Optimal Strategies for PID Prevention and Management

描述(由申请人提供)：多年来，我已经开始掌握决策和成本效益分析技术，使我能够参与几个初级保健传染病项目，作为临床、教育和管理角色的重要职责的副业。为了成为一名独立、严谨的研究人员，我需要更深入的研究培训，并从K23奖项允许的其他职责中解放出来。 职业发展活动的核心将是匹兹堡大学的K30支持的临床研究培训计划，提供必要的临床研究基础知识和生物统计学、决策科学、医学经济学和数据库分析方面的正式培训。除了这个项目，我的主要导师，医学博士，医学博士，MPP马克·S·罗伯茨，将继续我们的长期研究和教育合作。罗伯塔·内斯，医学博士，公共卫生硕士，将担任共同导师，提供妇女健康和性传播疾病流行病学方面的专业知识，并作为盆腔炎评估和临床健康(PEACH)研究的首席研究员，获得关于盆腔炎的评估、治疗和成本的数据。其他顾问将增加患者偏好评估、性传播疾病预防和治疗、模拟建模技术和医疗经济学方面的专业知识。 我的项目将是开发一个临床上现实的PID仿真模型，使用主要收集的患者效用数据以及来自桃子研究和其他来源的数据。对患有盆腔炎的女性的最佳护理将通过综合现有数据进行建模，捕捉循证最佳实践、患者对治疗方案的偏好和健康状况以及盆腔炎及其并发症的成本之间的紧张关系。该模型还将允许检查具有不同风险特征的亚组，以及预防措施对PID发生率、并发症和成本的影响。使用该模型，我们希望探索临床试验不太适合回答的问题，如不同风险亚组中的最优PID管理，PID预防策略的时机，以及不同筛查方法和策略对临床结果和成本的影响。

DESCRIPTION (provided by applicant): Over a period of years, I've begun to master decision and cost-effectiveness analysis techniques, allowing me to embark on several primary care infectious disease projects as a sidelight to significant responsibilities in clinical, educational, and administrative roles. To become an independent, rigorous researcher, I need more thorough research training and the release from other duties that a K23 award allows. The centerpiece of career development activities will be the K30 supported Clinical Research Training Program at the University of Pittsburgh, providing necessary background in clinical research fundamentals and formal training in biostatistics, decision sciences, medical economics, and database analysis. Along with this program, my primary mentor, Mark S. Roberts, MD, MPP, an expert in medical decision sciences, will continue our long-term research and educational collaboration. Roberta Ness, MD, MPH will act as co-mentor, providing expertise on women's health and sexually transmitted disease epidemiology and, as the principal investigator of the PID Evaluation and Clinical Health (PEACH) Study, access to data on the evaluation, treatment, and costs of pelvic inflammatory disease. Other advisors will add expertise in patient preference assessment, sexually transmitted disease prevention and treatment, simulation modeling techniques, and medical economics. My project will be the development of a clinically realistic simulation model of PID, using primarily collected patient utility data as well as data from the PEACH Study and other sources. Optimal care of women with PID will be modeled by synthesis of available data, capturing the tension between evidence-based best practice, patient preferences for therapeutic options and health states, and the costs of PID and its complications. The model will also allow examination of subgroups with different risk profiles and of the impact of preventive measures on PID incidence, complications, and costs. Using the model, we expect to explore questions that clinical trials are not well suited to answer regarding optimal PID management in different risk subgroups, timing of PID preventive strategies, and the impact of different screening methods and strategies on clinical outcomes and costs.