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用于识别儿童医疗保健需求的社区层面与个体层面指标

Community- versus individual-level indicators to identify pediatric health care need.

作者信息

Zlotnick Cheryl

机构信息

Center for the Vulnerable Child, Children's Hospital & Research Center at Oakland, Oakland, CA 94609-1809, USA.

出版信息

J Urban Health. 2007 Jan;84(1):45-59. doi: 10.1007/s11524-006-9123-9.

Abstract

Increasingly, geographic information systems employing spatial data are being used to identify communities with poorer health care status. Since health care indicators are strongly linked to income, could these data, usually based on adult indicators, be used for pediatric health care need? We hypothesized that individual-level indicators such as quality of life scales (QOL) would be better than community-level indicators at identifying families with poorer health care practices. Surveys and medical record reviews were used for a sample of 174 caregivers of young children. Lower level of income was associated with poorer scores on several QOL domains, and on the primary health practices (i.e., non-urgent emergency room use and lack of age-appropriate immunization status). One community-level indicator, the medically underserved area (MUA), was almost as good as the best individual-level indicators at predicting primary health care practices. The community-level indicator of MUA appears to meet its initial intent, providing information on the location of very low-income individuals with high health care need even among a sample of Medicaid-insured children with an identified health care provider.

摘要

越来越多地,采用空间数据的地理信息系统被用于识别医疗保健状况较差的社区。由于医疗保健指标与收入密切相关,这些通常基于成人指标的数据能否用于儿童医疗保健需求呢?我们假设,诸如生活质量量表(QOL)等个体层面的指标在识别医疗保健行为较差的家庭方面要优于社区层面的指标。对174名幼儿照料者进行了抽样调查并查阅了医疗记录。较低的收入水平与几个生活质量领域以及主要医疗保健行为(即非紧急情况下使用急诊室和缺乏适龄免疫接种状况)的较差得分相关。一个社区层面的指标,即医疗服务不足地区(MUA),在预测主要医疗保健行为方面几乎与最佳个体层面指标一样有效。MUA这一社区层面指标似乎达到了其最初目的,即使在有确定医疗保健提供者的医疗补助保险儿童样本中,也能提供有关有高医疗保健需求的极低收入个体所在位置的信息。

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