title: Developing prevalence-based prescribing units for analysing variations in general practitioner prescribing: a case study using statins.
abstract: OBJECTIVE
  To develop regionally specific prevalence-, age- and sex-standardized prescribing units (PASS-PUs) and to relate these to statin prescribing.
  
  
  METHODS
  Cross-sectional.
  
  
  METHODS
  Ninety-four general practitioner (GP) practices within one health authority in the north-west of England.
  
  
  METHODS
  Comparisons between specific therapeutic group age-sex-related prescribing units (STAR-PUs) and PASS-PUs for statin prescribing.
  
  
  RESULTS
  STAR-PUs and PASS-PUs were calculated for all GP practices and there was a high degree of correlation (Spearman's rank coefficient 0.88; P < 0.001). Using actual prescribing data for statins for a 12-month period, a statistically significant correlation was found between net ingredient cost per patient and STAR-PUs per patient (Spearman's rank coefficient 0.36; P < 0.01). However, the correlation between average daily quantities per patient and PASS-PUs per patient was not statistically significant. A scatter plot revealed a pattern whereby GP practices with high proportions of patients aged over 75 years exhibited low statin prescribing in relation to the expected prevalence of treated coronary heart disease (CHD) in their patient population.
  
  
  CONCLUSIONS
  Low weightings for patients aged over 75 years in calculating STAR-PUs lead to a much lower number of prescribing units within GP practice populations when compared with PASS-PUs. Current statin prescribing across GP practices in this study correlates with national prescribing cost patterns (as measured by STAR-PUs) although not with expected prevalence of treated CHD (as measured by PASS-PUs). PASS-PUs reflect prevalence of treated CHD and may therefore be used to monitor and predict GP prescribing arising from the implementation of the National Service Framework targets for CHD. In addition, PASS-PUs maybe derived for a wide range of therapeutic areas.
authors.affiliation: School of Social Sciences and Law, Sheffield Hallam University, Sheffield, UK. p.r.ward@shu.ac.uk
authors.forename: P R
authors.initials: PR
authors.lastname: Ward
authors.forename: P R
authors.initials: PR
authors.lastname: Noyce
authors.forename: A S
authors.initials: AS
authors.lastname: St Leger
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D003327:Coronary Disease / Q000188:drug therapy; D003430:Cross-Sectional Studies; D011307:Drug Prescriptions / Q000706:statistics & numerical data; D004363:Drug Utilization; D004739:England; D005260:Female; D006801:Humans; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors / Q000191:economics / Q000627:therapeutic use*; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D012737:Sex Factors
chemical_list: D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors