Understanding Anomalies in Primary Care Prescribing Data
Research type
Research Study
Full title
Understanding anomalies in primary care prescribing data
IRAS ID
234934
Contact name
Stephanie Hall
Contact email
Sponsor organisation
University of Aberdeen
Duration of Study in the UK
0 years, 2 months, 16 days
Research summary
Routinely collected, electronic prescribing and dispensing data are increasingly used in pharmacoepidemiological studies. These data provide an alternative platform to measure medication-related outcomes, such as adherence and polypharmacy. Previous University of Aberdeen research has identified anomalous patterns in primary care prescribing data when exploring medication adherence in patients with diabetes mellitus. Examples of these anomalous patterns included:
i. Duplicate prescriptions recorded on the same or consecutive dates;
ii. Different drugs from the same class prescribed to the same patient during the same period;
iii. A prescribed quantity greater than what would be expected for that period under the given dosing instructions.Similar anomalies have also been observed in dispensing data. These anomalous patterns limit the utilisation of electronic data for pharmacoepidemiology and other medication-related research. Although research using electronic prescribing and dispensing data exists, to our knowledge, no studies report anomalous patterns in these data as well as the reasons why such patterns arise or the methodological approaches to handling the anomalies. In this research project, we aim to explore these issues and inform the development of a protocol for classifying and interpreting these anomalies so that the data can be used with confidence in research.
REC name
London - West London & GTAC Research Ethics Committee
REC reference
18/LO/0187
Date of REC Opinion
16 Feb 2018
REC opinion
Further Information Favourable Opinion