Using Pre-Operative Variables to Predict Length of Stay

使用术前变量预测住院时间

• 批准号: 6934766
• 负责人: KATHERINE S ROWELL
• 金额: $ 17.5万
• 依托单位: QCMETRIX, INC.
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-06-01 至 2006-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6934766
• 关键词: Using; Pre; Operative; Variables; Predict

DESCRIPTION (provided by applicant): Abstract: QCMetrix, Inc. is proposing to research and develop innovative software that will use patient-specific peri-operative risk variables to project in real-time that patient's post-operative length of stay. The proposed software will combine proven statistical modeling techniques with a database of over 1 million surgical cases performed at fourteen major academic health centers nationwide and in the Veterans Administration hospital system. These data continue to be accumulated in the database of the National Surgical Quality Improvement Program (NSQIP) through continued data capture in the VA and through the AHRQ-funded Patient Safety in Surgery Study (PSS). Beyond the term of this project, the objective is to extend the modeling of patient's peri-operative risk factors using NSQIP data to predict post-operative morbidity and mortality for the purpose of real-time clinical management of the surgical patient and advanced, prospective clinical quality improvement. Proposed Commercial Applications: The potential users of this software include surgeons, hospital managers, nursing and affiliated clinical support staffs involved in the care and management of the surgical patient. This software will be the first to use real-time, patient-specific information to project that patient's likely length of stay. This is a critical tool for clinicians and managers who are faced with the daily burden of balancing the demands for surgical bed capacity between the demand from elective surgeries and the demands of emergency care. Additionally, this tool may prove useful to project and manage staffing demands for the surgical floors. Beyond the scope of this project, this underlying statistical projection techniques will be utilized to inform clinicians and patients about the risks of post-operative morbidity and mortality related to their specific surgery and to define, using evidence-based medicine, optimal treatment of the surgical patient in real time.

描述（由申请人提供）： 翻译后摘要：QCMemetry，公司。正在提议研究和开发创新软件，该软件将使用患者特定的围手术期风险变量来实时预测患者的术后住院时间。拟议的软件将结合联合收割机证明统计建模技术与数据库的100多万例手术中进行的14个主要学术卫生中心全国和退伍军人管理局医院系统。通过VA中的持续数据采集和AHRQ资助的手术患者安全性研究（PSS），这些数据继续在国家手术质量改进计划（NSQIP）的数据库中积累。在本项目期限之外，目标是使用NSQIP数据扩展患者围手术期风险因素的建模，以预测术后发病率和死亡率，从而实现手术患者的实时临床管理和先进的前瞻性临床质量改进。 建议的商业应用：该软件的潜在用户包括外科医生、医院管理人员、护理人员和参与手术患者护理和管理的附属临床支持人员。该软件将是第一个使用实时的、患者特定的信息来预测患者可能的住院时间的软件。这是临床医生和管理人员的一个重要工具，他们每天都面临着在择期手术需求和紧急护理需求之间平衡手术床容量需求的负担。此外，该工具可能被证明是有用的项目和管理人员需求的手术楼层。在本项目的范围之外，将利用这种基本的统计预测技术，告知临床医生和患者与其特定手术相关的术后发病率和死亡率风险，并使用循证医学，在真实的时间内确定手术患者的最佳治疗。