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Defining a staged-based process for economic and financial evaluations of mHealth programs

Overview of attention for article published in Cost Effectiveness and Resource Allocation, April 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

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16 X users

Citations

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21 Dimensions

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112 Mendeley
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Title
Defining a staged-based process for economic and financial evaluations of mHealth programs
Published in
Cost Effectiveness and Resource Allocation, April 2017
DOI 10.1186/s12962-017-0067-6
Pubmed ID
Authors

Amnesty E. LeFevre, Samuel D. Shillcutt, Sean Broomhead, Alain B. Labrique, Tom Jones

Abstract

Mobile and wireless technology for health (mHealth) has the potential to improve health outcomes by addressing critical health systems constraints that impede coverage, utilization, and effectiveness of health services. To date, few mHealth programs have been implemented at scale and there remains a paucity of evidence on their effectiveness and value for money. This paper aims to improve understanding among mHealth program managers and key stakeholders of how to select methods for economic evaluation (comparative analysis for determining value for money) and financial evaluation (determination of the cost of implementing an intervention, estimation of costs for sustaining or expanding an intervention, and assessment of its affordability). We outline a 6 stage-based process for selecting and integrating economic and financial evaluation methods into the monitoring and evaluation of mHealth solutions including (1) defining the program strategy and linkages with key outcomes, (2) assessment of effectiveness, (3) full economic evaluation or partial evaluation, (4) sub-group analyses, (5) estimating resource requirements for expansion, (6) affordability assessment and identification of models for financial sustainability. While application of these stages optimally occurs linearly, finite resources, limited technical expertise, and the timing of evaluation initiation may impede this. We recommend that analysts prioritize economic and financial evaluation methods based on programmatic linkages with health outcomes; alignment with an mHealth solution's broader stage of maturity and stage of evaluation; overarching monitoring and evaluation activities; stakeholder evidence needs; time point of initiation; and available resources for evaluations.

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 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 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 <1%
Unknown 111 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 20%
Researcher 17 15%
Student > Ph. D. Student 11 10%
Student > Bachelor 8 7%
Student > Doctoral Student 6 5%
Other 19 17%
Unknown 29 26%
Readers by discipline Count As %
Medicine and Dentistry 26 23%
Nursing and Health Professions 10 9%
Business, Management and Accounting 7 6%
Engineering 7 6%
Economics, Econometrics and Finance 6 5%
Other 17 15%
Unknown 39 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 08 October 2021.
All research outputs
#3,273,821
of 25,257,066 outputs
Outputs from Cost Effectiveness and Resource Allocation
#76
of 521 outputs
Outputs of similar age
#56,258
of 316,257 outputs
Outputs of similar age from Cost Effectiveness and Resource Allocation
#3
of 7 outputs
Altmetric has tracked 25,257,066 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 521 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.0. This one has done well, scoring higher than 85% of its peers.
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 316,257 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.