BackgroundDue to the increasing functionality of medical information systems, it is hard to imagine day to day work in hospitals without IT support. Therefore, the design of dialogues between humans and information systems is one of the most important issues to be addressed in health care. This survey presents an analysis of the current quality level of human-computer interaction of healthcare-IT in German hospitals, focused on the users' point of view.MethodsTo evaluate the usability of clinical-IT according to the design principles of EN ISO 9241-10 the IsoMetrics Inventory, an assessment tool, was used. The focus of this paper has been put on suitability for task, training effort and conformity with user expectations, differentiated by information systems. Effectiveness has been evaluated with the focus on interoperability and functionality of different IT systems.Results4521 persons from 371 hospitals visited the start page of the study, while 1003 persons from 158 hospitals completed the questionnaire. The results show relevant variations between different information systems.ConclusionsSpecialised information systems with defined functionality received better assessments than clinical information systems in general. This could be attributed to the improved customisation of these specialised systems for specific working environments. The results can be used as reference data for evaluation and benchmarking of human computer engineering in clinical health IT context for future studies.

mRNA vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), such as BNT162b2 (Comirnaty®), have proven to be highly immunogenic and efficient but also show marked reactogenicity, leading to adverse effects (AEs). Here, we analyzed whether the severity of AEs predicts the antibody response against the SARS-CoV-2 spike protein. Healthcare workers without prior SARS-CoV-2 infection, who received a prime-boost vaccination with BNT162b2, completed a standardized electronic questionnaire on the duration and severity of AEs. Serum specimens were collected two to four weeks after the boost vaccination and tested with the COVID-19 ELISA IgG (Vircell-IgG), the LIAISON® SARS-CoV-2 S1/S2 IgG CLIA (DiaSorin-IgG) and the iFlash-2019-nCoV NAb surrogate neutralization assay (Yhlo-NAb). A penalized linear regression model fitted by machine learning was used to correlate AEs with antibody levels. Eighty subjects were enrolled in the study. Systemic, but not local, AEs occurred more frequently after the boost vaccination. Elevated SARS-CoV-2 IgG antibody levels were measured in 92.5% of subjects with Vircell-IgG and in all subjects with DiaSorin-IgG and Yhlo-NAb. Gender, age and BMI showed no association with the antibody levels or with the AEs. The linear regression model identified headache, malaise and nausea as AEs with the greatest variable importance for higher antibody levels (Vircell-IgG and DiaSorin-IgG). However, the model performance for predicting antibody levels from AEs was very low for Vircell-IgG (squared correlation coefficient r2 = 0.04) and DiaSorin-IgG (r2 = 0.06). AEs did not predict the surrogate neutralization (Yhlo-NAb) results. In conclusion, AEs correlate only weakly with the SARS-CoV-2 spike protein antibody levels after COVID-19 vaccination with BNT162b2 mRNA.

The insertion of all patient details in one clinical information system (CIS) provides an enormous potential to rationalize and accelerate the administrative procedures in primary patient care. A successful data management system has to record not only the entire spectrum of the patient's medical data, but also the patient's personal data like name, address, date of birth, as well as names and addresses of other involved physicians. In addition, all aspects of the database gathered from varying sources must be compatible. The program has to be user-friendly enough that many different workers with varying backgrounds can effectively employ it. We investigated the effective saving of time in preparing a patient's discharge report based on conventional dictation using the clinical information system (Soarian) compared to a conventional, isolated word-processing program (Word). Existing potentials and limitations concerning the use of the CIS are presented. The objective analysis of measured processing times demonstrated a reduction for the typist, but no benefit for the physician dictating the discharge report. In the subjective perception of all users, the processing time appeared to have increased due to awkward editing and navigation functions. Improvements are required to increase the acceptance of the program by the users.

BackgroundToday, cancer documentation is still a tedious task involving many different information systems even within a single institution and it is rarely supported by appropriate documentation workflows.MethodsIn a comprehensive 14 step analysis we compiled diagnostic and therapeutic pathways for 13 cancer entities using a mixed approach of document analysis, workflow analysis, expert interviews, workflow modelling and feedback loops. These pathways were stepwise classified and categorized to create a final set of grouped pathways and workflows including electronic documentation forms.ResultsA total of 73 workflows for the 13 entities based on 82 paper documentation forms additionally to computer based documentation systems were compiled in a 724 page document comprising 130 figures, 94 tables and 23 tumour classifications as well as 12 follow-up tables. Stepwise classification made it possible to derive grouped diagnostic and therapeutic pathways for the three major classes- solid entities with surgical therapy- solid entities with surgical and additional therapeutic activities and- non-solid entities.For these classes it was possible to deduct common documentation workflows to support workflow-guided single-source documentation.ConclusionsClinical documentation activities within a Comprehensive Cancer Center can likely be realized in a set of three documentation workflows with conditional branching in a modern workflow supporting clinical information system.