N-of-1 Trials Using mHealth in Chronic Pain
N-of-1 Trials Using mHealth in Chronic Pain
批准号:
8419238
负责人:
RICHARD L KRAVITZ
金额:
$64.73万
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-09-26 至 2017-07-31
关键词:
Accident and Emergency departmentAccountingAcetaminophenAddressAdherenceAdjuvantAdultAffectAmericanAnalgesicsAnti-Inflammatory AgentsAnti-inflammatoryArchitectureBackBayesian MethodCar PhoneCaringChronicClinicalCommunitiesComputer softwareCross-Over StudiesDecision MakingDevicesDisadvantagedDoseDrug PrescriptionsEnrollmentGoalsHealthHealth Care CostsHealth PersonnelHealth systemHealthcareHealthcare SystemsHeterogeneityHourIndividualInternetLeadMusculoskeletal PainOffice VisitsOpioidOpioid AnalgesicsOpioid RotationOutcomePainPain intensityPain interferencePain managementParticipantPatientsPerceptionPharmaceutical PreparationsPlacebo EffectPopulationRandomizedRandomized Controlled TrialsRegimenResearchResearch InfrastructureResearch PersonnelResortRunningStagingTechniquesTechnologyTelephoneTestingTherapeuticTimeTitrationsToxic effectTractionUncertaintyVariantVisitWorkbasechronic paincompare effectivenesscostdesignevidence baseexperiencefollow-uphazardhealth related quality of lifeimprovedpatient orientedprimary outcomeresearch studyresponsesatisfactionsecondary outcomesuccesstooltreatment as usualtreatment effecttrial comparinguptakeusability
中文摘要
描述(申请人提供):慢性肌肉骨骼疼痛(MSP)是一个巨大的问题,影响着超过1亿美国人(许多来自弱势群体),花费超过1600亿美元。目前的药物治疗策略既有好处,也有风险。在通常的做法中,临床医生求助于阿片类止痛药,通常是不情愿的,
当其他药物似乎无效或禁药时。找到一种有效的养生法往往是一个反复试验的问题。这种方法可能会奏效,但容易产生偏见。一种在短期内看起来有效(或无效)的治疗可能只是因为患者潜在状况的随机波动而显得如此。为了发现真正的效果,从而优化个人治疗,需要一种更科学的方法。N-of-1试验是在单个患者中进行的随机对照交叉试验。通过将患者在两种治疗方法之间来回交叉几次,临床医生可以比通常做法更精确地为该患者确定更有效的方法。通过产生个人治疗效果,1中n试验对“基于证据的试验和错误”提出了挑战,“循证试验和错误”是治疗慢性症状疾病的主导临床范例。N-of-1试验是一种直观上有吸引力且明显成功的方法,但由于缺乏基础设施,未能获得太多吸引力。移动设备可以改变这一点。这项建议将移动技术与个性化医疗服务相结合,以解决确定什么对单个患者有效的临床问题。我们的目标是为患者和他们的临床医生提供确定个人治疗效果的工具,并根据患者的结果和医疗保健系统的成本来评估这种方法。这个应用程序的具体目标是:1)开发和改进一个移动Web应用程序(“Triist”),以进行n-of
1)在患有慢性肌肉骨骼疼痛的脆弱患者中进行临床试验;2)在随机对照试验(RCT)中评估参与流动n-of-1试验(与普通护理相比)对临床结果、参与性决策、满意度、依从性和医疗成本的影响。在Open mHealth.org已经开发的软件架构的基础上,研究团队将在项目的前18个月开发、改进和测试Triist软件。然后,296名患有慢性肌肉骨骼疼痛的患者将被随机分配到使用Triist进行n-of-1试验或接受常规护理的组。主要假设是,与那些被分配到常规护理的患者相比,被分配到试验者的患者将经历更好的长期结果(特别是6个月后的疼痛干预)。实现这些目标将为更广泛地采用mHealth n-of-1试验治疗慢性疼痛奠定基础,并促进在设计慢性保健管理时使用mHealth n-of-1试验。好了!
与公共卫生相关:慢性肌肉骨骼疼痛是一个巨大的问题,治疗方法通常是以“反复试验”的方式进行的。该项目旨在开发一种手机应用程序(APP),允许患者和他们的医疗保健提供者进行严格的个性化实验(n-of-1试验),比较两种不同的疼痛治疗方法。一旦这款应用程序被开发出来,调查人员将招募296名患者参加一项随机研究,观察被分配使用该应用程序与常规护理进行n-of-1试验的患者的长期疼痛结果。该项目利用移动技术帮助患者主动与临床医生合作,确定最适合他们的疼痛治疗方法。
英文摘要
DESCRIPTION (provided by applicant): Chronic musculoskeletal pain (MSP) is an enormous problem, affecting more than 100 million Americans (many from disadvantaged groups) and costing upwards of $160 billion. Current pharmaco-therapeutic strategies convey a mix of benefits and hazards. In usual practice, clinicians resort to opioid analgesics, often reluctantly,
when other drugs are seemingly ineffective or contraindicated. Finding an effective regimen is frequently a matter of trial and error. This approach may work but is subject to bias. A treatment that appears effective (or ineffective) over the short term may only seem so because of random fluctuation in the patient's underlying condition. To discover the true effect and thus optimize individual treatment, a more scientific approach is needed. N-of-1 trials are randomized controlled crossover trials conducted in a single patient. By crossing a patient back and forth between two treatments several times, clinicians can identify the more effective approach for that individual patient with greater precision than can be achieved in ordinary practice. By generating individual treatment effects, n-of-1 trials pose a challenge to "evidence-based trial and error," the reigning clinical paradigm for treatment of chronic, symptomatic conditions. N-of-1 trials are an intuitively appealing and demonstrably successful approach but have failed to gain much traction, largely due to lack of infrastructure. Mobile devices can change that. This proposal weds mobile technology with personalized health care to address the clinical problem of determining what works for an individual patient. Our goal is to provide tools for identifying individual treatment effects to patients and their clinicians, and to evaluate this approach in terms of patient outcomes and costs to the health care system. The specific aims of this application are: 1) to develop and refine a mobile web application ("the Trialist") to conduct n-of
1 trials among vulnerable patients with chronic musculoskeletal pain; and 2) to assess in a randomized controlled trial (RCT) the effects of participating in a mobile n-of-1 trial (versus usul care) on clinical outcomes; participatory decision making; satisfaction; adherence; and health care costs. Building on software architecture already developed by Open mHealth.org, the research team will develop, refine, and test the Trialist software over the first 18 months of the project. Then 296 patients with chronic musculoskeletal pain will be randomized to using Trialist to conduct an n-of-1 trial or to usual care. The main hypothesis is that patients assigned to the Trialist will experience better long term outcomes (particularly pain interference at 6 months) compared with those assigned to usual care. Achieving these aims will set the stage for broader uptake of mHealth n-of-1 trials in chronic pain and facilitate use of mHealth n-of-1 trials in designing chronic health care management. !
PUBLIC HEALTH RELEVANCE: Chronic musculoskeletal pain is an enormous problem, and treatments are often prescribed in a "trial and error" fashion. This project seeks to develop a mobile phone application ("app") that allows patients and their health care providers to run rigorous, personalized experiments ("n-of-1 trials") comparing two different pain treatments. Once the app is developed, the investigators will enroll 296 patients in a randomized study that looks at long term pain outcomes among patients assigned to undergo an n-of-1 trial using the app versus usual care. The project enlists mobile technology to help patients engage actively and collaboratively with their clinicians to identify the pain treatment that works best for them.
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