VIDEO INTERVENTION/PREVENTION ASSESSMENT-TRANSITIONS

Michael Rich，医学博士，MPJ，是一名青少年医学医师，具有特殊的临床专业知识和对慢性疾病的研究兴趣。他特别感兴趣的是调查病人的疾病经历，以开发有效和敏感的病人需求的医疗保健服务。1998年，他因创新的以患者为中心的研究方法“视频干预/预防评估”（VIA）而获得美国青少年医学学会1998年度新研究者奖。VIA源自已建立的社会科学研究方法，是一种定性技术，通过分析患者的“真实生活”疾病和医疗保健经历的“视频日记”，向临床医生传授疾病和残疾，因为它存在于他们的生活、环境和哮喘的社会心理特征中，这些在以前是传统调查技术无法获得的。获得K23奖将使Rich博士能够推进他的研究事业，并通过在基础研究方法和分析技术方面的正式课程学习，在医学博士Donald Goldmann的赞助指导下，通过整合临床有效性的定量测量，以及在共同导师的指导下工作，进一步发展VIA方法，这些导师是VIA研究领域的领先专家，包括视觉人类学，定性研究方法，以及定量和定性的卫生服务研究。研究计划将VIA应用于患有慢性、功能受限疾病和特殊卫生保健需求的年轻人从儿科向成人卫生保健系统的过渡的检查。VIA过渡期研究主要针对骨髓发育不良/脊柱裂和镰状细胞病患者，将采用临床、定性和定量手段调查：1)在从儿科护理过渡到成人护理之前、期间和之后，患者的健康相关生活质量（HRQL）是什么？2)患者在每个过渡阶段的需求是什么？这些需求得到了怎样的满足？3)对于有复杂需求和功能受限状况的患者，过渡性护理的经验是什么？研究参与者将通过临床访谈和标准化的HRQL工具进行评估，然后在三个时间点对他们的疾病经历进行视觉叙述：1)当他们在儿科医疗系统的护理下时，2)当他们离开儿科并开始在成人医疗系统中护理时，以及3)在他们建立了大约一年的成人护理之后。视觉叙事将被编码，并与来自临床访谈和HRQL工具的数据进行三角测量，以确定一致性和不一致性。这一发现将被应用于设计对患者更为敏感的过渡方案和管理策略。将VIA应用于一个新的临床问题，并分析来自原始哮喘试点和过渡研究的数据。Rich博士将完善和修改这种调查方法，使其足够灵活，可以应用于广泛的临床问题，同时保留所得数据的丰富性。

Michael Rich, MD, MPJ, is an Adolescent Medicine physician with special clinical expertise and research interest in chronic diseases. He is particularly interested in investigating the patient's illness experience in order to develop health care delivery that is effective and sensitive to patient needs. In 1998 , he was awarded the 1998 New Investigator Award of the Society for Adolescent Medicine for his innovative patient- centered research method, Video Intervention/Prevention Assessment (VIA). Derived from established social science research methods, VIA is a qualitative technique which analyzes "video diaries" created by patients of their "real life" experiences with illness and health care to teach clinicians about disease and disability as it exists in the contexts of their lives, environments, and psychosocial features of asthma which had previously been inaccessible to traditional investigative techniques. A K23 award would allow Dr. Rich to advance this research career and further develop the VIA methodology through formal course work in the underlying research methods and analytical techniques, by integrating quantitative measures of clinical effectiveness under the sponsoring mentorship of Donald Goldmann, MD, and by working under the guidance of co-mentors who are leading experts in the research fields which inform VIA, including visual anthropology, qualitative research methods, and quantitative and qualitative health services research. The Research Plan applies VIA to the examination of the transition from pediatric to adult health care systems by young people with chronic, function-limiting conditions and special health care needs. Focusing on patients with myelodysplasia/spina bifida and sickle cell disease, the VIA Transitions study will use clinical, qualitative, and quantitative means to investigate: 1) What is the patient's health-related quality of life (HRQL) before, during, and after transition from pediatric to adult care? 2) What are the patient's needs at each stage of transition and how well are they being met? 3) What is the experience of transitioning care for a patient with complex needs and a function-limiting condition? Study participants will be assessed with clinical interviews and standardized HRQL instruments before making visual narratives of their illness experience at three points: 1) while they are under the care of the pediatric medical system, 2) when they leave pediatrics and initiate care in the adult health care system, and 3) after they have established their adult care for approximately one year. The visual narratives will be coded and triangulated with the data derived from clinical interviews and HRQL instruments for areas of congruence and dissonance. The finding swill be applied to the design of more patient-sensitive transition programs and management strategies. Applying VIA to a new clinical problem and analyzing the data from the original asthma pilot and the Transitions study. Dr. Rich will refine and modify this investigative methodology so that it is flexible enough to be applied to a broad range of clinical questions while retaining the richness of the data derived.