Analysis of Sedation Accident Records Available in the Japan Council for Quality Health Care Public Database.

OBJECTIVE

Medical accidents occur frequently. However, only a few studies have been conducted on sedation-related medical accidents. This study aimed to classify sedation accidents and analyze their causes using the (Patient-management Software Hardware Environment Livewear (P-mSHELL) model.

METHODS

The Japan Council for Quality Health Care database on medical accidents was used. Sedation accidents that occurred during procedures between January 2010 and June 2022 were included. After examining the accident details for several variables, the accident factors were classified by factors in the P-mSHELL model, and statistical analyses, including multivariate analysis of each factor and outcome (presence or absence of residual disability), were conducted.

RESULTS

Regarding the influence of the P-mSHELL factors on outcome, P factor (odds ratio = 6.347, 95% confidence interval = 2.000, 20.144) was a factor for having disability. There was a significant association between outcome and accident timing (that is, preoperative, intraoperative, or postoperative; p =0.01). No significant association was found between the outcomes and types of drugs used (p =1, 0.722, 0.594); however, there was a significant association between the incidence of respiratory depression and multiple drug use (p <0.001).

CONCLUSIONS

To prevent sedation accidents, it is important to monitor patients throughout the perioperative period. However, it is especially important to know the patient's condition in advance, and strict postoperative management is essential, especially for high-risk patients, to prevent serious accidents.