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临床试验/NCT01034761
NCT01034761已完成不适用

Using Clinical Alerts in a Computerized Provider Order Entry System to Decrease Inappropriate Medication Prescribing Among Hospitalized Elders

Baystate Medical Center2 个研究点 分布在 1 个国家目标入组 719 人开始时间: 2013年4月最近更新:
适应症

试验速览

阶段
不适用
状态
已完成
入组人数
719
试验地点
2
主要终点
The percentage of elderly patients who receive a specified high-risk medication from the Beer's list.

研究概览

简要总结

Introduction:

The Beers list identifies medications that should be avoided in persons 65 years or older because they are ineffective, pose an unnecessarily high risk, or a safer alternative is available. In a recent study, we found a high rate of prescribing of Beers list medications to hospitalized patients. At Baystate, 41% of medical patients received at least one Beers list drug classified as "high severity," meaning it carried a high risk for an adverse drug reaction, while 5% received 3 or more. Some Beers drugs have been associated with delirium and falls. When compared to Baystate patients who did not receive a high severity medication, those who did had an increased risk of mortality (7.8% vs. 5.2%), longer length of stay (5.5 days vs. 3.9 days) and higher costs ($11,240 vs. 6243).

Specific Aims:

  1. Quantify the impact of synchronous electronic alerts on physician prescribing of high-severity Beers' list drugs to hospitalized patients over the age of 65 years.
  2. Compare physician reactions to each drug-specific alert

Project Description:

We will develop a series of clinical alerts in CIS, Baystate's computerized provider order entry system, to reduce the use of potentially inappropriate medications among hospitalized elders. We will randomize providers to electronic alerts or usual care. Whenever a provider randomized to alerts attempts to place an order for a high-risk medication on the Beers list and the intended recipient is over 65 years of age, a synchronous alert (i.e. a "pop-up") will inform the physician about the risks associated with the medication and will propose safer alternatives.

We will collect data on physician ordering and patient outcomes comparing the number of Beers list prescriptions from providers receiving electronic alerts to those not receiving alerts. Our anticipated outcome is a decrease in inappropriate prescribing during the period when the electronic alerts are activated. Other potential outcomes include decrease in length of stay and a decrease in falls.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Parallel
主要目的
Prevention
盲法
Single (Outcomes Assessor)

入排标准

年龄范围
65 Years 至 —(Older Adult)
性别
All
接受健康志愿者

入选标准

  • Hospitalized patients with Age > 65

排除标准

  • 未提供

结局指标

主要结局

The percentage of elderly patients who receive a specified high-risk medication from the Beer's list.

时间窗: Earlier of hospital stay or end of study

次要结局

  • The average number of specified high risk medications prescribed per patient.(Earlier of hospital stay or end of study)
  • Restraint use(Earlier of hospital stay or end of study)
  • Discharge status(6 months)
  • Falls(Earlier of hospital stay or end of study)
  • Length of stay(Earlier of hospital stay or end of study)
  • Total Cost(Earlier of hospital stay or end of study)

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Linda Canty, MD

Assistant Clinical Professor of Medine

Baystate Medical Center

研究点 (2)

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