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Process evaluation of implementation fidelity of the integrated chronic disease management model in two districts, South Africa

BACKGROUND: The Integrated Chronic Disease Management (ICDM) model has been implemented in South Africa to enhance quality of clinical services in Primary Healthcare (PHC) clinics in a context of a high prevalence of chronic conditions and multi-morbidity. This study aimed to assess the implementati...

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Autores principales: Lebina, Limakatso, Alaba, Olufunke, Ringane, Ashley, Hlongwane, Khuthadzo, Pule, Pogiso, Oni, Tolu, Kawonga, Mary
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6916104/
https://www.ncbi.nlm.nih.gov/pubmed/31842881
http://dx.doi.org/10.1186/s12913-019-4785-7
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author Lebina, Limakatso
Alaba, Olufunke
Ringane, Ashley
Hlongwane, Khuthadzo
Pule, Pogiso
Oni, Tolu
Kawonga, Mary
author_facet Lebina, Limakatso
Alaba, Olufunke
Ringane, Ashley
Hlongwane, Khuthadzo
Pule, Pogiso
Oni, Tolu
Kawonga, Mary
author_sort Lebina, Limakatso
collection PubMed
description BACKGROUND: The Integrated Chronic Disease Management (ICDM) model has been implemented in South Africa to enhance quality of clinical services in Primary Healthcare (PHC) clinics in a context of a high prevalence of chronic conditions and multi-morbidity. This study aimed to assess the implementation fidelity (adherence to guidelines) of the ICDM model. METHODS: A cross-sectional study in 16 PHC clinics in two health districts in South Africa: Dr. Kenneth Kaunda (DKK) and West Rand (WR). A fidelity assessment tool with 89 activities and maximum score of 158 was developed from the four interrelated ICDM model components: facility re-organization, clinical supportive management, assisted self-management and strengthening of support systems. Value stream mapping of patient flow was conducted to analyse waiting time and identify operational inefficiencies. ICDM items were scored based on structured observations, facility document reviews and structured questionnaires completed by healthcare workers. Fidelity scores were summarized using medians and proportions and compared by facilities and districts using Chi-Square and Kruskal Wallis test. RESULTS: The monthly patient headcount over a six-month period in these 16 PHC clinics was a median of 2430 (IQR: 1685–2942) individuals over 20 years. The DKK district had more newly diagnosed TB patients per month [median 5.5 (IQR: 4.00–9.33) vs 2.0 (IQR: 1.67–2.92)], and fewer medical officers per clinic [median 1 (IQR: 1–1) vs 3.5 (IQR:2–4.5)] compared to WR district. The median fidelity scores in both districts for facility re-organization, clinical supportive management, assisted self-management and strengthening of support systems were 78% [29/37, IQR: 27–31)]; 77% [30/39 (IQR: 27–34)]; 77% [30/39 (IQR: 28–34)]; and 80% [35/44 (IQR: 30–37)], respectively. The overall median implementation fidelity of the ICDM model was 79% (125/158, IQR, 117–132); WR was 80% (126/158, IQR, 123–132) while DKK was 74% (117/158, IQR, 106–130), p = 0.1409. The lowest clinic fidelity score was 66% (104/158), while the highest was 86% (136/158). A patient flow analysis showed long (2–5 h) waiting times and one stream of care for acute and chronic services. CONCLUSION: There was some variability of scores on components of the ICDM model by PHC clinics. More research is needed on contextual adaptations of the model.
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spelling pubmed-69161042019-12-30 Process evaluation of implementation fidelity of the integrated chronic disease management model in two districts, South Africa Lebina, Limakatso Alaba, Olufunke Ringane, Ashley Hlongwane, Khuthadzo Pule, Pogiso Oni, Tolu Kawonga, Mary BMC Health Serv Res Research Article BACKGROUND: The Integrated Chronic Disease Management (ICDM) model has been implemented in South Africa to enhance quality of clinical services in Primary Healthcare (PHC) clinics in a context of a high prevalence of chronic conditions and multi-morbidity. This study aimed to assess the implementation fidelity (adherence to guidelines) of the ICDM model. METHODS: A cross-sectional study in 16 PHC clinics in two health districts in South Africa: Dr. Kenneth Kaunda (DKK) and West Rand (WR). A fidelity assessment tool with 89 activities and maximum score of 158 was developed from the four interrelated ICDM model components: facility re-organization, clinical supportive management, assisted self-management and strengthening of support systems. Value stream mapping of patient flow was conducted to analyse waiting time and identify operational inefficiencies. ICDM items were scored based on structured observations, facility document reviews and structured questionnaires completed by healthcare workers. Fidelity scores were summarized using medians and proportions and compared by facilities and districts using Chi-Square and Kruskal Wallis test. RESULTS: The monthly patient headcount over a six-month period in these 16 PHC clinics was a median of 2430 (IQR: 1685–2942) individuals over 20 years. The DKK district had more newly diagnosed TB patients per month [median 5.5 (IQR: 4.00–9.33) vs 2.0 (IQR: 1.67–2.92)], and fewer medical officers per clinic [median 1 (IQR: 1–1) vs 3.5 (IQR:2–4.5)] compared to WR district. The median fidelity scores in both districts for facility re-organization, clinical supportive management, assisted self-management and strengthening of support systems were 78% [29/37, IQR: 27–31)]; 77% [30/39 (IQR: 27–34)]; 77% [30/39 (IQR: 28–34)]; and 80% [35/44 (IQR: 30–37)], respectively. The overall median implementation fidelity of the ICDM model was 79% (125/158, IQR, 117–132); WR was 80% (126/158, IQR, 123–132) while DKK was 74% (117/158, IQR, 106–130), p = 0.1409. The lowest clinic fidelity score was 66% (104/158), while the highest was 86% (136/158). A patient flow analysis showed long (2–5 h) waiting times and one stream of care for acute and chronic services. CONCLUSION: There was some variability of scores on components of the ICDM model by PHC clinics. More research is needed on contextual adaptations of the model. BioMed Central 2019-12-16 /pmc/articles/PMC6916104/ /pubmed/31842881 http://dx.doi.org/10.1186/s12913-019-4785-7 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Lebina, Limakatso
Alaba, Olufunke
Ringane, Ashley
Hlongwane, Khuthadzo
Pule, Pogiso
Oni, Tolu
Kawonga, Mary
Process evaluation of implementation fidelity of the integrated chronic disease management model in two districts, South Africa
title Process evaluation of implementation fidelity of the integrated chronic disease management model in two districts, South Africa
title_full Process evaluation of implementation fidelity of the integrated chronic disease management model in two districts, South Africa
title_fullStr Process evaluation of implementation fidelity of the integrated chronic disease management model in two districts, South Africa
title_full_unstemmed Process evaluation of implementation fidelity of the integrated chronic disease management model in two districts, South Africa
title_short Process evaluation of implementation fidelity of the integrated chronic disease management model in two districts, South Africa
title_sort process evaluation of implementation fidelity of the integrated chronic disease management model in two districts, south africa
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6916104/
https://www.ncbi.nlm.nih.gov/pubmed/31842881
http://dx.doi.org/10.1186/s12913-019-4785-7
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