Impact of Laboratory Value Flowsheet in Electronic Health Record (EHR) Documentation Time

Research on the use of EHR is contradictory since it presents contradicting results regarding the time spent documenting. There is research that supports the use of electronic records as a tool to speed documentation;and research that found that it is time consuming. The purpose of this quantitative retrospective before-after project was to measure the impact of using the laboratory value flowsheet within the EHR on documentation time. The research question was: “Does the use of a laboratory value flowsheet in the EHR impact documentation time by primary care providers (PCPs)?” The theoretical framework utilized in this project was the Donabedian Model. The population in this research was the two PCPs in a small primary care clinic in the northwest of Puerto Rico. The sample was composed of all the encounters during the months of October 2019 and December 2019. The data was obtained through data mining and analyzed using SPSS 27. The evaluative outcome of this project is that there is a decrease in documentation time after implementation of the use of the laboratory value flowsheet in the EHR. However, patients per day increase therefore having an impact on the number of patients seen per day/week/month. The implications for clinical practice include the use of templates to improve workflow and documentation as well as decreasing documentation time while also increasing the number of patients seen per day. .

A Secure Signcryption Scheme for Electronic Health Records Sharing in Blockchain

In the existing Electronic Health Records(EHRs),the medical information of patients is completely controlled by various medical institutions.As such,patients have no dominant power over their own EHRs.These personal data are not only inconvenient to access and share,but are also prone to cause privacy disclosure.The blockchain technology provides a new development direction in the medical field.Blockchain-based EHRs are characterized by decentralization,openness and non-tampering of records,which enable patients to better manage their own EHRs.In order to better protect the privacy of patients,only designated receivers can access EHRs,and receivers can authenticate the sharer to ensure that the EHRs are real and effective.In this study,we propose an identity-based signcryption scheme with multiple authorities for multiple receivers,which can resist N-1 collusion attacks among N authorities.In addition,the identity information of receivers is anonymous,so the relationship between them and the sharer is not disclosed.Under the random oracle model,it was proved that our scheme was secure and met the unforgeability and confidentiality requirements of signcryption.Moreover,we evaluated the performance of the scheme and found that it had the moderate signcryption efficiency and excellent signcryption attributes.

Hyperledger Fabric Blockchain: Secure and Efficient Solution for Electronic Health Records

Background:Electronic Health Record(EHR)systems are used as an efficient and effective technique for sharing patient’s health records among different hospitals and various other key stakeholders of the healthcare industry to achieve better diagnosis and treatment of patients globally.However,the existing EHR systems mostly lack in providing appropriate security,entrusted access control and handling privacy and secrecy issues and challenges in current hospital infrastructures.Objective:To solve this delicate problem,we propose a Blockchain-enabled Hyperledger Fabric Architecture for different EHR systems.Methodology:In our EHR blockchain system,Peer nodes from various organizations(stakeholders)create a ledger network,where channels are created to enable secure and private communication between different stakeholders on the ledger network.Individual patients and other stakeholders are identified and registered on the network by unique digital certificates issued by membership service provider(MSP)component of the fabric architecture.Results:We created and implemented different Chaincodes to handle the business logic for executing separate EHR transactions on the network.The proposed fabric architecture provides a secure,transparent and immutable mechanism to store,share and exchange EHRs in a peer-to-peer network of different healthcare stakeholders.It ensures interoperability,scalability and availability in adapting the existing EHRs for strengthening and providing an effective and secure method to integrate and manage patient records among medical institutions in the healthcare ecosystem.

Correlation between an Independent Electronic Health Record &External Ranking of Children’s Hospitals

Introduction: To evaluate the correlation between the presence of an independent EHR (compared to a shared EHR system within an adult hospital system) and an externally-derived third party ranking of children’s hospitals. Methods: Children’s hospitals that ranked in the top fifty of the 2019-2020 US News and World Report (USNWR) were included in the analysis. The mean and median ranking of children’s hospitals with independent versus a shared EHR was evaluated. The 2019-2020 USNWR rankings of the top twenty adult hospitals in the United States were then evaluated. For each children’s hospital with an associated adult hospital that was both ranked, it was noted as to whether the EHR for the children’s hospital was independent or shared and statistical differences in rankings compared. Results: Among the top 50 children’s hospitals included, the median USNWR ranking for hospitals was statistically different with an independent EHR than with a shared EHR (13 vs. 30.0) (p = 0.002). The 21 top ranked adult hospitals were associated with 17 children’s hospitals ranked in the top 50. The median ranking for those with an independent EHR was statistically different for those with independent EHR versus shared EHR (7 vs. 28) (p = 0.002). Conclusion: Children’s hospitals with an independent EHR are associated with higher scores on an independent external ranking of hospital quality compared to those which share an EHR with a partner adult hospital.

Nursing decision support system:application in electronic health records

The clinical decision support system makes electronic health records(EHRs)structured,intelligent,and knowledgeable.The nursing decision support system(NDSS)is based on clinical nursing guidelines and nursing process to provide intelligent suggestions and reminders.The impact on nurses’work is mainly in shortening the recording time,improving the quality of nursing diagnosis,reducing the incidence of nursing risk events,and so on.However,there is no authoritative standard for the NDSS at home and abroad.This review introduces development and challenges of EHRs and recommends the application of the NDSS in EHRs,namely the nursing assessment decision support system,the nursing diagnostic decision support system,and the nursing care planning decision support system(including nursing intervene),hoping to provide a new thought and method to structure impeccable EHRs.

Deletion and Recovery Scheme of Electronic Health Records Based onMedical Certificate Blockchain

The trusted sharing of Electronic Health Records(EHRs)can realize the efficient use of medical data resources.Generally speaking,EHRs are widely used in blockchain-based medical data platforms.EHRs are valuable private assets of patients,and the ownership belongs to patients.While recent research has shown that patients can freely and effectively delete the EHRs stored in hospitals,it does not address the challenge of record sharing when patients revisit doctors.In order to solve this problem,this paper proposes a deletion and recovery scheme of EHRs based on Medical Certificate Blockchain.This paper uses cross-chain technology to connect the Medical Certificate Blockchain and the Hospital Blockchain to real-ize the recovery of deleted EHRs.At the same time,this paper uses the Medical Certificate Blockchain and the InterPlanetary File System(IPFS)to store Personal Health Records,which are generated by patients visiting different medical institutions.In addition,this paper also combines digital watermarking technology to ensure the authenticity of the restored electronic medical records.Under the combined effect of blockchain technology and digital watermarking,our proposal will not be affected by any other rights throughout the process.System analysis and security analysis illustrate the completeness and feasibility of the scheme.

Evaluation of the HIV Case-Based Surveillance System: A Pilot of the Electronic Health Record System in Mutare District, Zimbabwe, 2021

Background: Zimbabwe started HIV case-based surveillance in April 2017. Rapid testing for HIV recent infection was introduced into routine HIV and testing services in 2019 along with the Impilo Electronic Health Record System. For the period January-June 2020, only 1 out of 13 health facilities in Mutare district reported seven newly diagnosed HIV patients through the electronic health record system compared to 483 in the District Health Information System (DHIS-2) recorded from paper-based registers. We evaluated the case-based surveillance system attributes, usefulness and reasons for under-reporting from January-December 2020. Methods: We conducted a descriptive cross-sectional study using updated Centres for Disease Control guidelines for evaluating public health surveillance systems. Questionnaires were administered to 36 health workers involved in HIV testing services. Facility checklists were used to collect data on knowledge, system attributes and usefulness of the system. Completed HIV case-based surveillance forms were assessed for completeness. Epi Info Version 7 was used to generate frequencies, means and proportions. Results: The reasons for under-reporting of patients in the electronic health record system were lack of reporting guidelines 26/36 (72%), limited coordination between technical staff and health facilities 24/36 (67%) and limited competency on the Electronic health record system 22/36 (61%). Timeliness, completeness, and validity were 88%, 82% and 100% respectively. The stability of the system was affected by the lack of standard operating procedures during system interruptions. Overall representativeness was 45% despite increasing from 3/226 (1%) to 224/303 (73%) between Quarter-1 and Quarter-4 of 2020. Acceptability was 100% due to reduced paperwork and the ability to generate simple reports. The information generated was used to identify new infection hotspots 28/36 (78%). Conclusion: The HIV cases based surveillance system was timely, acceptable with good data quality. Representativeness was poor due to limited competency on the electronic health record system. As a result, health workers received further training.

Machine-Learning-Enabled Obesity Level Prediction Through Electronic Health Records

Obesity is a critical health condition that severely affects an individual’s quality of life andwell-being.The occurrence of obesity is strongly associated with extreme health conditions,such as cardiac diseases,diabetes,hypertension,and some types of cancer.Therefore,it is vital to avoid obesity and or reverse its occurrence.Incorporating healthy food habits and an active lifestyle can help to prevent obesity.In this regard,artificial intelligence(AI)can play an important role in estimating health conditions and detecting obesity and its types.This study aims to see obesity levels in adults by implementing AIenabled machine learning on a real-life dataset.This dataset is in the form of electronic health records(EHR)containing data on several aspects of daily living,such as dietary habits,physical conditions,and lifestyle variables for various participants with different health conditions(underweight,normal,overweight,and obesity type I,II and III),expressed in terms of a variety of features or parameters,such as physical condition,food intake,lifestyle and mode of transportation.Three classifiers,i.e.,eXtreme gradient boosting classifier(XGB),support vector machine(SVM),and artificial neural network(ANN),are implemented to detect the status of several conditions,including obesity types.The findings indicate that the proposed XGB-based system outperforms the existing obesity level estimation methods,achieving overall performance rates of 98.5%and 99.6%in the scenarios explored.

Ensuring Information Security in Electronic Health Record System Using Cryptography and Cuckoo Search Algorithm

In the contemporary era,the abundant availability of health information through internet and mobile technology raises concerns.Safeguarding and maintaining the confidentiality of patients’medical data becomes paramount when sharing such information with authorized healthcare providers.Although electronic patient records and the internet have facilitated the exchange of medical information among healthcare providers,concerns persist regarding the security of the data.The security of Electronic Health Record Systems(EHRS)can be improved by employing the Cuckoo Search Algorithm(CS),the SHA-256 algorithm,and the Elliptic Curve Cryptography(ECC),as proposed in this study.The suggested approach involves usingCS to generate the ECCprivate key,thereby enhancing the security of data storage in EHR.The study evaluates the proposed design by comparing encoding and decoding times with alternative techniques like ECC-GA-SHA-256.The research findings indicate that the proposed design achieves faster encoding and decoding times,completing 125 and 175 iterations,respectively.Furthermore,the proposed design surpasses other encoding techniques by exhibiting encoding and decoding times that are more than 15.17%faster.These results imply that the proposed design can significantly enhance the security and performance of EHRs.Through the utilization of CS,SHA-256,and ECC,this study presents promising methods for addressing the security challenges associated with EHRs.

The development and impact of adopting electronic health records in the United States:A brief overview and implications for nursing education

1|DEVELOPMENT AND ADOPTION OF EHR IN THE UNITED STATES At present,health-care systems in the United States face enormous challenges in providing quality care,characterized by safe,effective,efficient,patientcentered,timely,and equitable care while containing health-care costs[1,2].To understand and address patients'increasingly complicated health-care needs,we need safe access to quality information that is characterized by integrity,reliability,and accuracy[3],and establish mutually beneficial relationships among a multidisciplinary team of professionals[4].Traditional paper-based clinical workflow produces many issues such as illegible handwriting,inconvenient access,the possibility of computational prescribing errors,inadequate patient hand-offs,and drug administration errors.These problems can lead to medical errors,omissions,and duplications and,ultimately,poor patient outcomes and compromised quality of care[2].

Constructing Large Scale Cohort for Clinical Study on Heart Failure with Electronic Health Record in Regional Healthcare Platform:Challenges and Strategies in Data Reuse

Regional healthcare platforms collect clinical data from hospitals in specific areas for the purpose of healthcare management.It is a common requirement to reuse the data for clinical research.However,we have to face challenges like the inconsistence of terminology in electronic health records (EHR) and the complexities in data quality and data formats in regional healthcare platform.In this paper,we propose methodology and process on constructing large scale cohorts which forms the basis of causality and comparative effectiveness relationship in epidemiology.We firstly constructed a Chinese terminology knowledge graph to deal with the diversity of vocabularies on regional platform.Secondly,we built special disease case repositories (i.e.,heart failure repository) that utilize the graph to search the related patients and to normalize the data.Based on the requirements of the clinical research which aimed to explore the effectiveness of taking statin on 180-days readmission in patients with heart failure,we built a large-scale retrospective cohort with 29647 cases of heart failure patients from the heart failure repository.After the propensity score matching,the study group (n=6346) and the control group (n=6346) with parallel clinical characteristics were acquired.Logistic regression analysis showed that taking statins had a negative correlation with 180-days readmission in heart failure patients.This paper presents the workflow and application example of big data mining based on regional EHR data.

An Investigation on the Barriers and Facilitators of the Implementation of Electronic Health Records (EHR)

The application of technology in health care, in the form of electronic health records (EHR), is the most important and necessary issue in order to improve the quality of health care, and studies have shown that, not only is it a way to integrate information and represent the condition of patients, and a dynamic source for health care, however it leads to gain access to clinical information and records, electronic communications, comprehensive training and management, and ultimately enhancing the public health;the aim of this study is to investigate the factors influencing the implementation of EHR, which are known as barriers and facilitators. The research is conducted in the form of a review research, and with the help of the Keywords of EHR;barriers and facilitators, articles, from 2008 to 2013, were searched and studied in the Internet-databases. The results of the studies show that the most effective factors include: efficiency, motivation, management, and the participation of end users. Factors such as technical aspects ease of use, available resources, and human resources, have limited effects. And security and privacy, the expected output, lack of time, and workload have relative effects, and also the relation between the patient and clinical staff, has no effects in the process of implementing EHR.

Psychiatric electronic health records privacy in Jordan: A policy brief

Psychiatric health records are highly sensitive data which requires special policy to maintain its privacy,without affecting data accessibility.The current authors reviewed social,ethical and legal underpinnings for psychiatric electronic health records(EHR),and suggests a policy to maintain privacy and confidentiality of the psychiatric data,without affecting data accessibility.The purpose of this policy brief is to discuss and provide alternatives regarding psychiatric electronic health records privacy and information access.The current policy applied in Jordan still immature to ensure high levels of reliability,as the psychiatric data is openly accessed to the non-specialized personnel.Sensitive personal data policy is recommended in this paper with developing overriding mechanisms to counteract obstacles to data accessibility.

Opportunities for nurses in the era of electronic health records

Nursing leaders are currently faced with opportunities to advance nursing’s role in the use of electronic health records (EHRs). Nurse leaders can advance the design of EHRs with nurse informaticists to improve health outcomes of individual and populations of patients.

E-Health环境下患者电子参与框架构建与策略研究

患者参与被认为是新阶段医疗改革的重要支柱和医疗保健质量改善的新活力。近年来E-Health技术发展迅速,为患者参与医疗保健提供了更广泛的途径以及更丰富的手段。归纳梳理出患者电子参与的基本内涵,结合国外推动患者电子参与的举措和相关文献研究构建患者电子参与框架,阐述患者电子参与的类型、媒介与方法,最后从项目支撑、患者教育和信息权限等方面提出我国在E-Health环境下推进患者电子参与具体举措。

The development of Electronic Health Literacy worldwide: a bibliometric analysis

Objective:This study aimed to review researches on electronic health literacy,provided some suggestions and identified directions for further research.Methods:The literatures were collected by searching the China National Knowledge Infrastructure(CNKI)and the core collection database of Web of Science from inception to November 17,2019.SPSS software was used for regression analysis,and citespace 5.5.R2 was used for visual analysis.Results:A total of 249 valid documents were retrieved,of which 205 were in English and 44 were in Chinese.Among them,USA had the largest number of publications,followed by Australia,Germany,Netherlands,and China.In China,Beijing has the most published literatures,followed by Anhui,Shanghai,Guangdong,and Shandong.The English-language journal with the most publications was journal of Medical Internet Research,and Chinese-language journal was Chinese health education.However,the Chinese and English core journals were relatively scattered,and no core journal group had yet formed.There were 111 funding institutions in both Chinese and English literature.Research content mainly included current situation investigation,influencing factors,clinical practice interventions,scale preparation and translation,qualitative interviews,etc.Conclusion:At present,there are many researches in the field of e-health literacy worldwide.However,the quality and depth of research still need to be further improved.The field of research also needs to be further expanded to meet the opportunities and challenges that the Internet brings to the medical industry.

E-Health and Telemedicine: Current State and Future Steps

The article reviews the questions related to building the e-health systems. The key element of the system is electronic healthcare record to be formed according to the modular approach in the form of primary and satellite electronic medical records. Person-centred healthcare is proposed as a foundation for e-health. Such an approach provides a potential opportunity for all the medical doctors to obtain necessary information about their patients at any time via the teleconsultations in particular. Transition to e-health is associated with the creation of new opportunities for making diagnostic and therapeutic decisions based on the use of build-in decision support modules. The computer-assisted software design or hybrid systems are considered as the fourth generation medical information systems. It is reasonable to implement the entire information space of e-health, including the information systems of medical institutions and regional data repositories, based on cloud-optimized storage and computing solutions. This approach is expected to be implemented in Russia as a part of the unified state health information system. The authorized access to integrated databases for medical doctors of various specialties is required. In the framework of e-health, telemedicine is considered as an important component. Main elements comprise the real-time access of medical consultants to personified medical databases and remote follow-up of patients by the means of personal or home-based telemedicine. The use of personal portable devices for the control of vital signs of the organism is especially promising. Electronic stethoscopes and specialized video cameras for acquiring objective information should be increasingly used by remote consultants. Unfortunately, this trend is still underdeveloped in Russia. In perspective, e-health as unified medical space will provide a transition to the integrated analysis of population health by medical doctors of various specialties from different countries and will open new prospects for studying health based on the intelligent analysis of integrated data of patients.

Thermally Conductive and UV-EMI Shielding Electronic Textiles for Unrestricted and Multifaceted Health Monitoring

Skin-attachable electronics have garnered considerable research attention in health monitoring and artificial intelligence domains,whereas susceptibility to elec-tromagnetic interference(EMI),heat accumulation issues,and ultraviolet(UV)-induced aging problems pose significant constraints on their potential applications.Here,an ultra-elas-tic,highly breathable,and thermal-comfortable epidermal sensor with exceptional UV-EMI shielding performance and remarkable thermal conductivity is developed for high-fidelity monitoring of multiple human electrophysiological signals.Via filling the elastomeric microfibers with thermally conductive boron nitride nanoparticles and bridging the insulating fiber interfaces by plating Ag nanoparticles(NPs),an interwoven thermal con-ducting fiber network(0.72 W m^(-1) K^(-1))is constructed benefiting from the seamless thermal interfaces,facilitating unimpeded heat dissipation for comfort skin wearing.More excitingly,the elastomeric fiber substrates simultaneously achieve outstanding UV protection(UPF=143.1)and EMI shielding(SET>65,X-band)capabilities owing to the high electrical conductivity and surface plasmon resonance of Ag NPs.Furthermore,an electronic textile prepared by printing liquid metal on the UV-EMI shielding and thermally conductive nonwoven textile is finally utilized as an advanced epidermal sensor,which succeeds in monitoring different electrophysiological signals under vigorous electromagnetic interference.This research paves the way for developing protective and environmentally adaptive epidermal electronics for next-generation health regulation.

Practical use of electronic health records among patients with diabetes in scientific research

Electronic health(medical)records,which are also considered as patients*information that are routinely collected,provide a great chance for researchers to develop an epidemiological understanding of disease.Electronic health records systems cannot develop without the advance of computer industries.While conducting clinical trials that are always costly,feasible and reasonable analysis of routine patients5 information is more cost-effective and reflective of clinical practice,which is also called real world study.Real world studies can be well supported by big data in healthcare industry.Real world studies become more and more focused and important with the development of evidence-based medicine.These big data will definitely help in making decisions,making policies and guidelines,monitoring of effectiveness and safety on new drugs or technologies.Extracting,cleaning,and analyzing such big data will be a great challenge for clinical researchers.Successful applications and developments of electronic health record in western countries(eg,disease registries,health insurance claims,etc)have provided a clear direction for Chinese researchers.However,it is still at primary stages in China.This review tries to provide a full perspective on how to translate the electronic health records into scientific achievements,for example,among patients with diabetes.As a summary in the end,resource sharing and collaborations are highly recommended among hospitals and healthcare groups.

Deep Learning with Heterogeneous Graph Embeddings for Mortality Prediction from Electronic Health Records

Computational prediction of in-hospital mortality in the setting of an intensive care unit can help clinical practitioners to guide care and make early decisions for interventions. As clinical data are complex and varied in their structure and components, continued innovation of modelling strategies is required to identify architectures that can best model outcomes. In this work, we trained a Heterogeneous Graph Model(HGM) on electronic health record(EHR) data and used the resulting embedding vector as additional information added to a Convolutional Neural Network(CNN) model for predicting in-hospital mortality. We show that the additional information provided by including time as a vector in the embedding captured the relationships between medical concepts, lab tests, and diagnoses, which enhanced predictive performance. We found that adding HGM to a CNN model increased the mortality prediction accuracy up to 4%. This framework served as a foundation for future experiments involving different EHR data types on important healthcare prediction tasks.