Andrew F. Beck (
Megan T. Sandel is an associate professor of pediatrics at the Boston University School of Medicine, in Massachusetts.
Health Aff (Millwood). 2017 Jun 1;36(6):999-1005. doi: 10.1377/hlthaff.2016.1425.
Health disparities, which can be understood as disadvantages in health associated with one's social, racial, economic, or physical environment, originate in childhood and persist across an individual's life course. One's neighborhood may drive or influence these disparities. Information on neighborhoods that can characterize their risks-what we call place-based risks-is rarely used in patient care. Community-level data, however, could inform and personalize interventions such as arranging for mold removal from the home of a person with asthma from the moment that person's address is recorded at the site of care. Efficient risk identification could lead to the tailoring of recommendations and targeting of resources, to improve care experiences and clinical outcomes while reducing disparities and costs. In this article we highlight how data on place-based social determinants of health from national and local sources could be incorporated more directly into patient-centered care, adding precision to risk assessment and mitigation. We also discuss how this information could stimulate cross-sector interventions that promote health equity: the attainment of the highest level of health for neighborhoods, patient panels, and individuals. Finally, we draw attention to research questions that focus on the role of geographical place at the bedside.
健康差异可以理解为与个人社会、种族、经济或身体环境相关的健康劣势,它们起源于儿童时期,并贯穿于个体的整个生命周期。一个人的社区环境可能会导致或影响这些差异。关于能够描述其风险的社区信息——我们称之为基于地点的风险——在患者护理中很少使用。然而,社区层面的数据可以为干预措施提供信息并使其个性化,例如在患者护理场所记录患者的地址时,就安排为患有哮喘的人清除家中的霉菌。有效的风险识别可以使建议和资源的针对性得到改善,从而提高护理体验和临床结果,同时减少差异和成本。在本文中,我们强调了如何更直接地将来自国家和地方来源的基于地点的社会决定因素健康数据纳入以患者为中心的护理中,从而提高风险评估和缓解的准确性。我们还讨论了这些信息如何激发促进健康公平的跨部门干预措施:实现社区、患者群体和个人的最高健康水平。最后,我们提请注意关注床边地理位置作用的研究问题。