@article{ficheur_interoperability_2011,
	title = {Interoperability of medical databases: construction of mapping between hospitals laboratory results assisted by automated comparison of their distributions},
	volume = {2011},
	copyright = {All rights reserved},
	issn = {1942-597X},
	shorttitle = {Interoperability of medical databases},
	url = {http://www.chazard.org/emmanuel/pdf_articles/paper_2011_amia_interoperabilitymappinglaboratoryresults.pdf},
	abstract = {In hospital information systems, laboratory results are stored using specific terminologies which may differ between hospitals. The objective is to create a tool helping to build a mapping between a target terminology (reference dataset) and a new one. Using a training sample consisting of correct and incorrect correspondences between parameters of different hospitals, a match probability score is built. This model also enables to determine the theoretical conversion factor between two parameters. This method is evaluated on a test sample of a new hospital: For each reference parameter, best candidates are returned and sorted in decreasing order using the probability given by the model. The correct correspondent of 14 among 15 reference parameters are ranked in the top five among more than 70. All conversion factors are correct. A mapping webtool is built to present the essential information for best candidates. Using this tool, an expert has found all the correct pairs.},
	language = {eng},
	journal = {AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium},
	author = {Ficheur, Grégoire and Chazard, Emmanuel and Schaffar, Aurélien and Genty, Matthieu and Beuscart, Régis},
	year = {2011},
	pmid = {22195092},
	keywords = {Clinical Laboratory Information Systems, Databases, Factual, Hospital Information Systems, Laboratories, Hospital, Medical Record Linkage, Models, Statistical, Systems Integration, Vocabulary, Controlled},
	pages = {392--401},
}

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The objective is to create a tool helping to build a mapping between a target terminology (reference dataset) and a new one. Using a training sample consisting of correct and incorrect correspondences between parameters of different hospitals, a match probability score is built. This model also enables to determine the theoretical conversion factor between two parameters. This method is evaluated on a test sample of a new hospital: For each reference parameter, best candidates are returned and sorted in decreasing order using the probability given by the model. The correct correspondent of 14 among 15 reference parameters are ranked in the top five among more than 70. All conversion factors are correct. A mapping webtool is built to present the essential information for best candidates. Using this tool, an expert has found all the correct pairs.","language":"eng","journal":"AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium","author":[{"propositions":[],"lastnames":["Ficheur"],"firstnames":["Grégoire"],"suffixes":[]},{"propositions":[],"lastnames":["Chazard"],"firstnames":["Emmanuel"],"suffixes":[]},{"propositions":[],"lastnames":["Schaffar"],"firstnames":["Aurélien"],"suffixes":[]},{"propositions":[],"lastnames":["Genty"],"firstnames":["Matthieu"],"suffixes":[]},{"propositions":[],"lastnames":["Beuscart"],"firstnames":["Régis"],"suffixes":[]}],"year":"2011","pmid":"22195092","keywords":"Clinical Laboratory Information Systems, Databases, Factual, Hospital Information Systems, Laboratories, Hospital, Medical Record Linkage, Models, Statistical, Systems Integration, Vocabulary, Controlled","pages":"392–401","bibtex":"@article{ficheur_interoperability_2011,\n\ttitle = {Interoperability of medical databases: construction of mapping between hospitals laboratory results assisted by automated comparison of their distributions},\n\tvolume = {2011},\n\tcopyright = {All rights reserved},\n\tissn = {1942-597X},\n\tshorttitle = {Interoperability of medical databases},\n\turl = {http://www.chazard.org/emmanuel/pdf_articles/paper_2011_amia_interoperabilitymappinglaboratoryresults.pdf},\n\tabstract = {In hospital information systems, laboratory results are stored using specific terminologies which may differ between hospitals. The objective is to create a tool helping to build a mapping between a target terminology (reference dataset) and a new one. Using a training sample consisting of correct and incorrect correspondences between parameters of different hospitals, a match probability score is built. This model also enables to determine the theoretical conversion factor between two parameters. This method is evaluated on a test sample of a new hospital: For each reference parameter, best candidates are returned and sorted in decreasing order using the probability given by the model. The correct correspondent of 14 among 15 reference parameters are ranked in the top five among more than 70. All conversion factors are correct. A mapping webtool is built to present the essential information for best candidates. Using this tool, an expert has found all the correct pairs.},\n\tlanguage = {eng},\n\tjournal = {AMIA ... Annual Symposium proceedings / AMIA Symposium. 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