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Objectives: In this synopsis, we give an overview of recent research and propose a selection of best papers published in 2021 in the field of Clinical Information Systems (CIS). Method: As CIS section editors, we annually apply a systematic process to retrieve articles for the IMIA Yearbook of Medical Informatics. For eight years now, we use the same query to find relevant publications in the CIS field. Each year we retrieve more than 2,400 papers which we categorize in a multi-pass review to distill a preselection of up to 15 candidate papers. External reviewers and yearbook editors then assess the selected candidate papers. Based on the review results, the IMIA Yearbook editorial board chooses up to four best publications for the section at a selection meeting. To get a comprehensive overview of the content of the retrieved articles, we use text mining and term co-occurrence mapping techniques. Results: We carried out the query in mid-January 2022 and retrieved a deduplicated result set of 2,688 articles from 1,062 different journals. This year, we nominated ten papers as candidates and finally selected two of them as the best papers in the CIS section. As in the previous years, the content analysis of the articles revealed the broad spectrum of topics covered by CIS research, but - on the other side – no real innovations or new upcoming research trends. However, the significant impact of COVID-19 on CIS research was observable also this year. Conclusions: The trends in CIS research, as seen in recent years, continue to be observable. The content analysis revealed nothing really new in the CIS domain. What was very visible was the impact of the COVID-19 pandemic, which still effects our lives and also CIS.

The Clinical Information Systems (CIS) section of the IMIA Yearbook of Medical Informatics systematically screens about 2,500 publications from more than 1,000 journals annually to find the best CIS publications. The editors of the CIS section have noticed a trend toward patient-centered care supported by AI and machine learning and increased research in cross-institutional data sharing, particularly in telemedicine. As a result, they adjusted their search query to include the MeSH term “telemedicine.” As a preliminary step and to get a sense of the historical development of telemedicine research activity, they performed a bibliometric analysis of all previously published papers in PubMed indexed with the tag “Telemedicine” as MeSH Major Topic. They retrieved 29,289 publications from 1976 to 2022 and used their titles and abstracts to create a bibliometric network that visualizes the most relevant terms, their frequency and relationship to each other, and the chronological sequence of their publication. The development over time also shows a clear move toward patient-centeredness. Interestingly, the term “Covid,” which has only recently come into use, takes on a central role in the network.

Background: Dashboards provide a good retrospective view of the development of the disease. Yet, current COVID-related dashboards typically lack the capability to predict future trends. However, this is important for health policy makers and health care providers in order to adopt meaningful containment strategies. Objectives: The aim of this paper is to present the Surviral dashboard, which allows the effective monitoring of infectious disease dynamics. Methods: The presented dashboard comprises a wide range of information, including retrospective and prognostic data based on an agent-based simulation framework. It served as the basis for informed decision-making and planning of disease control strategies within the federal state of Tyrol. Results: By visualizing the information in an understandable format, the dashboard provided a comprehensive overview of the COVID-19 situation in Tyrol and allowed for the identification of trends and patterns. Conclusion: The presented dashboard is a valuable tool for managing pandemics such as COVID-19. It provides a convenient and efficient way to monitor the spread of a disease and identify potential areas for intervention.

Data-driven decision-making in health care is becoming increasingly important in daily clinical use. A data warehouse, storing all the clinically relevant information in a highly structured way, is a primary basis for achieving this goal. We are developing a clinical data warehouse where more than 20 years of clinical data can be persisted, and newly generated data from different sources can be integrated. A back room was created to store all hospital information system data in a PostgreSQL database. Due to the enormous number of diverse forms in the hospital information system, a broker service was developed that integrates the individual data sources into the data warehouse as soon as they are released for storage. The front room represents the interface from the infrastructure to the targeted analysis. Database query and visualization tools or business intelligence tools can display and analyze processed and interleaved data. In all areas of business and medicine, structured and quality-adjusted data is of major importance. With the help of a clinical data warehouse system, it is possible to perform patient-centered analyses and thus realize optimal therapy. Furthermore, it is possible to provide staff and management with dashboards for control purposes.

The Community of Inquiry (CoI) Framework describes success factors for collaborative online-based learning. The CoI Survey is a validated instrument to measure these factors from the perspective of course participants. Until now, no validated translation of this Survey to German was available. The aim of this work was to translate the original English Survey to German and to validate the translated Survey instrument. After a systematic translation process, we validated the German translation in two higher education settings in two countries (entire data set of n=433 Surveys). By conducting item analysis, reliability analysis, exploratory factor analysis, and confirmatory factor analysis, we were able to confirm the reliability and validity of the German CoI Survey. Only one item (CP6) shows cross-loadings on two factors, a finding that was already discussed for the original CoI Survey. To conclude, the validated German version of the CoI Survey is now available.

The elicited anti-SARS-CoV-2 immunity is becoming increasingly complex with individuals receiving a different number of vaccine doses paired with or without recovery from breakthrough infections with different variants. Here we analyze the immunity of individuals that initially received two doses of mRNA vaccine and either received a booster vaccination, recovered from a breakthrough infection, or both. Our data suggest that two vaccine doses and delta breakthrough infection or three vaccine doses and optionally omicron or delta infection provide better B cell immunity than the initial two doses of mRNA vaccine with or without alpha breakthrough infection. A particularly potent B cell response against the currently circulating omicron variant (B. 1.1.529) was observed for thrice vaccinated individuals with omicron breakthrough infection; a 46-fold increase in plasma neutralization compared to two vaccine doses (p

BackgroundWorldwide vaccination campaigns significantly reduced mortality caused by SARS-CoV-2 infection and diminished the devastating effects of the pandemic. The first approved vaccines are based on novel mRNA technology and elicit potent immune responses offering high levels of protection from severe disease.MethodsHere we longitudinally assessed adaptive immune responses during a 12-month follow-up period after the initial immunization with 2 doses of mRNA vaccines and after the booster dose in blood and saliva.ResultsOur findings demonstrate a rapid waning of the anti-spike IgG titers between months 3 and 6 after the initial vaccination (1.7- and 2.5-fold decrease in plasma and saliva, respectively; PConclusionsCollectively, our findings offer a detailed insight into the kinetics of adaptive immune response following SARS-CoV-2 vaccination and underline the beneficial effects of a booster vaccination.

Determining SARS-CoV-2 immunity is critical to assess COVID-19 risk and the need for prevention and mitigation strategies. We measured SARS-CoV-2 Spike/Nucleocapsid seroprevalence and serum neutralizing activity against Wu01, BA.4/5 and BQ.1.1 in a convenience sample of 1,411 patients receiving medical treatment in the emergency departments of five university hospitals in North Rhine-Westphalia, Germany, in August/September 2022. 62% reported underlying medical conditions and 67.7% were vaccinated according to German COVID-19 vaccination recommendations (13.9% fully vaccinated, 54.3% one booster, 23.4% two boosters). We detected Spike-IgG in 95.6%, Nucleocapsid-IgG in 24.0%, and neutralization against Wu01, BA.4/5 and BQ.1.1 in 94.4%, 85.0%, and 73.8% of participants, respectively. Neutralization against BA.4/5 and BQ.1.1 was 5.6- and 23.4-fold lower compared to Wu01. Accuracy of S-IgG detection for determination of neutralizing activity against BQ.1.1 was reduced substantially. We explored previous vaccinations and infections as correlates of BQ.1.1 neutralization using multivariable and Bayesian network analyses. Given a rather moderate adherence to COVID-19 vaccination recommendations, this analysis highlights the need to improve vaccine-uptake to reduce the COVID-19 risk of immune evasive variants. The study was registered as clinical trial (DRKS00029414).

In this synopsis, we give an overview of recent research and propose a selection of best papers published in 2021 in the field of Clinical Information Systems (CIS).As CIS section editors, we annually apply a systematic process to retrieve articles for the IMIA Yearbook of Medical Informatics. For eight years now, we use the same query to find relevant publications in the CIS field. Each year we retrieve more than 2,400 papers which we categorize in a multi-pass review to distill a preselection of up to 15 candidate papers. External reviewers and yearbook editors then assess the selected candidate papers. Based on the review results, the IMIA Yearbook editorial board chooses up to four best publications for the section at a selection meeting. To get a comprehensive overview of the content of the retrieved articles, we use text mining and term co-occurrence mapping techniques.We carried out the query in mid-January 2022 and retrieved a deduplicated result set of 2,688 articles from 1,062 different journals. This year, we nominated ten papers as candidates and finally selected two of them as the best papers in the CIS section. As in the previous years, the content analysis of the articles revealed the broad spectrum of topics covered by CIS research, but - on the other side - no real innovations or new upcoming research trends. However, the significant impact of COVID-19 on CIS research was observable also this year.The trends in CIS research, as seen in recent years, continue to be observable. The content analysis revealed nothing really new in the CIS domain. What was very visible was the impact of the COVID-19 pandemic, which still effects our lives and also CIS.

Summary Objective: In this synopsis, we give an overview of recent research and propose a selection of best papers published in 2020 in the field of Clinical Information Systems (CIS). Method: As CIS section editors, we annually apply a systematic process to retrieve articles for the International Medical Informatics Association Yearbook of Medical Informatics. For seven years now, we use the same query to find relevant publications in the CIS field. Each year we retrieve more than 2,400 papers which we categorize in a multi-pass review to distill a preselection of 15 candidate papers. External reviewers and yearbook editors then assess the selected candidate papers. Based on the review results, the IMIA Yearbook editorial board chooses up to four best publications for the section at a selection meeting. To get an overview of the content of the retrieved articles, we use text mining and term co-occurrence mapping techniques. Results: We carried out the query in mid-January 2021 and retrieved a deduplicated result set of 2,787 articles from 1,135 different journals. We nominated 15 papers as candidates and finally selected four of them as the best papers in the CIS section. As in the previous years, the content analysis of the articles revealed the broad spectrum of topics covered by CIS research. Thus, this year we could observe a significant impact of COVID-19 on CIS research. Conclusions: The trends in CIS research, as seen in recent years, continue to be observable. What was very visible was the impact of the Corona Virus Disease 2019 (COVID-19) pandemic, which has affected not only our lives but also CIS.

The elicited anti-SARS-CoV-2 immunity worldwide is becoming increasingly complex with individuals receiving a different amount of vaccine doses paired with or without recovery from breakthrough infections with different variants. To understand the variety of anti-SARS-CoV-2 immunity we analyzed the adaptive immune responses of individuals that initially received 2 doses of mRNA vaccine and either received a booster vaccination, recovered from a breakthrough infection, or both. Our data suggest that two vaccine doses and delta breakthrough infection or three vaccine doses and optionally omicron or delta infection provide better B cell immunity than the initial 2 doses of mRNA vaccine with or without alpha breakthrough infection. A particularly potent humoral response against the currently circulating omicron variant was observed for the thrice vaccinated individuals with omicron breakthrough infection; a 46-fold increase in neutralization compared to 2 vaccine doses (P

Even if English is the leading language for international communication, it is essential to keep in mind that research runs at the local level by local teams generally communicating in their local/national language, especially in Europe among European projects.Therefore, the European Federation for Medical Informatics - Working Group on Health Informatics for Inter-regional Cooperation" has one objective: To develop a multilingual ontology focusing on Health Informatics and Digital Health as a collaboration tool that improves international and, in particular, European collaborations.We have developed the Medical Informatics and Digital Health Multilingual Ontology (MIMO). Hosted on the Health Terminology/Ontology Portal (HeTOP), MIMO contains around 1,000 concepts, 460 MeSH Descriptors, 220 MeSH Concepts, and more than 300 newly created concepts. MIMO is continuously updated to comprise as recent as possible concepts and their translations in more than 30 languages. Moreover, the MIMO's development team constantly improves MIMO content and supporting information. Thus, during workshop discussions and one-on-one exchanges, the MIMO team has collected domain experts' opinions about the community's interests and suggestions for future enhancements. Moreover, MIMO will be integrated to support the annotation and categorization of research products into the HosmartAI European project involving more than 20 countries around Europe and worldwide.MIMO is hosted by HeTOP (Health Terminology/Ontology Portal), which integrates 100 terminologies and ontologies in 55 languages. MIMO is freely available online. MIMO is portable to other knowledge platforms as part of MIMO's main aims to facilitate communication between medical librarians, translators, and researchers as well as to support students' self-learning.

Background Fluid management in patients after subarachnoid hemorrhage (SAH) aims at the optimization of cerebral blood flow and brain oxygenation. In this study, we investigated the effects of hemodynamic management on brain oxygenation by integrating advanced hemodynamic and invasive neuromonitoring. Methods This observational cohort bi-center study included data of consecutive poor-grade SAH patients who underwent pulse contour cardiac output (PiCCO) monitoring and invasive neuromonitoring. Fluid management was guided by the transpulmonary thermodilution system and aimed at euvolemia (cardiac index, CI ≥ 3.0 L/min/m2; global end-diastolic index, GEDI 680–800 mL/m2; stroke volume variation, SVV btO2) targeted protocol to prevent brain tissue hypoxia (BTH, PbtO2 btO2 and the effect of fluid challenges on CI and PbtO2, we used generalized estimating equations to account for repeated measurements. Results Among a total of 60 included patients (median age 56 [IQRs 47–65] years), BTH occurred in 23% of the monitoring time during the first 10 days since admission. Overall, mean CI was within normal ranges (ranging from 3.1 ± 1.3 on day 0 to 4.1 ± 1.1 L/min/m2 on day 4). Higher CI levels were associated with higher PbtO2 levels (Wald = 14.2; p btO2 levels (p = 0.94 and p = 0.85, respectively) or the occurrence of BTH (p = 0.68 and p = 0.71, respectively). PbtO2 levels were not significantly different in preload dependent patients compared to episodes of euvolemia. PbtO2 increased as a response to fluid boluses only if BTH was present at baseline (from 13 ± 6 to 16 ± 11 mmHg, OR = 13.3 [95% CI 2.6–67.4], p = 0.002), but not when all boluses were considered (p = 0.154). Conclusions In this study a moderate association between increased cardiac output and brain oxygenation was observed. Fluid challenges may improve PbtO2 only in the presence of baseline BTH. Individualized hemodynamic management requires advanced cardiac and brain monitoring in critically ill SAH patients.

Objective: To summarize recent research and to propose a selection of best papers published in 2018 in the field of Clinical Information Systems (CIS). Method: Each year a systematic process is carried out to retrieve articles for the CIS section of the IMIA Yearbook of Medical Informatics and to select a set of pest papers for the section. The same query as in the last five years was used. The retrieved articles were categorized in a multi-pass review carried out by the two section editors. The final selection of candidate papers was then peer-reviewed by Yearbook editors and external reviewers. Based on the review results the best papers were then chosen at the selection meeting with the IMIA Yearbook editorial board. Text mining, and term co-occurrence mapping techniques were again used to get an overview of the content of the retrieved articles. Results: The query was carried out in mid-January 2019, yielding a consolidated, deduplicated result set of 2,264 articles which had been published in 957 different journals. This year, we nominated twelve papers as candidates and three of them were finally selected as best papers in the CIS section. Again, the content analysis of the articles revealed the broad spectrum of topics which is covered by CIS research. Conclusions: We could observe ongoing trends from our 2017 analysis. The patient increasingly moves in the focus of the research activities and trans-institutional aggregation of data is still an important field of work. The move to use patient and other clinical data directly for the patient and to support data driven process management, the move away from clinical documentation to patient-focused knowledge generation and support of informed decision, is gaining momentum by the application of new or already known but, due to technological advances, now applicable methodological approaches.

In patients with aneurysmal subarachnoid hemorrhage (aSAH), increased brain extracellular interleukin (IL)-6 levels measured by cerebral microdialysis (CMD) were associated with disease severity, early brain injury, delayed cerebral infarction, and axonal injury. In this study, we analyzed brain extracellular IL-6 levels of aSAH patients following parenteral diclofenac. Twenty-four mechanically ventilated poor-grade aSAH patients were included. Changes in cerebral metabolism, brain/body temperature, and CMD-IL-6 levels following intravenous diclofenac infusion (DCF; 75 mg diluted in 100 cc normal saline) were retrospectively analyzed from prospectively collected bedside data (at 1 hour before DCF = baseline; and at 2, 4, and 8 hours after DCF). Statistical analysis was performed using generalized estimating equations. Seventy-two events in 24 aSAH patients were analyzed. Median age was 60 years (interquartile range [IQR]: 52-67), admission HuntHess grade was 4 (IQR: 3-5), and modified Fisher grade (mFisher) was 4 (IQR: 3-4). Higher CMD-IL-6 levels at baseline were linked to fever, higher mFisher, delayed cerebral infarction, and metabolic distress (p 0.05). CMD-IL-6 levels at baseline were 281.4 pg/mL (IQR: 47-1866) and significantly (p 0.001; Wald-X

Delirium is a patient safety issue that often occurs within the population of elderly people. As delirium may be characterized by fluctuating progress, the aim of this work is to find methods to visualize the occurrence of delirium over time in different patient stays in gerontopsychatric settings.We analyzed current data mining visualization techniques for clinical research using a delirium data set collected in a gerontopsychatric setting.We identified heatmaps and dendrograms resulting from hierarchical clustering as a suitable visualization method.Heat maps with hierarchical clustering are a suitable data mining tool or visualization technique to study delirium cases in the time course of patient stays.

Background: Delirium is a patient safety issue that often occurs within the population of elderly people. As delirium may be characterized by fluctuating progress, the aim of this work is to find methods to visualize the occurrence of delirium over time in different patient stays in gerontopsychatric settings. Methods: We analyzed current data mining visualization techniques for clinical research using a delirium data set collected in a gerontopsychatric setting. Results: We identified heatmaps and dendrograms resulting from hierarchical clustering as a suitable visualization method. Conclusion: Heat maps with hierarchical clustering are a suitable data mining tool or visualization technique to study delirium cases in the time course of patient stays.

Learning is a constructive and social process that works best in interaction with others. From this perspective, interaction and cooperation are seen as essential for learning especially in online-based learning environments. The objective of this chapter is to propose and test indicators for cooperative online-based learning. The indicators focus on three areas: presence of participants (indicators: access index, access pattern index), participation of participants (reading index, contribution index, completion index), and interaction of participants (answer contribution index, connectivity index, reciprocity index). The indicators can be applied both to students and instructors. The indicators were applied to three online-based courses in higher education. Log data from the learning management system was used. Also, success rates, student evaluations, and workload analysis were conducted. Results show that the indicators can be calculated automatically and can provide meaningful information for students' and instructors' dashboards. The presented indicators are tailored to cooperative online-based learning environments, where interaction and cooperation are means of fostering higher levels of learning.

Additional file 1: Figure S1. Institutional protocol to treat brain tissue hypoxia in IBK. Figure S2. Institutional protocol to treat brain tissue hypoxia in BRU. Table S1. Baseline characteristics, complications, and outcomes stratified by the two study sites. Table S2. Association between CI and PbtO2 (GEE model). Table S3. Changes of variables pre, during, and post fluid administration in a total of 198 infusions stratified by brain tissue hypoxia vs. normal brain tissue oxygenation at baseline. Table S4. Changes of variables pre, during, and post fluid administration in a total of 198 infusions stratified by CI responders and non-responders. Table S5. Changes of variables pre, during, and post fluid administration in a total of 198 infusions stratified by crystalloids vs colloids.

Clinical processes need to be well understood before a new health IT tool can be introduced. Observations, interviews, surveys, or documentation analysis are carried out to systematically collect information to better understand a clinical process. To aggregate and visualize the collected information about a clinical process, use case diagrams can build a basis. Formal process models such as process chain diagrams or BPMN diagrams are well suited to model the process in detail. The objective of this chapter is to discuss these methods for analyzing and modeling clinical processes, as this is an important precondition for systematic process management in health care.

Clinical processes need to be well understood before a new health IT tool can be introduced. Observations, interviews, surveys, or documentation analysis are carried out to systematically collect information to better understand a clinical process. To aggregate and visualize the collected information about a clinical process, use case diagrams can build a basis. Formal process models such as process chain diagrams or BPMN diagrams are well suited to model the process in detail. The objective of this chapter is to discuss these methods for analyzing and modeling clinical processes, as this is an important precondition for systematic process management in health care.

Big Data Analytics is changing the way medical information is processed. FHIR aims to provide a robust infrastructure to enable the interoperability of clinical information.Analyze the ongoing development of analytical implementations of FHIR.Pragmatic Review of current research and implementation projects.US healthcare providers have implemented FHIR in their products, enabling scalable analytical tools. Europe demonstrated interest in FHIR.The potential of FHIR analytics is a value-added use case of the implementation of FHIR.

The Community of Inquiry (CoI) describes success factors for online-based learning.To develop approaches for automatic analysis of CoI to be visualized within student and teacher dashboards.Extending indicators from social network analysis and linguistics; evaluation within a case study.The project is just starting.Results will help to better understand and improve cooperative online-based learning in higher education.

Delirium is an acute mental disturbance that particularly occurs during hospital stay. Current clinical assessment instruments include the Delirium Observation Screening Scale (DOSS) or the Confusion Assessment Method (CAM). The aim of this work is to analyze the performance of machine learning approaches to detect delirium based on DOSS and CAM information obtained from two geropsychiatric wards in Tyrol. From a machine learning perspective, the questions of these two assessment instruments represent the features and the ICD 10 diagnoses of delirium (yes/no) is the corresponding class variable. We compare seven popular classification methods and analyze the performance and interpretability of the learning models. As our dataset is highly imbalanced, we also evaluate the effect of common sampling methods including down- and up-sampling methods as well as hybrid methods. Our results indicate a high predictive ability of advanced methods such as Random Forest that can handle even unbalanced datasets. Overall, combining a good performance of a prediction model with the ability of users to understand the prediction is challenging. However, for clinical application in fully electronic settings, a good performance seems to be more important than an easy interpretation of the prediction by the user. On the other hand, explanations of decisions are often needed to assess other criteria such as safety.

Nursing Minimum Data Sets (NMDS) intend to systematically describe nursing care. Until now NMDS have been populated with nursing data by manual data ascertainment which is inefficient. The objective of this work was to evaluate an automated mapping pipeline for transforming nursing data into an NMDS. We used LEP Nursing 3 data as source data and the Austrian and German NMDS as target formats. Based on a human expert mapping between LEP and NMDS, an automated data mapping algorithm was developed and implemented in an automatic mapping pipeline. The results show that most LEP nursing interventions can be matched to the NMDS-AT and G-NMDS and that a fully automated mapping process from LEP Nursing 3 data to NMDS-AT performs effectively and very efficiently. The shown approach can also be used to map different nursing classifications and to automatically transform point-of-care nursing data into nursing minimum data sets.

Objective: To summarize recent research and to propose a selection of best papers published in 2017 in the field of Clinical Information Systems (CIS). Method: Each year a systematic process is carried out to retrieve articles and to select a set of best papers for the CIS section of the International Medical Informatics Association (IMIA) Yearbook of Medical Informatics. The query aiming at identifying relevant publications in the field of CIS was refined by the section editors during the last years. For three years now, the query is stable. It comprises search terms from the Medical Subject Headings (MeSH) thesaurus as well as additional free text search terms from PubMed and Web of Science®. The retrieved articles were categorized in a multi-pass review carried out by the two section editors. The final selection of candidate papers was then peer-reviewed by Yearbook editors and external reviewers. Based on the review results, the best papers were then selected by the IMIA Yearbook editorial board. Text mining, and term co-occurrence mapping techniques were used to get an overview on the content of the retrieved articles. Results: The query was carried out in mid-January 2018, yielding a consolidated result set of 2,255 articles which had been published in 939 different journals. Out of them, 15 papers were nominated as candidate best papers and four of them were finally selected as best papers in the CIS section. Again, the content analysis of the articles revealed the broad spectrum of topics which is covered by CIS research. Conclusions: Modern clinical information systems serve as backbone for a very complex, trans-institutional information logistics process. Data that is produced by, documented in, shared via, organized in, presented by, and stored within clinical information systems is more and more reused for multiple purposes. We found a lot of examples showing the benefits of such data reuse with various novel approaches implemented to tackle the challenges of this process. We also found that the patient moves in the focus of interest of CIS research. So the loop of information logistics begins to close: data from the patients is used to produce value for the patients.

Thermal decomposition experiments with monosilane diluted in hydrogen have been conducted in a free-space reactor with an extendable reaction zone, allowing for easy variation of residence time. Reactor effluent was analyzed by gas-chromatography combined with mass-spectrometry (GC-MS). The applied analysis technique enables detection of silanes with up nine silicon atoms, as well as absolute quantification of the concentrations of mono-, di-, and trisilane. For all the detected silanes, our gas analyses show a peak in reactor outlet concentration as function of temperature whose position and shape depend on the number of silicon atoms (nSi) contained in the silane species. The peak width decreases and the peak position shifts to higher temperatures with increasing nSi. At increased residence time, the concentration peak shifts to lower temperatures and the SiH4 consumption rate increases. This is consistent with the expected behavior for a system described by Arrhenius kinetics. The maximum outlet concentrations of all the measured silanes decrease with increasing residence time. However, the dependence of silane concentrations on temperature and residence time is not trivial: At a fixed temperature the measured outlet concentrations will increase with increasing residence time in some temperature regions and decrease with residence time in other temperature regions. By mapping outlet concentrations as function of temperature and residence time we attempt to decouple the effect of these two parameters and to untangle their effect from that of reactor geometry and operation.

Im Pflegebereich ist eine kontinuierliche Fort- und Weiterbildung wichtig, wobei zunehmend auch online-gestutzte Angebote entstehen. Studieren in online-gestutzten Lernsettings bietet eine Reihe von Vorteilen wie die Zeit- und Ortsunabhangigkeit des Lernens. Dem gegenuber steht die Herausforderung, auch in virtuellen Lernumgebungen und damit verbundenen asynchronen Lernsettings soziale Interaktionen und gemeinsames Lernen zu fordern. Entsprechende Angebote mussen daher sorgfaltig entworfen werden. Die Community of Inquiry ist ein etabliertes Rahmenwerk fur die Gestaltung und Bewertung online-gestutzter Lernprozesse. Es beschreibt drei Erfolgs-faktoren fur online-basiertes Lernen: Social Presence, Teaching Presence, und Cognitive Presence. Wir haben einen rein online-gestutzten Kurs zum Thema „eHealth“ fur Personen aus dem Gesundheitswesen durchgefuhrt und an diesem Fallbeispiel untersucht, inwiefern die in der Community of Inquiry formulierten Erfolgsfaktoren durch das kollaborative Instruktionsdesign erfullt werden. Die Ergebnisse zeigen eine gute Unterstutzung interaktiver und kollaborativer Lernprozesse und einen guten, subjektiv empfundenen Lernerfolg der Studierenden. Insgesamt war es also moglich, rein online-gestutzte Lernangebote so zu gestalten, dass studierenden-zentriertes und kollaboratives Lernen unterstutzt wird.

Spreading depolarizations (SDs) are highly active metabolic events, commonly occur in patients with intracerebral hemorrhage (ICH) and may be triggered by fever. We investigated the dynamics of brain-temperature (Tbrain) and core-temperature (Tcore) relative to the occurrence of SDs. Twenty consecutive comatose ICH patients with multimodal electrocorticograpy (ECoG) and Tbrain monitoring of the perihematomal area were prospectively enrolled. Clusters of SDs were defined as ≥2 SDs/h. Generalized estimating equations were used for statistical calculations. Data are presented as median and interquartile range. During 3097 h (173 h [81–223]/patient) of ECoG monitoring, 342 SDs were analyzed of which 51 (15%) occurred in clusters. Baseline Tcore and Tbrain was 37.3℃ (36.9–37.8) and 37.4℃ (36.7–37.9), respectively. Tbrain but not Tcore significantly increased 25 min preceding the onset of SDs by 0.2℃ (0.1–0.2; p brain increased to a higher level (+0.4℃ [0.1–0.4]; p = 0.006) when compared to single SDs. A higher probability (OR = 36.9; CI = 36.8–37.1; p brain ≥ 38.0℃ (23% probability), than during Tbrain ≤ 36.6℃ (9% probability). Spreading depolarizations – and in particular clusters of SDs – may increase brain temperature following ICH.

Summary Objectives: To set the scientific context and then suggest principles for an evidence-based approach to secondary uses of clinical data, covering both evaluation of the secondary uses of data and evaluation of health systems and services based upon secondary uses of data. Method: Working Group review of selected literature and policy approaches. Results: We present important considerations in the evaluation of secondary uses of clinical data from the angles of governance and trust, theory, semantics, and policy. We make the case for a multi-level and multi-factorial approach to the evaluation of secondary uses of clinical data and describe a methodological framework for best practice. We emphasise the importance of evaluating the governance of secondary uses of health data in maintaining trust, which is essential for such uses. We also offer examples of the re-use of routine health data to demonstrate how it can support evaluation of clinical performance and optimize health IT system design. Conclusions: Great expectations are resting upon “Big Data” and innovative analytics. However, to build and maintain public trust, improve data reliability, and assure the validity of analytic inferences, there must be independent and transparent evaluation. A mature and evidence-based approach needs not merely data science, but must be guided by the broader concerns of applied health informatics.

Under the term "big data", the secondary use of available IT-based clinical routine data promises to easily support quality management and research. Available clinical data can, for example, be used to measure care quality, as this is an important aspect in the evaluation of health interventions. Different indicators are available for measuring care quality, e.g. nursing sensitive outcome indicators. However, a specific methodology for using clinical routine data to measure quality of nursing care is not available at the moment. We present first ideas for a model to use clinical routine data to derive nursing outcome indicators measuring quality of care. In particular, we are interested in the question of which care indicators can be extracted to predict care outcome.

Patient safety is an important topic but non-trivial to measure, as it comprises very different phenomena. One important example of patient safety issues is delirium. Many approaches for the detection and prediction of delirium are described in the literature. However, additional effort is often needed for a comprehensive data collection and for the avoidance of potential biases. To systematize a process for the detection and prediction of delirium reusing available clinical routine data, we aim to develop a minimum data set (MDS) for delirium. By combining a top-down and bottom-up approach, we compiled a comprehensive delirium map containing potential delirium elements based on evidence. The alignment with clinical routine data led to a specific version of an MDS for delirium and revealed that most of the delirium elements could be identified within available nursing routine data.

Socio-constructive instructional designs for online-based learning focus on interaction and communication of students to allow in-depth learning. The objective of this study is to analyze whether increased interaction of students in online-based learning settings may contribute to better outcome. We developed indicators for presence, participation, and interactivity of students. We extracted log data from the learning management system for 31 students in 10 online courses (n=123 course attendances). We correlated indicators to final grades and also applied a decision tree based machine learning approach. We found only weak to moderate correlations between the indicators and final grades, but acceptable results concerning prediction of students' success based on the indicators. Our results support the theory that student presence and participation in online-based courses is related to learning outcome.

Nurses are increasingly confronted with IT-based systems as part of their daily work. However, they often lack basic competencies in managing these complex systems.To analyze the need for continuous education in health informatics among Austrian nurses.Survey within five of the largest healthcare organizations in Austria. Overall, 280 nursing practitioners with IT responsibilities and nursing managers from middle and top management participated.Participants assessed five topics (IT project management, IT in nursing, eHealth, nursing terminologies, and computer science basics) as important for continuous education in health informatics. Top management rated the importance of most topics higher than middle management did. Nursing practitioners gave ratings in between middle and top management.Austrian nursing practitioners with IT responsibilities and nursing managers see a need for continuous education in health informatics. This supports findings of international recommendations of nursing informatics continuous education. There is, however, a lack of suitable opportunities for continuous education in Austria.

Intravenous nonsteroidal anti-inflammatory drugs and nonopioid analgesics are used to achieve normothermia or relieve pain in patients with aneurysmal subarachnoid hemorrhage (aSAH). We investigated the effects of paracetamol (1 g), diclofenac (75 mg) and metamizole (1 g) on systemic and cerebral hemodynamics and temperature during febrile and nonfebrile episodes after aSAH. Prospectively collected data from 77 consecutive poor-grade aSAH patients with invasive neuromonitoring were included. The burden and occurrence of hypotension (mean arterial pressure70 mmHg), brain tissue hypoxia (P

The amino-acids tryptophan, phenylalanine and tyrosine seem to play an important role in the pathophysiology of depressive disorders. We measured daily brain extracellular levels of these amino-acids using cerebral microdialysis (CMD) and high performance liquid chromatography in 26 consecutive subarachnoid hemorrhage (SAH) patients and associated them with the presence of depressive disorders. Patients were grouped as follows: medical history of depression (prior to SAH), antidepressant intake 12 months after SAH (but not before), or neither. CMD-tryptophan, CMD-phenylalanine and CMD-tyrosine levels were significantly lower in patients with preexisting depressive disorders compared to those without depression (p 0.1). In conclusion, brain interstitial levels of tryptophan, phenylalanine and tyrosine measured in the context of the clinical management of SAH were significantly decreased in patients with a medical history of depression. This study supports the hypothesis that the availability of these neurotransmitter precursor amino-acids in the human brain may play an important role in the pathophysiology of depressive disorders.

Zeitschrift für Hochschulentwicklung Volume Nr. 14 Issue Nr. 3

SUMMARY Using an industry-relevant method of production we have demonstrated production of doped silicon nanoparticles for Li-ion batteries. The particles have been characterized and tested in Li-ion battery half-cells for demonstration of the performance as Li ion storage material in the anode. In this presentation we will show the results regarding the characterization of the particles as well as the performance results of the material in Li-ion half cells. BACKGROUND The use of silicon as part of the anode in Li-ion batteries enhances the potential storage capacity greatly. While the graphite anode used in standard Li-ion batteries has a theoretical capacity of 372 mAh/g, the theoretical capacity for Si is 3,572 mAh/g [1]. However, to be able to absorb the sufficient amount of Li ions reversibly, the silicon material needs to be nanostructured [2]. EXPERIMENTAL IFE has earlier demonstrated production of silicon particles prepared using a silane-based free-space reactor, which allows control of particle size distribution and crystallinity and a high production capacity [3]. In this work, the setup was modified to allow for introduction of phosphine gas in the production process. The intention was to introduce phosphorous dopant atoms to modify the electrical conductivity of the silicon material. The current particles were produced with a silane flow rate of 5 slm, and 5 slm of 3% phosphine diluted in He. Thus, the P concentration in the process gases was 3% with respect to Si. The production rate at 100% yield would be about 400 g/h, while the product recovered from the process typically was between 100 and 200 g/h. The processing temperature was varied from 475 °C to 600 °C to produce particles with different properties. All electrochemical tests were performed in a crimped 2032 coin cell with lithium metal used as a counter electrode, with a polymer separator (Celgard 3401) and 1 M LiPF6 in 1:1 EC/DMC electrolyte (LP30, BASF). For some experiments, 10 wt% fluoroethylene carbonate (FEC) was used as electrolyte additive. The cells were cycled at 25 °C between 0.05 and 1.0 V with a constant C-rate of C/10 (after initial 3 cycles at C/20) using an Arbin Battery cycler (Arbin Instruments). RESULTS AND CONCLUSIONS The phosphorus content of the particles was by inductively coupled plasma mass spectrometry (ICP-MS) and energy-dispersive x-ray spectroscopy (EDS) measured to be in the range of 1.7-1.8% with respect to silicon. Thus, it seems that the utilization of the phosphine is not complete, or phosphorous binds to materials which are not recovered from the production process. The particle size distribution was centered around 600 nm as measured by laser scattering in a Malvern Mastersizer 2000. SEM and TEM revealed that the particles consisted of aggregates of spherical silicon particles with a primary particle size of 50-400 nm. X-ray diffraction showed that we could produce amorphous or crystalline particles depending on the temperature of the process. Cycling of the particles in lithium battery half cells showed a life time of about 300 cycles for doped and undoped particles. Some measurements indicate a better conductivity of the doped material but the results were not conclusive. The cells were cycled with a limited capacity regime where the capacity was set to 1000 mAh/g(Si) and thus the end-voltage could vary. The most pronounced difference in the cycling performance between doped and undoped silicon particles was a shift in the increase in end voltage for the doped particles: While end-voltage increased from 0.4 V to 0.6 V over the first 25 cycles, this development is stretched out over the first 50 cycles or more for doped particles. See the attached figure for further details. References [1] D. Larcher, S. Beattie, M. Morcrette, K. Edström, J.-C. Jumas, and J.-M. Tarascon, “Recent findings and prospects in the field of pure metals as negative electrodes for Li-ion batteries,” J. Mater. Chem., vol. 17, no. 36, p. 3759, 2007. [2] H. Kim, M. Seo, M. H. Park, and J. Cho, “A critical size of silicon nano-anodes for lithium rechargeable batteries,” Angew. Chemie - Int. Ed., vol. 49, no. 12, pp. 2146–2149, 2010. [3] H. F. Andersen, W. O. Filtvedt, J. P. Mæhlen, T. Mongstad, M. Kirkengen, and A. Holt, “Production of Silicon Particles for High-Capacity Anode Material, Yielding Outstanding Production Capacity,” ECS Trans., vol. 62, no. 1, pp. 97–105, 2014. Figure 1

Today's most frequently used production path for polysilicon and solar grade silicon (SG-Si) is based on thermal decomposition of trichlorosilane (SiHCl 3 ) in a Siemens-type reactor. Due to the batch-wise mode of its operation and its requirement for heating and cooling, the Siemens technology is an energy demanding procedure. As an alternative to this process, SG-Si can be produced through the thermal decomposition of monosilane (SiH 4 ), for example in a fluidized bed reactor or a centrifugal chemical vapour deposition reactor. In order to avoid production of fine particulates and related clogging, this process requires knowledge of the nucleation properties of silane. In this work, the critical concentration for particle nucleation from SiH 4 , diluted in H 2 has been determined for temperatures in the range 400 - 700 °C. For this purpose, we used a free space reactor and an optical particle detector of own design for in-situ monitoring of the reactor exhaust. In a plot of logarithmic critical nucleation concentration against inverse temperature, an almost linear relation was found for temperatures below approximately 500 °C and above approximately 600 °C. Between 500 and 600 °C, a less temperature dependent behavior is observed. Apparent activation energies are estimated to be 32 kcal/mol for temperatures below 500 °C, 8 kcal/mol for temperatures between 500 and 600 °C and 23 kcal/mol for temperatures above 600 °C. The first and last of these values agree well with existing literature. The low temperature dependence in the range 500 °C to 600 °C, however represents a deviation from earlier studies. Investigations of reactor exhaust by GC-MS (gas chromatography - mass spectrometry), allowing detection of the concentrations of higher order silanes (disilane (Si 2 H 6 ), trisilane (Si 3 H 8 ), etc) as function of reactor temperature, suggest that the low temperature dependence of the nucleation concentration for some conditions is related to an increase of the concentration of Si 2 H 6 and Si 3 H 8 at the same temperature range.

SummaryBackground: Secondary use of clinical routine data is receiving an increasing amount of attention in biomedicine and healthcare. However, building and analysing integrated clinical routine data repositories are non -trivial, challenging tasks. As in most evolving fields, recognized standards, well-proven methodological frameworks, or accurately described best-practice approaches for the systematic planning of solutions for secon -dary use of routine medical record data are missing.Objective: We propose a conceptual best-practice framework and procedure model for the systematic planning of intelligent reuse of integrated clinical routine data (SPIRIT).Methods: SPIRIT was developed based on a broad literature overview and further refined in two case studies with different kinds of clinical routine data, including process-oriented nursing data from a large hospital group and high-volume multimodal clinical data from a neurologic intensive care unit.Results: SPIRIT aims at tailoring secondary use solutions to specific needs of single departments without losing sight of the institution as a whole. It provides a general conceptual best-practice framework consisting of three parts: First, a secondary use strategy for the whole organization is determined. Second, comprehensive analyses are conducted from two different viewpoints to define the requirements regarding a clinical routine data reuse solution at the system level from the data perspective (BOTTOM UP) and at the strategic level from the future users perspective (TOP DOWN). An obligatory clinical context analysis (IN BETWEEN) facilitates refinement, combination, and integration of the different requirements. The third part of SPIRIT is dedicated to implementation, which comprises design and realization of clinical data integration and management as well as data analysis solutions.Conclusions: The SPIRIT framework is intended to be used to systematically plan the intelligent reuse of clinical routine data for multiple purposes, which often was not intended when the primary clinical documentation systems were implemented. SPIRIT helps to overcome this gap. It can be applied in healthcare institutions of any size or specialization and allows a stepwise setup and evolution of holistic clinical routine data reuse solutions.

The rapid medical and technological progress and the resulting need for life-long learning lead to the proliferation of online-based programs in health informatics for health care and health informatics professionals. Effective learning in these online-based programs demands close interaction and cooperation between students and instructors. In such cooperative online-based programs, special emphasis is thus put on fostering a community of inquiry between all participants. The online-based master program on Health Information Management at the University UMIT is firmly based on the constructivist theory of situated learning in such a community of inquiry. Online activities in this master program are designed to promote social presence, cognitive presence and teacher presence as preconditions for successful learning. To verify whether these three forms of presences are visible and whether learning was successful, the first four six-week online-based modules with overall 60 participants were analyzed in depth, combining data from community of inquiry surveys, student evaluations, workload assessments and final assessment results. Results indicate that it was possible to build a community of inquiry (with scores of 4.2 and higher) and to foster effective learning. We conclude with recommendations on how to build a community of inquiry in online-based cooperative learning and also discuss some constraints.

While Nursing Informatics competencies seem essential for the daily work of nurses, they are not formally integrated into nursing education in Austria, Germany and Switzerland, nor are there any national educational recommendations. The aim of this paper is to show how such recommendations can be developed, what competency areas are most relevant in the three countries and how the recommendations can be implemented in practice. To this end, a triple iterative procedure was proposed and applied starting with national health informatics recommendations for other professionals, matching and enriching these findings with topics from the international literature and finally validating them in an expert survey with 87 experts and in focus group sessions. Out of the 24 compiled competency areas, the relevance ratings of the following four recommended areas achieved values above 90%: nursing documentation (including terminologies), principles of nursing informatics, data protection and security, and quality assurance and quality management. As there were no significant differences between the three countries, these findings laid the foundation of the DACH Recommendations of Nursing Informatics as joint German (D), Austrian (A), and Swiss (CH) recommendations in Nursing Informatics. The methodology proposed has been utilized internationally, which demonstrates the added value of this study also outside the confines of Austria, Germany, Switzerland.

Background and purpose Early pharmacological deep vein thrombosis (DVT) prophylaxis is recommended by guidelines, but rarely started within 48 h. We aimed to analyze the effect of early (within 48 h) versus late (>48 h) DVT prophylaxis on hematoma expansion (HE) and outcome in patients with spontaneous intracerebral hemorrhage (ICH). Methods We analyzed 134 consecutive patients admitted to a tertiary neurointensive care unit with diagnosed spontaneous ICH, without previous anticoagulation, severe coagulopathy, hematoma evacuation, early withdrawal of therapy or ineligibility for DVT prophylaxis according to our institutional protocol. Significant late HE was defined as ≥6 mL increase of hematoma volume between neuroimaging within 48 h and day 3-6. Multivariate analysis was performed to identify risk factors for late HE, poor 3-month outcome (modified Rankin Scale score ≥ 4) and mortality. Results Patients had a median Glasgow Coma Scale score of 14 [interquartile range (IQR), 10-15], ICH volume of 11 (IQR, 5-24) mL and were 71 (IQR, 61-76) years old. A total of 56% (n = 76) received early DVT prophylaxis, 37% (n = 50) received late DVT prophylaxis and 8 (6%) had unknown bleeding onset. Patients with early DVT prophylaxis had smaller ICH volume [9.5 (IQR, 4-18.5) vs. 17.5 (IQR, 8-29) mL, P = 0.038] and were more often comatose (26% vs. 10%, P = 0.025). Significant late HE [n = 5/134 (3.7%)] was associated with larger initial ICH volume (P = 0.02) and lower thrombocyte count (P = 0.03) but not with early DVT prophylaxis (P = 0.36). Early DVT prophylaxis was not associated with worse outcome. Conclusion Significant late HE is uncommon and DVT prophylaxis within 48 h of symptom onset may be safe in selected patients with ICH.

Patient safety is an important issue and receiving increasing attention. Information technology (IT) and IT-based strategies as the secondary use of already existing data within hospital information systems can help to improve patient safety.To investigate experts' knowledge and opinions regarding relevant patient safety problems, their measurability in existing clinical routine data and potential challenges in the field. We also wanted to get an overview of already deployed indicators for patient safety.Semi structured interviews with 20 experts from different healthcare domains were conducted and analyzed using a qualitative content analysis methodology.The expert interviews offered a deeper insight into patient safety and quarried relevant patient safety problems including possibilities to measure them. The most often mentioned indicators were infection, complication and pressure ulcer.From an experts' perspective there are several challenges but equally a high potential for improving patient safety by the use of health IT.

Cerebral edema and delayed cerebral infarction (DCI) are common complications after aneurysmal subarachnoid hemorrhage (aSAH) and associated with poor functional outcome. Experimental data suggest that the amino acid taurine is released into the brain extracellular space secondary to cytotoxic edema and brain tissue hypoxia, and therefore may serve as a biomarker for secondary brain injury after aSAH. On the other hand, neuroprotective mechanisms of taurine treatment have been described in the experimental setting. We analyzed cerebral taurine levels using high-performance liquid chromatography in the brain extracellular fluid of 25 consecutive aSAH patients with multimodal neuromonitoring including cerebral microdialysis (CMD). Patient characteristics and clinical course were prospectively recorded. Associations with CMD-taurine levels were analyzed using generalized estimating equations with an autoregressive process to handle repeated observations within subjects. CMD-taurine levels were highest in the first days after aSAH (11.2 ± 3.2 µM/l) and significantly decreased over time (p