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Chronology of prescribing error during the hospital stay and prediction of pharmacist's alerts overriding: a prospective analysis.

Caruba T, Colombet I, Gillaizeau F, Bruni V, Korb V, Prognon P, Bégué D, Durieux P, Sabatier B - BMC Health Serv Res (2010)

Bottom Line: The risk of a prescribing error decreased over time. 52% of the alerts were overridden (i.e error uncorrected by prescribers on the following day.Drug omissions were the most frequently taken into account by prescribers.The difference of overriding behavior between wards and according drug Anatomical Therapeutic Chemical class or type of error could also guide the validation tasks and programming of electronic alerts.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of pharmacy, APHP, Georges Pompidou European Hospital, 75015 Paris, France. thibaut.caruba@egp.aphp.fr

ABSTRACT

Background: Drug prescribing errors are frequent in the hospital setting and pharmacists play an important role in detection of these errors. The objectives of this study are (1) to describe the drug prescribing errors rate during the patient's stay, (2) to find which characteristics for a prescribing error are the most predictive of their reproduction the next day despite pharmacist's alert (i.e. override the alert).

Methods: We prospectively collected all medication order lines and prescribing errors during 18 days in 7 medical wards' using computerized physician order entry. We described and modelled the errors rate according to the chronology of hospital stay. We performed a classification and regression tree analysis to find which characteristics of alerts were predictive of their overriding (i.e. prescribing error repeated).

Results: 12 533 order lines were reviewed, 117 errors (errors rate 0.9%) were observed and 51% of these errors occurred on the first day of the hospital stay. The risk of a prescribing error decreased over time. 52% of the alerts were overridden (i.e error uncorrected by prescribers on the following day. Drug omissions were the most frequently taken into account by prescribers. The classification and regression tree analysis showed that overriding pharmacist's alerts is first related to the ward of the prescriber and then to either Anatomical Therapeutic Chemical class of the drug or the type of error.

Conclusions: Since 51% of prescribing errors occurred on the first day of stay, pharmacist should concentrate his analysis of drug prescriptions on this day. The difference of overriding behavior between wards and according drug Anatomical Therapeutic Chemical class or type of error could also guide the validation tasks and programming of electronic alerts.

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Related in: MedlinePlus

Number of new prescribing errors per 10 order lines by ith day of stay. Histogram represents the observed data ie the mean number of new prescribing errors per 10 order lines. The fitted curve with 95% confidence intervals represents the estimation of of the mean number of new prescribing errors per 10 order lines at ith day derived from the mixed Poisson regression model.
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Figure 1: Number of new prescribing errors per 10 order lines by ith day of stay. Histogram represents the observed data ie the mean number of new prescribing errors per 10 order lines. The fitted curve with 95% confidence intervals represents the estimation of of the mean number of new prescribing errors per 10 order lines at ith day derived from the mixed Poisson regression model.

Mentions: The histogram in Figure 1 shows the number of new prescribing errors per 10 order lines according to the day of stay. More than 51% of these errors (60/117) occurred on the day of admission (see figures below histogram). This rate was 80% over the first three days. Nine (7.7%) errors were observed in 8 of the 96 stays (8.3%) which lasted 8 days or more. These 9 errors were indifferently distributed between the 8th and the 15th day of stay (see Figure 1). The new prescribing errors rate per ten prescriptions order lines was maximum the day of admission and decreased in the first six days of stay. We observed an increase in the rate between the sixth and eighth day and after the fourteenth day but these fluctuations corresponded to small variations in the number of errors. The level of severity of errors was not significantly different in the first days of stay (71% were level C for the first 3 days and 84% for the next days).


Chronology of prescribing error during the hospital stay and prediction of pharmacist's alerts overriding: a prospective analysis.

Caruba T, Colombet I, Gillaizeau F, Bruni V, Korb V, Prognon P, Bégué D, Durieux P, Sabatier B - BMC Health Serv Res (2010)

Number of new prescribing errors per 10 order lines by ith day of stay. Histogram represents the observed data ie the mean number of new prescribing errors per 10 order lines. The fitted curve with 95% confidence intervals represents the estimation of of the mean number of new prescribing errors per 10 order lines at ith day derived from the mixed Poisson regression model.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2820036&req=5

Figure 1: Number of new prescribing errors per 10 order lines by ith day of stay. Histogram represents the observed data ie the mean number of new prescribing errors per 10 order lines. The fitted curve with 95% confidence intervals represents the estimation of of the mean number of new prescribing errors per 10 order lines at ith day derived from the mixed Poisson regression model.
Mentions: The histogram in Figure 1 shows the number of new prescribing errors per 10 order lines according to the day of stay. More than 51% of these errors (60/117) occurred on the day of admission (see figures below histogram). This rate was 80% over the first three days. Nine (7.7%) errors were observed in 8 of the 96 stays (8.3%) which lasted 8 days or more. These 9 errors were indifferently distributed between the 8th and the 15th day of stay (see Figure 1). The new prescribing errors rate per ten prescriptions order lines was maximum the day of admission and decreased in the first six days of stay. We observed an increase in the rate between the sixth and eighth day and after the fourteenth day but these fluctuations corresponded to small variations in the number of errors. The level of severity of errors was not significantly different in the first days of stay (71% were level C for the first 3 days and 84% for the next days).

Bottom Line: The risk of a prescribing error decreased over time. 52% of the alerts were overridden (i.e error uncorrected by prescribers on the following day.Drug omissions were the most frequently taken into account by prescribers.The difference of overriding behavior between wards and according drug Anatomical Therapeutic Chemical class or type of error could also guide the validation tasks and programming of electronic alerts.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of pharmacy, APHP, Georges Pompidou European Hospital, 75015 Paris, France. thibaut.caruba@egp.aphp.fr

ABSTRACT

Background: Drug prescribing errors are frequent in the hospital setting and pharmacists play an important role in detection of these errors. The objectives of this study are (1) to describe the drug prescribing errors rate during the patient's stay, (2) to find which characteristics for a prescribing error are the most predictive of their reproduction the next day despite pharmacist's alert (i.e. override the alert).

Methods: We prospectively collected all medication order lines and prescribing errors during 18 days in 7 medical wards' using computerized physician order entry. We described and modelled the errors rate according to the chronology of hospital stay. We performed a classification and regression tree analysis to find which characteristics of alerts were predictive of their overriding (i.e. prescribing error repeated).

Results: 12 533 order lines were reviewed, 117 errors (errors rate 0.9%) were observed and 51% of these errors occurred on the first day of the hospital stay. The risk of a prescribing error decreased over time. 52% of the alerts were overridden (i.e error uncorrected by prescribers on the following day. Drug omissions were the most frequently taken into account by prescribers. The classification and regression tree analysis showed that overriding pharmacist's alerts is first related to the ward of the prescriber and then to either Anatomical Therapeutic Chemical class of the drug or the type of error.

Conclusions: Since 51% of prescribing errors occurred on the first day of stay, pharmacist should concentrate his analysis of drug prescriptions on this day. The difference of overriding behavior between wards and according drug Anatomical Therapeutic Chemical class or type of error could also guide the validation tasks and programming of electronic alerts.

Show MeSH
Related in: MedlinePlus