Cognitive Basis of CHD Disparities: Factorial Experiment
Cognitive Basis of CHD Disparities: Factorial Experiment
批准号:
7048016
负责人:
John B McKinlay
金额:
$44.52万
依托单位国家:
美国
项目类别:
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-03-20 至 2009-01-31
关键词:
age differencebehavior testbehavioral /social science research tagbiasclinical researchcoronary disorderdecision makingdiagnosis design /evaluationdiagnosis quality /standardgender differencehealth care personnel performancehealth care service evaluationhealth disparityhealth services research tagheart disorder diagnosishuman subjectpatient care personnel attitudepatient care planningpatient oriented researchracial /ethnic differencesocioeconomicsvideotape /videodisc
中文摘要
描述(由申请人提供):这项研究代表了临床决策研究的范式转变,将重点从前三代工作转移到新的“第四代”认知(和推理)过程研究。这项基于理论的研究直接(且具有成本效益)建立在成功完成的研究基础上,这些研究使用实验(析因)设计,并证明患者属性(性别,年龄,种族和SES),提供者特征(性别,医学专业和临床经验年数)和医疗保健系统特征独立影响(大多数p<.001)冠心病(CHD)的诊断和管理。关于CHD的临床决策(CDM)取决于患者是谁,提供者是谁以及提供护理的环境,因为患者实际表现(CHD的体征/症状)。该研究将描述如何并解释为什么(而不仅仅是)不同的医生,在不同的实践环境中,在相当的患者中,在广泛的CHD护理中存在差异。这个项目有四个目标。(1)评估两种认知实验操作的独立影响:(a)医生对CHD可能性的认知“启动”;(B)据称与CHD相关的患者属性的系统替代;对以下主要结局的影响:CHD诊断的概率,回忆的诊断特征的数量和类型,以及CHD诊断的时间。认知干预(a)对干预(B)的影响将提供分析与非分析推理的估计效果(即,故意与非故意折扣),由主要结果衡量。(2)了解患者属性如何干扰医生的认知推理过程,从而产生所观察到的CHD变异。(3)解释,使用认知分析,供应商的特点如何有助于记录冠心病的变异性。(4)了解组织的影响如何也侵入CHD决策。来自纽约州的初级保健提供者(遇到大多数CHD的人)将被随机抽样(n=256),并被邀请观看临床上真实的CHD体征/症状“患者”的录像演示。将通过结构化访谈获得关于主要结局(CHD诊断概率)和一系列充分合理的次要结局的信息。析因设计允许估计独立(无混杂)主效应和所有双向相互作用。从拟议的研究结果可以减少或消除至少两种类型的干预措施的医疗保健变化:(a)组织和报销政策可以制定和评估,引导供应商远离模式的决策,产生医疗保健的变化;(B)在医学教育的干预措施,当实践风格尚未牢固确立。
英文摘要
DESCRIPTION (provided by applicant): This research represents a paradigm shift in studies of Clinical Decision Making by moving the focus from three earlier generations of work to a new "fourth generation" study of cognitive (and reasoning) processes. This theoretically based study builds directly (and cost efficiently) on successfully completed studies which used experimental (factorial) designs and demonstrate that patient attributes (gender, age, race and SES), provider characteristics (gender, medical specialty and years of clinical experience) and health care system characteristics independently influence (most p<.001) the diagnosis and management of Coronary Heart Disease (CHD). Clinical decision-making (CDM) with respect to CHD is shaped as much by who the patient is, who the provider is and the setting in which care is provided as it is by what the patient actually presents (the signs/symptoms of CHD). The study will describe how and explain why (and not simply that) different physicians, in different practice settings evidence variations in a broad-range of CHD care with equivalent patients. This project has 4 aims. (1) To estimate the independent effects of two cognitive experimental manipulations: (a) cognitive "priming" of physicians as to CHD possibility; and (b) systematic substitution of patient attributes purportedly associated with CHD; on the following primary outcomes: probability of a CHD diagnosis, the number and type of diagnostic features recalled, and the timing of CHD diagnosis. The impact of cognitive intervention (a) on intervention (b) will provide estimated effects of analytic vs. non- analytic reasoning (i.e., intentional vs. non-intentional discounting) as measured by the primary outcomes. (2) To understand how patient attributes intrude on physicians' cognitive reasoning processes to produce the observed CHD variations. (3) To explain, using cognitive analysis, how provider characteristics contribute to the documented CHD variability. (4) To understand how organizational influences also intrude on CHD decision-making. Primary care providers (who encounter most CHD) from New York State will be randomly sampled (n=256) and invited to view a clinically authentic videotaped presentation of a "patient" presenting with signs/symptoms of CHD. Information concerning the primary outcome (probability of CHD diagnosis) and a range of well-justified secondary outcomes will be elicited through structured interviewing. The factorial design permits estimation of independent (unconfounded) main effects and all two-way interactions. Results from the proposed research could reduce or eliminate health care variation in at least two types of interventions: (a) Organizational and reimbursement policies could be developed and evaluated which steer providers away from the patterns of decision-making which produce healthcare variations; (b) Interventions during medical education, when practice styles are not yet firmly established.
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