A Test of Accuracy and Completeness in Data Flow Value Chain Within the Context of Early Infant Diagnosis of HIV Using Mixed Methods Approaches

Leonard King’wara; David Omondi Okeyo; Charles Obonyo

doi:doi:10.11648/j.cmr.20160504.11

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A Test of Accuracy and Completeness in Data Flow Value Chain Within the Context of Early Infant Diagnosis of HIV Using Mixed Methods Approaches

Leonard King’wara, David Omondi Okeyo, Charles Obonyo

Published in Clinical Medicine Research (Volume 5, Issue 4)

Received: 5 May 2016 Accepted: 17 May 2016 Published: 4 June 2016

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Abstract

Recent changes to Kenya’s early infant diagnosis (EID) testing algorithm have raised hope that the national goal of reducing perinatal HIV transmission rates to less than 5% can be attained. While programmatic efforts to reach this target are underway, obtaining complete and accurate data from clinical sites to track progress presents a major challenge. The purpose of this study was therefore to assess data completeness, accuracy and challenges in relation to routine EID data management in Kisumu East and Kisumu West Districts within Kisumu County, Kenya. Purposive sampling was used to select 23 active health facilities across the two districts disproportionate by partners. From the selected facilities a sampling frame of 192 patients was established and a sample size of 130 patient’s data selected. Accuracy and completeness were determined by computing sensitivity, specificity, and predictive values. Infant sex, Infant prophylaxis, Breastfeeding information, Entry point, and Test results were found to have registered replication completeness not significantly different from 99% replication at (p>0.05) as oppose to Sample code, Infant Age, Date of sample collection, and PMTCT prophylaxis were found to be significantly different from the 99% replication (p<0.05). On completeness; Sample code and date of sample collection registered completeness beyond the hypothesized value, implying they were complete as required. The remaining data elements including infant sex, infant age, infant prophylaxis, PMTCT prophylaxis, breastfeeding information and entry point were significantly lower than the hypothesized completeness value (p<0.0001) except for test results that had completeness score equal to 0.99. The study, therefore, concludes that despite the shortage of staffing and other challenges, personnel working in the data management system appear to be dedicated, informed and conscientious. However, this research suggests that there is a suboptimal use of the information for local action in certain areas. This assessment thus serves to enlighten policy-makers on the current state of the EID data management system in Kisumu East and West districts.

Published in	Clinical Medicine Research (Volume 5, Issue 4)
DOI	10.11648/j.cmr.20160504.11
Page(s)	63-72
Creative Commons	This is an Open Access article, 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 or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Data Accuracy, Completeness, Early Infant Diagnosis, HIV, PMTCT

References

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[7]	Mbor-Ngacha, D and Shaffer, N (2010). Prevention of Mother-to-Child Transmission of HIV (PMTCT) and Paediatric HIV Care and Treatment. Joint IATT Technical Review mission Report. Ministry of Health Kenya.
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[15]	Cole, C; Israel, E; Ladha, S; Lulu, K; Mathew, R; Mwakangalu, D; Nouga, A (2013. Strengthening Community and Health Systems for Quality PMTCT: Applications in Kenya, Nigeria, South Africa, and Ethiopia. Pathfinder International, 9 Galen Street, Watertown, MA, 02472, USA
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APA Style

Leonard King’wara, David Omondi Okeyo, Charles Obonyo. (2016). A Test of Accuracy and Completeness in Data Flow Value Chain Within the Context of Early Infant Diagnosis of HIV Using Mixed Methods Approaches. Clinical Medicine Research, 5(4), 63-72. https://doi.org/10.11648/j.cmr.20160504.11

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ACS Style

Leonard King’wara; David Omondi Okeyo; Charles Obonyo. A Test of Accuracy and Completeness in Data Flow Value Chain Within the Context of Early Infant Diagnosis of HIV Using Mixed Methods Approaches. Clin. Med. Res. 2016, 5(4), 63-72. doi: 10.11648/j.cmr.20160504.11

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AMA Style

Leonard King’wara, David Omondi Okeyo, Charles Obonyo. A Test of Accuracy and Completeness in Data Flow Value Chain Within the Context of Early Infant Diagnosis of HIV Using Mixed Methods Approaches. Clin Med Res. 2016;5(4):63-72. doi: 10.11648/j.cmr.20160504.11

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@article{10.11648/j.cmr.20160504.11,
  author = {Leonard King’wara and David Omondi Okeyo and Charles Obonyo},
  title = {A Test of Accuracy and Completeness in Data Flow Value Chain Within the Context of Early Infant Diagnosis of HIV Using Mixed Methods Approaches},
  journal = {Clinical Medicine Research},
  volume = {5},
  number = {4},
  pages = {63-72},
  doi = {10.11648/j.cmr.20160504.11},
  url = {https://doi.org/10.11648/j.cmr.20160504.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cmr.20160504.11},
  abstract = {Recent changes to Kenya’s early infant diagnosis (EID) testing algorithm have raised hope that the national goal of reducing perinatal HIV transmission rates to less than 5% can be attained. While programmatic efforts to reach this target are underway, obtaining complete and accurate data from clinical sites to track progress presents a major challenge. The purpose of this study was therefore to assess data completeness, accuracy and challenges in relation to routine EID data management in Kisumu East and Kisumu West Districts within Kisumu County, Kenya. Purposive sampling was used to select 23 active health facilities across the two districts disproportionate by partners. From the selected facilities a sampling frame of 192 patients was established and a sample size of 130 patient’s data selected. Accuracy and completeness were determined by computing sensitivity, specificity, and predictive values. Infant sex, Infant prophylaxis, Breastfeeding information, Entry point, and Test results were found to have registered replication completeness not significantly different from 99% replication at (p>0.05) as oppose to Sample code, Infant Age, Date of sample collection, and PMTCT prophylaxis were found to be significantly different from the 99% replication (p<0.05). On completeness; Sample code and date of sample collection registered completeness beyond the hypothesized value, implying they were complete as required. The remaining data elements including infant sex, infant age, infant prophylaxis, PMTCT prophylaxis, breastfeeding information and entry point were significantly lower than the hypothesized completeness value (p<0.0001) except for test results that had completeness score equal to 0.99. The study, therefore, concludes that despite the shortage of staffing and other challenges, personnel working in the data management system appear to be dedicated, informed and conscientious. However, this research suggests that there is a suboptimal use of the information for local action in certain areas. This assessment thus serves to enlighten policy-makers on the current state of the EID data management system in Kisumu East and West districts.},
 year = {2016}
}

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TY  - JOUR
T1  - A Test of Accuracy and Completeness in Data Flow Value Chain Within the Context of Early Infant Diagnosis of HIV Using Mixed Methods Approaches
AU  - Leonard King’wara
AU  - David Omondi Okeyo
AU  - Charles Obonyo
Y1  - 2016/06/04
PY  - 2016
N1  - https://doi.org/10.11648/j.cmr.20160504.11
DO  - 10.11648/j.cmr.20160504.11
T2  - Clinical Medicine Research
JF  - Clinical Medicine Research
JO  - Clinical Medicine Research
SP  - 63
EP  - 72
PB  - Science Publishing Group
SN  - 2326-9057
UR  - https://doi.org/10.11648/j.cmr.20160504.11
AB  - Recent changes to Kenya’s early infant diagnosis (EID) testing algorithm have raised hope that the national goal of reducing perinatal HIV transmission rates to less than 5% can be attained. While programmatic efforts to reach this target are underway, obtaining complete and accurate data from clinical sites to track progress presents a major challenge. The purpose of this study was therefore to assess data completeness, accuracy and challenges in relation to routine EID data management in Kisumu East and Kisumu West Districts within Kisumu County, Kenya. Purposive sampling was used to select 23 active health facilities across the two districts disproportionate by partners. From the selected facilities a sampling frame of 192 patients was established and a sample size of 130 patient’s data selected. Accuracy and completeness were determined by computing sensitivity, specificity, and predictive values. Infant sex, Infant prophylaxis, Breastfeeding information, Entry point, and Test results were found to have registered replication completeness not significantly different from 99% replication at (p>0.05) as oppose to Sample code, Infant Age, Date of sample collection, and PMTCT prophylaxis were found to be significantly different from the 99% replication (p<0.05). On completeness; Sample code and date of sample collection registered completeness beyond the hypothesized value, implying they were complete as required. The remaining data elements including infant sex, infant age, infant prophylaxis, PMTCT prophylaxis, breastfeeding information and entry point were significantly lower than the hypothesized completeness value (p<0.0001) except for test results that had completeness score equal to 0.99. The study, therefore, concludes that despite the shortage of staffing and other challenges, personnel working in the data management system appear to be dedicated, informed and conscientious. However, this research suggests that there is a suboptimal use of the information for local action in certain areas. This assessment thus serves to enlighten policy-makers on the current state of the EID data management system in Kisumu East and West districts.
VL  - 5
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Author Information

Leonard King’wara

Department of Public Health, Maseno University, Kisumu, Kenya
David Omondi Okeyo

Schools of Public Health, Maseno University, Kisumu, Kenya
Charles Obonyo

Kenya Medical Research Institute, Kisumu, Kenya

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APA Style

Leonard King’wara, David Omondi Okeyo, Charles Obonyo. (2016). A Test of Accuracy and Completeness in Data Flow Value Chain Within the Context of Early Infant Diagnosis of HIV Using Mixed Methods Approaches. Clinical Medicine Research, 5(4), 63-72. https://doi.org/10.11648/j.cmr.20160504.11

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ACS Style

Leonard King’wara; David Omondi Okeyo; Charles Obonyo. A Test of Accuracy and Completeness in Data Flow Value Chain Within the Context of Early Infant Diagnosis of HIV Using Mixed Methods Approaches. Clin. Med. Res. 2016, 5(4), 63-72. doi: 10.11648/j.cmr.20160504.11

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AMA Style

Leonard King’wara, David Omondi Okeyo, Charles Obonyo. A Test of Accuracy and Completeness in Data Flow Value Chain Within the Context of Early Infant Diagnosis of HIV Using Mixed Methods Approaches. Clin Med Res. 2016;5(4):63-72. doi: 10.11648/j.cmr.20160504.11

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@article{10.11648/j.cmr.20160504.11,
  author = {Leonard King’wara and David Omondi Okeyo and Charles Obonyo},
  title = {A Test of Accuracy and Completeness in Data Flow Value Chain Within the Context of Early Infant Diagnosis of HIV Using Mixed Methods Approaches},
  journal = {Clinical Medicine Research},
  volume = {5},
  number = {4},
  pages = {63-72},
  doi = {10.11648/j.cmr.20160504.11},
  url = {https://doi.org/10.11648/j.cmr.20160504.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cmr.20160504.11},
  abstract = {Recent changes to Kenya’s early infant diagnosis (EID) testing algorithm have raised hope that the national goal of reducing perinatal HIV transmission rates to less than 5% can be attained. While programmatic efforts to reach this target are underway, obtaining complete and accurate data from clinical sites to track progress presents a major challenge. The purpose of this study was therefore to assess data completeness, accuracy and challenges in relation to routine EID data management in Kisumu East and Kisumu West Districts within Kisumu County, Kenya. Purposive sampling was used to select 23 active health facilities across the two districts disproportionate by partners. From the selected facilities a sampling frame of 192 patients was established and a sample size of 130 patient’s data selected. Accuracy and completeness were determined by computing sensitivity, specificity, and predictive values. Infant sex, Infant prophylaxis, Breastfeeding information, Entry point, and Test results were found to have registered replication completeness not significantly different from 99% replication at (p>0.05) as oppose to Sample code, Infant Age, Date of sample collection, and PMTCT prophylaxis were found to be significantly different from the 99% replication (p<0.05). On completeness; Sample code and date of sample collection registered completeness beyond the hypothesized value, implying they were complete as required. The remaining data elements including infant sex, infant age, infant prophylaxis, PMTCT prophylaxis, breastfeeding information and entry point were significantly lower than the hypothesized completeness value (p<0.0001) except for test results that had completeness score equal to 0.99. The study, therefore, concludes that despite the shortage of staffing and other challenges, personnel working in the data management system appear to be dedicated, informed and conscientious. However, this research suggests that there is a suboptimal use of the information for local action in certain areas. This assessment thus serves to enlighten policy-makers on the current state of the EID data management system in Kisumu East and West districts.},
 year = {2016}
}

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TY  - JOUR
T1  - A Test of Accuracy and Completeness in Data Flow Value Chain Within the Context of Early Infant Diagnosis of HIV Using Mixed Methods Approaches
AU  - Leonard King’wara
AU  - David Omondi Okeyo
AU  - Charles Obonyo
Y1  - 2016/06/04
PY  - 2016
N1  - https://doi.org/10.11648/j.cmr.20160504.11
DO  - 10.11648/j.cmr.20160504.11
T2  - Clinical Medicine Research
JF  - Clinical Medicine Research
JO  - Clinical Medicine Research
SP  - 63
EP  - 72
PB  - Science Publishing Group
SN  - 2326-9057
UR  - https://doi.org/10.11648/j.cmr.20160504.11
AB  - Recent changes to Kenya’s early infant diagnosis (EID) testing algorithm have raised hope that the national goal of reducing perinatal HIV transmission rates to less than 5% can be attained. While programmatic efforts to reach this target are underway, obtaining complete and accurate data from clinical sites to track progress presents a major challenge. The purpose of this study was therefore to assess data completeness, accuracy and challenges in relation to routine EID data management in Kisumu East and Kisumu West Districts within Kisumu County, Kenya. Purposive sampling was used to select 23 active health facilities across the two districts disproportionate by partners. From the selected facilities a sampling frame of 192 patients was established and a sample size of 130 patient’s data selected. Accuracy and completeness were determined by computing sensitivity, specificity, and predictive values. Infant sex, Infant prophylaxis, Breastfeeding information, Entry point, and Test results were found to have registered replication completeness not significantly different from 99% replication at (p>0.05) as oppose to Sample code, Infant Age, Date of sample collection, and PMTCT prophylaxis were found to be significantly different from the 99% replication (p<0.05). On completeness; Sample code and date of sample collection registered completeness beyond the hypothesized value, implying they were complete as required. The remaining data elements including infant sex, infant age, infant prophylaxis, PMTCT prophylaxis, breastfeeding information and entry point were significantly lower than the hypothesized completeness value (p<0.0001) except for test results that had completeness score equal to 0.99. The study, therefore, concludes that despite the shortage of staffing and other challenges, personnel working in the data management system appear to be dedicated, informed and conscientious. However, this research suggests that there is a suboptimal use of the information for local action in certain areas. This assessment thus serves to enlighten policy-makers on the current state of the EID data management system in Kisumu East and West districts.
VL  - 5
IS  - 4
ER  -

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