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谁获得了戒烟药物的处方?利用大型初级保健数据库进行关联规则挖掘分析。

Who receives prescriptions for smoking cessation medications? An association rule mining analysis using a large primary care database.

机构信息

UK Centre for Tobacco Control Studies, Division of Epidemiology and Public Health, University of Nottingham, Clinical Sciences Building, City Hospital, Nottingham, UK.

出版信息

Tob Control. 2013 Jul;22(4):274-9. doi: 10.1136/tobaccocontrol-2011-050124. Epub 2012 Jan 13.

DOI:10.1136/tobaccocontrol-2011-050124
PMID:22246781
Abstract

AIMS

To use association rule mining methods to investigate prescribing of smoking cessation medication in the UK primary care and to identify the characteristics of numerically important groups of patients who typically do, or do not, receive cessation therapy.

DESIGN

An association rule mining study using The Health Improvement Network Database.

SETTINGS AND PARTICIPANTS

282 433 patients aged 16 years and over from 419 UK general practices, who were registered with the practice throughout 2008 and recorded as a current smoker during that year.

OUTCOME

Prescription for any type of smoking cessation medications in 2008 (nicotine replacement therapy, bupropion or varenicline).

VARIABLES

Age, gender, lifestyle indicators and co-morbidity.

RESULTS

Of the current smokers, 37 731 (13.4%) were given prescriptions for smoking cessation treatment during 2008. Prescriptions were particularly likely to be given to women, those aged 31-60 years, and people with diagnoses of chronic obstructive pulmonary disease and depression. On the contrary, of patients with dementia, with alcohol intake over recommended levels, atrial fibrillation or chronic kidney disease was extremely unlikely to be prescribed a smoking cessation medication. However, the largest group of patients who did not receive therapy was young and otherwise healthy individuals.

CONCLUSIONS

This novel approach identified sizeable and easily definable groups of patients who are systematically failing to receive support for smoking cessation in primary care. Association rule mining can be used to identify key numerically important groups at high or low risk of receiving treatment and hence potentially to improve healthcare delivery.

摘要

目的

使用关联规则挖掘方法调查英国初级保健中戒烟药物的开具情况,并确定通常接受或不接受戒烟治疗的重要患者群体的特征。

设计

一项使用健康改善网络数据库的关联规则挖掘研究。

设置和参与者

419 家英国全科诊所中年龄在 16 岁及以上的 282433 名患者,他们在整个 2008 年期间在诊所注册,并在该年度被记录为当前吸烟者。

结果

2008 年任何类型的戒烟药物处方(尼古丁替代疗法、安非他酮或伐尼克兰)。

变量

年龄、性别、生活方式指标和合并症。

结果

在当前吸烟者中,有 37731 人(13.4%)在 2008 年接受了戒烟治疗处方。处方特别可能开给女性、31-60 岁的人,以及患有慢性阻塞性肺疾病和抑郁症的人。相反,患有痴呆症、饮酒量超过推荐水平、心房颤动或慢性肾病的患者极不可能开戒烟药物。然而,未接受治疗的最大患者群体是年轻且健康的个体。

结论

这种新方法确定了相当大且易于定义的患者群体,他们在初级保健中系统地未能获得戒烟支持。关联规则挖掘可用于识别接受治疗的高风险或低风险的关键重要患者群体,从而有可能改善医疗保健服务的提供。

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