@book{MeinelDoellnerWeskeetal.2021,
  author    = {Meinel, Christoph and D{\"o}llner, J{\"u}rgen Roland Friedrich and Weske, Mathias and Polze, Andreas and Hirschfeld, Robert and Naumann, Felix and Giese, Holger and Baudisch, Patrick and Friedrich, Tobias and B{\"o}ttinger, Erwin and Lippert, Christoph and D{\"o}rr, Christian and Lehmann, Anja and Renard, Bernhard and Rabl, Tilmann and Uebernickel, Falk and Arnrich, Bert and H{\"o}lzle, Katharina},
  title     = {Proceedings of the HPI Research School on Service-oriented Systems Engineering 2020 Fall Retreat},
  number    = {138},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-513-2},
  issn      = {1613-5652},
  doi       = {10.25932/publishup-50413},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-504132},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {vi, 144},
  year      = {2021},
  abstract  = {Design and Implementation of service-oriented architectures imposes a huge number of research questions from the fields of software engineering, system analysis and modeling, adaptability, and application integration. Component orientation and web services are two approaches for design and realization of complex web-based system. Both approaches allow for dynamic application adaptation as well as integration of enterprise application. Service-Oriented Systems Engineering represents a symbiosis of best practices in object-orientation, component-based development, distributed computing, and business process management. It provides integration of business and IT concerns. The annual Ph.D. Retreat of the Research School provides each member the opportunity to present his/her current state of their research and to give an outline of a prospective Ph.D. thesis. Due to the interdisciplinary structure of the research school, this technical report covers a wide range of topics. These include but are not limited to: Human Computer Interaction and Computer Vision as Service; Service-oriented Geovisualization Systems; Algorithm Engineering for Service-oriented Systems; Modeling and Verification of Self-adaptive Service-oriented Systems; Tools and Methods for Software Engineering in Service-oriented Systems; Security Engineering of Service-based IT Systems; Service-oriented Information Systems; Evolutionary Transition of Enterprise Applications to Service Orientation; Operating System Abstractions for Service-oriented Computing; and Services Specification, Composition, and Enactment.},
  language  = {en}
}
@misc{LewkowiczWohlbrandtBoettinger2020,
  author    = {Lewkowicz, Daniel and Wohlbrandt, Attila and B{\"o}ttinger, Erwin},
  title     = {Economic impact of clinical decision support interventions based on electronic health records},
  series = {Postprints der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t},
  journal   = {Postprints der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t},
  number    = {5},
  doi       = {10.25932/publishup-50137},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-501376},
  pages     = {14},
  year      = {2020},
  abstract  = {Background Unnecessary healthcare utilization, non-adherence to current clinical guidelines, or insufficient personalized care are perpetual challenges and remain potential major cost-drivers for healthcare systems around the world. Implementing decision support systems into clinical care is promised to improve quality of care and thereby yield substantial effects on reducing healthcare expenditure. In this article, we evaluate the economic impact of clinical decision support (CDS) interventions based on electronic health records (EHR). Methods We searched for studies published after 2014 using MEDLINE, CENTRAL, WEB OF SCIENCE, EBSCO, and TUFTS CEA registry databases that encompass an economic evaluation or consider cost outcome measures of EHR based CDS interventions. Thereupon, we identified best practice application areas and categorized the investigated interventions according to an existing taxonomy of front-end CDS tools. Results and discussion Twenty-seven studies are investigated in this review. Of those, twenty-two studies indicate a reduction of healthcare expenditure after implementing an EHR based CDS system, especially towards prevalent application areas, such as unnecessary laboratory testing, duplicate order entry, efficient transfusion practice, or reduction of antibiotic prescriptions. On the contrary, order facilitators and undiscovered malfunctions revealed to be threats and could lead to new cost drivers in healthcare. While high upfront and maintenance costs of CDS systems are a worldwide implementation barrier, most studies do not consider implementation cost. Finally, four included economic evaluation studies report mixed monetary outcome results and thus highlight the importance of further high-quality economic evaluations for these CDS systems. Conclusion Current research studies lack consideration of comparative cost-outcome metrics as well as detailed cost components in their analyses. Nonetheless, the positive economic impact of EHR based CDS interventions is highly promising, especially with regard to reducing waste in healthcare.},
  language  = {en}
}
@article{DeFreitasJohnsonGoldenetal.2021,
  author    = {De Freitas, Jessica K. and Johnson, Kipp W. and Golden, Eddye and Nadkarni, Girish N. and Dudley, Joel T. and B{\"o}ttinger, Erwin and Glicksberg, Benjamin S. and Miotto, Riccardo},
  title     = {Phe2vec},
  series = {Patterns},
  volume    = {2},
  journal   = {Patterns},
  number    = {9},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {2666-3899},
  doi       = {10.1016/j.patter.2021.100337},
  pages     = {9},
  year      = {2021},
  abstract  = {Robust phenotyping of patients from electronic health records (EHRs) at scale is a challenge in clinical informatics. Here, we introduce Phe2vec, an automated framework for disease phenotyping from EHRs based on unsupervised learning and assess its effectiveness against standard rule-based algorithms from Phenotype KnowledgeBase (PheKB). Phe2vec is based on pre-computing embeddings of medical concepts and patients' clinical history. Disease phenotypes are then derived from a seed concept and its neighbors in the embedding space. Patients are linked to a disease if their embedded representation is close to the disease phenotype. Comparing Phe2vec and PheKB cohorts head-to-head using chart review, Phe2vec performed on par or better in nine out of ten diseases. Differently from other approaches, it can scale to any condition and was validated against widely adopted expert-based standards. Phe2vec aims to optimize clinical informatics research by augmenting current frameworks to characterize patients by condition and derive reliable disease cohorts.},
  language  = {en}
}
@article{LewkowiczWohlbrandtBoettinger2020,
  author    = {Lewkowicz, Daniel and Wohlbrandt, Attila and B{\"o}ttinger, Erwin},
  title     = {Economic impact of clinical decision support interventions based on electronic health records},
  series = {BMC Health Services Research},
  volume    = {20},
  journal   = {BMC Health Services Research},
  publisher = {BioMed Central},
  address   = {London},
  issn      = {1472-6963},
  doi       = {10.1186/s12913-020-05688-3},
  pages     = {12},
  year      = {2020},
  abstract  = {Background Unnecessary healthcare utilization, non-adherence to current clinical guidelines, or insufficient personalized care are perpetual challenges and remain potential major cost-drivers for healthcare systems around the world. Implementing decision support systems into clinical care is promised to improve quality of care and thereby yield substantial effects on reducing healthcare expenditure. In this article, we evaluate the economic impact of clinical decision support (CDS) interventions based on electronic health records (EHR). Methods We searched for studies published after 2014 using MEDLINE, CENTRAL, WEB OF SCIENCE, EBSCO, and TUFTS CEA registry databases that encompass an economic evaluation or consider cost outcome measures of EHR based CDS interventions. Thereupon, we identified best practice application areas and categorized the investigated interventions according to an existing taxonomy of front-end CDS tools. Results and discussion Twenty-seven studies are investigated in this review. Of those, twenty-two studies indicate a reduction of healthcare expenditure after implementing an EHR based CDS system, especially towards prevalent application areas, such as unnecessary laboratory testing, duplicate order entry, efficient transfusion practice, or reduction of antibiotic prescriptions. On the contrary, order facilitators and undiscovered malfunctions revealed to be threats and could lead to new cost drivers in healthcare. While high upfront and maintenance costs of CDS systems are a worldwide implementation barrier, most studies do not consider implementation cost. Finally, four included economic evaluation studies report mixed monetary outcome results and thus highlight the importance of further high-quality economic evaluations for these CDS systems. Conclusion Current research studies lack consideration of comparative cost-outcome metrics as well as detailed cost components in their analyses. Nonetheless, the positive economic impact of EHR based CDS interventions is highly promising, especially with regard to reducing waste in healthcare.},
  language  = {en}
}
@misc{GorskiJungLietal.2020,
  author    = {Gorski, Mathias and Jung, Bettina and Li, Yong and Matias-Garcia, Pamela R. and Wuttke, Matthias and Coassin, Stefan and Thio, Chris H. L. and Kleber, Marcus E. and Winkler, Thomas W. and Wanner, Veronika and Chai, Jin-Fang and Chu, Audrey Y. and Cocca, Massimiliano and Feitosa, Mary F. and Ghasemi, Sahar and Hoppmann, Anselm and Horn, Katrin and Li, Man and Nutile, Teresa and Scholz, Markus and Sieber, Karsten B. and Teumer, Alexander and Tin, Adrienne and Wang, Judy and Tayo, Bamidele O. and Ahluwalia, Tarunveer S. and Almgren, Peter and Bakker, Stephan J. L. and Banas, Bernhard and Bansal, Nisha and Biggs, Mary L. and Boerwinkle, Eric and B{\"o}ttinger, Erwin and Brenner, Hermann and Carroll, Robert J. and Chalmers, John and Chee, Miao-Li and Chee, Miao-Ling and Cheng, Ching-Yu and Coresh, Josef and de Borst, Martin H. and Degenhardt, Frauke and Eckardt, Kai-Uwe and Endlich, Karlhans and Franke, Andre and Freitag-Wolf, Sandra and Gampawar, Piyush and Gansevoort, Ron T. and Ghanbari, Mohsen and Gieger, Christian and Hamet, Pavel and Ho, Kevin and Hofer, Edith and Holleczek, Bernd and Foo, Valencia Hui Xian and Hutri-Kahonen, Nina and Hwang, Shih-Jen and Ikram, M. Arfan and Josyula, Navya Shilpa and Kahonen, Mika and Khor, Chiea-Chuen and Koenig, Wolfgang and Kramer, Holly and Kraemer, Bernhard K. and Kuehnel, Brigitte and Lange, Leslie A. and Lehtimaki, Terho and Lieb, Wolfgang and Loos, Ruth J. F. and Lukas, Mary Ann and Lyytikainen, Leo-Pekka and Meisinger, Christa and Meitinger, Thomas and Melander, Olle and Milaneschi, Yuri and Mishra, Pashupati P. and Mononen, Nina and Mychaleckyj, Josyf C. and Nadkarni, Girish N. and Nauck, Matthias and Nikus, Kjell and Ning, Boting and Nolte, Ilja M. and O'Donoghue, Michelle L. and Orho-Melander, Marju and Pendergrass, Sarah A. and Penninx, Brenda W. J. H. and Preuss, Michael H. and Psaty, Bruce M. and Raffield, Laura M. and Raitakari, Olli T. and Rettig, Rainer and Rheinberger, Myriam and Rice, Kenneth M. and Rosenkranz, Alexander R. and Rossing, Peter and Rotter, Jerome and Sabanayagam, Charumathi and Schmidt, Helena and Schmidt, Reinhold and Schoettker, Ben and Schulz, Christina-Alexandra and Sedaghat, Sanaz and Shaffer, Christian M. and Strauch, Konstantin and Szymczak, Silke and Taylor, Kent D. and Tremblay, Johanne and Chaker, Layal and van der Harst, Pim and van der Most, Peter J. and Verweij, Niek and Voelker, Uwe and Waldenberger, Melanie and Wallentin, Lars and Waterworth, Dawn M. and White, Harvey D. and Wilson, James G. and Wong, Tien-Yin and Woodward, Mark and Yang, Qiong and Yasuda, Masayuki and Yerges-Armstrong, Laura M. and Zhang, Yan and Snieder, Harold and Wanner, Christoph and Boger, Carsten A. and Kottgen, Anna and Kronenberg, Florian and Pattaro, Cristian and Heid, Iris M.},
  title     = {Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t},
  number    = {19},
  doi       = {10.25932/publishup-56537},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-565379},
  pages     = {14},
  year      = {2020},
  abstract  = {Rapid decline of glomerular filtration rate estimated from creatinine (eGFRcrea) is associated with severe clinical endpoints. In contrast to cross-sectionally assessed eGFRcrea, the genetic basis for rapid eGFRcrea decline is largely unknown. To help define this, we meta-analyzed 42 genome-wide association studies from the Chronic Kidney Diseases Genetics Consortium and United Kingdom Biobank to identify genetic loci for rapid eGFRcrea decline. Two definitions of eGFRcrea decline were used: 3 mL/min/1.73m(2)/year or more ("Rapid3"; encompassing 34,874 cases, 107,090 controls) and eGFRcrea decline 25\% or more and eGFRcrea under 60 mL/min/1.73m(2) at follow-up among those with eGFRcrea 60 mL/min/1.73m(2) or more at baseline ("CKDi25"; encompassing 19,901 cases, 175,244 controls). Seven independent variants were identified across six loci for Rapid3 and/or CKDi25: consisting of five variants at four loci with genome-wide significance (near UMOD-PDILT (2), PRKAG2, WDR72, OR2S2) and two variants among 265 known eGFRcrea variants (near GATM, LARP4B). All these loci were novel for Rapid3 and/or CKDi25 and our bioinformatic follow-up prioritized variants and genes underneath these loci. The OR2S2 locus is novel for any eGFRcrea trait including interesting candidates. For the five genome-wide significant lead variants, we found supporting effects for annual change in blood urea nitrogen or cystatin-based eGFR, but not for GATM or (LARP4B). Individuals at high compared to those at low genetic risk (8-14 vs. 0-5 adverse alleles) had a 1.20-fold increased risk of acute kidney injury (95\% confidence interval 1.08-1.33). Thus, our identified loci for rapid kidney function decline may help prioritize therapeutic targets and identify mechanisms and individuals at risk for sustained deterioration of kidney function.},
  language  = {en}
}
@misc{KonigorskiWernickeSlosareketal.2023,
  author    = {Konigorski, Stefan and Wernicke, Sarah and Slosarek, Tamara and Zenner, Alexander Maximilian and Strelow, Nils and Ruether, Darius Ferenc and Henschel, Florian and Manaswini, Manisha and Pottb{\"a}cker, Fabian and Edelman, Jonathan Antonio and Owoyele, Babajide and Danieletto, Matteo and Golden, Eddye and Zweig, Micol and Nadkarni, Girish N. and B{\"o}ttinger, Erwin},
  title     = {StudyU: A Platform for Designing and Conducting Innovative Digital N-of-1 Trials},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t},
  number    = {12},
  doi       = {10.25932/publishup-58037},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-580370},
  pages     = {12},
  year      = {2023},
  abstract  = {N-of-1 trials are the gold standard study design to evaluate individual treatment effects and derive personalized treatment strategies. Digital tools have the potential to initiate a new era of N-of-1 trials in terms of scale and scope, but fully functional platforms are not yet available. Here, we present the open source StudyU platform, which includes the StudyU Designer and StudyU app. With the StudyU Designer, scientists are given a collaborative web application to digitally specify, publish, and conduct N-of-1 trials. The StudyU app is a smartphone app with innovative user-centric elements for participants to partake in trials published through the StudyU Designer to assess the effects of different interventions on their health. Thereby, the StudyU platform allows clinicians and researchers worldwide to easily design and conduct digital N-of-1 trials in a safe manner. We envision that StudyU can change the landscape of personalized treatments both for patients and healthy individuals, democratize and personalize evidence generation for self-optimization and medicine, and can be integrated in clinical practice.},
  language  = {en}
}
@misc{DellepianeVaidJaladankietal.2021,
  author    = {Dellepiane, Sergio and Vaid, Akhil and Jaladanki, Suraj K. and Coca, Steven and Fayad, Zahi A. and Charney, Alexander W. and B{\"o}ttinger, Erwin and He, John Cijiang and Glicksberg, Benjamin S. and Chan, Lili and Nadkarni, Girish},
  title     = {Acute kidney injury in patients hospitalized with COVID-19 in New York City},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Reihe der Digital Engineering Fakult{\"a}t},
  number    = {5},
  issn      = {2590-0595},
  doi       = {10.25932/publishup-58541},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-585415},
  pages     = {5},
  year      = {2021},
  language  = {en}
}
@article{DellepianeVaidJaladankietal.2021,
  author    = {Dellepiane, Sergio and Vaid, Akhil and Jaladanki, Suraj K. and Coca, Steven and Fayad, Zahi A. and Charney, Alexander W. and B{\"o}ttinger, Erwin and He, John Cijiang and Glicksberg, Benjamin S. and Chan, Lili and Nadkarni, Girish},
  title     = {Acute kidney injury in patients hospitalized with COVID-19 in New York City},
  series = {Kidney medicine},
  volume    = {3},
  journal   = {Kidney medicine},
  number    = {5},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {2590-0595},
  doi       = {10.1016/j.xkme.2021.06.008},
  pages     = {877 -- 879},
  year      = {2021},
  language  = {en}
}
@misc{HorowitzFeiRamosetal.2018,
  author    = {Horowitz, Carol R. and Fei, Kezhen and Ramos, Michelle A. and Hauser, Diane and Ellis, Stephen B. and Calman, Neil and B{\"o}ttinger, Erwin},
  title     = {Receipt of genetic risk information significantly improves blood pressure control among African anecestry adults with hypertension},
  series = {Journal of General Internal Medicine},
  volume    = {33},
  journal   = {Journal of General Internal Medicine},
  publisher = {Springer},
  address   = {New York},
  issn      = {0884-8734},
  doi       = {10.1007/s11606-018-4413-y},
  pages     = {S322 -- S323},
  year      = {2018},
  language  = {en}
}
@article{Boettinger2019,
  author    = {B{\"o}ttinger, Erwin},
  title     = {Wendepunkt f{\"u}r Gesundheit},
  series = {Die Zukunft der Medizin : Disruptive Innovationen revolutionieren Medizin und Gesundheit},
  journal   = {Die Zukunft der Medizin : Disruptive Innovationen revolutionieren Medizin und Gesundheit},
  publisher = {Medizinisch Wissenschaftliche Verlagsgesellschaft},
  address   = {Berlin},
  isbn      = {978-3-95466-398-9},
  pages     = {201 -- 210},
  year      = {2019},
  language  = {de}
}