Nursing Home Pain Management Algorithm Clinical Trial

疗养院疼痛管理算法临床试验

• 批准号: 7414489
• 负责人: MARY ERSEK
• 金额: $ 46.93万
• 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/7414489
• 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）：疼痛评估和护理院（NH）的管理缺陷有据可查。在这种情况下，未缓解的疼痛会导致住院患者的预后较差，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结合强烈扩散策略在改善NH居民身体功能和减少疼痛和抑郁方面的疗效。本研究的具体目的是：1）评估疼痛管理算法（ALG）与强扩散策略相结合的有效性，与疼痛教育（EDU）和弱扩散策略相比，在改善NH居民的自我护理，运动和流动性，减少疼痛和抑郁方面; 2）确定对ALG的坚持和组织因素与居民自我护理、运动、移动性、疼痛的变化相关的程度，以及这些变量的变化与结果变化的相关程度; 3）评估长期随访过程和结果变量变化的持续性; 4）评估行为问题之间的关系（由SDE VE-AD测量）和不适（由DS-DAT测量）在严重认知受损的居民谁是无法提供自我报告。NH疼痛管理算法是一系列决策工具，其开始是与住院医生的认知状态相匹配的定期、全面的疼痛评估，并通过适合疼痛特征、严重程度和模式的镇痛治疗进行。该算法基于研究人员早期的研究，并与老年疼痛专家合作进行了调整。初步试验表明，初步支持算法的有效性。该算法的实现将利用应用罗杰的创新扩散理论的原则的程序。实施方案强调NH工作人员在使用算法的教育;在应用算法的假设和真实的案例研究的做法;建立NH疼痛团队组成的意见领袖谁是专家在使用算法;和使用助推器和支持性的策略，嵌入到日常的算法，持续的疼痛管理实践。随机对照试验将涉及20个设施，10个ALG和10个EDU。设施将是随机化的单位，尽管临床结果将在设施内的个体居民中进行测量。将对510名住院医生（每个治疗组255名）的临床结局进行评价，以确定ALG的疗效。这项研究的结果将有助于NH工作人员有效地评估和治疗认知完整和受损居民的疼痛。长期随访将确立临床实践和住院医师结局变化的持续性。