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）： Candidate: Dr. Danil Makarov is a urologist and a fellowship-trained health services researcher.他计划通过这个职业发展奖，以获得卫生服务研究方法和行为干预方面的更多专业知识。候选人将与他的主要导师，医师行为干预专家以及决策科学专家，大型数据集分析和定性方法合作。对这些方法的掌握将使候选人成为独立的VA调查员，能够确定医疗实践和交付效率低下，以及设计和实施优化医疗服务的策略。背景：在对前列腺癌的初步评估（美国男性中最常见的非肉眼恶性肿瘤）中，患者接受指导方面的成像的机会可能更依赖于他所生活的地区，而不是其疾病特征。临床医生使用成像的倾向可能会在恒温器上的设置等区域中有所不同，在某些地区大多数患者接受扫描并在其他很少扫描的地区拨号的地区拨号高。这表明，仅关注不适当成像的政策可能会通过拨动恒温器来起作用，从而有可能减少适当的成像。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以及恒温器模型对其做出贡献的程度。项目：拟议的研究项目的目标是了解前列腺癌成像中区域变化的范围，原因和影响。在特定的目标＃1中，候选人将在两个新数据集中测试恒温器模型，其中包括来自VA中央癌症注册表和Seer-Medicare的患者，代表具有不同支付模型，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，该项目将探索跨递送系统的区域前列腺癌成像率（特定目的＃2），并将使用半结构化访谈（特定目的＃3）为这些数据提供进一步的深度和细节，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，候选人将构建一个决策分析模型（特定目的＃4），以评估各种成像策略的成本和疾病检测方面的权衡。这些基于模型的策略将与当前的护理进行比较，以确定新策略可能提供的可能收益的幅度。候选人将学习并利用定性和定量（混合方法）方法来解决这个问题，因为两种方法都不能孤立地做到这一点。他还将学习决策分析建模和行为干预，这对于将有效实践转化为大型医疗保健系统至关重要。候选人计划利用获得的数据和研究经验作为IIR应用程序的基础，以开发和试行决策援助和行为干预措施，以优化患有前列腺癌的退伍军人的成像使用。 公共卫生相关性： 拟议的研究项目的目标是了解前列腺癌成像中区域变化的范围，原因和影响。候选人将学习并利用定性和定量（混合方法）方法以及解决此问题的决策分析。该提案将有助于提高为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弗吉尼亚州的独立调查员，该研究人员着重于癌症相关的医疗服务研究。