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: 10668268
• 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/10668268
• 关键词: Adoption; Area; Authorization documentation; Caring; Characteristics; Chronic Disease; Cladribine; 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; Homogeneously Staining Region; Hybrids; Intervention; Intervention Studies; Investments; 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 Adjustment; Structure; Substance Use Disorder; Surveys; System; Testing; 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：在退伍军人事务部的134个社区生活中，无法缓解的疼痛对退伍军人来说是非常普遍和毁灭性的

项目成果

Integrating CFIR-ERIC and e-Delphi Methods to Increase Telegeriatrics Uptake.

整合 CFIR-ERIC 和 e-Delphi 方法以提高远程老年医学的采用率。

• DOI: 10.1093/geront/gnac107
• 发表时间: 2023
• 期刊: The Gerontologist
• 作者: Kernan,LauraM;Dryden,EileenM;Nearing,Kathryn;Kennedy,MeaghanA;Hung,Will;Moo,Lauren;Pimentel,CamillaB
• 通讯作者: Pimentel,CamillaB

Perceived benefits of geriatric specialty telemedicine among rural patients and caregivers.

• DOI: 10.1111/1475-6773.14055
• 发表时间: 2023-02
• 期刊: HEALTH SERVICES RESEARCH
• 影响因子: 3.4
• 作者: Dryden, Eileen M.;Kennedy, Meaghan A.;Conti, Jennifer;Boudreau, Jacqueline H.;Anwar, Chitra P.;Nearing, Kathryn;Pimentel, Camilla B.;Hung, William W.;Moo, Lauren R.
• 通讯作者: Moo, Lauren R.

Response to Letter to the Editor: Account for Identity in URM Mentorship.

对致编辑的信的回复：URM 指导中的身份说明。

• DOI: 10.1007/s11606-021-07186-6
• 发表时间: 2022
• 期刊: Journal of general internal medicine
• 影响因子: 5.7
• 作者: Quach,EmmaD;Pimentel,CamillaB;Hartmann,ChristineW
• 通讯作者: Hartmann,ChristineW

The Development and Use of a New Visual Tool (REVISIT) to Support Participant Recall: Web-Based Interview Study Among Older Adults.

开发和使用新的视觉工具（REVISIT）来支持参与者回忆：基于网络的老年人访谈研究。

• DOI: 10.2196/52096
• 发表时间: 2024
• 期刊: JMIR formative research
• 影响因子: 2.2
• 作者: Dryden,EileenM;Anwar,Chitra;Conti,Jennifer;Boudreau,JacquelineH;Kennedy,MeaghanA;Hung,WilliamW;Nearing,KathrynA;Pimentel,CamillaB;Moo,Lauren
• 通讯作者: Moo,Lauren