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- PublikationRWD-Cockpit. Application for quality assessment of real-world data(JMIR Publications, 18.10.2022) Degen, Markus; Babrak, Lmar; Smakaj, Erand; Agac, Teyfik; Asprion, Petra; Grimberg, Frank; Van der Werf, Daan; Van Ginkel, Erwin Willem; Tosoni, Deniz David; Clay, Ieuan; Brodbeck, Dominique; Natali, Eriberto; Schkommodau, Erik; Miho, Enkelejda [in: JMIR Formative Research]Digital technologies are transforming the health care system. A large part of information is generated as real-world data (RWD). Data from electronic health records and digital biomarkers have the potential to reveal associations between the benefits and adverse events of medicines, establish new patient-stratification principles, expose unknown disease correlations, and inform on preventive measures. The impact for health care payers and providers, the biopharmaceutical industry, and governments is massive in terms of health outcomes, quality of care, and cost. However, a framework to assess the preliminary quality of RWD is missing, thus hindering the conduct of population-based observational studies to support regulatory decision-making and real-world evidence.01A - Beitrag in wissenschaftlicher Zeitschrift
- PublikationNaming images in aphasia: effects of illustrative and photographic images on naming performance in people with and without aphasia(Taylor & Francis, 03.05.2022) Reymond, Claire; Widmer Beierlein, Sandra; Müller, Christine; Kuntner, Katrin Petra; Falcón García, Noelia; Grumbinaite, Indre; Hemm-Ode, Simone; Degen, Markus; Parrillo, Fabrizio; Karlin, Stefan; Park, Sung Hea; Blechschmidt, Anja; Reutimann, Ricarda [in: Aphasiology]Background: Picture naming is a common tool in aphasia diagnosis and therapy. However, opin-ions differ as to which type of image (e.g., photographs, drawings) is most suitable for naming tasks and whether there is a difference on naming correctness and latencies based on image type. Moreover, recent studies have mainly analysed colour photographs and black-and-white line drawings leaving out image types like graphic representations that apply image features that can facilitate naming such as colour, controlled size, or texture. Aims: To shed more light on ap-propriate image types for persons with aphasia, we created graphic representations depicting nouns and verbs and compared them to photographic stimuli in a naming task including persons with aphasia (PWA) and a control group (CG). Methods & Procedures: 33 PWA and 33 age matched persons (CG) participated in the study. Naming correctness and latencies were meas-ured in two different conditions: concepts depicted as coloured photographs vs. as graphic rep-resentations. 128 pictures of linguistically controlled German-language concepts (64 nouns, 64 verbs) had to be named. The designed graphic stimuli were developed by professional designers based on photographs. The photographs were selected from stock image databases according to a defined image concept. This image concept was based on empirical findings regarding im-age features that facilitate naming (e.g., colour, texture, shading) and was applied to the selec-tion of the photographs as well as to the creation of the graphic representations. The images were presented in pseudo-randomized sequences on a tablet and all reactions of the participants were videotaped. The data from the main study was analysed using generalized linear mixed models (GLMM) and linear mixed models (LMM).01A - Beitrag in wissenschaftlicher Zeitschrift
- PublikationRWD-Cockpit: application for quality assessment of real-world data(JMIR Publications, 2022) Babrak, Lmar; Smakaj, Erand; Agac, Teyfik; Asprion, Petra; Grimberg, Frank; Van der Werf, Daan; van Ginkel, Erwin Willem; Tosoni, Deniz David; Clay, Ieuan; Degen, Markus; Brodbeck, Dominique; Natali, Eriberto Noel; Schkommodau, Erik; Miho, Enkelejda [in: JMIR Formative Research]Background: Digital technologies are transforming the health care system. A large part of information is generated as real-world data (RWD). Data from electronic health records and digital biomarkers have the potential to reveal associations between the benefits and adverse events of medicines, establish new patient-stratification principles, expose unknown disease correlations, and inform on preventive measures. The impact for health care payers and providers, the biopharmaceutical industry, and governments is massive in terms of health outcomes, quality of care, and cost. However, a framework to assess the preliminary quality of RWD is missing, thus hindering the conduct of population-based observational studies to support regulatory decision-making and real-world evidence. Objective: To address the need to qualify RWD, we aimed to build a web application as a tool to translate characterization of some quality parameters of RWD into a metric and propose a standard framework for evaluating the quality of the RWD. Methods: The RWD-Cockpit systematically scores data sets based on proposed quality metrics and customizable variables chosen by the user. Sleep RWD generated de novo and publicly available data sets were used to validate the usability and applicability of the web application. The RWD quality score is based on the evaluation of 7 variables: manageability specifies access and publication status; complexity defines univariate, multivariate, and longitudinal data; sample size indicates the size of the sample or samples; privacy and liability stipulates privacy rules; accessibility specifies how the data set can be accessed and to what granularity; periodicity specifies how often the data set is updated; and standardization specifies whether the data set adheres to any specific technical or metadata standard. These variables are associated with several descriptors that define specific characteristics of the data set. Results: To address the need to qualify RWD, we built the RWD-Cockpit web application, which proposes a framework and applies a common standard for a preliminary evaluation of RWD quality across data sets—molecular, phenotypical, and social—and proposes a standard that can be further personalized by the community retaining an internal standard. Applied to 2 different case studies—de novo–generated sleep data and publicly available data sets—the RWD-Cockpit could identify and provide researchers with variables that might increase quality Conclusions: The results from the application of the framework of RWD metrics implemented in the RWD-Cockpit application suggests that multiple data sets can be preliminarily evaluated in terms of quality using the proposed metrics. The output scores—quality identifiers—provide a first quality assessment for the use of RWD. Although extensive challenges remain to be addressed to set RWD quality standards, our proposal can serve as an initial blueprint for community efforts in the characterization of RWD quality for regulated settings.01A - Beitrag in wissenschaftlicher Zeitschrift