Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
HEALTH BANK - A Workbench for Data Science Applications in Healthcare
58
Zitationen
5
Autoren
2015
Jahr
Abstract
The enormous amounts of data that are generated in the healthcare process and stored in electronic health record (EHR) systems are an underutilized resource that, with the use of data science applications, can be exploited to improve healthcare. To foster the development and use of data science applications in healthcare, there is a fundamental need for access to EHR data, which is typically not readily available to researchers and developers. A relatively rare exception is the large EHR database, the Stockholm EPR Corpus, comprising data from more than two million patients, that has been been made available to a limited group of researchers at Stockholm University. Here, we describe a number of data science applications that have been developed using this database, demonstrating the potential reuse of EHR data to support healthcare and public health activities, as well as facilitate medical research. However, in order to realize the full potential of this resource, it needs to be made available to a larger community of researchers, as well as to industry actors. To that end, we envision the provision of an infrastructure around this database called HEALTH BANK - the Swedish Health Record Research Bank. It will function both as a workbench for the development of data science applications and as a data exploration tool, allowing epidemiologists, pharmacologists and other medical researchers to generate and evaluate hypotheses. Aggregated data will be fed into a pipeline for open e-access, while non-aggregated data will be provided to researchers within an ethical permission framework. We believe that HEALTH BANK has the potential to promote a growing industry around the development of data science applications that will ultimately increase the efficiency and effectiveness of healthcare. Copyright © 2015 held by the authors. Copyright © 2015 for the individual papers by the papers' authors.
Ähnliche Arbeiten
Machine Learning in Medicine
2019 · 3.818 Zit.
Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical Care
2006 · 3.176 Zit.
Effects of Computerized Clinical Decision Support Systems on Practitioner Performance and Patient Outcomes
2005 · 2.972 Zit.
Studies in health technology and informatics
2008 · 2.903 Zit.
An overview of clinical decision support systems: benefits, risks, and strategies for success
2020 · 2.743 Zit.