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Impact of Health System Inputs on Health Outcome: A Multilevel Longitudinal Analysis of Botswana National Antiretroviral Program (2002-2013)
OBJECTIVE: To measure the association between the number of doctors, nurses and hospital beds per 10,000 people and individual HIV-infected patient outcomes in Botswana. DESIGN: Analysis of routinely collected longitudinal data from 97,627 patients who received ART through the Botswana National HIV/...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4974006/ https://www.ncbi.nlm.nih.gov/pubmed/27490477 http://dx.doi.org/10.1371/journal.pone.0160206 |
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author | Farahani, Mansoor Price, Natalie El-Halabi, Shenaaz Mlaudzi, Naledi Keapoletswe, Koona Lebelonyane, Refeletswe Fetogang, Ernest Benny Chebani, Tony Kebaabetswe, Poloko Masupe, Tiny Gabaake, Keba Auld, Andrew F. Nkomazana, Oathokwa Marlink, Richard |
author_facet | Farahani, Mansoor Price, Natalie El-Halabi, Shenaaz Mlaudzi, Naledi Keapoletswe, Koona Lebelonyane, Refeletswe Fetogang, Ernest Benny Chebani, Tony Kebaabetswe, Poloko Masupe, Tiny Gabaake, Keba Auld, Andrew F. Nkomazana, Oathokwa Marlink, Richard |
author_sort | Farahani, Mansoor |
collection | PubMed |
description | OBJECTIVE: To measure the association between the number of doctors, nurses and hospital beds per 10,000 people and individual HIV-infected patient outcomes in Botswana. DESIGN: Analysis of routinely collected longitudinal data from 97,627 patients who received ART through the Botswana National HIV/AIDS Treatment Program across all 24 health districts from 2002 to 2013. Doctors, nurses, and hospital bed density data at district-level were collected from various sources. METHODS: A multilevel, longitudinal analysis method was used to analyze the data at both patient- and district-level simultaneously to measure the impact of the health system input at district-level on probability of death or loss-to-follow-up (LTFU) at the individual level. A marginal structural model was used to account for LTFU over time. RESULTS: Increasing doctor density from one doctor to two doctors per 10,000 population decreased the predicted probability of death for each patient by 27%. Nurse density changes from 20 nurses to 25 nurses decreased the predicted probability of death by 28%. Nine percent decrease was noted in predicted mortality of an individual in the Masa program for every five hospital bed density increase. CONCLUSION: Considerable variation was observed in doctors, nurses, and hospital bed density across health districts. Predictive margins of mortality and LTFU were inversely correlated with doctor, nurse and hospital bed density. The doctor density had much greater impact than nurse or bed density on mortality or LTFU of individual patients. While long-term investment in training more healthcare professionals should be made, redistribution of available doctors and nurses can be a feasible solution in the short term. |
format | Online Article Text |
id | pubmed-4974006 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-49740062016-08-18 Impact of Health System Inputs on Health Outcome: A Multilevel Longitudinal Analysis of Botswana National Antiretroviral Program (2002-2013) Farahani, Mansoor Price, Natalie El-Halabi, Shenaaz Mlaudzi, Naledi Keapoletswe, Koona Lebelonyane, Refeletswe Fetogang, Ernest Benny Chebani, Tony Kebaabetswe, Poloko Masupe, Tiny Gabaake, Keba Auld, Andrew F. Nkomazana, Oathokwa Marlink, Richard PLoS One Research Article OBJECTIVE: To measure the association between the number of doctors, nurses and hospital beds per 10,000 people and individual HIV-infected patient outcomes in Botswana. DESIGN: Analysis of routinely collected longitudinal data from 97,627 patients who received ART through the Botswana National HIV/AIDS Treatment Program across all 24 health districts from 2002 to 2013. Doctors, nurses, and hospital bed density data at district-level were collected from various sources. METHODS: A multilevel, longitudinal analysis method was used to analyze the data at both patient- and district-level simultaneously to measure the impact of the health system input at district-level on probability of death or loss-to-follow-up (LTFU) at the individual level. A marginal structural model was used to account for LTFU over time. RESULTS: Increasing doctor density from one doctor to two doctors per 10,000 population decreased the predicted probability of death for each patient by 27%. Nurse density changes from 20 nurses to 25 nurses decreased the predicted probability of death by 28%. Nine percent decrease was noted in predicted mortality of an individual in the Masa program for every five hospital bed density increase. CONCLUSION: Considerable variation was observed in doctors, nurses, and hospital bed density across health districts. Predictive margins of mortality and LTFU were inversely correlated with doctor, nurse and hospital bed density. The doctor density had much greater impact than nurse or bed density on mortality or LTFU of individual patients. While long-term investment in training more healthcare professionals should be made, redistribution of available doctors and nurses can be a feasible solution in the short term. Public Library of Science 2016-08-04 /pmc/articles/PMC4974006/ /pubmed/27490477 http://dx.doi.org/10.1371/journal.pone.0160206 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Research Article Farahani, Mansoor Price, Natalie El-Halabi, Shenaaz Mlaudzi, Naledi Keapoletswe, Koona Lebelonyane, Refeletswe Fetogang, Ernest Benny Chebani, Tony Kebaabetswe, Poloko Masupe, Tiny Gabaake, Keba Auld, Andrew F. Nkomazana, Oathokwa Marlink, Richard Impact of Health System Inputs on Health Outcome: A Multilevel Longitudinal Analysis of Botswana National Antiretroviral Program (2002-2013) |
title | Impact of Health System Inputs on Health Outcome: A Multilevel Longitudinal Analysis of Botswana National Antiretroviral Program (2002-2013) |
title_full | Impact of Health System Inputs on Health Outcome: A Multilevel Longitudinal Analysis of Botswana National Antiretroviral Program (2002-2013) |
title_fullStr | Impact of Health System Inputs on Health Outcome: A Multilevel Longitudinal Analysis of Botswana National Antiretroviral Program (2002-2013) |
title_full_unstemmed | Impact of Health System Inputs on Health Outcome: A Multilevel Longitudinal Analysis of Botswana National Antiretroviral Program (2002-2013) |
title_short | Impact of Health System Inputs on Health Outcome: A Multilevel Longitudinal Analysis of Botswana National Antiretroviral Program (2002-2013) |
title_sort | impact of health system inputs on health outcome: a multilevel longitudinal analysis of botswana national antiretroviral program (2002-2013) |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4974006/ https://www.ncbi.nlm.nih.gov/pubmed/27490477 http://dx.doi.org/10.1371/journal.pone.0160206 |
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