Incorporating patient generated health data into pharmacoepidemiological research.

big data data privacy digital epidemiology mobile apps mobile health patient generated health data patient reported outcomes pharmacoepidemiology real world data real world evidence social media

Journal

Pharmacoepidemiology and drug safety
ISSN: 1099-1557
Titre abrégé: Pharmacoepidemiol Drug Saf
Pays: England
ID NLM: 9208369

Informations de publication

Date de publication:
12 2020
Historique:
received: 12 03 2020
revised: 17 09 2020
accepted: 31 10 2020
pubmed: 5 11 2020
medline: 25 11 2021
entrez: 4 11 2020
Statut: ppublish

Résumé

Epidemiology and pharmacoepidemiology frequently employ Real-World Data (RWD) from healthcare teams to inform research. These data sources usually include signs, symptoms, tests, and treatments, but may lack important information such as the patient's diet or adherence or quality of life. By harnessing digital tools a new fount of evidence, Patient (or Citizen/Person) Generated Health Data (PGHD), is becoming more readily available. This review focusses on the advantages and considerations in using PGHD for pharmacoepidemiological research. New and corroborative types of data can be collected directly from patients using digital devices, both passively and actively. Practical issues such as patient engagement, data linking, validation, and analysis are among important considerations in the use of PGHD. In our ever increasingly patient-centric world, PGHD incorporated into more traditional Real-Word data sources offers innovative opportunities to expand our understanding of the complex factors involved in health and the safety and effectiveness of disease treatments. Pharmacoepidemiologists have a unique role in realizing the potential of PGHD by ensuring that robust methodology, governance, and analytical techniques underpin its use to generate meaningful research results.

Identifiants

pubmed: 33146896
doi: 10.1002/pds.5169
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

1540-1549

Informations de copyright

© 2020 John Wiley & Sons Ltd.

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Auteurs

Alison Bourke (A)

Real World Solutions, IQVIA, London, UK.

William G Dixon (WG)

Arthritis Research UK Centre for Epidemiology, The University of Manchester, Manchester, UK.

Andrew Roddam (A)

Data & Computational Sciences, GSK, London, UK.

Kueiyu Joshua Lin (KJ)

Brigham and Women's & Department of Medicine, Boston, Massachusetts, USA.

Gillian C Hall (GC)

Gillian Hall Epidemiology Ltd, London, UK.

Jeffrey R Curtis (JR)

Division of Clinical Immunology & Rheumatology, The University of Birmingham, Birmingham, Alabama, USA.

Sabine N van der Veer (SN)

Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.

Montse Soriano-Gabarró (M)

Bayer AG, Berlin, Germany.

Juliane K Mills (JK)

PRA Health Sciences, Raleigh, North Carolina, USA.

Jacqueline M Major (JM)

Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.

Thomas Verstraeten (T)

P95 Pharmacovigilance and Epidemiology, Leuven, Belgium.

Matthew J Francis (MJ)

The Procter & Gamble Company, Cincinnati, Ohio, USA.

Dorothee B Bartels (DB)

UCB Pharma, Anderlecht, Belgium.

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