Optimizing Imaging Use Among Veterans with Prostate Cancer

优化患有前列腺癌的退伍军人的成像使用

• 批准号: 8399138
• 负责人: DANIL V. MAKAROV
• 金额: --
• 依托单位: VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-10-01 至 2017-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8399138
• 关键词: Address; Affect; Area; Attitude; Behavior; Behavior Therapy; Biological Models; Boxing; Caring; Cost of Illness; Data; Data Analyses; Data Set; Decision Aid; Decision Analysis; Decision Making; Detection; Diagnosis; Diagnostic; Eligibility Determination; Environmental Risk Factor; Evaluation; Fellowship; Foundations; Goals; Guidelines; Health; Health Services; Health Services Research; Healthcare Systems; Image; Interview; Investigator-Initiated Research; K-Series Research Career Programs; Learning; Malignant Neoplasms; Malignant neoplasm of prostate; Medical; Medical center; Medicare; Mentors; Methodology; Methods; Modeling; Odds Ratio; Patients; Pattern; Perception; Physicians; Policies; Probability; Prostate; Provider; Qualitative Methods; Research; Research Methodology; Research Personnel; Research Project Grants; Research Proposals; Risk; Scanning; Science; Source; Staging; Structure; System; Testing; Training; Translations; Urologist; Variant; Veterans; base; cancer care; cancer imaging; cost; design; disease characteristic; experience; health care quality; improved; men; neoplasm registry; payment; provider intervention; public health relevance

DESCRIPTION (provided by applicant): Candidate: Dr. Danil Makarov is a urologist and a fellowship-trained health services researcher. He plans, through this career development award, to gain additional expertise in health services research methodology and behavioral intervention. The candidate will collaborate with his primary mentor, an expert in physician behavioral intervention, as well as others expert in decision science, analysis of large datasets and qualitative methods. Mastery of these methodologies will allow the candidate to become an independent VA investigator, able to identify inefficiencies in medical practice and delivery as well as to design and implement strategies optimizing the delivery of medical care. Background: In the initial evaluation of prostate cancer (the most-commonly diagnosed non-cutaneous malignancy among US men), a patient's chances of receiving guideline-concordant imaging may be more dependent on the region in which he lives than on his disease characteristics. The propensity for clinicians to use imaging may vary across regions like settings on a thermostat, dialed up high in some areas where most patients receive scans and dialed down low in other areas where few are scanned. This suggests that policies focusing solely on reducing inappropriate imaging might simply act by dialing the thermostat down, potentially risking a reduction in appropriate imaging. In order to design and implement policies to optimize prostate cancer imaging, it is important to understand regional variation in prostate cancer imaging and the extent to which the thermostat model contributes to it. Project: The goals of the proposed research project are to understand the scope, the causes and the effects of regional variation in prostate cancer imaging. In Specific Aim #1, the candidate will test the thermostat model in two new datasets comprising patients from the VA Central Cancer Registry and SEER- Medicare, representing systems with different payment models, system structures, and eligibility criteria. To understand further the potential causes of imaging variation the project will explore regional prostate cancer imaging rates across delivery systems (Specific Aim #2) and will contribute further depth and detail to these data using semi-structured interviews (Specific Aim #3) to determine physicians' and patients' attitudes regarding imaging. To determine the effects of regional imaging variation, the candidate will construct a decision analytic model (Specific Aim #4) assessing the tradeoffs in cost and disease detection of various imaging strategies. These model-based strategies will be compared to current care in order to determine the magnitude of possible benefit which a new strategy might deliver. The candidate will learn and utilize both qualitative and quantitative (mixed-methods) methodologies to address this question, as neither method could adequately do so in isolation. He will also learn decision analytic modeling and behavioral intervention, skils essential for the translation of effective practices into large healthcare systems. The candidate plans to use the acquired data and research experience as a foundation for an IIR application to develop and pilot a decision aid and behavioral intervention to optimize imaging use among veterans with incident prostate cancer. PUBLIC HEALTH RELEVANCE: The goals of the proposed research project are to understand the scope, the causes and the effects of regional variation in prostate cancer imaging amongveterans. The candidate will learn and utilize both qualitative and quantitative (mixed-methods) methodologies as well as decision analysis to address this problem. The proposal will serve to improve the quality of healthcare delivered to veterans with prostate cancer and allow the candidate to develop into an independent investigator in the VA focused on cancer-related health services research.

描述（由申请人提供）： 候选人：Danil Makarov博士是一名泌尿科医生，也是一名受过奖学金培训的卫生服务研究员。他计划，通过这个职业发展奖，以获得更多的专业知识，在卫生服务的研究方法和行为干预。候选人将与他的主要导师（医生行为干预专家）以及决策科学、大型数据集分析和定性方法方面的其他专家合作。掌握这些方法将使候选人成为独立的VA调查员，能够识别医疗实践和交付中的效率低下，以及设计和实施优化医疗服务交付的策略。背景资料：在前列腺癌（美国男性中最常诊断的非皮肤恶性肿瘤）的初步评估中，患者接受指南一致性成像的机会可能更多地取决于他所居住的地区，而不是他的疾病特征。临床医生使用成像的倾向可能会因地区而异，就像恒温器上的设置一样，在大多数患者接受扫描的某些地区调高，而在很少扫描的其他地区调低。这表明，仅仅关注减少不适当的成像的政策可能只是通过调低恒温器来采取行动，这可能会降低适当成像的风险。为了 设计和实施政策，以优化前列腺癌成像，重要的是要了解前列腺癌成像的区域变化和恒温器模型在多大程度上有助于it. Project：拟议的研究项目的目标是了解前列腺癌成像的范围，原因和区域变化的影响。在具体目标#1中，候选人将在两个新的数据集中测试恒温器模型，这些数据集包括来自VA中央癌症登记处和SEER- Medicare的患者，代表具有不同支付模式，系统结构和资格标准的系统。为了进一步了解成像变化的潜在原因，该项目将探索各输送系统的区域前列腺癌成像率（具体目标#2），并将使用半结构化访谈（具体目标#3）进一步深入和详细地分析这些数据，以确定医生和患者对成像的态度。为了确定区域成像变化的影响，候选人将构建决策分析模型（特定目标#4），评估各种成像策略的成本和疾病检测的权衡。将这些基于模型的策略与当前的护理进行比较，以确定新策略可能带来的潜在益处的大小。候选人将学习和利用定性和定量（混合方法）方法来解决这个问题，因为任何一种方法都不能单独完成。他还将学习决策分析建模和行为干预，这些技能对于将有效实践转化为大型医疗保健系统至关重要。候选人计划使用获得的数据和研究经验作为IIR应用程序的基础，以开发和试点决策辅助和行为干预，以优化患有前列腺癌的退伍军人的成像使用。 公共卫生关系： 拟议的研究项目的目标是了解前列腺癌成像退伍军人的范围，原因和区域变化的影响。候选人将学习和利用定性和定量（混合方法）方法以及决策分析来解决这个问题。该提案将有助于提高向患有前列腺癌的退伍军人提供的医疗保健质量，并允许候选人发展成为VA的独立调查员，专注于癌症相关的医疗服务研究。