2015
DOI: 10.1016/j.ijmedinf.2015.01.005
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Implementation of a cloud-based electronic medical record for maternal and child health in rural Kenya

Abstract: Background: Complete and timely health information is essential to inform public health decision-

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Cited by 62 publications
(42 citation statements)
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“…Strategies to minimise paper (e.g. cell phone-based audit [ 39 ], cloud-storage [ 49 ]) have been piloted but not scaled up in many low-income settings. Even in settings where an electronic health information system has been rolled out more widely, like the District Health Information System (DHIS) used in Malawi, Rwanda and South Africa, this may have a limited impact if data quality remains poor [ 36 ].…”
Section: Resultsmentioning
confidence: 99%
“…Strategies to minimise paper (e.g. cell phone-based audit [ 39 ], cloud-storage [ 49 ]) have been piloted but not scaled up in many low-income settings. Even in settings where an electronic health information system has been rolled out more widely, like the District Health Information System (DHIS) used in Malawi, Rwanda and South Africa, this may have a limited impact if data quality remains poor [ 36 ].…”
Section: Resultsmentioning
confidence: 99%
“…This sub group has received the most attention at 32% of studies reviewed in the category of evaluation. The rest of the studies assessed data completeness in different healthcare institutions (Cruz-Correia et al, 2013;Haskew et al, 2015;Köpcke et al, 2013), pre-and post-implementation of data quality interventions regarding introduction of advanced information systems (Bruland et al, 2014;Herzberg et al, 2011;van Engen-Verheul et al, 2016) and during different time points (Haskew et al, 2015;Puttkammer et al, 2016;Taggart et al, 2015;Tu et al, 2015).…”
Section: Discussionmentioning
confidence: 99%
“…The ease of electronic feedback of data to providers is associated with improved quality of data [ 16 ]. eRegistry forms improve data quality with functionalities such as logical checks and limitations, warning prompts for improbable or missing data entries [ 29 , 50 , Frost et al, submitted], or pre-defined algorithms to improve correct categorizations, e.g. for causes of death [ 31 ].…”
Section: Resultsmentioning
confidence: 99%