Dataset Information

Association Between Mobile Telephone Interruptions and Medication Administration Errors in a Pediatric Intensive Care Unit.

ABSTRACT:

Importance

Incoming text messages and calls on nurses' mobile telephones may interrupt medication administration, but whether such interruptions are associated with errors has not been established.

Objective

To assess whether a temporal association exists between mobile telephone interruptions and subsequent errors by pediatric intensive care unit (PICU) nurses during medication administration.

Design, setting, and participants

A retrospective cohort study was performed using telecommunications and electronic health record data from a PICU in a children's hospital. Data were collected from August 1, 2016, through September 30, 2017. Participants included 257 nurses and the 3308 patients to whom they administered medications.

Exposures

Primary exposures were incoming telephone calls and text messages received on the institutional mobile telephone assigned to the nurse in the 10 minutes leading up to a medication administration attempt. Secondary exposures were the nurse's PICU experience, work shift (day vs night), nurse to patient ratio, and level of patient care required.

Main outcomes and measures

Primary outcome, errors during medication administration, was a composite of reported medication administration errors and bar code medication administration error alerts generated when nurses attempted to give medications without active orders for the patient whose bar code they scanned.

Results

Participants included 257 nurses, of whom 168 (65.4%) had 6 months or more of PICU experience; and 3308 patients, of whom 1839 (55.6%) were male, 1539 (46.5%) were white, and 2880 (87.1%) were non-Hispanic. The overall rate of errors during 238?540 medication administration attempts was 3.1% (95% CI, 3.0%-3.3%) when nurses were uninterrupted by incoming telephone calls and 3.7% (95% CI, 3.4%-4.0%) when they were interrupted by such calls. During day shift, the odds ratios (ORs) for error when interrupted by calls (compared with uninterrupted) were 1.02 (95% CI, 0.92-1.13; P?=?.73) among nurses with 6 months or more of PICU experience and 1.22 (95% CI, 1.00-1.47; P?=?.046) among nurses with less than 6 months of experience. During night shift, the ORs for error when interrupted by calls were 1.35 (95% CI, 1.16-1.57; P?Conclusions and relevanceThis study's findings suggest that incoming telephone call interruptions may be temporally associated with medication administration errors among PICU nurses. Risk of error varied by shift, experience, nurse to patient ratio, and level of patient care required.

SUBMITTER: Bonafide CP

PROVIDER: S-EPMC6990809 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Publications

Association Between Mobile Telephone Interruptions and Medication Administration Errors in a Pediatric Intensive Care Unit.

Bonafide Christopher P CP Miller Jeffrey M JM Localio A Russell AR Khan Amina A Dziorny Adam C AC Mai Mark M Stemler Shannon S Chen Wanxin W Holmes John H JH Nadkarni Vinay M VM Keren Ron R

JAMA pediatrics 20200201 2

<h4>Importance</h4>Incoming text messages and calls on nurses' mobile telephones may interrupt medication administration, but whether such interruptions are associated with errors has not been established.<h4>Objective</h4>To assess whether a temporal association exists between mobile telephone interruptions and subsequent errors by pediatric intensive care unit (PICU) nurses during medication administration.<h4>Design, setting, and participants</h4>A retrospective cohort study was performed usi ...[more]

PMID: 31860017

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Dataset Information

Association Between Mobile Telephone Interruptions and Medication Administration Errors in a Pediatric Intensive Care Unit.

Importance

Objective

Design, setting, and participants

Exposures

Main outcomes and measures

Results

Publications

Association Between Mobile Telephone Interruptions and Medication Administration Errors in a Pediatric Intensive Care Unit.

Similar Datasets

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