Temporal and other factors that influence the time doctors take to prescribe using an electronic prescribing system

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Temporal and other factors that influence the time doctors take to prescribe using an electronic prescribing system. / Coleman, Jamie; Hodson, James; Thomas, Sarah; Brooks, Hannah; Ferner, Robin.

In: Journal of the American Medical Informatics Association, Vol. 22, No. 1, 10.1136/amiajnl-2014-002822, 01.2015, p. 206-12.

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@article{64352d15e40c479ca8958f04aacd33d9,
title = "Temporal and other factors that influence the time doctors take to prescribe using an electronic prescribing system",
abstract = "BACKGROUND: A computerized physician order entry (CPOE) system with embedded clinical decision support can reduce medication errors in hospitals, but might increase the time taken to generate orders. AIMS: We aimed to quantify the effects of temporal (month, day of week, hour of shift) and other factors (grade of doctor, prior experience with the system, alert characteristics, and shift type) on the time taken to generate a prescription order. SETTING: A large university teaching hospital using a locally developed CPOE system with an extensive audit database. DESIGN: We retrospectively analyzed prescription orders from the audit database between August 2011 and July 2012. RESULTS: The geometric mean time taken to generate a prescription order within the CPOE system was 11.75 s (95% CI 11.72 to 11.78). Time to prescribe was most affected by the display of high-level (24.59 s (24.43 to 24.76); p<0.001) or previously unseen (18.87 s (18.78 to 18.96); p<0.001) alerts. Prescribers took significantly less time at weekends (11.29 s (11.23 to 11.35)) than on weekdays (11.88 s (11.84 to 11.91); p<0.001), in the first (11.25 s (11.16 to 11.34); p<0.001) and final (11.56 s (11.47 to 11.66); p<0.001) hour of their shifts, and after the first month of using the system. CONCLUSIONS: The display of alerts, prescribing experience, system familiarity, and environment all affect the time taken to generate a prescription order. Our study reinforces the need for appropriate alerts to be presented to individuals at an appropriate place in the workflow, in order to improve prescribing efficiency",
keywords = "Electronic prescribing",
author = "Jamie Coleman and James Hodson and Sarah Thomas and Hannah Brooks and Robin Ferner",
year = "2015",
month = jan,
language = "English",
volume = "22",
pages = "206--12",
journal = "Journal of the American Medical Informatics Association",
issn = "1067-5027",
publisher = "Oxford University Press",
number = "1",

}

RIS

TY - JOUR

T1 - Temporal and other factors that influence the time doctors take to prescribe using an electronic prescribing system

AU - Coleman, Jamie

AU - Hodson, James

AU - Thomas, Sarah

AU - Brooks, Hannah

AU - Ferner, Robin

PY - 2015/1

Y1 - 2015/1

N2 - BACKGROUND: A computerized physician order entry (CPOE) system with embedded clinical decision support can reduce medication errors in hospitals, but might increase the time taken to generate orders. AIMS: We aimed to quantify the effects of temporal (month, day of week, hour of shift) and other factors (grade of doctor, prior experience with the system, alert characteristics, and shift type) on the time taken to generate a prescription order. SETTING: A large university teaching hospital using a locally developed CPOE system with an extensive audit database. DESIGN: We retrospectively analyzed prescription orders from the audit database between August 2011 and July 2012. RESULTS: The geometric mean time taken to generate a prescription order within the CPOE system was 11.75 s (95% CI 11.72 to 11.78). Time to prescribe was most affected by the display of high-level (24.59 s (24.43 to 24.76); p<0.001) or previously unseen (18.87 s (18.78 to 18.96); p<0.001) alerts. Prescribers took significantly less time at weekends (11.29 s (11.23 to 11.35)) than on weekdays (11.88 s (11.84 to 11.91); p<0.001), in the first (11.25 s (11.16 to 11.34); p<0.001) and final (11.56 s (11.47 to 11.66); p<0.001) hour of their shifts, and after the first month of using the system. CONCLUSIONS: The display of alerts, prescribing experience, system familiarity, and environment all affect the time taken to generate a prescription order. Our study reinforces the need for appropriate alerts to be presented to individuals at an appropriate place in the workflow, in order to improve prescribing efficiency

AB - BACKGROUND: A computerized physician order entry (CPOE) system with embedded clinical decision support can reduce medication errors in hospitals, but might increase the time taken to generate orders. AIMS: We aimed to quantify the effects of temporal (month, day of week, hour of shift) and other factors (grade of doctor, prior experience with the system, alert characteristics, and shift type) on the time taken to generate a prescription order. SETTING: A large university teaching hospital using a locally developed CPOE system with an extensive audit database. DESIGN: We retrospectively analyzed prescription orders from the audit database between August 2011 and July 2012. RESULTS: The geometric mean time taken to generate a prescription order within the CPOE system was 11.75 s (95% CI 11.72 to 11.78). Time to prescribe was most affected by the display of high-level (24.59 s (24.43 to 24.76); p<0.001) or previously unseen (18.87 s (18.78 to 18.96); p<0.001) alerts. Prescribers took significantly less time at weekends (11.29 s (11.23 to 11.35)) than on weekdays (11.88 s (11.84 to 11.91); p<0.001), in the first (11.25 s (11.16 to 11.34); p<0.001) and final (11.56 s (11.47 to 11.66); p<0.001) hour of their shifts, and after the first month of using the system. CONCLUSIONS: The display of alerts, prescribing experience, system familiarity, and environment all affect the time taken to generate a prescription order. Our study reinforces the need for appropriate alerts to be presented to individuals at an appropriate place in the workflow, in order to improve prescribing efficiency

KW - Electronic prescribing

M3 - Article

VL - 22

SP - 206

EP - 212

JO - Journal of the American Medical Informatics Association

JF - Journal of the American Medical Informatics Association

SN - 1067-5027

IS - 1

M1 - 10.1136/amiajnl-2014-002822

ER -