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J Am Med Inform Assoc. 2019 Jul 1;26(7):637-645. doi: 10.1093/jamia/ocz014.

A federated EHR network data completeness tracking system.

Author information

1
Laboratory of Computer Science, Massachusetts General Hospital, Boston, Massachusetts, USA.
2
Research Information Science and Computing, Partners HealthCare, Charlestown, Massachusetts, USA.
3
Harvard Medical School, Boston, Massachusetts, USA.
4
Morehouse School of Medicine, Atlanta, Georgia, USA.
5
School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, Texas, USA.
6
Boston University School of Medicine/Boston Medical Center, Boston, Massachusetts, USA.
7
Information Services Department, Boston Children's Hospital, Boston, Massachusetts, USA.
8
Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.
9
Department of Pediatrics, Boston University School of Medicine/Boston Medical Center, Boston, Massachusetts, USA.
10
Computational Health Informatics Program, Boston Children's Hospital, Boston, Massachusetts, USA.
11
Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA.
12
Program in Pediatric Rheumatology, Department of Pediatrics, Mass General Hospital for Children, Boston, Massachusetts, USA.
13
Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA.
14
Division of General Internal Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas, USA.
15
Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA.
16
Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.

Abstract

OBJECTIVE:

The study sought to design, pilot, and evaluate a federated data completeness tracking system (CTX) for assessing completeness in research data extracted from electronic health record data across the Accessible Research Commons for Health (ARCH) Clinical Data Research Network.

MATERIALS AND METHODS:

The CTX applies a systems-based approach to design workflow and technology for assessing completeness across distributed electronic health record data repositories participating in a queryable, federated network. The CTX invokes 2 positive feedback loops that utilize open source tools (DQe-c and Vue) to integrate technology and human actors in a system geared for increasing capacity and taking action. A pilot implementation of the system involved 6 ARCH partner sites between January 2017 and May 2018.

RESULTS:

The ARCH CTX has enabled the network to monitor and, if needed, adjust its data management processes to maintain complete datasets for secondary use. The system allows the network and its partner sites to profile data completeness both at the network and partner site levels. Interactive visualizations presenting the current state of completeness in the context of the entire network as well as changes in completeness across time were valued among the CTX user base.

DISCUSSION:

Distributed clinical data networks are complex systems. Top-down approaches that solely rely on technology to report data completeness may be necessary but not sufficient for improving completeness (and quality) of data in large-scale clinical data networks. Improving and maintaining complete (high-quality) data in such complex environments entails sociotechnical systems that exploit technology and empower human actors to engage in the process of high-quality data curating.

CONCLUSIONS:

The CTX has increased the network's capacity to rapidly identify data completeness issues and empowered ARCH partner sites to get involved in improving the completeness of respective data in their repositories.

KEYWORDS:

data completeness; data quality; electronic health records; systems thinking

PMID:
30925587
DOI:
10.1093/jamia/ocz014

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