VA ASSIST Project

VA 协助项目

• 批准号: 8182131
• 负责人: Karl Lorenz
• 金额: --
• 依托单位: VA GREATER LOS ANGELES HEALTHCARE SYSTEM
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-02-01 至 2013-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8182131
• 关键词: Accounting; Address; Advanced Malignant Neoplasm; Adverse effects; Age; Alcoholism; Anorexia; Benchmarking; Bipolar Disorder; Cancer Patient; Capital; Caregivers; Caring; Case Mixes; Characteristics; Chronic; Chronic Disease; Clinical; Clinical Services; Colorectal; Colorectal Cancer; Comorbidity; Complex; Computerized Medical Record; Data; Development; Diagnosis; Diagnostic Neoplasm Staging; Disease; Dyspnea; Effectiveness; Elderly; Eligibility Determination; Ethnic Origin; Etiology; Evaluation; Facility Controls; Family; Fatigue; Funding; Gender; Guidelines; Health Services Research; Healthcare Systems; Hour; Inpatients; Intervention; Investments; Leadership; Life; Linear Regressions; Link; Los Angeles; Lung; Malignant Neoplasms; Malignant neoplasm of lung; Measurement; Measures; Medical; Medicare; Mental Depression; Methodology; Metric; Modeling; National Cancer Institute; Nausea and Vomiting; Needs Assessment; Non-Small-Cell Lung Carcinoma; Nurses; Nursing Staff; Outcome; Outpatients; Pain; Palliative Care; Patients; Performance; Persons; Physicians; Policies; Process; Process Measure; Protocols documentation; Quality Indicator; Quality of Care; Quality of life; Race; Recording of previous events; Registered nurse; Research; Resources; Sampling; Schizophrenia; Selection for Treatments; Services; Solid Neoplasm; Staging; Substance abuse problem; Supportive care; Symptoms; System; Toxic effect; Training; Translating; Uncertainty; Universities; Variant; Veterans; Workload; advanced disease; austin; base; cancer care; cohort; cost; data modeling; evidence base; experience; health care quality; neoplasm registry; oncology; palliative; satisfaction; screening; severe mental illness; tool

Objectives: Using a national random sample of veterans diagnosed with colorectal and nonsmall cell lung cancer drawn from the VA national cancer registry, we will use the Cancer Quality-ASSIST indicator set to evaluate the overall quality of veterans' supportive cancer care, as well as: 1. Patient-level factors and facility factors that may be associated with overall quality, and 2. Whether palliative care services use is associated with higher quality supportive care. Research Plan: We will use the VA national cancer registry and link it to Austin data in order to identify approximately 750 veterans with advanced lung and colorectal cancer. We will conduct remote chart abstraction using the VA electronic medical record and an Access graphical user data entry tool. Methodology: A cohort of veterans with advanced cancer will be developed by obtaining data about incident cases in 2008 with metastatic disease. We will also obtain data about earlier stage incident cases for the previous 2 years. We will link these files with Austin data (patient treatment files) to determine preliminary eligibility (based on inpatient, outpatient usage and disease status). PTF files will provide patient data to supplement patient characteristics obtained from chart review. We will link patient data to KLFMenu files to characterize facilities. Following revision of the Cancer Quality ASSIST guidelines and quality indicator abstraction tool,oncology and other experienced nurses with a background in chart abstraction will train using the ASSIST guidelines and protocol to achieve an initial kappa for key variables of 0.8 or higher. Nurses will follow an abstraction protocol of approximately 2.75 hours / case to evaluate the quality of symptoms related to cancer and its complications, treatment-related toxicities, and information and care planning needs. Palliative care service use and descriptions will be obtained from chart review. Analyses will evaluate the overall quality of supportive cancer care, and control for age, gender, type of cancer, stage, co-morbidity, as well as the analytic variables of race / ethnicity, serious mental illnesses, and palliative care service use. Complete models will control for patient and facility factors. Given likely selection effects, we will explore the use of treatment selection models including propensity matching and instrumental variable analysis to evaluate the effect of service use. We will attempt multivariable linear regression and explore count data models for main models and consider evaluating facility effects with fixed effects and multi-level approaches. Results: This is a new project and results have not yet been obtained. Significance: Information on the quality of supportive care management, veterans who are particularly vulnerable and may receive lower quality supportive care, and the effectiveness of palliative care services in addressing these issues is urgently needed to information programmatic development, and other research and clinical priorities.

目标：使用诊断患有结直肠癌和非小细胞肺的退伍军人的全国随机样本 癌症来自 VA 国家癌症登记处，我们将使用癌症质量-ASSIST 指标集来 评估退伍军人支持性癌症护理的整体质量，以及： 1. 可能与整体质量相关的患者层面因素和设施因素，以及 2. 姑息治疗服务的使用是否与更高质量的支持治疗相关。 研究计划：我们将使用 VA 国家癌症登记处并将其与奥斯汀数据联系起来，以便识别 大约 750 名退伍军人患有晚期肺癌和结直肠癌。我们将进行远程图表 使用 VA 电子病历和 Access 图形用户数据输入工具进行抽象。 方法：通过获取有关事件的数据，将开发一组患有晚期癌症的退伍军人 2008年有转移性疾病病例。我们还将获取有关早期事件案例的数据 前2年。我们将把这些文件与奥斯汀数据（患者治疗文件）联系起来，以确定初步的 资格（基于住院患者、门诊患者的使用情况和疾病状况）。 PTF 文件将提供患者数据 补充从图表审查中获得的患者特征。我们将患者数据链接到 KLFMenu 文件 表征设施。癌症质量 ASSIST 指南和质量指标修订后 抽象工具、肿瘤科和其他具有图表抽象背景的经验丰富的护士将使用 ASSIST 指南和协议，以实现关键变量的初始 kappa 为 0.8 或更高。护士会 遵循大约 2.75 小时/病例的抽象方案来评估与以下相关的症状的质量 癌症及其并发症、治疗相关的毒性以及信息和护理计划需求。姑息治疗 护理服务的使用和描述将从图表审查中获得。分析将评估整体质量 支持性癌症护理，并控制年龄、性别、癌症类型、分期、合并症以及 种族/族裔、严重精神疾病和姑息治疗服务使用的分析变量。型号齐全 将控制患者和设施因素。考虑到可能的选择效应，我们将探索治疗的使用 选择模型，包括倾向匹配和工具变量分析，以评估效果 服务使用。我们将尝试多元线性回归并探索主要模型的计数数据模型 并考虑采用固定效应和多层次方法评估设施效应。 结果：这是一个新项目，尚未获得结果。 意义：有关支持性护理管理质量的信息，特别是退伍军人 弱势群体，可能会接受较低质量的支持性护理，以及姑息治疗服务的有效性 迫切需要解决这些问题，以促进信息规划的发展以及其他研究和 临床优先事项。