Hussey Peter S
RAND, 1200 S. Hayes St. w6w, Arlington, VA 22202, USA.
Health Policy. 2007 Dec;84(2-3):298-307. doi: 10.1016/j.healthpol.2007.04.005. Epub 2007 Jun 14.
To analyze the dynamics of physician international migration patterns and identify the countries deviating most from expected migration rates.
A negative binomial log-linear model of physician migration to the United States from every other country was constructed using a panel of country-level data for years 1994-2000. The model was used to identify factors associated with physician migration and to identify countries with higher or lower rates of physician migration than expected.
Physician migration varied with a country's GDP per capita in an inverse-U pattern, with highest migration rates from middle-income countries. The absence of medical schools, immigrant networks in the United States, medical instruction in English, proximity to the United States, and the lack of political and civil liberties were also associated with higher migration rates. Countries with higher-than-predicted migration rates included Iceland, Albania, Armenia, Dominica, Lebanon, Syria, the United Arab Emirates, and Bulgaria. Countries with lower-than-predicted migration rates included Mexico, Japan, Brazil, Zimbabwe, Mauritania, Portugal, Senegal, and France.
This analysis shows that many of the most powerful factors associated with physician migration are difficult or impossible for countries to change through public policy. GDP per capita and proximity to the U.S. are two of the most powerful predictors of physician migration. Networks of immigrants in the U.S. and fewer political and civil liberties also put countries at higher risk for physician emigration. Several other factors that were associated with physician migration might be more easily amenable to policy intervention. These factors include the absence of a medical school and medical instruction in English. Policies addressing these factors would involve making several difficult tradeoffs, however. Other examples of policies that are effective in minimizing physician migration might be found by examining countries with lower-than-expected migration rates.
分析医生国际移民模式的动态变化，并确定与预期移民率偏差最大的国家。
利用1994 - 2000年国家层面的数据面板，构建了一个从其他国家向美国医生移民的负二项对数线性模型。该模型用于确定与医生移民相关的因素，并识别医生移民率高于或低于预期的国家。
医生移民率与一个国家的人均国内生产总值呈倒U型关系，中等收入国家的移民率最高。医学院校的缺乏、美国的移民网络、英语医学教育、与美国的距离以及政治和公民自由的缺乏也与较高的移民率相关。移民率高于预测的国家包括冰岛、阿尔巴尼亚、亚美尼亚、多米尼克、黎巴嫩、叙利亚、阿拉伯联合酋长国和保加利亚。移民率低于预测的国家包括墨西哥、日本、巴西、津巴布韦、毛里塔尼亚、葡萄牙、塞内加尔和法国。
该分析表明，许多与医生移民相关的最有力因素，国家很难或不可能通过公共政策加以改变。人均国内生产总值和与美国的距离是医生移民的两个最有力预测因素。美国的移民网络以及较少的政治和公民自由也使各国面临更高的医生移民风险。与医生移民相关的其他几个因素可能更容易受到政策干预。这些因素包括医学院校的缺乏和英语医学教育。然而，解决这些因素的政策将涉及做出一些艰难的权衡。通过研究移民率低于预期的国家，可能会找到其他有效减少医生移民的政策例子。
