Computerized Decision Support for Managing Lung Nodules

描述（由申请人提供）：临床实践指南是将研究结果转化为实践的重要工具。理想情况下，遵循循证指南应减少医疗资源利用中不必要的变化，控制成本并改善临床结果。然而，要在地方一级成功执行准则，就需要克服多重障碍。其中一个障碍是认为指南中的一般建议不适用于特定患者或实践环境。为了解决这一问题和其他已知的实施障碍，我们建议扩展以前的工作，我们开发和测试了一个基于计算机的决策支持系统，该系统可以生成基于证据的，针对特定患者的建议，用于预防高危人群的心脏性猝死。在拟议的研究中，我们调整我们的系统，并评估其对孤立性肺结节患者的管理的影响。肺结节的管理是基于计算机的决策支持的一个非常有吸引力的目标。这是一个常见的问题，在初级保健和专业设置，多种可能的管理策略存在，最佳的管理方法取决于预测试的概率，手术并发症的风险，和其他几个因素。我们的目的是证明决策支持可以提高孤立性肺结节患者的诊断和管理。 为了实现这一总体目标，我们有三个具体目标：（1）开发ALCHEMIST-SPN，一个交互式决策支持系统，用于孤立性肺结节患者的管理，通过连接已发表的决策分析模型和现有的基于计算机的决策支持体系结构;（2）验证ALCHEMIST-SPN决策支持系统生成的预测;以及（3）通过要求医生参与者管理一系列基于患有已知原因的肺结节的实际患者的临床小插曲，来进行用于肺结节管理的基于计算机的决策支持的对照交叉试验。 通过完成这些目标，我们将：（1）证明创造和实施循证实践建议的创新策略的有用性;（2）确认我们的决策支持系统可以推广到比我们以前工作中评估的管理问题复杂得多的管理问题;以及（3）为在真实的临床环境中使用ALCHEMIST-SPN进行基于计算机的决策支持的随机试验奠定基础。

DESCRIPTION (PROVIDED BY APPLICANT): Clinical practice guidelines are an essential tool for translating research findings into practice. Ideally, adherence to evidence-based guidelines should reduce unnecessary variation in the utilization of health care resources, contain costs and improve clinical outcomes. However, successful implementation of guidelines at the local level requires overcoming multiple barriers. One such barrier is a perception that the general recommendations found in guidelines do not apply to specific patients or practice settings. To address this and other known barriers to implementation, we propose to extend previous work in which we developed and tested a computer-based decision support system that generates evidence-based, patient-specific recommendations for the prevention of sudden cardiac death in at-risk populations. In the proposed research, we adapt our system and evaluate its impact on the management of patients with solitary pulmonary nodules. Management of lung nodules is a very attractive target for computer-based decision support. It is a common problem in both primary care and specialty settings, multiple possible management strategies exist, and the optimal management approach depends on pre-test probability, the risk of surgical complications, and several other factors. We aim to demonstrate that decision support can improve diagnosis and management in patients with solitary pulmonary nodules. To achieve this overall goal, we have three specific aims: (1) to develop ALCHEMIST-SPN, an interactive decision support system for management of patients with solitary pulmonary nodules, by linking a published decision analysis model and an existing architecture for computer-based decision support; (2) to validate the predictions generated by the ALCHEMIST-SPN decision support system; and (3) to conduct a controlled, cross-over trial of computer-based decision support for pulmonary nodule management by asking physician participants to manage a series of clinical vignettes that are based on actual patients with pulmonary nodules of known cause. By completing these aims, we will: (1) demonstrate the usefulness of an innovative strategy for creating and implementing evidence-based practice recommendations; (2) confirm that our system for decision support can be generalized to a management problem that is considerably more complicated than the one evaluated in our previous work; and (3) set the stage for a randomized trial of computer-based decision support with ALCHEMIST-SPN in real world clinical settings.