The purpose of this paper is to implement Six Sigma approach to decrease the length of stay (LOS) of neonatal jaundice patients in an Indian government rural hospital situated in northern hill region.
Six Sigma’s Define–Measure–Analyse–Improve–Control procedure is applied in order to decrease the LOS of neonatal jaundice patients. The mean and standard deviation have been computed as 34.53 and 20.01 h, respectively. The cause and effect diagram is used in the “Analyse” phase of the Six Sigma. The regression analysis and GEMBA observation techniques are used to validate the causes identified through cause and effect diagram.
The waiting time for registration, waiting time for tests, waiting time for phototherapy and time for discharge implementation are the main factors that are responsible for longer LOS. Based on the identified root causes, some recommendations are suggested to the hospital administration and staff members in order to reduce the LOS.
The present research is limited to provide recommendations to the hospital administration to reduce LOS and it entirely depends upon the implementation of the administration. However, target of administration is to reduce the LOS up to 24 h.
Six Sigma model will reduce bottlenecks in LOS and enhance service quality of hospital. The developed regression model will help the doctors and staff members to assess and control the LOS by controlling and minimising the independent variables.
The project will directly provide benefits to society, as LOS will decrease and patients’ satisfaction will automatically increase.
Six Sigma is a developed methodology, but its application in paediatric department is very limited. This is the first ever study of applying Six Sigma for neonatal jaundice patients in India.
Prajapati, D. and Suman, G. (2019), "Six sigma approach for neonatal jaundice patients in an Indian rural hospital – a case study", International Journal of Health Care Quality Assurance, Vol. 33 No. 1, pp. 36-51. https://doi.org/10.1108/IJHCQA-07-2019-0135Download as .RIS
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