K-means clustering is a popular clustering algorithm but is having some problems as initial conditions and it will fuse in local minima. A method was proposed to overcome this problem known as Global K-Means clustering algorithm (GKM). This algorithm has excellent skill to reduce the computational load without significantly affecting the solution quality. We studied GKM and its variants and presents a survey with critical analysis. We also proposed a new concept of Faster Global K-means algorithms for Streamed Data sets (FGKM-SD). FGKM-SD improves the efficiency of clustering and will take low time & storage space.

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Background:Ministry of Health and Family Welfare has developed National Quality Framework to assess the quality of services for improvement and helps in certification of facilities, while Kayakalp was launched to promote cleanliness and hygiene in public health facilities.Objective:The objective of the study is to assess if Kayakalp implementation within the public health facilities supports quality certification of health facilities.Methods:A retrospective study was designed to gather data for 32 quality-certified district hospitals under National Quality Assurance Standards (NQAS) between May 2015 and April 2018 by reviewing records. Certification criteria and their external assessment checklist under NQAS and Kayakalp program for district hospitals were extracted from their respective states. External assessment score of all district hospitals under study was entered and analyzed using Statistical Package for the Social Sciences version 22 for Pearson's correlation analysis and MS Excel 2016 for statistical analysis.Results:Pearson's correlation coefficient was 0.217, which means that Kayakalp implementation has less significance on the quality certification of public health facilities to NQAS. A scatter chart was plotted which depicts nonlinear relationship between dependent and independent variable.Conclusion:Overall impact of implementation of Kayakalp initiative on quality certification of public health facilities to NQAS was significantly low; however, this could be due to less weightage given to the checkpoints in NQAS as compared to in NQAS.

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