Risk factors analysis and prediction model of nursing medication errors
10.3760/cma.j.issn.1674-2907.2020.03.007
- VernacularTitle:护理给药错误事件的危险因素分析及预测模型的构建
- Author:
Shiyao LIANG
1
;
Duo XU
;
Xiaoqun XU
Author Information
1. 温州医科大学附属第一医院胰腺炎诊治中心
- Keywords:
Nursing care;
Medication error;
Risk factor;
Prediction model
- From:
Chinese Journal of Modern Nursing
2020;26(3):316-322
- CountryChina
- Language:Chinese
-
Abstract:
Objective To quickly screen the risk events of nursing medication, propose comprehensive and targeted preventive measures to guide clinical nursing work, ensure the safety of patient medication, improve the quality of care, and provide a more reliable theoretical framework and basis for the quality management system of drug care. Methods In this retrospective case-control study, totally 688 nursing medication errors reported from a Class Ⅲ Grade A hospital from January 2016 to December 2018 were selected as the case group, and 1376 cases without nursing medication errors were randomly selected as the control group from the drug execution database at the same time. Univariate and multivariate Logistic regression analysis was performed on the objective and human factors related to the occurrence of medication errors to explore the potential risk factors of nursing medication errors and construct a risk prediction model for nursing medication errors. Results Univariate analysis showed that nurses' job title and working years, patients' gender, education level and age, dosing shift, time of shift, working hours, route of administration, and department of drug administration were the influencing factors of error events in nursing medication (P<0.05). Multivariate Logistic regression analysis was used to incorporate nursing years, department, route of administration,patient's age, whether or not in the shift period into the final risk prediction model for nursing medication errors (P< 0.05). The receiver operating characteristic curve (ROC) was drawn and the area under the ROC (AUC) was calculated. The AUC was 0.765, which was > 0.7, showing that the model had sound predictive power in clinical practice. Conclusions The construction of the prediction model for nursing medication errors can provide a theoretical basis for clinical drug care,which is more targeted and practical for the hospital drug care management system and can ensure the safety of nursing.
