Measurement, Optimization, and Impact of Health Care Accessibility: A Methodological Review

被引:505
作者
Wang, Fahui [1 ]
机构
[1] Louisiana State Univ, Dept Geog & Anthropol, Baton Rouge, LA 70803 USA
关键词
accessibility measure; health care access; late-stage cancer; optimization; MEASURING SPATIAL ACCESSIBILITY; INTEGRATED APPROACH; SPACE-TIME; ACCESS; LOCATION; DIAGNOSIS; SERVICES; MODELS; EQUITY; INDEX;
D O I
10.1080/00045608.2012.657146
中图分类号
P9 [自然地理学]; K9 [地理];
学科分类号
0705 ; 070501 ;
摘要
Despite spending more than any other nation on medical care per person, the United States ranks behind other industrialized nations in key health performance measures. A main cause is the deep disparities in access to care and health outcomes. Federal programs such as the designations of Medically Underserved Areas/Populations and Health Professional Shortage Areas are designed to boost the number of health professionals serving these areas and to help alleviate the access problem. Their effectiveness relies first and foremost on an accurate measure of accessibility so that resources can be allocated to truly needy areas. Various measures of accessibility need to be integrated into one framework for comparison and evaluation. Optimization methods can be used to improve the distribution and supply of health care providers to maximize service coverage, minimize travel needs of patients, limit the number of facilities, and maximize health or access equality. Inequality in health care access comes at a personal and societal price, evidenced in disparities in health outcomes, including late-stage cancer diagnosis. This review surveys recent literature on the three named issues with emphasis on methodological advancements and implications for public policy.
引用
收藏
页码:1104 / 1112
页数:9
相关论文
共 56 条
[1]  
[Anonymous], 2010, DEATHS MORT
[2]  
[Anonymous], 2000, World Health Report 2000: Health Systems: Improving Performance
[3]  
[Anonymous], AHRQ PUBL
[4]   The effects of geography and spatial behavior on health care utilization among the residents of a rural region [J].
Arcury, TA ;
Gesler, WM ;
Preisser, JS ;
Sherman, J ;
Spencer, J ;
Perin, J .
HEALTH SERVICES RESEARCH, 2005, 40 (01) :135-155
[5]   Spatial Poisson regression for health and exposure data measured at disparate resolutions [J].
Best, NG ;
Ickstadt, K ;
Wolpert, RL .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2000, 95 (452) :1076-1088
[6]  
Church Richard., 1999, Geographical Infor- mation Systems: Principles, Techniques, Management and Applications, V2, P293
[7]   EMPIRICAL BAYES ESTIMATES OF AGE-STANDARDIZED RELATIVE RISKS FOR USE IN DISEASE MAPPING [J].
CLAYTON, D ;
KALDOR, J .
BIOMETRICS, 1987, 43 (03) :671-681
[8]   EQUITY AND EQUALITY IN HEALTH AND HEALTH-CARE [J].
CULYER, AJ ;
WAGSTAFF, A .
JOURNAL OF HEALTH ECONOMICS, 1993, 12 (04) :431-457
[9]   Black residential segregation, disparities in spatial access to health care facilities, and late-stage breast cancer diagnosis in metropolitan Detroit [J].
Dai, Dajun .
HEALTH & PLACE, 2010, 16 (05) :1038-1052
[10]  
Department of Health and Human Services, 2008, DES MED UND POP HLTH