Decision Support for Evaluation of the Febrile Infant

发热婴儿评估的决策支持

• 批准号: 7052833
• 负责人: Carrie L. Byington
• 金额: $ 12.05万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-04-15 至 2010-03-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7052833
• 关键词: antibiotics; bacterial disease; behavioral /social science research tag; clinical research; computer assisted diagnosis; computer assisted medical decision making; diagnosis design /evaluation; diagnosis quality /standard; health care service evaluation; health services research tag; hospital utilization; human data; hyperthermia; infant human (0-1 year); parents; patient oriented research; patient safety /medical error; pediatrics; satisfaction

DESCRIPTION (provided by applicant): The purpose of this K24 application is to support the patient-oriented research performed by Carrie Byington, MD and to provide her with career development opportunities that will enhance her ability to mentor young clinical investigators, especially women and minorities. The research application focuses on the application of computerized decision support to the management of the febrile infant 1-90 days of age. The evaluation and management of fever accounts for 20% of medical encounters in this age group. There is significant variation in the management of febrile infants and this variation has serious implications for patient safety and health care cost. In the last decade, research data has been generated that could be translated into improved quality of care for febrile infants in the US. Using data I have collected and analyzed over the last 9 years, I have developed a method for the management of the febrile infant, that incorporates viral diagnostic testing, that I believe will improve care and patient safety by providing physicians with information needed to calculate an individual infant's risk of bacterial infection. This algorithm exists as a computerized Bayesian model that must be tested prospectively. I hypothesize that 1) There is significant and inappropriate variation among Intermountain Health Care (IHC) physicians in the diagnosis and management of febrile infants, 2) variation will be reduced by the use of a decision support module that is based on a software program that integrates new data and diagnostic methods, and 3) The use of the module will result in a 50% reduction in length of stay and in duration of antibiotic treatment for febrile infants with no increase in missed cases of serious bacterial infection. The Specific Aims of this project are: 1) Determine baseline practices regarding the evaluation and management of febrile infants at three IHC facilities (Primary Children's, Utah Valley, and McKay Dee Medical Centers) from 2000-2004 by analyzing data from the computerized IHC Data warehouse, 2) Implement, during a 24-month period, the decision support tool at the same three hospitals, 3) Compare data obtained before and after computerized decision support was available to determine whether improvements in patient care and safety can be documented. This project can provide data that will improve the care of the febrile infant regionally and can inform future national studies.

描述（由申请人提供）：此 K24 申请的目的是支持医学博士 Carrie Byington 进行的以患者为导向的研究，并为她提供职业发展机会，以增强她指导年轻临床研究人员（尤其是女性和少数族裔）的能力。该研究应用的重点是计算机化决策支持在1-90天龄发热婴儿管理中的应用。发烧的评估和处理占该年龄段医疗事故的 20%。发热婴儿的治疗存在显着差异，这种差异对患者安全和医疗保健成本产生严重影响。在过去的十年中，已经产生的研究数据可以转化为改善美国发热婴儿的护理质量。利用我在过去 9 年中收集和分析的数据，我开发了一种治疗发热婴儿的方法，其中包含病毒诊断测试，我相信该方法将通过向医生提供计算发热婴儿所需的信息来改善护理和患者安全。个别婴儿受细菌感染的风险。该算法作为计算机化的贝叶斯模型存在，必须进行前瞻性测试。我假设 1) 山间医疗保健 (IHC) 医生在发热婴儿的诊断和管理方面存在显着且不适当的差异，2) 通过使用基于软件程序的决策支持模块，可以减少差异集成了新的数据和诊断方法，以及 3) 该模块的使用将导致发热婴儿的住院时间和抗生素治疗持续时间减少 50%，而严重细菌感染的漏诊病例不会增加。该项目的具体目标是： 1) 通过分析计算机化 IHC 数据，确定 2000-2004 年三个 IHC 机构（Primary Children's、Utah Valley 和 McKay Dee 医疗中心）评估和管理发热婴儿的基线实践仓库，2) 在 24 个月期间，在同一三家医院实施决策支持工具，3) 比较计算机决策支持可用之前和之后获得的数据确定是否可以记录患者护理和安全方面的改进。该项目可以提供数据，改善区域内发热婴儿的护理，并为未来的国家研究提供信息。