Abstract
Background: Anesthesia information management systems (AIMSs) automatically import real-time vital signs from physiological monitors to anesthetic records, replacing part of anesthetists’ traditional manual record keeping. However, only a handful of studies have examined the effects of AIMSs on anesthetists’ monitoring performance.
Objective: This study aimed to compare the effects of AIMS use and manual record keeping on anesthetists’ monitoring performance, using a full-scale high-fidelity simulation.
Methods: This simulation study was a randomized controlled trial with a parallel group design that compared the effects of two record-keeping methods (AIMS vs manual) on anesthetists’ monitoring performance. Twenty anesthetists at a tertiary hospital in Hong Kong were randomly assigned to either the AIMS or manual condition, and they participated in a 45-minute scenario in a high-fidelity simulation environment. Participants took over a case involving general anesthesia for below-knee amputation surgery and performed record keeping. The three primary outcomes were participants’ (1) vigilance detection accuracy (%), (2) situation awareness accuracy (%), and (3) subjective mental workload (0-100).
Results: With regard to the primary outcomes, there was no significant difference in participants’ vigilance detection accuracy (AIMS, 56.7% vs manual, 56.7%; P=.50), and subjective mental workload was significantly lower in the AIMS condition than in the manual condition (AIMS, 34.2 vs manual, 46.7; P=.02). However, the result for situation awareness accuracy was inconclusive as the study did not have enough power to detect a difference between the two conditions.
Conclusions: Our findings suggest that it is promising for AIMS use to become a mainstay of anesthesia record keeping. AIMSs are effective in reducing anesthetists’ workload and improving the quality of their anesthetic record keeping, without compromising vigilance.
Objective: This study aimed to compare the effects of AIMS use and manual record keeping on anesthetists’ monitoring performance, using a full-scale high-fidelity simulation.
Methods: This simulation study was a randomized controlled trial with a parallel group design that compared the effects of two record-keeping methods (AIMS vs manual) on anesthetists’ monitoring performance. Twenty anesthetists at a tertiary hospital in Hong Kong were randomly assigned to either the AIMS or manual condition, and they participated in a 45-minute scenario in a high-fidelity simulation environment. Participants took over a case involving general anesthesia for below-knee amputation surgery and performed record keeping. The three primary outcomes were participants’ (1) vigilance detection accuracy (%), (2) situation awareness accuracy (%), and (3) subjective mental workload (0-100).
Results: With regard to the primary outcomes, there was no significant difference in participants’ vigilance detection accuracy (AIMS, 56.7% vs manual, 56.7%; P=.50), and subjective mental workload was significantly lower in the AIMS condition than in the manual condition (AIMS, 34.2 vs manual, 46.7; P=.02). However, the result for situation awareness accuracy was inconclusive as the study did not have enough power to detect a difference between the two conditions.
Conclusions: Our findings suggest that it is promising for AIMS use to become a mainstay of anesthesia record keeping. AIMSs are effective in reducing anesthetists’ workload and improving the quality of their anesthetic record keeping, without compromising vigilance.
| Original language | English |
|---|---|
| Article number | e16036 |
| Pages (from-to) | e16036 |
| Journal | JMIR Human Factors |
| Volume | 7 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 16 Jun 2020 |
Bibliographical note
This study would not have been possible without support from the Department of Anaesthesia and Intensive Care and the Quality and Safety Division at Tuen Mun Hospital. We would like to sincerely thank Tuen Mun Hospital’s anesthetists who participated in the study and Francis Leung Wai Sing who generously made time to prepare and participate in the simulation. We would also like to express our gratitude to Professor Penelope Sanderson and Professor Robert Loeb for their encouragement and valuable comments that helped us improve the research. This research was supported by a postgraduate studentship from Lingnan University awarded to MKT.Keywords
- Anesthesia information management system
- Automated record keeping
- Mental workload
- Situation awareness
- Vigilance
