title: Development of an optical character recognition pipeline for handwritten form fields from an electronic health record.
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.
  
  
  METHODS
  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%.
  
  
  CONCLUSIONS
  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.
authors: Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin 54449, USA. rasmussen.luke@mcrf.mfldclin.edu
authors: Luke V
authors: LV
authors: Rasmussen
authors: Peggy L
authors: PL
authors: Peissig
authors: Catherine A
authors: CA
authors: McCarty
authors: Justin
authors: J
authors: Starren
mesh_terms: D001330:Electronic Data Processing; D057286:Electronic Health Records; D006801:Humans