Workforce analysis using data mining and linear regression to understand HIV/AIDS prevalence patterns

Elizabeth A. Madigan, Olivier Louis Curet, M. Zrínyi

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number2
JournalHuman Resources for Health
Volume6
DOIs
Publication statusPublished - Jan 31 2008

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Data Mining
Health Manpower
Linear Models
Acquired Immunodeficiency Syndrome
AIDS
data analysis
HIV
regression
Physicians
nurse
health
physician
Nursing
Nurses
nursing
International Council of Nurses
WHO
United Nations
supply
Atlases

ASJC Scopus subject areas

  • Health Policy

Cite this

Workforce analysis using data mining and linear regression to understand HIV/AIDS prevalence patterns. / Madigan, Elizabeth A.; Curet, Olivier Louis; Zrínyi, M.

In: Human Resources for Health, Vol. 6, 2, 31.01.2008.

Research output: Contribution to journalArticle

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