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.

International Comparison of Six Basic eHealth Indicators Across 14 Countries: An eHealth Benchmarking Study.

BACKGROUND: Many countries adopt eHealth applications to support patient-centered care. Through information exchange, these eHealth applications may overcome institutional data silos and support holistic and ubiquitous (regional or national) information logistics. Available eHealth indicators mostly describe usage and acceptance of eHealth in a country. The eHealth indicators focusing on the cross-institutional availability of patient-related information for health care professionals, patients, and care givers are rare. OBJECTIVES: This study aims to present eHealth indicators on cross-institutional availability of relevant patient data for health care professionals, as well as for patients and their caregivers across 14 countries (Argentina, Australia, Austria, Finland, Germany, Hong Kong as a special administrative region of China, Israel, Japan, Jordan, Kenya, South Korea, Sweden, Turkey, and the United States) to compare our indicators and the resulting data for the examined countries with other eHealth benchmarks and to extend and explore changes to a comparable survey in 2017. We defined "availability of patient data" as the ability to access data in and to add data to the patient record in the respective country. METHODS: The invited experts from each of the 14 countries provided the indicator data for their country to reflect the situation on August 1, 2019, as date of reference. Overall, 60 items were aggregated to six eHealth indicators. RESULTS: Availability of patient-related information varies strongly by country. Health care professionals can access patients' most relevant cross-institutional health record data fully in only four countries. Patients and their caregivers can access their health record data fully in only two countries. Patients are able to fully add relevant data only in one country. Finland showed the best outcome of all eHealth indicators, followed by South Korea, Japan, and Sweden. CONCLUSION: Advancement in eHealth depends on contextual factors such as health care organization, national health politics, privacy laws, and health care financing. Improvements in eHealth indicators are thus often slow. However, our survey shows that some countries were able to improve on at least some indicators between 2017 and 2019. We anticipate further improvements in the future.

Register-Based Research of Adverse Events Revealing Incomplete Records Threatening Patient Safety.

Inadequate, missing or incorrect patient information is usually related to poor documentation. It has several negative effects on patient care processes, and, thus to quality of care, care continuity, and patient safety. It is one of the causes of patient claims. The aim of this study was to analyze patient safety reports and to find out which documentation hazards are damaging to patient safety. Data consisted of the patient incident reports (n=82 353) from seven health and social care areas from 2007-2016 in Finland. A descriptive analysis was conducted to explore the type of service provider and incidents reporting risks in patient data management and documentation. Adverse events due to patient data management and documentation were unusual; however, 18 cases were documented where patients suffered serious harm. Nearly half of the reports resulted from inadequate, missing or incorrect information. Uniform structures, documentation, and service processes need to be developed.

Reporting medical device safety incidents to regulatory authorities: An analysis and classification of technology-induced errors.

The European Union Medical Device Directive 2007/47/EC1 defines software with a medical purpose as a medical device. The implementation of health information technology suffers from patient safety problems that require effective post-market surveillance. The purpose of this study was to review, classify and discuss the incident data submitted to a nationwide database of the Finnish National Competent Authority with other forms of data. We analysed incident reports submitted to the authority database by users of electronic health records from 2010 to 2015. We identified 138 valid reports. Adverse events associated with electronic health record vulnerabilities, clustered around certain error types, cause serious harm and occur in all types of healthcare settings. The low rate of reported incidents raises questions about not only the challenges associated with medical software oversight but also the obstacles for reporting.

Lack of Patient Data Privacy Challenges Patient Safety.

Patient data privacy is emphasized due to increase in electronic health data processing. This paper highlights the importance of data privacy in healthcare and its connection to the European Union's (EU) General Data Protection Regulation, which aims to protect all EU citizens from privacy and data violations. The clinical environment is prone to hazards in information management, especially in care coordination, the management of patient data, and verbal communication. The Swiss cheese model was used to discuss the importance of patient data privacy based on statistics from a national patient safety incident registry. Patient identification proved an important factor leading to hazards that can cause severe harm to patients.

Differences between serious and nonserious patient safety incidents in the largest hospital district in Finland.

OBJECTIVES: To determine if and in what ways serious patient safety incidents differ from nonserious patient safety incidents. METHODS: Statistical analysis was performed on patient safety incident reports that were reported in 2015 in Finland's largest hospital district (Helsinki and Uusimaa, HUS). Reports were divided into two groups: nonserious incidents and serious incidents. Differences between groups were studied from several types of categorically divided information. RESULTS: Of the total number of reports (15,863), 1% were serious incidents (175). Serious and nonserious incidents differed significantly from each other. Serious incidents concerning laboratory, imaging, or medical equipment were more common. On the other hand, incidents concerning medication, infusion, and blood transfusion were less frequent. In serious incidents, the proportion of doctors reporting was greater, and contributing factors were better recognized, the most common being working of procedures. CONCLUSIONS: In the future, special attention should be given to the particular aspects of serious patient safety incidents, such as safe use of medical equipment, training, and handling of procedures. Root cause analysis is an effective way to handle serious incidents and enables the prevention of their reoccurrence. However, a systematic follow-up of the root cause analysis should be developed.

An analysis of electronic health record-related patient safety incidents.

The aim of this study was to analyse electronic health record-related patient safety incidents in the patient safety incident reporting database in fully digital hospitals in Finland. We compare Finnish data to similar international data and discuss their content with regard to the literature. We analysed the types of electronic health record-related patient safety incidents that occurred at 23 hospitals during a 2-year period. A procedure of taxonomy mapping served to allow comparisons. This study represents a rare examination of patient safety risks in a fully digital environment. The proportion of electronic health record-related incidents was markedly higher in our study than in previous studies with similar data. Human-computer interaction problems were the most frequently reported. The results show the possibility of error arising from the complex interaction between clinicians and computers.

A Comparison of Two Principal Systems for Monitoring of Technology-Induced Errors in Electronic Health Records.

Current methods for monitoring harm caused by health information technology (HIT) are minimal, even if there are known risks associated with the use of HIT. Monitoring is predominantly based on voluntary reporting using generic patient safety adverse events reporting systems. Another important means for monitoring technology-induced errors is a health authority reporting system. International oversight systems have medical devices' related software's adverse event and failure reporting models, but these systems differ due to differencies in the legislation. The protocol for this study included an electronic database literature search and the eliciting of information for study purposes from the literature. The purpose is to provide a scoping review focused on two types of systems and provide implications for monitoring technology-induced errors in the future. The analysis revealed not only differences, but also similarities between these systems which raises the question of these systems' effectiveness due to overlapping goals in collecting data.

FIN-TIERA: A Tool for Assessing Technology Induced Errors.

BACKGROUND: Due to the complexity of healthcare processes, the potential for Health Information Systems (HIS) to cause technology-induced errors is a growing concern. Health Information Technology (HIT) errors nearly always threaten good patient care and can lead to patient harm. Instruments to allow hospitals to proactively identify areas of Electronic Health Records (EHR) safety, to set priorities and to intervene before incidents occur are currently underdeveloped. OBJECTIVES: The aim was to design a Finnish questionnaire to measure EHR users' perceptions of common EHR-related safety concerns in a specialized hospital district context through the lens of the theory of socio-technical dimensions. Moreover, the aim was to measure its reliability by assessing its internal consistency and validity, namely its content and construct validity. METHODS: We constructed the instrument, based on the socio-technical theory and Sittig and Singh's study findings, through a multi-stage process, and expert panels evaluated it to ensure its content validity. The final questionnaire consisted of eight error types to be assessed on a qualitative risk matrix scale. We used a cross-sectional design to test its psychometric properties. Application of the FIN-TIERA Questionnaire to a sample of 2864 clinicians in 2015 then served to evaluate the instrument's reliability as well as its construct validity. RESULTS: All eight multi-item scales showed high internal consistency (range α >  0.798-0.932 and CR 0.845-0.983). The average variance extracted (AVE) served to assess the confirmatory factor analysis (CFA). The results of the model fit with AGFI = .86, CFI = .898, RMSEA = .052, SRMR = .048 were deemed acceptable. For all factors, AVE yielded values > 0.5, which indicates adequate convergence and supports convergent validity. Discriminant validity was established for five out of a total of eight latent variables. CONCLUSIONS: FIN-TIERA is a new multi-dimensional instrument which may be a useful tool for assessing risk in EHR. Our testing shows its potential for use in-hospital settings: the involvement of EHR users demonstrated initial reliability and validity. Further research is recommended to assess the instrument's psychometric properties.

Reducing Technology-Induced Errors: Organizational and Health Systems Approaches.

Technology-induced errors are a growing concern for health care organizations. Such errors arise from the interaction between healthcare and information technology deployed in complex settings and contexts. As the number of health information technologies that are used to provide patient care rises so will the need to develop ways to improve the quality and safety of the technology that we use. The objective of the panel is to describe varying approaches to improving software safety from and organizational and health systems perspective. We define what a technology-induced error is. Then, we discuss how software design and testing can be used to improve health information technologies. This discussion is followed by work in the area of monitoring and reporting at a health district and national level. Lastly, we draw on the quality, safety and resilience literature. The target audience for this work are nursing and health informatics researchers, practitioners, administrators, policy makers and students.

Electronic Health Record-Related Safety Concerns: A Cross-Sectional Survey of Electronic Health Record Users.

BACKGROUND: The rapid expansion in the use of electronic health records (EHR) has increased the number of medical errors originating in health information systems (HIS). The sociotechnical approach helps in understanding risks in the development, implementation, and use of EHR and health information technology (HIT) while accounting for complex interactions of technology within the health care system. OBJECTIVE: This study addresses two important questions: (1) "which of the common EHR error types are associated with perceived high- and extreme-risk severity ratings among EHR users?", and (2) "which variables are associated with high- and extreme-risk severity ratings?" METHODS: This study was a quantitative, non-experimental, descriptive study of EHR users. We conducted a cross-sectional web-based questionnaire study at the largest hospital district in Finland. Statistical tests included the reliability of the summative scales tested with Cronbach's alpha. Logistic regression served to assess the association of the independent variables to each of the eight risk factors examined. RESULTS: A total of 2864 eligible respondents provided the final data. Almost half of the respondents reported a high level of risk related to the error type "extended EHR unavailability". The lowest overall risk level was associated with "selecting incorrectly from a list of items". In multivariate analyses, profession and clinical unit proved to be the strongest predictors for high perceived risk. Physicians perceived risk levels to be the highest ( P<.001 in six of eight error types), while emergency departments, operating rooms, and procedure units were associated with higher perceived risk levels ( P<.001 in four of eight error types). Previous participation in eLearning courses on EHR-use was associated with lower risk for some of the risk factors. CONCLUSIONS: Based on a large number of Finnish EHR users in hospitals, this study indicates that HIT safety hazards should be taken very seriously, particularly in operating rooms, procedure units, emergency departments, and intensive care units/critical care units. Health care organizations should use proactive and systematic assessments of EHR risks before harmful events occur. An EHR training program should be compulsory for all EHR users in order to address EHR safety concerns resulting from the failure to use HIT appropriately.