- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
Background: Human resources are consistently cited as a leading contributor to health care costs; however the availability of internationally comparable data on health worker earnings for all countries is a challenge for estimating the costs of health care services. This paper describes an econometric model using cross sectional earnings data from the International Labour Organization (ILO) that the World Health Organizations (WHO)-Choosing Interventions that are Cost-efective programme (CHOICE) has used to prepare estimates of health worker earnings (in 2010 USD) for all WHO member states. Methods: The ILO data contained 324 observations of earnings data across 4 skill levels for 193 countries. Using this data, along with the assumption that data were missing not at random, we used a Heckman two stage selection model to estimate earning data for each of the 4 skill levels for all WHO member states. Results: It was possible to develop a prediction model for health worker earnings for all countries for which GDP data was available. Health worker earnings vary both within country due to skill level, as well as across countries. As a multiple of GDP per capita, earnings show a negative correlation with GDP—that is lower income countries pay their health workers relatively more than higher income countries. Conclusions: Limited data on health worker earnings is a limiting factor in estimating the costs of global health programmes. It is hoped that these estimates will support robust health care intervention costings and projections of resources needs over the Sustainable Development Goal period.
When unpublished raw data, that is, uncorrected for onbudget overseas development assistance or exposed to rigorous validity checks, are expressed as a proportion of total health expenditure, human resource costs account for 57% of total health expenditure data. With such a high (nominal) contribution to total health expenditure, the limited data on expected wages by country is a major limiting factor in estimating the fnancial needs required to achieve the sustainable development goals, and particularly to achieve the target on universal health coverage . Tis analysis uses existing datasets to estimate health worker wages by country and to examine trends by income level, as well as to provide information for health care planners, analysts and global health donors to use in developing fnancing projections.
Overall the earnings data show an inverse relationship with income, in that higher-income countries and regions show lower estimated health-worker wage indexes. In other words, the wages of health workers are higher (as a multiple of GDP per capita) in lower-income than in higher-income countries, despite wages in higher-income countries being higher in absolute terms. Both the wages data published by ILO and the aggregate-level data on wages obtained from the Global Health Expenditure Database display many missing observations, and there are in addition multiple potential sources of measurement error. Yet these two sources of estimates agree in important respects and therefore appear to show a plausible range for GDP per capita wages indexes for health workers.