Technological progress in electronic health record system optimization: Systematic review of systematic literature reviews.
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ABSTRACT: Background
The recent, rapid development of digital technologies offers new possibilities for more efficient implementation of electronic health record (EHR) and personal health record (PHR) systems. A growing volume of healthcare data has been the hallmark of this digital transformation. The large healthcare datasets' complexity and their dynamic nature pose various challenges related to processing, analysis, storage, security, privacy, data exchange, and usability.Materials and methods
We performed a systematic review of systematic reviews to assess technological progress in EHR and PHR systems. We searched MEDLINE, Cochrane, Web of Science, and Scopus for systematic literature reviews on technological advancements that support EHR and PHR systems published between January 1, 2010, and October 06, 2020.Results
The searches resulted in a total of 2,448 hits. Of these, we finally selected 23 systematic reviews. Most of the included papers dealt with information extraction tools and natural language processing technology (n = 10), followed by studies that assessed the use of blockchain technology in healthcare (n = 8). Other areas of digital technology research included EHR and PHR systems in austere settings (n = 1), de-identification methods (n = 1), visualization techniques (n = 1), communication tools within EHR and PHR systems (n = 1), and methodologies for defining Clinical Information Models that promoted EHRs and PHRs interoperability (n = 1).Conclusions
Technological advancements can improve the efficiency in the implementation of EHR and PHR systems in numerous ways. Natural language processing techniques, either rule-based, machine-learning, or deep learning-based, can extract information from clinical narratives and other unstructured data locked in EHRs and PHRs, allowing secondary research (i.e., phenotyping). Moreover, EHRs and PHRs are expected to be the primary beneficiaries of the blockchain technology implementation on Health Information Systems. Governance regulations, lack of trust, poor scalability, security, privacy, low performance, and high cost remain the most critical challenges for implementing these technologies.
SUBMITTER: Negro-Calduch E
PROVIDER: S-EPMC8223493 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundElectronic health record (EHR) system transitions are challenging for healthcare organizations. High-volume, safety-critical tasks like barcode medication administration (BCMA) should be evaluated, yet standards for ensuring safety during transition have not been established.ObjectiveIdentify risks in common and problem-prone medication tasks to inform safe transition between BCMA systems and establish benchmarks for future system changes.DesignStaff nurses completed simulation-based usability testing in the legacy system (R1) and new system pre- (R2) and post-go-live (R3). Tasks included (1) Hold/Administer, (2) IV Fluids, (3) PRN Pain, (4) Insulin, (5) Downtime/PRN, and (6) Messaging. Audiovisual recordings of task performance were systematically analyzed for time, navigation, and errors. The System Usability Scale measured perceived usability and satisfaction. Post-simulation interviews captured nurses' qualitative comments and perceptions of the systems.ParticipantsFifteen staff nurses completed 2-3-h simulation sessions. Eleven completed both R1 and R2, and seven completed all three rounds. Clinical experience ranged from novice (< 1 year) to experienced (> 10 years). Practice settings included adult and pediatric patient populations in ICU, stepdown, and acute care departments.Main measuresTask completion rates/times, safety and non-safety-related use errors (interaction difficulties), and user satisfaction.Key resultsOverall success rates remained relatively stable in all tasks except two: IV Fluids task success increased substantially (R1: 17%, R2: 54%, R3: 100%) and Downtime/PRN task success decreased (R1: 92%, R2: 64%, R3: 22%). Among the seven nurses who completed all rounds, overall safety-related errors decreased 53% from R1 to R3 and 50% from R2 to R3, and average task times for successfully completed tasks decreased 22% from R1 to R3 and 38% from R2 to R3.ConclusionsUsability testing is a reasonable approach to compare different BCMA tasks to anticipate transition problems and establish benchmarks with which to monitor and evaluate system changes going forward.
| S-EPMC10593701 | biostudies-literature
Project description:The UK government had intended to introduce a comprehensive Electronic Health Record (EHR) system in England by 2020. These EHRs would run across primary, secondary, and social care, linking data in a single digital platform. The objectives of this systematic review were to identify studies that compare EHR in terms of direct comparison between systems and to evaluate them using System and Software Quality Requirements and Evaluation (SQuaRE) ISO/IEC 25010. A systematic review was performed by searching Embase and Ovid MEDLINE databases between 1974 and April 2021. All original studies that appraised EHR systems and their providers were included. The main outcome measures were EHR system comparison and the eight characteristics of SQuaRE: functional suitability, performance efficiency, compatibility, usability, reliability, security, maintainability, and portability. A total of 724 studies were identified using the search criteria. After a review of titles and abstracts, this was filtered down to 40 studies as per the exclusion and inclusion criteria set out in our study. Seven studies compared more than one EHR. The following number of studies looked at the various aspects of the SQuaRE, respectively - 19 studies: functional suitability, performance efficiency: 18 studies, compatibility: 12 studies, usability: 25 studies, reliability: 6 studies, security: 2 studies, maintainability: 16 studies, portability: 13 studies. Epic was the most studied EHR system and one of the most implemented systems in the US market and one of the top ten in the UK. It is difficult to assess which is the most advantageous EHR system when they are assessed by SQuaRE's 8 characteristics for software evaluation.
| S-EPMC9485928 | biostudies-literature
Project description:BACKGROUND:Electronic mental (e-mental) health care for depression aims to overcome barriers to and limitations of face-to-face treatment. Owing to the high and growing demand for mental health care, a large number of such information and communication technology systems have been developed in recent years. Consequently, a diverse system landscape formed. OBJECTIVE:This literature review aims to give an overview of this landscape of e-mental health systems for the prevention and treatment of major depressive disorder, focusing on three main research questions: (1) What types of systems exist? (2) How technologically advanced are these systems? (3) How has the system landscape evolved between 2000 and 2017? METHODS:Publications eligible for inclusion described e-mental health software for the prevention or treatment of major depressive disorder. Additionally, the software had to have been evaluated with end users and developed since 2000. After screening, 270 records remained for inclusion. We constructed a taxonomy concerning software systems, their functions, how technologized these were in their realization, and how systems were evaluated, and then, we extracted this information from the included records. We define here as functions any component of the system that delivers either treatment or adherence support to the user. For this coding process, an elaborate classification hierarchy for functions was developed yielding a total of 133 systems with 2163 functions. The systems and their functions were analyzed quantitatively, with a focus on technological realization. RESULTS:There are various types of systems. However, most are delivered on the World Wide Web (76%), and most implement cognitive behavioral therapy techniques (85%). In terms of content, systems contain twice as many treatment functions as adherence support functions, on average. Furthermore, autonomous systems, those not including human guidance, are equally as technologized and have one-third less functions than guided ones. Therefore, lack of guidance is neither compensated with additional functions nor compensated by technologizing functions to a greater degree. Although several high-tech solutions could be found, the average system falls between a purely informational system and one that allows for data entry but without automatically processing these data. Moreover, no clear increase in the technological capabilities of systems showed in the field, between 2000 and 2017, despite a marked growth in system quantity. Finally, more sophisticated systems were evaluated less often in comparative trials than less sophisticated ones (OR 0.59). CONCLUSIONS:The findings indicate that when developers create systems, there is a greater focus on implementing therapeutic treatment than adherence support. Although the field is very active, as evidenced by the growing number of systems developed per year, the technological possibilities explored are limited. In addition to allowing developers to compare their system with others, we anticipate that this review will help researchers identify opportunities in the field.
| S-EPMC6997926 | biostudies-literature
Project description:ObjectiveDisease surveillance systems are expanding using electronic health records (EHRs). However, there are many challenges in this regard. In the present study, the solutions and challenges of implementing EHR-based disease surveillance systems (EHR-DS) have been reviewed.Materials and methodsWe searched the related keywords in ProQuest, PubMed, Web of Science, Cochrane Library, Embase, and Scopus. Then, we assessed and selected articles using the inclusion and exclusion criteria and, finally, classified the identified solutions and challenges.ResultsFinally, 50 studies were included, and 52 unique solutions and 47 challenges were organized into 6 main themes (policy and regulatory, technical, management, standardization, financial, and data quality). The results indicate that due to the multifaceted nature of the challenges, the implementation of EHR-DS is not low cost and easy to implement and requires a variety of interventions. On the one hand, the most common challenges include the need to invest significant time and resources; the poor data quality in EHRs; difficulty in analyzing, cleaning, and accessing unstructured data; data privacy and security; and the lack of interoperability standards. On the other hand, the most common solutions are the use of natural language processing and machine learning algorithms for unstructured data; the use of appropriate technical solutions for data retrieval, extraction, identification, and visualization; the collaboration of health and clinical departments to access data; standardizing EHR content for public health; and using a unique health identifier for individuals.ConclusionsEHR systems have an important role in modernizing disease surveillance systems. However, there are many problems and challenges facing the development and implementation of EHR-DS that need to be appropriately addressed.
| S-EPMC7727341 | biostudies-literature
Project description:BACKGROUND:Many health care systems now allow patients to access their electronic health record (EHR) notes online through patient portals. Medical jargon in EHR notes can confuse patients, which may interfere with potential benefits of patient access to EHR notes. OBJECTIVE:The aim of this study was to develop and evaluate the usability and content quality of NoteAid, a Web-based natural language processing system that links medical terms in EHR notes to lay definitions, that is, definitions easily understood by lay people. METHODS:NoteAid incorporates two core components: CoDeMed, a lexical resource of lay definitions for medical terms, and MedLink, a computational unit that links medical terms to lay definitions. We developed innovative computational methods, including an adapted distant supervision algorithm to prioritize medical terms important for EHR comprehension to facilitate the effort of building CoDeMed. Ten physician domain experts evaluated the user interface and content quality of NoteAid. The evaluation protocol included a cognitive walkthrough session and a postsession questionnaire. Physician feedback sessions were audio-recorded. We used standard content analysis methods to analyze qualitative data from these sessions. RESULTS:Physician feedback was mixed. Positive feedback on NoteAid included (1) Easy to use, (2) Good visual display, (3) Satisfactory system speed, and (4) Adequate lay definitions. Opportunities for improvement arising from evaluation sessions and feedback included (1) improving the display of definitions for partially matched terms, (2) including more medical terms in CoDeMed, (3) improving the handling of terms whose definitions vary depending on different contexts, and (4) standardizing the scope of definitions for medicines. On the basis of these results, we have improved NoteAid's user interface and a number of definitions, and added 4502 more definitions in CoDeMed. CONCLUSIONS:Physician evaluation yielded useful feedback for content validation and refinement of this innovative tool that has the potential to improve patient EHR comprehension and experience using patient portals. Future ongoing work will develop algorithms to handle ambiguous medical terms and test and evaluate NoteAid with patients.
| S-EPMC5799720 | biostudies-literature
Project description:BackgroundEHR systems are widely used in hospitals and primary care centres but it is usually difficult to share information and to collect patient data for clinical research. This is partly due to the different proprietary information models and inconsistent data quality. Our objective was to provide a more flexible solution enabling the clinicians to define which data to be recorded and shared for both routine documentation and clinical studies. The data should be possible to reuse through a common set of variable definitions providing a consistent nomenclature and validation of data. Another objective was that the templates used for the data entry and presentation should be possible to use in combination with the existing EHR systems.MethodsWe have designed and developed a template based system (called Julius) that was integrated with existing EHR systems. The system is driven by the medical domain knowledge defined by clinicians in the form of templates and variable definitions stored in a common data repository. The system architecture consists of three layers. The presentation layer is purely web-based, which facilitates integration with existing EHR products. The domain layer consists of the template design system, a variable/clinical concept definition system, the transformation and validation logic all implemented in Java. The data source layer utilizes an object relational mapping tool and a relational database.ResultsThe Julius system has been implemented, tested and deployed to three health care units in Stockholm, Sweden. The initial responses from the pilot users were positive. The template system facilitates patient data collection in many ways. The experience of using the template system suggests that enabling the clinicians to be in control of the system, is a good way to add supplementary functionality to the present EHR systems.ConclusionThe approach of the template system in combination with various local EHR systems can facilitate the sharing and reuse of validated clinical information from different health care units. However, future system developments for these purposes should consider using the openEHR/CEN models with shareable archetypes.
| S-EPMC1868711 | biostudies-literature
Project description:Background and study aims
The Federal Ministry of Education and Research (BMBF) has funded the development of a patient controlled “Personal Electronic Health Record” (PEPA) as part of their current INFOPAT project. PEPA allows for the exchange of medical data between all interested groups, including the patients thenselves. A PEPA contains medical reports and findings including, for example, x-rays, CT scans and MRIs. The patients can safeguard their information and access all content. The aim of this study is to test the PEPA-prototype for cancer patients being treated at the National Center for Tumor Diseases (NCT) in Heidelberg.
Who can participate?
Adult colorectal cancer patients being treated at the National Center for Tumor Diseases (NCT) in Heidelberg.
What does the study involve?
There are two part to this study. The first part involves focus groups, in which a group of people are asked their opinion and attitudes towards, for example, an idea, product or service. Here, focus groups are set up that involve the patients, doctors and other health professionals to discuss current problems with the coordination of care offered to cancer patients, as well as discuss what people want to get from using PEPA (i.e. user requirements). The PEPA-prototype is then developed taking into account the conclusions from the focus groups. In the second part of the study, patients are encouraged to use the PEPA-prototype to prepare and follow up meetings with their physicians.
| 2424890 | ecrin-mdr-crc
Project description:Background: Research increasingly shows how selective and targeted use of technology within care and welfare can have several advantages including improved quality of care and active user involvement. Purpose: The current overview of reviews aims to summarize the research on the effectiveness of technology for mental health and wellbeing. The goal is to highlight and structure the diverse combinations of technologies and interventions used so far, rather than to summarize the effectiveness of singular approaches. Methods: The current overview includes reviews published in the past five years with a focus on effectiveness of digital and technological interventions targeting mental health and wellbeing. Results: A total of 246 reviews could be included. All reviews examined the effectiveness of digital and technological interventions in the context of care and welfare. A combination of two taxonomies was created through qualitative analysis, based on the retrieved interventions and technologies in the reviews. Review classification shows a predominance of reviews on psychotherapeutic interventions using computers and smartphones. It is furthermore shown that when smartphone applications as stand-alone technology are researched, the primary focus is on self-help, and that extended reality is the most researched emerging technology to date. Conclusion: This overview of reviews shows that a wide range of interventions and technologies, with varying focus and target populations, have been studied in the field of care and wellbeing. The current overview of reviews is a first step to add structure to this rapidly changing field and may guide both researchers and clinicians in further exploring the evidence-base of particular approaches.
| S-EPMC8732948 | biostudies-literature
Project description:Background With the widespread adoption of electronic health records (EHRs), there is a growing awareness of problems in EHR training for new users and subsequent problems with the quality of information present in EHR-generated progress notes. By standardizing the case, simulation allows for the discovery of EHR patterns of use as well as a modality to aid in EHR training. Objective To develop a high-fidelity EHR training exercise for internal medicine interns to understand patterns of EHR utilization in the generation of daily progress notes. Methods Three months after beginning their internship, 32 interns participated in an EHR simulation designed to assess patterns in note writing and generation. Each intern was given a simulated chart and instructed to create a daily progress note. Notes were graded for use of copy-paste, macros, and accuracy of presented data. Results A total of 31 out of 32 interns (97%) completed the exercise. There was wide variance in use of macros to populate data, with multiple macro types used for the same data category. Three-quarters of notes contained either copy-paste elements or the elimination of active medical problems from the prior days' notes. This was associated with a significant number of quality issues, including failure to recognize a lack of deep vein thrombosis prophylaxis, medications stopped on admission, and issues in prior discharge summary. Conclusions Interns displayed wide variation in the process of creating progress notes. Additional studies are being conducted to determine the impact EHR-based simulation has on standardization of note content.
| S-EPMC4857515 | biostudies-literature
Project description:BackgroundElectronic 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.ObjectiveThe 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.MethodsWe 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.ResultsWe 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.ConclusionsThe 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.
| S-EPMC10757236 | biostudies-literature