Veninga C C, Denig P, Pont L G, Haaijer-Ruskamp F M
Northern Centre for Healthcare Research, Department of Clinical Pharmacology, University of Groningen, The Netherlands.
Health Serv Res. 2001 Apr;36(1 Pt 1):143-61.
To compare different indicators for assessing the quality of drug prescribing and establish their agreement in identifying doctors who may not adhere to treatment guidelines.
DATA SOURCES/STUDY SETTING: Data from 181 general practitioners (GPs) from The Netherlands. The case of asthma is used as an example because, in this area, different quality indicators exist whose validity is questioned. The study is part of the European Drug Education Project.
Spearman rank correlations were assessed among the GPs' scores on self-report instruments, aggregated prescribing indicators, and individualized prescribing indicators. Kappa values were calculated as agreement measures for identifying low adherence to the guidelines.
Prescribing data from GPs were collected through pharmacies, public health insurance companies, or computerized GP databases. Two self-report instruments were mailed to the GPs. The GPs first received a questionnaire assessing their competence regarding the treatment of asthma patients. Three months later they received a series of 16 written asthma cases asking for their intended treatment for each case.
Correlations between scores based on self-report instruments and indicators based on actual prescribing data were mostly nonsignificant and varied between 0 and 0.21. GPs identified as not adhering to the guidelines by the prescribing indicators often had high scores on the self-report instruments. Correlations between 0.20 and 0.55 were observed among indicators based on aggregated prescribing data and those based on individualized data. The agreement for identifying low adherence was small, with kappa values ranging from 0.19 to 0.30.
Indicators based on self-report instruments seem to overestimate guideline adherence. Indicators assessing prescribing quality at an aggregated level give clearly different results, as compared to indicators evaluating prescribing data on an individual patient level. Caution is needed when using such prescribing indicators to identify low adherence to guidelines. Further validation studies using a gold standard comparison are needed to define the best possible indicator.
比较评估药物处方质量的不同指标,并确定它们在识别可能未遵循治疗指南的医生方面的一致性。
数据来源/研究背景:来自荷兰的181名全科医生(GP)的数据。以哮喘病例为例,因为在该领域存在不同的质量指标,其有效性受到质疑。该研究是欧洲药物教育项目的一部分。
评估全科医生在自我报告工具、汇总处方指标和个体化处方指标上的得分之间的斯皮尔曼等级相关性。计算卡帕值作为识别低指南遵循率的一致性度量。
通过药房、公共健康保险公司或计算机化的全科医生数据库收集全科医生的处方数据。向全科医生邮寄了两份自我报告工具。全科医生首先收到一份评估其治疗哮喘患者能力的问卷。三个月后,他们收到一系列16个书面哮喘病例,要求他们针对每个病例给出预期的治疗方案。
基于自我报告工具的得分与基于实际处方数据的指标之间的相关性大多不显著,范围在0至0.21之间。被处方指标识别为未遵循指南的全科医生在自我报告工具上的得分往往较高。基于汇总处方数据的指标与基于个体化数据的指标之间的相关性在0.20至0.55之间。识别低遵循率的一致性较小,卡帕值范围为0.19至0.30。
基于自我报告工具的指标似乎高估了指南遵循率。与评估个体患者层面处方数据的指标相比,汇总层面评估处方质量的指标给出的结果明显不同。在使用此类处方指标识别低指南遵循率时需要谨慎。需要使用金标准比较进行进一步的验证研究,以确定最佳可能指标。