Validation of a method for identifying nursing home admissions using administrative claims
<p>Abstract</p> <p>Background</p> <p>Currently there is no standard algorithm to identify whether a subject is residing in a nursing home from administrative claims. Our objective was to develop and validate an algorithm that identifies nursing home admissions at the re...
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doaj-d6fea149fd074300836a5dd77a6097762020-11-25T01:32:30ZengBMCBMC Health Services Research1472-69632007-12-017120210.1186/1472-6963-7-202Validation of a method for identifying nursing home admissions using administrative claimsHsu Van DorenSato MasayoZuckerman Ilene HHernandez Jose J<p>Abstract</p> <p>Background</p> <p>Currently there is no standard algorithm to identify whether a subject is residing in a nursing home from administrative claims. Our objective was to develop and validate an algorithm that identifies nursing home admissions at the resident-month level using the MarketScan Medicare Supplemental and Coordination of Benefit (COB) database.</p> <p>Methods</p> <p>The computer algorithms for identifying nursing home admissions were created by using provider type, place of service, and procedure codes from the 2000 – 2002 MarketScan Medicare COB database. After the algorithms were reviewed and refined, they were compared with a detailed claims review by an expert reviewer. A random sample of 150 subjects from the claims was selected and used for the validity analysis of the algorithms. Contingency table analysis, comparison of mean differences, correlations, and t-test analyses were performed. Percentage agreement, sensitivity, specificity, and Kappa statistics were analyzed.</p> <p>Results</p> <p>The computer algorithm showed strong agreement with the expert review (99.9%) for identification of the first month of nursing home residence, with high sensitivity (96.7%), specificity (100%) and a Kappa statistic of 0.97. Weighted Pearson correlation coefficient between the algorithm and the expert review was 0.97 (<it>p </it>< 0.0001).</p> <p>Conclusion</p> <p>A reliable algorithm indicating evidence of nursing home admission was developed and validated from administrative claims data. Our algorithm can be a useful tool to identify patient transitions from and to nursing homes, as well as to screen and monitor for factors associated with nursing home admission and nursing home discharge.</p> http://www.biomedcentral.com/1472-6963/7/202 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hsu Van Doren Sato Masayo Zuckerman Ilene H Hernandez Jose J |
spellingShingle |
Hsu Van Doren Sato Masayo Zuckerman Ilene H Hernandez Jose J Validation of a method for identifying nursing home admissions using administrative claims BMC Health Services Research |
author_facet |
Hsu Van Doren Sato Masayo Zuckerman Ilene H Hernandez Jose J |
author_sort |
Hsu Van Doren |
title |
Validation of a method for identifying nursing home admissions using administrative claims |
title_short |
Validation of a method for identifying nursing home admissions using administrative claims |
title_full |
Validation of a method for identifying nursing home admissions using administrative claims |
title_fullStr |
Validation of a method for identifying nursing home admissions using administrative claims |
title_full_unstemmed |
Validation of a method for identifying nursing home admissions using administrative claims |
title_sort |
validation of a method for identifying nursing home admissions using administrative claims |
publisher |
BMC |
series |
BMC Health Services Research |
issn |
1472-6963 |
publishDate |
2007-12-01 |
description |
<p>Abstract</p> <p>Background</p> <p>Currently there is no standard algorithm to identify whether a subject is residing in a nursing home from administrative claims. Our objective was to develop and validate an algorithm that identifies nursing home admissions at the resident-month level using the MarketScan Medicare Supplemental and Coordination of Benefit (COB) database.</p> <p>Methods</p> <p>The computer algorithms for identifying nursing home admissions were created by using provider type, place of service, and procedure codes from the 2000 – 2002 MarketScan Medicare COB database. After the algorithms were reviewed and refined, they were compared with a detailed claims review by an expert reviewer. A random sample of 150 subjects from the claims was selected and used for the validity analysis of the algorithms. Contingency table analysis, comparison of mean differences, correlations, and t-test analyses were performed. Percentage agreement, sensitivity, specificity, and Kappa statistics were analyzed.</p> <p>Results</p> <p>The computer algorithm showed strong agreement with the expert review (99.9%) for identification of the first month of nursing home residence, with high sensitivity (96.7%), specificity (100%) and a Kappa statistic of 0.97. Weighted Pearson correlation coefficient between the algorithm and the expert review was 0.97 (<it>p </it>< 0.0001).</p> <p>Conclusion</p> <p>A reliable algorithm indicating evidence of nursing home admission was developed and validated from administrative claims data. Our algorithm can be a useful tool to identify patient transitions from and to nursing homes, as well as to screen and monitor for factors associated with nursing home admission and nursing home discharge.</p> |
url |
http://www.biomedcentral.com/1472-6963/7/202 |
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