{"title":"通过使用数据挖掘技术寻找不同社会经济和教育分割区域的有影响力的医疗保健干预措施:对印度九个高度关注的州的案例研究","authors":"P. Saha, U. K. Banerjee","doi":"10.20894/IJDMTA.102.005.002.013","DOIUrl":null,"url":null,"abstract":"- United Nations at Millennium Summit 2000 made targets on Under-five Mortality Ratio (U5MR) and Maternal Mortality Ratio (MMR) for improving health condition of mothers and children. Though India did not be able to achieve those targets but have improved significantly. Aim of the study is to find out influential healthcare interventions of socio-economically and educationally different regions which have high impact on their HIs. At resource constrained condition, strategic evidence based planning will help healthcare department to reduce inequity in HIs among different regions. Data of different HIs has been collected from Family Welfare Statistics of India 2012 and healthcare interventions have been collected from District Level Household Survey 3. 192 districts from ‘Nine High Focus States of India’ have been used as case study area in this research work. Both hierarchical and k-means, clustering techniques have been used for segmenting 192 districts based on their socio-economic and educational status and decision tree classification technique has been used for building relationship model for each segment. Total six decision tree classifiers have been developed for identifying most influential interventions on Infant Mortality Rate (IMR) and U5MR. From this work it has become clear that impact of healthcare interventions on healthcare indicators varies from region to region. In hilly regions, adolescent interventions had more impact on U5MR and IMR than child age interventions.","PeriodicalId":414709,"journal":{"name":"International Journal of Data Mining Techniques and Applications","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Finding influential healthcare interventions of different socio-economically and educationally segmented regions by using data mining techniques: case study on nine high focus states of India\",\"authors\":\"P. Saha, U. K. Banerjee\",\"doi\":\"10.20894/IJDMTA.102.005.002.013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"- United Nations at Millennium Summit 2000 made targets on Under-five Mortality Ratio (U5MR) and Maternal Mortality Ratio (MMR) for improving health condition of mothers and children. Though India did not be able to achieve those targets but have improved significantly. Aim of the study is to find out influential healthcare interventions of socio-economically and educationally different regions which have high impact on their HIs. At resource constrained condition, strategic evidence based planning will help healthcare department to reduce inequity in HIs among different regions. Data of different HIs has been collected from Family Welfare Statistics of India 2012 and healthcare interventions have been collected from District Level Household Survey 3. 192 districts from ‘Nine High Focus States of India’ have been used as case study area in this research work. Both hierarchical and k-means, clustering techniques have been used for segmenting 192 districts based on their socio-economic and educational status and decision tree classification technique has been used for building relationship model for each segment. Total six decision tree classifiers have been developed for identifying most influential interventions on Infant Mortality Rate (IMR) and U5MR. From this work it has become clear that impact of healthcare interventions on healthcare indicators varies from region to region. In hilly regions, adolescent interventions had more impact on U5MR and IMR than child age interventions.\",\"PeriodicalId\":414709,\"journal\":{\"name\":\"International Journal of Data Mining Techniques and Applications\",\"volume\":\"73 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Data Mining Techniques and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.20894/IJDMTA.102.005.002.013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Data Mining Techniques and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20894/IJDMTA.102.005.002.013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Finding influential healthcare interventions of different socio-economically and educationally segmented regions by using data mining techniques: case study on nine high focus states of India
- United Nations at Millennium Summit 2000 made targets on Under-five Mortality Ratio (U5MR) and Maternal Mortality Ratio (MMR) for improving health condition of mothers and children. Though India did not be able to achieve those targets but have improved significantly. Aim of the study is to find out influential healthcare interventions of socio-economically and educationally different regions which have high impact on their HIs. At resource constrained condition, strategic evidence based planning will help healthcare department to reduce inequity in HIs among different regions. Data of different HIs has been collected from Family Welfare Statistics of India 2012 and healthcare interventions have been collected from District Level Household Survey 3. 192 districts from ‘Nine High Focus States of India’ have been used as case study area in this research work. Both hierarchical and k-means, clustering techniques have been used for segmenting 192 districts based on their socio-economic and educational status and decision tree classification technique has been used for building relationship model for each segment. Total six decision tree classifiers have been developed for identifying most influential interventions on Infant Mortality Rate (IMR) and U5MR. From this work it has become clear that impact of healthcare interventions on healthcare indicators varies from region to region. In hilly regions, adolescent interventions had more impact on U5MR and IMR than child age interventions.