Weiner Michael, Fan Ming-Yu, Johnson Brent A, Kasper Judith D, Anderson Gerard F, Fried Linda P
Indiana University Center for Aging Research, Indianapolis, Indiana, USA.
J Am Geriatr Soc. 2003 Mar;51(3):371-9. doi: 10.1046/j.1532-5415.2003.51111.x.
To identify specific clinical factors that could best predict resource use by disabled older women.
Cross-sectional.
Urban community in Baltimore, Maryland.
One thousand two community-dwelling, moderately to severely disabled, female Medicare beneficiaries aged 65 and older, from the Women's Health and Aging Study I (WHAS).
WHAS data were merged with participants' 1992-1994 Medicare claims data for the year after baseline evaluation, reflecting inpatient, outpatient, home-based, and skilled-nursing services. The independent contributions of factors hypothesized to predict health expenditures were assessed, using chi-square and regression analyses, with the logarithm of Medicare expenditures as the primary outcome.
Demographic factors were not associated with Medicare expenditures. Factors associated with expenditures in bivariate analyses included heart disease (1.4x), chronic obstructive pulmonary disease (1.3x), diabetes mellitus (1.1x), smoking, comorbidity, and severity of disability, as well as low creatinine clearance, serum albumin, caloric expenditure, or skinfold thickness. Heart disease, diabetes mellitus, and low skinfold thickness remained significant after adjustment for other factors.
Heart disease, diabetes mellitus, and low skinfold thickness are important independent predictors of 1-year Medicare expenditures by disabled older women. Many other variables that reflect disease, disability, nutrition, or personal habits have less predictive ability. Most demographic factors are not predictors of expenditures in this population. Focusing on the best predictors may facilitate more-effective risk adjustment and creation of related health policies.
确定能够最准确预测残疾老年女性资源使用情况的特定临床因素。
横断面研究。
马里兰州巴尔的摩市的城市社区。
来自女性健康与衰老研究I(WHAS)的1200名居住在社区、中度至重度残疾、年龄在65岁及以上的女性医疗保险受益人。
将WHAS数据与参与者在基线评估后一年(1992 - 1994年)的医疗保险理赔数据合并,这些数据反映了住院、门诊、家庭护理和专业护理服务情况。以医疗保险支出的对数作为主要结果,采用卡方检验和回归分析评估假设用于预测健康支出的因素的独立贡献。
人口统计学因素与医疗保险支出无关。在双变量分析中与支出相关的因素包括心脏病(1.4倍)、慢性阻塞性肺疾病(1.3倍)、糖尿病(1.1倍)、吸烟、合并症、残疾严重程度,以及低肌酐清除率、血清白蛋白、热量消耗或皮褶厚度。在对其他因素进行调整后,心脏病、糖尿病和低皮褶厚度仍然具有显著意义。
心脏病、糖尿病和低皮褶厚度是残疾老年女性1年医疗保险支出的重要独立预测因素。许多其他反映疾病、残疾、营养或个人习惯的变量预测能力较弱。大多数人口统计学因素不是该人群支出的预测因素。关注最佳预测因素可能有助于更有效地进行风险调整并制定相关卫生政策。