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JMIR Med Inform. 2017 Sep 13;5(3):e27. doi: 10.2196/medinform.7465.

Prototype Development: Context-Driven Dynamic XML Ophthalmologic Data Capture Application.

Author information

1
Marshfield Clinic Research Institute, Biomedical Informatics Research Center, Marshfield, WI, United States.
2
Marshfield Clinic Research Institute, Center for Oral and Systemic Health, Marshfield, WI, United States.
3
Marshfield Clinic, Department of Ophthalmology, Marshfield, WI, United States.
4
Essentia Institute of Rural Health, Center for Research and Education, Duluth, MN, United States.
5
Center for Genetic Medicine, Northwestern University, Chicago, IL, United States.
6
Weill Cornell Medical College, Healthcare Policy and Research, Cornell University, New York, NY, United States.
7
Personalized Medicine Institute, Mount Sinai, New York, NY, United States.
8
School of Medicine, Biomedical Informatics, Vanderbilt University, Nashville, TN, United States.
9
Division of Health and Biomedical Informatics, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.
10
Autism and Developmental Medicine Institute (ADMI), Geisinger, Danville, PA, United States.
11
Genomic Medical Institute, Geisinger, Danville, PA, United States.
12
Department of Ophthalmology, Geisinger, Danville, PA, United States.
13
Marshfield Clinic Research Foundation, Human Genetics, Marshfield, WI, United States.

Abstract

BACKGROUND:

The capture and integration of structured ophthalmologic data into electronic health records (EHRs) has historically been a challenge. However, the importance of this activity for patient care and research is critical.

OBJECTIVE:

The purpose of this study was to develop a prototype of a context-driven dynamic extensible markup language (XML) ophthalmologic data capture application for research and clinical care that could be easily integrated into an EHR system.

METHODS:

Stakeholders in the medical, research, and informatics fields were interviewed and surveyed to determine data and system requirements for ophthalmologic data capture. On the basis of these requirements, an ophthalmology data capture application was developed to collect and store discrete data elements with important graphical information.

RESULTS:

The context-driven data entry application supports several features, including ink-over drawing capability for documenting eye abnormalities, context-based Web controls that guide data entry based on preestablished dependencies, and an adaptable database or XML schema that stores Web form specifications and allows for immediate changes in form layout or content. The application utilizes Web services to enable data integration with a variety of EHRs for retrieval and storage of patient data.

CONCLUSIONS:

This paper describes the development process used to create a context-driven dynamic XML data capture application for optometry and ophthalmology. The list of ophthalmologic data elements identified as important for care and research can be used as a baseline list for future ophthalmologic data collection activities.

KEYWORDS:

data acquisition; data collection; electronic health records; extensible markup language XML; ophthalmology

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