Improving Palliative Measurement Application with Computer-Assisted-Abstraction Study

通过计算机辅助抽象研究改进姑息测量应用

• 批准号: 10216351
• 负责人: Karl Lorenz
• 金额: --
• 依托单位: VETERANS ADMIN PALO ALTO HEALTH CARE SYS
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10216351
• 关键词: Advanced Malignant Neoplasm; Affect; American; Attention; Boston; Cancer Center; Caregivers; Caring; Characteristics; Clinical; Communication; Communities; Computer Assisted; Consultations; Consumption; Data; Disease; Ethnic Origin; Family; Family member; Fostering; Goals; Healthcare; Healthcare Systems; Hospitals; Improve Access; Intervention; Interview; Learning; Life; Life Experience; Machine Learning; Malignant Neoplasms; Manuals; Measurement; Measures; Medical Records; Medicare; Mental Health; Methodology; Methods; Monitor; Natural Language Processing; Opioid; Pain; Pain management; Palliative Care; Participant; Patients; Performance; Policies; Process; Process Measure; Provider; Quality of life; Race; Research; Risk; Rural; Sampling; Site; Surveys; Symptoms; System; Text; Time; United States; United States Department of Veterans Affairs; Variant; Veterans; Voice; Work; base; cancer care; cancer therapy; care systems; cost; end of life; end of life care; experience; health care disparity; health care service utilization; health care settings; health goals; hospice environment; improved; innovation; operation; palliative; racial and ethnic disparities; recruit; response; rural residence; side effect; systematic review

Background: VA needs to incorporate the Veteran and family voice in measuring performance, and it may improve care to involve Veterans and families more deeply in improvement. This is especially true for palliative and end of life care, given the 30% of lifetime Medicare costs in the last year of life, and the divergent perspectives that Americans have expressed regarding end of life care. We have identified major gaps in VA performance, but work is needed to prioritize indicators from the Veteran and family perspective and to improve measure feasibility. The latter will foster better VA quality and experience of care and facilitate monitoring the potential impact of paid, non-VA care on seriously ill Veterans. Aims: The Improving Palliative Measurement Application with Computer-Assisted-Abstraction Study (ImPACS), will prioritize measures and operationalize a subset of higher, intermediate, and lower feasibility process and utilization measures for palliative and end of life cancer care. We aim to: Aim 1: Solicit priorities from two Delphi panels - one of Veterans and families and a second of experts regarding process and healthcare use quality measures for advanced cancer care, including which of the 42 Cancer Quality ASSIST measures to extract, and conduct interviews regarding how to integrate Veterans and families in VA measurement and improvement for palliative and end of life cancer care, and Aim 2: Extract high priority process and utilization measures using natural language processing of VA charts and administrative data and in a sample drawn from Stanford and Dana Farber’s Healthcare's Epic systems, focusing on the domains of pain and opioids, mental health, and goals of care communication, and Aim 3: Examine associations of the extracted measures with Veteran characteristics, focusing on disparities in the care of rural and nonwhite Veterans and palliative care use. Methods: For Aim 1, we will recruit two Delphi panels - one of Veterans, family members, and a second of expert stakeholders. Veteran-family members will have experience with cancer. Experts will have expertise in the methods and application of quality measures. Purposive sampling will focus on critical attributes (e.g., race) that may affect priorities. Panelists will rate and rank measures within tiers of high, intermediate, and low feasibility, informed by reviews of the evidence for intervention and impact of performance gaps on patients and caregivers. We will also interview Veterans, family members and VA leaders at high and low performing VA facilities based on the Bereaved Family Survey of end of life experience, to see how deeper Veterans-family involvement might strengthen quality and experience of end of life care. For Aim 2, we will operationalize a subset of prioritized process measures from Aim 1 including Cancer Quality ASSIST measures using natural language processing of text notes and machine learning. In Aim 3, we will characterize variation in measures with Veteran characteristics focusing on known disparities among rural and nonwhite Veterans and palliative care services use. Impact: We will produce Veteran and family-informed priorities for a balanced measure set for palliative and end of life cancer care. We will inform how Veterans and families might be more deeply engaged in fostering improved quality and experience and fostering a learning healthcare system. Finally, we will extract prioritized measures using state of the art methods to improve their feasibility, characterize variation at the Veteran level focused on known disparities and palliative care potential to mitigate them.

背景：VA需要将资深人士和家庭声音纳入衡量表现，并且可能 改善护理，使退伍军人和家庭更深入地改善。尤其如此 鉴于生命的最后一年的终身医疗保险费用的30％，以及生命的终结 美国人对生命终结的看法有分歧的观点。我们已经确定了专业 VA性能的差距，但是需要工作以确定老兵和家人的指标 视角并提高测量可行性。后者将培养更好的VA质量和经验 护理并促进监测付费，非VA护理对严重病重的退伍军人的潜在影响。 目的：通过计算机辅助研究的改进的姑息测量应用 （IMPAC），将优先考虑措施并运行较高，中间和较低的可行性子集 姑息治疗和生命终止癌症护理的过程和利用措施。我们的目标是： 目标1：从两个德尔菲面板征求优先事项 - 一名退伍军人和家庭和第二个专家 关于流程和医疗保健使用高级癌症护理的质量措施，包括哪些 42癌症质量辅助措施提取并进行有关如何整合的访谈 在VA测量和改进的姑息治疗和寿命终止的退伍军人和家庭，以及 目标2：使用VA的自然语言处理提取高优先级过程和利用措施 图表和行政数据以及来自斯坦福大学和Dana Farber的Healthcare的样本 史诗系统，重点关注疼痛和阿片类药物的领域，心理健康和护理目标 沟通和 目标3：检查提取的措施与退伍军人特征的关联，重点 护理和非白人退伍军人以及姑息治疗的差异。 方法：对于AIM 1，我们将招募两个Delphi面板 - 一名退伍军人，家庭成员，第二个 专家利益相关者。资深家庭成员将有癌症经验。专家将拥有专业知识 在质量措施的方法和应用中。目的抽样将集中于关键属性 （例如，种族）可能会影响优先事项。小组成员将在高级级别内进行评分和排名措施 中级和低可行性，通过审查干预和影响的证据的审查 患者和护理人员的表现差距。我们还将采访退伍军人，家庭成员和弗吉尼亚州 基于死去的家庭终结调查，高和低表现的VA设施的领导者 经验，看看有多么深的退伍军人参与可以增强质量和经验 生命的尽头。对于AIM 2，我们将对AIM 1的优先过程度量进行操作。 包括癌症质量辅助措施，使用文本注释和机器的自然语言处理 学习。在AIM 3中，我们将表征具有重点关注的资深特征的测量差异 艰难和非白人退伍军人和姑息治疗服务的已知分布使用。 影响：我们将生产老兵和家庭形式的优先级，以用于姑息治疗 和生命癌症护理的结束。我们将告知退伍军人和家庭如何更深入地参与 促进提高质量和经验，并培养学习医疗系统。最后，我们会的 使用最新方法提取优先措施来提高其可行性，表征 退伍军人水平的变化集中在已知差异和姑息治疗潜力上，以减轻它们。