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Bayesian cohort and cross-sectional analyses of the PINCER trial: a pharmacist-led intervention to reduce medication errors in primary care.

Hemming K, Chilton PJ, Lilford RJ, Avery A, Sheikh A - PLoS ONE (2012)

Bottom Line: Medication errors are an important source of potentially preventable morbidity and mortality.However, for the other two main outcomes considered, the evidence that the intervention is able to reduce the likelihood of prescription errors is less conclusive.Depending on the clinical importance of the respective errors, careful consideration should be given before implementation, and refinement targeted at the other errors may be something to consider.

View Article: PubMed Central - PubMed

Affiliation: School of Public Health, Epidemiology and Biostatistics, University of Birmingham, Birmingham, United Kingdom. k.hemming@bham.ac.uk

ABSTRACT

Background: Medication errors are an important source of potentially preventable morbidity and mortality. The PINCER study, a cluster randomised controlled trial, is one of the world's first experimental studies aiming to reduce the risk of such medication related potential for harm in general practice. Bayesian analyses can improve the clinical interpretability of trial findings.

Methods: Experts were asked to complete a questionnaire to elicit opinions of the likely effectiveness of the intervention for the key outcomes of interest--three important primary care medication errors. These were averaged to generate collective prior distributions, which were then combined with trial data to generate bayesian posterior distributions. The trial data were analysed in two ways: firstly replicating the trial reported cohort analysis acknowledging pairing of observations, but excluding non-paired observations; and secondly as cross-sectional data, with no exclusions, but without acknowledgement of the pairing. Frequentist and bayesian analyses were compared.

Findings: Bayesian evaluations suggest that the intervention is able to reduce the likelihood of one of the medication errors by about 50 (estimated to be between 20% and 70%). However, for the other two main outcomes considered, the evidence that the intervention is able to reduce the likelihood of prescription errors is less conclusive.

Conclusions: Clinicians are interested in what trial results mean to them, as opposed to what trial results suggest for future experiments. This analysis suggests that the PINCER intervention is strongly effective in reducing the likelihood of one of the important errors; not necessarily effective in reducing the other errors. Depending on the clinical importance of the respective errors, careful consideration should be given before implementation, and refinement targeted at the other errors may be something to consider.

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Cross-sectional analysis of odds of error in control to intervention arm in the PINCER trial.The conservative and optimistic priors are elicited expert priors. CI refers to frequentist confidence interval or credible interval for Bayesian analyses.
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pone-0038306-g003: Cross-sectional analysis of odds of error in control to intervention arm in the PINCER trial.The conservative and optimistic priors are elicited expert priors. CI refers to frequentist confidence interval or credible interval for Bayesian analyses.

Mentions: Thirty-four experts were approached via email. Of these, 15 agreed to participate; a further four responded stating they would not like to participate (two because they had already seen the trial results; one forwarded to a colleague; and one who was too busy); and the remaining 15 failed to respond. Of the 15 responses obtained, 11 responded directly by electronic completion of the form and four responses were obtained by telephone interview. One expert, whilst providing opinions for the first two outcomes, did not feel able to provide an opinion on the third outcome. Opinions provided by each of the experts are presented in Figure 1. The conservative interpretations of the elicited opinions are much less precise than those of the optimistic interpretation. Pooling over experts the conservative and optimistic prior distributions are shown in Table 1. Results are presented from the frequentist analysis for the three outcomes and for both the cohort (Figure 2) and cross-sectional analyses (Figure 3).


Bayesian cohort and cross-sectional analyses of the PINCER trial: a pharmacist-led intervention to reduce medication errors in primary care.

Hemming K, Chilton PJ, Lilford RJ, Avery A, Sheikh A - PLoS ONE (2012)

Cross-sectional analysis of odds of error in control to intervention arm in the PINCER trial.The conservative and optimistic priors are elicited expert priors. CI refers to frequentist confidence interval or credible interval for Bayesian analyses.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3369915&req=5

pone-0038306-g003: Cross-sectional analysis of odds of error in control to intervention arm in the PINCER trial.The conservative and optimistic priors are elicited expert priors. CI refers to frequentist confidence interval or credible interval for Bayesian analyses.
Mentions: Thirty-four experts were approached via email. Of these, 15 agreed to participate; a further four responded stating they would not like to participate (two because they had already seen the trial results; one forwarded to a colleague; and one who was too busy); and the remaining 15 failed to respond. Of the 15 responses obtained, 11 responded directly by electronic completion of the form and four responses were obtained by telephone interview. One expert, whilst providing opinions for the first two outcomes, did not feel able to provide an opinion on the third outcome. Opinions provided by each of the experts are presented in Figure 1. The conservative interpretations of the elicited opinions are much less precise than those of the optimistic interpretation. Pooling over experts the conservative and optimistic prior distributions are shown in Table 1. Results are presented from the frequentist analysis for the three outcomes and for both the cohort (Figure 2) and cross-sectional analyses (Figure 3).

Bottom Line: Medication errors are an important source of potentially preventable morbidity and mortality.However, for the other two main outcomes considered, the evidence that the intervention is able to reduce the likelihood of prescription errors is less conclusive.Depending on the clinical importance of the respective errors, careful consideration should be given before implementation, and refinement targeted at the other errors may be something to consider.

View Article: PubMed Central - PubMed

Affiliation: School of Public Health, Epidemiology and Biostatistics, University of Birmingham, Birmingham, United Kingdom. k.hemming@bham.ac.uk

ABSTRACT

Background: Medication errors are an important source of potentially preventable morbidity and mortality. The PINCER study, a cluster randomised controlled trial, is one of the world's first experimental studies aiming to reduce the risk of such medication related potential for harm in general practice. Bayesian analyses can improve the clinical interpretability of trial findings.

Methods: Experts were asked to complete a questionnaire to elicit opinions of the likely effectiveness of the intervention for the key outcomes of interest--three important primary care medication errors. These were averaged to generate collective prior distributions, which were then combined with trial data to generate bayesian posterior distributions. The trial data were analysed in two ways: firstly replicating the trial reported cohort analysis acknowledging pairing of observations, but excluding non-paired observations; and secondly as cross-sectional data, with no exclusions, but without acknowledgement of the pairing. Frequentist and bayesian analyses were compared.

Findings: Bayesian evaluations suggest that the intervention is able to reduce the likelihood of one of the medication errors by about 50 (estimated to be between 20% and 70%). However, for the other two main outcomes considered, the evidence that the intervention is able to reduce the likelihood of prescription errors is less conclusive.

Conclusions: Clinicians are interested in what trial results mean to them, as opposed to what trial results suggest for future experiments. This analysis suggests that the PINCER intervention is strongly effective in reducing the likelihood of one of the important errors; not necessarily effective in reducing the other errors. Depending on the clinical importance of the respective errors, careful consideration should be given before implementation, and refinement targeted at the other errors may be something to consider.

Show MeSH