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A simple statistical method for measuring health status for a child: The case of Indonesia
Syuhada K.a, Wanda D.b, Hartati S.c
a Statistics Research Division, Institut Teknologi Bandung, Indonesia
b Faculty of Nursing, Universitas Indonesia, Indonesia
c Nursing College of Mitra Keluarga, Jakarta, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© ISOSS Publications 2015.In developing countries such as Indonesia, to become a healthy child is an expensive matter. This is due to some factors, especially the level of income of child’s parent. Suppose that a child is not physically ill (a. k. a healthy child). Then, to keep the child healthy may be hard/difficult since the cost (for food and live/stay healthy) is quite high. In this study, we pay particular attention to the economics of becoming a healthy child for the case above (a healthy child) as well as if the child is ill and hospitalized. We do investigate the cost of becoming healthy when (i) the child is fully recovered from his/her illness, and compare it when (ii) the child is discharged before completely recovered due to family request. Some factors related to the recovery of a hospitalized child are type of illness (1-acute, 2-chronic, 3-emergency), nutritional status (1-normal, 2-wasting, 3-severe wasting), length of stay (1-short, 2long) and, of course, its nursing care (1-minimal care, 2-partial care, 3dependent care). A simple health status score is proposed and used to predict the health cost. Statistical logistic regression analysis is carried out to do such computation.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Child,Cost,Healthy life,Logistic regression,Nursing care,Statistical analysis[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]