儿科普通病房的处方模式及其与处方错误的关系:一项回顾性观察研究。

IF 1.9 Q3 PHARMACOLOGY & PHARMACY
Drugs - Real World Outcomes Pub Date : 2023-12-01 Epub Date: 2023-10-13 DOI:10.1007/s40801-023-00392-0
Aylin N Satir, Miriam Pfiffner, Christoph R Meier, Angela Caduff Good
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引用次数: 0

摘要

目的:关于儿科住院患者,尤其是普通病房的药物使用模式,只有有限的数据。这项研究的目的是描述瑞士德语区一所大学儿童医院的处方模式及其与处方错误的关系。方法:这是一项回顾性单中心观察性研究的亚分析。489名患者(2693张处方)的患者特征和药物使用与处方错误有关。根据解剖治疗化学分类系统(ATC)对药物进行分类、根据欧洲药品管理局指南按年龄组对患者进行分类,并根据类型[欧洲药物护理网络(PCNE)分类]和错误严重程度[适用的国家药物错误报告协调委员会(NCC-MERP)指数]分析处方错误,和抗感染药物(J)(10.7%)。82%的患者服用了止痛药。大多数药物是口服(47%)或静脉注射(32%),但直肠途径也很常见(10%)。最常见的处方药是扑热息痛、安乃近和布洛芬。大量的安乃近处方(37%的患者服用了安乃近)是德语国家的典型情况。年龄较大的儿科患者比年龄较小的患者开了更多的药。不同年龄组和性别的潜在有害错误率存在统计学显著差异;2岁至11岁的儿童比2岁以下的婴儿有更高的潜在有害错误发生率(p=0.029),女性患者比男性患者有更高潜在有害错误的发生率(p=0.023)。某些药物(那布芬、头孢唑林)会出现复发性错误瑞士大学儿童医院,并强调了未来研究的一些领域。尤其是,女性儿科患者处方错误的风险更高,需要进一步调查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prescribing Patterns in Pediatric General Wards and Their Association with Prescribing Errors: A Retrospective Observational Study.

Purpose: There are only limited data on drug utilization patterns in pediatric inpatients, especially on general wards. The aim of the study was to describe prescribing patterns and their associations with prescribing errors in a university children's hospital in the German-speaking part of Switzerland.

Method: This was a subanalysis of a retrospective single-center observational study. Patient characteristics and drug use of 489 patients with 2693 drug prescriptions were associated with prescribing errors. Drugs were categorized by the Anatomic Therapeutic Chemical Classification System (ATC), patients were categorized by age group according to European Medicines Agency guidelines, and prescribing errors were analyzed by type [Pharmaceutical Care Network Europe (PCNE) classification] and severity of error [adapted National Coordinating Council for Medication Error Reporting (NCC MERP) index].

Results: The most frequently prescribed ATC classes were nervous system (N) (42.6%), alimentary system (A) (15.6%), and anti-infective drugs (J) (10.7%). Eighty-two percent of patients were prescribed an analgesic. Most drugs were prescribed for oral (47%) or intravenous (32%) administration, but the rectal route was also frequent (10%). The most frequently prescribed drugs were paracetamol, metamizole, and ibuprofen. The high number of metamizole prescriptions (37% of patients were prescribed metamizole) is typical for German-speaking countries. Older pediatric patients were prescribed more drugs than younger patients. A statistically significant difference was found in the rate of potentially harmful errors across age groups and for gender; children between 2 and 11 years had a higher rate of potentially harmful errors than infants under 2 years (p = 0.029) and female patients had a higher rate of potentially harmful errors than male patients (p = 0.023). Recurring errors were encountered with certain drugs (nalbuphine, cefazolin).

Conclusions: Our study provides insight into prescribing patterns on pediatric general wards in a university children's hospital in Switzerland and highlights some areas for future research. Especially, the higher risk for prescribing errors among female pediatric patients needs further investigation.

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来源期刊
Drugs - Real World Outcomes
Drugs - Real World Outcomes PHARMACOLOGY & PHARMACY-
CiteScore
3.60
自引率
5.00%
发文量
49
审稿时长
8 weeks
期刊介绍: Drugs - Real World Outcomes targets original research and definitive reviews regarding the use of real-world data to evaluate health outcomes and inform healthcare decision-making on drugs, devices and other interventions in clinical practice. The journal includes, but is not limited to, the following research areas: Using registries/databases/health records and other non-selected observational datasets to investigate: drug use and treatment outcomes prescription patterns drug safety signals adherence to treatment guidelines benefit : risk profiles comparative effectiveness economic analyses including cost-of-illness Data-driven research methodologies, including the capture, curation, search, sharing, analysis and interpretation of ‘big data’ Techniques and approaches to optimise real-world modelling.
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