[Development of competencies in the Medical Informatics Initiative (MII)-educational offers for a competent and secure handling of medical data]. / Kompetenzentwicklung in der Medizininformatik-Initiative (MII) ­ Lehrangebote für einen souveränen und sicheren Umgang mit medizinischen Daten.

In order to achieve the goals of the Medical Informatics Initiative (MII), staff with skills in the field of medical informatics and data science are required. Each consortium has established training activities. Further, cross-consortium activities have emerged. This article describes the concepts, implemented programs, and experiences in the consortia. Fifty-one new professorships have been established and 10 new study programs have been created: 1 bachelor's degree and 6 consecutive and 3 part-time master's degree programs. Further, learning and training opportunities can be used by all MII partners. Certification and recognition opportunities have been created.The educational offers are aimed at target groups with a background in computer science, medicine, nursing, bioinformatics, biology, natural science, and data science. Additional qualifications for physicians in computer science and computer scientists in medicine seem to be particularly important. They can lead to higher quality in software development and better support for treatment processes by application systems.Digital learning methods were important in all consortia. They offer flexibility for cross-location and interprofessional training. This enables learning at an individual pace and an exchange between professional groups.The success of the MII depends largely on society's acceptance of the multiple use of medical data in both healthcare and research. The information required for this is provided by the MII's public relations work. There is also an enormous need in society for medical and digital literacy.

Predictors of students' self-reported adoption of a smartphone application for medical education in general practice.

BACKGROUND: Smartphones and related applications are increasingly gaining relevance in the healthcare domain. We previously assessed the demands and preferences of medical students towards an application accompanying them during a course on general practice. The current study aims to elucidate the factors associated with adoption of such a technology. Therefore we provided students with a prototype of an application specifically related to their studies in general practice. METHODS: A total estimation among students participating in a general practice examination at the Leipzig Medical School was conducted in May 2014. Students were asked to answer a structured self-designed questionnaire. Univariable comparisons were made to identify significant differences between those students who reported to have used the application frequently and those who did not. Multivariable binary logistic regression was used to reveal independent predictors of frequent application usage. RESULTS: The response rate was 99.3 % (n = 305/307). The majority (59 %, n = 180/305) were female students. The mean age was 24.5 years and 79.9 % (n = 243/304) owned a smartphone or tablet computer. Regarding the usage of the provided application, 2.3 % (n = 7/303) did not use the app while 68.0 % (n = 206/303) replied to have used it more than five times. Frequent users significantly differed from non-frequent users with regard to being female rather than male, higher mobile device ownership, more frequent exchange about obtaining the course certificate, higher personal interest in new technologies, larger enjoyment of the technology, lower intention to not use smartphone applications in the future, better opinion towards smartphone applications for the profession of a doctor, higher perceived importance of medical applications on the job, higher compatibility of smartphone applications with personal work style, higher perceived relevance of university support and personal benefit of use. Multivariable analysis revealed a set of four variables independently predicting frequent usage: being female, a higher perceived benefit of the supplied application, a higher personal interest in new technologies, and a higher perceived impact of previous experiences on smartphone adoption (Pseudo-R(2)(Nagelkerke) = 0.245). CONCLUSIONS: Understanding medical students' adoption of smartphone applications used for educational purposes may provide useful information to guide the implementation process as well as the design of respective applications.

[Electronic drug prescription - auto pilot for drug therapy?]. / Elektronische Arzneimittelverordnung - Autopilot in der Arzneimitteltherapie? Eine Literatur- und Datenanalyse.

In tertiary care, computerized physician order entries may improve performance, cross-linking, and documentation when prescribing drugs. A clinical decision support integrated in these systems is discussed to prevent additional medication errors. For an optimal performance, the implementation into the clinical information systems is required to gain access to patient data (e. g. from laboratory). In routine care, the question rises whether a benefit of the systems can be proven in clinical studies and whether there is a difference between the systems. To achieve optimal results, these systems should also consider specific requirements, i. e. the patient groups and prescribed drugs in the local setting. We performed a systematic literature evaluation searching for published data in the topic electronic prescribing to assess them in a structured analysis considering medical-pharmaceutical aspects. Additionally, we assessed three databases in German language and one in English language taking drug-drug-interactions as an example to compare the identification of drug-related problems. Medication data from our own patients in a paediatric intensive care unit of a university hospital were analysed by the systems. Our results revealed strengths but also limitations of electronic prescribing.

Assessing the prognoses on Health care in the information society 2013--thirteen years after.

Health care and information technology in health care is advancing at tremendous speed. We analysed whether the prognoses by Haux et al. - first presented in 2000 and published in 2002 - have been fulfilled in 2013 and which might be the reasons for match or mismatch. Twenty international experts in biomedical and health informatics met in May 2013 in a workshop to discuss match or mismatch of each of the 71 prognoses. After this meeting a web-based survey among workshop participants took place. Thirty-three prognoses were assessed matching; they reflect e.g. that there is good progress in storing patient data electronically in health care institutions. Twenty-three prognoses were assessed mismatching; they reflect e.g. that telemedicine and home monitoring as well as electronic exchange of patient data between institutions is not established as widespread as expected. Fifteen prognoses were assessed neither matching nor mismatching. ICT tools have considerably influenced health care in the last decade, but in many cases not as far as it was expected by Haux et al. in 2002. In most cases this is not a matter of the availability of technical solutions but of organizational and ethical issues. We need innovative and modern information system architectures which support multiple use of data for patient care as well as for research and reporting and which are able to integrate data from home monitoring into a patient centered health record. Since innovative technology is available the efficient and wide-spread use in health care has to be enabled by systematic information management.

Past and next 10 years of medical informatics.

More than 10 years ago Haux et al. tried to answer the question how health care provision will look like in the year 2013. A follow-up workshop was held in Braunschweig, Germany, for 2 days in May, 2013, with 20 invited international experts in biomedical and health informatics. Among other things it had the objectives to discuss the suggested goals and measures of 2002 and how priorities on MI research in this context should be set from the viewpoint of today. The goals from 2002 are now as up-to-date as they were then. The experts stated that the three goals: "patient-centred recording and use of medical data for cooperative care"; "process-integrated decision support through current medical knowledge" and "comprehensive use of patient data for research and health care reporting" have not been reached yet and are still relevant. A new goal for ICT in health care should be the support of patient centred personalized (individual) medicine. MI as an academic discipline carries out research concerning tools that support health care professionals in their work. This research should be carried out without the pressure that it should lead to systems that are immediately and directly accepted in practice.

Concept for a Basic ISO 14721 Archive Information Package for Clinical Studies.

Secondary use of medical data for research is desirable for intrinsic, ethical and financial reasons. In this context, the question becomes relevant as to how such datasets are to be made accessible to a larger target group in the long term. Typically, datasets are not extracted ad hoc from the primary systems, because they are processed qualitatively (FAIR data). Special data repositories are currently being built for this purpose. This paper examines the requirements for the reuse of clinical trial data in a data repository utilizing the Open Archiving Information System (OAIS) reference model. In particular, a concept for an Archive Information Package (AIP) is developed with the central focus on a cost-effective trade-off between the effort of creation for the data producer and the comprehensibility of the data for the data consumer.

A Tool for Specifying Data Quality Checks for Clinical Data Management Systems - A Technical Case Report.

INTRODUCTION: Prospective data collection in clinical trials is considered the gold standard of clinical research. Validating data entered in input fields in case report forms is unavoidable to maintain good data quality. Data quality checks include both the conformance of individual inputs to the specification of the data element, the detection of missing values, and the plausibility of the values entered. STATE-OF-THE-ART: Besides Libre-/OpenClinica there are many applications for capturing clinical data. While most of them have a commercial approach, free and open-source solutions lack intuitive operation. CONCEPT: Our ocRuleTool is made for the specific use case to write validation rules for Open-/LibreClinica, a clinical study management software for designing case report forms and managing medical data in clinical trials. It addresses parts of all three categories of data quality checks mentioned above. IMPLEMENTATION: The required rules and error messages are entered in the normative Excel specification and then converted to an XML document which can be uploaded to Open-/LibreClinica. The advantage of this intermediate step is a better readability as the complex XML elements are broken down into easy to fill out columns in Excel. The tool then generates the ready to use XML file by itself. LESSONS LEARNED: This approach saves time, is less error-prone and allows collaboration with clinicians on improving data quality. CONCLUSION: Our ocRuleTool has proven useful in over a dozen studies. We hope to increase the user base by releasing it to open source on GitHub.

Identifying Relevant FHIR Elements for Data Quality Assessment in the German Core Data Set.

The German Medical Informatics Initiative makes clinical routine data available for biomedical research. In total, 37 university hospitals have set up so-called data integration centers to facilitate this data reuse. A standardized set of HL7 FHIR profiles ("MII Core Data Set") defines the common data model across all centers. Regular Projectathons ensure continuous evaluation of the implemented data sharing processes on artificial and real-world clinical use cases. In this context, FHIR continues to rise in popularity for exchanging patient care data. As reusing data from patient care in clinical research requires high trust in the data, data quality assessments are a key point of concern in the data sharing process. To support the setup of data quality assessments within data integration centers, we suggest a process for finding elements of interest from FHIR profiles. We focus on the specific data quality measures defined by Kahn et al.

A Linked Open Data-Based Terminology to Describe Libre/Free and Open-source Software: Incremental Development Study.

BACKGROUND: There is a variety of libre/free and open-source software (LIFOSS) products for medicine and health care. To support health care and IT professionals select an appropriate software product for given tasks, several comparison studies and web platforms, such as Medfloss.org, are available. However, due to the lack of a uniform terminology for health informatics, ambiguous or imprecise terms are used to describe the functionalities of LIFOSS. This makes comparisons of LIFOSS difficult and may lead to inappropriate software selection decisions. Using Linked Open Data (LOD) promises to address these challenges. OBJECTIVE: We describe LIFOSS systematically with the help of the underlying Health Information Technology Ontology (HITO). We publish HITO and HITO-based software product descriptions using LOD to obtain the following benefits: (1) linking and reusing existing terminologies and (2) using Semantic Web tools for viewing and querying the LIFOSS data on the World Wide Web. METHODS: HITO was incrementally developed and implemented. First, classes for the description of software products in health IT evaluation studies were identified. Second, requirements for describing LIFOSS were elicited by interviewing domain experts. Third, to describe domain-specific functionalities of software products, existing catalogues of features and enterprise functions were analyzed and integrated into the HITO knowledge base. As a proof of concept, HITO was used to describe 25 LIFOSS products. RESULTS: HITO provides a defined set of classes and their relationships to describe LIFOSS in medicine and health care. With the help of linked or integrated catalogues for languages, programming languages, licenses, features, and enterprise functions, the functionalities of LIFOSS can be precisely described and compared. We publish HITO and the LIFOSS descriptions as LOD; they can be queried and viewed using different Semantic Web tools, such as Resource Description Framework (RDF) browsers, SPARQL Protocol and RDF Query Language (SPARQL) queries, and faceted searches. The advantages of providing HITO as LOD are demonstrated by practical examples. CONCLUSIONS: HITO is a building block to achieving unambiguous communication among health IT professionals and researchers. Providing LIFOSS product information as LOD enables barrier-free and easy access to data that are often hidden in user manuals of software products or are not available at all. Efforts to establish a unique terminology of medical and health informatics should be further supported and continued.

Pitfalls in Analyzing FHIR Data from Different University Hospitals.

The German Medical Informatics Initiative has agreed on a HL7 FHIR-based core data set as the common data model that all 37 university hospitals use for their patient's data. These data are stored locally at the site but are centrally queryable for researchers and accessible upon request. This infrastructure is currently under construction, and its functionality is being tested by so-called Projectathons. In the 6th Projectathon, a clinical hypothesis was formulated, executed in a multicenter scenario, and its results were analyzed. A number of oddities emerged in the analysis of data from different sites. Biometricians, who had previously performed analyses in prospective data collection settings such as clinical trials or cohorts, were not consistently aware of these idiosyncrasies. This field report describes data quality problems that have occurred, although not all are genuine errors. The aim is to point out such circumstances of data generation that may affect statistical analysis.

Modeling the Application of IHE QRPH Profiles in Data Integration Centers: A Practical Approach with 3LGM2.

The Data Integration Centers (DICs), all part of the German Medical Informatics Initiative (MII), prepare routine care data captured in university hospitals to enable its reuse in clinical research. Tackling this challenging task requires them to maintain multiple data stores, implement the necessary transformation processes, and provide the required terminology services, all while also addressing the use case specific needs researchers might have. An MII wide application of the standardized profiles defined in the IHE QRPH domain might therefore be able to drastically reduce the overhead at any one DIC. The MII DIC reference model built in 3LGM2, a method to describe complex information system architectures, serves as a starting point to evaluate whether such an application is possible. We first extend the IHE modeling capabilities of 3LGM2 to also support the five profiles from the QRPH domain that our experts evaluated as relevant in the MII DIC context. We then expand the DIC reference model by some IHE QRPH actors and transactions, showing that their application could be beneficial in the MII DIC context, provided they surpass their trial status.

On the Effective Dissemination and Use of Learning Objectives Catalogs for Health Information Curricula Development.

Catalogs of competency-based learning objectives (CLO) were introduced and promoted as a prerequisite for high-quality, systematic curriculum development. While this is common in medicine, the consistent use of CLO is not yet well established in epidemiology, biometry, medical informatics, biomedical informatics, and nursing informatics especially in Germany. This paper aims to identify underlying obstacles and give recommendations in order to promote the dissemination of CLO for curricular development in health data and information sciences. To determine these obstacles and recommendations a public online expert workshop was organized. This paper summarizes the findings.

SNIK Quiz: A Multiple Choice Game About Information Management in Hospitals.

SNIK is a knowledge base about the management of health information systems generated by extracting Linked Data from textbooks and other sources. SNIK describes functions, roles executing these functions, and entity types, the information used or updated by these functions. We present SNIK Quiz, a browser game in which students answer multiple-choice questions about information management in hospitals based on SNIK. The questions are semi-automatically generated using templates in order to train basic facts, more complex patterns, and connections between textbooks encoded in SNIK.

Implementation of a Clinical Trial Recruitment Support System Based on Fast Healthcare Interoperability Resources (FHIR) in a Cardiology Department.

Clinical Trial Recruitment Support Systems can booster patient inclusion of clinical trials by automatically analyzing eligibility criteria based on electronic health records. However, missing interoperability has hindered introduction of those systems on a broader scale. Therefore, our aim was to develop a recruitment support system based on FHIR R4 and evaluate its usage and features in a cardiology department. Clinical conditions, anamnesis, examinations, allergies, medication, laboratory data and echocardiography results were imported as FHIR resources. Clinical trial information, eligibility criteria and recruitment status were recorded using the appropriate FHIR resources without extensions. Eligibility criteria linked by the logical operation "OR" were represented by using multiple FHIR Group resources for enrollment. The system was able to identify 52 of 55 patients included in four clinical trials. In conclusion, use of FHIR for defining eligibility criteria of clinical trials may facilitate interoperability and allow automatic screening for eligible patients at multiple sites of different healthcare providers in the future. Upcoming changes in FHIR should allow easier description of "OR"-linked eligibility criteria.

Improving Findability of Digital Assets in Research Data Repositories Using the W3C DCAT Vocabulary.

Research data management requires stable, trustworthy repositories to safeguard scientific research results. In this context, rich markup with metadata is crucial for the discoverability and interpretability of the relevant resources. SEEK is a web-based software to manage all important artifacts of a research project, including project structures, involved actors, documents and datasets. SEEK is organized along the ISA model (Investigation - Study - Assay). It offers several machine-readable serializations, including JSON and RDF. In this paper, we extend the power of RDF serialization by leveraging the W3C Data Catalog Vocabulary (DCAT). DCAT was specifically designed to improve interoperability between digital assets on the Web and enables cross-domain markup. By using community-consented gold standard vocabularies and a formal knowledge description language, findability and interoperability according to the FAIR principles are significantly improved.

3LGM2IHE: Requirements for Data-Protection-Compliant Research Infrastructures-A Systematic Comparison of Theory and Practice-Oriented Implementation.

OBJECTIVES: The TMF (Technology, Methods, and Infrastructure for Networked Medical Research) Data Protection Guide (TMF-DP) makes path-breaking recommendations on the subject of data protection in research projects. It includes comprehensive requirements for applications such as patient lists, pseudonymization services, and consent management services. Nevertheless, it lacks a structured, categorized list of requirements for simplified application in research projects and systematic evaluation. The 3LGM2IHE ("Three-layer Graphbased meta model - Integrating the Healthcare Enterprise [IHE] " ) project is funded by the German Research Foundation (DFG). 3LGM2IHE aims to define modeling paradigms and implement modeling tools for planning health care information systems. In addition, one of the goals is to create and publish 3LGM2 information system architecture design patterns (short "design patterns") for the community as design models in terms of a framework. A structured list of data protection-related requirements based on the TMF-DP is a precondition to integrate functions (3LGM2 Domain Layer) and building blocks (3LGM2 Logical Tool Layer) in 3LGM2 design patterns. METHODS: In order to structure the continuous text of the TMF-DP, requirement types were defined in a first step. In a second step, dependencies and delineations of the definitions were identified. In a third step, the requirements from the TMF-DP were systematically extracted. Based on the identified lists of requirements, a fourth step included the comparison of the identified requirements with exemplary open source tools as provided by the "Independent Trusted Third Party of the University Medicine Greifswald" (TTP tools). RESULTS: As a result, four lists of requirements were created, which contain requirements for the "patient list", the "pseudonymization service", and the "consent management", as well as cross-component requirements from the TMF-DP chapter 6 in a structured form. Further to requirements (1), possible variants (2) of implementations (to fulfill a single requirement) and recommendations (3) were identified. A comparison of the requirements lists with the functional scopes of the open source tools E-PIX (record linkage), gPAS (pseudonym management), and gICS (consent management) has shown that these fulfill more than 80% of the requirements. CONCLUSIONS: A structured set of data protection-related requirements facilitates a systematic evaluation of implementations with respect to the fulfillment of the TMF-DP guidelines. These re-usable lists provide a decision aid for the selection of suitable tools for new research projects. As a result, these lists form the basis for the development of data protection-related 3LGM2 design patterns as part of the 3LGM2IHE project.

A Formal Model for the FAIR4Health Information Architecture.

In the EU project FAIR4Health, a ETL pipeline for the FAIRification of structured health data as well as an agent-based, distributed query platform for the analysis of research hypotheses and the training of machine learning models were developed. The system has been successfully tested in two clinical use cases with patient data from five university hospitals. Currently, the solution is also being considered for use in other hospitals. However, configuring the system and deploying it in the local IT architecture is non-trivial and meets with understandable concerns about security. This paper presents a model for describing the information architecture based on a formal approach, the 3LGM metamodel. The model was evaluated by the developers. As a result, the clear separation of tasks and the software components that implement them as well as the rich description of interactions via interfaces were positively emphasized.

A KPI framework for process-based benchmarking of hospital information systems.

Benchmarking is a major topic for monitoring, directing and elucidating the performance of hospital information systems (HIS). Current approaches neglect the outcome of the processes that are supported by the HIS and their contribution to the hospital's strategic goals. We suggest to benchmark HIS based on clinical documentation processes and their outcome. A framework consisting of a general process model and outcome criteria for clinical documentation processes is introduced.

Health Informatics Learning Objectives on an Interoperable, Collaborative Platform.

Catalogues of learning objectives for Biomedical and Health Informatics are relevant prerequisites for systematic and effective qualification. Catalogue management needs to integrate different catalogues and support collaborative revisioning. The Health Informatics Learning Objectives Navigator (HI-LONa) offers an open, interoperable platform based on Semantic Web Technology. At present HI-LONa contains 983 learning objectives of three relevant catalogues. HI-LONa successfully supported a multiprofessional consensus process.

The Process of Modeling Information System Architectures with IHE.

IHE has defined more than 200 integration profiles in order to improve the interoperability of application systems in healthcare. These profiles describe how standards should be used in particular use cases. These profiles are very helpful but their correct use is challenging, if the user is not familiar to the specifications. Therefore, inexperienced modelers of information systems quickly lose track of existing IHE profiles. In addition, the users of these profiles are often not aware of rules that are defined within these profiles and of dependencies that exist between the profiles. There are also modelers that do not notice the differences between the implemented actors, because they do not know the optional capabilities of some actors. The aim of this paper is therefore to describe a concept how modelers of information systems can be supported in the selection and use of IHE profiles and how this concept was prototypically implemented in the "Three-layer Graph-based meta model" modeling tool (3LGM2 Tool). The described modeling process consists of the following steps that can be looped: defining the use case, choosing suitable integration profiles, choosing actors and their options and assigning them to application systems, checking for required actor groupings and modeling transactions. Most of these steps were implemented in the 3LGM2 Tool. Further implementation effort and evaluation of our approach by inexperienced users is needed. But after that our tool should be a valuable tool for modelers planning healthcare information system architectures, in particular those based on IHE.