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...
| Publicado en: | BioMed Research International Vol. 2015; pp. 1 - 6 |
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| Autores principales: | , , , , , |
| Formato: | Journal Article |
| Publicado: |
Wiley-Blackwell
9/6/2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=109571554&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109571554 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 9/6/2015 vid: 2015 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 109571554 109571554 NLM26425565 10.1155/2015/973857 NLM26425565 PMC4575725 109571554 ppf: 1 ppct: 5 formats: fmt: @attributes: type: P tig: atl: Following Up Crack Users after Hospital Discharge Using Record Linkage Methodology: An Alternative to Find Hidden Populations. aug: au: Gonçalves, Veralice Maria Pedroso, Rosemeri Santos, Antônio Marcos dos Diemen, Lisia Von Pechansky, Flavio Dos Santos, Antônio Marcos affil: Center for Drug and Alcohol Research, Clinics Hospital of Porto Alegre, Federal University of Rio Grande do Sul, 400 Professor Alvaro Alvim Street, 90420-020 Porto Alegre, RS, Brazil sug: ab: 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. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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