Literature DB >> 25308525

Protecting the privacy of individual general practice patient electronic records for geospatial epidemiology research.

Soumya Mazumdar1, Paul Konings, Michael Hewett, Nasser Bagheri, Ian McRae, Peter Del Fante.   

Abstract

BACKGROUND: General practitioner (GP) practices in Australia are increasingly storing patient information in electronic databases. These practice databases can be accessed by clinical audit software to generate reports that inform clinical or population health decision making and public health surveillance. Many audit software applications also have the capacity to generate de-identified patient unit record data. However, the de-identified nature of the extracted data means that these records often lack geographic information. Without spatial references, it is impossible to build maps reflecting the spatial distribution of patients with particular conditions and needs. Links to socioeconomic, demographic, environmental or other geographically based information are also not possible. In some cases, relatively coarse geographies such as postcode are available, but these are of limited use and researchers cannot undertake precision spatial analyses such as calculating travel times.
METHODS: We describe a method that allows researchers to implement meaningful mapping and spatial epidemiological analyses of practice level patient data while preserving privacy.
RESULTS: This solution has been piloted in a diabetes risk research project in the patient population of a practice in Adelaide. CONCLUSIONS AND IMPLICATIONS: The method offers researchers a powerful means of analysing geographic clinic data in a privacy-protected manner.
© 2014 Public Health Association of Australia.

Entities:  

Keywords:  Australia; Geographical Information Systems (GIS); confidentiality; de-identified data; general practice (GP) data collection; geospatial; privacy

Mesh:

Year:  2014        PMID: 25308525     DOI: 10.1111/1753-6405.12262

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


  6 in total

1.  Development of the Australian neighborhood social fragmentation index and its association with spatial variation in depression across communities.

Authors:  Nasser Bagheri; Philip J Batterham; Luis Salvador-Carulla; Yingxi Chen; Andrew Page; Alison L Calear; Peter Congdon
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2019-04-15       Impact factor: 4.328

2.  Community cardiovascular disease risk from cross-sectional general practice clinical data: a spatial analysis.

Authors:  Nasser Bagheri; Bridget Gilmour; Ian McRae; Paul Konings; Paresh Dawda; Peter Del Fante; Chris van Weel
Journal:  Prev Chronic Dis       Date:  2015-02-26       Impact factor: 2.830

3.  Is Walk Score associated with hospital admissions from chronic diseases? Evidence from a cross-sectional study in a high socioeconomic status Australian city-state.

Authors:  Soumya Mazumdar; Vincent Learnihan; Thomas Cochrane; Hai Phung; Bridget O'Connor; Rachel Davey
Journal:  BMJ Open       Date:  2016-12-08       Impact factor: 2.692

4.  Accuracy of two geocoding methods for geographic information system-based exposure assessment in epidemiological studies.

Authors:  Elodie Faure; Aurélie M N Danjou; Françoise Clavel-Chapelon; Marie-Christine Boutron-Ruault; Laure Dossus; Béatrice Fervers
Journal:  Environ Health       Date:  2017-02-24       Impact factor: 5.984

Review 5.  Factors influencing the development of primary care data collection projects from electronic health records: a systematic review of the literature.

Authors:  Marie-Line Gentil; Marc Cuggia; Laure Fiquet; Camille Hagenbourger; Thomas Le Berre; Agnès Banâtre; Eric Renault; Guillaume Bouzille; Anthony Chapron
Journal:  BMC Med Inform Decis Mak       Date:  2017-09-25       Impact factor: 2.796

Review 6.  Spatial Modelling Tools to Integrate Public Health and Environmental Science, Illustrated with Infectious Cryptosporidiosis.

Authors:  Aparna Lal
Journal:  Int J Environ Res Public Health       Date:  2016-02-02       Impact factor: 3.390

  6 in total

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