CM-Extractor: An Application for Automating Medical Quality Measures Abstraction in a Hospital Setting
Abstract
In the US, health care providers are required to report evidence-based quality measures to various governmental and independent regulatory agencies. Abstracting appropriate facts from a patient’s medical record provides the data for these measures. Finding and maintaining qualified staff for this vital function is a challenge to many healthcare providers. Emerging systems and technologies in large-scale clinical repositories and AI techniques for information extraction have the potential to make the process of collecting measures more consistent, accurate and efficient. This paper presents CM-Extractor, a computerized system that automates the process of quality measures abstraction using natural language processing and a rule-based approach. An evaluation of a deployed system used for hospital inpatient
Cite
Text
Morsch et al. "CM-Extractor: An Application for Automating Medical Quality Measures Abstraction in a Hospital Setting." AAAI Conference on Artificial Intelligence, 2006.Markdown
[Morsch et al. "CM-Extractor: An Application for Automating Medical Quality Measures Abstraction in a Hospital Setting." AAAI Conference on Artificial Intelligence, 2006.](https://mlanthology.org/aaai/2006/morsch2006aaai-cm/)BibTeX
@inproceedings{morsch2006aaai-cm,
title = {{CM-Extractor: An Application for Automating Medical Quality Measures Abstraction in a Hospital Setting}},
author = {Morsch, Mark L. and Vengco, Joel L. and Jr., Ronald E. Sheffer and Heinze, Daniel T.},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2006},
pages = {1814-1821},
url = {https://mlanthology.org/aaai/2006/morsch2006aaai-cm/}
}