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Enhancing an Existing Clinical Information System to Improve Study Recruitment and Census Gathering Efficiency

机译:加强现有的临床信息系统以提高研究招募和人口普查收集效率

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摘要

Information technology can improve healthcare efficiency. We developed and implemented a simple and inexpensive tool, the “Automated Case Finding and Alerting System” (ACAS), using data from an existing clinical information system to facilitate identification of potentially eligible patients for clinical trials and patient encounters for billing purposes. We validated the ACAS by calculating the level of agreement in patient identification with data generated from manual identification methods. There was substantial agreement between the two methods both for clinical trial (kappa:0.84) and billing (kappa:0.97). Automated identification occurred instantaneously vs. about 2 hours/day for clinical trial and 1 hour 10 minutes/day for billing, and was inexpensive ($98.95, one time fee) compared to manual identification ($1,200/month for clinical trial and $670/month for billing). Automated identification was more efficient and cost-effective than manual identification methods. Repurposing clinical information beyond their traditional use has the potential to improve efficiency and decrease healthcare cost.
机译:信息技术可以提高医疗保健效率。我们使用现有临床信息系统中的数据,开发并实施了一个简单且廉价的工具“自动病例查找和警报系统”(ACAS),以帮助识别可能合格的患者进行临床试验以及为计费目的而遇到的患者。我们通过使用手动识别方法生成的数据计算患者识别中的一致性水平,从而验证了ACAS。两种方法在临床试验(kappa:0.84)和计费(kappa:0.97)之间都达成了实质性共识。自动识别是即时进行的,而临床试验大约为每天2小时/天,计费为1小时10分钟/天,与人工识别(临床试验为1200美元/月和670美元/月,人工识别相比,价格便宜(98.95美元,一次费用)结算)。自动识别比手动识别方法更有效和更具成本效益。重新利用传统用途之外的临床信息具有提高效率和降低医疗保健成本的潜力。

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