Precursors of first-episode psychosis in a population-based sample

描述(申请人提供)：在15至44岁的人群中，精神分裂症估计是因伤残和过早死亡而丧失的寿命年数排名第八的原因。减轻这一疾病负担是公共卫生的优先事项。在首次出现精神病症状的人中，延迟接受有效治疗极大地导致长期结果不佳。此外，警示迹象或前驱症状可以在实际的精神病症状出现之前识别出来。越来越多的证据表明，预防性干预(在实际精神病症状出现之前)或早期临床干预(缩短症状出现和接受有效护理之间的间隔)都可以改善长期预后。现有的早期检测和早期干预模式--无论是用于研究还是提供护理--的覆盖范围和可扩展性有限。我们的初步研究表明，一种可追溯到电子病历数据的通用算法可以准确地识别首发精神病发作，阳性预测值为80%至90%，而 敏感度超过80%-与结构化图表审查相比。如果大型卫生系统中的电子记录可以有效地识别首发精神病患者的大样本和有代表性的样本，这种方法可以极大地加快研究和改变医疗服务的提供。我们提出了一个基于人群的研究计划，以解决有关早期干预计划的紧迫问题，并开发支持下一代早期干预研究的方法。这项研究将从5个大型卫生系统中提取数据，这些系统为超过750万人的多样化和代表性人口提供服务。该计划的具体目标包括：1)使用来自大型综合医疗保健系统的电子记录数据来验证和改进用于识别首发精神病症状的通用算法。2)在首次诊断精神病之前检查卫生保健接触的模式，以确定早期发现计划和预防干预的最佳护理环境和目标人群。3)检查首次诊断为精神病后的治疗模式，以确定导致未治疗精神病持续时间延长的护理差距。4)在首次诊断精神障碍时检查医疗保险的覆盖来源，以及随后的保险失误，以便为未来干预计划的设计提供信息。5)探索使用文本挖掘方法在精神病首次诊断前的门诊就诊笔记中识别潜在的前驱症状指标，以开发准确实时识别前驱症状的创新策略。6)了解患者、家庭和临床医生对精神病新诊断后基于人群的研究推广的观点--为未来的研究和护理提供信息。

DESCRIPTION (provided by applicant): Schizophrenia is estimated to be the 8th-ranked cause of life years lost to disability and premature death among people aged 15 to 44. Reducing this disease burden is a public health priority. Among people experiencing first onset of psychotic symptoms, delay in receipt of effective treatment contributes significantly to poor long-term outcomes. Furthermore, warning signs or prodromal symptoms may be identifiable prior to onset of actual psychotic symptoms. Accumulating evidence suggests that preventive interventions (prior to onset of actual psychotic symptoms) or early clinical interventions (to reduce the interval between onset of symptoms and receipt of effective care) can both improve long-term prognosis. Existing models for early detection and early intervention - either for research or care delivery - have limited reach and scalability. Our preliminary studies suggest that a generalizable algorithm retrospectively applied to electronic medical records data can accurately identify first episodes of psychosis with a positive predictive value of 80 to 90% and a sensitivity of over 80% - when compared to structured chart review. If electronic records in large health systems could be used to efficiently identify large and representative samples of people experiencing first- episode psychosis, this method could dramatically accelerate research and transform care delivery. We propose a population-based research program to address immediate questions regarding early intervention programs and to develop methods to support the next generation of early intervention research. This research will draw from 5 large health systems serving a diverse and representative population of over 7.5 million people. Specific aims of this program include: 1) Use electronic records data from large integrated health care systems to validate and refine a generalizable algorithm for identifying first presentations of psychosis. 2) Examine patterns of health care contact prior to first diagnosis of psychosis to identify the optimal care settings and target populations for early detection programs and preventive interventions. 3) Examine patterns of treatment following first diagnosis of psychosis in order to identify the gaps in care leading to prolonged duration of untreated psychosis. 4) Examine sources of health insurance coverage at first diagnosis of psychotic disorder and subsequent lapses in coverage in order to inform the design of future intervention programs. 5) Explore the use of text mining methods to identify potential indicators of prodromal symptoms in notes of outpatient visits prior to first diagnosis of psychosis in order to develop innovative strategies for accurate real-time identification of prodromal symptoms. 6) Understand patient, family, and clinician perspectives regarding population-based research outreach following a new diagnosis of psychosis - to inform future research and care delivery.