Center for Healthcare Equity and Institute for Healthcare Studies, Division of General Internal Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL 60611, USA.
Am J Manag Care. 2012 Sep;18(6 Suppl):s141-7.
The systematic collection and use of race/ethnicity and language (REL) data by healthcare organizations has long been recognized as a critical step to reducing healthcare disparities locally and nationally. We seek to identify the challenges and opportunities in implementing community-level interventions to collect REL data for detecting and reducing disparities in care in the 14 multi-stakeholder communities participating in the Aligning Forces for Quality initiative.
This was a cross-sectional descriptive qualitative study.
We conducted 1-hour, face-to-face, semi-structured interviews with identified key informants during 2-day visits to each of the 14 communities in 2010, and supplemented this information with 2 rounds of semi-structured telephone interviews. Data were analyzed using a qualitative analysis software program, which assists with organizing and analyzing large quantities of interview data through creation of analytic units. We used deductive and inductive qualitative methods to analyze the data.
Communities found it challenging to implement a community-level intervention to collect standardized REL data because addressing disparities is complex, the utility of having individual healthcare organizations collect these data is difficult to communicate, and perceptions of disparities in the community vary across stakeholders. Opportunities include working with credible "early adopters" in the community and leveraging federal or state mandates to encourage providers to collect this information.
Community-level efforts to collect REL data require securing buy-in from organizational leadership, developing a dialogue across the community, and generating awareness across key players about disparities-reduction efforts, especially REL data collection, without alienating patients, communities, and providers.
医疗机构系统地收集和使用种族/民族和语言（REL）数据，长期以来一直被认为是减少当地和全国医疗保健差异的关键步骤。我们试图确定在实施社区层面干预措施以收集 REL 数据以检测和减少参与质量联盟倡议的 14 个多利益相关者社区中护理差异方面所面临的挑战和机遇。
这是一项横断面描述性定性研究。
我们在 2010 年对每个社区进行为期两天的访问期间，对 14 个社区的确定的主要信息员进行了 1 小时的面对面半结构式访谈，并通过两轮半结构式电话访谈补充了这些信息。使用定性分析软件程序分析数据，该软件程序通过创建分析单元来协助组织和分析大量访谈数据。我们使用演绎和归纳定性方法分析数据。
社区发现实施社区层面的干预措施来收集标准化 REL 数据具有挑战性，因为解决差异问题很复杂，很难传达让个别医疗机构收集这些数据的实用性，并且社区内的利益相关者对差异的看法各不相同。机会包括与社区内可信的“早期采用者”合作，并利用联邦或州的授权来鼓励提供者收集这些信息。
收集 REL 数据的社区层面努力需要获得组织领导层的认可，在社区内开展对话，并在关键参与者中提高对减少差异的努力，特别是 REL 数据收集的认识，同时避免疏远患者、社区和提供者。
