Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Jan 1:2019:baz039.
doi: 10.1093/database/baz039.

A dimensional warehouse for integrating operational data from clinical trials

Michael A Farnum  1 , Lalit Mohanty  1 , Mathangi Ashok  1 , Paul Konstant  1 , Joseph Ciervo  1 , Victor S Lobanov  1 , Dimitris K Agrafiotis  1
Affiliations

A dimensional warehouse for integrating operational data from clinical trials

Michael A Farnum et al. Database (Oxford). .

Abstract

Timely, consistent and integrated access to clinical trial data remains one of the pharmaceutical industry's most pressing needs. As part of a comprehensive clinical data repository, we have developed a data warehouse that can integrate operational data from any source, conform it to a canonical data model and make it accessible to study teams in a timely, secure and contextualized manner to support operational oversight, proactive risk management and other analytic and reporting needs. Our solution consists of a dimensional relational data warehouse, a set of extraction, transformation and loading processes to coordinate data ingestion and mapping, a generalizable metrics engine to enable the computation of operational metrics and key performance, quality and risk indicators and a set of graphical user interfaces to facilitate configuration, management and administration. When combined with the appropriate data visualization tools, the warehouse enables convenient access to raw operational data and derived metrics to help track study conduct and performance, identify and mitigate risks, monitor and improve operational processes, manage resource allocation, strengthen investigator and sponsor relationships and other purposes.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Xcellerate architecture.
Figure 2
Figure 2
Simplified representation of the operational data model.
Figure 3
Figure 3
Representative study and portfolio metrics and attributes.
Figure 4
Figure 4
Metric configuration UI. This application allows the configurators to specify the parameters stored in the system to describe and implement the metric. Metrics can be defined using arbitrarily complex and parameterized SQL statements. The parameters are entered separately to promote reuse of the overall logic.
Figure 5
Figure 5
Xcellerate Monitoring Administration Console. The interface allows a set of metrics to be edited and configured into templates for use across sets of studies.
Figure 6
Figure 6
Representative screenshot of the Xcellerate Monitoring Study Configuration Console. The study configuration console allows study-specific updates to be made for individual metrics, including changing parameterized values and thresholds for scoring the risk levels. The particular example illustrated below shows the rules used to define various risk indicators used in RBM.
Figure 7
Figure 7
Representative screenshots of the Study Reporting UI that uses the ODW as a source. Top left: study summary view. Top right: monthly metrics view. Middle left: country view. Middle right: site view. Bottom left: protocol deviations view. Bottom right: data management view.
Figure 8
Figure 8
Representative screenshots of the Portfolio Reporting UI created with metrics derived from the ODW. Top left: milestones. Top right: KPIs. Bottom left: site readiness. Bottom right: KPI scorecard.
Figure 9
Figure 9
CRA Dashboard (mobile version).
See this image and copyright information in PMC

References

    1. Park Y.R., Yoon Y.J., Koo H. et al. (2018) Utilization of a clinical trial management system for the whole clinical trial process as an integrated database: system development. J. Med. Internet Res., 20, e103. - PMC - PubMed
    1. Bose A. and Das S. (2012) Trial analytics: a tool for clinical trial management. Acta Pol. Pharm., 69, 523–533. - PubMed
    1. Kimball R. and Ross M. (2002) The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, 2nd edn. Wiley Computer Publishing, New York.
    1. Holmes J.H., Elliott T.E., Brown J.S. et al. (2014) Clinical research data warehouse governance for distributed research networks in the USA: a systematic review of the literature. J. Am. Med. Inform. Assoc., 21, 730–736. - PMC - PubMed
    1. Chelico J.D., Wilcox A.B., Vawdrey D.K. et al. (2016) Designing a clinical data warehouse architecture to support quality improvement initiatives. AMIA Annu. Symp. Proc., 2016, 381–390. - PMC - PubMed