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Development of a Database of Health Insurance Claims: Standardization of Disease Classifications and Anonymous Record Linkage

BACKGROUND: Health insurance claims (ie, receipts) record patient health care treatments and expenses and, although created for the health care payment system, are potentially useful for research. Combining different types of receipts generated for the same patient would dramatically increase the ut...

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Autores principales: Kimura, Shinya, Sato, Toshihiko, Ikeda, Shunya, Noda, Mitsuhiko, Nakayama, Takeo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Japan Epidemiological Association 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3900837/
https://www.ncbi.nlm.nih.gov/pubmed/20699602
http://dx.doi.org/10.2188/jea.JE20090066
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author Kimura, Shinya
Sato, Toshihiko
Ikeda, Shunya
Noda, Mitsuhiko
Nakayama, Takeo
author_facet Kimura, Shinya
Sato, Toshihiko
Ikeda, Shunya
Noda, Mitsuhiko
Nakayama, Takeo
author_sort Kimura, Shinya
collection PubMed
description BACKGROUND: Health insurance claims (ie, receipts) record patient health care treatments and expenses and, although created for the health care payment system, are potentially useful for research. Combining different types of receipts generated for the same patient would dramatically increase the utility of these receipts. However, technical problems, including standardization of disease names and classifications, and anonymous linkage of individual receipts, must be addressed. METHODS: In collaboration with health insurance societies, all information from receipts (inpatient, outpatient, and pharmacy) was collected. To standardize disease names and classifications, we developed a computer-aided post-entry standardization method using a disease name dictionary based on International Classification of Diseases (ICD)-10 classifications. We also developed an anonymous linkage system by using an encryption code generated from a combination of hash values and stream ciphers. Using different sets of the original data (data set 1: insurance certificate number, name, and sex; data set 2: insurance certificate number, date of birth, and relationship status), we compared the percentage of successful record matches obtained by using data set 1 to generate key codes with the percentage obtained when both data sets were used. RESULTS: The dictionary’s automatic conversion of disease names successfully standardized 98.1% of approximately 2 million new receipts entered into the database. The percentage of anonymous matches was higher for the combined data sets (98.0%) than for data set 1 (88.5%). CONCLUSIONS: The use of standardized disease classifications and anonymous record linkage substantially contributed to the construction of a large, chronologically organized database of receipts. This database is expected to aid in epidemiologic and health services research using receipt information.
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spelling pubmed-39008372014-02-04 Development of a Database of Health Insurance Claims: Standardization of Disease Classifications and Anonymous Record Linkage Kimura, Shinya Sato, Toshihiko Ikeda, Shunya Noda, Mitsuhiko Nakayama, Takeo J Epidemiol Study Profile BACKGROUND: Health insurance claims (ie, receipts) record patient health care treatments and expenses and, although created for the health care payment system, are potentially useful for research. Combining different types of receipts generated for the same patient would dramatically increase the utility of these receipts. However, technical problems, including standardization of disease names and classifications, and anonymous linkage of individual receipts, must be addressed. METHODS: In collaboration with health insurance societies, all information from receipts (inpatient, outpatient, and pharmacy) was collected. To standardize disease names and classifications, we developed a computer-aided post-entry standardization method using a disease name dictionary based on International Classification of Diseases (ICD)-10 classifications. We also developed an anonymous linkage system by using an encryption code generated from a combination of hash values and stream ciphers. Using different sets of the original data (data set 1: insurance certificate number, name, and sex; data set 2: insurance certificate number, date of birth, and relationship status), we compared the percentage of successful record matches obtained by using data set 1 to generate key codes with the percentage obtained when both data sets were used. RESULTS: The dictionary’s automatic conversion of disease names successfully standardized 98.1% of approximately 2 million new receipts entered into the database. The percentage of anonymous matches was higher for the combined data sets (98.0%) than for data set 1 (88.5%). CONCLUSIONS: The use of standardized disease classifications and anonymous record linkage substantially contributed to the construction of a large, chronologically organized database of receipts. This database is expected to aid in epidemiologic and health services research using receipt information. Japan Epidemiological Association 2010-09-05 /pmc/articles/PMC3900837/ /pubmed/20699602 http://dx.doi.org/10.2188/jea.JE20090066 Text en © 2010 Japan Epidemiological Association. http://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Study Profile
Kimura, Shinya
Sato, Toshihiko
Ikeda, Shunya
Noda, Mitsuhiko
Nakayama, Takeo
Development of a Database of Health Insurance Claims: Standardization of Disease Classifications and Anonymous Record Linkage
title Development of a Database of Health Insurance Claims: Standardization of Disease Classifications and Anonymous Record Linkage
title_full Development of a Database of Health Insurance Claims: Standardization of Disease Classifications and Anonymous Record Linkage
title_fullStr Development of a Database of Health Insurance Claims: Standardization of Disease Classifications and Anonymous Record Linkage
title_full_unstemmed Development of a Database of Health Insurance Claims: Standardization of Disease Classifications and Anonymous Record Linkage
title_short Development of a Database of Health Insurance Claims: Standardization of Disease Classifications and Anonymous Record Linkage
title_sort development of a database of health insurance claims: standardization of disease classifications and anonymous record linkage
topic Study Profile
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3900837/
https://www.ncbi.nlm.nih.gov/pubmed/20699602
http://dx.doi.org/10.2188/jea.JE20090066
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