King's College London School of Medicine, Department of Palliative Care, Policy and Rehabilitation, London, UK.
Disabil Rehabil. 2012;34(22):1871-9. doi: 10.3109/09638288.2012.670033. Epub 2012 Apr 16.
This article explores the rationale for choosing the instruments included within the UK Rehabilitation Outcomes Collaborative (UKROC) data set. Using one specialist neuro-rehabilitation unit as an exemplar service, it describes an approach to engaging the hearts and minds of clinicians in recording the data.
Measures included within a national data set for rehabilitation should be psychometrically robust and feasible to use in routine clinical practice; they should also support clinical decision-making so that clinicians actually want to use them. Learning from other international casemix models and benchmarking data sets, the UKROC team has developed a cluster of measures to inform the development of effective and cost-efficient rehabilitation services. These include measures of (1) "needs" for rehabilitation (complexity), (2) inputs provided to meet those needs (nursing and therapy intervention), and (3) outcome, including the attainment of personal goals as well as gains in functional independence.
By integrating the use of the data set measures in everyday clinical practice, we have achieved a very high rate of compliance with data collection. However, staff training and ongoing commitment from senior staff and managers are critical to the maintenance of effort required to provide assurance of data quality in the longer term.
本文探讨了选择英国康复成果协作组织（UKROC）数据集中包含的工具的基本原理。本文以一个专门的神经康复单位为例，介绍了一种让临床医生参与记录数据的方法。
康复的国家数据集应包含具有心理测量学可靠性且便于在常规临床实践中使用的措施；这些措施还应支持临床决策，使临床医生真正愿意使用这些措施。UKROC 团队从其他国际病例组合模型和基准数据集学习，开发了一组措施来为制定有效和具有成本效益的康复服务提供信息。这些措施包括（1）康复“需求”（复杂性）、（2）为满足这些需求提供的投入（护理和治疗干预）和（3）结果，包括实现个人目标以及在功能独立性方面的收益。
通过将数据集措施整合到日常临床实践中，我们实现了非常高的数据收集合规率。然而，工作人员培训以及高级工作人员和管理人员的持续承诺对于确保数据质量的长期维护至关重要。
