Nursing Home Pain Management Algorithm Clinical Trial

疗养院疼痛管理算法临床试验

• 批准号: 7222670
• 负责人: MARY ERSEK
• 金额: $ 48.03万
• 依托单位: SWEDISH MEDICAL CENTER, FIRST HILL
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-01 至 2010-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7222670
• 关键词: Adherence; Adopted; Algorithms; Analgesics; Behavioral; Case Study; Clinical; Clinical Trials; Cognitive; Collaborations; Consultations; Coupled; Decision Making; Diffusion; Diffusion of Innovation; Discomfort Scale for Patients with Dementia of the Alzheimer' s Type; Education; Effectiveness; Elderly; Ensure; Feedback; Home environment; Impaired cognition; Individual; Intervention; Locomotion; Long-Term Care Nursing; Measures; Mental Depression; Modeling; Needs Assessment; Nurses; Nursing Education; Nursing Homes; Outcome; Pain; Pain Measurement; Pain management; Patient Self-Report; Pattern; Performance; Physical Function; Problem behavior; Process; Randomized; Randomized Controlled Trials; Research; Research Personnel; Resources; Self Care; Series; Severities; Sleep disturbances; Social Functioning; Testing; Time; Upper arm; Writing; base; follow-up; improved; improved functioning; indium arsenide; posters; programs; theories; tool; treatment planning

DESCRIPTION (provided by applicant): Pain assessment and management deficiencies in nursing homes (NHs) are well documented. Unrelieved pain in this setting results in poorer resident outcomes, including depression, decreased mobility, sleep disturbance, and impaired physical and social functioning. This randomized controlled trial will evaluate the efficacy of a pain management algorithm coupled with intense diffusion strategies in improving physical function and decreasing pain and depression among NH residents. Specific aims of the study are to: 1) Evaluate the effectiveness of a pain management algorithm (ALG) coupled with intense diffusion strategies, as compared with pain education (EDU) and weak diffusion strategies, in improving self-care, locomotion, and mobility, and decreasing pain and depression among NH residents; 2) Determine the extent to which adherence to the ALG and organizational factors are associated with changes in residents' self-care, locomotion, mobility, pain, and depression and the extent to which changes in these variables are associated with changes in outcomes; 3) Evaluate the persistence of changes in process and outcome variables at long-term follow-up and 4) Evaluate the relationships among behavioral problems (measured by the BEHAVE-AD) and discomfort (as measured by the DS-DAT) in severely cognitively impaired residents who are unable to provide self-report. The NH pain management algorithm is a series of decision-making tools that begin with regular, comprehensive pain assessment matched to residents' cognitive status and proceed through analgesic therapy appropriate to the character, severity, and pattern of pain. The algorithm is based on the investigators' earlier research and was adapted in collaboration with geriatric pain experts. Initial pilot testing demonstrated preliminary support for the effectiveness of the algorithm. Implementation of the algorithm will utilize a program that applies the principles of Roger's Diffusion of Innovations Theory. The implementation program emphasizes the education of NH staff in the use of the algorithm; practice in applying the algorithm to hypothetical and real case studies; establishment of NH pain teams comprised of opinion leaders who are experts in using the algorithm; and use of booster and supportive strategies to imbed the algorithm into everyday, ongoing pain management practices. The randomized controlled trial will involve 20 facilities, 10 ALG and 10 EDU. Facilities will be the unit of randomization, although clinical outcomes will be measured in individual residents within facilities. Clinical outcomes from 510 residents, 255 in each treatment arm, will be evaluated to determine the efficacy of the ALG. Findings from this study will assist NH staff to assess and treat pain effectively in cognitively intact and impaired residents. Long-term follow-up will establish the persistence of changes in clinical practice and resident outcomes.

描述（由申请人提供）：疗养院 (NH) 的疼痛评估和管理缺陷有详细记录。在这种情况下，持续的疼痛会导致住院医师的预后较差，包括抑郁、活动能力下降、睡眠障碍以及身体和社会功能受损。这项随机对照试验将评估疼痛管理算法与强化扩散策略相结合在改善新罕布什尔州居民的身体功能、减少疼痛和抑郁方面的功效。该研究的具体目的是： 1) 与疼痛教育 (EDU) 和弱扩散策略相比，评估疼痛管理算法 (ALG) 结合强扩散策略在改善自我护理、运动和活动能力方面的有效性，并减少新罕布什尔州居民的疼痛和抑郁； 2) 确定对 ALG 和组织因素的遵守程度与居民自我护理、运动、行动能力、疼痛和抑郁变化的相关程度，以及这些变量的变化与结果变化的相关程度； 3) 评估长期随访中过程和结果变量变化的持续性，以及 4) 评估严重认知障碍患者的行为问题（通过 BEHAVE-AD 测量）和不适（通过 DS-DAT 测量）之间的关系无法提供自我报告的受损居民。 NH 疼痛管理算法是一系列决策工具，首先根据住院医师的认知状态进行定期、全面的疼痛评估，然后根据疼痛的性质、严重程度和模式进行适当的镇痛治疗。该算法基于研究人员的早期研究，并与老年疼痛专家合作进行了调整。初步的试点测试证明了对该算法有效性的初步支持。该算法的实现将利用一个应用罗杰创新扩散理论原理的程序。实施方案强调对 NH 工作人员进行算法使用方面的教育；将算法应用于假设和真实案例研究的练习；建立由擅长使用算法的意见领袖组成的 NH 疼痛团队；并使用增强和支持策略将算法嵌入到日常、持续的疼痛管理实践中。随机对照试验将涉及 20 个设施、10 个 ALG 和 10 个 EDU。尽管临床结果将在设施内的个体居民中进行测量，但设施将是随机化的单位。将评估 510 名居民（每个治疗组 255 名居民）的临床结果，以确定 ALG 的疗效。这项研究的结果将帮助 NH 工作人员有效评估和治疗认知完好和受损居民的疼痛。长期随访将确定临床实践和住院医师结果变化的持续性。