A DEA evaluation of U.S. States' healthcare systems in terms of their birth outcomes. (15th November 2021)

• Record Type: Journal Article
• Authors: Darabi, Negar; Ebrahimvandi, Alireza; Hosseinichimeh, Niyousha; Triantis, Konstantinos
• Is Part Of: Expert systems with applications. Volume 182(2021)
• Publication Date: 2021-11-15
• Subjects: Data envelopment analysis -- Bootstrapping -- Robust principal component analysis -- Birth outcomes -- Healthcare system efficiency; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2021.115278
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: Data envelopment analysis, robust principal component analysis, and bootstrapping. Performance of healthcare systems of the US in terms of their birth outcomes. Contextual factors explain the variation in healthcare systems' performance. Identify those who are at higher risk of giving unfavorable birth outcome. Abstract: States vary substantially in terms of infant mortality and preterm birth rates. Despite all the attention and effort at the national level in improving birth outcomes, many states' healthcare systems are still suffering from high rates of unfavorable birth outcomes. Hence, the important question is what makes a healthcare system more successful when evaluating birth outcomes at the state level. To answer this question, we build a state–level database using data from the Centers for Disease Control and Prevention, Kaiser Family Foundation, and Area Health Resources File. Then, we implement a mixed-methods approach that includes Data Envelopment Analysis (DEA), robust principal component analysis, bootstrapping, and statistical characteristics methods such as truncated regression to systematically compare and contrast the performance of 50 state's healthcare systems with respect to their birth outcomes (i.e., infant mortality, preterm birth, and low birthweight) and to provide benchmarks. Our findings reveal that socio-economic and demographic factors such as the poverty rate and the number of African-American women per 1000 population significantly explain the major variation in healthcare systems' performance in terms of their birth outcomes. Therefore, disregarding these environmental factors leads to an overestimation of the system's efficiency. Furthermore, our work contributes to the body of literature by introducing a unique application in the domain of efficiency performance measurement of states' healthcare systems in the U.S., using a unique dataset that has not been analyzed before, identifying efficient and inefficient states, providing peers for each inefficient state and indicating how those inefficient states can make improvement in their performance, and providing unique policy insights.