Published in:
Open Access 01-12-2008 | Research
Workforce analysis using data mining and linear regression to understand HIV/AIDS prevalence patterns
Published in: Human Resources for Health | Issue 1/2008
Login to get accessAbstract
Background
The achievement of the Millennium Development Goals (MDGs) depends on sufficient supply of health workforce in each country. Although country-level data support this contention, it has been difficult to evaluate health workforce supply and MDG outcomes at the country level. The purpose of the study was to examine the association between the health workforce, particularly the nursing workforce, and the achievement of the MDGs, taking into account other factors known to influence health status, such as socioeconomic indicators.
Methods
A merged data set that includes country-level MDG outcomes, workforce statistics, and general socioeconomic indicators was utilized for the present study. Data were obtained from the Global Human Resources for Health Atlas 2004, the WHO Statistical Information System (WHOSIS) 2000, UN Fund for Development and Population Assistance (UNFDPA) 2000, the International Council of Nurses "Nursing in the World", and the WHO/UNAIDS database.
Results
The main factors in understanding HIV/AIDS prevalence rates are physician density followed by female literacy rates and nursing density in the country. Using general linear model approaches, increased physician and nurse density (number of physicians or nurses per population) was associated with lower adult HIV/AIDS prevalence rate, even when controlling for socioeconomic indicators.
Conclusion
Increased nurse and physician density are associated with improved health outcomes, suggesting that countries aiming to attain the MDGs related to HIV/AIDS would do well to invest in their health workforce. Implications for international and country level policy are discussed.