ArticlePloS one2018
Prescriptive variability of drugs by general practitioners.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- A Multi-Indicator Concentration Index for Primary-Care Reimbursement Analytics: Evidence from the Albanian Health-Insurance System.Healthcare (Basel, Switzerland) · 2026Article
- Antibiotic prescribing and antimicrobial resistance awareness among medical students in Lebanon using novel assessment scales.Scientific reports · 2025Article
- Identifying Patterns of Clinical Interest in Clinicians' Treatment Preferences: Hypothesis-free Data Science Approach to Prioritizing Prescribing Outliers for Clinical Review.JMIR medical informatics · 2022Article
- Article
- Treatment of Sarcoidosis in US Rheumatology Practices: Data From the American College of Rheumatology's Rheumatology Informatics System for Effectiveness (RISE) Registry.Arthritis care & research · 2022Observational
- Trends, Variation, and Factors Influencing Antibiotic Prescribing: A Longitudinal Study in Primary Care Using a Multilevel Modelling Approach.Antibiotics (Basel, Switzerland) · 2021Article
- Observational
- Discovering and comparing types of general practitioner practices using geolocational features and prescribing behaviours by means of K-means clustering.Scientific reports · 2021Article
- Epidemiology and associated factors of polypharmacy in older patients in primary care: a northern Italian cross-sectional study.BMC geriatrics · 2021Article
- GP prescribing in Northern Ireland by deprivation index: retrospective analysis.Family medicine and community health · 2020Article
- Primary care use of laboratory tests in Northern Ireland's Western Health and Social Care Trust: a cross-sectional study.BMJ open · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prescription drug spending is growing faster than any other sector of healthcare. However, very little is known about patterns of prescribing and cost of prescribing between general practices. In this study, we examined variation in prescription rates and prescription costs through time for 55 GP surgeries in Northern Ireland Western Health and Social Care Trust. Temporal changes in variability of prescribing rates and costs were assessed using the Mann-Kendall test. Outlier practices contributing to between practice variation in prescribing rates were identified with the interquartile range outlier detection method. The relationship between rates and cost of prescribing was explored with Spearman's statistics. The differences in variability and mean number of prescribing rates associated with the practice setting and socioeconomic deprivation were tested using t-test and F-test respectively. The largest between-practice difference in prescribing rates was observed for Apr-Jun 2015, with the number of prescriptions ranging from 3.34 to 8.36 per patient. We showed that practices with outlier prescribing rates greatly contributed to between-practice variability. The largest difference in prescribing costs was reported for Apr-Jun 2014, with the prescription cost per patient ranging from £26.4 to £64.5. In addition, the temporal changes in variability of prescribing rates and costs were shown to undergo an upward trend. We demonstrated that practice setting and socio-economic deprivation accounted for some of the between-practice variation in prescribing. Rural practices had higher between practice variability than urban practices at all time points. Practices situated in more deprived areas had higher prescribing rates but lower variability than those located in less deprived areas. Further analysis is recommended to assess if variation in prescribing can be explained by demographic characteristics of patient population and practice features. Identification of other factors contributing to prescribing variability can help us better address potential inappropriateness of prescribing.
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