↓ Skip to main content

PLOS

Costs and Cost-Effectiveness of a Mobile Phone Text-Message Reminder Programmes to Improve Health Workers' Adherence to Malaria Guidelines in Kenya

Overview of attention for article published in PLOS ONE, December 2012
Altmetric Badge

Mentioned by

policy
1 policy source
twitter
6 X users
facebook
1 Facebook page

Citations

dimensions_citation
64 Dimensions

Readers on

mendeley
210 Mendeley
citeulike
1 CiteULike
Title
Costs and Cost-Effectiveness of a Mobile Phone Text-Message Reminder Programmes to Improve Health Workers' Adherence to Malaria Guidelines in Kenya
Published in
PLOS ONE, December 2012
DOI 10.1371/journal.pone.0052045
Pubmed ID
Authors

Dejan Zurovac, Bruce A. Larson, Raymond K. Sudoi, Robert W. Snow

Abstract

Simple interventions for improving health workers' adherence to malaria case-management guidelines are urgently required across Africa. A recent trial in Kenya showed that text-message reminders sent to health workers' mobile phones improved management of pediatric outpatients by 25 percentage points. In this paper we examine costs and cost-effectiveness of this intervention.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 210 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
South Africa 3 1%
United Kingdom 2 <1%
Bangladesh 1 <1%
United States 1 <1%
Philippines 1 <1%
Unknown 202 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 47 22%
Researcher 34 16%
Student > Ph. D. Student 22 10%
Student > Bachelor 18 9%
Student > Doctoral Student 14 7%
Other 47 22%
Unknown 28 13%
Readers by discipline Count As %
Medicine and Dentistry 46 22%
Social Sciences 28 13%
Nursing and Health Professions 19 9%
Computer Science 19 9%
Agricultural and Biological Sciences 12 6%
Other 40 19%
Unknown 46 22%