What question did this study set out to answer?

To compare the incidence and clinical severity rating of dose prescribing errors before and after the introduction of a commercial electronic prescribing system at a tertiary children's hospital.

August 1, 2010BMJ Quality & Safety

Paediatric dosing errors before and after electronic prescribing

View Full Paper

Ask AI

Bookmark

Authors

YJYogini JaniDharmsinh Desai University NBNick BarberMcPin Foundation IWIan Chi Kei WongMacau University of Science and Technology

Discussion

Member takes

Implication

Pre-post comparative study reveals reduced pediatric dosing errors after electronic prescribing implementation, indicating improved medication safety in hospital care.

Key Points

To compare the incidence and clinical severity rating of dose prescribing errors before and after the introduction of a commercial electronic prescribing system at a tertiary children's hospital.
Conducted prescription reviews to identify dose errors across outpatient, inpatient, and discharge orders before (N=3,939 prescribed items) and after (N=4,784 prescribed items) electronic prescribing implementation.
Assigned error severity using a validated scoring tool evaluated by five judges, using the mean score as an index of severity.
Total dose prescribing errors dropped from 88 of 3,939 items (2.2%) pre-implementation to 57 of 4,784 items (1.2%) post-implementation, an absolute reduction of 1.0% (95% CI of difference, -1.6% to -0.5%; p < 0.001).
Minor severity errors decreased from 35/3,939 (0.89%) to 21/4,784 (0.44%; 95% CI, -0.8% to -0.11%; p = 0.009), and moderate severity errors decreased from 46/3,939 (1.17%) to 33/4,784 (0.69%; 95% CI, -0.91% to -0.08%; p = 0.019).
Severe outcome errors declined from 7/3,939 (0.18%) pre-implementation to 3/4,784 (0.06%) post-implementation, but the change did not achieve statistical significance (95% CI, -0.31% to +0.04%; p = 0.11).

Cite This Study

Jani et al. (2010) studied this question.

synapsesocial.com/papers/6a1d8fcacc9f7df1b705a126 https://doi.org/10.1136/qshc.2009.033068

View Full Paper

Ask AI

Bookmark

August 1, 2010BMJ Quality & Safety

Paediatric dosing errors before and after electronic prescribing

View Full Paper

Ask AI

Bookmark

Authors

YJYogini JaniDharmsinh Desai University NBNick BarberMcPin Foundation IWIan Chi Kei WongMacau University of Science and Technology

Discussion

Member takes

Implication

Pre-post comparative study reveals reduced pediatric dosing errors after electronic prescribing implementation, indicating improved medication safety in hospital care.

Key Points

To compare the incidence and clinical severity rating of dose prescribing errors before and after the introduction of a commercial electronic prescribing system at a tertiary children's hospital.
Conducted prescription reviews to identify dose errors across outpatient, inpatient, and discharge orders before (N=3,939 prescribed items) and after (N=4,784 prescribed items) electronic prescribing implementation.
Assigned error severity using a validated scoring tool evaluated by five judges, using the mean score as an index of severity.
Total dose prescribing errors dropped from 88 of 3,939 items (2.2%) pre-implementation to 57 of 4,784 items (1.2%) post-implementation, an absolute reduction of 1.0% (95% CI of difference, -1.6% to -0.5%; p < 0.001).
Minor severity errors decreased from 35/3,939 (0.89%) to 21/4,784 (0.44%; 95% CI, -0.8% to -0.11%; p = 0.009), and moderate severity errors decreased from 46/3,939 (1.17%) to 33/4,784 (0.69%; 95% CI, -0.91% to -0.08%; p = 0.019).
Severe outcome errors declined from 7/3,939 (0.18%) pre-implementation to 3/4,784 (0.06%) post-implementation, but the change did not achieve statistical significance (95% CI, -0.31% to +0.04%; p = 0.11).

Cite This Study

Jani et al. (2010) studied this question.

synapsesocial.com/papers/6a1d8fcacc9f7df1b705a126 https://doi.org/10.1136/qshc.2009.033068

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

View Full Paper

Ask AI

Bookmark