Literature DB >> 21973256

Development and validation of reporting guidelines for studies involving data linkage.

Megan A Bohensky1, Damien Jolley, Vijaya Sundararajan, Sue Evans, Joseph Ibrahim, Caroline Brand.   

Abstract

OBJECTIVE: Data or record linkage is commonly used to combine existing data sets for the purpose of creating more comprehensive information to conduct research. Linked data may create additional concerns about error if cases are not linked accurately. It is important that factors compromising the quality of studies using linked data be reported in a clear and consistent way that allows readers and researchers to accurately appraise the results. The aim of this study was to develop and test reporting guidelines for evaluating the methodological quality of studies using linked data.
METHOD: The development process included a literature review, a Delphi process and a validation process. Participants in the process were all Australian and included biostatisticians, epidemiologists, registry administrators, academic clinicians and a peer-reviewed journal editor.
RESULTS: The final guidelines included four domains and 14 reporting items. These included: data sources (six items), research selected variables (four items), linkage technology and data analysis (three items), and ethics, privacy and data security (one item).
CONCLUSION: This study is the first to develop guidelines for appraising the quality of reported data linkage studies. IMPLICATIONS: These guidelines will assist authors to report their results in a consistent, high-quality manner. They will also assist readers to interpret the quality of results derived from data linkage studies.
© 2011 The Authors. ANZJPH © 2011 Public Health Association of Australia.

Entities:  

Mesh:

Year:  2011        PMID: 21973256     DOI: 10.1111/j.1753-6405.2011.00741.x

Source DB:  PubMed          Journal:  Aust N Z J Public Health        ISSN: 1326-0200            Impact factor:   2.939


  14 in total

1.  Methodological challenges in using routinely collected health data to investigate long-term effects of medication use during pregnancy.

Authors:  Luke E Grzeskowiak; Andrew L Gilbert; Janna L Morrison
Journal:  Ther Adv Drug Saf       Date:  2013-02

2.  Using probabilistic record linkage and propensity-score matching to identify a community-based comparison population.

Authors:  Margaret L Holland; Rose M Taylor; Eileen Condon; Gabrielle R Rinne; Sarah Bleicher; Margaret L Seldin; Lois S Sadler; Connie Li
Journal:  Res Nurs Health       Date:  2022-04-06       Impact factor: 2.238

Review 3.  Pharmacovigilance in children: detecting adverse drug reactions in routine electronic healthcare records. A systematic review.

Authors:  Corri Black; Nara Tagiyeva-Milne; Peter Helms; Dorothy Moir
Journal:  Br J Clin Pharmacol       Date:  2015-05-28       Impact factor: 4.335

4.  Birthplace in New South Wales, Australia: an analysis of perinatal outcomes using routinely collected data.

Authors:  Caroline S E Homer; Charlene Thornton; Vanessa L Scarf; David A Ellwood; Jeremy J N Oats; Maralyn J Foureur; David Sibbritt; Helen L McLachlan; Della A Forster; Hannah G Dahlen
Journal:  BMC Pregnancy Childbirth       Date:  2014-06-14       Impact factor: 3.007

5.  Validation of multisource electronic health record data: an application to blood transfusion data.

Authors:  Loan R van Hoeven; Martine C de Bruijne; Peter F Kemper; Maria M W Koopman; Jan M M Rondeel; Anja Leyte; Hendrik Koffijberg; Mart P Janssen; Kit C B Roes
Journal:  BMC Med Inform Decis Mak       Date:  2017-07-14       Impact factor: 2.796

6.  GUILD: GUidance for Information about Linking Data sets.

Authors:  Ruth Gilbert; Rosemary Lafferty; Gareth Hagger-Johnson; Katie Harron; Li-Chun Zhang; Peter Smith; Chris Dibben; Harvey Goldstein
Journal:  J Public Health (Oxf)       Date:  2018-03-01       Impact factor: 2.341

7.  Protocol for development of the guideline for reporting evidence based practice educational interventions and teaching (GREET) statement.

Authors:  Anna C Phillips; Lucy K Lewis; Maureen P McEvoy; James Galipeau; Paul Glasziou; Marilyn Hammick; David Moher; Julie Tilson; Marie T Williams
Journal:  BMC Med Educ       Date:  2013-01-25       Impact factor: 2.463

8.  Investigating linkage rates among probabilistically linked birth and hospitalization records.

Authors:  Jason P Bentley; Jane B Ford; Lee K Taylor; Katie A Irvine; Christine L Roberts
Journal:  BMC Med Res Methodol       Date:  2012-09-25       Impact factor: 4.615

9.  Impact of a population-based HPV vaccination program on cervical abnormalities: a data linkage study.

Authors:  Dorota M Gertig; Julia M L Brotherton; Alison C Budd; Kelly Drennan; Genevieve Chappell; A Marion Saville
Journal:  BMC Med       Date:  2013-10-22       Impact factor: 8.775

10.  Evaluating bias due to data linkage error in electronic healthcare records.

Authors:  Katie Harron; Angie Wade; Ruth Gilbert; Berit Muller-Pebody; Harvey Goldstein
Journal:  BMC Med Res Methodol       Date:  2014-03-05       Impact factor: 4.615

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