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Design and implementation of an affordable, public sector electronic medical record in rural Nepal.

Overview of attention for article published in BMJ Health & Care Informatics, June 2017
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Title
Design and implementation of an affordable, public sector electronic medical record in rural Nepal.
Published in
BMJ Health & Care Informatics, June 2017
DOI 10.14236/jhi.v24i2.862
Pubmed ID
Authors

Anant Raut, Chase Yarbrough, Vivek Singh, Bikash Gauchan, David Citrin, Varun Verma, Jessica Hawley, Dan Schwarz, Alex Harsha Bangura, Biplav Shrestha, Ryan Schwarz, Mukesh Adhikari, Duncan Maru

Abstract

Globally, electronic medical records are central to the infrastructure of modern healthcare systems. Yet the vast majority of electronic medical records have been designed for resource-rich environments and are not feasible in settings of poverty. Here we describe the design and implementation of an electronic medical record at a public sector district hospital in rural Nepal, and its subsequent expansion to an additional public sector facility.DevelopmentThe electronic medical record was designed to solve for the following elements of public sector healthcare delivery: 1) integration of the systems across inpatient, surgical, outpatient, emergency, laboratory, radiology, and pharmacy sites of care; 2) effective data extraction for impact evaluation and government regulation; 3) optimization for longitudinal care provision and patient tracking; and 4) effectiveness for quality improvement initiatives. For these purposes, we adapted Bahmni, a product built with open-source components for patient tracking, clinical protocols, pharmacy, laboratory, imaging, financial management, and supply logistics. In close partnership with government officials, we deployed the system in February of 2015, added on additional functionality, and iteratively improved the system over the following year. This experience enabled us then to deploy the system at an additional district-level hospital in a different part of the country in under four weeks. We discuss the implementation challenges and the strategies we pursued to build an electronic medical record for the public sector in rural Nepal.DiscussionOver the course of 18 months, we were able to develop, deploy and iterate upon the electronic medical record, and then deploy the refined product at an additional facility within only four weeks. Our experience suggests the feasibility of an integrated electronic medical record for public sector care delivery even in settings of rural poverty.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 134 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 134 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 16%
Student > Bachelor 16 12%
Other 10 7%
Student > Doctoral Student 8 6%
Researcher 8 6%
Other 24 18%
Unknown 46 34%
Readers by discipline Count As %
Medicine and Dentistry 30 22%
Nursing and Health Professions 17 13%
Computer Science 7 5%
Social Sciences 5 4%
Engineering 5 4%
Other 18 13%
Unknown 52 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 February 2019.
All research outputs
#15,237,808
of 25,870,940 outputs
Outputs from BMJ Health & Care Informatics
#306
of 501 outputs
Outputs of similar age
#170,314
of 333,921 outputs
Outputs of similar age from BMJ Health & Care Informatics
#7
of 9 outputs
Altmetric has tracked 25,870,940 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 501 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.7. This one is in the 37th percentile – i.e., 37% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 333,921 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.