Distributional issues in the analysis of preventable hospitalizations
Distributional issues in the analysis of preventable hospitalizations
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DOI：
10.1111/j.1475-6773.2003.00201.x
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发表时间：
2003-12-01
影响因子：
3.4
通讯作者：
DeLia, D
中科院分区：
文献类型：
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作者：
DeLia, D
Objective.根据邮政编码人口统计学和其他特征，描述邮政编码水平的门诊护理敏感（ACS）入院模式。这些模式包括随时间变化的趋势，随时间变化的邮政编码内的持续性，以及社会经济阶层之间和内部的变化。纽约州医院1990-1998年出院数据，美国1990年人口普查数据，和纽约州1990年出生记录。年龄和性别调整的ACS入院率和数量是在邮政编码水平计算的。对描述性统计量进行了横断面和随时间的分析。核密度函数估计跨收入阶层。普通和分位数回归技术用于确定社会经济变量对ACS入院率分布的平均值和极端值的影响。在研究期间，门诊护理敏感的入院率下降，但总体入院率下降幅度更大。因此，作为总录取人数的百分比，他们实际上上升了4%。门诊护理敏感的入院是地理集中和利率是高度持久的邮政编码随着时间的推移。即使在对数尺度上，ACS的入学率通常也更高，并且在低收入邮政编码中表现出更多的可变性。与ACS入院呈正相关的其他变量是总人口，未婚母亲的出生（家庭结构的代理），黑人人口，西班牙裔人口和非ACS入院人数。移民母亲（移民人口的代表）的出生与ACS入院率呈负相关。ACS入院的集中和持续性表明，在大多数服务不足的社区，初级门诊护理存在慢性的、地理上有限的不足。高收入地区和低收入地区之间可预防住院水平的差异主要是由于低收入地区的高住院量造成的，与人口密度无关。纽约的数据表明，通过关注目标社区，可以节省可预防的住院治疗的大部分费用。社会经济和地区利用率变量在邮政编码水平的可预防住院率的平均值和极端值中发挥作用。由于影响可预防住院平均数量的变量可能会改变该数量的分布，因此仅基于平均数的分析可能是不够的。关于地区人口统计和非ACS入院的调查结果表明，需要更好地了解社会和文化问题以及当地的入院实践模式，以鼓励适当和有效地利用医疗保健服务系统。
Objective. To describe patterns in ambulatory care sensitive (ACS) admissions at the zip code level based on zip code demographic and other characteristics. These patterns include trends over time, persistence within zip codes over time, and variation between and within socioeconomic strata.Data Sources. New York State hospital discharge data 1990-1998, U.S. census data 1990, and New York State birth records 1990.Study Design. Age- and sex-adjusted rates and volumes of ACS admissions are calculated at the zip code level. Descriptive statistics are analyzed cross-sectionally and over time. Kernel density functions are estimated across income strata. Ordinary and quantile regression techniques are used to determine the impact of socioeconomic variables on average and extreme values of the distribution of ACS admission rates.Principal Findings. Ambulatory care sensitive admissions rates declined during the study period but in conjunction with a greater decline in overall admission rates. Thus, as a percentage of total admissions, they actually rose by 4 percent. Ambulatory care sensitive admissions are geographically concentrated and rates are highly persistent within zip codes over time. Even on a log scale ACS admissions are typically greater and exhibit more variability among low-income zip codes. Other variables positively associated with ACS admissions are total population, births to unwed mothers (a proxy for family structure), black population, Hispanic population, and the number of non-ACS admissions. Births to immigrant mothers (a proxy for immigrant population) are negatively associated with ACS admissions.Conclusions. The concentration and persistence of ACS admissions point to a chronic, geographically limited deficiency of primary ambulatory care in the most underserved neighborhoods. Much of the difference in preventable hospitalization levels between high- and low-income areas is driven by very high volumes in the low-income areas unrelated to population density. New York data suggest that most costs from preventable hospitalizations could be saved by focusing on targeted neighborhoods. Socioeconomic and area utilization variables play a role in both average and extreme values of the rate of preventable hospitalizations at the zip code level. Since variables that affect the average volume of preventable hospitalizations can change the distribution of that volume, analysis based on averages alone may be inadequate. The findings on area demographics and non-ACS admissions point to the need to better understand social and cultural issues as well as local admitting practice patterns to encourage appropriate and efficient use of the health care delivery system.