Implementation of eHealth and AI integrated diagnostics with multidisciplinary digitized data: are we ready from an international perspective?

Abstract

Digitization of medicine requires systematic handling of the increasing amount of health data to improve medical diagnosis. In this context, the integration of the versatile diagnostic information, e.g., from anamnesis, imaging, histopathology, and clinical chemistry, and its comprehensive analysis by artificial intelligence (AI)-based tools is expected to improve diagnostic precision and the therapeutic conduct. However, the complex medical environment poses a major obstacle to the translation of integrated diagnostics into clinical research and routine. There is a high need to address aspects like data privacy, data integration, interoperability standards, appropriate IT infrastructure, and education of staff. Besides this, a plethora of technical, political, and ethical challenges exists. This is complicated by the high diversity of approaches across Europe. Thus, we here provide insights into current international activities on the way to digital comprehensive diagnostics. This includes a technical view on challenges and solutions for comprehensive diagnostics in terms of data integration and analysis. Current data communications standards and common IT solutions that are in place in hospitals are reported. Furthermore, the international hospital digitalization scoring and the European funding situation were analyzed. In addition, the regional activities in radiomics and the related publication trends are discussed. Our findings show that prerequisites for comprehensive diagnostics have not yet been sufficiently established throughout Europe. The manifold activities are characterized by a heterogeneous digitization progress and they are driven by national efforts. This emphasizes the importance of clear governance, concerted investments, and cooperation at various levels in the health systems.Key Points• Europe is characterized by heterogeneity in its digitization progress with predominantly national efforts. Infrastructural prerequisites for comprehensive diagnostics are not given and not sufficiently funded throughout Europe, which is particularly true for data integration.• The clinical establishment of comprehensive diagnostics demands for a clear governance, significant investments, and cooperation at various levels in the healthcare systems.• While comprehensive diagnostics is on its way, concerted efforts should be taken in Europe to get consensus concerning interoperability and standards, security, and privacy as well as ethical and legal concerns.

Keywords: Artificial intelligence; Diagnosis; Electronic health records; Europe; Information storage and retrieval.

Fig. 1

Overview of different data solutions for comprehensive diagnostics (CD) infrastructure. CD requires solutions for data integration and data analysis. Data integration can be performed based on own data (internal) or data imports (external) or a mixture of both. Data integration can be performed locally or in the cloud to build data warehouses or data lakes. One can also build the data bases from individual cases or groups. Data warehouses store organized data, which requires efforts of structuring and cleaning. Data lakes store raw data. Subsequent efforts need to be taken for the specific selection and organization of the data for each need/analysis. Data analysis can be performed on the integrated data. It can be descriptive (e.g., graphical presentation of data), inferential (concluding from the sample case to the collective), and predictive (pattern found in historical data are used to foresee the fate of present cases). These analyses can be performed locally or by cloud computing. For this purpose, statistical methods, artificial intelligence, and data mining are applied

Fig. 2

Annual international publication activity in radiomics from 2011 to 2019 (total 3009) based on a Web of Science search. a Number of publications. b Top 5 countries ranked by their number of (co-)authorships in publications (e.g., in 2012 there were two publications, both NL and US were involved, so each of them has two co-authorships in the two publications of 2012). c Number of highly cited publications (top 1% of the citations). d Top 5 countries ranked by their number of highly cited (co-)authorship publications (in total 60 high cited publications with 167 citations on average) (the methods and table of highly cited publications are part of the Supplement)

Fig. 3

Share of 3009 radiomics publications in the clinical and technical research areas assigned by the Web of Science for 2011 to 2019. Multiple assignments of research areas per publications are possible (see Supplement for further details on the methods)

Fig. 4

Degree of digitization of different countries’ hospitals based on the annually averaged EMRAM Score provided by HIMSS Analytics. Since in 2018, the criteria of the EMRAM stages were slightly modified and recent data are not yet available, we present data evaluated between 2011 and 2017. The eight-stage EMRAM Score ranges from 0 “paper-based” to 7 “paperless with data analytics” and it considers specific aspects such as closed-loop medication management. Besides single European nations, also United States (US), Middle East, Canada, and Asia-Pacific (APAC) are included. The numbers on the right represent the EMRAM Scores from 2017. In addition to the countries, the numbers of hospitals with EMRAM Score in 2017 are indicated. We would like to point out that due to the different number of hospitals assessed with the EMRAM Score, only a tendency can be evaluated (see Supplement for further details on the methods)

Fig. 5

Challenges and implemented solutions for the digitalization of national healthcare systems including examples of countries at different stages of evolution