@article{SommerAmrBavendieketal.2022,
  author    = {Sommer, Kim K. and Amr, Ali and Bavendiek, Udo and Beierle, Felix and Brunecker, Peter and Dathe, Henning and Eils, J{\"u}rgen and Ertl, Maximilian and Fette, Georg and Gietzelt, Matthias and Heidecker, Bettina and Hellenkamp, Kristian and Heuschmann, Peter and Hoos, Jennifer D. E. and Keszty{\"u}s, Tibor and Kerwagen, Fabian and Kindermann, Aljoscha and Krefting, Dagmar and Landmesser, Ulf and Marschollek, Michael and Meder, Benjamin and Merzweiler, Angela and Prasser, Fabian and Pryss, R{\"u}diger and Richter, Jendrik and Schneider, Philipp and St{\"o}rk, Stefan and Dieterich, Christoph},
  title     = {Structured, harmonized, and interoperable integration of clinical routine data to compute heart failure risk scores},
  series = {Life},
  volume    = {12},
  journal   = {Life},
  number    = {5},
  issn      = {2075-1729},
  doi       = {10.3390/life12050749},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-275239},
  year      = {2022},
  abstract  = {Risk prediction in patients with heart failure (HF) is essential to improve the tailoring of preventive, diagnostic, and therapeutic strategies for the individual patient, and effectively use health care resources. Risk scores derived from controlled clinical studies can be used to calculate the risk of mortality and HF hospitalizations. However, these scores are poorly implemented into routine care, predominantly because their calculation requires considerable efforts in practice and necessary data often are not available in an interoperable format. In this work, we demonstrate the feasibility of a multi-site solution to derive and calculate two exemplary HF scores from clinical routine data (MAGGIC score with six continuous and eight categorical variables; Barcelona Bio-HF score with five continuous and six categorical variables). Within HiGHmed, a German Medical Informatics Initiative consortium, we implemented an interoperable solution, collecting a harmonized HF-phenotypic core data set (CDS) within the openEHR framework. Our approach minimizes the need for manual data entry by automatically retrieving data from primary systems. We show, across five participating medical centers, that the implemented structures to execute dedicated data queries, followed by harmonized data processing and score calculation, work well in practice. In summary, we demonstrated the feasibility of clinical routine data usage across multiple partner sites to compute HF risk scores. This solution can be extended to a large spectrum of applications in clinical care.},
  language  = {en}
}
@article{KerwagenFuchsUllrichetal.2023,
  author    = {Kerwagen, Fabian and Fuchs, Konrad F. and Ullrich, Melanie and Schulze, Andres and Straka, Samantha and Krop, Philipp and Latoschik, Marc E. and Gilbert, Fabian and Kunz, Andreas and Fette, Georg and St{\"o}rk, Stefan and Ertl, Maximilian},
  title     = {Usability of a mHealth solution using speech recognition for point-of-care diagnostic management},
  series = {Journal of Medical Systems},
  volume    = {47},
  journal   = {Journal of Medical Systems},
  number    = {1},
  doi       = {10.1007/s10916-022-01896-y},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-324002},
  year      = {2023},
  abstract  = {The administrative burden for physicians in the hospital can affect the quality of patient care. The Service Center Medical Informatics (SMI) of the University Hospital W{\"u}rzburg developed and implemented the smartphone-based mobile application (MA) ukw.mobile1 that uses speech recognition for the point-of-care ordering of radiological examinations. The aim of this study was to examine the usability of the MA workflow for the point-of-care ordering of radiological examinations. All physicians at the Department of Trauma and Plastic Surgery at the University Hospital W{\"u}rzburg, Germany, were asked to participate in a survey including the short version of the User Experience Questionnaire (UEQ-S) and the Unified Theory of Acceptance and Use of Technology (UTAUT). For the analysis of the different domains of user experience (overall attractiveness, pragmatic quality and hedonic quality), we used a two-sided dependent sample t-test. For the determinants of the acceptance model, we employed regression analysis. Twenty-one of 30 physicians (mean age 34 ± 8 years, 62\% male) completed the questionnaire. Compared to the conventional desktop application (DA) workflow, the new MA workflow showed superior overall attractiveness (mean difference 2.15 ± 1.33), pragmatic quality (mean difference 1.90 ± 1.16), and hedonic quality (mean difference 2.41 ± 1.62; all p < .001). The user acceptance measured by the UTAUT (mean 4.49 ± 0.41; min. 1, max. 5) was also high. Performance expectancy (beta = 0.57, p = .02) and effort expectancy (beta = 0.36, p = .04) were identified as predictors of acceptance, the full predictive model explained 65.4\% of its variance. Point-of-care mHealth solutions using innovative technology such as speech-recognition seem to address the users' needs and to offer higher usability in comparison to conventional technology. Implementation of user-centered mHealth innovations might therefore help to facilitate physicians' daily work.},
  language  = {en}
}
@article{KerwagenRiemerWachteretal.2023,
  author    = {Kerwagen, Fabian and Riemer, Uwe and Wachter, Rolf and von Haehling, Stephan and Abdin, Amr and B{\"o}hm, Michael and Schulz, Martin and St{\"o}rk, Stefan},
  title     = {Impact of the COVID-19 pandemic on implementation of novel guideline-directed medical therapies for heart failure in Germany: a nationwide retrospective analysis},
  series = {The Lancet Regional Health - Europe},
  volume    = {35},
  journal   = {The Lancet Regional Health - Europe},
  issn      = {2666-7762},
  doi       = {10.1016/j.lanepe.2023.100778},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-350510},
  year      = {2023},
  abstract  = {Background Guideline-directed medical therapy (GDMT) is the cornerstone in the treatment of patients with heart failure and reduced ejection fraction (HFrEF) and novel substances such as sacubitril/valsartan (S/V) and sodium-glucose co-transporter-2 inhibitors (SGLT2i) have demonstrated marked clinical benefits. We investigated their implementation into real-world HF care in Germany before, during, and after the COVID-19 pandemic period. Methods The IQVIA LRx data set is based on ∼80\% of 73 million people covered by the German statutory health insurance. Prescriptions of S/V were used as a proxy for HFrEF. Time trends were analysed between Q1/2016 and Q2/2023 for prescriptions for S/V alone and in combination therapy with SGLT2i. Findings The number of patients treated with S/V increased from 5260 in Q1/2016 to 351,262 in Q2/2023. The share of patients with combination therapy grew from 0.6\% (29 of 5260) to 14.2\% (31,128 of 219,762) in Q2/2021, and then showed a steep surge up to 54.8\% (192,429 of 351,262) in Q2/2023, coinciding with the release of the European Society of Cardiology (ESC) guidelines for HF in Q3/2021. Women and patients aged >80 years were treated less often with combined therapy than men and younger patients. With the start of the COVID-19 pandemic, the number of patients with new S/V prescriptions dropped by 17.5\% within one quarter, i.e., from 26,855 in Q1/2020 to 22,145 in Q2/2020, and returned to pre-pandemic levels only in Q1/2021. Interpretation The COVID-19 pandemic was associated with a 12-month deceleration of S/V uptake in Germany. Following the release of the ESC HF guidelines, the combined prescription of S/V and SGLT2i was readily adopted. Further efforts are needed to fully implement GDMT and strengthen the resilience of healthcare systems during public health crises.},
  language  = {en}
}