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BMC Med Inform Decis Mak. 2017 Jul 19;17(1):111. doi: 10.1186/s12911-017-0501-x.

Utilizing patient data from the veterans administration electronic health record to support web-based clinical decision support: informatics challenges and issues from three clinical domains.

Author information

1
VA Connecticut Healthcare System, 950 Campbell Avenue, West Haven, CT, 06516, USA. n.rajeevan@yale.edu.
2
Yale Center for Medical Informatics, Yale University School of Medicine, 300 George Street, Ste 501, New Haven, CT, 06511, USA. n.rajeevan@yale.edu.
3
Department of Anesthesiology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA. n.rajeevan@yale.edu.
4
VA Connecticut Healthcare System, 950 Campbell Avenue, West Haven, CT, 06516, USA.
5
Department of Medicine, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA.
6
Yale University School of Public Health, 60 College Street, New Haven, CT, 06520, USA.
7
Yale Center for Medical Informatics, Yale University School of Medicine, 300 George Street, Ste 501, New Haven, CT, 06511, USA.
8
Department of Emergency Medicine, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA.
9
Department of Anesthesiology, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA.

Abstract

BACKGROUND:

The US Veterans Administration (VA) has developed a robust and mature computational infrastructure in support of its electronic health record (EHR). Web technology offers a powerful set of tools for structuring clinical decision support (CDS) around clinical care. This paper describes informatics challenges and design issues that were confronted in the process of building three Web-based CDS systems in the context of the VA EHR.

METHODS:

Over the course of several years, we implemented three Web-based CDS systems that extract patient data from the VA EHR environment to provide patient-specific CDS. These were 1) the VACS (Veterans Aging Cohort Study) Index Calculator which estimates prognosis for HIV+ patients, 2) Neuropath/CDS which assists in the medical management of patients with neuropathic pain, and 3) TRIM (Tool to Reduce Inappropriate Medications) which identifies potentially inappropriate medications in older adults and provides recommendations for improving the medication regimen.

RESULTS:

The paper provides an overview of the VA EHR environment and discusses specific informatics issues/challenges that arose in the context of each of the three Web-based CDS systems. We discuss specific informatics methods and provide details of approaches that may be useful within this setting.

CONCLUSIONS:

Informatics issues and challenges relating to data access and data availability arose because of the particular architecture of the national VA infrastructure and the need to link to that infrastructure from local Web-based CDS systems. Idiosyncrasies of VA patient data, especially the medication data, also posed challenges. Other issues related to specific functional needs of individual CDS systems. The goal of this paper is to describe these issues so that our experience may serve as a useful foundation to assist others who wish to build such systems in the future.

KEYWORDS:

Biomedical informatics; Clinical decision support; Electronic health records systems

PMID:
28724368
PMCID:
PMC5517800
DOI:
10.1186/s12911-017-0501-x
[Indexed for MEDLINE]
Free PMC Article

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