TY  - GEN
A1  - Lewkowicz, Daniel
A1  - Wohlbrandt, Attila
A1  - Böttinger, Erwin
T1  - Economic impact of clinical decision support interventions based on electronic health records
T2  - Postprints der Universität Potsdam : Reihe der Digital Engineering Fakultät
N2  - 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.
T3  - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 5 
KW  - Economic evaluation
KW  - Electronic health record
KW  - Clinical decision support
KW  - Behavioral economics
Y1  - 2021
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-501376
IS  - 5
ER  - 
TY  - JOUR
A1  - De Freitas, Jessica K.
A1  - Johnson, Kipp W.
A1  - Golden, Eddye
A1  - Nadkarni, Girish N.
A1  - Dudley, Joel T.
A1  - Böttinger, Erwin
A1  - Glicksberg, Benjamin S.
A1  - Miotto, Riccardo
T1  - Phe2vec
BT  - Automated disease phenotyping based on unsupervised embeddings from electronic health records
JF  - Patterns
N2  - 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.
Y1  - 2021
U6  - https://doi.org/10.1016/j.patter.2021.100337
SN  - 2666-3899
VL  - 2
IS  - 9
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Lewkowicz, Daniel
A1  - Wohlbrandt, Attila
A1  - Böttinger, Erwin
T1  - Economic impact of clinical decision support interventions based on electronic health records
JF  - BMC Health Services Research
N2  - 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.
KW  - Economic evaluation
KW  - Electronic health record
KW  - Clinical decision support
KW  - Behavioral economics
Y1  - 2020
U6  - https://doi.org/10.1186/s12913-020-05688-3
SN  - 1472-6963
VL  - 20
PB  - BioMed Central
CY  - London
ER  - 
TY  - GEN
A1  - Gorski, Mathias
A1  - Jung, Bettina
A1  - Li, Yong
A1  - Matias-Garcia, Pamela R.
A1  - Wuttke, Matthias
A1  - Coassin, Stefan
A1  - Thio, Chris H. L.
A1  - Kleber, Marcus E.
A1  - Winkler, Thomas W.
A1  - Wanner, Veronika
A1  - Chai, Jin-Fang
A1  - Chu, Audrey Y.
A1  - Cocca, Massimiliano
A1  - Feitosa, Mary F.
A1  - Ghasemi, Sahar
A1  - Hoppmann, Anselm
A1  - Horn, Katrin
A1  - Li, Man
A1  - Nutile, Teresa
A1  - Scholz, Markus
A1  - Sieber, Karsten B.
A1  - Teumer, Alexander
A1  - Tin, Adrienne
A1  - Wang, Judy
A1  - Tayo, Bamidele O.
A1  - Ahluwalia, Tarunveer S.
A1  - Almgren, Peter
A1  - Bakker, Stephan J. L.
A1  - Banas, Bernhard
A1  - Bansal, Nisha
A1  - Biggs, Mary L.
A1  - Boerwinkle, Eric
A1  - Böttinger, Erwin
A1  - Brenner, Hermann
A1  - Carroll, Robert J.
A1  - Chalmers, John
A1  - Chee, Miao-Li
A1  - Chee, Miao-Ling
A1  - Cheng, Ching-Yu
A1  - Coresh, Josef
A1  - de Borst, Martin H.
A1  - Degenhardt, Frauke
A1  - Eckardt, Kai-Uwe
A1  - Endlich, Karlhans
A1  - Franke, Andre
A1  - Freitag-Wolf, Sandra
A1  - Gampawar, Piyush
A1  - Gansevoort, Ron T.
A1  - Ghanbari, Mohsen
A1  - Gieger, Christian
A1  - Hamet, Pavel
A1  - Ho, Kevin
A1  - Hofer, Edith
A1  - Holleczek, Bernd
A1  - Foo, Valencia Hui Xian
A1  - Hutri-Kahonen, Nina
A1  - Hwang, Shih-Jen
A1  - Ikram, M. Arfan
A1  - Josyula, Navya Shilpa
A1  - Kahonen, Mika
A1  - Khor, Chiea-Chuen
A1  - Koenig, Wolfgang
A1  - Kramer, Holly
A1  - Kraemer, Bernhard K.
A1  - Kuehnel, Brigitte
A1  - Lange, Leslie A.
A1  - Lehtimaki, Terho
A1  - Lieb, Wolfgang
A1  - Loos, Ruth J. F.
A1  - Lukas, Mary Ann
A1  - Lyytikainen, Leo-Pekka
A1  - Meisinger, Christa
A1  - Meitinger, Thomas
A1  - Melander, Olle
A1  - Milaneschi, Yuri
A1  - Mishra, Pashupati P.
A1  - Mononen, Nina
A1  - Mychaleckyj, Josyf C.
A1  - Nadkarni, Girish N.
A1  - Nauck, Matthias
A1  - Nikus, Kjell
A1  - Ning, Boting
A1  - Nolte, Ilja M.
A1  - O'Donoghue, Michelle L.
A1  - Orho-Melander, Marju
A1  - Pendergrass, Sarah A.
A1  - Penninx, Brenda W. J. H.
A1  - Preuss, Michael H.
A1  - Psaty, Bruce M.
A1  - Raffield, Laura M.
A1  - Raitakari, Olli T.
A1  - Rettig, Rainer
A1  - Rheinberger, Myriam
A1  - Rice, Kenneth M.
A1  - Rosenkranz, Alexander R.
A1  - Rossing, Peter
A1  - Rotter, Jerome
A1  - Sabanayagam, Charumathi
A1  - Schmidt, Helena
A1  - Schmidt, Reinhold
A1  - Schoettker, Ben
A1  - Schulz, Christina-Alexandra
A1  - Sedaghat, Sanaz
A1  - Shaffer, Christian M.
A1  - Strauch, Konstantin
A1  - Szymczak, Silke
A1  - Taylor, Kent D.
A1  - Tremblay, Johanne
A1  - Chaker, Layal
A1  - van der Harst, Pim
A1  - van der Most, Peter J.
A1  - Verweij, Niek
A1  - Voelker, Uwe
A1  - Waldenberger, Melanie
A1  - Wallentin, Lars
A1  - Waterworth, Dawn M.
A1  - White, Harvey D.
A1  - Wilson, James G.
A1  - Wong, Tien-Yin
A1  - Woodward, Mark
A1  - Yang, Qiong
A1  - Yasuda, Masayuki
A1  - Yerges-Armstrong, Laura M.
A1  - Zhang, Yan
A1  - Snieder, Harold
A1  - Wanner, Christoph
A1  - Boger, Carsten A.
A1  - Kottgen, Anna
A1  - Kronenberg, Florian
A1  - Pattaro, Cristian
A1  - Heid, Iris M.
T1  - Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline
T2  - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät
N2  - 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.
T3  - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 19 
KW  - acute kidney injury
KW  - end-stage kidney disease
KW  - genome-wide association
KW  - study
KW  - rapid eGFRcrea decline
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-565379
IS  - 19
ER  - 
TY  - GEN
A1  - Konigorski, Stefan
A1  - Wernicke, Sarah
A1  - Slosarek, Tamara
A1  - Zenner, Alexander Maximilian
A1  - Strelow, Nils
A1  - Ruether, Darius Ferenc
A1  - Henschel, Florian
A1  - Manaswini, Manisha
A1  - Pottbäcker, Fabian
A1  - Edelman, Jonathan Antonio
A1  - Owoyele, Babajide
A1  - Danieletto, Matteo
A1  - Golden, Eddye
A1  - Zweig, Micol
A1  - Nadkarni, Girish N.
A1  - Böttinger, Erwin
T1  - StudyU: A Platform for Designing and Conducting Innovative Digital N-of-1 Trials
T2  - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät
N2  - 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.
T3  - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 12 
KW  - digital interventions
KW  - N-of-1 trial
KW  - SCED
KW  - single-case experimental design
KW  - web application
KW  - mobile application
KW  - app
KW  - digital health
Y1  - 2023
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-580370
IS  - 12
ER  - 
TY  - GEN
A1  - Horowitz, Carol R.
A1  - Fei, Kezhen
A1  - Ramos, Michelle A.
A1  - Hauser, Diane
A1  - Ellis, Stephen B.
A1  - Calman, Neil
A1  - Böttinger, Erwin
T1  - Receipt of genetic risk information significantly improves blood pressure control among African anecestry adults with hypertension
BT  - results of a randomized trail
T2  - Journal of General Internal Medicine
Y1  - 2018
U6  - https://doi.org/10.1007/s11606-018-4413-y
SN  - 0884-8734
SN  - 1525-1497
VL  - 33
SP  - S322
EP  - S323
PB  - Springer
CY  - New York
ER  - 
TY  - JOUR
A1  - Böttinger, Erwin
T1  - Wendepunkt für Gesundheit
JF  - Die Zukunft der Medizin : Disruptive Innovationen revolutionieren Medizin und Gesundheit
Y1  - 2019
SN  - 978-3-95466-398-9
SN  - 978-3-95466-448-1
SP  - 201
EP  - 210
PB  - Medizinisch Wissenschaftliche Verlagsgesellschaft
CY  - Berlin
ER  - 
TY  - GEN
A1  - Zenner, Alexander M.
A1  - Böttinger, Erwin
A1  - Konigorski, Stefan
T1  - StudyMe
BT  - a new mobile app for user-centric N-of-1 trials
T2  - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät
N2  - N-of-1 trials are multi-crossover self-experiments that allow individuals to systematically evaluate the effect of interventions on their personal health goals. Although several tools for N-of-1 trials exist, there is a gap in supporting non-experts in conducting their own user-centric trials. In this study, we present StudyMe, an open-source mobile application that is freely available from https://play.google.com/store/apps/details?id=health.studyu.me and offers users flexibility and guidance in configuring every component of their trials. We also present research that informed the development of StudyMe, focusing on trial creation. Through an initial survey with 272 participants, we learned that individuals are interested in a variety of personal health aspects and have unique ideas on how to improve them. In an iterative, user-centered development process with intermediate user tests, we developed StudyMe that features an educational part to communicate N-of-1 trial concepts. A final empirical evaluation of StudyMe showed that all participants were able to create their own trials successfully using StudyMe and the app achieved a very good usability rating. Our findings suggest that StudyMe provides a significant step towards enabling individuals to apply a systematic science-oriented approach to personalize health-related interventions and behavior modifications in their everyday lives.
T3  - Zweitveröffentlichungen der Universität Potsdam : Reihe der Digital Engineering Fakultät - 18 
Y1  - 2022
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-589763
IS  - 18
ER  - 
TY  - JOUR
A1  - Chan, Lili
A1  - Chaudhary, Kumardeep
A1  - Saha, Aparna
A1  - Chauhan, Kinsuk
A1  - Vaid, Akhil
A1  - Zhao, Shan
A1  - Paranjpe, Ishan
A1  - Somani, Sulaiman
A1  - Richter, Felix
A1  - Miotto, Riccardo
A1  - Lala, Anuradha
A1  - Kia, Arash
A1  - Timsina, Prem
A1  - Li, Li
A1  - Freeman, Robert
A1  - Chen, Rong
A1  - Narula, Jagat
A1  - Just, Allan C.
A1  - Horowitz, Carol
A1  - Fayad, Zahi
A1  - Cordon-Cardo, Carlos
A1  - Schadt, Eric
A1  - Levin, Matthew A.
A1  - Reich, David L.
A1  - Fuster, Valentin
A1  - Murphy, Barbara
A1  - He, John C.
A1  - Charney, Alexander W.
A1  - Böttinger, Erwin
A1  - Glicksberg, Benjamin
A1  - Coca, Steven G.
A1  - Nadkarni, Girish N.
T1  - AKI in hospitalized patients with COVID-19
JF  - Journal of the American Society of Nephrology : JASN
N2  - Background:
Early reports indicate that AKI is common among patients with coronavirus disease 2019 (COVID-19) and associatedwith worse outcomes. However, AKI among hospitalized patients with COVID19 in the United States is not well described. 

Methods:
This retrospective, observational study involved a review of data from electronic health records of patients aged >= 18 years with laboratory-confirmed COVID-19 admitted to the Mount Sinai Health System from February 27 to May 30, 2020. We describe the frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aORs) with mortality. 

Results:
Of 3993 hospitalized patients with COVID-19, AKI occurred in 1835 (46%) patients; 347 (19%) of the patientswith AKI required dialysis. The proportionswith stages 1, 2, or 3 AKIwere 39%, 19%, and 42%, respectively. A total of 976 (24%) patients were admitted to intensive care, and 745 (76%) experienced AKI. Of the 435 patients with AKI and urine studies, 84% had proteinuria, 81% had hematuria, and 60% had leukocyturia. Independent predictors of severe AKI were CKD, men, and higher serum potassium at admission. In-hospital mortality was 50% among patients with AKI versus 8% among those without AKI (aOR, 9.2; 95% confidence interval, 7.5 to 11.3). Of survivors with AKI who were discharged, 35% had not recovered to baseline kidney function by the time of discharge. An additional 28 of 77 (36%) patients who had not recovered kidney function at discharge did so on posthospital follow-up. 

Conclusions:
AKI is common among patients hospitalized with COVID-19 and is associated with high mortality. Of all patients with AKI, only 30% survived with recovery of kidney function by the time of discharge.
KW  - acute renal failure
KW  - clinical nephrology
KW  - dialysis
KW  - COVID-19
Y1  - 2021
U6  - https://doi.org/10.1681/ASN.2020050615
SN  - 1046-6673
SN  - 1533-3450
VL  - 32
IS  - 1
SP  - 151
EP  - 160
PB  - American Society of Nephrology
CY  - Washington
ER  - 
TY  - JOUR
A1  - Lewkowicz, Daniel
A1  - Wohlbrandt, Attila M.
A1  - Böttinger, Erwin
T1  - Digital therapeutic care apps with decision-support interventions for people with low back pain in Germany
BT  - Cost-effectiveness analysis
JF  - JMIR mhealth and uhealth
N2  - Background:
Digital therapeutic care apps provide a new effective and scalable approach for people with nonspecific low back pain (LBP). Digital therapeutic care apps are also driven by personalized decision-support interventions that support the user in self-managing LBP, and may induce prolonged behavior change to reduce the frequency and intensity of pain episodes. However, these therapeutic apps are associated with high attrition rates, and the initial prescription cost is higher than that of face-to-face physiotherapy. In Germany, digital therapeutic care apps are now being reimbursed by statutory health insurance; however, price targets and cost-driving factors for the formation of the reimbursement rate remain unexplored.

Objective: 
The aim of this study was to evaluate the cost-effectiveness of a digital therapeutic care app compared to treatment as usual (TAU) in Germany. We further aimed to explore under which circumstances the reimbursement rate could be modified to consider value-based pricing.

Methods:
We developed a state-transition Markov model based on a best-practice analysis of prior LBP-related decision-analytic models, and evaluated the cost utility of a digital therapeutic care app compared to TAU in Germany. Based on a 3-year time horizon, we simulated the incremental cost and quality-adjusted life years (QALYs) for people with nonacute LBP from the societal perspective. In the deterministic sensitivity and scenario analyses, we focused on diverging attrition rates and app cost to assess our model's robustness and conditions for changing the reimbursement rate. All costs are reported in Euro (euro1=US $1.12).

Results:
Our base case results indicated that the digital therapeutic care strategy led to an incremental cost of euro121.59, but also generated 0.0221 additional QALYs compared to the TAU strategy, with an estimated incremental cost-effectiveness ratio (ICER) of euro5486 per QALY. The sensitivity analysis revealed that the reimbursement rate and the capability of digital therapeutic care to prevent reoccurring LBP episodes have a significant impact on the ICER. At the same time, the other parameters remained unaffected and thus supported the robustness of our model. In the scenario analysis, the different model time horizons and attrition rates strongly influenced the economic outcome. Reducing the cost of the app to euro99 per 3 months or decreasing the app's attrition rate resulted in digital therapeutic care being significantly less costly with more generated QALYs, and is thus considered to be the dominant strategy over TAU.

Conclusions:
The current reimbursement rate for a digital therapeutic care app in the statutory health insurance can be considered a cost-effective measure compared to TAU. The app's attrition rate and effect on the patient's prolonged behavior change essentially influence the settlement of an appropriate reimbursement rate. Future value-based pricing targets should focus on additional outcome parameters besides pain intensity and functional disability by including attrition rates and the app's long-term effect on quality of life.
KW  - cost-utility analysis
KW  - low back pain
KW  - back pain
KW  - cost-effectiveness
KW  - Markov model
KW  - digital therapy
KW  - digital health app
KW  - mHealth
KW  - orthopedic;
KW  - eHealth
KW  - mobile health
KW  - digital health
KW  - pain management
KW  - health apps
Y1  - 2022
U6  - https://doi.org/10.2196/35042
SN  - 2291-5222
VL  - 10
IS  - 2
PB  - JMIR Publications
CY  - Toronto
ER  -