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

Background: 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. Objective: 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? Methods: 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. Results: 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). Conclusions: 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.

Systematized Nomenclature of Medicine-Clinical Terminology (SNOMED CT) Clinical Use Cases in the Context of Electronic Health Record Systems: Systematic Literature Review.

BACKGROUND: The Systematized Medical Nomenclature for Medicine-Clinical Terminology (SNOMED CT) is a clinical terminology system that provides a standardized and scientifically validated way of representing clinical information captured by clinicians. It can be integrated into electronic health records (EHRs) to increase the possibilities for effective data use and ensure a better quality of documentation that supports continuity of care, thus enabling better quality in the care process. Even though SNOMED CT consists of extensively studied clinical terminology, previous research has repeatedly documented a lack of scientific evidence for SNOMED CT in the form of reported clinical use cases in electronic health record systems. OBJECTIVE: The aim of this study was to explore evidence in previous literature reviews of clinical use cases of SNOMED CT integrated into EHR systems or other clinical applications during the last 5 years of continued development. The study sought to identify the main clinical use purposes, use phases, and key clinical benefits documented in SNOMED CT use cases. METHODS: The Cochrane review protocol was applied for the study design. The application of the protocol was modified step-by-step to fit the research problem by first defining the search strategy, identifying the articles for the review by isolating the exclusion and inclusion criteria for assessing the search results, and lastly, evaluating and summarizing the review results. RESULTS: In total, 17 research articles illustrating SNOMED CT clinical use cases were reviewed. The use purpose of SNOMED CT was documented in all the articles, with the terminology as a standard in EHR being the most common (8/17). The clinical use phase was documented in all the articles. The most common category of use phases was SNOMED CT in development (6/17). Core benefits achieved by applying SNOMED CT in a clinical context were identified by the researchers. These were related to terminology use outcomes, that is, to data quality in general or to enabling a consistent way of indexing, storing, retrieving, and aggregating clinical data (8/17). Additional benefits were linked to the productivity of coding or to advances in the quality and continuity of care. CONCLUSIONS: While the SNOMED CT use categories were well supported by previous research, this review demonstrates that further systematic research on clinical use cases is needed to promote the scalability of the review results. To achieve the best out-of-use case reports, more emphasis is suggested on describing the contextual factors, such as the electronic health care system and the use of previous frameworks to enable comparability of results. A lesson to be drawn from our study is that SNOMED CT is essential for structuring clinical data; however, research is needed to gather more evidence of how SNOMED CT benefits clinical care and patient safety.

Preliminary Exploration of Main Elements for Systematic Classification Development: Case Study of Patient Safety Incidents.

BACKGROUND: Currently, there is no holistic theoretical approach available for guiding classification development. On the basis of our recent classification development research in the area of patient safety in health information technology, this focus area would benefit from a more systematic approach. Although some valuable theoretical and methodological approaches have been presented, classification development literature typically is limited to methodological development in a specific domain or is practically oriented. OBJECTIVE: The main purposes of this study are to fill the methodological gap in classification development research by exploring possible elements of systematic development based on previous literature and to promote sustainable and well-grounded classification outcomes by identifying a set of recommended elements. Specifically, the aim is to answer the following question: what are the main elements for systematic classification development based on research evidence and our use case? METHODS: This study applied a qualitative research approach. On the basis of previous literature, preliminary elements for classification development were specified, as follows: defining a concept model, documenting the development process, incorporating multidisciplinary expertise, validating results, and maintaining the classification. The elements were compiled as guiding principles for the research process and tested in the case of patient safety incidents (n=501). RESULTS: The results illustrate classification development based on the chosen elements, with 4 examples of technology-induced errors. Examples from the use case regard usability, system downtime, clinical workflow, and medication section problems. The study results confirm and thus suggest that a more comprehensive and theory-based systematic approach promotes well-grounded classification work by enhancing transparency and possibilities for assessing the development process. CONCLUSIONS: We recommend further testing the preliminary main elements presented in this study. The research presented herein could serve as a basis for future work. Our recently developed classification and the use case presented here serve as examples. Data retrieved from, for example, other type of electronic health records and use contexts could refine and validate the suggested methodological approach.

Classification of Electronic Health Record-Related Patient Safety Incidents: Development and Validation Study.

BACKGROUND: It is assumed that the implementation of health information technology introduces new vulnerabilities within a complex sociotechnical health care system, but no international consensus exists on a standardized format for enhancing the collection, analysis, and interpretation of technology-induced errors. OBJECTIVE: This study aims to develop a classification for patient safety incident reporting associated with the use of mature electronic health records (EHRs). It also aims to validate the classification by using a data set of incidents during a 6-month period immediately after the implementation of a new EHR system. METHODS: The starting point of the classification development was the Finnish Technology-Induced Error Risk Assessment Scale tool, based on research on commonly recognized error types. A multiprofessional research team used iterative tests on consensus building to develop a classification system. The final classification, with preliminary descriptions of classes, was validated by applying it to analyze EHR-related error incidents (n=428) during the implementation phase of a new EHR system and also to evaluate this classification's characteristics and applicability for reporting incidents. Interrater agreement was applied. RESULTS: The number of EHR-related patient safety incidents during the implementation period (n=501) was five-fold when compared with the preimplementation period (n=82). The literature identified new error types that were added to the emerging classification. Error types were adapted iteratively after several test rounds to develop a classification for reporting patient safety incidents in the clinical use of a high-maturity EHR system. Of the 427 classified patient safety incidents, interface problems accounted for 96 (22.5%) incident reports, usability problems for 73 (17.1%), documentation problems for 60 (14.1%), and clinical workflow problems for 33 (7.7%). Altogether, 20.8% (89/427) of reports were related to medication section problems, and downtime problems were rare (n=8). During the classification work, 14.8% (74/501) of reports of the original sample were rejected because of insufficient information, even though the reports were deemed to be related to EHRs. The interrater agreement during the blinded review was 97.7%. CONCLUSIONS: This study presents a new classification for EHR-related patient safety incidents applicable to mature EHRs. The number of EHR-related patient safety incidents during the implementation period may reflect patient safety challenges during the implementation of a new type of high-maturity EHR system. The results indicate that the types of errors previously identified in the literature change with the EHR development cycle.

Harmonization of Finnish Vaccination Data.

Vaccination information is needed at individual and at population levels, as it is an important part of public health measures. In Finland, a vaccination data structure has been developed for centralized information services that include patient access to information. Harmonization of data with national vaccination registry is ongoing. New requirements for vaccination certificates have emerged because of COVID-19 pandemic. We explore, what is the readiness of Finnish development of vaccination data structures and what can be learned from Finnish harmonization efforts in order to accomplish required level of interoperability.

The European Cross-Border Health Data Exchange: Focus on Clinically Relevant Data.

The eHealth Digital Service Infrastructure (eHDSI) is an infrastructure ensuring the continuity of care for European citizens while they are travelling abroad in the EU. We present the Finnish readiness of implementing datasets of diagnosis, vaccinations and medication summary in a case study, and discuss challenges emerging from the national perspective. International harmonized standards are a key element in the smooth development of European information exchange.

Electronic Health Record System-Related Patient Safety Incidents - How to Classify Them?

The implementation of electronic health record systems (EHRs) may cause multidimensional patient safety issues that deserve research attention. Our research aims to identify the current body of evidence on EHRs-related incident types and how incidents are classified in these studies. A literature search resulted in 44 peer-reviewed papers and six papers were included in the final analysis. The error types do not concern solely the technological features of the EHRs but may involve also non-technical aspects. Our review indicates that standard classification systems would facilitate comparisons across countries. To achieve the goal, more research evidence, testing and development of classifications are required.

Typology-Based Analysis of Covid-19 Mobile Applications: Implications for Patient Empowerment.

During COVID-19 pandemic, mobile technology is seen as potential tool for epidemic control and citizens' empowerment. Based on literature, we explore, which are the currently known types of the mobile apps and what implications do the apps have for patient empowerment. There is a need for evidence and an assessment framework to ensure that COVID-19 apps deliver on their promises.

Literature Review of Patient Record Structures from the Physician's Perspective.

The Finnish Patient Data Repository is a nationwide electronic health record (EHR) system collecting patient data from all healthcare providers. The usefulness of the large amount of data stored in the system depends on the underlying data structures, and thus a solid understanding of these structures is in focus in further development of the data repository. This study seeks to improve that understanding by a systematic literature review. The review takes the physician's perspective to the use and usefulness of the data structures. The articles included in this review study data structures intended to be used in the actual care process. Secondary use and nursing aspects have been covered in separate reviews. After applying the predefined inclusion and exclusion criteria only 40 articles were included in the review. The research on widespread systems in everyday use was especially scarce, most studies concentrated on narrow fields. Majority of these studies were primarily developed for specialist use in secondary care units. Most structures or applications studied were at an early stage of development. In many applications the use of structured data was found to improve the completeness of the documented data and facilitate its automated use. However, there seem to be some applications where narrative text cannot be easily replaced by structured data. Usability results regarding structured representation were conflicting. The scattered nature and paucity of research hinders the generalizability of the findings, and from the system design or implementation point of view the practical value of the scientific literature reviewed is limited.

Impacts of structuring the electronic health record: Results of a systematic literature review from the perspective of secondary use of patient data.

PURPOSE: To explore the impacts that structuring of electronic health records (EHRs) has had from the perspective of secondary use of patient data as reflected in currently published literature. This paper presents the results of a systematic literature review aimed at answering the following questions; (1) what are the common methods of structuring patient data to serve secondary use purposes; (2) what are the common methods of evaluating patient data structuring in the secondary use context, and (3) what impacts or outcomes of EHR structuring have been reported from the secondary use perspective. METHODS: The reported study forms part of a wider systematic literature review on the impacts of EHR structuring methods and evaluations of their impact. The review was based on a 12-step systematic review protocol adapted from the Cochrane methodology. Original articles included in the study were divided into three groups for analysis and reporting based on their use focus: nursing documentation, medical use and secondary use (presented in this paper). The analysis from the perspective of secondary use of data includes 85 original articles from 1975 to 2010 retrieved from 15 bibliographic databases. RESULTS: The implementation of structured EHRs can be roughly divided into applications for documenting patient data at the point of care and application for retrieval of patient data (post hoc structuring). Two thirds of the secondary use articles concern EHR structuring methods which were still under development or in the testing phase. METHODS: of structuring patient data such as codes, terminologies, reference information models, forms or templates and documentation standards were usually applied in combination. Most of the identified benefits of utilizing structured EHR data for secondary use purposes concentrated on information content and quality or on technical quality and reliability, particularly in the case of Natural Language Processing (NLP) studies. A few individual articles evaluated impacts on care processes, productivity and costs, patient safety, care quality or other health impacts. In most articles these endpoints were usually discussed as goals of secondary use and less as evidence-supported impacts, resulting from the use of structured EHR data for secondary purposes. CONCLUSIONS: Further studies and more sound evaluation methods are needed for evidence on how EHRs are utilized for secondary purposes, and how structured documentation methods can serve different users' needs, e.g. administration, statistics and research and development, in parallel to medical use purposes.

Towards Citizen-Centred Care: Interim Results from an E-Prescription Case.

Medication data is a crucial part of patient data. Medication data is stored in a centralized archive, and made accessible to health care professionals and citizens. Re-usability of medication data requires it to be not only interoperable, but also complete and reliable. We evaluated e-prescription data stored in a national archive. The data consists of 596 patients with 76411 e-prescriptions. The interim results show the data to be complete when stored, whereas data reliability would require more user training.

Secondary use of structured patient data: interim results of a systematic review.

In addition to patient care, EHR data are increasingly in demand for secondary purposes, e.g. administration, research and enterprise resource planning. We conducted a systematic literature review and subsequent analysis of 85 articles focusing on the secondary use of structured patient records. We grounded the analysis on how patient records have been structured, how these structures have been evaluated and what are the main results achieved from the secondary use viewpoint. We conclude that secondary use requires complete and interoperable patient records, which in turn depend on better alignment of primary and secondary users' needs and benefits.

Improving health care service delivery with a national code service.

An implementation of eHealth services including a national code service is ongoing in Finland. The code service shares and maintains all common codes and data structures used in electronic patient records. In this paper, we describe the code service process and the challenges of developing the process as a part of national eHealth services.

Impacts of structuring the electronic health record: a systematic review protocol and results of previous reviews.

PURPOSE: This paper (1) presents the protocol of an on-going systematic literature review on the methods of structuring electronic health record (EHR) data and studying the impacts of implemented structures, thus laying basis for the analysis of the empirical articles (2) describes previous reviews published on the subject and retrieved during the search of bibliographic databases, and (3) presents a summary of the results of previous reviews. METHODS: Cochrane instructions were exploited to outline the review protocol - phases and search elements. Test searches were conducted to refine the search. The abstracts and/or full texts of review papers captured by the search were read by two of the team members independently, with disagreements first negotiated between them and if necessary eventually resolved in the team meetings. Additional review articles were picked from the reference lists of the reviews included in our search results. The elements defined in the search strategy and analytic framework were converted to a data extraction tool, which was tested by extracting data from the reviews captured by the search. Descriptive analysis of the extracted data was conducted. RESULTS: The 12-stage review protocol that we developed includes definition of the problem, the search strategy and search terms, testing the strategy, conducting the search, updating search from references found, removing duplicates, defining the inclusion and exclusion criteria, exclusion and inclusion of papers, definition of the analytic framework to extract data, extracting data and reporting results. Our searches in fifteen electronic bibliographic databases retrieved 27 reviews, of which 14 were included for full text analysis. Of these, 11 focused on medical and three on nursing record structures. The data structures included forms, ontologies, classifications and terminologies. Some evidence was found on data structure impact on information quality, process quality and efficiency, but not on patients or professionals. CONCLUSIONS: The 12 step review protocol resulted in a variety of reviews of different ways to structure EHR data. None of them compared outcomes of different structuring methods; all had a narrower definition of the Intervention (a specific EHR structure) and Outcome (a specific impact category). Several reviews missed a clear connection between the data structures (interventions) and outcomes, indicating that the methods and applications for structuring patient data have rarely been viewed as independent variables. The review protocol should be defined in a manner that allows replication of the review. There are different ways of structuring patient data with varying impacts, which should be distinguished in further empirical studies, as well as reviews.

Issue orders and discontinued EPR.

Users gave us 104 different reasons for the failure of implementing an EPR in a surgical clinic. We classify the reasons with the issue order model, where the first issue level is for simple and technical issues, the second one for more complex and combined issues, and the third one for political or ideological issues. However, what appears as a first order issue to a manager might be seen as an insurmountable third order issue for a worker and vice versa. The issues are interrelated, and solving one issue might have a substantial influence on other issues. Also, the issues seemed to accumulate and concentrate on points. The analysis helps focus on key problems, with consideration to related issues.