Department of Epidemiology & Biostatistics, McGill University, Montreal, Quebec, Canada.
J Am Med Inform Assoc. 2012 Jul-Aug;19(4):635-43. doi: 10.1136/amiajnl-2011-000609. Epub 2012 Jan 12.
Computerized drug alerts for psychotropic drugs are expected to reduce fall-related injuries in older adults. However, physicians over-ride most alerts because they believe the benefit of the drugs exceeds the risk.
To determine whether computerized prescribing decision support with patient-specific risk estimates would increase physician response to psychotropic drug alerts and reduce injury risk in older people.
Cluster randomized controlled trial of 81 family physicians and 5628 of their patients aged 65 and older who were prescribed psychotropic medication.
Intervention physicians received information about patient-specific risk of injury computed at the time of each visit using statistical models of non-modifiable risk factors and psychotropic drug doses. Risk thermometers presented changes in absolute and relative risk with each change in drug treatment. Control physicians received commercial drug alerts.
Injury risk at the end of follow-up based on psychotropic drug doses and non-modifiable risk factors. Electronic health records and provincial insurance administrative data were used to measure outcomes.
Mean patient age was 75.2 years. Baseline risk of injury was 3.94 per 100 patients per year. Intermediate-acting benzodiazepines (56.2%) were the most common psychotropic drug. Intervention physicians reviewed therapy in 83.3% of visits and modified therapy in 24.6%. The intervention reduced the risk of injury by 1.7 injuries per 1000 patients (95% CI 0.2/1000 to 3.2/1000; p=0.02). The effect of the intervention was greater for patients with higher baseline risks of injury (p<0.03).
Patient-specific risk estimates provide an effective method of reducing the risk of injury for high-risk older people.
clinicaltrials.gov Identifier: NCT00818285.
预计计算机化的精神药物药物警报可减少老年人跌倒相关的伤害。然而,医生通常会忽略大多数警报,因为他们认为药物的好处超过了风险。
确定是否具有患者特定风险估计的计算机化处方决策支持会增加医生对精神药物警报的反应,并降低老年人的受伤风险。
81 名家庭医生和他们的 5628 名年龄在 65 岁及以上的患者的聚类随机对照试验,这些患者被开了精神药物。
干预组医生在每次就诊时,使用不可改变的危险因素和精神药物剂量的统计模型,获得有关患者特定受伤风险的信息。风险温度计每次药物治疗改变时都会显示绝对和相对风险的变化。对照组医生收到了商业药物警报。
根据精神药物剂量和不可改变的危险因素,在随访结束时的伤害风险。电子健康记录和省级保险行政数据用于衡量结果。
平均患者年龄为 75.2 岁。受伤的基线风险为每年每 100 名患者 3.94 人。中效苯二氮䓬类药物(56.2%)是最常见的精神药物。干预医生在 83.3%的就诊时审查了治疗方案,并在 24.6%的就诊时修改了治疗方案。该干预措施使每 1000 名患者的受伤风险降低了 1.7 人(95%CI,0.2/1000 至 3.2/1000;p=0.02)。对于基线受伤风险较高的患者,干预的效果更大(p<0.03)。
患者特定的风险估计为高风险老年人降低受伤风险提供了一种有效的方法。
clinicaltrials.gov 标识符:NCT00818285。