CC BY 4.0 · ACI open 2022; 06(01): e1-e10
DOI: 10.1055/s-0042-1744383
Special Section on Informatics Governance

The Role of Analytics Governance to Promote Health Care Transformation

Bruce Levy
1   Department of Medical Education, Geisinger Commonwealth School of Medicine, Scranton, Pennsylvania, United States
,
Karen Murphy
2   Steele Institute for Health Innovation, Geisinger Health, Danville, Pennsylvania, United States
,
Greg Strevig
2   Steele Institute for Health Innovation, Geisinger Health, Danville, Pennsylvania, United States
,
Ilia Decker
2   Steele Institute for Health Innovation, Geisinger Health, Danville, Pennsylvania, United States
,
Kirk Hanson
2   Steele Institute for Health Innovation, Geisinger Health, Danville, Pennsylvania, United States
,
Raghuveer Puttagunta
1   Department of Medical Education, Geisinger Commonwealth School of Medicine, Scranton, Pennsylvania, United States
,
Shikha Sinha
1   Department of Medical Education, Geisinger Commonwealth School of Medicine, Scranton, Pennsylvania, United States
,
Spencer Tavares
1   Department of Medical Education, Geisinger Commonwealth School of Medicine, Scranton, Pennsylvania, United States
,
Leyla Warsame
1   Department of Medical Education, Geisinger Commonwealth School of Medicine, Scranton, Pennsylvania, United States
,
David Vawdrey
2   Steele Institute for Health Innovation, Geisinger Health, Danville, Pennsylvania, United States
› Author Affiliations
Funding None.

Abstract

Objectives Rapid digitization in health care during the 21st century has created significant data and analytics challenges for our providers and health systems. Just as information technology (IT) governance has helped manage exploding demand for IT services and increased efficiencies, analytics governance promises to bring these same benefits to data and analytics efforts. Potential governance models exist in other industries yet have not significantly penetrated health care.

Methods and Results Geisinger has implemented analytics governance throughout our enterprise. We identified and accomplished six core goals toward the establishment of analytics governance, including developing a vision; defining the organizational structure, roles, and responsibilities; managing our data assets; implementing robust data governance; establishing standardized analytics processes; and utilizing metrics to evaluate our progress. Early outcomes include improved tracking and intelligence around data/analytics requests, decreases in duplicative data/analytics efforts, the creation of the Enterprise Analytics Hub for employees to consume data, and initial steps toward self-service analytics.

Conclusion Our experiences support the proposition that analytics governance can provide meaningful benefits to health systems. It is clear from the experiences in other industries that health systems who can best manage their data and analytics will have a significant competitive advantage. Analytics governance will also provide a proper foundation for the use of advanced analytics, machine learning, and visualization tools, and prepare our workforce to utilize these tools for the benefit of patients.

Author Contributions

All authors have significantly contributed to this work and this manuscript.


Protection of Human and Animal Subjects

No human or animal subjects were included in this study.




Publication History

Received: 13 April 2021

Accepted: 19 November 2021

Article published online:
27 June 2022

© 2022. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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