Towards an Interoperability Landscape for a National Research Data Infrastructure for Personal Health Data.

The German initiative "National Research Data Infrastructure for Personal Health Data" (NFDI4Health) focuses on research data management in health research. It aims to foster and develop harmonized informatics standards for public health, epidemiological studies, and clinical trials, facilitating access to relevant data and metadata standards. This publication lists syntactic and semantic data standards of potential use for NFDI4Health and beyond, based on interdisciplinary meetings and workshops, mappings of study questionnaires and the NFDI4Health metadata schema, and literature search. Included are 7 syntactic, 32 semantic and 9 combined syntactic and semantic standards. In addition, 101 ISO Standards from ISO/TC 215 Health Informatics and ISO/TC 276 Biotechnology could be identified as being potentially relevant. The work emphasizes the utilization of standards for epidemiological and health research data ensuring interoperability as well as the compatibility to NFDI4Health, its use cases, and to (inter-)national efforts within these sectors. The goal is to foster collaborative and inter-sectoral work in health research and initiate a debate around the potential of using common standards.

Artificial Intelligence Bias in Health Care: Web-Based Survey.

BACKGROUND: Resources are increasingly spent on artificial intelligence (AI) solutions for medical applications aiming to improve diagnosis, treatment, and prevention of diseases. While the need for transparency and reduction of bias in data and algorithm development has been addressed in past studies, little is known about the knowledge and perception of bias among AI developers. OBJECTIVE: This study's objective was to survey AI specialists in health care to investigate developers' perceptions of bias in AI algorithms for health care applications and their awareness and use of preventative measures. METHODS: A web-based survey was provided in both German and English language, comprising a maximum of 41 questions using branching logic within the REDCap web application. Only the results of participants with experience in the field of medical AI applications and complete questionnaires were included for analysis. Demographic data, technical expertise, and perceptions of fairness, as well as knowledge of biases in AI, were analyzed, and variations among gender, age, and work environment were assessed. RESULTS: A total of 151 AI specialists completed the web-based survey. The median age was 30 (IQR 26-39) years, and 67% (101/151) of respondents were male. One-third rated their AI development projects as fair (47/151, 31%) or moderately fair (51/151, 34%), 12% (18/151) reported their AI to be barely fair, and 1% (2/151) not fair at all. One participant identifying as diverse rated AI developments as barely fair, and among the 2 undefined gender participants, AI developments were rated as barely fair or moderately fair, respectively. Reasons for biases selected by respondents were lack of fair data (90/132, 68%), guidelines or recommendations (65/132, 49%), or knowledge (60/132, 45%). Half of the respondents worked with image data (83/151, 55%) from 1 center only (76/151, 50%), and 35% (53/151) worked with national data exclusively. CONCLUSIONS: This study shows that the perception of biases in AI overall is moderately fair. Gender minorities did not once rate their AI development as fair or very fair. Therefore, further studies need to focus on minorities and women and their perceptions of AI. The results highlight the need to strengthen knowledge about bias in AI and provide guidelines on preventing biases in AI health care applications.

Fetal Echocardiography in Predicting Postnatal Outcome in Borderline Left Ventricle.

OBJECTIVES: Prenatal prediction of postnatal univentricular versus biventricular circulation in patients with borderline left ventricle (bLV) remains challenging. This study investigated prenatal fetal echocardiographic parameters and postnatal outcome of patients with a prenatally diagnosed bLV. METHODS: We report a retrospective study of bLV patients at four prenatal centers with a follow-up of one year. BLV was defined as z-scores of the left ventricle (LV) between -2 and -4. Single-ventricle palliation (SVP), biventricular repair (BVR), and no surgical or catheter-based intervention served as the dependent outcome. Prenatal ultrasound parameters were used as independent variables. Cut-off values from receiver operating characteristic curves (ROC) were determined for significant discrimination between outcomes. RESULTS: A total of 54 patients were diagnosed with bLV from 2010 to 2018. All were live births. Out of the entire cohort, 8 (15 %) received SVP, 34 (63 %) BVR, and 12 (22 %) no intervention. There was no significant difference with regard to genetic or extracardiac anomalies. There were significantly more patients with endocardial fibroelastosis (EFE) in the SVP group compared to the BVR group (80 % vs. 10 %), (p < 0.001). Apex-forming LV (100 % vs. 70 %) and lack of retrograde arch flow (20 % vs. 80 %) were associated with no intervention (p < 0.001). With respect to BVR vs. SVP, the LV sphericity index provided the highest specificity (91.7 %) using a cutoff value of ≤ 0.5. CONCLUSION: The majority of bLV patients maintained biventricular circulation. EFE, retrograde arch flow, and LV sphericity can be helpful parameters for counseling parents and further prospective studies can be developed.

Fast Healthcare Interoperability Resources (FHIR) for Interoperability in Health Research: Systematic Review.

BACKGROUND: The standard Fast Healthcare Interoperability Resources (FHIR) is widely used in health information technology. However, its use as a standard for health research is still less prevalent. To use existing data sources more efficiently for health research, data interoperability becomes increasingly important. FHIR provides solutions by offering resource domains such as "Public Health & Research" and "Evidence-Based Medicine" while using already established web technologies. Therefore, FHIR could help standardize data across different data sources and improve interoperability in health research. OBJECTIVE: The aim of our study was to provide a systematic review of existing literature and determine the current state of FHIR implementations in health research and possible future directions. METHODS: We searched the PubMed/MEDLINE, Embase, Web of Science, IEEE Xplore, and Cochrane Library databases for studies published from 2011 to 2022. Studies investigating the use of FHIR in health research were included. Articles published before 2011, abstracts, reviews, editorials, and expert opinions were excluded. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and registered this study with PROSPERO (CRD42021235393). Data synthesis was done in tables and figures. RESULTS: We identified a total of 998 studies, of which 49 studies were eligible for inclusion. Of the 49 studies, most (73%, n=36) covered the domain of clinical research, whereas the remaining studies focused on public health or epidemiology (6%, n=3) or did not specify their research domain (20%, n=10). Studies used FHIR for data capture (29%, n=14), standardization of data (41%, n=20), analysis (12%, n=6), recruitment (14%, n=7), and consent management (4%, n=2). Most (55%, 27/49) of the studies had a generic approach, and 55% (12/22) of the studies focusing on specific medical specialties (infectious disease, genomics, oncology, environmental health, imaging, and pulmonary hypertension) reported their solutions to be conferrable to other use cases. Most (63%, 31/49) of the studies reported using additional data models or terminologies: Systematized Nomenclature of Medicine Clinical Terms (29%, n=14), Logical Observation Identifiers Names and Codes (37%, n=18), International Classification of Diseases 10th Revision (18%, n=9), Observational Medical Outcomes Partnership common data model (12%, n=6), and others (43%, n=21). Only 4 (8%) studies used a FHIR resource from the domain "Public Health & Research." Limitations using FHIR included the possible change in the content of FHIR resources, safety, legal matters, and the need for a FHIR server. CONCLUSIONS: Our review found that FHIR can be implemented in health research, and the areas of application are broad and generalizable in most use cases. The implementation of international terminologies was common, and other standards such as the Observational Medical Outcomes Partnership common data model could be used as a complement to FHIR. Limitations such as the change of FHIR content, lack of FHIR implementation, safety, and legal matters need to be addressed in future releases to expand the use of FHIR and, therefore, interoperability in health research.

Implementing SNOMED CT in Open Software Solutions to Enhance the Findability of COVID-19 Questionnaires.

SNOMED CT fosters interoperability in healthcare and research. This use case implemented SNOMED CT for browsing COVID-19 questionnaires in the open-software solutions OPAL/MICA. We implemented a test server requiring files in a given YAML format for implementation of taxonomies with only two levels of hierarchy. Within this format, neither the implementation of SNOMED CT hierarchies and post-coordination nor the use of release files were possible. To solve this, Python scripts were written to integrate the required SNOMED CT concepts (Fully Specified Name, FSN and SNOMED CT Identifier, SCTID) into the YAML format (YAML Mode). Mappings of SNOMED CT to data items of the questionnaires had to be provided as Excel files for implementation into Opal/MICA and further Python scripts were established within the Excel Mode. Finally, a total of eight questionnaires containing 1.178 data items were successfully mapped to SNOMED CT and implemented in OPAL/MICA. This use case showed that implementing SNOMED CT for browsing COVID-19 questionnaires is feasible despite software solutions not supporting SNOMED CT. However, limitations of not being able to implement SNOMED CT release files and its provided hierarchy and post-coordination still have to be overcome.

Prenatal Diagnosis and Postnatal Outcome of Eight Cases with Criss-Cross Heart - A Multicenter Case Series.

OBJECTIVE: Criss-cross heart (CCH) is a rare congenital cardiac defect defined by crossing of ventricular inflow streams contributing to less than 0.1 % of all congenital heart anomalies. Due to its rarity and complexity, prenatal diagnosis in these patients remains challenging. We sought to describe prenatal findings and postnatal course in eight cases of prenatally diagnosed CCH. METHODS: This is a retrospective case series of prenatally diagnosed CCH in three centers between 2010-2017. We reviewed fetal echocardiograms as well as postnatal clinical charts and surgical reports. RESULTS: 8 cases of CCH were included. The median gestational age at diagnosis was 27 weeks. 7 patients were found with situs solitus, one fetus with situs ambiguous. In all patients, the four-chamber view was abnormal. There was atrioventricular discordance in half of the patients, while all patients showed ventriculoarterial discordance. All patients were found with additional cardiac anomalies, including ventricular septal defect, double outlet right ventricle, right aortic arch, atrial septal defect and pulmonary stenosis. Three patients underwent amniocentesis without pathological findings. All patients were born alive at a median gestational age of 38 + 2 weeks and survived our median follow-up of 181 days. CONCLUSION: CCH can be diagnosed prenatally by detailed fetal echocardiography when observing an abnormal four-chamber view with crossing of inflow streams into both ventricles and a lack of parallel orientation of the atrioventricular valve axis due to a clockwise or counterclockwise rotation of the ventricular mass along its axis. With the help of prenatal ultrasound, parental guidance and counselling as well as postnatal pediatric cardiac management can be warranted.

Fast Healthcare Interoperability Resources (FHIR) in a FAIR Metadata Registry for COVID-19 Research.

Adopting international standards within health research communities can elevate data FAIRness and widen analysis possibilities. The purpose of this study was to evaluate the mapping feasibility against HL7® Fast Healthcare Interoperability Resources® (FHIR)® of a generic metadata schema (MDS) created for a central search hub gathering COVID-19 health research (studies, questionnaires, documents = MDS resource types). Mapping results were rated by calculating the percentage of FHIR coverage. Among 86 items to map, total mapping coverage was 94%: 50 (58%) of the items were available as standard resources in FHIR and 31 (36%) could be mapped using extensions. Five items (6%) could not be mapped to FHIR. Analyzing each MDS resource type, there was a total mapping coverage of 93% for studies and 95% for questionnaires and documents, with 61% of the MDS items available as standard resources in FHIR for studies, 57% for questionnaires and 52% for documents. Extensions in studies, questionnaires and documents were used in 32%, 38% and 43% of items, respectively. This work shows that FHIR can be used as a standardized format in registries for clinical, epidemiological and public health research. However, further adjustments to the initial MDS are recommended - and two additional items even needed when implementing FHIR. Developing a MDS based on the FHIR standard could be a future approach to reduce data ambiguity and foster interoperability.

Evaluating Suitability of SNOMED CT in Structured Searches for COVID-19 Studies.

Studies investigating the suitability of SNOMED CT in COVID-19 datasets are still scarce. The purpose of this study was to evaluate the suitability of SNOMED CT for structured searches of COVID-19 studies, using the German Corona Consensus Dataset (GECCO) as example. Suitability of the international standard SNOMED CT was measured with the scoring system ISO/TS 21564, and intercoder reliability of two independent mapping specialists was evaluated. The resulting analysis showed that the majority of data items had either a complete or partial equivalent in SNOMED CT (complete equivalent: 141 items; partial equivalent: 63 items; no equivalent: 1 item). Intercoder reliability was moderate, possibly due to non-establishment of mapping rules and high percentage (74%) of different but similar concepts among the 86 non-equal chosen concepts. The study shows that SNOMED CT can be utilized for COVID-19 cohort browsing. However, further studies investigating mapping rules and further international terminologies are necessary.

Prenatal Diagnosis and Outcome of Congenital Corrected Transposition of the Great Arteries - A Multicenter Report of 69 Cases.

OBJECTIVE: Congenital corrected transposition of the great arteries (ccTGA) is a rare congenital cardiac anomaly which remains difficult to diagnose prenatally. We aim to investigate the natural history, associated anomalies and the outcome of patients in prenatally diagnosed ccTGA. METHOD: This was an international multicenter retrospective analysis of fetuses with a diagnosis of ccTGA from 2002 to 2017. We reviewed clinical and echocardiographic databases of seven centers. Anatomic survey and fetal echocardiography were performed according to international guidelines of ISUOG. RESULTS: We considered 69 fetuses with prenatally suspected ccTGA. There was an overall survival rate of 91 % among 54 patients with a confirmed diagnosis. Survival to live birth was 96 % (52/54) and survival on an intention-to-treat basis was 94 % (49/52). The mean gestational age at the time of diagnosis was 25.6 ±â€Š5.9 weeks of gestation. In 7 out of 54 fetuses (13 %), ccTGA was an isolated finding. Dextro/mesocardia was present in 15 cases (27.8 %). Intracardiac anomalies were present in 46/54 cases (85.2 %) with the most frequent anomaly being a ventricular septal defect present in 41 fetuses (75.9 %). Complete heart block was diagnosed in 10 cases (18.5 %). Extracardiac anomalies were observed in 9 out of 54 cases (16.7 %). Prenatal karyotyping of the fetus was available in 30/54 (55.6 %) cases with chromosomal anomalies in 4/30 (13.3 %). CONCLUSION: ccTGA is a rare cardiac anomaly often accompanied by a variable spectrum of further intracardiac abnormalities. Accurate diagnosis of ccTGA, which can be integrated into parental counselling, is feasible with a favorable short-term outcome for affected neonates.