Secondary use of routine data in hospitals: description of a scalable analytical platform based on a business intelligence system

Jan A Roth; Nicole Goebel; Thomas Sakoparnig; Simon Neubauer; Eleonore Kuenzel-Pawlik; Martin Gerber; Andreas F Widmer; Christian Abshagen; Rakesh Padiyath; Balthasar L Hug; PATREC Study Group

doi:10.1093/jamiaopen/ooy039

Secondary use of routine data in hospitals: description of a scalable analytical platform based on a business intelligence system

JAMIA Open. 2018 Sep 20;1(2):172-177. doi: 10.1093/jamiaopen/ooy039. eCollection 2018 Oct.

Authors

Jan A Roth^{1

2}, Nicole Goebel^{2

3

4}, Thomas Sakoparnig^{2

5

6}, Simon Neubauer^{2

3

4}, Eleonore Kuenzel-Pawlik^{2

3

4}, Martin Gerber^{2

4}, Andreas F Widmer^{1

2}, Christian Abshagen^{2

4}, Rakesh Padiyath^{2

4}, Balthasar L Hug^{2

7}; PATREC Study Group

Collaborators

PATREC Study Group:
Christian Abshagen, Geoffrey Fucile, Martin Gerber, Nicole Goebel, Balthasar L Hug, Bernd Jaegle, Eleonore Kuenzel-Pawlik, Simon Neubauer, Rakesh Padiyath, Jan A Roth, Thomas Sakoparnig, Thierry Sengstag, Damian Spyra, Andreas F Widmer

Affiliations

¹ Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Basel, Switzerland.
² University of Basel, Basel, Switzerland.
³ Analytics Unit, Department of Finance, University Hospital Basel, Basel, Switzerland.
⁴ Department of Finance, University Hospital Basel, Basel, Switzerland.
⁵ Focal Area of Computational and Systems Biology, Biozentrum, University of Basel, Basel, Switzerland.
⁶ Swiss Institute of Bioinformatics, Biozentrum, University of Basel, Basel, Switzerland.
⁷ Department of Internal Medicine, Kantonsspital Luzern, Lucerne, Switzerland.

Abstract

We describe a scalable platform for research-oriented analyses of routine data in hospitals, which evolved from a state-of-the-art business intelligence architecture for enterprise resource planning. This platform involves an in-memory database management system for data modeling and analytics and a high-performance cluster for more computing-intensive analytical tasks. Setting up platforms for research-oriented analyses is a highly dynamic, time-consuming, and costly process. In some health care institutions, effective research platforms may be derived from existing business intelligence systems.

Keywords: database management systems; health information systems; health services research; high performance analytic appliance (HANA); machine learning.

Publication types

Case Reports