Implementation of Kenya Electronic Medical Records (KenyaEMR): Costs and Efficiencies

Sebastian Kevany; Starley Shade; Chloe Waters; Nancy Puttkammer

doi:doi:10.11648/j.sjph.20231105.11

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Implementation of Kenya Electronic Medical Records (KenyaEMR): Costs and Efficiencies

Sebastian Kevany, Starley Shade, Chloe Waters, Nancy Puttkammer

Published in Science Journal of Public Health (Volume 11, Issue 5)

Received: 29 March 2023 Accepted: 22 May 2023 Published: 6 September 2023

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Abstract

Background: Electronic medical record (EMR) rollout is a key element of health systems strengthening activities. To facilitate national rollout and country ownership of KenyaEMR, we assessed costs associated with development and point-of-care implementation of KenyaEMR supported by the International Training and Education Center for Health (I-TECH) between April 2012 and September 2013. Methods: We reviewed and collated I-TECH costing records and considered KenyaEMR implementation costs through two lenses: (1) overall direct I-TECH project costs to characterize costs across resource category, activity and location; and (2) health facility-specific costs to estimate cost per facility and explore variation in costs across facilities. Results: KenyaEMR development and implementation during this period cost I-TECH US$3,803,810. Human resources represented the majority of costs (51%), followed by travel (25%), and equipment (10%). Deployment (34%), project management (33%), and training and capacity building (22%) made up the largest proportion of I-TECH KenyaEMR costs; software (9%) and curriculum (2%) development costs were lowest. In-country expenses made up 65.9% of costs; this proportion increased over time. I-TECH was able to initiate implementation in 204 facilities and complete an equivalent of 128 implementations. Implementation in a facility, from sensitization through installation and back data entry, cost an average of US$9,879. The cost per patient of KenyaEMR implementation decreased as the number of patients in a facility increased. Cost per patient was uniformly less than US$20 per patient in facilities with more than 700 patients. Conclusions: Human resources, rather than equipment and infrastructure, drove costs of KenyaEMR implementation. Implementation quickly transitioned to be country-led. We observed substantial economies of scale in implementation of KenyaEMR. Resource limited countries should prioritize of implementation of point-of-care EMRs facilities in larger health facilities. Additional research is needed to determine whether point-of-care EMRs improve efficiency or cost-effectiveness of HIV care and treatment in resource-limited settings.

Published in	Science Journal of Public Health (Volume 11, Issue 5)
DOI	10.11648/j.sjph.20231105.11
Page(s)	143-153
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), 2024. Published by Science Publishing Group

Keywords

Electronic Medical Record, Cost, HIV, Resource Limited Settings, Health Systems, Kenya

References

[1]	UNAIDS/PEPFAR (2007). Interim Guidelines on Protecting the Confidentiality and Security of HIV information: Proceedings from a Workshop, 15–17 May 2006, Geneva, Switzerland.
[2]	Government of Kenya (2009b). Health Sector Strategic Plan for Health Information System and Health Sector Health Information System Policy. Government of Kenya Ministry of Health Report: November 2009.
[3]	Forster M, Bailey C, Brinkhof M, Graber C, Boulle A, Spohr M, Balestre E, May M, Keiser O, Jahnf A, & Eggera M (2008). Electronic medical record systems, data quality and loss to follow-up: survey of antiretroviral therapy programmes in resource-limited settings. Bulletin of the World Health Organization (86).
[4]	National AIDS Control Program, Ministries of Health, Government of Kenya (2012), “Standards and Guidelines for EMR Systems in Kenya” (http://www.nascop.or.ke/library/3d/Standards_and_Guidelines_for_EMR_Systems.pdf).
[5]	Tierney WM, Overhage M, McDonald CJ. Demonstrating the Effects of an IAIMS on Health Care Quality and Cost. Journal of the American Medical Informatics Association Volume Number 1997; 4 (2): S41–S56.
[6]	Poissant L. The Impact of Electronic Health Records on Time Efficiency of Physicians and Nurses: A Systematic Review. Journal of the American Medical Informatics Association 2005; 12 (5): 505–516.
[7]	Pizziferri L, Kittler AF, Volk LA, Honour MM, Gupta S, Wang S, et al. Primary care physician time utilization before and after implementation of an electronic health record: A time-motion study. Journal of Biomedical Informatics 2005; 38 (3): 176–188.
[8]	Were MC, Sutherland JM, Bwana M, Ssali J, Emenyonu N, Tierney WM. Patterns of care in two HIV continuity clinics in Uganda, Africa: a time-motion study. AIDS Care 2008; 20 (6): 677–682.
[9]	Castelnuovo B, Babigumira J, Lamorde M, Muwanga A, Kambugu A, Colebunders R. Improvement of the patient flow in a large urban clinic with high HIV seroprevalence in Kampala, Uganda. International Journal of STD & AIDS 2009; 20 (2): 123–124.
[10]	Wanyenze RK, Wagner G, Alamo S, Amanyire G, Ouma J, Kwarisima D, et al. Evaluation of the Efficiency of Patient Flow at Three HIV Clinics in Uganda. AIDS Patient Care and STDs 2010; 24 (7): 441–446.
[11]	Uslu AM, Stausberg J. Value of the electronic patient record: An analysis of the literature. Journal of Biomedical Informatics 2008; 41 (4): 675–682.
[12]	Miller RH, West C, Brown TM, Sim I, Ganchoff C. The Value Of Electronic Health Records In Solo Or Small Group Practices. Health Affairs 2005; 24 (5): 1127–1137.
[13]	Government of Kenya (2009). National AIDS and STI Control Program: The EMR Systems Assessment Harmonization Report. Government of Kenya Ministry of Health Report: November 2009.
[14]	Kirengo, Thomas Onyango. "Frugal digitization of analog video endoscopic medical records in a Kenyan rural medical center." Annals of African Surgery 20, no. 1 (2023): 3-6.
[15]	Mohamed, Yahia, Xing Song, Tamara M. McMahon, Suman Sahil, Meredith Zozus, Zhan Wang, Greater Plains Collaborative, and Lemuel R. Waitman. "Electronic Health Record Data Quality Variability Across a Multistate Clinical Research Network." Journal of Clinical and Translational Science: 1-22.

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APA Style

Sebastian Kevany, Starley Shade, Chloe Waters, Nancy Puttkammer. (2023). Implementation of Kenya Electronic Medical Records (KenyaEMR): Costs and Efficiencies. Science Journal of Public Health, 11(5), 143-153. https://doi.org/10.11648/j.sjph.20231105.11

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ACS Style

Sebastian Kevany; Starley Shade; Chloe Waters; Nancy Puttkammer. Implementation of Kenya Electronic Medical Records (KenyaEMR): Costs and Efficiencies. Sci. J. Public Health 2023, 11(5), 143-153. doi: 10.11648/j.sjph.20231105.11

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AMA Style

Sebastian Kevany, Starley Shade, Chloe Waters, Nancy Puttkammer. Implementation of Kenya Electronic Medical Records (KenyaEMR): Costs and Efficiencies. Sci J Public Health. 2023;11(5):143-153. doi: 10.11648/j.sjph.20231105.11

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@article{10.11648/j.sjph.20231105.11,
  author = {Sebastian Kevany and Starley Shade and Chloe Waters and Nancy Puttkammer},
  title = {Implementation of Kenya Electronic Medical Records (KenyaEMR): Costs and Efficiencies},
  journal = {Science Journal of Public Health},
  volume = {11},
  number = {5},
  pages = {143-153},
  doi = {10.11648/j.sjph.20231105.11},
  url = {https://doi.org/10.11648/j.sjph.20231105.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjph.20231105.11},
  abstract = {Background: Electronic medical record (EMR) rollout is a key element of health systems strengthening activities. To facilitate national rollout and country ownership of KenyaEMR, we assessed costs associated with development and point-of-care implementation of KenyaEMR supported by the International Training and Education Center for Health (I-TECH) between April 2012 and September 2013. Methods: We reviewed and collated I-TECH costing records and considered KenyaEMR implementation costs through two lenses: (1) overall direct I-TECH project costs to characterize costs across resource category, activity and location; and (2) health facility-specific costs to estimate cost per facility and explore variation in costs across facilities. Results: KenyaEMR development and implementation during this period cost I-TECH US$3,803,810. Human resources represented the majority of costs (51%), followed by travel (25%), and equipment (10%). Deployment (34%), project management (33%), and training and capacity building (22%) made up the largest proportion of I-TECH KenyaEMR costs; software (9%) and curriculum (2%) development costs were lowest. In-country expenses made up 65.9% of costs; this proportion increased over time. I-TECH was able to initiate implementation in 204 facilities and complete an equivalent of 128 implementations. Implementation in a facility, from sensitization through installation and back data entry, cost an average of US$9,879. The cost per patient of KenyaEMR implementation decreased as the number of patients in a facility increased. Cost per patient was uniformly less than US$20 per patient in facilities with more than 700 patients. Conclusions: Human resources, rather than equipment and infrastructure, drove costs of KenyaEMR implementation. Implementation quickly transitioned to be country-led. We observed substantial economies of scale in implementation of KenyaEMR. Resource limited countries should prioritize of implementation of point-of-care EMRs facilities in larger health facilities. Additional research is needed to determine whether point-of-care EMRs improve efficiency or cost-effectiveness of HIV care and treatment in resource-limited settings.},
 year = {2023}
}

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TY - JOUR
T1 - Implementation of Kenya Electronic Medical Records (KenyaEMR): Costs and Efficiencies
AU - Sebastian Kevany
AU - Starley Shade
AU - Chloe Waters
AU - Nancy Puttkammer
Y1 - 2023/09/06
PY - 2023
N1 - https://doi.org/10.11648/j.sjph.20231105.11
DO - 10.11648/j.sjph.20231105.11
T2 - Science Journal of Public Health
JF - Science Journal of Public Health
JO - Science Journal of Public Health
SP - 143
EP - 153
PB - Science Publishing Group
SN - 2328-7950
UR - https://doi.org/10.11648/j.sjph.20231105.11
AB - Background: Electronic medical record (EMR) rollout is a key element of health systems strengthening activities. To facilitate national rollout and country ownership of KenyaEMR, we assessed costs associated with development and point-of-care implementation of KenyaEMR supported by the International Training and Education Center for Health (I-TECH) between April 2012 and September 2013. Methods: We reviewed and collated I-TECH costing records and considered KenyaEMR implementation costs through two lenses: (1) overall direct I-TECH project costs to characterize costs across resource category, activity and location; and (2) health facility-specific costs to estimate cost per facility and explore variation in costs across facilities. Results: KenyaEMR development and implementation during this period cost I-TECH US$3,803,810. Human resources represented the majority of costs (51%), followed by travel (25%), and equipment (10%). Deployment (34%), project management (33%), and training and capacity building (22%) made up the largest proportion of I-TECH KenyaEMR costs; software (9%) and curriculum (2%) development costs were lowest. In-country expenses made up 65.9% of costs; this proportion increased over time. I-TECH was able to initiate implementation in 204 facilities and complete an equivalent of 128 implementations. Implementation in a facility, from sensitization through installation and back data entry, cost an average of US$9,879. The cost per patient of KenyaEMR implementation decreased as the number of patients in a facility increased. Cost per patient was uniformly less than US$20 per patient in facilities with more than 700 patients. Conclusions: Human resources, rather than equipment and infrastructure, drove costs of KenyaEMR implementation. Implementation quickly transitioned to be country-led. We observed substantial economies of scale in implementation of KenyaEMR. Resource limited countries should prioritize of implementation of point-of-care EMRs facilities in larger health facilities. Additional research is needed to determine whether point-of-care EMRs improve efficiency or cost-effectiveness of HIV care and treatment in resource-limited settings.
VL - 11
IS - 5
ER -

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Author Information

Sebastian Kevany

Asia-Pacific Center for Security Studies, Honolulu, Hawaii, USA
Starley Shade

Division of Prevention Science, Department of Medicine, University of California, San Francisco, USA
Chloe Waters

International Training and Education Center for Health (I-TECH), University of Washington, Washington D.C., USA
Nancy Puttkammer

International Training and Education Center for Health (I-TECH), University of Washington, Washington D.C., USA

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Plain Text BibTeX RIS

APA Style

Sebastian Kevany, Starley Shade, Chloe Waters, Nancy Puttkammer. (2023). Implementation of Kenya Electronic Medical Records (KenyaEMR): Costs and Efficiencies. Science Journal of Public Health, 11(5), 143-153. https://doi.org/10.11648/j.sjph.20231105.11

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ACS Style

Sebastian Kevany; Starley Shade; Chloe Waters; Nancy Puttkammer. Implementation of Kenya Electronic Medical Records (KenyaEMR): Costs and Efficiencies. Sci. J. Public Health 2023, 11(5), 143-153. doi: 10.11648/j.sjph.20231105.11

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AMA Style

Sebastian Kevany, Starley Shade, Chloe Waters, Nancy Puttkammer. Implementation of Kenya Electronic Medical Records (KenyaEMR): Costs and Efficiencies. Sci J Public Health. 2023;11(5):143-153. doi: 10.11648/j.sjph.20231105.11

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@article{10.11648/j.sjph.20231105.11,
  author = {Sebastian Kevany and Starley Shade and Chloe Waters and Nancy Puttkammer},
  title = {Implementation of Kenya Electronic Medical Records (KenyaEMR): Costs and Efficiencies},
  journal = {Science Journal of Public Health},
  volume = {11},
  number = {5},
  pages = {143-153},
  doi = {10.11648/j.sjph.20231105.11},
  url = {https://doi.org/10.11648/j.sjph.20231105.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjph.20231105.11},
  abstract = {Background: Electronic medical record (EMR) rollout is a key element of health systems strengthening activities. To facilitate national rollout and country ownership of KenyaEMR, we assessed costs associated with development and point-of-care implementation of KenyaEMR supported by the International Training and Education Center for Health (I-TECH) between April 2012 and September 2013. Methods: We reviewed and collated I-TECH costing records and considered KenyaEMR implementation costs through two lenses: (1) overall direct I-TECH project costs to characterize costs across resource category, activity and location; and (2) health facility-specific costs to estimate cost per facility and explore variation in costs across facilities. Results: KenyaEMR development and implementation during this period cost I-TECH US$3,803,810. Human resources represented the majority of costs (51%), followed by travel (25%), and equipment (10%). Deployment (34%), project management (33%), and training and capacity building (22%) made up the largest proportion of I-TECH KenyaEMR costs; software (9%) and curriculum (2%) development costs were lowest. In-country expenses made up 65.9% of costs; this proportion increased over time. I-TECH was able to initiate implementation in 204 facilities and complete an equivalent of 128 implementations. Implementation in a facility, from sensitization through installation and back data entry, cost an average of US$9,879. The cost per patient of KenyaEMR implementation decreased as the number of patients in a facility increased. Cost per patient was uniformly less than US$20 per patient in facilities with more than 700 patients. Conclusions: Human resources, rather than equipment and infrastructure, drove costs of KenyaEMR implementation. Implementation quickly transitioned to be country-led. We observed substantial economies of scale in implementation of KenyaEMR. Resource limited countries should prioritize of implementation of point-of-care EMRs facilities in larger health facilities. Additional research is needed to determine whether point-of-care EMRs improve efficiency or cost-effectiveness of HIV care and treatment in resource-limited settings.},
 year = {2023}
}

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