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J Am Med Inform Assoc. 2012 Jun;19(e1):e90-5. Epub 2011 Sep 2.

Development of an optical character recognition pipeline for handwritten form fields from an electronic health record.

Author information

1
Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin 54449, USA. rasmussen.luke@mcrf.mfldclin.edu

Abstract

BACKGROUND:

Although the penetration of electronic health records is increasing rapidly, much of the historical medical record is only available in handwritten notes and forms, which require labor-intensive, human chart abstraction for some clinical research. The few previous studies on automated extraction of data from these handwritten notes have focused on monolithic, custom-developed recognition systems or third-party systems that require proprietary forms.

METHODS:

We present an optical character recognition processing pipeline, which leverages the capabilities of existing third-party optical character recognition engines, and provides the flexibility offered by a modular custom-developed system. The system was configured and run on a selected set of form fields extracted from a corpus of handwritten ophthalmology forms.

OBSERVATIONS:

The processing pipeline allowed multiple configurations to be run, with the optimal configuration consisting of the Nuance and LEADTOOLS engines running in parallel with a positive predictive value of 94.6% and a sensitivity of 13.5%.

DISCUSSION:

While limitations exist, preliminary experience from this project yielded insights on the generalizability and applicability of integrating multiple, inexpensive general-purpose third-party optical character recognition engines in a modular pipeline.

PMID:
21890871
PMCID:
PMC3392858
DOI:
10.1136/amiajnl-2011-000182
[Indexed for MEDLINE]
Free PMC Article

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