| Title |
Health Equity Assessment Toolkit (HEAT): software for exploring and comparing health inequalities in countries
|
|---|---|
| Published in |
BMC Medical Research Methodology, October 2016
|
| DOI | 10.1186/s12874-016-0229-9 |
| Pubmed ID | |
| Authors |
Ahmad Reza Hosseinpoor, Devaki Nambiar, Anne Schlotheuber, Daniel Reidpath, Zev Ross |
| Abstract |
It is widely recognised that the pursuit of sustainable development cannot be accomplished without addressing inequality, or observed differences between subgroups of a population. Monitoring health inequalities allows for the identification of health topics where major group differences exist, dimensions of inequality that must be prioritised to effect improvements in multiple health domains, and also population subgroups that are multiply disadvantaged. While availability of data to monitor health inequalities is gradually improving, there is a commensurate need to increase, within countries, the technical capacity for analysis of these data and interpretation of results for decision-making. Prior efforts to build capacity have yielded demand for a toolkit with the computational ability to display disaggregated data and summary measures of inequality in an interactive and customisable fashion that would facilitate interpretation and reporting of health inequality in a given country. To answer this demand, the Health Equity Assessment Toolkit (HEAT), was developed between 2014 and 2016. The software, which contains the World Health Organization's Health Equity Monitor database, allows the assessment of inequalities within a country using over 30 reproductive, maternal, newborn and child health indicators and five dimensions of inequality (economic status, education, place of residence, subnational region and child's sex, where applicable). HEAT was beta-tested in 2015 as part of ongoing capacity building workshops on health inequality monitoring. This is the first and only application of its kind; further developments are proposed to introduce an upload data feature, translate it into different languages and increase interactivity of the software. This article will present the main features and functionalities of HEAT and discuss its relevance and use for health inequality monitoring. |
X Demographics
The data shown below were collected from the profiles of 49 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 11 | 22% |
| Australia | 3 | 6% |
| Switzerland | 2 | 4% |
| South Africa | 2 | 4% |
| Finland | 2 | 4% |
| Sri Lanka | 1 | 2% |
| United Kingdom | 1 | 2% |
| Pakistan | 1 | 2% |
| Spain | 1 | 2% |
| Other | 7 | 14% |
| Unknown | 18 | 37% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 30 | 61% |
| Practitioners (doctors, other healthcare professionals) | 11 | 22% |
| Scientists | 8 | 16% |
Mendeley readers
The data shown below were compiled from readership statistics for 169 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | <1% |
| Unknown | 168 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 25 | 15% |
| Student > Master | 24 | 14% |
| Researcher | 20 | 12% |
| Other | 16 | 9% |
| Student > Bachelor | 15 | 9% |
| Other | 27 | 16% |
| Unknown | 42 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 42 | 25% |
| Nursing and Health Professions | 23 | 14% |
| Social Sciences | 16 | 9% |
| Economics, Econometrics and Finance | 6 | 4% |
| Biochemistry, Genetics and Molecular Biology | 4 | 2% |
| Other | 31 | 18% |
| Unknown | 47 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 41. 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 13 August 2021.
All research outputs
#1,003,240
of 25,292,646 outputs
Outputs from BMC Medical Research Methodology
#98
of 2,257 outputs
Outputs of similar age
#18,463
of 323,772 outputs
Outputs of similar age from BMC Medical Research Methodology
#5
of 42 outputs
Altmetric has tracked 25,292,646 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,257 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. This one has done particularly well, scoring higher than 95% of its peers.
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We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.