Developing Block Wise Composite Health Index in Yavatmal District, Maharashtra State, India: An Analysis of Available Data

被引:0
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作者
Doke, Prakash Prabhakarrao [1 ]
Naravane, Minal [2 ]
Deshpande, Aruna [3 ]
机构
[1] Bharati Vidyapeeth Deemed Univ Med Coll, Dept Community Med, Pune, Maharashtra, India
[2] Yashwantrao Chavan Acad Dev Adm, State Training Planning & Evaluat Agcy, Ctr Human Dev, Pune, Maharashtra, India
[3] Engender Hlth, Pune, Maharashtra, India
关键词
Health System Indicators; Health Outcome Indicators; Other Determinants; Utilization of Health Services;
D O I
暂无
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Introduction: Numerous health indicators from different domains and comprehensive systems for describing health of community at state or district level are in vogue. Some sub-district information is also available from Health Management Information System but the numbers of indicators are many. Here composite health index of sub-district level is calculated similar to documented procedure. Objective: To develop block wise composite health index in an average district, Yavatmal district using available data. Methods: We grouped health indicators in following four categories; health outcomes, health system, other determinants and utilization of services. From these categories we selected four, three, two and one indicator respectively. Almost all the information is collected from already available data. There are 16 blocks in Yavatmal district. Block wise information of all indicators was first compiled. The block having best value was given 100 marks and remaining blocks were given proportionately less marks. The block wise total marks were calculated. The total score was converted into index by dividing by 1,000. Results: The composite health index ranged from 0.369 to 0.794. The median was 0.425 and interquartile range was 0.126. Out of ten, nine health indicators had normal distribution. We observed positive correlation between urbanization and composite health index. The Yavatmal block obtained highest composite index 0.794 and was an outlier. Principal component analysis extracted four components which contributed 82.06% to total variance. Conclusion: Using only ten indicators and simple method blocks composite health index can be developed which may be used to compare blocks or even districts.
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页码:258 / 266
页数:9
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