This paper is in the following e-collection/theme issue:

Secondary Use of Clinical Data for Research and Surveillance (366) Data Science (270) Electronic Health Records (1053) Decision Support for Health Professionals (1185)

Published on in Vol 10, No 12 (2022): December

This is a member publication of University of Oxford (Jisc)

Preprints (earlier versions) of this paper are available at https://www.medrxiv.org/content/10.1101/2022.03.22.22272504v1, first published .
Identifying Patterns of Clinical Interest in Clinicians’ Treatment Preferences: Hypothesis-free Data Science Approach to Prioritizing Prescribing Outliers for Clinical Review

Identifying Patterns of Clinical Interest in Clinicians’ Treatment Preferences: Hypothesis-free Data Science Approach to Prioritizing Prescribing Outliers for Clinical Review

Identifying Patterns of Clinical Interest in Clinicians’ Treatment Preferences: Hypothesis-free Data Science Approach to Prioritizing Prescribing Outliers for Clinical Review

Authors of this article:

Brian MacKenna1 Author Orcid Image ;   Helen J Curtis1 Author Orcid Image ;   Lisa E M Hopcroft1 Author Orcid Image ;   Alex J Walker1 Author Orcid Image ;   Richard Croker1 Author Orcid Image ;   Orla Macdonald1 Author Orcid Image ;   Stephen J W Evans2 Author Orcid Image ;   Peter Inglesby1 Author Orcid Image ;   David Evans1 Author Orcid Image ;   Jessica Morley1 Author Orcid Image ;   Sebastian C J Bacon1 Author Orcid Image ;   Ben Goldacre1 Author Orcid Image
Article Authors Cited by (1) Tweetations (14) Metrics

Journals

  1. Hopcroft L, Massey J, Curtis H, Mackenna B, Croker R, Brown A, O'Dwyer T, Macdonald O, Evans D, Inglesby P, Bacon S, Goldacre B, Walker A. Data-Driven Identification of Unusual Prescribing Behavior: Analysis and Use of an Interactive Data Tool Using 6 Months of Primary Care Data From 6500 Practices in England. JMIR Medical Informatics 2023;11:e44237 View