Alpha-1-antitrypsin-deficiency is associated with lower cardiovascular risk: an approach based on federated learning.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is an inflammatory multisystemic disease caused by environmental exposures and/or genetic factors. Inherited alpha-1-antitrypsin deficiency (AATD) is one of the best recognized genetic factors increasing the risk for an early onset COPD with emphysema. The aim of this study was to gain a better understanding of the associations between comorbidities and specific biomarkers in COPD patients with and without AATD to enable future investigations aimed, for example, at identifying risk factors or improving care. METHODS: We focused on cardiovascular comorbidities, blood high sensitivity troponin (hs-troponin) and lipid profiles in COPD patients with and without AATD. We used clinical data from six German University Medical Centres of the MIRACUM (Medical Informatics Initiative in Research and Medicine) consortium. The codes for the international classification of diseases (ICD) were used for COPD as a main diagnosis and for comorbidities and blood laboratory data were obtained. Data analyses were based on the DataSHIELD framework. RESULTS: Out of 112,852 visits complete information was available for 43,057 COPD patients. According to our findings, 746 patients with AATD (1.73%) showed significantly lower total blood cholesterol levels and less cardiovascular comorbidities than non-AATD COPD patients. Moreover, after adjusting for the confounder factors, such as age, gender, and nicotine abuse, we confirmed that hs-troponin is a suitable predictor of overall mortality in COPD patients. The comorbidities associated with AATD in the current study differ from other studies, which may reflect geographic and population-based differences as well as the heterogeneous characteristics of AATD. CONCLUSION: The concept of MIRACUM is suitable for the analysis of a large healthcare database. This study provided evidence that COPD patients with AATD have a lower cardiovascular risk and revealed that hs-troponin is a predictor for hospital mortality in individuals with COPD.

DQAgui: a graphical user interface for the MIRACUM data quality assessment tool.

BACKGROUND: With the growing impact of observational research studies, there is also a growing focus on data quality (DQ). As opposed to experimental study designs, observational research studies are performed using data mostly collected in a non-research context (secondary use). Depending on the number of data elements to be analyzed, DQ reports of data stored within research networks can grow very large. They might be cumbersome to read and important information could be overseen quickly. To address this issue, a DQ assessment (DQA) tool with a graphical user interface (GUI) was developed and provided as a web application. METHODS: The aim was to provide an easy-to-use interface for users without prior programming knowledge to carry out DQ checks and to present the results in a clearly structured way. This interface serves as a starting point for a more detailed investigation of possible DQ irregularities. A user-centered development process ensured the practical feasibility of the interactive GUI. The interface was implemented in the R programming language and aligned to Kahn et al.'s DQ categories conformance, completeness and plausibility. RESULTS: With DQAgui, an R package with a web-app frontend for DQ assessment was developed. The GUI allows users to perform DQ analyses of tabular data sets and to systematically evaluate the results. During the development of the GUI, additional features were implemented, such as analyzing a subset of the data by defining time periods and restricting the analyses to certain data elements. CONCLUSIONS: As part of the MIRACUM project, DQAgui is now being used at ten German university hospitals for DQ assessment and to provide a central overview of the availability of important data elements in a datamap over 2 years. Future development efforts should focus on design optimization and include a usability evaluation.

Data Model Requirements for a Digital Cognitive Aid for Anesthesia to Support Intraoperative Crisis Management.

OBJECTIVE: The aim of this study is to define data model requirements supporting the development of a digital cognitive aid (CA) for intraoperative crisis management in anesthesia, including medical emergency text modules (text elements) and branches or loops within emergency instructions (control structures) as well as their properties, data types, and value ranges. METHODS: The analysis process comprised three steps: reviewing the structure of paper-based CAs to identify common text elements and control structures, identifying requirements derived from content, design, and purpose of a digital CA, and validating requirements by loading exemplary emergency checklist data into the resulting prototype data model. RESULTS: The analysis of paper-based CAs identified 19 general text elements and two control structures. Aggregating these elements and analyzing the content, design and purpose of a digital CA revealed 20 relevant data model requirements. These included checklist tags to enable different search options, structured checklist action steps (items) in groups and subgroups, and additional information on each item. Checklist and Item were identified as two main classes of the prototype data model. A data object built according to this model was successfully integrated into a digital CA prototype. CONCLUSION: To enable consistent design and interactivity with the content, presentation of critical medical information in a digital CA for crisis management requires a uniform structure. So far it has not been investigated which requirements need to be met by a data model for this purpose. The results of this study define the requirements and structure that enable the presentation of critical medical information. Further research is needed to develop a comprehensive data model for a digital CA for crisis management in anesthesia, including supplementation of requirements resulting from simulation studies and feasibility analyses regarding existing data models. This model may also be a useful template for developing data models for CAs in other medical domains.

Evaluation of a Patient-Facing Digital Prototype for Perioperative Risk Assessment.

Preparations for anesthesiological management of patients build on preoperative patient self-reports concerning risk factors and comorbidities. In this setting, electronic documentation could facilitate innovative computerized functions, although patient-facing digital questionnaires require appropriate tools that patients can access effectively. To explore the feasibility of an electronic application for preoperative data acquisition directly from patients, a digital, tablet-based prototypical application has been developed within a user-centered design process in order to replace a previously used paper-based anamnesis sheet for perioperative risk evaluation. The implemented prototype has been extensively tested and iteratively improved to progressively provide an easy-to-use data entry function. To assess the suitability of this tool for everyday data acquisition by patients and physicians and to identify usability problems, the stepwise development process was accompanied by a heuristic evaluation as well as a think-aloud evaluation, while another 56 participating patients completed a feedback sheet according to ISO 9241/10. The latter method detected additional usability problems that occurred during the use of the application, which contributed to iterative improvements of the prototype. Throughout the development process, 81 issues were identified and largely resolved. After these revisions of the prototype, the number of problems found per tester decreased from 4.75 to 0.96, while the overall rating increased to 6.14 out of 7 points (SD = 1.2). These improvements demonstrate the value and efficiency of such a user-centered design process and illustrate that a user-friendly patient-facing digital data entry can replace preoperative paper questionnaires for anesthesiological management.

A Digital Cognitive Aid for Anesthesia to Support Intraoperative Crisis Management: Results of the User-Centered Design Process.

BACKGROUND: Stressful situations during intraoperative emergencies have negative impact on human cognitive functions. Consequently, task performance may decrease and patient safety may be compromised. Cognitive aids can counteract these effects and support anesthesiologists in their crisis management. The Professional Association of German Anesthesiologists set up a project to develop a comprehensive set of digital cognitive aids for intraoperative emergencies. A parallel development for several software platforms and stationary and mobile devices will accommodate the inhomogeneity of the information technology infrastructure within German anesthesia departments. OBJECTIVE: This paper aimed to provide a detailed overview of how the task of developing a digital cognitive aid for intraoperative crisis management in anesthesia was addressed that meets user requirements and is highly user-friendly. METHODS: A user-centered design (UCD) process was conducted to identify, specify, and supplement the requirements for a digital cognitive aid. The study covered 4 aspects: analysis of the context of use, specification of user requirements, development of design solutions, and evaluation of design solutions. Three prototypes were developed and evaluated by end users of the application. Following each evaluation, the new requirements were prioritized and used for redesign. For the first and third prototype, the System Usability Scale (SUS) score was determined. The second prototype was evaluated with an extensive Web-based questionnaire. The evaluation of the third prototype included a think-aloud protocol. RESULTS: The chosen methods enabled a comprehensive collection of requirements and helped to improve the design of the application. The first prototype achieved an average SUS score of 74 (SD 12), indicating good usability. The second prototype included the following main revisions: 2-column layout, initial selection of patient type (infant, adult, or parturient), 4 offered search options, and the option to check off completed action steps. Its evaluation identified the following major revision points: add quick selection for resuscitation checklists, design the top bar and tabs slightly larger, and add more pictograms to the text. The third prototype achieved an average SUS score of 77 (SD 15). The evaluation of the think-aloud protocol revealed a good intuitiveness of the application and identified a missing home button as the main issue. CONCLUSIONS: Anesthesiology-as an acute medical field-is particularly characterized by its high demands on decision making and action in dynamic, or time-critical situations. The integration of usability aspects is essential for everyday and emergency suitability. The UCD process allowed us to develop a prototypical digital cognitive aid, exhibiting high usability and user satisfaction in the demanding environment of anesthesiological emergencies. Both aspects are essential to increase the acceptance of the application in later stages. The study approach, combining different methods for determining user requirements, may be useful for other implementation projects in a highly demanding environment.