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.

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.

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.

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.

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.

Digital teaching as an instrument for cross-location teaching networks in medical informatics: opportunities and challenges.

The increasingly digitized healthcare system requires new skills from all those involved. In order to impart these competencies, appropriate courses must be developed at educational institutions. In view of the rapid development of new aspects of digitization, this presents a challenge; suitable teaching formats must be developed successively. The establishment of cross-location teaching networks is one way to better meet training needs and to make the necessary spectrum of educational content available. As part of the Medical Informatics Initiative, the HiGHmed consortium is establishing such a teaching network, in the field of medical informatics, which covers many topics related to the digitization of the health care system. Various problem areas in the German education system were identified that hinder the development of the teaching network. These problem areas were prioritized firstly according to the urgency of the solution from the point of view of the HiGHmed consortium and secondly according to existing competencies in the participating societies. A workshop on the four most relevant topics was organized with experts from the German Society for Medical Informatics, Biometry and Epidemiology (GMDS), the Society for Medical Education (GMA) and the HiGHmed consortium. These are: recognition of exam results from teaching modules that are offered digitally and across locations, and their integration into existing curricula; recognition of digital, cross-location teaching in the teachers' teaching load; nationwide uniform competencies for teachers, in order to be able to conduct digital teaching effectively and with comparable quality; technical infrastructure to efficiently and securely communicate and manage the recognition of exam results between educational institutions. For all subject areas, existing preliminary work was identified on the basis of working questions, and short- and long-term needs for action were formulated. Finally, a need for the redesign of a technologically supported syntactic and semantic interoperability of learning performance recording was identified.

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.

eHealth and Clinical Documentation Systems.

eHealth is the use of modern information and communication technology (ICT) for trans-institutional healthcare purposes. Important subtopics of eHealth are health data sharing and telemedicine. Most of the clinical documentation to be shared is collected in patient records to support patient care. More sophisticated approaches to electronic patient records are trans-institutional or (inter-)national. Other aims for clinical documentation are quality management, reimbursement, legal issues, and medical research. Basic prerequisite for eHealth is interoperability, which can be divided into technical, semantic and process interoperability. There is a variety of international standards to support interoperability. Telemedicine is a subtopic of eHealth, which bridges spatial distance by using ICT for medical (inter-)actions. We distinguish telemedicine among healthcare professionals and telemedicine between health care professionals and patients. Both have a great potential to face the challenges of aging societies, the increasing number of chronically ill patients, multimorbidity and low number of physicians in remote areas. With ongoing digitalization more and more data are available digitally. Clinical documentation is an important source for big data analysis and artificial intelligence. The patient has an important role: Telemonitoring, wearable technologies, and smart home devices provide digital health data from daily life. These are high-quality data which can be used for medical decisions.

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.

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".

A Concept for Graph-Based Temporal Similarity of Patient Data.

Computer-based decision support systems are often used for dedicated tasks such as the detection of sepsis. However, positive predictive values for sepsis detection are reported to achieve only around 46%. In this paper we describe a novel approach to use temporal data of electronic patient records based on similarity measures. We apply the concept of case-based reasoning, which is well-established in many fields of medical informatics. Temporal patient data are organized in a time-graph structure. For the quantification of similarity between cases, we exploit graph theory based approaches. For development and evaluation of our time-graph similarity frame we use the open MIMIC III dataset. In a later phase, we envision to transfer our concept from sepsis to other diseases.

A Mobile Application for Patient Engagement to Support Interdisciplinary Care.

There is evidence on interrelationships between several dental and chronic diseases. However, dentists and general practitioners often lack information when treating such multimorbid patients. Engagement of the patient in the decision making process may help to fill this gap and improve intersectoral care. The Dent@Prevent project therefore aims to develop a mobile application that can be used by patients to report information about their health status for interdisciplinary care. In this paper, the user interface concept and evaluation of the prototype of this mobile application is presented.

Using FAIR Metadata for Secondary Use of Administrative Claims Data.

The FAIR principles require the reporting of rich metadata. However, when researchers use data for secondary use from external data owners, the FAIR principles require a different implementation as if the researchers would describe their own data. In this paper, we specify how FAIR metadata can be implemented for secondary data analyses and provide a suggestion for relevant metadata.

Development of a Research-Based Teaching Course as Blended-Learning Format in a Medical Informatics Program.

We consider Medical Informatics programs at universities as one of the main education resources for young scientists in our field and thus present a new design for a course teaching scientific skill at the University of Heidelberg as blended-learning format. We utilize common E-learning methods and created the whole course with respect to the concept of research-based teaching. Finally, we present our lessons learned from the current activities of the course.

A Framework for Enhancing and Updating Study Programs in Public Health and Medical Informatics Fields in Montenegro.

Montenegro plans to enhance and modernize the curricula and programs in public health fields in line with EU standards and hence the Erasmus-Phelim project developed a framework to develop, implement, and evaluate the education process. A stepwise approach consisting of three dimensions per step was implemented for workshop development. For the evaluation, a train-the-trainer approach was developed and a self-regulation concept consisting of three phases was applied. Semi-structured interviews with the workshop participants were conducted and results suggested that self-regulation is an understandable concept and can be applied as a training and knowledge transfer method.

Development of an HL7 FHIR Architecture for Implementation of a Knowledge-based Interdisciplinary EHR.

The treatment of multimorbid patients confronts physicians with special challenges. Complex disease correlations, insufficient evidence, lack of interdisciplinary guidelines, limited communication between physicians of different specialties, etc. complicate the treatment. To improve the present care situation for multimorbid patients we describe a development approach for an interdisciplinary Electronic Health Record (EHR). As part of the Dent@Prevent project, which aims to improve the intersectoral care of patients with correlating dental and chronic systemic diseases, the proposed EHR will first be tested in the field of dentistry and general medicine. Based on the HL7 FHIR standard the proposed EHR uses a modern three-tier (client-server) architecture. Crucial element of the EHR is a knowledge base, which comprises components for mapping diseases with their complex correlations, integrates patient reported parameters and classifies information in evidence levels. Using the FHIR standard the described elements need to be transferred into the data schema of FHIR resources. The development of an EHR to improve the treatment of multimorbid patients needs to be tailored to the specific needs of multimorbid patients. An interdisciplinary EHR offers the potential to facilitate communication between patients and physicians and provide them with evidence-based information on disease correlations. The next step is to test the practical implementation and applicability for further interdisciplinary disease correlations.