Exploring Opportunities for Clinical Data Warehouse Enhancement Through Data Catalog Integration

Secondary use of clinical health data implies a prior integration of mostly heterogenous and multidimensional data sets. A clinical data warehouse addresses the technological and organizational framework conditions required for this, by making any data available for analysis. However, users of a data warehouse often do not have a comprehensive overview of all available data and only know about their own data in their own systems - a situation which is also referred to as 'data siloed state'. This problem can be addressed and ultimately solved by implementation of a data catalog. Its core function is a search engine, which allows for searching the metadata collected from different data sources and thereby accessing all data there is. With this in mind, we conducted an explorative online market survey followed by vendor comparison as a pre-requisite for system selection of a data catalog. Assessment of vendor performance was based on seven predetermined and weighted selection criteria. Although three vendors achieved the highest score, results were lying closely together. Detailed investigations and test installations are needed for further narrowing down the selection process.

Quality and Effectiveness of AI Tools for Students and Researchers for Scientific Literature Review and Analysis

This study scrutinizes free AI tools tailored for supporting literature review and analysis in academic research, emphasizing their response to direct inquiries. Through a targeted keyword search, we cataloged relevant AI tools and evaluated their output variation and source validity. Our results reveal a spectrum of response qualities, with some tools integrating non-academic sources and others depending on outdated information. Notably, most tools showed a lack of transparency in source selection. Our study highlights two key limitations: the exclusion of commercial AI tools and the focus solely on tools that accept direct research queries. This raises questions about the potential capabilities of paid tools and the efficacy of combining various AI tools for enhanced research outcomes. Future research should explore the integration of diverse AI tools, assess the impact of commercial tools, and investigate the algorithms behind response variability. This study contributes to a better understanding of AI's role in academic research, emphasizing the importance of careful selection and critical evaluation of these tools in academic endeavors.

Understanding IT in Healthcare: Relevance and Training Needs of IT in Private Medical Practice

BACKGROUND

The integration of Information Technology (IT) into private medical practice is crucial in modern healthcare. Physicians managing office-related IT without proper knowledge risk operational inefficiencies and security.

OBJECTIVES

This study determines the relevance of specific IT topics in medical practice and identifies the training needs of physicians for enhancing IT competencies in healthcare.

METHODS

In March 2023 a cross-sectional online survey was conducted with physicians comprising nine IT-related topics in Tyrol, Austria.

RESULTS

The survey results highlighted a strong perceived relevance and high demand for IT education among physicians working in their medical practice, especially in areas of core medical IT and security. The majority of responses indicated high relevance (76.7%) and high demand (69.7%) for IT topics in medical practice.

CONCLUSION

The findings underscore a significant need for targeted IT training and support in medical practices, particularly in areas related to the medical practice and security. Addressing these needs could lead to improved healthcare delivery and better management of technological resources in the healthcare sector.

Unveiling the Surge: A Comprehensive Analysis of the Stimulating Impact of the Covid-19 Pandemic on Telemedicine and Its Academic Landscape

The Covid-19 pandemic spurred an unprecedented shift towards digitalization, prompting a surge in telehealth practices. This paper explores the impact of the pandemic on telemedicine through a comprehensive analysis of scientific publications. Utilizing a bibliometric approach, the study examines trends in telemedicine research before and after the onset of Covid-19. The systematic search in PubMed yielded 8,454 pre-Covid-19 publications (2016-2019) and 16,633 post-Covid-19 publications (2020-2023). A total of 21,989 distinct keywords were extracted. Co-occurrence maps reveal evolving thematic clusters, with "mhealth" and "ehealth" dominating pre-Covid-19, while "Covid-19" emerges as a top keyword post-pandemic. The Top-10 keywords shift post-Covid-19, reflecting dynamic research priorities. The bibliometric approach illuminates a heightened exploration of telehealth solutions post-pandemic, emphasizing the enduring impact of the crisis on academic discourse. Changes in key terms and shifts in key term ranking indicate dynamic research priorities and a broader consideration of multidimensional healthcare challenges. Acknowledging study limitations, the analysis offers a high-level perspective, focusing on authors' keywords. Despite challenges, the study provides a systematic overview, revealing the emergence of new telemedicine application domains and the need for further in-depth analyses. Future research directions may explore the ecological impact of telemedicine applications and other intriguing aspects, contributing to a comprehensive understanding of telemedicine's scholarly trajectory.

Transforming Clinical Information Systems: Empowering Healthcare through Telemedicine, Data Science, and Artificial Intelligence Applications

OBJECTIVE

In this synopsis, the editors of the Clinical Information Systems (CIS) section of the IMIA Yearbook of Medical Informatics overview recent research and propose a selection of best papers published in 2022 in the CIS field.

METHODS

The editors follow a systematic approach to gather relevant articles and select the best papers for the section. This year, they updated the query to incorporate the topic of telemedicine and removed search terms related to geographic information systems. The revised query resulted in a larger number of identified papers, necessitating the appointment of a third section editor to handle the increased workload. The editors narrowed the initial pool of articles to 15 candidate papers through a multi-stage selection process. At least seven independent reviews were collected for each candidate paper, and a selection meeting with the IMIA Yearbook editorial board led to the final selection of the best papers for the CIS section.

RESULTS

The query was carried out in mid-January 2023 and retrieved a deduplicated result set of 5,206 articles from 1,500 journals. This year, 15 papers were nominated as candidates, and four were finally selected as the best papers in the CIS section.Including telemedicine in the query resulted in a substantial increase in the number of papers found. The analysis highlights the growing convergence between clinical information systems and telemedicine, with mobile health (mHealth) technologies and data science applications gaining prominence. The selected candidate papers emphasize the practical impact of research efforts, focusing on patient-centric outcomes and benefits, including intelligent mobile health monitoring systems and AI-assisted decision-making in healthcare.

CONCLUSIONS

Looking ahead, the field of CIS is expected to continue evolving, driven by advances in telemedicine, mHealth technologies, data science, and AI integration, leading to more efficient, patient-oriented, and intelligent healthcare systems and overall improvement of global healthcare outcomes.

The Surviral Epidemiological Early Warning System Tyrol Dashboard - System, Functionality and Findings

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.

Telemedicine Research from Big Bang to 2022

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.

Making a Virtue of Necessity - A Highly Structured Clinical Data Warehouse as the Source of Assured Truth in a Hospital

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.

"All Quiet on the Western Front" - Clinical Information Systems Research in the Year 2021

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.

Medical Informatics and Digital Health Multilingual Ontology (MIMO): a tool to improve international collaborations

Background

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.

Objective

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.

Results

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.

Conclusion

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.

The effect of the volemic and cardiac status on brain oxygenation in patients with subarachnoid hemorrhage: a bi-center cohort study

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 < 10%). Patients were managed using a brain tissue oxygenation (P_btO₂) targeted protocol to prevent brain tissue hypoxia (BTH, P_btO₂ < 20 mmHg). To assess the association between CI and P_btO₂ and the effect of fluid challenges on CI and P_btO₂, 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 P_btO₂ levels (Wald = 14.2; p < 0.001). Neither daily fluid input nor fluid balance was associated with absolute P_btO₂ levels (p = 0.94 and p = 0.85, respectively) or the occurrence of BTH (p = 0.68 and p = 0.71, respectively). P_btO₂ levels were not significantly different in preload dependent patients compared to episodes of euvolemia. P_btO₂ 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 P_btO₂ only in the presence of baseline BTH. Individualized hemodynamic management requires advanced cardiac and brain monitoring in critically ill SAH patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13613-021-00960-z.

Clinical Information Systems Research in the Pandemic Year 2020

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.

Visual Analytics in Delirium Management

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.

IT-Assisted Process Management in Healthcare

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.

Evaluating Performance and Interpretability of Machine Learning Methods for Predicting Delirium in Gerontopsychiatric Patients

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.

Trends in Clinical Information Systems Research in 2019

Objective : To give an overview of recent research and to propose a selection of best papers published in 2019 in the field of Clinical Information Systems (CIS).

Method : Each year, we apply a systematic process to retrieve articles for the CIS section of the IMIA Yearbook of Medical Informatics. For six years now, we use the same query to find relevant publications in the CIS field. Each year we retrieve more than 2,000 papers. As CIS section editors, we categorize the retrieved articles in a multi-pass review to distill a pre-selection of 15 candidate best papers. Then, Yearbook editors and external reviewers assess the selected candidate best papers. Based on the review results, the IMIA Yearbook Editorial Committee chooses the best papers during the selection meeting. We used text mining, and term co-occurrence mapping techniques to get an overview of the content of the retrieved articles.

Results : We carried out the query in mid-January 2020 and retrieved a de-duplicated result set of 2,407 articles from 1,023 different journals. This year, we nominated 14 papers as candidate best papers, and three of them were finally selected as best papers in the CIS section. As in previous years, the content analysis of the articles revealed the broad spectrum of topics covered by CIS research.

Conclusions : We could observe ongoing trends, as seen in the last years. Patient benefit research is in the focus of many research activities, and trans-institutional aggregation of data remains a relevant field of work. Powerful machine-learning-based approaches, that use readily available data now often outperform human-based procedures. However, the ethical perspective of this development often comes too short in the considerations. We thus assume that ethical aspects will and should deliver much food for thought for future CIS research.

Implementing National Electronic Health Records in Nursing Homes in Tyrol: A Nursing Management Perspective

BACKGROUND

Health information technologies as electronic health records (EHR) have the potential to improve the quality and efficiency of health care. Implementing national EHR in nursing homes in Tyrol is a required task within the next years.

OBJECTIVES

To explore and analyze the current situation of information exchange in nursing homes in Tyrol as well as expected potentials and challenges of an ELGA implementation from a nursing management perspective.

METHODS

Semi-structured interviews with nine nursing managers of nursing homes in Tyrol were conducted and analyzed using qualitative content analysis.

RESULTS

The explorative interviews offered a glance at the actual information exchange with other institutions and at the perception of nursing managers regarding potentials (e.g. decreasing organizational effort) and challenges (e.g. incompleteness of available patient information) of the nationally mandated implementation of ELGA in the nursing homes in Tyrol.

CONCLUSION

The interviews with the nine nursing managers of nursing homes in Tyrol revealed some hopes (e.g. the reduction of double documentation) that ELGA will probably not be able to fulfill.

Learning Analytics and the Community of Inquiry: Indicators to Analyze and Visualize Online-Based Learning

BACKGROUND

The Community of Inquiry (CoI) describes success factors for online-based learning.

OBJECTIVES

To develop approaches for automatic analysis of CoI to be visualized within student and teacher dashboards.

METHODS

Extending indicators from social network analysis and linguistics; evaluation within a case study.

RESULTS

The project is just starting.

CONCLUSION

Results will help to better understand and improve cooperative online-based learning in higher education.

FHIR Analytics - Pragmatic Review of Recent Studies

BACKGROUND

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.

OBJECTIVES

Analyze the ongoing development of analytical implementations of FHIR.

METHODS

Pragmatic Review of current research and implementation projects.

RESULTS

US healthcare providers have implemented FHIR in their products, enabling scalable analytical tools. Europe demonstrated interest in FHIR.

CONCLUSION

The potential of FHIR analytics is a value-added use case of the implementation of FHIR.

Automated Mapping of LEP Nursing Data to Nursing Minimum Data Sets

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.

Developing a Model for Using Clinical Routine Data to Analyze Nursing Sensitive Patient Outcome Indicators

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.

Towards a Systematic Construction of a Minimum Data Set for Delirium to Support Secondary Use of Clinical Routine Data

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.

Managing Complexity. From Documentation to Knowledge Integration and Informed Decision Findings from the Clinical Information Systems Perspective for 2018

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.

Impact of Students' Presence and Course Participation on Learning Outcome in Co-Operative Online-based Courses

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.

Topics for Continuous Education in Nursing Informatics: Results of a Survey Among 280 Austrian Nurses

BACKGROUND

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.

OBJECTIVES

To analyze the need for continuous education in health informatics among Austrian nurses.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

On the Way to Close the Loop in Information Logistics: Data from the Patient - Value for the Patient

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.

Brain Extracellular Interleukin-6 Levels Decrease Following Antipyretic Therapy with Diclofenac in Patients with Spontaneous Subarachnoid Hemorrhage

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 Hunt & Hess 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-X² = 106) decreased at 2 hours to 86.3 pg/mL (IQR: 7-1946), at 4 hours to 40.9 pg/mL (IQR: 4-1237), and at 8 hours to 53.5 pg/mL (IQR: 5-1085), independent of probe location or day after bleeding. Parenteral diclofenac may attenuate brain extracellular proinflammatory response in poor-grade aSAH patients.

Brain temperature but not core temperature increases during spreading depolarizations in patients with spontaneous intracerebral hemorrhage

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 (T_brain) and core-temperature (T_core) relative to the occurrence of SDs. Twenty consecutive comatose ICH patients with multimodal electrocorticograpy (ECoG) and T_brain 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 T_core and T_brain was 37.3℃ (36.9-37.8) and 37.4℃ (36.7-37.9), respectively. T_brain but not T_core significantly increased 25 min preceding the onset of SDs by 0.2℃ (0.1-0.2; p < 0.001) and returned to baseline 35 min following SDs. During clusters, T_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 < 0.001) of developing SDs was observed during episodes of T_brain ≥ 38.0℃ (23% probability), than during T_brain ≤ 36.6℃ (9% probability). Spreading depolarizations - and in particular clusters of SDs - may increase brain temperature following ICH.

Building a Community of Inquiry Within an Online-Based Health Informatics Program: Instructional Design and Lessons Learned

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.

Improving Patient Safety by Reusing Clinical Routine Data - An Expert Survey on Patient Safety Indicators

BACKGROUND

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.

OBJECTIVE

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.

METHODS

Semi structured interviews with 20 experts from different healthcare domains were conducted and analyzed using a qualitative content analysis methodology.

RESULTS

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.

CONCLUSION

From an experts' perspective there are several challenges but equally a high potential for improving patient safety by the use of health IT.

Clinical Information Systems as the Backbone of a Complex Information Logistics Process: Findings from the Clinical Information Systems Perspective for 2016

Objective: To summarize recent research and to propose a selection of best papers published in 2016 in the field of Clinical Information Systems (CIS). Method: The query used to retrieve the articles for the CIS section of the 2016 edition of the IMIA Yearbook of Medical Informatics was reused. It again aimed at identifying relevant publications in the field of CIS from PubMed and Web of Science and comprised search terms from the Medical Subject Headings (MeSH) catalog as well as additional free text search terms. 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, term co-occurrence mapping, and topic modelling techniques were used to get an overview on the content of the retrieved articles. Results: The query was carried out in mid-January 2017, yielding a consolidated result set of 2,190 articles published in 921 different journals. Out of them, 14 papers were nominated as candidate best papers and three of them were finally selected as the best papers of the CIS field. The content analysis of the articles revealed the broad spectrum of topics covered by CIS research. Conclusions: The CIS field is multi-dimensional and complex. It is hard to draw a well-defined outline between CIS and other domains or other sections of the IMIA Yearbook. The trends observed in the previous years are progressing. Clinical information systems are more than just sociotechnical systems for data collection, processing, exchange, presentation, and archiving. They are the backbone of a complex, trans-institutional information logistics process.

EsPRit: ethics committee proposals for Long Term Medical Data Registries in rapidly evolving research fields - a future-proof best practice approach

Background

Long-term data collection is a challenging task in the domain of medical research. Many effects in medicine require long periods of time to become traceable e.g. the development of secondary malignancies based on a given radiotherapeutic treatment of the primary disease. Nevertheless, long-term studies often suffer from an initial lack of available information, thus disallowing a standardized approach for their approval by the ethics committee. This is due to several factors, such as the lack of existing case report forms or an explorative research approach in which data elements may change over time.

In connection with current medical research and the ongoing digitalization in medicine, Long Term Medical Data Registries (MDR-LT) have become an important means of collecting and analyzing study data. As with any clinical study, ethical aspects must be taken into account when setting up such registries.

This work addresses the problem of creating a valid, high-quality ethics committee proposal for medical registries by suggesting groups of tasks (building blocks), information sources and appropriate methods for collecting and analyzing the information, as well as a process model to compile an ethics committee proposal (EsPRit).

Methods

To derive the building blocks and associated methods software and requirements engineering approaches were utilized. Furthermore, a process-oriented approach was chosen, as information required in the creating process of ethics committee proposals remain unknown in the beginning of planning an MDR-LT. Here, we derived the needed steps from medical product certification. This was done as the medical product certification itself also communicates a process-oriented approach rather than merely focusing on content. A proposal was created for validation and inspection of applicability by using the proposed building blocks. The proposed best practice was tested and refined within SEMPER (Secondary Malignoma - Prospective Evaluation of the Radiotherapeutics dose distribution as the cause for induction) as a case study.

Results

The proposed building blocks cover the topics of “Context Analysis”, “Requirements Analysis”, “Requirements Validation”, “Electronic Case Report (eCRF) Design” and “Overall Concept Creation”. Additional methods are attached with regards to each topic. The goals of each block can be met by applying those methods. The proposed methods are proven methods as applied in e.g. existing Medical Data Registry projects, as well as in software or requirements engineering.

Conclusion

Several building blocks and attached methods could be identified in the creation of a generic ethics committee proposal. Hence, an Ethics Committee can make informed decisions on the suggested study via said blocks, using the suggested methods such as “Defining Clinical Questions” within the Context Analysis. The study creators have to confirm that they adhere to the proposed procedure within the ethic proposal statement. Additional existing Medical Data Registry projects can be compared to EsPRit for conformity to the proposed procedure. This allows for the identification of gaps, which can lead to amendments requested by the ethics committee.

On Teaching International Courses on Health Information Systems. Lessons Learned during 16 Years of Frank - van Swieten Lectures on Strategic Information Management in Health Information Systems

Background

Health information systems (HIS) are one of the most important areas for biomedical and health informatics. In order to professionally deal with HIS well-educated informaticians are needed. Because of these reasons, in 2001 an international course has been established: The Frank – van Swieten Lectures on Strategic Information Management of Health Information Systems.

Objectives

Reporting about the Frank – van Swieten Lectures and about our students‘ feedback on this course during the last 16 years. Summarizing our lessons learned and making recommendations for such international courses on HIS.

Methods

The basic concept of the Frank – van Swieten lectures is to teach the theoretical background in local lectures, to organize practical exercises on modelling sub-information systems of the respective local HIS and finally to conduct Joint Three Days as an international meeting were the resulting models are introduced and compared.

Results

During the last 16 years, the Universities of Amsterdam, Braunschweig, Heidelberg/Heilbronn, Leipzig as well as UMIT were involved in running this course. Overall, 517 students from these universities participated. Our students‘ feedback was clearly positive. The Joint Three Days of the Frank – van Swieten Lectures, where at the end of the course all students can meet, turned out to be an important component of this course. Based on the last 16 years, we recommend common teaching materials, agreement on equivalent clinical areas for the exercises, support of group building of international student groups, motivation of using a collaboration platform, ensuring quality management of the course, addressing different levels of knowledge of the students, and ensuring sufficient funding for joint activities.

Conclusions

Although associated with considerable additional efforts, we can clearly recommend establishing such international courses on HIS, such as the Frank – van Swieten Lectures.

Innovative Power of Health Care Organisations Affects IT Adoption: A bi-National Health IT Benchmark Comparing Austria and Germany

Multinational health IT benchmarks foster cross-country learning and have been employed at various levels, e.g. OECD and Nordic countries. A bi-national benchmark study conducted in 2007 revealed a significantly higher adoption of health IT in Austria compared to Germany, two countries with comparable healthcare systems. We now investigated whether these differences still persisted. We further studied whether these differences were associated with hospital intrinsic factors, i.e. the innovative power of the organisation and hospital demographics. We thus performed a survey to measure the "perceived IT availability" and the "innovative power of the hospital" of 464 German and 70 Austrian hospitals. The survey was based on a questionnaire with 52 items and was given to the directors of nursing in 2013/2014. Our findings confirmed a significantly greater IT availability in Austria than in Germany. This was visible in the aggregated IT adoption composite score "IT function" as well as in the IT adoption for the individual functions "nursing documentation" (OR = 5.98), "intensive care unit (ICU) documentation" (OR = 2.49), "medication administration documentation" (OR = 2.48), "electronic archive" (OR = 2.27) and "medication" (OR = 2.16). "Innovative power" was the strongest factor to explain the variance of the composite score "IT function". It was effective in hospitals of both countries but significantly more effective in Austria than in Germany. "Hospital size" and "hospital system affiliation" were also significantly associated with the composite score "IT function", but they did not differ between the countries. These findings can be partly associated with the national characteristics. Indicators point to a more favourable financial situation in Austrian hospitals; we thus argue that Austrian hospitals may possess a larger degree of financial freedom to be innovative and to act accordingly. This study is the first to empirically demonstrate the effect of "innovative power" in hospitals on health IT adoption in a bi-national health IT benchmark. We recommend directly including the financial situation into future regression models. On a political level, measures to stimulate the "innovative power" of hospitals should be considered to increase the digitalisation of healthcare.

Monitoring of Students' Interaction in Online Learning Settings by Structural Network Analysis and Indicators

Learning as a constructive process works best in interaction with other learners. Support of social interaction processes is a particular challenge within online learning settings due to the spatial and temporal distribution of participants. It should thus be carefully monitored. We present structural network analysis and related indicators to analyse and visualize interaction patterns of participants in online learning settings. We validate this approach in two online courses and show how the visualization helps to monitor interaction and to identify activity profiles of learners. Structural network analysis is a feasible approach for an analysis of the intensity and direction of interaction in online learning settings.

Developing and Evaluating Collaborative Online-Based Instructional Designs in Health Information Management

The number of students enrolled in online courses is increasing steadily. Distance education offers many advantages, but also has inherent challenges. Successful distance education needs a thoughtfully designed instructional strategy where students are supported to actively create knowledge. We present the design and evaluation of three online-based courses in health informatics. The courses were based on a collaborative instructional strategy. The evaluation comprised workload analysis, student evaluation, student interviews and student reflections. Students expressed high satisfaction with online learning, despite a high workload, and high perceived learning outcomes. Using the Community of Inquiry framework as reference, we found very high levels of teaching presence, social presence and cognitive presence. Summarizing, we found that the chosen instructional strategy supported student-centered, collaborative learning. We conclude by presenting lesson learned for online-based instructional design.

New Problems - New Solutions: A Never Ending Story. Findings from the Clinical Information Systems Perspective for 2015

OBJECTIVE

To summarize recent research and to propose a selection of best papers published in 2015 in the field of Clinical Information Systems (CIS).

METHOD

The query which had been used last year to retrieve articles for the CIS section of the IMIA Yearbook of Medical Informatics 2015 was refined. It again aimed at identifying relevant publications in the field of CIS and comprised search terms from the Medical Subject Headings (MeSH) catalog 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 separately by the two section editors. The final selection of 15 candidate papers was then peer-reviewed by Yearbook editors and external reviewers. Based on the review results the four best papers were then selected at the best papers selection meeting with the IMIA Yearbook editorial board. To get an overview on the content of the retrieved articles we applied text mining and term co-occurrence mapping techniques.

RESULTS

The query was carried out in mid-January 2016, yielding a combined result set of 1851 articles which were published in 790 different journals. The most relevant terms from abstracts and titles of these articles were assigned to six different clusters. A majority of articles dealt with two thematic blocks, problems and solutions in the CIS field. The majority of the 2016 CIS candidate papers and all four best papers could be assigned to these two thematic blocks.

CONCLUSIONS

We identified two main tracks among the CIS candidate and best papers as well as in CIS research activities in general: problems and solutions. A never ending cycle of continuous improvement.

SPIRIT: Systematic Planning of Intelligent Reuse of Integrated Clinical Routine Data. A Conceptual Best-practice Framework and Procedure Model

BACKGROUND

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 nontrivial, 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 secondary 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.

Intelligent Re-Use of Nursing Routine Data: Opportunities and Challenges

Secondary use of structured nursing routine data receives an increasing attention in healthcare and is supposed to bear huge potential for different purposes. However, building and analyzing such integrated nursing routine data repositories are nontrivial, challenging tasks. The workshop gives an insight in the state of the art of secondary data analysis in nursing and addresses possible opportunities as well as the main challenges when re-using nursing data for secondary analyses. The target audience of the workshop comprises all stakeholders who are interested in the intelligent re-use of nursing data (e.g. decision-makers, public health officials, nursing managers, nursing informatics/IT staff, scientists, data analysts as well as industry representatives).

An Iterative Methodology for Developing National Recommendations for Nursing Informatics Curricula

The increasing importance of IT in nursing requires educational measures to support its meaningful application. However, many countries do not yet have national recommendations for nursing informatics competencies. We thus developed an iterative triple methodology to yield validated and country specific recommendations for informatics core competencies in nursing. We identified relevant competencies from national sources (step 1), matched and enriched these with input from the international literature (step 2) and fed the resulting 24 core competencies into a survey (120 invited experts from which 87 responded) and two focus group sessions with a total of 48 experts (steps 3a/3b). The subsequent focus group sessions confirmed and expanded the findings. As a result, we were able to define role specific informatics core competencies for three countries.

Implementation of the Austrian Nursing Minimum Data Set (NMDS-AT): A Feasibility Study

BACKGROUND

An Austrian Nursing Minimum Data Set (NMDS-AT) has been developed to describe the diversity of patient populations and variability of nursing care based on nursing diagnoses, nursing interventions, and nursing outcomes. The aim of this study is to test the feasibility of using this NMDS-AT by assessing the availability of data needed for the NMDS-AT in routine nursing documentation, and to assess its reliability and usefulness.

METHODS

Data were collected in a general hospital from patient records of 20 patients representing 457 patient days. Availability of needed data was assessed by two raters in a chart review based on an NMDS-AT form. The interrater reliability (n=20) and intrarater reliability (n=5) was assessed using Cohen's kappa coefficient and intraclass correlation coefficient (ICC). Usefulness was assessed by verifying whether typical analysis questions can be answered by the documented NMDS-AT data.

RESULTS

In the 20 patient records, thirteen nursing diagnoses, 50 nursing interventions, and five nursing outcomes occurred, representing 68 (58.6%) of the overall 116 data elements of the NMDS-AT. The data were found at different data sources (e.g., electronic nursing record or paper-based fever chart) and in various forms (e.g., standardized or free text). The interrater reliability of the thirteen nursing diagnoses showed kappa values (percentage of agreement) ranging from 0.35 (85%) to 1.00 (100%). The 50 nursing interventions showed ICCs ranging from 0.03 to 1.00. All nursing outcomes showed an ICC of 1.00. The intrarater reliability showed 100% agreement. Performing typical analysis questions showed that the extracted NMDS-AT data are able to answer questions of clinical management, of policy makers, and of nursing science.

CONCLUSIONS

The NMDS-AT was found to be feasible: needed data was available in the analysed patient records, data extraction showed good reliability, and typical analysis could be performed and showed interesting results. Before the NMDS-AT can be introduced in healthcare institutions, the following challenges need to be addressed: 1. improve the quality of nursing documentation; 2. reduce fragmentation of documentation; 3. use a standardized nursing classification system; and 4. establish mappings between nursing classification systems and the NMDS-AT.

Findings from the Clinical Information Systems Perspective

OBJECTIVE

To summarize recent research and to propose a selection of best papers published in 2014 in the field of Clinical Information Systems (CIS).

METHOD

A query with search terms from the Medical Subject Headings (MeSH) catalog as well as additional free text search terms was designed to identify relevant publications in the field of clinical information systems from PubMed and Web of Science®. The retrieved articles were then categorized in a multi-pass review carried out separately by the section editors. The final selection of 15 candidate papers was then peerreviewed by Yearbook editors and external reviewers. Based on the review results the four best papers were then selected at the best papers selection meeting with the IMIA Yearbook editorial board.

RESULTS

The query was carried out in mid-January 2015, yielding a combined result set of 1525 articles which were published in 722 different journals. Among these articles two main thematic sections were identified: i) Interoperability from a syntactical and semantic point of view as well as from a longterm preservation and organizational/legal point of view and ii) secondary use of existing health data in all its shades. Here, patient safety was a major scope of application.

CONCLUSIONS

CIS have become mature over the last years. The focus has now moved beyond data acquisition for just supporting the local care workflows. Actual research efforts in the CIS domain comprise the breakdown of information silos, the reduction of barriers between different systems of different care providers and secondary use of accumulated health data for multiple purposes.

A Nursing Intelligence System to Support Secondary Use of Nursing Routine Data

BACKGROUND

Nursing care is facing exponential growth of information from nursing documentation. This amount of electronically available data collected routinely opens up new opportunities for secondary use.

OBJECTIVES

To present a case study of a nursing intelligence system for reusing routinely collected nursing documentation data for multiple purposes, including quality management of nursing care.

METHODS

The SPIRIT framework for systematically planning the reuse of clinical routine data was leveraged to design a nursing intelligence system which then was implemented using open source tools in a large university hospital group following the spiral model of software engineering.

RESULTS

The nursing intelligence system is in routine use now and updated regularly, and includes over 40 million data sets. It allows the outcome and quality analysis of data related to the nursing process.

CONCLUSIONS

Following a systematic approach for planning and designing a solution for reusing routine care data appeared to be successful. The resulting nursing intelligence system is useful in practice now, but remains malleable for future changes.

Job Profiles of Biomedical Informatics Graduates. Results of a Graduate Survey

BACKGROUND

Biomedical informatics programs exist in many countries. Some analyses of the skills needed and of recommendations for curricular content for such programs have been published. However, not much is known of the job profiles and job careers of their graduates.

OBJECTIVES

To analyse the job profiles and job careers of 175 graduates of the biomedical informatics bachelor and master program of the Tyrolean university UMIT.

METHODS

Survey of all biomedical informatics students who graduated from UMIT between 2001 and 2013.

RESULTS

Information is available for 170 graduates. Eight percent of graduates are male. Of all bachelor graduates, 86% started a master program. Of all master graduates, 36% started a PhD. The job profiles are quite diverse: at the time of the survey, 35% of all master graduates worked in the health IT industry, 24% at research institutions, 9% in hospitals, 9% as medical doctors, 17% as informaticians outside the health care sector, and 6% in other areas. Overall, 68% of the graduates are working as biomedical informaticians. The results of the survey indicate a good job situation for the graduates.

CONCLUSIONS

The job opportunities for biomedical informaticians who graduated with a bachelor or master degree from UMIT seem to be quite good. The majority of graduates are working as biomedical informaticians. A larger number of comparable surveys of graduates from other biomedical informatics programs would help to enhance our knowledge about careers in biomedical informatics.

Development of the Austrian Nursing Minimum Data Set (NMDS-AT): the third Delphi Round, a quantitative online survey

BACKGROUND

A Nursing Minimum Data Set (NMDS) aims at systematically describing nursing care in terms of patient problems, nursing activities, and patient outcomes. In an earlier Delphi study, 56 data elements were proposed to be included in an Austrian Nursing Minimum Data Set (NMDS-AT).

OBJECTIVES

To identify the most important data elements of this list, and to identify appropriate coding systems.

METHODS

Online Delphi-based survey with 88 experts.

RESULTS

43 data elements were rated as relevant for an NMDS-AT (strong agreement of more than half of the experts): nine data elements concerning the institution, patient demographics, and medical condition; 18 data elements concerning patient problems by using nursing diagnosis; seven data elements concerning nursing outcomes, and nine data elements concerning nursing interventions. As classification systems, national classification systems were proposed besides ICNP, NNN, and nursing-sensitive indicators.

CONCLUSION

The resulting proposal for an NMDS-AT will now be tested with routine data.

Crucial factors for the acceptance of a computerized national medication list: insights into findings from the evaluation of the Austrian e-Medikation pilot

OBJECTIVE

The objective of this paper is to present crucial factors among registered doctors and pharmacists for acceptance of the Austrian 'e-Medikation' system which is aimed at providing, on a national level, complete and recent information on all the medication that were prescribed or dispensed to a patient.

METHODS

As the accompanying formative evaluation study of the pilot project showed different overall acceptance rates among participating physicians and pharmacists, a decision tree analysis of 30 standardized survey items was performed to identify crucial acceptance factors.

RESULTS

For the physicians' group, only two items (fear of improper data use and satisfaction with software support) were crucial for overall e-Medikation acceptance. The analysis of the pharmacists' data resulted in five crucial factors primarily focusing on functional aspects and the perceived benefits of e-Medikation.

CONCLUSION

The results indicate that the acceptance among physicians and pharmacists depends on quite different factors. This must be taken into account during the planned rollout of e-Medikation or of comparable products.