Maternal and Child Health Care Quality Assessment: An Improved Approach Using K-Means Clustering
Open Access
- 1 January 2022
- journal article
- research article
- Published by Scientific Research Publishing, Inc. in Journal of Data Analysis and Information Processing
- Vol. 10 (03), 170-183
- https://doi.org/10.4236/jdaip.2022.103011
Abstract
High maternal and child deaths in developing countries are frequently linked to poor health services provided to pregnant women and children. To improve the quality of maternal, neonatal and child health (MNCH) services, the government and other stakeholders in MNCH emphasize the importance of quality assessment. However, effective quality assessment approaches are mostly lacking in most developing countries, particularly in Tanzania. This study, therefore, aimed at developing a quality assessment approach that can effectively assess and report on the quality of MNCH services. Due to the need for a good quality assessment approach that suits a resource-constrained environment, machine learning-based approach was proposed and developed. K-means algorithm was used to develop a clustering model that groups MNCH data and performs cluster summarization to discover the knowledge portrayed in each group on the quality of MNCH services. Results confirmed the clustering model’s ability to assign the data points into appropriate clusters; cluster analysis with the collaboration of MNCH experts successfully discovered insights on the quality of services portrayed by each group.Keywords
This publication has 28 references indexed in Scilit:
- Donabedian’s Lasting Framework for Health Care QualityThe New England Journal of Medicine, 2016
- Measuring Quality of Maternal and Newborn Care in Developing Countries Using Demographic and Health SurveysPLOS ONE, 2016
- Accountability for quality of care: Monitoring all aspects of quality across a framework adapted for actionInternational Journal of Gynecology & Obstetrics, 2015
- Quality of antenatal and childbirth care in rural health facilities in Burkina Faso, Ghana and Tanzania: an intervention studyTropical Medicine & International Health, 2015
- Reliability Prediction of Webpages in the Medical DomainLecture Notes in Computer Science, 2012
- Guideline for good evaluation practice in health informatics (GEP-HI)International Journal of Medical Informatics, 2011
- An Agent Oriented Approach for Implementation of the Range Method of Initial Centroids in K-Means Clustering Data Mining AlgorithmInternational Journal of Information Processing and Management, 2010
- Unsupervised LearningLecture Notes in Computer Science, 2004
- The quality of care. How can it be assessed?JAMA, 1988
- Quality Assessment and MonitoringEvaluation & the Health Professions, 1983