, including the US, Canada, and several nations in Western Europe. With 30 references used that provided the recommendations to adopt the best practice solutions for Australian My Health Record system while implementation. This paper has further exposed the problems with EHR systems as implemented worldwide. The recommendations can be summarised as follows: improve the overall awareness of the stakeholders, conduct training sessions for stakeholders on My Health Record system, reward physicians for using the system, achieve ongoing technical and systems security integrity and compliance, implement a response plan in the event of a breach of the EHR system, and implement a simple graphical user interface to facilitate access to stakeholders. Further results as recommendations are provided in the results section. The research concluded that by adopting these best practice solutions, Australia will be able to achieve a stable healthcare system, which will ensure a higher level of healthcare quality to patients and healthcare alike. This paper will give stakeholders a clear vision to determine the original cause that hinders satisfying results while implementing My Health Record system in Australia.

Nurses are one of the largest user groups of the electronic health record (EHR) system, relying on its tools to support patient care and nursing workflows. Recent studies suggested that the redesign of nursing documentation may reduce the time spent in the EHR system and improve nurse satisfaction. We aimed to assess nurses' perceptions of the redesigned EHR, evaluate the impact of documentation interventions, and identify future improvement needs. Guided by the American Nursing Informatics Association's Six Domains of Burden conceptual framework, this multimethod project combined both qualitative and quantitative approaches. Registered nurses across the academic health system were recruited via email invitations to participate in focus group discussions. The focus groups were conducted via a web conference and ranged from 60 to 90 minutes in duration. The focus group discussions were transcribed and analyzed through thematic analysis. The EHR vendor's time data were used to analyze nurses' time spent in documentation. In total, 20 registered nurses participated in the focus group discussions, and 17 nurses completed the demographic survey; 88% (15/17) of participants had ≥3 years of EHR experience at the academic health system, and 53% (9/17) self-reported being competent in the EHR system. The following six themes emerged: positive feedback, usability and workflow opportunities, nuisance, training and education, communication, and time spent in the system. EHR vendor time data revealed that the time spent in flowsheets averaged 31.11% per 12-hour shift. Overall, participants reported a positive experience and that the EHR supported patient care. There are opportunities to further reduce redundancies in documentation and implement programs that support continuous learning about EHR and health technology tools. Specific suggestions include optimizing the oral health assessment tool. Analyzing frontline nursing perspectives in the redesign of EHR workflows is imperative for identifying interventions that support nurses' satisfaction with the EHR.

The electronic health record (EHR) system is a cloud-based patient health record in digital format that often includes contact information about the patient, test reports, medical history, and current and previous prescriptions. However, data breaches in cloud-based EHRs pose significant privacy and security concerns for a variety of health care organizations. Cryptographic techniques currently in use are inadequate to secure EHR data in the cloud from data breaches. Blockchain technology is a new technology that can be used to address security and privacy problems with EHR data on the blockchain in a decentralized manner. We have created a stable decentralized medical blockchain in this paper to address privacy and security concerns when sharing patient data on health care between medical organizations. The health care data is encrypted using Advanced Encryption Standard-based lightweight authenticated encryption algorithm before being uploaded to a cloud-based blockchain and Solidity smart code built on Ethereum to restrict access to EHR data in the cloud. We have used an InterPlanetary file system to store data because it is distributed and ensures record immutability. The medical blockchain also ensures that patient EHR data is interoperable, traceable, and anonymous across organizations. The stable cloud-based blockchain of medical records visualizes patient care data in a distributed and immutable environment with enhanced protection.KeywordsIPFSBlockchainSmart contractEthereum

Introduction: The digital technology in healthcare has revolutionized during the last decade with the increased implementation of Electronic Health Record (EHR) systems. The growth of EHR has been from the simple database system to incorporating the applications of artificial intelligence and machine learning systems in the system. One of the most important aspects of digital system proves to be electronic health record system because of the intense data produced geographically which can be used for epidemiological studies and research. The EHRs also have a wide range of benefits such as effective communication between the clinicians, clinicians and laboratory, decreased human errors, effective tool for diagnosis and treatment planning, increased patient satisfaction, and quality care. Materials and Methods: The quantitative study included opinions and perspectives of dental clinicians toward EHR system. The data collection of the participants was from April to December 2024. The quantitative part involved a descriptive survey. After obtaining written informed consent from each participant, a structured survey e-questionnaire was given to dental clinicians to fill it through online mode by dental practitioners who had independent clinics. The sample size calculation done by www.openepi.com software quantitative study which included two hundred and eighty five (285) dentists participated. Results: The findings indicated a favorable disposition among dentists regarding the adoption of EHR; however, dental practitioners also emphasized the problems encountered during EHR implementation. Conclusion: EHRs are an effective way inside health information systems; however, they necessitate ongoing training, regular upgrades, and the integration of artificial intelligence and machine learning technologies in the future. The threat to data security continues to be a concern for dental practitioners due to the anticipated rise in cybercrimes, as patient-sensitive information is highly confidential.

The advent of the Bitcoin system has brought another boom in the Internet era. In a very short time, many Blockchain systems come into being successively, whose decentration, consensus mechanisms, intelligent contract, and other characteristics make them applicable to various fields such as finance, education, medical, technology, etc. The consensus mechanism is the core of Blockchain technology. And a good consensus mechanism plays a very important role in the stable operation of the Blockchain system. The continuous improvement of consensus mechanisms such as PoW (proof-of-work), PoS (proof-of-stake), DPoS (delegated-proof-of-stake), and PBFT (Practical Byzantine Fault Tolerance) has led to the evolution of Blockchain technology to Blockchain 3.0. Starting from the issue of Byzantine generals, this article analyzes common consensus mechanisms based on existing Blockchain applications and then evaluates their consistency. This paper has a unique perspective, selection and comment on the latest progress and important literature in the field of block chain. At last, it also has a high degree of summary and prospect to the existing problems and the future development trend.

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