title: Cost effectiveness of a pharmacist-led information technology intervention for reducing rates of clinically important errors in medicines management in general practices (PINCER).
abstract: OBJECTIVE
  We recently showed that a pharmacist-led information technology-based intervention (PINCER) was significantly more effective in reducing medication errors in general practices than providing simple feedback on errors, with cost per error avoided at £79 (US$131). We aimed to estimate cost effectiveness of the PINCER intervention by combining effectiveness in error reduction and intervention costs with the effect of the individual errors on patient outcomes and healthcare costs, to estimate the effect on costs and QALYs.
  
  
  METHODS
  We developed Markov models for each of six medication errors targeted by PINCER. Clinical event probability, treatment pathway, resource use and costs were extracted from literature and costing tariffs. A composite probabilistic model combined patient-level error models with practice-level error rates and intervention costs from the trial. Cost per extra QALY and cost-effectiveness acceptability curves were generated from the perspective of NHS England, with a 5-year time horizon.
  
  
  RESULTS
  The PINCER intervention generated £2,679 less cost and 0.81 more QALYs per practice [incremental cost-effectiveness ratio (ICER): -£3,037 per QALY] in the deterministic analysis. In the probabilistic analysis, PINCER generated 0.001 extra QALYs per practice compared with simple feedback, at £4.20 less per practice. Despite this extremely small set of differences in costs and outcomes, PINCER dominated simple feedback with a mean ICER of -£3,936 (standard error £2,970). At a ceiling 'willingness-to-pay' of £20,000/QALY, PINCER reaches 59 % probability of being cost effective.
  
  
  CONCLUSIONS
  PINCER produced marginal health gain at slightly reduced overall cost. Results are uncertain due to the poor quality of data to inform the effect of avoiding errors.
authors.affiliation: Division for Social Research in Medicines and Health, The School of Pharmacy, University of Nottingham, University Park, East Drive, Nottingham, NG7 2RD, UK, rachel.elliott@nottingham.ac.uk.
authors.forename: Rachel A
authors.initials: RA
authors.lastname: Elliott
authors.forename: Koen D
authors.initials: KD
authors.lastname: Putman
authors.forename: Matthew
authors.initials: M
authors.lastname: Franklin
authors.forename: Lieven
authors.initials: L
authors.lastname: Annemans
authors.forename: Nick
authors.initials: N
authors.lastname: Verhaeghe
authors.forename: Martin
authors.initials: M
authors.lastname: Eden
authors.forename: Jasdeep
authors.initials: J
authors.lastname: Hayre
authors.forename: Sarah
authors.initials: S
authors.lastname: Rodgers
authors.forename: Aziz
authors.initials: A
authors.lastname: Sheikh
authors.forename: Anthony J
authors.initials: AJ
authors.lastname: Avery
mesh_terms: D003362:Cost-Benefit Analysis; D004739:England; D058006:General Practice; D006801:Humans; D008390:Markov Chains; D008490:Medical Informatics; D008508:Medication Errors / Q000191:economics* / Q000517:prevention & control*; D018803:Models, Economic; D015233:Models, Statistical; D009313:National Health Programs / Q000191:economics; D010595:Pharmacists; D019057:Quality-Adjusted Life Years