Assessment of facility-level antiretroviral treatment patient status utilizing a national-level laboratory cohort : Toward an understanding of system-level tracking and clinic switching in South Africa
Copyright © 2022 Murphy, Shumba, Jamieson, Nattey, Pascoe, Fox, Miot and Maskew..
Background: Most estimates of HIV retention are derived at the clinic level through antiretroviral (ART) patient management systems, which capture ART clinic visit data, yet these cannot account for silent transfers across HIV treatment sites. Patient laboratory monitoring visits may also be observed in routinely collected laboratory data, which include ART monitoring tests such as CD4 count and HIV viral load, key to our work here.
Methods: In this analysis, we utilized the NHLS National HIV Cohort (a system-wide viewpoint) to investigate the accuracy of facility-level estimates of retention in care for adult patients accessing care (defined using clinic visit data on patients under ART recorded in an electronic patient management system) at Themba Lethu Clinic (TLC). Furthermore, we describe patterns of facility switching among all patients and those patients classified as lost to follow-up (LTFU) at the facility level.
Results: Of the 43,538 unique patients in the TLC dataset, we included 20,093 of 25,514 possible patient records (78.8%) in our analysis that were linked with the NHLS National Cohort, and we restricted the analytic sample to patients initiating ART between 1 January 2007 and 31 December 2017. Most (60%) patients were female, and the median age (IQR) at ART initiation was 37 (31-45) years. We found the laboratory records augmented retention estimates by a median of 860 additional active records (about 8% of all median active records across all years) from the facility viewpoint; this augmentation was more noticeable from the system-wide viewpoint, which added evidence of activity of about one-third of total active records in 2017. In 2017, we found 7.0% misclassification at the facility-level viewpoint, a gap which is potentially solvable through data integration/triangulation. We observed 1,134/20,093 (5.6%) silent transfers; these were noticeably more female and younger than the entire dataset. We also report the most common locations for clinic switching at a provincial level.
Discussion: Integration of multiple data sources has the potential to reduce the misclassification of patients as being lost to care and help understand situations where clinic switching is common. This may help in prioritizing interventions that would assist patients moving between clinics and hopefully contribute to services that normalize formal transfers and fewer silent transfers.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:10 |
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| Enthalten in: |
Frontiers in public health - 10(2022) vom: 01., Seite 959481 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Murphy, Joshua P [VerfasserIn] |
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| Links: |
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| Themen: |
Anti-Retroviral Agents |
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| Anmerkungen: |
Date Completed 03.01.2023 Date Revised 23.01.2023 published: Electronic-eCollection Citation Status MEDLINE |
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| doi: |
10.3389/fpubh.2022.959481 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM351013172 |
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| 100 | 1 | |a Murphy, Joshua P |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Assessment of facility-level antiretroviral treatment patient status utilizing a national-level laboratory cohort |b Toward an understanding of system-level tracking and clinic switching in South Africa |
| 264 | 1 | |c 2022 | |
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| 500 | |a Date Completed 03.01.2023 | ||
| 500 | |a Date Revised 23.01.2023 | ||
| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2022 Murphy, Shumba, Jamieson, Nattey, Pascoe, Fox, Miot and Maskew. | ||
| 520 | |a Background: Most estimates of HIV retention are derived at the clinic level through antiretroviral (ART) patient management systems, which capture ART clinic visit data, yet these cannot account for silent transfers across HIV treatment sites. Patient laboratory monitoring visits may also be observed in routinely collected laboratory data, which include ART monitoring tests such as CD4 count and HIV viral load, key to our work here | ||
| 520 | |a Methods: In this analysis, we utilized the NHLS National HIV Cohort (a system-wide viewpoint) to investigate the accuracy of facility-level estimates of retention in care for adult patients accessing care (defined using clinic visit data on patients under ART recorded in an electronic patient management system) at Themba Lethu Clinic (TLC). Furthermore, we describe patterns of facility switching among all patients and those patients classified as lost to follow-up (LTFU) at the facility level | ||
| 520 | |a Results: Of the 43,538 unique patients in the TLC dataset, we included 20,093 of 25,514 possible patient records (78.8%) in our analysis that were linked with the NHLS National Cohort, and we restricted the analytic sample to patients initiating ART between 1 January 2007 and 31 December 2017. Most (60%) patients were female, and the median age (IQR) at ART initiation was 37 (31-45) years. We found the laboratory records augmented retention estimates by a median of 860 additional active records (about 8% of all median active records across all years) from the facility viewpoint; this augmentation was more noticeable from the system-wide viewpoint, which added evidence of activity of about one-third of total active records in 2017. In 2017, we found 7.0% misclassification at the facility-level viewpoint, a gap which is potentially solvable through data integration/triangulation. We observed 1,134/20,093 (5.6%) silent transfers; these were noticeably more female and younger than the entire dataset. We also report the most common locations for clinic switching at a provincial level | ||
| 520 | |a Discussion: Integration of multiple data sources has the potential to reduce the misclassification of patients as being lost to care and help understand situations where clinic switching is common. This may help in prioritizing interventions that would assist patients moving between clinics and hopefully contribute to services that normalize formal transfers and fewer silent transfers | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, N.I.H., Extramural | |
| 650 | 4 | |a Research Support, U.S. Gov't, Non-P.H.S. | |
| 650 | 4 | |a HIV | |
| 650 | 4 | |a clinic switching | |
| 650 | 4 | |a misclassification | |
| 650 | 4 | |a mobility | |
| 650 | 4 | |a retention in care | |
| 650 | 4 | |a silent transfers | |
| 650 | 7 | |a Anti-Retroviral Agents |2 NLM | |
| 700 | 1 | |a Shumba, Khumbo |e verfasserin |4 aut | |
| 700 | 1 | |a Jamieson, Lise |e verfasserin |4 aut | |
| 700 | 1 | |a Nattey, Cornelius |e verfasserin |4 aut | |
| 700 | 1 | |a Pascoe, Sophie |e verfasserin |4 aut | |
| 700 | 1 | |a Fox, Matthew P |e verfasserin |4 aut | |
| 700 | 1 | |a Miot, Jacqui |e verfasserin |4 aut | |
| 700 | 1 | |a Maskew, Mhairi |e verfasserin |4 aut | |
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