HIV Patients Drop Out in Indonesia: Associated Factors and Potential Productivity Loss

Aim: this study reported various factors associated with a higher probability of HIV patients drop out, and potential productivity loss due to HIV patients drop out. Methods: we analyzed data of 658 HIV patients from a database in a main referral hospital in Bandung city, West Java, Indonesia from 2...

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Main Authors: Adiatma YM. Siregar, Pipit Pitriyan, Rudi Wisaksana
Format: Article
Language:English
Published: Interna Publishing 2017-05-01
Series:Acta Medica Indonesiana
Subjects:
Online Access:https://actamedindones.org/index.php/ijim/article/view/199
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author Adiatma YM. Siregar
Pipit Pitriyan
Rudi Wisaksana
author_facet Adiatma YM. Siregar
Pipit Pitriyan
Rudi Wisaksana
author_sort Adiatma YM. Siregar
collection DOAJ
description Aim: this study reported various factors associated with a higher probability of HIV patients drop out, and potential productivity loss due to HIV patients drop out. Methods: we analyzed data of 658 HIV patients from a database in a main referral hospital in Bandung city, West Java, Indonesia from 2007 to 2013. First, we utilized probit regression analysis and included, among others, the following variables: patients’ status (active or drop out), CD4 cell count, TB and opportunistic infection (OI), work status, sex, history of injecting drugs, and support from family and peers. Second, we used the drop out data from our database and CD 4 cell count decline rate from another study to estimate the productivity loss due to HIV patients drop out. Results: lower CD4 cell count was associated with a higher probability of drop out. Support from family/peers, living with family, and diagnosed with TB were associated with lower probability of drop out. The productivity loss at national level due to treatment drop out (consequently, due to CD4 cell count decline) can reach US$365 million (using average wage). Conclusion: first, as lower CD 4 cell count was associated with higher probability of drop out, we recommend (to optimize) early ARV initiation at a higher CD 4 cell count, involving scaling up HIV service at the community level. Second, family/peer support should be further emphasized to further ensure treatment success. Third, dropping out from ART will result in a relatively large productivity loss.
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spelling doaj-art-a4c3b78f914f415fa98cc30dea36e0782025-08-20T03:13:54ZengInterna PublishingActa Medica Indonesiana0125-93262338-27322017-05-01483HIV Patients Drop Out in Indonesia: Associated Factors and Potential Productivity LossAdiatma YM. Siregar0Pipit Pitriyan1Rudi Wisaksana2Department of Economics, Center for Economics and Development Studies, Faculty of Economics and Business, Padjadjaran University, Bandung, IndonesiaDepartment of Economics, Center for Economics and Development Studies, Faculty of Economics and Business, Padjadjaran University, Bandung, IndonesiaDepartment of Internal Medicine, Hasan Sadikin Hospital/ Faculty of Medicine, Padjadjaran University, Bandung, IndonesiaAim: this study reported various factors associated with a higher probability of HIV patients drop out, and potential productivity loss due to HIV patients drop out. Methods: we analyzed data of 658 HIV patients from a database in a main referral hospital in Bandung city, West Java, Indonesia from 2007 to 2013. First, we utilized probit regression analysis and included, among others, the following variables: patients’ status (active or drop out), CD4 cell count, TB and opportunistic infection (OI), work status, sex, history of injecting drugs, and support from family and peers. Second, we used the drop out data from our database and CD 4 cell count decline rate from another study to estimate the productivity loss due to HIV patients drop out. Results: lower CD4 cell count was associated with a higher probability of drop out. Support from family/peers, living with family, and diagnosed with TB were associated with lower probability of drop out. The productivity loss at national level due to treatment drop out (consequently, due to CD4 cell count decline) can reach US$365 million (using average wage). Conclusion: first, as lower CD 4 cell count was associated with higher probability of drop out, we recommend (to optimize) early ARV initiation at a higher CD 4 cell count, involving scaling up HIV service at the community level. Second, family/peer support should be further emphasized to further ensure treatment success. Third, dropping out from ART will result in a relatively large productivity loss.https://actamedindones.org/index.php/ijim/article/view/199HIVsocio-economicantiretroviral therapyIndonesiadrop out
spellingShingle Adiatma YM. Siregar
Pipit Pitriyan
Rudi Wisaksana
HIV Patients Drop Out in Indonesia: Associated Factors and Potential Productivity Loss
Acta Medica Indonesiana
HIV
socio-economic
antiretroviral therapy
Indonesia
drop out
title HIV Patients Drop Out in Indonesia: Associated Factors and Potential Productivity Loss
title_full HIV Patients Drop Out in Indonesia: Associated Factors and Potential Productivity Loss
title_fullStr HIV Patients Drop Out in Indonesia: Associated Factors and Potential Productivity Loss
title_full_unstemmed HIV Patients Drop Out in Indonesia: Associated Factors and Potential Productivity Loss
title_short HIV Patients Drop Out in Indonesia: Associated Factors and Potential Productivity Loss
title_sort hiv patients drop out in indonesia associated factors and potential productivity loss
topic HIV
socio-economic
antiretroviral therapy
Indonesia
drop out
url https://actamedindones.org/index.php/ijim/article/view/199
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AT pipitpitriyan hivpatientsdropoutinindonesiaassociatedfactorsandpotentialproductivityloss
AT rudiwisaksana hivpatientsdropoutinindonesiaassociatedfactorsandpotentialproductivityloss