Interoperable Electronic Health Record Research Articles

Integrating electronic health records (EHRs) to facilitate cancer biomarker testing: Real-world implementation barriers and solutions.

e13649 Background: Effective integration between EHRs and cancer biomarker testing processes is an unmet need across academic and community settings. Despite the benefits of EHR-integrated workflows and the desire for streamlined test results, as supported by a recent ASCO Workforce Survey, many health systems do not currently have this capacity, especially when reference labs are external to the ordering institution. Methods: The Association of Cancer Care Centers (ACCC) convened a live summit on October 4, 2023 to understand facilitators and barriers to integrating biomarker orders and results into the EHR. To capture a comprehensive perspective, ACCC convened 37 oncologists, pathologists, nurse navigators, and administrators from diverse settings using a range of EHRs, patient advocacy groups, and EHR/testing companies. Thematic analysis of the summit transcript and a post-summit assessment was employed to identify common experiences among participants. Results: The key benefits of EHR integration include increased efficiency with test ordering/result retrieval, streamlined communication, and improved clinical decision-making. Factors associated with successful EHR integration include strong clinical champions, creation of a precision medicine oversight committee, buy-in from administrative leadership, IT support to build EHR customizations, support from EHR vendors/reference labs, and coordinated project management. Notable barriers include variations in EHR interoperability, utilization of multiple reference labs, lack of consistent nomenclature, resistance to change, allocation of time for post-integration updates/maintenance, lack of internal IT capabilities/resources, and a need to establish different clinical workflows depending on which clinician places the biomarker order. Conclusions: The rapid expansion of biomarker-driven cancer treatments requires oncologists to have timely access to guideline-concordant clinical information to inform complex clinical decision-making. While EHRs can streamline clinical workflows, these results underscore the need to address operational and human factors to facilitate successful EHR-laboratory integration. Strategies to address barriers and build successful EHR integrations across diverse clinical oncology settings are crucial for optimizing how cancer biomarker tests are ordered, reported and used in clinical practice.

Implementation and adaptation of a hub-based psychiatric and primary care program: A qualitative descriptive analysis of The Seamless Care Optimizing the Patient Experience (SCOPE) Mental Health program.

The Seamless Care Optimizing the Patient Experience (SCOPE)-Mental Health program is a comprehensive case management and psychiatric care initiative that supports primary care physicians in independent medical practices. This program offers a range of services that aims to enhance primary care capacity for mental health and provide accessible clinical care for patients. With its flexible hub-based approach, this program allows participating sites to tailor their implementation based on their available resources and specific needs within their community. The aim of this quality improvement initiative was to investigate the evolution of this collaborative mental health model, focusing on specific site adaptations, local implementation challenges, and opportunities for ongoing development and sustainability across SCOPE sites in the Greater Toronto Area. This evaluation employed a qualitative descriptive design where semi-structured interviews, guided by the Reach Effectiveness Adoption, Implementation, and Maintenance framework were conducted with staff from all 8 SCOPE-Mental Health sites. Site representatives were interviewed virtually between March and July 2023 and data were analyzed using qualitative content analysis. The SCOPE-Mental Health model permits flexibility through specific local adaptations led by community need that leverage existing assets either at the site or within the individual community. Adoption by primary care physicians was crucial to program success and facilitated efficiency and interprofessional collaboration. Maintenance efforts included pathway refinement, and marketing and funding considerations. Challenges to program development included continuity of staff, physician compensation issues, and electronic health record interoperability. The SCOPE-Mental Health program fosters linkages among unaffiliated primary care offices, hospitals, and community-based resources to improve mental health care. Key recommendations include advocating for sustainable funding and facilitated mechanisms for psychiatric consultations. This initiative offers valuable insights for healthcare organizations seeking to develop similar programs, emphasizing the need for tailored approaches and ongoing evaluation to ensure a lasting impact in underserved communities.

Semantic Interoperability of Electronic Health Records: Systematic Review of Alternative Approaches for Enhancing Patient Information Availability.

Semantic interoperability facilitates the exchange of and access to health data that are being documented in electronic health records (EHRs) with various semantic features. The main goals of semantic interoperability development entail patient data availability and use in diverse EHRs without a loss of meaning. Internationally, current initiatives aim to enhance semantic development of EHR data and, consequently, the availability of patient data. Interoperability between health information systems is among the core goals of the European Health Data Space regulation proposal and the World Health Organization's Global Strategy on Digital Health 2020-2025. To achieve integrated health data ecosystems, stakeholders need to overcome challenges of implementing semantic interoperability elements. To research the available scientific evidence on semantic interoperability development, we defined the following research questions: What are the key elements of and approaches for building semantic interoperability integrated in EHRs? What kinds of goals are driving the development? and What kinds of clinical benefits are perceived following this development? Our research questions focused on key aspects and approaches for semantic interoperability and on possible clinical and semantic benefits of these choices in the context of EHRs. Therefore, we performed a systematic literature review in PubMed by defining our study framework based on previous research. Our analysis consisted of 14 studies where data models, ontologies, terminologies, classifications, and standards were applied for building interoperability. All articles reported clinical benefits of the selected approach to enhancing semantic interoperability. We identified 3 main categories: increasing the availability of data for clinicians (n=6, 43%), increasing the quality of care (n=4, 29%), and enhancing clinical data use and reuse for varied purposes (n=4, 29%). Regarding semantic development goals, data harmonization and developing semantic interoperability between different EHRs was the largest category (n=8, 57%). Enhancing health data quality through standardization (n=5, 36%) and developing EHR-integrated tools based on interoperable data (n=1, 7%) were the other identified categories. The results were closely coupled with the need to build usable and computable data out of heterogeneous medical information that is accessible through various EHRs and databases (eg, registers). When heading toward semantic harmonization of clinical data, more experiences and analyses are needed to assess how applicable the chosen solutions are for semantic interoperability of health care data. Instead of promoting a single approach, semantic interoperability should be assessed through several levels of semantic requirements A dual model or multimodel approach is possibly usable to address different semantic interoperability issues during development. The objectives of semantic interoperability are to be achieved in diffuse and disconnected clinical care environments. Therefore, approaches for enhancing clinical data availability should be well prepared, thought out, and justified to meet economically sustainable and long-term outcomes.

Electronic Health Record Interoperability System in Peru Using Blockchain

In Peru, there is currently no integrated electronic health record (EHR) system that can be automatically shared between healthcare facilities. This leads to increased service costs due to duplicated examinations and records, as well as additional time required to manage patients’ clinical information. One alternative for ensuring the secure interoperability of EHRs while preserving data privacy is the use of blockchain technology. However, existing works consider a pre-established format for exchanging EHRs, which is not applicable when systems have different formats, as is the case in Peru. This work proposes an architecture and a web application for exchanging EHRs in heterogeneous systems. The proposed system includes the homologation of an EHR with rapid interoperability resources for medical attention using FHIR HL7, and vice versa, to achieve interoperability. Additionally, it utilizes blockchain technology to ensure data security and privacy. The web application was tested using a case simulation to demonstrate EHR interoperability between clinics in a clear, secure, and efficient manner. In addition, a survey was conducted with 30 patients regarding adoption, and another survey was conducted with 10 doctors from a public hospital in Peru regarding usability. The results demonstrate a very high level of adoption and usability for them all. Unlike other studies, the proposal does not necessitate alterations to existing EHR systems for interoperability. In other words, the proposal presents a feasible and cost-effective alternative to addressing the EHR interoperability issue in clinics and hospitals in Peru.

Empowering Electronic Health Record Systems (EHRs) with Cloud Storage Management

We present a novel method for building cloud based interoperable electronic health record (EHR) systems. All members of the healthcare ecosystem, including patients, providers, and payers, can benefit from cloud computing in a number of ways. The exchange of healthcare information among diverse stakeholders has been significantly hampered by the lack of standardised data interoperability. In order to solve this problem, semantic interoperability is used. With the use of a reference model that outlines a common set of data structures and an archetype model that details the characteristics of clinical data, we employ a general design technique. The loosely connected, asynchronously communicating components of the application are created utilising the cloud component model technique. This article discusses our methods for attaining semantic interoperability, data integration, and high-level architecture of our EHR system.

Transforming cancer clinical trials: The integral role of artificial intelligence in electronic health records for efficient patient recruitment

Healthcare is one of the sectors where artificial intelligence (AI) is currently viewed as a crucial driving factor. Patient care, medical research, and clinical trial enrollment could all significantly improve due to AI's incorporation into electronic health records (EHRs). This short communication highlights how AI may improve the recruitment process regarding speed, accuracy, and overall cancer clinical trial efficiency. AI can automate this procedure by utilizing machine learning (ML) algorithms, identifying potential trial participants quickly and precisely. Many challenges could be addressed due to this integration, including data privacy and security that can be resolved through cutting-edge encryption techniques and differential privacy algorithms that ensure data anonymization. Another significant obstacle is the lack of common EHR formats and interoperability that can be addressed by creating a standardized structured layout. Automating and improving recruitment processes with AI may speed up research, increase the effectiveness of clinical trials, and open the door to more specialized cancer treatments.

Electronic Health Record (EHR) System Development for Study on EHR Data-based Early Prediction of Diabetes Using Machine Learning Algorithms

Aims: This research work aims to develop an interoperable electronic health record (EHR) system to aid the early detection of diabetes by the use of Machine Learning (ML) algorithms. A decision support system developed using many ML algorithms results in optimizing the decision in preventive care in the health information system. Methods: The proposed system consisted of two models. The first model included interoperable EHR system development using a precise database structure. The second module comprised of data extraction from the EHR system, data cleaning, and data processing and prediction. For testing and training, about 1080 patients’ health record was considered. Among 1080, 1000 records were from the Kaggle dataset, and 80 records were demographic information from patients who visited our health center of Siddaganga organization for a regular checkup or during emergencies. The demographic information was collected from the proposed EHR system. Results: The proposed system was tested for the interoperability nature of the EHR system and accuracy in diabetic disease prediction using the proposed decision support system. The proposed EHR system development was tested for interoperability by random updations from various systems maintained in the laboratory. Each system acted like the admin system of different hospitals. The EHR system was tested for handling the load and interoperability by considering user view status, system matching with the real world, consistency in data updations, security etc. However, in the prediction phase, diabetes prediction was concentrated. The features considered were not randomly chosen; however, the features were those prescribed by a doctor who insisted that the features were sufficient for initial prediction. The reports collected from the doctors revealed several features they considered before giving the test details. The proposed system dataset was split into test and train datasets with eight proper features taken as input and one set as a target variable where the result was present. After this, the model was imported using standard “sklearn” libraries, and it fit with the required number of estimators, that is, the number of decision trees. The features included pregnancies, glucose level, blood pressure, skin thickness, insulin level, bone marrow index, diabetic pedigree function, age, weight, etc. At the outset, the research work concentrated on developing an interoperable EHR system, identifying the expectation of diabetic and non-diabetic conditions and demonstrating the accuracy of the system. Conclusion: In this study, the first aim was to design an interoperable EHR system that could help in accumulating, storing, and sharing patients' timely health records over a lifetime. The second aim was to use EHR data for early prediction of diabetes in the user. To confirm the accuracy of the system, the system was tested regarding interoperability to support early prediction through a decision support system.

Virtual twin for healthcare management.

Healthcare is increasingly fragmented, resulting in escalating costs, patient dissatisfaction, and sometimes adverse clinical outcomes. Strategies to decrease healthcare fragmentation are therefore attractive from payer and patient perspectives. In this commentary, a patient-centered smart phone application called Virtual Twin for Healthcare Management (VTHM) is proposed, including its organizational layout, basic functionality, and potential clinical applications. The platform features a virtual twin hub that displays the body and its health data. This is a physiologically based human model that is "virtualized" for the patient based on their unique genetic, molecular, physiological, and disease characteristics. The spokes of the system are a full service and interoperable electronic-health record, accessible to healthcare providers with permission on any device with internet access. Theoretical case studies based on real scenarios are presented to show how VTHM could potentially improve patient care and clinical efficiency. Challenges that must be overcome to turn VTHM into reality are also briefly outlined. Notably, the VTHM platform is designed to operationalize current and future precision medicine initiatives, such as access to molecular diagnostic results, pharmacogenomics-guided prescribing, and model-informed precision dosing.

Machine Learning-Enabled Clinical Information Systems Using Fast Healthcare Interoperability Resources Data Standards: Scoping Review.

Machine learning-enabled clinical information systems (ML-CISs) have the potential to drive health care delivery and research. The Fast Healthcare Interoperability Resources (FHIR) data standard has been increasingly applied in developing these systems. However, methods for applying FHIR to ML-CISs are variable. This study evaluates and compares the functionalities, strengths, and weaknesses of existing systems and proposes guidelines for optimizing future work with ML-CISs. Embase, PubMed, and Web of Science were searched for articles describing machine learning systems that were used for clinical data analytics or decision support in compliance with FHIR standards. Information regarding each system's functionality, data sources, formats, security, performance, resource requirements, scalability, strengths, and limitations was compared across systems. A total of 39 articles describing FHIR-based ML-CISs were divided into the following three categories according to their primary focus: clinical decision support systems (n=18), data management and analytic platforms (n=10), or auxiliary modules and application programming interfaces (n=11). Model strengths included novel use of cloud systems, Bayesian networks, visualization strategies, and techniques for translating unstructured or free-text data to FHIR frameworks. Many intelligent systems lacked electronic health record interoperability and externally validated evidence of clinical efficacy. Shortcomings in current ML-CISs can be addressed by incorporating modular and interoperable data management, analytic platforms, secure interinstitutional data exchange, and application programming interfaces with adequate scalability to support both real-time and prospective clinical applications that use electronic health record platforms with diverse implementations.

Perceptions of chief clinical information officers on the state of electronic health records systems interoperability in NHS England: a qualitative interview study

BackgroundIn the era of electronic health records (EHR), the ability to share clinical data is a key facilitator of healthcare delivery. Since the introduction of EHRs, this aspect has been extensively studied from the perspective of healthcare providers. Less often explored are the day-to-day challenges surrounding the procurement, deployment, maintenance, and use of interoperable EHR systems, from the perspective of healthcare administrators, such as chief clinical information officers (CCIOs).ObjectiveOur study aims to capture the perceptions of CCIOs on the current state of EHR interoperability in the NHS, its impact on patient safety, the perceived facilitators and barriers to improving EHR interoperability, and what the future of EHR development in the NHS may entail.MethodsSemi-structured interviews were conducted between November 2020 – October 2021. Convenience sampling was employed to recruit NHS England CCIOs. Interviews were digitally recorded and transcribed verbatim. A thematic analysis was performed by two independent researchers to identify emerging themes.ResultsFifteen CCIOs participated in the study. Participants reported that limited EHR interoperability contributed to the inability to easily access and transfer data into a unified source, thus resulting in data fragmentation. The resulting lack of clarity on patients' health status negatively impacts patient safety through suboptimal care coordination, duplication of efforts, and more defensive practice. Facilitators to improving interoperability included the recognition of the need by clinicians, patient expectations, and the inherent centralised nature of the NHS. Barriers included systems usability difficulties, and institutional, data management, and financial-related challenges. Looking ahead, participants acknowledged that realising that vision across the NHS would require a renewed focus on mandating data standards, user-centred design, greater patient involvement, and encouraging inter-organisational collaboration.ConclusionTackling poor interoperability will require solutions both at the technical level and in the wider policy context. This will involve demanding interoperability functionalities from the outset in procurement contracts, fostering greater inter-organisation cooperation on implementation strategies, and encouraging systems vendors to prioritise interoperability in their products. Only by comprehensively addressing these challenges would the full potential promised by the use of fully interoperable EHRs be realised.

What does it take to create a European Health Data Space? International commitments and national realities

Public health concerns in Europe demonstrate the necessity of building a health policy that could contribute to the long-term sustainable development of the European Union (EU), as stated in the European Health Union (EHU) manifesto. The main desire to create an EHU is embodied in the launch of the European Health Data Space (EHDS). The EHDS seeks to foster a genuine single market for digital health services and products by, among other things, accelerating the uptake and implementation of harmonised and interoperable electronic health record (EHR) systems across the EU. In the context of primary and secondary use of EHR data, developments in Europe have thus far resulted in patchy and, in some places, non-interoperable solutions. Taking the gap between international ambitions and national realities as a starting point, this paper contends that both EU level and Member State level circumstances should be considered to make the EHDS a reality.

Artificial intelligence–enabled tools in cardiovascular medicine: A survey of current use, perceptions, and challenges

Numerous artificial intelligence (AI)-enabled tools for cardiovascular diseases have been published, with a high impact on public health. However, few have been adopted into, or have meaningfully affected, routine clinical care. To evaluate current awareness, perceptions, and clinical use of AI-enabled digital health tools for patients with cardiovascular disease, and challenges to adoption. This mixed-methods study included interviews with 12 cardiologists and 8 health information technology (IT) administrators, and a follow-on survey of 90 cardiologists and 30 IT administrators. We identified 5 major challenges: (1) limited knowledge, (2) insufficient usability, (3) cost constraints, (4) poor electronic health record interoperability, and (5) lack of trust. A minority of cardiologists were using AI tools; more were prepared to implement AI tools, but their sophistication level varied greatly. Most respondents believe in the potential of AI-enabled tools to improve care quality and efficiency, but they identified several fundamental barriers to wide-scale adoption.

Does circle priming improve smart infusion pump and electronic health record interoperability for chemotherapy in a pediatric hematology/oncology setting?

The objective of this project was to assess the percentage of interoperability compliance within our pediatric hematology/oncology patient care areas for intravenous chemotherapy medications before and after the implementation of circle priming. We conducted a retrospective quality improvement project at an inpatient pediatric hematology/oncology floor and outpatient pediatric infusion center before and after implementation of circle priming. There was a statistically significant increase in percent interoperability compliance for the inpatient pediatric hematology/oncology floor from 4.1% prior to implementation of circle priming to 35.6% after (odds ratio 13.1 (95% CI, 3.96-43.1), p < 0.001), as well as for the outpatient pediatric infusion center from 18.5% to 47.3%, respectively (odds ratio 3.9 (95% CI, 2.7-5.9), p < 0.001). Implementation of circle priming has significantly increased the percentage of interoperability compliance for intravenous chemotherapy medications in our pediatric hematology/oncology patient care areas.

Blockchain-Based Framework for Interoperable Electronic Health Records for an Improved Healthcare System

The healthcare industry has been transitioning from paper-based medical records to electronic health records (EHRs) in most healthcare facilities. However, the current EHR frameworks face challenges in secure data storage, credibility, and management. Interoperability and user control of personal data are also significant concerns in the healthcare sector. Although block chain technology has emerged as a powerful solution that can offer the properties of immutability, security, and user control on stored records, its potential application in EHR frameworks is not yet fully understood. To address this gap in knowledge, this research aims to provide an interoperable blockchain-based EHR framework that can fulfill the requirements defined by various national and international EHR standards such as HIPAA and HL7. The research method employed is a systematic literature review to explore the current state of the art in the field of EHRs, including blockchain-based implementations of EHRs. The study defines the interoperability issues in the existing blockchain-based EHR frameworks, reviews various national and international standards of EHR, and further defines the interoperability requirements based on these standards. The proposed framework can offer safer methods to interchange health information for the healthcare sector and can provide the properties of immutability, security, and user control on stored records without the need for centralized storage. The contributions of this work include enhancing the understanding of the potential application of blockchain technology in EHR frameworks and proposing an interoperable blockchain-based EHR framework that can fulfill the requirements defined by various national and international EHR standards. Overall, this study has significant implications for the healthcare sector, as it can enhance the secure sharing and storage of electronic health data while ensuring the confidentiality, privacy, and integrity of medical records.

Characteristics of telemedicine workflows in nursing homes during the COVID-19 pandemic

BackgroundThe use of telemedicine increased dramatically in nursing homes (NHs) during the COVID-19 pandemic. However, little is known about the actual process of conducting a telemedicine encounter in NHs. The objective of this study was to identify and document the work processes associated with different types of telemedicine encounters conducted in NHs during the COVID-19 pandemic.MethodsA mixed methods convergent study was utilized. The study was conducted in a convenience sample of two NHs that had newly adopted telemedicine during the COVID-19 pandemic. Participants included NH staff and providers involved in telemedicine encounters conducted in the study NHs. The study involved semi-structured interviews and direct observation of telemedicine encounters and post-encounter interviews with staff and providers involved in telemedicine encounters observed by research staff. The semi-structured interviews were structured using the Systems Engineering Initiative for Patient Safety (SEIPS) model to collect information about telemedicine workflows. A structured checklist was utilized to document steps performed during direct observations of telemedicine encounters. Information from interviews and observations informed the creation of a process map of the NH telemedicine encounter.ResultsA total of 17 individuals participated in semi-structured interviews. Fifteen unique telemedicine encounters were observed. A total of 18 post-encounter interviews with 7 unique providers (15 interviews in total) and three NH staff were performed. A 9-step process map of the telemedicine encounter, along with two microprocess maps related to encounter preparation and activities within the telemedicine encounter, were created. Six main processes were identified: encounter planning, family or healthcare authority notification, pre-encounter preparation, pre-encounter huddle, conducting the encounter, and post-encounter follow-up.ConclusionThe COVID-19 pandemic changed the delivery of care in NHs and increased reliance on telemedicine services in these facilities. Workflow mapping using the SEIPS model revealed that the NH telemedicine encounter is a complex multi-step process and identified weaknesses related to scheduling, electronic health record interoperability, pre-encounter planning, and post-encounter information exchange, which represent opportunities to improve and enhance the telemedicine encounter process in NHs. Given public acceptance of telemedicine as a care delivery model, expanding the use of telemedicine beyond the COVID-19 pandemic, especially for certain NH telemedicine encounters, could improve quality of care.

Electronic health record interoperability using FHIR and blockchain: A bibliometric analysis and future perspective.

Electronic health records (EHRs) constitute vital statistics, current health condition, ongoing therapies, and patient data; hence, their interoperability could be useful for epidemiologic and clinical research. Fast Healthcare Interoperability Resources (FHIR) and blockchain are currently "in-use" and tested for exchange of such data. The annual scientific production of publications for both FHIR and blockchain shows steady growth. The data interoperability and electronic data interchange have been introduced in the field of EHR in 2020, hence inferring that data interoperability is relatively a new domain. The thematic mapping suggested "interoperability" of EHR is well-developed and important for the structure of the research field.

Acceptance of Interoperable Electronic Health Record (EHRs) Systems: A Tanzanian e-Health Perspective

Acceptance of Interoperable Electronic Health Record (EHRs) Systems: A Tanzanian e-Health Perspective

LIKELIHOOD OF ADOPTION OF CAREMOBI: ADDRESSING COMMUNICATION GAPS BETWEEN ADULT DAY HEALTH CENTERS AND PRIMARY CARE

Abstract Adult Day Health Centers (ADHC) are non-residential congregate facilities that serve 250,000 cognitively and functionally impaired adults daily. These centers are effective platforms for chronic disease management and interdisciplinary care coordination, with serial observations on participants over multiple hours and days per week. However, previous research indicates that ADHCs experience challenges in communication with primary care providers (PCPs). This is because 92% of ADHCs lack interoperable EHRs (electronic health record systems) and do not have the financial and technical infrastructure to implement them. CareMOBI (Mhealth for Organizations to Bolster Interconnectedness) is a mobile application in development meant to streamline the information communication between ADHC, PCP, and family caregiver populations. The purpose of this study was to understand the likelihood of adoption of CareMOBI by primary care providers. Demographics of the study included 87.50% female and 12.5% male primary care providers with a median age of 38 years. Participants were recruited through parallel convergent design, and data was merged into a matrix defined by 4 major themes: perceived value in geriatric care, ease of use, fit within workflow, and likelihood of adoption. The results revealed that a majority percentage of providers were likely to adopt the app, saw the app as valuable, and easy to use. In response to fit within a provider’s workflow, apprehensions surrounding interoperability arose. These apprehensions regarding interoperability are the most important to address through a user-centered approach and as the app is pilot tested into adult day health centers.

Blockchain Technology for Electronic Health Records.

Compared with traditional paper-based medical records, electronic health records (EHRs) are widely used because of their efficiency, security, and reducing data redundancy. However, EHRs still manifest poor interoperability and privacy issues are unresolved. As a distributed ledger protocol composed of encrypted blocks of data organized in chains, blockchain represents a potential tool to solve the shortcomings of EHRs in terms of interoperability and privacy. In this paper, we define EHRs and blockchain technology and introduce several classic schemes based on blockchain technology to strengthen EHR interoperability and privacy protection. We then review ongoing challenges in the areas of data management efficiency, fairness of access, and trust in the systems. In this commentary, we suggest ongoing research needs for health informatics, data sciences, and ethics to establish EHRs based on blockchain technology. Blockchain-based EHR schemes must address the potential inequality of healthcare resources, the huge carbon footprint of computational needs, and potential distrust of health providers and patients that may ensue with wider use of blockchain technology.

The Impact of Electronic Health Record Interoperability on Safety and Quality of Care in High-Income Countries: Systematic Review.

BackgroundElectronic health records (EHRs) and poor system interoperability are well-known issues in the use of health information technologies in most high-income countries worldwide. Despite the abundance of literature exploring their relationship, their practical implications on patient safety and quality of care remain unclear.ObjectiveThis study aimed to examine how EHR interoperability affects patient safety, or other dimensions of care quality, in high-income health care settings.MethodsA systematic search was conducted using 4 web-based medical journal repositories and grey literature sources. The publications included were published in English between 2010 and 2022, pertaining to EHR use, interoperability, and patient safety or care quality in high-income settings. Screening was completed by 3 researchers in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Risk of bias assessments were performed using the Risk of Bias in Non-randomized Studies of Interventions and the Cochrane Risk of Bias 2 tools. The findings were presented as a narrative synthesis and mapped based on the Institute of Medicine’s framework for health care quality.ResultsA total of 12 studies met the inclusion criteria to be included in our review. The findings were categorized into 6 common outcome measure categories: patient safety events, medication safety, data accuracy and errors, care effectiveness, productivity, and cost savings. EHR interoperability positively influenced medication safety, reduced patient safety events, and reduced costs. Improvements in time saving and clinical workflow are mixed. However, true measures of effect are difficult to determine with certainty because of the heterogeneity in the outcome measures used and notable variation in study quality.ConclusionsThe benefits of EHR interoperability on the quality and safety of care remain unclear and reflect extensive heterogeneity in the interventions, designs, and outcome measures used. The establishment of common health information technology research outcome measures would support higher-quality research on the topic. Future research efforts should focus on both the positive and negative impacts of interoperable EHR interventions and explore patient perspectives, given the growing trend for patient involvement and stewardship over their own electronic clinical data.Trial RegistrationPROSPERO CRD42020209285; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=209285International Registered Report Identifier (IRRID)RR2-10.1136/bmjopen-2020-044941