Applying Positive Deviance Methods to Harness Optimal Practices for Effective Pain Management in Community Living Centers

应用正偏差方法来利用最佳实践，在社区生活中心进行有效的疼痛管理

• 批准号: 10443564
• 负责人: Camilla Benedicto Pimentel
• 金额: --
• 依托单位: EDITH NOURSE ROGERS MEMORIAL VETERANS HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10443564
• 关键词: Adoption; Area; Caring; Characteristics; Chronic Disease; Clinical; Clinical effectiveness; Collaborations; Custom; Data; Data Set; Development; Disabled Persons; Disease Management; Diving; Elderly; Evidence based intervention; Excision; Feedback; Future; Geriatrics; Gerontology; Goals; Growth; Health; Health Services Research; Healthcare; Home; Hybrids; Intervention; Intervention Studies; K-Series Research Career Programs; Knowledge; Lead; Learning; Long-Term Care; Measurement; Measures; Medicare/Medicaid; Mentors; Mentorship; Methodology; Methods; Modeling; Monitor; Nursing Homes; Opioid; Outcome; Pain; Pain Clinics; Pain Measurement; Pain management; Pain quality; Patients; Pattern; Performance; Policies; Practice Management; Preparation; Process; Provider; Qualitative Evaluations; Qualitative Research; Quality of life; Randomized; Reaction; Reporting; Research; Research Design; Risk; Risk Adjustment; Structure; Substance Use Disorder; Surveys; System; Testing; Time; Training; Validity and Reliability; Variant; Veterans; Vulnerable Populations; Work; acceptability and feasibility; analytical method; authority; career; clinical implementation; clinical practice; community living; comparative; contextual factors; dashboard; data warehouse; design; deviant; effectiveness testing; evidence base; evidence based guidelines; formative assessment; health care delivery; health care quality; hybrid type 2 design; implementation intervention; implementation science; improved; innovation; organizational structure; pain model; pain outcome; population health; programs; severe mental illness; skills; social; symptom management

Background: Unrelieved pain is highly prevalent and devastating for Veterans in VA’s 134 Community Living Centers (CLCs). Imminent removal of pain as one of the CLC quality measures offers an opportunity, per VA’s Office of Geriatrics and Extended Care (GEC), to develop new, risk-adjusted measures that more accurately characterize CLC pain management. These measures can identify CLCs successful at pain management while minimizing biased underestimates for CLCs with the sickest residents. Then, by diving deeply into structures and processes of high performers, we can learn how to intervene. My background in gerontology, quantitative methods, and implementation science partially prepares me for this work. But I need additional training in risk adjustment, qualitative research, cutting-edge analytic methods, and intervention study designs for the study and my health services research career to succeed. Specific Aims: The proposed CDA simultaneously fills the considerable gaps in my background and provides VA with rigorous, actionable research on which to ground future quality improvement efforts. A social- ecological model frames the work. GEC commits to serving as an invested partner. I have 3 aims, which I will achieve with my mentors and training. 1. Evaluate how risk adjustment changes judgements of CLC pain management performance. 2. Use mixed methods to perform in-depth studies of CLCs with high outlying performance. 3. Adapt an existing, evidence-based intervention comprising lessons learned from “positive deviants.” Methods: Aim 1: Using VA administrative data of CLC residents, I will (1) calculate unadjusted pain measures, (2) apply risk adjustment, (3) assess the measures’ reliability and validity, and (4) identify high and low outlying performance on pain management. Aim 2: I will use quantitative (survey) and qualitative data from staff and residents at 5 top-performing CLCs, contrasted with qualitative data from 5 low-performing CLCs, to develop hypotheses of contextual factors and pain management practices unique to positive deviants. I will test causal relationships using configurational comparative analytic methods. Aim 3: I will adapt an existing nursing home pain management intervention for use in VA CLCs, using empirical evidence from Aim 2 about necessary conditions for optimal pain management. A modified e-Delphi panel of CLC stakeholders and pain management experts will provide feedback on the intervention package’s design. I will use a developmental formative evaluation of qualitative data from staff at 1 low-performing CLC to assess the intervention’s feasibility and acceptability, in preparation for rigorous testing in future work. Expected Results and Next Steps: I will provide GEC with interim deliverables to enable assessment of CLC pain management quality, guide CLC policy, and support clinical practice in CLCs struggling with pain management. Knowledge from this CDA will lead me to develop studies to refine risk adjustment methods for quality measurement in other critical areas and to rigorously evaluate, using a hybrid type II design, clinical effectiveness and implementation of the intervention. Significance & Relevance to Veterans’ Health: Coming at a critical juncture in my VA research career, this timely study responds to the VA priority of Greater Choice for Veterans, ORD’s priority to increase substantial real-world impact of VA research, and HSR&D’s Long-term Care and Opioid/Pain priority domains. Although pain is highly prevalent and debilitating for the 42,000 vulnerable Veterans CLCs serve, almost nothing is systematically known about CLCs’ pain management quality. And current pain measures are about to disappear. This study seizes this opportunity, developing nuanced, VA-specific approaches that are custom- made to reflect the accurate state of CLC pain management and help improve VA long-term care.

背景：对于 VA 134 社区生活中的退伍军人来说，无法缓解的疼痛非常普遍，并且具有毁灭性 根据 VA 的说法，作为 CLC 质量措施之一的即将消除疼痛提供了机会。 老年病学和延伸护理办公室 (GEC)，制定新的风险调整措施，更准确地 这些措施可以表征 CLC 疼痛管理的特征，同时可以识别 CLC 在疼痛管理方面是否成功。 然后，通过深入研究结构，最大限度地减少对病情最严重的居民的 CLC 的偏见低估。 和高绩效者的过程，我们可以学习如何干预我的老年学背景，定量。 方法、实施和科学使我为这项工作做好了部分准备，但我需要额外的风险培训。 研究的调整、定性研究、前沿分析方法和干预研究设计 我的健康服务研究事业取得成功。 具体目标：拟议的 CDA 同时填补了我的背景中的相当大的空白，并提供了 VA 进行严格、可行的研究，为未来的质量改进工作奠定基础。 GEC 致力于作为投资合作伙伴的生态模型，我有 3 个目标。 通过我的导师和培训取得成就。 1. 评估风险调整如何改变对 CLC 疼痛管理绩效的判断。 2. 采用混合方法对异常性能高的 CLC 进行深入研究。 3. 调整现有的基于证据的干预措施，其中包括从“积极偏差”中吸取的经验教训。 方法：目标 1：使用 CLC 居民的 VA 管理数据，我将 (1) 计算未经调整的疼痛测量值， (2) 应用风险调整，(3) 评估措施的可靠性和有效性，以及 (4) 识别高低外围 目标 2：我将使用来自工作人员的定量（调查）和定性数据。 5 个表现最好的 CLC 的居民与 5 个表现不佳的 CLC 的定性数据进行对比，以制定 我将测试积极偏差所特有的情境因素和疼痛管理实践的假设。 目标 3：我将改造现有的疗养院 用于 VA CLC 的疼痛管理干预，使用目标 2 中关于必要性的经验证据 最佳疼痛管理的条件。经过修改的 CLC 利益相关者和疼痛的 e-Delphi 小组。 管理专家将提供有关干预方案设计的反馈。我将使用发展性的方案。 对 1 个表现不佳的 CLC 工作人员的定性数据进行形成性评估，以评估干预措施的效果 可行性和可接受性，为今后工作中的严格测试做好准备。 预期结果和后续步骤：我将向​​ GEC 提供临时可交付成果，以评估 CLC 疼痛管理质量，指导 CLC 政策，并支持与疼痛作斗争的 CLC 的临床实践 来自该 CDA 的知识将引导我开展研究，以完善风险调整方法。 其他关键领域的质量测量，并使用混合 II 型设计、临床 干预措施的有效性和实施情况。 对退伍军人健康的意义和相关性：在我退伍军人管理局研究生涯的关键时刻，这 及时的研究响应了 VA 优先事项“为退伍军人提供更多选择”，ORD 的优先事项大幅增加 VA 研究以及 HSR&D 的长期护理和阿片类药物/疼痛优先领域的现实影响。 对于 42,000 名 CLC 服务的弱势退伍军人来说，疼痛非常普遍，并且使人衰弱，但几乎没有什么是 显然，人们对 CLC 的疼痛管理质量有所了解，并且当前的疼痛措施即将实现。 这项研究抓住了这个机会，开发了细致入微的、针对 VA 的定制方法。 旨在反映 CLC 疼痛管理的准确状态并帮助改善 VA 长期护理。