Carr Helen, de Lusignan Simon, Liyanage Harshana, Liaw Siaw-Teng, Terry Amanda, Rafi Imran
Department of Health Care Management and Policy, Clinical Informatics and Health Outcomes Research Group, University of Surrey, Guildford, UK.
School of Public Health & Community Medicine, UNSW Medicine Australia, Sydney, New South Wales, 2052, Australia.
BMC Fam Pract. 2014 Nov 26;15:169. doi: 10.1186/s12875-014-0169-6.
Recruitment to research studies in primary care is challenging despite widespread implementation of electronic patient record (EPR) systems which potentially make it easier to identify eligible cases.
Literature review and applying the learning from a European research readiness assessment tool, the TRANSFoRm International Research Readiness instrument (TIRRE), to the context of the English NHS in order to develop a model to assess a practice's research readiness.
Seven dimensions of research readiness were identified: (1) Data readiness: Is there good data quality in EPR systems; (2) Record readiness: Are EPR data able to identify eligible cases and other study data; (3) Organisational readiness: Are the health system and socio-cultural environment supportive; (4) Governance readiness: Does the study meet legal and local health system regulatory compliance; (5) Study-specific readiness; (6) Business process readiness: Are business processes tilted in favour of participation: including capacity and capability to take on extra work, financial incentives as well as intangibles such as social and intellectual capital; (7) Patient readiness: Are systems in place to recruit patients and obtain informed consent?
The model might enable the development of interventions to increase participation in primary care-based research and become a tool to measure the progress of practice networks towards the most advanced state of readiness.
尽管电子病历(EPR)系统已广泛应用,理论上更易于识别符合条件的病例,但在初级保健机构开展研究招募工作仍具挑战性。
进行文献综述,并将欧洲研究准备评估工具“转化国际研究准备工具”(TIRRE)的经验应用于英国国民健康服务体系(NHS)的实际情况,以建立一个评估医疗机构研究准备情况的模型。
确定了研究准备的七个维度:(1)数据准备:EPR系统中的数据质量是否良好;(2)记录准备:EPR数据能否识别符合条件的病例及其他研究数据;(3)组织准备:卫生系统和社会文化环境是否支持;(4)治理准备:研究是否符合法律及当地卫生系统监管要求;(5)特定研究准备;(6)业务流程准备:业务流程是否倾向于参与研究,包括承担额外工作的能力、经济激励以及社会和智力资本等无形资产;(7)患者准备:是否具备招募患者并获得知情同意的系统?
该模型可能有助于制定干预措施,以提高对基于初级保健的研究的参与度,并成为衡量实践网络向最先进准备状态发展进程的工具。