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Following Up Crack Users after Hospital Discharge Using Record Linkage Methodology: An Alternative to Find Hidden Populations
This paper presents the probabilistic record linkage (PRL) methodology as an alternative way to find or follow up hard-to-reach population as crack users. PRL was based on secondary data from public health information systems and the strategy used from standardization; phonetic encoding and the roun...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4575725/ https://www.ncbi.nlm.nih.gov/pubmed/26425565 http://dx.doi.org/10.1155/2015/973857 |
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author | Gonçalves, Veralice Maria Pedroso, Rosemeri dos Santos, Antônio Marcos Diemen, Lisia Von Pechansky, Flavio |
author_facet | Gonçalves, Veralice Maria Pedroso, Rosemeri dos Santos, Antônio Marcos Diemen, Lisia Von Pechansky, Flavio |
author_sort | Gonçalves, Veralice Maria |
collection | PubMed |
description | This paper presents the probabilistic record linkage (PRL) methodology as an alternative way to find or follow up hard-to-reach population as crack users. PRL was based on secondary data from public health information systems and the strategy used from standardization; phonetic encoding and the rounds of matching data were described. A total of 293 patient records from medical database and two administrative datasets obtained from Ministry of Health Information Systems were used. Patient information from the medical database was the identifiers to the administrative datasets containing data on outpatient treatment and hospital admissions. 40% of patient records were found in the hospital database and 12% were found in the outpatient database; 95% of the patients were hospitalized up to 5 times, and only 10 out of them had outpatient information. The record linkage methodology by linking government databases may help to address research questions about the path of patients in the care network without spending time and financial resources with primary data collection. |
format | Online Article Text |
id | pubmed-4575725 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-45757252015-09-30 Following Up Crack Users after Hospital Discharge Using Record Linkage Methodology: An Alternative to Find Hidden Populations Gonçalves, Veralice Maria Pedroso, Rosemeri dos Santos, Antônio Marcos Diemen, Lisia Von Pechansky, Flavio Biomed Res Int Research Article This paper presents the probabilistic record linkage (PRL) methodology as an alternative way to find or follow up hard-to-reach population as crack users. PRL was based on secondary data from public health information systems and the strategy used from standardization; phonetic encoding and the rounds of matching data were described. A total of 293 patient records from medical database and two administrative datasets obtained from Ministry of Health Information Systems were used. Patient information from the medical database was the identifiers to the administrative datasets containing data on outpatient treatment and hospital admissions. 40% of patient records were found in the hospital database and 12% were found in the outpatient database; 95% of the patients were hospitalized up to 5 times, and only 10 out of them had outpatient information. The record linkage methodology by linking government databases may help to address research questions about the path of patients in the care network without spending time and financial resources with primary data collection. Hindawi Publishing Corporation 2015 2015-09-06 /pmc/articles/PMC4575725/ /pubmed/26425565 http://dx.doi.org/10.1155/2015/973857 Text en Copyright © 2015 Veralice Maria Gonçalves et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Gonçalves, Veralice Maria Pedroso, Rosemeri dos Santos, Antônio Marcos Diemen, Lisia Von Pechansky, Flavio Following Up Crack Users after Hospital Discharge Using Record Linkage Methodology: An Alternative to Find Hidden Populations |
title | Following Up Crack Users after Hospital Discharge Using Record Linkage Methodology: An Alternative to Find Hidden Populations |
title_full | Following Up Crack Users after Hospital Discharge Using Record Linkage Methodology: An Alternative to Find Hidden Populations |
title_fullStr | Following Up Crack Users after Hospital Discharge Using Record Linkage Methodology: An Alternative to Find Hidden Populations |
title_full_unstemmed | Following Up Crack Users after Hospital Discharge Using Record Linkage Methodology: An Alternative to Find Hidden Populations |
title_short | Following Up Crack Users after Hospital Discharge Using Record Linkage Methodology: An Alternative to Find Hidden Populations |
title_sort | following up crack users after hospital discharge using record linkage methodology: an alternative to find hidden populations |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4575725/ https://www.ncbi.nlm.nih.gov/pubmed/26425565 http://dx.doi.org/10.1155/2015/973857 |
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