A review of PHR, EMR and EHR integration: A more personalized healthcare and public health policy

Keeping medical information safe and confidential: a qualitative study on perceptions of Israeli physicians

BACKGROUND

Patients expect their information to remain confidential, and physicians have a legal and ethical obligation to keep it this way. Confidentiality is not just a legal requirement but a crucial element in establishing trust between patients and healthcare providers. Patients must feel confident that their personal and medical information is kept confidential and shared only with those who need to know. Previous studies have primarily concentrated on patients' perceptions of medical confidentiality, data privacy, and data protection issues. However, research on the practical practices and perceptions of medical confidentiality among hospital physicians is scant, underscoring the need for a deeper understanding of this critical issue.

METHODS

Through qualitative methods and as part of a large-scale study on aspects of patient dignity and responsiveness in Israel, physicians shared their views and practices on managing medical information.

RESULTS

The study revealed the practical challenges physicians face in upholding various aspects of data protection within hospital settings. These challenges, strategies, and deviations from data protection principles that physicians discussed are of significant practical relevance. The importance of patient consent and the practical measures for safeguarding patient information were also highlighted. While physicians acknowledged the importance of protecting patient information, they also grappled with the realities of doing so in a complex healthcare environment. In future healthcare policies, it is critical to ensure robust measures are in place to safeguard and uphold medical confidentiality. These can include specific measures to increase compliance, such as regularly monitoring compliance with confidentiality policies, producing safe and anonymous channels to voice concerns, and enforcing consequences for any breaches to ensure accountability.

CONCLUSIONS

While protecting medical information has emerged as an important goal, it is equally crucial to strike a balance between the need to share information to advance and provide quality medical care. Physicians and policymakers must navigate this delicate balance. Additionally, organizations should strengthen compliance to enhance their monitoring and enforcement of confidentiality policies. Ineffective implementation of medical confidentiality leads to theoretical guidelines that do not translate effectively into practice.

Emergency Medical Access Control System Based on Public Blockchain

IT has made significant progress in various fields over the past few years, with many industries transitioning from paper-based to electronic media. However, sharing electronic medical records remains a long-term challenge, particularly when patients are in emergency situations, making it difficult to access and control their medical information. Previous studies have proposed permissioned blockchains with limited participants or mechanisms that allow emergency medical information sharing to pre-designated participants. However, permissioned blockchains require prior participation by medical institutions, and limiting sharing entities restricts the number of potential partners. This means that sharing medical information with local emergency doctors becomes impossible if a patient is unconscious and far away from home, such as when traveling abroad. To tackle this challenge, we propose an emergency access control system for a global electronic medical information system that can be shared using a public blockchain, allowing anyone to participate. Our proposed system assumes that the patient wears a pendant with tamper-proof and biometric authentication capabilities. In the event of unconsciousness, emergency doctors can perform biometrics on behalf of the patient, allowing the family doctor to share health records with the emergency doctor through a secure channel that uses the Diffie-Hellman (DH) key exchange protocol. The pendant's biometric authentication function prevents unauthorized use if it is stolen, and we have tested the blockchain's fee for using the public blockchain, demonstrating that the proposed system is practical.

A framework for understanding selection bias in real-world healthcare data

Using administrative patient-care data such as Electronic Health Records (EHR) and medical/pharmaceutical claims for population-based scientific research has become increasingly common. With vast sample sizes leading to very small standard errors, researchers need to pay more attention to potential biases in the estimates of association parameters of interest, specifically to biases that do not diminish with increasing sample size. Of these multiple sources of biases, in this paper, we focus on understanding selection bias. We present an analytic framework using directed acyclic graphs for guiding applied researchers to dissect how different sources of selection bias may affect estimates of the association between a binary outcome and an exposure (continuous or categorical) of interest. We consider four easy-to-implement weighting approaches to reduce selection bias with accompanying variance formulae. We demonstrate through a simulation study when they can rescue us in practice with analysis of real-world data. We compare these methods using a data example where our goal is to estimate the well-known association of cancer and biological sex, using EHR from a longitudinal biorepository at the University of Michigan Healthcare system. We provide annotated R codes to implement these weighted methods with associated inference.

Factors Influencing Data Quality in Electronic Health Record Systems in 50 Health Facilities in Rwanda and the Role of Clinical Alerts: Cross-Sectional Observational Study

BACKGROUND

Electronic health records (EHRs) play an increasingly important role in delivering HIV care in low- and middle-income countries. The data collected are used for direct clinical care, quality improvement, program monitoring, public health interventions, and research. Despite widespread EHR use for HIV care in African countries, challenges remain, especially in collecting high-quality data.

OBJECTIVE

We aimed to assess data completeness, accuracy, and timeliness compared to paper-based records, and factors influencing data quality in a large-scale EHR deployment in Rwanda.

METHODS

We randomly selected 50 health facilities (HFs) using OpenMRS, an EHR system that supports HIV care in Rwanda, and performed a data quality evaluation. All HFs were part of a larger randomized controlled trial, with 25 HFs receiving an enhanced EHR with clinical decision support systems. Trained data collectors visited the 50 HFs to collect 28 variables from the paper charts and the EHR system using the Open Data Kit app. We measured data completeness, timeliness, and the degree of matching of the data in paper and EHR records, and calculated concordance scores. Factors potentially affecting data quality were drawn from a previous survey of users in the 50 HFs.

RESULTS

We randomly selected 3467 patient records, reviewing both paper and EHR copies (194,152 total data items). Data completeness was >85% threshold for all data elements except viral load (VL) results, second-line, and third-line drug regimens. Matching scores for data values were close to or >85% threshold, except for dates, particularly for drug pickups and VL. The mean data concordance was 10.2 (SD 1.28) for 15 (68%) variables. HF and user factors (eg, years of EHR use, technology experience, EHR availability and uptime, and intervention status) were tested for correlation with data quality measures. EHR system availability and uptime was positively correlated with concordance, whereas users' experience with technology was negatively correlated with concordance. The alerts for missing VL results implemented at 11 intervention HFs showed clear evidence of improving timeliness and completeness of initially low matching of VL results in the EHRs and paper records (11.9%-26.7%; P<.001). Similar effects were seen on the completeness of the recording of medication pickups (18.7%-32.6%; P<.001).

CONCLUSIONS

The EHR records in the 50 HFs generally had high levels of completeness except for VL results. Matching results were close to or >85% threshold for nondate variables. Higher EHR stability and uptime, and alerts for entering VL both strongly improved data quality. Most data were considered fit for purpose, but more regular data quality assessments, training, and technical improvements in EHR forms, data reports, and alerts are recommended. The application of quality improvement techniques described in this study should benefit a wide range of HFs and data uses for clinical care, public health, and disease surveillance.

The Epidemic of Congenital Syphilis in the Indigenous and Rural Populations of South Dakota

From 2020 to 2023, South Dakota witnessed a substantial increase in cases of congenital syphilis (CS), with the highest rates identified in rural and Native American (NA) communities. Here, we discuss 3 severe cases of CS in premature infants born to NA individuals and communities in South Dakota with poor access to prenatal care. The infants in these 3 cases presented with varying clinical conditions, including respiratory failure, persistent pulmonary hypertension of the newborn, severe direct hyperbilirubinemia, feeding intolerance, and necrotizing enterocolitis. Lack of prenatal care and other systemic health disparities likely contributed to the increased disease burden. For NA communities, rurality, limited resources, systemic racism, historical trauma, and lack of trust in medical institutions likely contribute to inadequate prenatal care. All 3 of these cases also occurred in pregnant people with a present or history of substance use disorders, which may have led to further hesitancy to seek care because of fear of prosecution. To combat the rising number of syphilis and CS cases, we advocate for new and continued outreach that provides education about and testing for sexually transmitted diseases to NA and rural populations, increased care coordination, the integration of point-of-care testing and treatment strategies in lower resource centers, and legislative allocation of additional resources to engage pregnant people with or at risk for substance use disorders.

The role of information systems in emergency department decision-making-a literature review

OBJECTIVES

Healthcare providers employ heuristic and analytical decision-making to navigate the high-stakes environment of the emergency department (ED). Despite the increasing integration of information systems (ISs), research on their efficacy is conflicting. Drawing on related fields, we investigate how timing and mode of delivery influence IS effectiveness. Our objective is to reconcile previous contradictory findings, shedding light on optimal IS design in the ED.

MATERIALS AND METHODS

We conducted a systematic review following PRISMA across PubMed, Scopus, and Web of Science. We coded the ISs' timing as heuristic or analytical, their mode of delivery as active for automatic alerts and passive when requiring user-initiated information retrieval, and their effect on process, economic, and clinical outcomes.

RESULTS

Our analysis included 83 studies. During early heuristic decision-making, most active interventions were ineffective, while passive interventions generally improved outcomes. In the analytical phase, the effects were reversed. Passive interventions that facilitate information extraction consistently improved outcomes.

DISCUSSION

Our findings suggest that the effectiveness of active interventions negatively correlates with the amount of information received during delivery. During early heuristic decision-making, when information overload is high, physicians are unresponsive to alerts and proactively consult passive resources. In the later analytical phases, physicians show increased receptivity to alerts due to decreased diagnostic uncertainty and information quantity. Interventions that limit information lead to positive outcomes, supporting our interpretation.

CONCLUSION

We synthesize our findings into an integrated model that reveals the underlying reasons for conflicting findings from previous reviews and can guide practitioners in designing ISs in the ED.

Factors identified as barriers or facilitators to EMR/EHR based interprofessional primary care: a scoping review

As interprofessional collaboration (IPC) in primary care receives increasing attention, the role of electronic medical and health record (EMR/EHR) systems in supporting IPC is important to consider. A scoping review was conducted to synthesize the current literature on the barriers and facilitators of EMR/EHRs to interprofessional primary care. Four online databases (OVID Medline, EBSCO CINAHL, OVID EMBASE, and OVID PsycINFO) were searched without date restrictions. Twelve studies were included in the review. Of six facilitator and barrier themes identified, the key facilitator was teamwork support and a significant barrier was data management. Other important barriers included usability related mainly to interoperability, and practice support primarily in terms of patient care. Additional themes were organization attributes and user features. Although EMR/EHR systems facilitated teamwork support, there is potential for team features to be strengthened further. Persistent barriers may be partly addressed by advances in software design, particularly if interprofessional perspectives are included. Organizations and teams might also consider strategies for working with existing EMR/EHR systems, for instance by developing guidelines for interprofessional use. Further research concerning the use of electronic records in interprofessional contexts is needed to support IPC in primary care.

Searchable Blockchain-Based Healthcare Information Exchange System to Enhance Privacy Preserving and Data Usability

Ensuring the security and usability of electronic health records (EHRs) is important in health information exchange (HIE) systems that handle healthcare records. This study addressed the need to balance privacy preserving and data usability in blockchain-based HIE systems. We propose a searchable blockchain-based HIE system that enhances privacy preserving while improving data usability. The proposed methodology includes users collecting healthcare information (HI) from various Internet of Medical Things (IoMT) devices and compiling this information into EHR blocks for sharing on a blockchain network. This approach allows participants to search and utilize specific health data within the blockchain effectively. The results demonstrate that the proposed system mitigates the issues of traditional HIE systems by providing secure and user-friendly access to EHRs. The proposed searchable blockchain-based HIE system resolves the trade-off dilemma in HIE by achieving a balance between security and the data usability of EHRs.

An empirical investigation into the preferences of the elderly for user interface design in personal electronic health record systems

Background

With the continuous advancement of digital technologies, electronic Personal Health Records (ePHR) offer end-users greater control and convenience over their health data. Although ePHR are perceived as innovative tools in medical services that provide patient-centered care and disease prevention, many system interfaces are inclined toward younger users, overlooking investigations pertinent to elderly users. Our objective is to uncover the preferences of the elderly for an ideal ePHR system interface.

Materials and methods

Relying on a literature review, we identified six interface attributes. Utilizing conjoint analysis, we constructed 16 representative design scenarios based on orthogonal design by combining different attribute levels. We invited 187 elderly participants to evaluate these scenarios. Data analysis was performed using SPSS 26.0. The results indicate that among the ePHR interface design attributes, the elderly prioritize color attributes, followed by the notification method. Designs with contrasting color schemes, skeuomorphic design approaches, and icon-centric menu navigation with segmented layouts, and voice notifications when a message is received, are the most preferred interface design choices.

Discussion

This research elucidates the ideal interface design elements for ePHR as perceived by the elderly, offering valuable references for age-friendly design considerations in ePHR systems.

Results

Implementing these insights can aid in promoting mobile health services among the elderly demographic, enhancing their user experience in health management interfaces. This, in turn, fosters the widespread adoption of mobile health service technologies, further advancing the development of a healthy aging society.

Analysis of Publications on Health Information Management Using the Science Mapping Method: A Holistic Perspective

OBJECTIVE

In the age of digital transformation, there is a need for a sustainable information management vision in health. Understanding the accumulation of health information management (HIM) knowledge from the past to the present and building a new vision to meet this need reveals the importance of understanding the available scientific knowledge. With this research, it is aimed to examine the scientific documents of the last 40 years of HIM literature with a holistic approach using science mapping techniques and to guide future research.

METHODS

This study used a bibliometric analysis method for science mapping. Co-citation and co-occurrence document analyses were performed on 630 academic publications selected from the Web of Science core collection (WoSCC) database using the keyword "Health Information Management" and inclusion criteria. The analyses were performed using the R-based software Bibliometrix (Version 4.0; K-Synth Srl), Python (Version 3.12.1; The Python Software Foundation), and Microsoft® Excel® 2016.

RESULTS

Co-occurrence analyses revealed the themes of personal health records, clinical coding and data quality, and health information management. The HIM theme consisted of five subthemes: "electronic records", "medical informatics", "e-health and telemedicine", "health education and awareness", and "health information systems (HISs)". As a result of the co-citation analysis, the prominent themes were technology acceptance, standardized clinical coding, the success of HISs, types of electronic records, people with HIM, health informatics used by consumers, e-health, e-mobile health technologies, and countries' frameworks and standards for HISs.

CONCLUSIONS

This comprehensive bibliometric study shows that structured information can be helpful in understanding research trends in HIM. This study identified critical issues in HIM, identified meaningful themes, and explained the topic from a holistic perspective for all health system actors and stakeholders who want to work in the field of HIM.

Iraqi Population Trusts in Electronic Healthcare Records: A Cross-sectional Study

This study investigated the perceptions of Iraqi patients regarding Electronic Healthcare Records (EHRs) in terms of trust and propensity to share and exchange medical and personal information and data within the healthcare ecosystem. During the period of April to June 2022, a researcher-assisted questionnaire was disseminated to adult Iraqi patients attending public or private healthcare facilities in a subset of Iraqi governorates. Data collection was followed by descriptive and inferential analyses. In total, 552 respondents filled out the questionnaire. The findings revealed that 71.6% of respondents were conversant with EHRs and trusted them as data collection and storage systems. In addition, 10% of respondents did not want their EHRs to be shared between healthcare professionals and institutions. However, only 3.6% of participants were willing to share all of their personal information with healthcare professionals. Female respondents were considerably more willing to share their full names with healthcare professionals than male respondents, despite the society's reputation for conservatism. The findings of this study highlighted the necessity of tailoring initiatives to enhance patients' trust in EHRs and their interactions with healthcare professionals other than medical physicians.

Architectural design of national evidence based medicine information system based on electronic health record

BACKGROUND

The global implementation of Electronic Health Records has significantly enhanced the quality of medical care and the overall delivery of public health services. The incorporation of Evidence-Based Medicine offers numerous benefits and enhances the efficacy of decision-making in areas such as prevention, prognosis, diagnosis, and therapeutic approaches.

OBJECTIVE

The objective of this paper is to propose an architectural design of an Evidence-Based Medicine information system based on the Electronic Health Record, taking into account the existing and future level of interoperability of health information systems in Greece.

METHODS

A study of the suggested evidence-based medicine architectures found in the existing literature was conducted. Moreover, the interoperability architecture of health information systems in Greece was analyzed. The architecture design reviewed by specialized personnel and their recommendations were incorporated into the final design of the proposed architecture.

RESULTS

The proposed integrated architecture of an Evidence-Based Medicine system based on the Electronic Health Record integrates and utilizes citizens' health data while leveraging the existing knowledge available in the literature.

CONCLUSIONS

Taking into consideration the recently established National Interoperability Framework, which aligns with the European Interoperability Framework, the proposed realistic architectural approach contributes to improving the quality of healthcare provided through the ability to make safe, timely and accurate decisions by physicians.

Use of Epic Electronic Health Record System for Health Care Research: Scoping Review

BACKGROUND

Electronic health records (EHRs) enable health data exchange across interconnected systems from varied settings. Epic is among the 5 leading EHR providers and is the most adopted EHR system across the globe. Despite its global reach, there is a gap in the literature detailing how EHR systems such as Epic have been used for health care research.

OBJECTIVE

The objective of this scoping review is to synthesize the available literature on use cases of the Epic EHR for research in various areas of clinical and health sciences.

METHODS

We used established scoping review methods and searched 9 major information repositories, including databases and gray literature sources. To categorize the research data, we developed detailed criteria for 5 major research domains to present the results.

RESULTS

We present a comprehensive picture of the method types in 5 research domains. A total of 4669 articles were screened by 2 independent reviewers at each stage, while 206 articles were abstracted. Most studies were from the United States, with a sharp increase in volume from the year 2015 onwards. Most articles focused on clinical care, health services research and clinical decision support. Among research designs, most studies used longitudinal designs, followed by interventional studies implemented at single sites in adult populations. Important facilitators and barriers to the use of Epic and EHRs in general were identified. Important lessons to the use of Epic and other EHRs for research purposes were also synthesized.

CONCLUSIONS

The Epic EHR provides a wide variety of functions that are helpful toward research in several domains, including clinical and population health, quality improvement, and the development of clinical decision support tools. As Epic is reported to be the most globally adopted EHR, researchers can take advantage of its various system features, including pooled data, integration of modules and developing decision support tools. Such research opportunities afforded by the system can contribute to improving quality of care, building health system efficiencies, and conducting population-level studies. Although this review is limited to the Epic EHR system, the larger lessons are generalizable to other EHRs.

Relative bed allocation for COVID-19 patients, EHR investments, and COVID-19 mortality outcomes

Managing flexibility in the relative bed allocation for COVID-19 and non-COVID-19 patients was a key challenge for hospitals during the COVID-19 pandemic. Based on organizational information processing theory (OIPT), we propose that the local electronic health record (EHR) systems could improve patient outcomes through improved bed allocation in the local area. In an empirical analysis of county-level weekly hospital data in the US, relative capacity of beds in hospitals with higher EHR was associated with lower 7-, 14-, and 21-day forward-looking COVID-19 death rate at the county-level. Testing for cross-state variation in non-pharmaceutical interventions along contiguous county border-pair analysis to control for spatial correlation varying between state variations in non-pharmaceutical intervention policies, 2SLS analysis using quality ratings, and using foot-traffic data at the US hospitals our findings are generally supported. The findings have implications for policymakers and stakeholders of the local healthcare supply chains and EHR systems.

End-users' perspectives on factors affecting implementation and utilization of the Iranian electronic health record system: a qualitative study in a developing country

BACKGROUND

As one of the most important information technologies for storing, managing, and exchanging health information, the electronic health record (EHR) plays a major role in the health system. However, these systems in developing countries have been associated with multidimensional issues. The purpose of the present study was the assessment of nonclinical end-users' points of view on the implementation and utilization of the Iranian electronic health record system.

METHODS

This was a large qualitative study conducted in 2021 for 7 months from February to August. In this study, data were collected through in-depth semi-structured interviews with 70 non-clinical end-users in 22 public and six private hospitals of West Azerbaijan province in Iran. To analyze the data, the thematic analysis method was used.

RESULTS

The study results indicated that technical, human, cultural, managerial, and financial readiness are the most important factors affecting the implementation of EHRs in Iran. Among the mentioned factors, technical and human readiness were emphasized more by the users. Also, technical, organizational, human, and managerial factors were identified as factors influencing EHRs utilization, and technical and organizational factors had a stronger role in the system utilization.

CONCLUSIONS

According to the results, several factors influence EHR implementation and adequate utilization in Iran. To achieve the predetermined goals of this system, implementation issues and problems of using the system should be considered and solved.

Clinical named entity recognition and relation extraction using natural language processing of medical free text: A systematic review

BACKGROUND

Natural Language Processing (NLP) applications have developed over the past years in various fields including its application to clinical free text for named entity recognition and relation extraction. However, there has been rapid developments the last few years that there's currently no overview of it. Moreover, it is unclear how these models and tools have been translated into clinical practice. We aim to synthesize and review these developments.

METHODS

We reviewed literature from 2010 to date, searching PubMed, Scopus, the Association of Computational Linguistics (ACL), and Association of Computer Machinery (ACM) libraries for studies of NLP systems performing general-purpose (i.e., not disease- or treatment-specific) information extraction and relation extraction tasks in unstructured clinical text (e.g., discharge summaries).

RESULTS

We included in the review 94 studies with 30 studies published in the last three years. Machine learning methods were used in 68 studies, rule-based in 5 studies, and both in 22 studies. 63 studies focused on Named Entity Recognition, 13 on Relation Extraction and 18 performed both. The most frequently extracted entities were "problem", "test" and "treatment". 72 studies used public datasets and 22 studies used proprietary datasets alone. Only 14 studies defined clearly a clinical or information task to be addressed by the system and just three studies reported its use outside the experimental setting. Only 7 studies shared a pre-trained model and only 8 an available software tool.

DISCUSSION

Machine learning-based methods have dominated the NLP field on information extraction tasks. More recently, Transformer-based language models are taking the lead and showing the strongest performance. However, these developments are mostly based on a few datasets and generic annotations, with very few real-world use cases. This may raise questions about the generalizability of findings, translation into practice and highlights the need for robust clinical evaluation.

Personal Health Record (PHR) Experience and Recommendations for a Transformation in Saudi Arabia

A Personal Health Record (PHR) is a patient-managed platform for health data. Most hospitals provide a PHR as an extension of the Electronic Medical Record (EMR). However, there are unresolved issues around the adoption rate, functionalities, barriers and, more importantly, the impact of the PHR on patients' health. A cross-sectional, survey-based descriptive study was conducted in which patients from four main tertiary hospitals in Saudi Arabia were targeted from September 2022 to February 2023. The survey was tested and validated to address the objectives of the study. The survey covered components related to intention to use the PHR, required functions, obstacles and expected outcomes. This study involved 396 participants from the top four hospitals. It was discovered that the majority of them had intentions to use the PHR (93%) and believed it to be useful (94%) and easy to use (94%). It was widely agreed that accessing medical records (77%), scheduling appointments (88%), renewing medication (90%), tracking patient data (70%) and receiving personalized education (78%) were essential aspects of the PHR. Furthermore, the survey revealed that 54% of respondents saw a positive effect on their health status. A significant number of participants, around 54%, expressed concerns about the privacy of their PHR, and 46% reported concerns about the accuracy of their information. The study found that demographic factors and the type of hospital did not have a statistically significant association with the intention to use the PHR. Our findings showed that there were no significant barriers to adopting the PHR. Additionally, we found that less than half of the participants believed that their current PHR helped them to improve their health. This highlights the need for healthcare organizations to focus on improving the PHR's functionality and overall purpose. Instead of simply providing basic features, the PHR should allow patients to manage their health information comprehensively, including compiling information from hospitals and patient-generated data. Having a PHR is crucial in improving an individual's overall health. As technology advances, more data are being generated that should be included in the PHR to ensure an accurate and comprehensive view of the patient's health. Expanding the scope of the PHR to include capabilities beyond merely hospital data is important. Achieving this requires an open and honest discussion about the role of the PHR, potential obstacles and how to coordinate efforts among different stakeholders.

Integrated Personal Health Record in Indonesia: Design Science Research Study

BACKGROUND

Personal health records (PHRs) are consumer-centric tools designed to facilitate the tracking, management, and sharing of personal health information. PHR research has mainly been conducted in high-income countries rather than in low- and middle-income countries. Moreover, previous studies that proposed PHR design in low- and middle-income countries did not describe integration with other systems, or there was no stakeholder involvement in exploring PHR requirements.

OBJECTIVE

This study developed an integrated PHR architecture and prototype in Indonesia using design science research. We conducted the research in Indonesia, a low- to middle-income country with the largest population in Southeast Asia and a tiered health system.

METHODS

This study followed the design science research guidelines. The requirements were identified through interviews with 37 respondents from health organizations and a questionnaire with 1012 patients. Afterward, the proposed architecture and prototype were evaluated via interviews with 6 IT or eHealth experts.

RESULTS

The architecture design refers to The Open Group Architecture Framework version 9.2 and comprises 5 components: architecture vision, business architecture, application architecture, data architecture, and technology architecture. We developed a high-fidelity prototype for patients and physicians. In the evaluation, improvements were made to add the stakeholders and the required functionality to the PHR and add the necessary information to the functions that were developed in the prototype.

CONCLUSIONS

We used design science to illustrate PHR integration in Indonesia, which involves related stakeholders in requirement gathering and evaluation. We developed architecture and application prototypes based on health systems in Indonesia, which comprise routine health services, including disease treatment and health examinations, as well as promotive and preventive health efforts.

Automatic documentation of professional health interactions: A systematic review

Electronic systems are increasingly present in the healthcare system and are often related to improved medical care. However, the widespread use of these technologies ended up building a relationship of dependence that can disrupt the doctor-patient relationship. In this context, digital scribes are automated clinical documentation systems that capture the physician-patient conversation and then generate the documentation for the appointment, enabling the physician to engage with the patient entirely. We have performed a systematic literature review on intelligent solutions for automatic speech recognition (ASR) with automatic documentation during a medical interview. The scope included only original research on systems that could detect speech and transcribe it in a natural and structured fashion simultaneously with the doctor-patient interaction, excluding speech-to-text-only technologies. The search resulted in a total of 1995 titles, with eight articles remaining after filtering for the inclusion and exclusion criteria. The intelligent models mainly consisted of an ASR system with natural language processing capability, a medical lexicon, and structured text output. None of the articles had a commercially available product at the time of the publication and reported limited real-life experience. So far, none of the applications has been prospectively validated and tested in large-scale clinical studies. Nonetheless, these first reports suggest that automatic speech recognition may be a valuable tool in the future to facilitate medical registration in a faster and more reliable manner. Improving transparency, accuracy, and empathy could drastically change how patients and doctors experience a medical visit. Unfortunately, clinical data on the usability and benefits of such applications is almost non-existent. We believe that future work in this area is necessary and needed.

Synergistic Effect of Medical Information Systems Integration: To What Extent Will It Affect the Accuracy Level in the Reports and Decision-Making Systems?

Nowadays, according to the intention of many hospitals and medical centers to computerize their processes and medical treatments, including data forms and medical images, which are generating a considerable amount of data, IT specialists and data scientists who are oriented to eHealth and related issues know the importance of data integration and its benefits. This study indicates the significance of data integration, especially in medical information systems. It means that the medical subsystems in the HIS (hospital information system) must be integrated, and it is also necessary to unify with the MIS (management information system). In this paper, the accuracy level of the extracted reports from the information system (to evaluate the staff’s performance) will be measured in two ways: (1) At first, the performance of the clinic reception staff will be evaluated. In this way, the personnel attendance system is an independent and separate software, and the mentioned evaluation has been performed by its report. (2) The following year, in the same location, the same evaluation has been performed based on the data extracted from the personnel attendance subsystem, which has been added to the medical information system as an integrated information system. After comparing the accuracy level of both ways, this paper concludes that when the personnel attendance subsystem as a part of the MIS has been unified with the HIS, the reports and, consequently, management decisions will be more accurate; therefore, the managers and decision-makers will perceive the importance of data integration more than in the past.

A privacy-preserving and computation-efficient federated algorithm for generalized linear mixed models to analyze correlated electronic health records data

Large collaborative research networks provide opportunities to jointly analyze multicenter electronic health record (EHR) data, which can improve the sample size, diversity of the study population, and generalizability of the results. However, there are challenges to analyzing multicenter EHR data including privacy protection, large-scale computation resource requirements, heterogeneity across sites, and correlated observations. In this paper, we propose a federated algorithm for generalized linear mixed models (Fed-GLMM), which can flexibly model multicenter longitudinal or correlated data while accounting for site-level heterogeneity. Fed-GLMM can be applied to both federated and centralized research networks to enable privacy-preserving data integration and improve computational efficiency. By communicating a limited amount of summary statistics, Fed-GLMM can achieve nearly identical results as the gold-standard method where the GLMM is directly fitted to the pooled dataset. We demonstrate the performance of Fed-GLMM in numerical experiments and an application to longitudinal EHR data from multiple healthcare facilities.

Strengthening the evidence base for mHealth in clinical practice: Conducting research with standalone or interoperable systems - a viewpoint

Objective

The aim of this viewpoint is to inform mobile health (mHealth) evidence development in using standalone or interoperable systems in hospital practice.

Methods

There is a gap between mHealth research and its widespread uptake in clinical practice. Evidence generation is not keeping up with the introduction and implementation of technologies. This is partly a consequence of the technology characteristics and the way research is conducted in a clinical setting. Research and development of mHealth technology can be conducted standalone in a laboratory like setting, standalone in a clinical setting or interoperable with already existing technology in hospital practice.

Results

Standalone systems operate relatively independent from an organizations' existing infrastructure. Using laboratory settings does not reflect the complexity of real-life, but in clinical practice this may be suitable for research assessing usability, feasibility or even clinical and process outcomes at a small scale. Realizing research and development on interoperable mHealth technology solutions, especially with operational EMR systems, is a challenging, time- and resource intensive process and requires large(r) investments, as it is often complicated by a myriad of interfering factors. Interoperable systems are however a more sustainable option in the long run, and generated evidence reflects the real hospital care setting and this option may therefore facilitate dissemination. Choosing either a standalone or interoperable setting affects the research design, the implementation pace and ultimately widespread adoption of the mHealth technology.

Conclusion

We recommend to include these technology characteristics in implementation frameworks and think of evaluation research designs in an early phase.

The Role of Access Type and Age Group in the Breadth of Use of Patient Portals: Observational Study

BACKGROUND

Health care delivery and patient satisfaction are improved when patients engage with their medical information through patient portals. Despite their wide availability and multiple functionalities, patient portals and their functionalities are still underused.

OBJECTIVE

We seek to understand factors that lead to patient engagement through multiple portal functionalities. We provide recommendations that could lead to higher patients' usage of their portals.

METHODS

Using data from the Health Information National Trends Survey 5, Cycle 3 (N=2093), we performed descriptive statistics and used a chi-square test to analyze the association between the demographic variables and the use of mobile health apps for accessing medical records. We further fitted a generalized linear model to examine the association between access type and the use of portal functionalities. We further examined the moderation effects of age groups on the impact of access type on portal usage.

RESULTS

Our results show that accessing personal health records using a mobile health app is positively associated with greater patient usage of access capabilities (β=.52; P<.001), patient-provider interaction capabilities (β=.24, P=.006), and patient-personal health information interaction capabilities (β=.23, P=.009). Patients are more likely to interact with their records and their providers when accessing their electronic medical records using a mobile health app. The impacts of mobile health app usage fade with age for tasks consisting of viewing, downloading, and transmitting medical results to a third party (β=-.43, P=.005), but not for those involving patient-provider interaction (β=.05, P=.76) or patient-personal health information interaction (β=-.15, P=.19).

CONCLUSIONS

These findings provide insights on how to increase engagement with diverse portal functionalities for different age groups and thus improve health care delivery and patient satisfaction.

Decentralized Patient-Centric Report and Medical Image Management System Based on Blockchain Technology and the Inter-Planetary File System

Several academicians have been actively contributing to establishing a practical solution to storing and distributing medical images and test reports in the research domain of health care in recent years. Current procedures mainly rely on cloud-assisted centralized data centers, which raise maintenance expenditure, necessitate a large amount of storage space, and raise privacy concerns when exchanging data across a network. As a result, it is critically essential to provide a framework that allows for the efficient exchange and storage of large amounts of medical data in a secure setting. In this research, we describe a unique proof-of-concept architecture for a distributed patient-centric test report and image management (PCRIM) system that aims to facilitate patient privacy and control without the need for a centralized infrastructure. We used an Ethereum blockchain and a distributed file system technology called the Inter-Planetary File System in this system (IPFS). Then, to secure a distributed and trustworthy access control policy, we designed an Ethereum smart contract termed the patient-centric access control protocol. The IPFS allows for the decentralized storage of medical metadata, such as images, with worldwide accessibility. We demonstrate how the PCRIM system design enables hospitals, patients, and image requestors to obtain patient-centric data in a distributed and secure manner. Finally, we tested the proposed framework in the Windows environment by deploying a smart contract prototype on an Ethereum TESTNET blockchain. The findings of the study indicate that the proposed strategy is both efficient and practicable.

A survey of data element perspective: Application of artificial intelligence in health big data

Artificial intelligence (AI) based on the perspective of data elements is widely used in the healthcare informatics domain. Large amounts of clinical data from electronic medical records (EMRs), electronic health records (EHRs), and electroencephalography records (EEGs) have been generated and collected at an unprecedented speed and scale. For instance, the new generation of wearable technologies enables easy-collecting peoples’ daily health data such as blood pressure, blood glucose, and physiological data, as well as the application of EHRs documenting large amounts of patient data. The cost of acquiring and processing health big data is expected to reduce dramatically with the help of AI technologies and open-source big data platforms such as Hadoop and Spark. The application of AI technologies in health big data presents new opportunities to discover the relationship among living habits, sports, inheritances, diseases, symptoms, and drugs. Meanwhile, with the development of fast-growing AI technologies, many promising methodologies are proposed in the healthcare field recently. In this paper, we review and discuss the application of machine learning (ML) methods in health big data in two major aspects: (1) Special features of health big data including multimodal, incompletion, time validation, redundancy, and privacy. (2) ML methodologies in the healthcare field including classification, regression, clustering, and association. Furthermore, we review the recent progress and breakthroughs of automatic diagnosis in health big data and summarize the challenges, gaps, and opportunities to improve and advance automatic diagnosis in the health big data field.

Security research of blockchain technology in electronic medical records

BACKGROUND

A blockchain-based Electronic Health Record(EHR) data-sharing scheme was proposed to solve the problems of data sharing difficulties and privacy disclosure.

METHODS

This paper designs a blockchain-based electronic health record model based on the characteristics of blockchain antitampering, decentralization, and distributed storage. Utilize blockchain network and distributed database to store encryption-related access control policies to prevent EHR data from being tampered with and leaked. Data security sharing protocol combines Distributed Key Generation (DKG) and reencryption.

RESULTS

The protocol used the Delegated Proof of Stake(DPOS) algorithm to select the proxy node, which reencrypted the EHR to share data between a pair of users. Simulation experiments and comparative analysis showed that DPOS efficiency was higher than Proof of Work (POW) and slightly lower than the Practical Byzantine Fault Tolerance(PBFT).

CONCLUSIONS

The scheme proposed in this paper is more decentralized and less computationally intensive.

Measuring the impact of anonymization on real-world consolidated health datasets engineered for secondary research use: Experiments in the context of MODELHealth project

Introduction

Electronic Health Records (EHRs) are essential data structures, enabling the sharing of valuable medical care information for a diverse patient population and being reused as input to predictive models for clinical research. However, issues such as the heterogeneity of EHR data and the potential compromisation of patient privacy inhibit the secondary use of EHR data in clinical research.

Objectives

This study aims to present the main elements of the MODELHealth project implementation and the evaluation method that was followed to assess the efficiency of its mechanism.

Methods

The MODELHealth project was implemented as an Extract-Transform-Load system that collects data from the hospital databases, performs harmonization to the HL7 FHIR standard and anonymization using the k-anonymity method, before loading the transformed data to a central repository. The integrity of the anonymization process was validated by developing a database query tool. The information loss occurring due to the anonymization was estimated with the metrics of generalized information loss, discernibility and average equivalence class size for various values of k.

Results

The average values of generalized information loss, discernibility and average equivalence class size obtained across all tested datasets and k values were 0.008473 ± 0.006216252886, 115,145,464.3 ± 79,724,196.11 and 12.1346 ± 6.76096647, correspondingly. The values of those metrics appear correlated with factors such as the k value and the dataset characteristics, as expected.

Conclusion

The experimental results of the study demonstrate that it is feasible to perform effective harmonization and anonymization on EHR data while preserving essential patient information.

Specified keywords search scheme for EHR sharing

Searchable encryption allows data users to search for encrypted files by keywords without restriction. However, electronic health record (EHR) contains sensitive information, and data users should search for and share EHR with restriction. If data users are not restricted when EHR is searched and shared, there is a high risk that EHR will be misused and reveal large amounts of private patient information. This paper proposes a specified keywords search scheme for EHR sharing based on searchable encryption and proxy re-encryption to address this problem. In the scheme, the data user searches with the keywords specified by the doctor and obtains EHR from the medical cloud. Proxy re-encryption is used to implement the sharing of EHR and privacy preservation securely. The security proof demonstrates that our scheme is secure against chosen keyword attack. Furthermore, the experimental results show that the scheme achieves computational efficiency

Facilitating clinical research through automation: Combining optical character recognition with natural language processing

BACKGROUND/AIMS

Performance status is crucial for most clinical research, as an eligibility criterion, a comorbidity covariate, or a trial endpoint. Yet information on performance status often is embedded as free text within a patient's electronic medical record, rather than coded directly, thereby making this concept extremely difficult to extract for research. Furthermore, performance status information frequently resides in outside reports, which are scanned into the electronic medical record along with thousands of clinic notes. The image format of scanned documents also is a major obstacle to the search and retrieval of information, as natural language processing cannot be applied to unstructured text within an image. We, therefore, utilized optical character recognition software to convert images to a searchable format, allowing the application of natural language processing to identify pertinent performance status data elements within scanned electronic medical records.

METHODS

Our study cohort consisted of 189 subjects diagnosed with diffuse large B-cell lymphoma for whom performance status was a required data element for analysis of prognostic factors related to recurrence and survival. Manual abstraction of performance status was previously conducted by a clinical Subject Matter Expert, serving as the gold standard. Leveraging our data warehouse, we extracted relevant scanned electronic medical record documents and applied optical character recognition to these images using the ABBYY FineReader software. The Linguamatics i2e natural language processing software was then used to run queries for performance status against the corpus of electronic medical record documents. We evaluated our optical character recognition/natural language processing pipeline for accuracy and reduction in data extraction effort.

RESULTS

We found that there was high accuracy and reduced time for extraction of performance status data by applying our optical character recognition/natural language processing pipeline. The transformed scanned documents from a random sample of patients yielded excellent precision, recall, and F score, with <1% incorrect results. Time savings from a second cohort showed that median time to review documents for patients with performance status data present was reduced by a third. The major time savings was in the review of those documents that in fact did not contain performance status information: median of 18 minutes versus 108 minutes for manual review, an 83% reduction in data abstraction effort.

CONCLUSION

By applying this optical character recognition/natural language processing pipeline, we achieved significant operational improvement and reduced time for information retrieval to support clinical research. Our study demonstrated that optical character recognition software provides an effective mechanism to transform scanned electronic medical record images to allow the application of natural language processing, yielding highly accurate data abstraction. We conclude that our optical character recognition/natural language processing pipeline can greatly facilitate research data abstraction by providing a highly focused data review, eliminating unnecessary manual review of the entire chart, and thus freeing time for abstracting other data elements requiring more human interpretation.

HL7 FHIR with SNOMED-CT to Achieve Semantic and Structural Interoperability in Personal Health Data: A Proof-of-Concept Study

Heterogeneity is a problem in storing and exchanging data in a digital health information system (HIS) following semantic and structural integrity. The existing literature shows different methods to overcome this problem. Fast healthcare interoperable resources (FHIR) as a structural standard may explain other information models, (e.g., personal, physiological, and behavioral data from heterogeneous sources, such as activity sensors, questionnaires, and interviews) with semantic vocabularies, (e.g., Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT)) to connect personal health data to an electronic health record (EHR). We design and develop an intuitive health coaching (eCoach) smartphone application to prove the concept. We combine HL7 FHIR and SNOMED-CT vocabularies to exchange personal health data in JavaScript object notion (JSON). This study explores and analyzes our attempt to design and implement a structurally and logically compatible tethered personal health record (PHR) that allows bidirectional communication with an EHR. Our eCoach prototype implements most PHR-S FM functions as an interoperability quality standard. Its end-to-end (E2E) data are protected with a TSD (Services for Sensitive Data) security mechanism. We achieve 0% data loss and 0% unreliable performances during data transfer between PHR and EHR. Furthermore, this experimental study shows the effectiveness of FHIR modular resources toward flexible management of data components in the PHR (eCoach) prototype.

Changes in patient portal adoption due to the emergence of COVID-19 pandemic

Even though patient portals are recognized as a promising mechanism to support greater patient engagement, questions remain about access and utilization. This study aims to identify factors related to portal adoption in 2019 and 2020 (before and during the COVID-19). Cross-sectional data from the Health Information National Trends Survey (HINTS) cycles- 2019 HINTS 5 cycle 3 (N = 5,438) and 2020 HINTS 5 cycle 4 (N = 3,865) were analyzed using STATA-SE version 17 to factors predicting portal adoption. Next, HINTS 5 cycles 3 and 4 were pooled to identify changes in portal feature use and ease of usage among portal users, and barrier to portal use among non-users. Respondents who were college graduates, high income, and married were more likely to adopt patient portals during 2019 and 2020. Aged 75+ and Hispanic respondents reported less frequency of portal access in 2020 versus 2019. Men were more likely to adopt patient portals in 2019 versus women in 2020. Portal users were more likely to use the portal-system features in 2019 versus 2020. Portal non-users reported having multiple-health records as less of a barrier in 2020 compared to 2019. Patient engagement needs heightened attention during the COVID-19 pandemic.

Investigating the Impact of Outsourcing on IT Flexibility

Modern healthcare organizations try to leverage their IT infrastructures to enhance the efficiency of processes and the quality of patient services. The flexibility of the IT infrastructure is a critical factor in the process of establishing strategic and operational value. The authors examine how applied principles of Conceptual Independence (CI) in information systems (IS) influence the flexibility of IT infrastructures. Furthermore, it is presumed that IT outsourcing plays a role in IT flexibility. The second question asks whether IT outsourcing configurations change when CI has been applied or not. Quantitative and qualitative data have been collected in 9 mental healthcare organizations. Findings – based on integration of the data with a mixed-method approach - suggest that the healthcare organizations that apply the principles of CI are better equipped to adapt their IT infrastructure to changing demands, requests and needs. Likewise, results suggest that they have changed the government of IT outsourcing thereby increasing IT flexibility even further.

Privacy Preservation in Patient Information Exchange Systems Based on Blockchain: System Design Study

Background

With the increasing sophistication of the medical industry, various advanced medical services such as medical artificial intelligence, telemedicine, and personalized health care services have emerged. The demand for medical data is also rapidly increasing today because advanced medical services use medical data such as user data and electronic medical records (EMRs) to provide services. As a result, health care institutions and medical practitioners are researching various mechanisms and tools to feed medical data into their systems seamlessly. However, medical data contain sensitive personal information of patients. Therefore, ensuring security while meeting the demand for medical data is a very important problem in the information age for which a solution is required.

Objective

Our goal is to design a blockchain-based decentralized patient information exchange (PIE) system that can safely and efficiently share EMRs. The proposed system preserves patients’ privacy in the EMRs through a medical information exchange process that includes data encryption and access control.

Methods

We propose a blockchain-based EMR-sharing system that allows patients to manage their EMRs scattered across multiple hospitals and share them with other users. Our PIE system protects the patient’s EMR from security threats such as counterfeiting and privacy attacks during data sharing. In addition, it provides scalability by using distributed data-sharing methods to quickly share an EMR, regardless of its size or type. We implemented simulation models using Hyperledger Fabric, an open source blockchain framework.

Results

We performed a simulation of the EMR-sharing process and compared it with previous works on blockchain-based medical systems to check the proposed system’s performance. During the simulation, we found that it takes an average of 0.01014 (SD 0.0028) seconds to download 1 MB of EMR in our proposed PIE system. Moreover, it has been confirmed that data can be freely shared with other users regardless of the size or format of the data to be transmitted through the distributed data-sharing technique using the InterPlanetary File System. We conducted a security analysis to check whether the proposed security mechanism can effectively protect users of the EMR-sharing system from security threats such as data forgery or unauthorized access, and we found that the distributed ledger structure and re-encryption–based data encryption method can effectively protect users’ EMRs from forgery and privacy leak threats and provide data integrity.

Conclusions

Blockchain is a distributed ledger technology that provides data integrity to enable patient-centered health information exchange and access control. PIE systems integrate and manage fragmented patient EMRs through blockchain and protect users from security threats during the data exchange process among users. To increase safety and efficiency in the EMR-sharing process, we used access control using security levels, data encryption based on re-encryption, and a distributed data-sharing scheme.

Hyperledger Healthchain: Patient-Centric IPFS-Based Storage of Health Records

Blockchain-based electronic health system growth is hindered by privacy, confidentiality, and security. By protecting against them, this research aims to develop cybersecurity measurement approaches to ensure the security and privacy of patient information using blockchain technology in healthcare. Blockchains need huge resources to store big data. This paper presents an innovative solution, namely patient-centric healthcare data management (PCHDM). It comprises the following: (i) in an on-chain health record database, hashes of health records are stored as health record chains in Hyperledger fabric, and (ii) off-chain solutions that encrypt actual health data and store it securely over the interplanetary file system (IPFS) which is the decentralized cloud storage system that ensures scalability, confidentiality, and resolves the problem of blockchain data storage. A security smart contract hosted through container technology with Byzantine Fault Tolerance consensus ensures patient privacy by verifying patient preferences before sharing health records. The Distributed Ledger technology performance is tested under hyper ledger caliper benchmarks in terms of transaction latency, resource utilization, and transaction per second. The model provides stakeholders with increased confidence in collaborating and sharing their health records.

Nurses’ Views on the Use, Quality, and Satisfaction with Electronic Medical Record in the Outpatient Department at a Tertiary Hospital

Background:

Many nurses perceive that the Electronic Medical Record (EMR) reduces the workload, improves the quality of documentation, and improves safety and patient care. However, other nurses reported that the system and environment of healthcare might impede EMR documentation at the bedside.

Objective:

The study aimed to describe the nurses' views of the use, quality, and satisfaction with EMR in daily practice in outpatient settings. Furthermore, the relationships among the use, quality, and user’s satisfaction of EMR were assessed in the study.

Methods:

The proposed study employed a cross-sectional, descriptive correlational design. Inclusion criteria were nurses willing to participate in the study, fluent in the English language, and have been working in the Outpatient Department for more than three months until the time of study implementation. A self-reported questionnaire with strong validity and reliability was used to assess nurses’ views of use, quality and satisfaction of EMR.

Results:

The response rate was 77.2% (170 out of 220), 91.2% of the participants were females. Results about the use of EMR have shown positive views ranging from 51.2% to 84.7%, with the lowest scores reported when to write nurse care worksheets (Kardex). For the quality of EMR, the results have shown positive views ranging from 70% to 87.6% with the lowest scores reported related to the EMR system problems and crashes, and for the user’s satisfaction, the results have shown positive views ranging from 76.5% to 87.1%. There were significant positive correlations between the three elements use, quality, and user’s satisfaction of EMR.

Conclusion:

Participants reported positive views in the domain of use, quality, and satisfaction with EMR. Furthermore, positive correlations were reported between the use, quality, and satisfaction domains of EMR.

Patient empowerment through a user-centered design of an electronic personal health record: a qualitative study of user requirements in chronic kidney disease

Background

To improve chronic disease outcomes, self-management is an effective strategy. An electronic personal health record (ePHR) is a promising tool with the potential to support chronic patient’s education, counseling, and self-management. Fitting ePHRs within the daily practices of chronic care providers and chronic patients requires user-centered design approaches. We aimed to understand users’ needs and requirements in chronic kidney disease (CKD) care to consider in the design of an ePHR to facilitate its implementation, adoption, and use.

Methods

A qualitative study was conducted in a major Iranian nephrology center including inpatient and outpatient settings in 2019. We conducted 28 semi-structured interviews with CKD patients, nurses, and adult nephrologists. To confirm or modify the requirements extracted from the interviews, a focus group was also held. Data were analyzed to extract especially those requirements that can facilitate implementation, adoption, and sustained use based on the PHR adoption model and the unified theory of acceptance and use of technology.

Results

Participants requested an ePHR that provides access to up to date patient information, facilitates patient-provider communication, and increases awareness about patient individualized conditions. Participants expected a system that is able to cater to low patient e-health literacy and high provider workload. They requested the ePHR to include purposeful documentation of medical history, diagnostic and therapeutic procedures, tailored educational content, and scheduled care reminders. Messaging function, tailored educational content to individual patients’ conditions, and controlled access to information were highly valued in order to facilitate its implementation, adoption, and use.

Conclusions

We focused on the ePHR’s content and functionalities in the face of facilitators and/or barriers envisioned for its adoption in nephrology care. Designers and implementers should value CKD patients’ needs and requirements for self-management such as providing personalized education and counseling (on the basis of their condition and risk factors), health literacy, and disease progression levels. The socio-technical aspects of care also need further attention to facilitate ePHR’s adoption.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-021-01689-2.

A new methodological framework for hazard detection models in health information technology systems

The adoption of health information technology (HIT) has facilitated efforts to increase the quality and efficiency of health care services and decrease health care overhead while simultaneously generating massive amounts of digital information stored in electronic health records (EHRs). However, due to patient safety issues resulting from the use of HIT systems, there is an emerging need to develop and implement hazard detection tools to identify and mitigate risks to patients. This paper presents a new methodological framework to develop hazard detection models and to demonstrate its capability by using the US Department of Veterans Affairs' (VA) Corporate Data Warehouse, the data repository for the VA's EHR. The overall purpose of the framework is to provide structure for research and communication about research results. One objective is to decrease the communication barriers between interdisciplinary research stakeholders and to provide structure for detecting hazards and risks to patient safety introduced by HIT systems through errors in the collection, transmission, use, and processing of data in the EHR, as well as potential programming or configuration errors in these HIT systems. A nine-stage framework was created, which comprises programs about feature extraction, detector development, and detector optimization, as well as a support environment for evaluating detector models. The framework forms the foundation for developing hazard detection tools and the foundation for adapting methods to particular HIT systems.

Interoperability opportunities and challenges in linking mhealth applications and eRecord systems: Botswana as an exemplar

Background

Significant investments have been made towards the implementation of mHealth applications and eRecord systems globally. However, fragmentation of these technologies remains a big challenge, often unresolved in developing countries. In particular, evidence shows little consideration for linking mHealth applications and eRecord systems. Botswana is a typical developing country in sub-Saharan Africa that has explored mHealth applications, but the solutions are not interoperable with existing eRecord systems. This paper describes Botswana’s eRecord systems interoperability landscape and provides guidance for linking mHealth applications to eRecord systems, both for Botswana and for developing countries using Botswana as an exemplar.

Methods

A survey and interviews of health ICT workers and a review of the Botswana National eHealth Strategy were completed. Perceived interoperability benefits, opportunities and challenges were charted and analysed, and future guidance derived.

Results

Survey and interview responses showed the need for interoperable mHealth applications and eRecord systems within the health sector of Botswana and within the context of the National eHealth Strategy. However, the current Strategy does not address linking mHealth applications to eRecord systems. Across Botswana’s health sectors, global interoperability standards and Application Programming Interfaces are widely used, with some level of interoperability within, but not between, public and private facilities. Further, a mix of open source and commercial eRecord systems utilising relational database systems and similar data formats are supported. Challenges for linking mHealth applications and eRecord systems in Botswana were identified and categorised into themes which led to development of guidance to enhance the National eHealth Strategy.

Conclusion

Interoperability between mHealth applications and eRecord systems is needed and is feasible. Opportunities and challenges for linking mHealth applications to eRecord systems were identified, and future guidance stemming from this insight presented. Findings will aid Botswana, and other developing countries, in resolving the pervasive disconnect between mHealth applications and eRecord systems.

Nursing education and training on electronic health record systems: An integrative review

AIM

This integrative review aimed to synthesize evidence pertaining to interventions that have been used to facilitate nurse education and training on electronic health records.

BACKGROUND

Inadequate education and training can threaten the adoption of electronic health records and negatively impact the quality of nursing documentation. A review of the literature may help facilitate the development of evidence-based interventions for nursing education and training on electronic health records.

DESIGN

An integrative review framework was used to address the research question: What is the available evidence to inform best practices for nursing education and training on electronic health records?

METHODS

A systematic search was conducted in five databases: the Cumulative Index to Nursing and Allied Health Literature, Scopus, PubMed, CBCA Education, and ProQuest Education Database. Included articles were peer-reviewed studies, published in English, in which nurses participated in an electronic health record education or training intervention.

RESULTS

Fifteen articles, from a search conducted between 2010 and 2020, were reviewed. Findings identified a shift from classroom learning towards blended approaches for nursing education and training on electronic health records, incorporating methods such as e-learning, peer coaching, and simulation. Ongoing staff engagement is needed to develop interventions that allow nurses to integrate electronic health records into their daily workflows. Higher quality studies and more meaningful assessment of learning outcomes are needed to identify the most effective interventions to incorporate in blended learning strategies.

CONCLUSIONS

Consensus in the reviewed literature indicated that electronic health record education and training for nurses should be multipronged and targeted to nurses' clinical workflows. Key findings of this review identified a shift from classroom-based learning towards blended approaches for electronic health record education and training. Blended approaches often incorporated non-traditional methods that could support interactive and workflow-based content. These included e-learning, nurse superusers or peer coaches, and simulation training. The findings of this review also highlighted the need for early and ongoing involvement of frontline nurses during electronic health record education and implementation. However, more rigorous studies that assess both patient and organizational outcomes are needed to identify the most effective "cocktail" of blended learning strategies.

Non-communicable Disease Surveillance in Malaysia: An Overview of Existing Systems and Priorities Going Forward

In 2012, the World Health Organization (WHO) set a comprehensive set of nine global voluntary targets, including the landmark “25 by 25” mortality reduction target, and 25 indicators. WHO has also highlighted the importance of Non-Communicable Disease (NCD) surveillance as a key action by Member States in addressing NCDs. This study aimed to examine the current national NCD surveillance tools, activities and performance in Malaysia based on the WHO Global Monitoring Framework for NCDs and to highlight gaps and priorities moving forward. A desk review was conducted from August to October in 2020, to examine the current national NCD surveillance activities in Malaysia from multiple sources. Policy and program documents relating to NCD surveillance in Malaysia from 2010 to 2020 were identified and analyzed. The findings of this review are presented according to the three major themes of the Global Monitoring Framework: monitoring of exposure/risk factor, monitoring of outcomes and health system capacity/response. Currently, there is a robust monitoring system for NCD Surveillance in Malaysia for indicators that are monitored by the WHO NCD Global Monitoring Framework, particularly for outcome and exposure monitoring. However, Malaysia still lacks data for the surveillance of the health system indicators of the framework. Although Malaysia has an NCD surveillance in place that is adequate for the WHO NCD Global Monitoring Framework, there are areas that require strengthening. The country must also look beyond these set of indicators in view of the increasing burden and impact of the COVID-19 pandemic. This includes incorporating mental health indicators and leveraging on alternate sources of data relating to behaviors.

EMR2vec: Bridging the gap between patient data and clinical trial

The human suffering from diseases caused by life-threatening viruses such as SARS, Ebola, and COVID-19 motivated many of us to study and discover the best means to harness the potential of data integration to assist clinical researchers to curb these viruses. Integrating patients data with clinical trials data is enormously promising as it provides a comprehensive knowledge base that accelerates the clinical research response-ability to tackle emerging infectious disease outbreaks. This work introduces EMR2vec, a platform that customises advanced NLP, machine learning and semantic web techniques to link potential patients to suitable clinical trials. Linking these two different but complementary datasets allows clinicians and researchers to compare patients to clinical research opportunities or to automatically select patients for personalized clinical care. The platform derives a 'bag of medical terms' (BoMT) from eligibility criteria by normalizing extracted entities through SNOMED-CT ontology. With the usage of BoMT, an ontological reasoning method is proposed to represent EMR and clinical trials in a vector space model. The platform presents a matching process that reduces vector dimensionality using a neural network, then applies orthogonality projection to measure the similarity between vectors. Finally, the proposed EMR2vec platform is evaluated with an extendable prototype based on Big data tools.

Design and preliminarily validation of a tool to assess the impact of chronic non-cancer pain on people's daily life in Spanish-language: PAIN_Integral Scale©

AIM

To build and preliminarily validate a Spanish-language instrument to assess the impact that CNCP has on the daily lives of people who suffer from it.

BACKGROUND

The experience of pain is multifactorial and a correct assessment of it helps to control the intensity of pain. Although there are instruments that evaluate areas on which Chronic Non-Cancer Pain impacts, it would be necessary to include other aspects that scientific literature identifies as relevant.

DESIGN

Instrument and construct cross-sectional study for psychometric validation.

METHODS

A total of 157 items based on items from validated questionnaires were evaluated by a group of 21 chronic pain experts using Delphi methodology in three evaluation rounds. A final questionnaire of 55 items with a 5-point Likert-type scale was formed. This questionnaire was piloted on a total of 30 patients to assess their understanding of the items and the psychometric validation process was carried out (January to March 2020) on a subsequent sample of 395 people, all of whom attended Pain Units and Primary Care Centres of the Public Health System in Spain.

RESULTS

The PAIN_Integral Scale^© showed acceptable internal consistency scores measured by Cronbach's alpha. Exploratory Factor Analysis indicated a structure of nine factors that explain 71.02% of the total variance, from 157 to a final total of 36 items. Confirmatory Factor Analysis showing adequate values confirmed this structure. The effect size was used to calculate the cut-off points for the overall scale, setting them at scores of 130 and 135.

CONCLUSION

This instrument would allow to assess other constructs and dimensions not included in the instruments previously available such as treatment compliance, proactivity, resilience, hopelessness due to pain and pain catastrophizing. However, despite the fact that the preliminary analysis shows good results, it is necessary to continue with its validation process in subsequent studies.

IMPACT

The PAIN_Integral Scale^© , once the validation process is finished, could be a complete enough instrument to allow a comprehensive healthcare assessment of Chronic Non-Cancer Pain's impact on daily nursing clinical practice and other healthcare professionals.

Review of National-Level Personal Health Records in Advanced Countries

OBJECTIVES

This review article examines international examples of personal health records (PHRs) in advanced countries and discusses the implications of these examples for the establishment and utilization of PHRs in South Korea.

METHODS

This article synthesized PHR case reports of Organization for Economic Co-operation and Development (OECD) member countries, the Global Digital Health Partnership website on PHRs, and patient portals of individual countries to review the status of PHR services. The concept and significance of PHRs were also discussed with respect to PHR utilization status in European Union and OECD countries.

RESULTS

A review of international PHR services showed that the countries shared common points regarding the establishment of Electronic Health Records and national health information infrastructure. In addition, the countries provided services centered on primary healthcare institutions and public hospitals. However, promoting more positive participation and increasing the PHR acceptance rate requires workflow integration, including Electronic Medical Records, the provision of incentives, and the preparation of a supportive legal framework.

CONCLUSIONS

South Korea is also conducting a national-level PHR project. Since the scope of PHRs is extensive and a wide range of PHR services must be connected, an extensive trial-and-error process will be necessary. A long-term strategy should be prepared, and necessary resources should be secured to establish national-level PHRs.

Utility, Value, and Benefits of Contemporary Personal Health Records: Integrative Review and Conceptual Synthesis

Background

Contemporary personal health record (PHR) technologies offer a useful platform for individuals to maintain a lifelong record of personally reported and clinically sourced data from various points of medical care.

Objective

This paper presents an integrative review and synthesis of the extant literature on PHRs. This review draws upon multiple lenses of analysis and deliberates value perspectives of PHRs at the product, consumer, and industry levels.

Methods

Academic databases were searched using multiple keywords related to PHRs for the years 2001-2020. Three research questions were formulated and used as selection criteria in our review of the extant literature relevant to our study.

Results

We offer a high-level functional utility model of PHR features and functions. We also conceptualize a consumer value framework of PHRs, highlighting the applications of these technologies across various health care delivery activities. Finally, we provide a summary of the benefits of PHRs for various health care constituents, including consumers, providers, payors, and public health agencies.

Conclusions

PHR products offer a myriad of content-, connectivity-, and collaboration-based features and functions for their users. Although consumers benefit from the tools provided by PHR technologies, their overall value extends across the constituents of the health care delivery chain. Despite advances in technology, our literature review identifies a shortfall in the research addressing consumer value enabled by PHR tools. In addition to scholars and researchers, our literature review and proposed framework may be especially helpful for value analysis committees in the health care sector that are commissioned for the appraisal of innovative health information technologies such as PHRs.

Governing Personalized Health: A Scoping Review

Genetic research is advancing rapidly. One important area for the application of the results from this work is personalized health. These are treatments and preventive interventions tailored to the genetic profile of specific groups or individuals. The inclusion of personalized health in existing health systems is a challenge for policymakers. In this article, we present the results of a thematic scoping review of the literature dealing with governance and policy of personalized health. Our analysis points to four governance challenges that decisionmakers face against the background of personalized health. First, researchers have highlighted the need to further extend and harmonize existing research infrastructures in order to combine different types of genetic data. Second, decisionmakers face the challenge to create trust in personalized health applications, such as genetic tests. Third, scholars have pointed to the importance of the regulation of data production and sharing to avoid discrimination of disadvantaged groups and to facilitate collaboration. Fourth, researchers have discussed the challenge to integrate personalized health into regulatory-, financing-, and service provision structures of existing health systems. Our findings summarize existing research and help to guide further policymaking and research in the field of personalized health governance.