An indirect time study for nursing tasks in Belgian hospitals : methodological aspects and optimal sampling
- Author
- Stijn De Vuyst (UGent) , Kurt De Cock (UGent) and Dieter Claeys (UGent)
- Organization
- Abstract
- In this presentation we report on a large-scale time study to estimate the expected duration of a set of common nursing tasks in 25 Belgian hospitals involving over 600 nurses. A direct time measurement by starting and stopping a timer at the beginning and end of every executed task proved to be too invasive and complicated if done by the nurse itself and too expensive if done by an outside expert. We therefore used an indirect method by equipping each nurse with a smart phone running an application that beeps at irregular time intervals. After every beep, within a time-out interval, the nurse registers what task type she was executing. In addition, after the nurse's work shift is finished, she is presented with a list of 10 task types and asked to tally how many tasks of each type were executed during the shift. For a certain task type, the beeps allow us to estimate the fraction of time a nurse spends on tasks of this type, while the tallies estimate their rate, i.e. how many tasks of this type occur per time unit. The ratio of the fraction and rate is the expected duration. We provide approximations of the bias and the variance of the resulting estimator using the Delta method leading to reliable confidence intervals and optimal strategies for deciding which task types to tally in future nurse shifts. In addition, we investigate the quality of our approximation by comparing to Monte Carlo simulations.
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01HRSWSHGHPSG92FFVEFK3A27F
- MLA
- De Vuyst, Stijn, et al. “An Indirect Time Study for Nursing Tasks in Belgian Hospitals : Methodological Aspects and Optimal Sampling.” EURO 2024 Conference Handbook & Abstracts : 33rd European Conference on Operational Research (EURO XXXIII), Copenhagen, Denmark, June 30 - July 3, 2024, 2024, pp. 288–288.
- APA
- De Vuyst, S., De Cock, K., & Claeys, D. (2024). An indirect time study for nursing tasks in Belgian hospitals : methodological aspects and optimal sampling. EURO 2024 Conference Handbook & Abstracts : 33rd European Conference on Operational Research (EURO XXXIII), Copenhagen, Denmark, June 30 - July 3, 2024, 288–288.
- Chicago author-date
- De Vuyst, Stijn, Kurt De Cock, and Dieter Claeys. 2024. “An Indirect Time Study for Nursing Tasks in Belgian Hospitals : Methodological Aspects and Optimal Sampling.” In EURO 2024 Conference Handbook & Abstracts : 33rd European Conference on Operational Research (EURO XXXIII), Copenhagen, Denmark, June 30 - July 3, 2024, 288–288.
- Chicago author-date (all authors)
- De Vuyst, Stijn, Kurt De Cock, and Dieter Claeys. 2024. “An Indirect Time Study for Nursing Tasks in Belgian Hospitals : Methodological Aspects and Optimal Sampling.” In EURO 2024 Conference Handbook & Abstracts : 33rd European Conference on Operational Research (EURO XXXIII), Copenhagen, Denmark, June 30 - July 3, 2024, 288–288.
- Vancouver
- 1.De Vuyst S, De Cock K, Claeys D. An indirect time study for nursing tasks in Belgian hospitals : methodological aspects and optimal sampling. In: EURO 2024 Conference Handbook & Abstracts : 33rd European Conference on Operational Research (EURO XXXIII), Copenhagen, Denmark, June 30 - July 3, 2024. 2024. p. 288–288.
- IEEE
- [1]S. De Vuyst, K. De Cock, and D. Claeys, “An indirect time study for nursing tasks in Belgian hospitals : methodological aspects and optimal sampling,” in EURO 2024 Conference Handbook & Abstracts : 33rd European Conference on Operational Research (EURO XXXIII), Copenhagen, Denmark, June 30 - July 3, 2024, Copenhagen, Denmark, 2024, pp. 288–288.
@inproceedings{01HRSWSHGHPSG92FFVEFK3A27F,
abstract = {{In this presentation we report on a large-scale time study to estimate the expected duration of a set of common nursing tasks in 25 Belgian hospitals involving over 600 nurses. A direct time measurement by starting and stopping a timer at the beginning and end of every executed task proved to be too invasive and complicated if done by the nurse itself and too expensive if done by an outside expert. We therefore used an indirect method by equipping each nurse with a smart phone running an application that beeps at irregular time intervals. After every beep, within a time-out interval, the nurse registers what task type she was executing. In addition, after the nurse's work shift is finished, she is presented with a list of 10 task types and asked to tally how many tasks of each type were executed during the shift. For a certain task type, the beeps allow us to estimate the fraction of time a nurse spends on tasks of this type, while the tallies estimate their rate, i.e. how many tasks of this type occur per time unit. The ratio of the fraction and rate is the expected duration.
We provide approximations of the bias and the variance of the resulting estimator using the Delta method leading to reliable confidence intervals and optimal strategies for deciding which task types to tally in future nurse shifts. In addition, we investigate the quality of our approximation by comparing to Monte Carlo
simulations.}},
author = {{De Vuyst, Stijn and De Cock, Kurt and Claeys, Dieter}},
booktitle = {{EURO 2024 Conference Handbook & Abstracts : 33rd European Conference on Operational Research (EURO XXXIII), Copenhagen, Denmark, June 30 - July 3, 2024}},
isbn = {{9788793458260}},
language = {{eng}},
location = {{Copenhagen, Denmark}},
pages = {{288--288}},
title = {{An indirect time study for nursing tasks in Belgian hospitals : methodological aspects and optimal sampling}},
year = {{2024}},
}