title: Bad apples or spoiled barrels? Multilevel modelling analysis of variation in high-risk prescribing in Scotland between general practitioners and between the practices they work in.
abstract: OBJECTIVE
  Primary care high-risk prescribing causes significant harm, but it is unclear if it is largely driven by individuals (a 'bad apple' problem) or by practices having higher or lower risk prescribing cultures (a 'spoiled barrel' problem). The study aimed to examine the extent of variation in high-risk prescribing between individual prescribers and between the practices they work in.
  
  
  METHODS
  Multilevel logistic regression modelling of routine cross-sectional data from 38 Scottish general practices for 181,010 encounters between 398 general practitioners (GPs) and 26,539 patients particularly vulnerable to adverse drug events (ADEs) of non-steroidal anti-inflammatory drugs (NSAIDs) due to age, comorbidity or co-prescribing.
  
  
  METHODS
  Initiation of a new NSAID prescription in an encounter between GPs and eligible patients.
  
  
  RESULTS
  A new high-risk NSAID was initiated in 1953 encounters (1.1% of encounters, 7.4% of patients). Older patients, those with more vulnerabilities to NSAID ADEs and those with polypharmacy were less likely to have a high-risk NSAID initiated, consistent with GPs generally recognising the risk of NSAIDs in eligible patients. Male GPs were more likely to initiate a high-risk NSAID than female GPs (OR 1.73, 95% CI 1.39 to 2.16). After accounting for patient characteristics, 4.2% (95% CI 2.1 to 8.3) of the variation in high-risk NSAID prescribing was attributable to variation between practices, and 14.2% (95% CI 11.4 to 17.3) to variation between GPs. Three practices had statistically higher than average high-risk prescribing, but only 15.7% of GPs with higher than average high-risk prescribing and 18.5% of patients receiving such a prescription were in these practices.
  
  
  CONCLUSIONS
  There was much more variation in high-risk prescribing between GPs than between practices, and only targeting practices with higher than average rates will miss most high-risk NSAID prescribing. Primary care prescribing safety improvement should ideally target all practices, but encourage practices to consider and act on variation between prescribers in the practice.
authors.affiliation: Quality, Safety and Informatics Research Group, Population Health Sciences Division, Medical Research Institute, University of Dundee, Mackenzie Building, Kirsty Semple Way, Dundee, UK.
authors.forename: Bruce
authors.initials: B
authors.lastname: Guthrie
authors.affiliation: Dundee Epidemiology and Biostatistics Unit, Population Health Sciences Division, Medical Research Institute, University of Dundee, Mackenzie Building, Kirsty Semple Way, Dundee, UK.
authors.forename: Peter T
authors.initials: PT
authors.lastname: Donnan
authors.affiliation: University of Dundee Medical School, Dundee, UK.
authors.forename: Douglas J
authors.initials: DJ
authors.lastname: Murphy
authors.affiliation: Faculty of Medicine, Department of Public Health, University of Botswana, Gaborone, Botswana.
authors.forename: Boikanyo
authors.initials: B
authors.lastname: Makubate
authors.affiliation: NHS Tayside Medicines Governance Unit, Mackenzie Building, Kirsty Semple Way, Dundee, UK.
authors.forename: Tobias
authors.initials: T
authors.lastname: Dreischulte
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000894:Anti-Inflammatory Agents, Non-Steroidal / Q000009:adverse effects*; D003430:Cross-Sectional Studies; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology*; D005260:Female; D058006:General Practice; D058005:General Practitioners; D006801:Humans; D057970:Inappropriate Prescribing / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D055361:Multilevel Analysis; D017063:Outcome Assessment, Health Care; D019338:Polypharmacy; D010818:Practice Patterns, Physicians' / Q000592:standards*; D011320:Primary Health Care; D012606:Scotland
chemical_list: D000894:Anti-Inflammatory Agents, Non-Steroidal
keywords: PRIMARY CARE; STATISTICS & RESEARCH METHODS; THERAPEUTICS