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. .

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.

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.

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.

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.

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.

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.

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.

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.

Integrating Electronic Systems for Requesting Clinical Laboratory Test into Digital Clinical Records: Design and Implementation

Clinical laboratory tests are basic elements that support healthcare tasks such as disease detection, diagnosis and monitoring of response to treatments. Current laboratory information systems focus on the patient database, tests and results, with multiple modules available, connecting with the various analytical systems or work areas. However laboratory information systems functioned as “islands of information”, because their design was fundamentally inward-looking and disconnected from other healthcare computer applications. Actually, the Electronic Health Register (EHR) is considered by clinicians as a tool with great potential healthcare benefits. The EHR, in the sense of a unique and complete record of a patient’s healthcare and state of health, regardless of the healthcare level used, is a real attempt to eliminate these “islands of information” and need modules to act as “bridges” with the laboratory information systems. This type of module, which in generic terms may be referred to as a laboratory test request module, has become an essential feature of the EHR. These modules need to use a laboratory coding system as a common language for exchanging information, ensuring that tests and results are unequivocally identified. The development of the laboratory test request module requires the commitment of professionals and political authorities, being necessary time for their design and an adequate pilot phase. The laboratory professionals have to assume a leadership role in the whole process of design, development and implementation of these modules, integrating in the equipment of information technologies of healthcare providers. In our manuscript we review the elements that may prove electronic systems for requesting clinical laboratory test into digital clinical records and the key elements to move from theory to practice.

A Proposed Layered Architecture to Maintain Privacy Issues in Electronic Medical Records

Securing large amounts of electronic medical records stored in different forms and in many locations, while making availability to authorized users is considered as a great challenge. Maintaining protection and privacy of personal information is a strong motivation in the development of security policies. It is critical for health care organizations to access, analyze, and ensure security policies to meet the challenge and to develop the necessary policies to ensure the security of medical information. The problem, then, is how we can maintain the availability of the electronic medical records and at the same time maintain the privacy of patients’ information. This paper will propose a novel architecture model for the Electronic Medical Record (EMR), in which useful statistical medical records will be available to the interested parties while maintaining the privacy of patients’ information.

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.

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.

支持用户撤销的可搜索电子健康记录共享方案

随着物联网与云存储技术的快速发展和广泛应用,每年都有大量的传感器设备被部署到医疗物联网(IoMT)系统,虽然这促进了电子健康记录(EHR)应用的普及,但EHR的安全存储与检索尚未得到妥善的解决。针对以上问题,基于可搜索加密构造长度固定的陷门用于对密文的搜索验证,减小了用户所需的通信开销;采用在线/离线加密技术,减小了用户端在线加密所需的计算开销;同时基于变色龙哈希函数,构造具有抗碰撞、语义安全等特点的私钥,避免了未撤销用户私钥频繁更新的问题,极大地减小了用户的计算开销。理论分析与实验结果表明所提方案在DBDH(Decisional Bilinear Diffie-Hellman)假设下是选择明文攻击是安全的,且与类似属性基加密方案相比,所提方案效率更高,在功能上支持在线加密、高效的用户撤销并具有更低的计算开销和存储开销。

心房颤动及心房扑动智能评分系统在门诊的应用情况及来诊患者特点

目的:评价心房颤动及心房扑动智能评分系统在门诊的应用情况及来诊患者特点。方法:收集2020年8月至2022年6月于中国医学科学院阜外医院门诊就诊的25 223例心房颤动及心房扑动患者的所有就诊记录。比较系统更新(2021年9月)前后来诊患者的特点。另从25 223例患者中筛选出系统更新前后1年内相邻2次就诊的患者404例,比较2次评分的变化趋势及抗凝药物使用情况。结果:与系统更新前比,系统更新后CHA_(2)DS_(2)-VASc评分中男性≥2分或女性≥3分的患者比例差异无统计学意义(P>0.05),这些患者中抗凝治疗比例升高(25.2%vs. 35.9%,P<0.001)。无不评分理由患者比例系统更新前为37.9%,更新后下降至21.2%。比较404例系统更新前后1年内相邻2次就诊记录发现,与更新前比,更新后患者的CHA_(2)DS_(2)-VASc评分升高[(2.12±1.48)分vs.(2.35±1.51)分,P=0.029],同时CHA_(2)DS_(2)-VASc评分中男性≥2分或女性≥3分的患者比例升高(49.5%vs. 58.7%,P=0.011),这些患者中抗凝治疗比例也升高(28.5%vs. 41.4%,P<0.001)。HAS-BLED评分及HAS-BLED评分≥3分患者的比例在系统更新前后差异均无统计学意义(P均>0.05)。结论:本院门诊所应用的智能评分系统可有效帮助医生掌握来诊心房颤动及心房扑动患者的血栓栓塞和出血风险及相应的变化趋势,并帮助改善抗凝药物的使用。但还需进一步优化评分流程,规范患者评估及治疗。

基于CNN和双向LSTM的房颤预测模型

现有基于CNN的模型无法提取患者数据中的时序特征,而基于RNN的模型忽略了各医学变量的差异性特征。针对这种情况,提出一种结合CNN和RNN的房颤预测模型,利用一个独立CNN模块捕获电子病历数据中各医学变量间的差异性特征,同时使用一个独立的RNN模块捕获电子病历数据中时序性特征以及各医学变量间的相关性特征。在真实医院数据集上的实验结果表明,与最新的一些基于电子病历数据的疾病预测方法相比,该模型在房颤的预测方面表现得更加突出,F1值提高了2.14%,AUC值提高了1.32%。

基于关联规则挖掘的健康信息学主题分析——以dHealth会议为例

本研究旨在析出当前健康信息学领域的研究主题和方向、研究热点和前沿问题,以2014—2020年共七年的dHealth会议文献作为研究对象,运用关联规则方法对会议文献的关键词进行分析,归纳总结出健康信息学的主要研究方向,并对相关主题的会议文献进行回溯介绍。分析结果表明,近年来dHealth会议文献在健康信息学领域有六个主要研究方向,包括标准与标准化研究、电子健康档案研究、互操作性研究、计算机技术与应用研究、移动医疗与远程医疗研究及临床信息学研究。研究结论有助于进一步明晰健康信息学的研究热点与主流话题,并探索未来发展的方向。

基于CTSA-Net的急性肾损伤风险预测研究

针对过去对急性肾损伤(acute kidney injury,AKI)患者的识别存在临床时间序列数据未被充分利用、提前预测窗口较短及缺少连续预测研究等不足,本研究提出了一种卷积神经网络和两阶段交叉注意力的混合网络模型(CTSA-Net),实现对1期及以上AKI的每小时连续预测。CTSA-Net的注意力支路、CNN支路及特征融合模块可增强对时间序列数据的全局表示以及局部细节的感知能力,从而提高对AKI的连续预测性能。在AKI发生时、发生前24、48及72 h四个预测时间点,模型预测AKI的受试者工作特征曲线下面积分别为0.946、0.907、0.895和0.879,准确率-召回率曲线下面积分别为0.979、0.960、0.949和0.939。实验结果表明,CTSA-Net模型在多个预测时间点进行AKI预测的性能较好,可用于患者的实时监测,辅助医生进行临床决策。