DeLia Derek
Center for State Health Policy, The Institute for Health, Health Care Policy, and Aging Research Rutgers, The State University, New Brunswick, NJ 08901-2008, USA.
Health Serv Res. 2003 Dec;38(6 Pt 2):1761-79. doi: 10.1111/j.1475-6773.2003.00201.x.
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.
New York State hospital discharge data 1990-1998, U.S. census data 1990, and New York State birth records 1990.
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.
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.
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.
根据邮政编码区域的人口统计学特征及其他特点，描述邮政编码区域层面的门诊医疗敏感型（ACS）住院情况模式。这些模式包括随时间的趋势、邮政编码区域内随时间的持续性，以及社会经济阶层之间和内部的差异。
1990 - 1998年纽约州医院出院数据、1990年美国人口普查数据以及1990年纽约州出生记录。
在邮政编码区域层面计算年龄和性别调整后的ACS住院率及住院量。对描述性统计数据进行横断面分析和随时间的分析。估计各收入阶层的核密度函数。运用普通回归和分位数回归技术来确定社会经济变量对ACS住院率分布的均值和极值的影响。
在研究期间，门诊医疗敏感型住院率有所下降，但总体住院率下降幅度更大。因此，作为总住院人数的百分比，其实际上上升了4%。门诊医疗敏感型住院在地理上集中，且邮政编码区域内的住院率随时间高度持续。即使按对数尺度衡量，低收入邮政编码区域的ACS住院率通常更高且变异性更大。与ACS住院呈正相关的其他变量包括总人口、未婚母亲生育数（家庭结构的一个指标）、黑人人口、西班牙裔人口以及非ACS住院数。移民母亲生育数（移民人口的一个指标）与ACS住院呈负相关。
ACS住院的集中性和持续性表明，在服务最不足的社区，初级门诊医疗长期存在地理上有限的不足。高收入和低收入地区可预防住院水平的大部分差异是由低收入地区与人口密度无关的极高住院量驱动的。纽约的数据表明，通过关注特定社区，可节省大部分可预防住院的费用。社会经济和地区利用变量在邮政编码区域层面可预防住院率的均值和极值方面均发挥作用。由于影响可预防住院平均数量的变量会改变该数量的分布，仅基于均值的分析可能并不充分。关于地区人口统计学和非ACS住院的研究结果表明，有必要更好地理解社会和文化问题以及当地的住院实践模式，以鼓励对医疗保健提供系统进行适当且有效的利用。
