Chien Alyna T, Newhouse Joseph P, Iezzoni Lisa I, Petty Carter R, Normand Sharon-Lise T, Schuster Mark A
Division of General Pediatrics, Department of Medicine and
Departments of Pediatrics.
Pediatrics. 2017 Nov;140(5). doi: 10.1542/peds.2017-1640. Epub 2017 Oct 3.
Risk-adjustment algorithms typically incorporate demographic and clinical variables to equalize compensation to insurers for enrollees who vary in expected cost, but including information about enrollees' socioeconomic background is controversial.
We studied 1 182 847 continuously insured 0 to 19-year-olds using 2008-2012 Blue Cross Blue Shield of Massachusetts and American Community Survey data. We characterized enrollees' socioeconomic background using the validated area-based socioeconomic measure and calculated annual plan payments using paid claims. We evaluated the relationship between annual plan payments and geocoded socioeconomic background using generalized estimating equations (γ distribution and log link). We expressed outcomes as the percentage difference in spending and utilization between enrollees with high and low socioeconomic backgrounds.
Geocoded socioeconomic background had a significant, positive association with annual plan payments after applying standard adjusters. Every 1 SD increase in socioeconomic background was associated with a 7.8% (95% confidence interval, 7.2% to 8.3%; < .001) increase in spending. High socioeconomic background enrollees used higher-priced outpatient and pharmacy services more frequently than their counterparts from low socioeconomic backgrounds (eg, 25% more outpatient encounters annually; 8% higher price per encounter; < .001), which outweighed greater emergency department spending among low socioeconomic background enrollees.
Higher socioeconomic background is associated with greater levels of pediatric health care spending in commercially insured children. Including socioeconomic information in risk-adjustment algorithms may address concerns about adverse selection from an economic perspective, but it would direct funds away from those caring for children and adolescents from lower socioeconomic backgrounds who are at greater risk of poor health.
风险调整算法通常纳入人口统计学和临床变量,以便在预期成本各异的参保者之间,使保险公司获得的赔付趋于均衡,但纳入参保者社会经济背景信息存在争议。
我们利用2008 - 2012年马萨诸塞州蓝十字蓝盾公司和美国社区调查数据,对1182847名0至19岁持续参保儿童进行了研究。我们使用经过验证的基于区域的社会经济指标来描述参保者的社会经济背景,并根据已支付的索赔计算年度计划赔付。我们使用广义估计方程(γ分布和对数链接)评估年度计划赔付与地理编码的社会经济背景之间的关系。我们将结果表示为社会经济背景高和低的参保者在支出和利用方面的百分比差异。
在应用标准调整因素后,地理编码的社会经济背景与年度计划赔付存在显著的正相关。社会经济背景每增加1个标准差,支出增加7.8%(95%置信区间,7.2%至8.3%;P <.001)。社会经济背景高的参保者比社会经济背景低的参保者更频繁地使用价格较高的门诊和药房服务(例如,每年门诊就诊次数多25%;每次就诊价格高8%;P <.001),这超过了社会经济背景低的参保者更高的急诊科支出。
较高的社会经济背景与商业保险儿童的儿科医疗保健支出水平较高有关。在风险调整算法中纳入社会经济信息可能从经济角度解决对逆向选择的担忧,但这会将资金从照顾社会经济背景较低、健康状况较差风险较高的儿童和青少年的人那里转移走。