Recommendations and Interventions for and Changes in the Ocular Health and visual Function of Veterans with Traumatic Brain Injury

超过65%的爆炸相关和非爆炸相关创伤性脑损伤患者报告 视力问题。创伤性脑损伤（TBI）相关的视觉障碍不仅会损害大脑， 眼睛，但视觉（感觉和眼运动）通路和/或皮质处理区。因此，在本发明中， 与眼睛相关的失明或低视力的传统目标和治疗计划可能不 适用于战斗和TBI相关的视力损伤。2008年，退伍军人健康管理局 (VHA)2008 - 065号指令，标题为"特定眼部创伤性脑损伤的性能" 多发伤康复中心患者的健康和视觉功能检查" 规定所有被诊断为TBI的患者， 康复中心（PRC）进行TBI特定的眼部健康和视觉功能检查 由验光师或眼科医生进行。几项研究已经确定了 这一群体的生物学;然而，这一规定所产生的服务提供数据 考试没有分析。这项研究将评估如何选择尝试， 组织护理结构（指令2008 - 065）影响视力健康的获得和利用 护理服务。具体目标是：（1）确定获取和利用 在有视力和眼部缺陷的TBI退伍军人中提供的服务;（2）描述康复服务 分娩;和（3）通过视觉和眼部结果来探索临床恢复。这 一项基于人群的研究将采用回顾性队列设计和前瞻性调查组成部分 找出跟进预约的障碍。人口定义为所有退伍军人， 五个VHA PRC之一收治的TBI现役军人（约n = 2，500）。 患者标识符（退伍军人和现役军人）由物理医学提供， 国家康复计划办公室。使用VA信息学和计算基础设施 在工作空间中，结构化和非结构化数据都将用于创建分析数据集。 结构化数据将从企业数据仓库的相关数据表中提取。 非结构化数据将从存储在电子健康记录中的文本文档中提取， 存储在企业数据仓库中，使用信息提取系统。提取 方法包括专家手动图表审查，自然语言处理，命名实体 识别、机器学习和特殊方法，如手工规则或正则表达式。 提取的数据将由眼科和视力专家组成的专家小组进行验证 来自五个PRC中的每一个，多创伤护理系统，以及911前视力和盲人服务 诊所。地理信息系统工具将用于确定地理准入（ 驾驶距离和驾驶时间）到健康服务。最终的数据集将由不同的变量组成 包括患者特征、治疗建议、访问因素、设施位置， 诊所就诊，治疗/辅助设备，以及患者水平的结果， 变量之间的依赖关系，所有这些变量都以复杂的非线性方式相互关联。 将使用频率论和贝叶斯网络方法分析数据。这项研究的影响 关于退伍军人和VHA护理系统将制定建议，以改善 通过改善获得和利用与创伤性脑损伤有关的高质量视力， 服务这将通过将中国的专业知识转化为非专业知识来实现 VHA设施更接近患者的住所。

More than 65% of patients with blast-related and non-blast-related traumatic brain injuries report vision problems. Traumatic brain injury (TBI) related visual impairment can damage not only the eye, but the visual (sensory and ocular-motor) pathways and/or cortical processing areas. Thus, the traditional objectives and treatment plans for eye-related blindness or low-vision may not be appropriate for combat and TBI related vision injuries. In 2008, the Veteran Health Administration (VHA) published Directive 2008-065 titled “Performance of Traumatic Brain Injury Specific Ocular Health and Visual Functioning Examinations for Polytrauma Rehabilitation Center Patients” specifying that all patients with a diagnosis of TBI who are admitted to VHA Polytrauma Rehabilitation Centers (PRCs) have a TBI-specific ocular health and visual functioning examination performed by an optometrist or ophthalmologist. Several studies have identified the prevalence and symptomology of this cohort; however, the service delivery data generated by this mandated exam have not been analyzed. The purposed study will evaluate how a selected attempt to organize the structure of care (Directive 2008-065) affects access to and utilization of vision health care services. The Specific Aims are to (1) Determine the pattern of access to and utilization of services among Veterans with TBI with visual and ocular deficits; (2) Describe rehabilitation service delivery; and (3) Explore clinical recovery as measured by visual and ocular outcomes. This population-based study will use a retrospective cohort design with a prospective survey component to identify access barriers to follow up appointments. The population is defined as all Veterans and active duty service persons with TBI admitted to one of the five VHA PRCs (approximate n=2,500). Patient identifiers (both Veteran and active duty) are provided by the Physical Medicine and Rehabilitation National Program Office. Using the VA Informatics and Computing Infrastructure workspace, both structured and unstructured data will be used to create an analytic data set. Structured data will be extracted from relevant data tables from the Corporate Data Warehouse. Unstructured data will be extracted from text documents stored in the electronic health record, also housed in the Corporate Data Warehouse, using an Information Extraction system. Extraction methods include manual chart review by experts, natural language processing, named entity recognition, machine learning and ad-hoc methods like handcrafted rules or regular expressions. Extracted data will be validated by an Expert Panel composed of oculomotor and vision experts from each of the five PRCs, the Polytrauma System of Care, and pre-911 vision and blind services clinics. Geographic Information System tools will be used to determine geographic access (both drive distance and drive time) to health services. The final dataset will consist of diverse variables including patient characteristics, treatment recommendations, access factors, facility locations, clinic visits, treatments/assistive devices, and patient-level outcomes with substantial inter- dependencies among the variables, all of which are interrelated in a complex non-linear fashion. Frequentist and Bayesian Network methods will be used to analyze data. The impact of this study on Veterans and the VHA system of care will be the development of recommendations to improve community reintegration by improving access to and utilization of quality TBI-related vision services. This will be accomplished by translating PRC specialized knowledge to non-specialized VHA facilities closer to the patients' residences.