Effectiveness of eHealth interventions and information needs in palliative care: a systematic literature review.

BACKGROUND: One of the key components in palliative care is communication. eHealth technologies can be an effective way to support communications among participants in the process of palliative care. However, it is unclear to what extent information technology has been established in this field. OBJECTIVE: Our goal was to systematically identify studies and analyze the effectiveness of eHealth interventions in palliative care and the information needs of people involved in the palliative care process. METHODS: We conducted a systematic literature search using PubMed, Embase, and LILACS according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We collected and analyzed quantitative and qualitative data regarding effectiveness of eHealth interventions and users' information needs in palliative care. RESULTS: Our search returned a total of 240 articles, 17 of which met our inclusion criteria. We found no randomized controlled trial studying the effects of eHealth interventions in palliative care. Studies tended to be observational, non-controlled studies, and a few quasi-experimental studies. Overall there was great heterogeneity in the types of interventions and outcome assessments; some studies reported some improvement on quality of care, documentation effort, cost, and communications. The most frequently reported information need concerned pain management. CONCLUSIONS: There is limited evidence around the effectiveness of eHealth interventions for palliative care patients, caregivers, and health care professionals. Focused research on information needs and high-quality clinical trials to assess their effectiveness are needed.

Reflections on 'health care in the information society--a prognosis for the year 2013'.

In the year 2000 a talk was given and later published on how health care could look like in the year 2013. The aim was to "identify priorities in medical informatics research and necessary activities by policymakers in order to ensure an efficient, advanced, and yet affordable future health care system" (Haux R, Ammenwerth E, Herzog W, Knaup P. Health care in the information society. A prognosis for the year 2013. Int J Med Inform. 2002; 66: 3-21). In the year 2013 a workshop took place, critically reflecting on the prognoses and theses made for the year 2013. This editorial is reporting on the 2013-workshop and is introducing three papers, in which the workshop results have been summarized.

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

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

Architecture of the Mass Spectrometry Data Management Pipeline in the SMART-CARE Project.

In the SMART-CARE project- a systems medicine approach to stratification of cancer recurrence in Heidelberg, Germany - a streamlined mass-spectrometry (MS) workflow for identification of cancer relapse was developed. This project has multiple partners from clinics, laboratories and computational teams. For optimal collaboration, consistent documentation and centralized storage, the linked data repository was designed. Clinical, laboratory and computational group members interact with this platform and store meta- and raw-data. The specific architectural choices, such as pseudonymization service, uploading process and other technical specifications as well as lessons learned are presented in this work. Altogether, relevant information in order to provide other research groups with a head-start for tackling MS data management in the context of systems medicine research projects is described.

Usability and User Experience of an mHealth App for Therapy Support of Patients With Breast Cancer: Mixed Methods Study Using Eye Tracking.

BACKGROUND: Early identification of quality of life (QoL) loss and side effects is a key challenge in breast cancer therapy. Digital tools can be helpful components of therapeutic support. Enable, a smartphone app, was used in a multicenter, prospective randomized controlled trial in 3 breast cancer centers. The app simultaneously serves as a therapy companion (eg, by displaying appointments), a tool for documenting QoL (eg, by enabling data collection for QoL questionnaires), and documentation of patient-reported side effects. The need for digital tools is continually rising. However, evidence of the effects of long-term use of mobile health (mHealth) apps in aftercare for patients with breast cancer is limited. Therefore, evaluating the usability and understanding the user experience of this mHealth app could potentially contribute valuable insights in this field. OBJECTIVE: A usability study was conducted to explore how patients with breast cancer receiving neoadjuvant, adjuvant, or palliative outpatient treatment rated their engagement with the app , the user experience, and the benefits of using the app. METHODS: A mixed methods approach was chosen to combine subjective and objective measures, including an eye-tracking procedure, a standardized usability questionnaire (mHealth App Usability Questionnaire), and semistructured interviews. Participants were surveyed twice during the study period. Interviews were transcribed verbatim and analyzed using thematic analysis. Analysis of the eye-tracking data was carried out using the tracker-integrated software. Descriptive analysis was conducted for the quantitative data. RESULTS: The mHealth App Usability Questionnaire results (n=105) indicated good overall usability for 2 different time points (4 wk: mean 89.15, SD 9.65; 20 wk: mean 85.57, SD 12.88). The qualitative analysis of the eye-tracking recordings (n=10) and interviews (n=16) showed that users found the Enable app easy to use. The design of the app, information about therapies and side effects, and usefulness of the app as a therapy companion were rated positively. Additionally, participants contributed requests for additional app features and suggestions for improving the content and usability of the app. Relevant themes included optimization of the appointment feature, updating the app's content regularly, and self-administration. In contrast to the app's current passive method of operation, participants expressed a desire for more active engagement through messaging, alarms, or emails. CONCLUSIONS: The results of this study demonstrate the good usability of the Enable app as well as the potential for further development. We concluded from patients' feedback and requests that mHealth apps could benefit from giving patients a more active role (eg, being able to actively document side effects as they occur). Additionally, regular updates of app content could further contribute to encouraging continued use of mHealth apps. Our findings may also assist other researchers in tailoring their mHealth apps to the actual needs of patients undergoing breast cancer therapy.

Next-generation study databases require FAIR, EHR-integrated, and scalable Electronic Data Capture for medical documentation and decision support.

Structured patient data play a key role in all types of clinical research. They are often collected in study databases for research purposes. In order to describe characteristics of a next-generation study database and assess the feasibility of its implementation a proof-of-concept study in a German university hospital was performed. Key characteristics identified include FAIR access to electronic case report forms (eCRF), regulatory compliant Electronic Data Capture (EDC), an EDC with electronic health record (EHR) integration, scalable EDC for medical documentation, patient generated data, and clinical decision support. In a local case study, we then successfully implemented a next-generation study database for 19 EDC systems (n = 2217 patients) that linked to i.s.h.med (Oracle Cerner) with the local EDC system called OpenEDC. Desiderata of next-generation study databases for patient data were identified from ongoing local clinical study projects in 11 clinical departments at Heidelberg University Hospital, Germany, a major tertiary referral hospital. We compiled and analyzed feature and functionality requests submitted to the OpenEDC team between May 2021 and July 2023. Next-generation study databases are technically and clinically feasible. Further research is needed to evaluate if our approach is feasible in a multi-center setting as well.

Automated calculation of ontology-based planning proposals: An application in reconstructive oral and maxillofacial surgery.

BACKGROUND: Structured modelling of surgical knowledge and its automated processing is still challenging. The aim of this work is to introduce a novel approach for automated calculation of ontology-based planning proposals in mandibular reconstruction and conduct a feasibility study. METHODS: The presented approach is composed of an RDF(S) ontology, a 3D mandible template and a calculator-optimiser algorithm to automatically calculate reconstruction proposals with fibula grafts. To validate the viability of the approach, a feasibility study was conducted on 164 simulated mandibular reconstructions. RESULTS: The ontology defines 244 different reconstruction variants and 80 analyses for optimization. In 146 simulated cases, a proposal could be automatically calculated (average time 8.79 ± 4.03 s). The assessments of the proposals by three clinical experts indicate the viability of the approach. CONCLUSIONS: Due to the modular separation between computational logic and domain knowledge, the developed concepts can be easily maintained, reused and adapted for other applications.

Proposing a Novel Hybrid Short-Term Exchange Program in Biomedical and Health Informatics Education.

International student exchange is a valuable opportunity for Biomedical and Health Informatics students to gain new perspectives and experiences. In the past, such exchanges have been made possible through international partnerships between universities. Unfortunately, numerous obstacles such as housing, financial concerns, and environmental implications related to travel, have made it difficult to continue international exchange. Experiences with hybrid and online education during covid-19 paved the way for a new approach that allows for short international exchange with a hybrid online-offline supervision model. This will be initiated with an exploration project between two international universities , each related to their respective institute's research focus.

IT as an enabler of sustainable use of data from innovative technical components for assisted living.

The authors see the major potential of systematically processing data from AAL-technology in higher sustainability, higher technology acceptance, higher security, higher robustness, higher flexibility and better integration in existing structures and processes. This potential is currently underachieved and not yet systematically promoted. The authors have written a position paper on potential and necessity of substantial IT research enhancing Ambient Assisted Living (AAL) applications. This paper summarizes the most important challenges in the fields health care, data protection, operation and user interfaces. Research in medical informatics is necessary among others in the fields flexible authorization concept, medical information needs, algorithms to evaluate user profiles and visualization of aggregated data.

The intellectual property management for data sharing in a German liver cancer research network.

Sharing data in biomedical research networks has great potential benefits including efficient use of resources, avoiding duplicate experiments and promoting collaboration. However, concerns from data producers about difficulties of getting proper acknowledgement for their contributions are becoming obstacles for efficient and network wide data sharing in reality. Effective and convenient ways of intellectual property management and acknowledging contributions to the data producers are required. This paper analyzed the system requirements for intellectual property management in a German liver cancer research network and proposed solutions for facilitating acknowledgement of data contributors using informatics tools instead of pure policy level strategies.

An encapsulated R application for the guided analysis of genomic data.

Microarrays are widely used in biomedical research. However, researchers conducting the biomedical assays are often not skilled to perform the necessary biostatistical preprocessing of the resulting data. As a result, researchers with different backgrounds contribute to the analysis, but often without documenting how the data were transformed. For a biomedical research network on liver cancer, we implemented a prototype that has two major aims: First, it should guide biomedical researchers through the analysis of microarray data by providing a limited amount of appropriate choices for the biostatistical procedures to be applied. Second, it should help to ensure data quality by documenting all transformations applied to the data set.

Towards Data Analysis Environment for Multi-Partner Clinical Research Project - SMART-CARE.

A Systems Medicine Approach to Stratification of Cancer Recurrence (SMART-CARE) establishes mass spectrometry-based systems medicine technologies and data analysis pipelines employing expertise of the multiple partners from Heidelberg biomedical campus. We have established a central linked data repository that links clinical, mass spectrometry, and data analysis teams to enable a full cycle of data management. Other questions of setting up the data analysis environment for the multi-partner clinical research project are addressed in this work, too.

Large-File Raw Data Synchronization for openBIS Research Repositories.

In a systems medicine research consortium, openBIS is used as a research data repository. To facilitate efficient upload of large files, openBIS is complemented by a Nextcloud data cloud system. Using a Nextcloud client, raw mass spectrometry data is automatically imported into the repository in the background, enabling comprehensive data provenance.

Service oriented data integration for a biomedical research network.

In biomedical research, a variety of data like clinical, genetic, expression of coding or non-coding ribonucleic acid (RNA) transcripts, or proteomic data are processed to gain new insights into diseases and therapies. In transregional research networks, geographically distributed projects work on comparable research questions with data from different resources and in different formats. Providing an information platform that integrates the data of the projects can enable cross-project analysis and provides an overview of available data and resources (tissue, blood, etc.). For a German liver cancer research network consisting of 22 individual projects, we develop the integrated information platform pelican - platform enhancing liver cancer networked research. In our generic approach, data are made available to the research network by standardized data services based on technologies provided by the cancer Biomedical Informatics Grid (caBIG). It has shown that publishing service metadata in a corresponding repository is a major prerequisite for automated discovery, integration, and conversion of data records and data services. We identified data confidentiality and intellectual property considerations as major challenges while establishing such an integrated information platform. As a first result we implemented a working prototype to validate our approach.

Measurement Performance of Activity Measurements with Newer Generation of Apple Watch in Wheelchair Users with Spinal Cord Injury.

BACKGROUND: The level of physical activity (PA) of people with spinal cord injury (SCI) has an impact on long-term complications. Currently, PA is mostly assessed by interviews. Wearable activity trackers are promising tools to objectively measure PA under everyday conditions. The only off-the-shelf, wearable activity tracker with specific measures for wheelchair users is the Apple Watch. OBJECTIVES: This study analyzes the measurement performance of Apple Watch Series 4 for wheelchair users and compares it with an earlier generation of the device. METHODS: Fifteen participants with subacute SCI during their first in-patient phase followed a test course using their wheelchair. The number of wheelchair pushes was counted manually by visual inspection and with the Apple Watch. Difference between the Apple Watch and the rater was analyzed with mean absolute percent error (MAPE) and a Bland-Altman plot. To compare the measurement error of Series 4 and an older generation of the device a t-test was calculated using data for Series 1 from a former study. RESULTS: The average of differences was 12.33 pushes (n = 15), whereas participants pushed the wheelchair 138.4 times on average (range 86-271 pushes). The range of difference and the Bland-Altman plot indicate an overestimation by Apple Watch. MAPE is 9.20% and the t-test, testing for an effect of Series 4 on the percentage of error compared with Series 1, was significant with p < 0.05. CONCLUSION: Series 4 shows a significant improvement in measurement performance compared with Series 1. Series 4 can be considered as a promising data source to capture the number of wheelchair pushes on even grounds. Future research should analyze the long-term measurement performance during everyday conditions of Series 4.

Data Management for Systems Medicine: The SMART-CARE Joint Environment.

For a research project on mass spectrometry, a streamlined, harmonized and robust analytical pipeline is built to predict tumor recurrence. By means of standardization all steps from sample collection, analysis, proteome, and metabolome analysis are harmonized. Challenges like non-central identificators and distributed data are overcome with a centralized high-performant IT-platform in combination with a pseudonymization service and harmonization.

Facilitating secondary use of medical data by using openEHR archetypes.

Clinical trials are of high importance for medical progress. But even though more and more clinical data is available in electronic patient records (EPRs) and more and more electronic data capture (EDC) systems are used in trials, there is still a gap which makes EPR / EDC interoperability difficult and hampers secondary use of medical routine data. The openEHR architecture for Electronic Health Records is based on a two level modeling approach which makes use of 'archetypes'. We want to analyze whether archetypes can help to bridge this gap by building an integrated EPR / EDC system based on openEHR archetypes. We used the 'openEHR Reference Framework and Application' (Opereffa) and existing archetypes for medical data. Furthermore, we developed dedicated archetypes to document study meta data. We developed a first prototype implementation of an archetype based integrated EPR / EDC system. Next steps will be the evaluation of an extended prototype in a real clinical trial scenario. Opereffa was a good starting point for our work. OpenEHR archetypes proved useful for secondary use of health data.

Hospital Information Systems.

Hospital information systems (HIS) have to be considered as socio-technical systems, which consist of technical components as well as of the human aspect like hospital staff and patients. HIS strive for the optimization of information logistics, to support tasks like patient care and administration of a hospital. To systematically manage such complex systems, HIS can be analyzed on three layers: First, tasks and entity types should be considered. Entity types represent information which is used and updated by tasks like 'Patient Admission' or 'Decision Making'. Second, application components of a HIS should be analyzed, they can be either computer-based or paper-based; both of them support tasks from the first layer. Therefore, they store and exchange information. The third layer analyzes physical data processing components of a HIS, like servers, workstations or networks. The three-layered view can be used for the systematic information management of HIS on three perspectives: strategic information management plans the development of the whole HIS for the next 5 years and longer. Measures from strategic information management are implemented as projects, coordinated by the tactical information management. The operational information management ensures a continuous and reliable operation of the HIS.

Current Use of Sensor-Based Measurements for Paraplegics: A Literature Review.

Sensors are used in many fields to measure physical phenomena, often on mobile persons. Paraplegia is a disease with a massive impact on the ability to move, so patients show changes in walking behaviour or are even wheelchair users. It is unclear how sensors can be used with paraplegics to generate valid data for research. In the ParaReg project, such data shall be integrated with a medical register. In this paper, we elaborate current approaches for sensor measurements that might serve as an additional data source for ParaReg with the help of a literature review. We queried IEEE Xplore and MEDLINE to find publications that describe the current use of sensors for patients with paraplegia. The retrieved publications were screened for eligibility by two reviewers independently. To ensure reproducibility, we conducted an initial alignment. All publications were assessed based on their abstract. Inclusions were analysed for their major topic, and we proposed categories, which were statistically described afterwards. We retrieved 685 publications in total and included 287 publications in our analysis. The categories we found are: "diagnostic sensor tools for clinical environments", "seating position analysis", "functional electrical stimulation (FES) / neuroprosthesis control", "seating position analysis", "control systems for devices" and "assessment of physical activity". "FES / neuroprosthesis control" shows most publications and the highest publication rate in history, followed by "assessment of physical activity".

On the Construction of Multilingual Corpora for Clinical Text Mining.

The amount of digital data derived from healthcare processes have increased tremendously in the last years. This applies especially to unstructured data, which are often hard to analyze due to the lack of available tools to process and extract information. Natural language processing is often used in medicine, but the majority of tools used by researchers are developed primarily for the English language. For developing and testing natural language processing methods, it is important to have a suitable corpus, specific to the medical domain that covers the intended target language. To improve the potential of natural language processing research, we developed tools to derive language specific medical corpora from publicly available text sources. n order to extract medicine-specific unstructured text data, openly available pub-lications from biomedical journals were used in a four-step process: (1) medical journal databases were scraped to download the articles, (2) the articles were parsed and consolidated into a single repository, (3) the content of the repository was de-scribed, and (4) the text data and the codes were released. In total, 93 969 articles were retrieved, with a word count of 83 868 501 in three different languages (German, English, and Spanish) from two medical journal databases Our results show that unstructured text data extraction from openly available medical journal databases for the construction of unified corpora of medical text data can be achieved through web scraping techniques.