Chapter 1. Country and territory dashboards
The aim of this chapter is to show a set of key indicators to compare performance across countries and territories in each of the following dimensions:
For each dimension, a set of five indicators is presented in the form of country and territories dashboards. The indicators are selected based on their policy relevance, but also on data availability and interpretability. Indicators where coverage is highest are therefore prioritised.
In order to assess comparative performance across countries and territory, each country/territory is classified for every indicator based on how they compare against the income group-specific median. Therefore, countries and territories significantly above/below their respective group median will be classified as better/worse than median (▲/▼), with the remaining countries and territories classified as close to the median (⦿).
In order to allow for cross-country comparisons of performance, countries and territories are split according to their income group (high income, upper-middle income, lower-middle and low income). The central tendency measures presented, for all indicators and income groups, are medians.
In order to classify countries and territories as “better than”, “close to”, or “worse than” the central tendency of any indicator, a measure of statistical dispersion is needed to compute the reasonable range for values close to the central tendency value, with anything above or below classified accordingly. The preferred measure is the Median Absolute Deviation (MAD), since it is a robust measure that is both more efficient and less biased than a simple standard deviation when outliers are present.
Countries and territories are classified as “better than median” if they lie above the median + 1 MAD, “worse than median” if they lie below the median – 1 MAD, and “close to the median” if they lie within ± 1 MAD from the median. Given the nature of the indicators presented, for “under age 5 mortality rate” and “smoking”, “alcohol consumption” and “children and adolescent overweight”, countries and territories are classified as “better than median” if they lie below the median - 1 MAD, “worse than median” if they lie above the median + 1 MAD, and “close to the median” if they lie within ± 1 MAD from the median.
The five indicators used to compare health status are life expectancy at birth for females (2018), life expectancy at birth for males (2018), survival to age 65 for females (2018), survival to age 65 for males (2018), and under age 5 mortality rate per 1 000 live births (2018).
The five indicators used to compare risk factors are the age-standardised prevalence estimates for daily tobacco smoking among persons aged 15 and above (2018), recorded alcohol consumption in litres per capita among persons aged 15 and above (2016), the share of population with access to basic sanitation (latest year available), the share of population with access to basic drinking water (latest year available) and the prevalence of overweight among children and adolescent (2016).
The five indicators used to compare quality of care are the five-year net survival rate for breast cancer, lung cancer and stomach cancer among persons aged 15 and above (2010-14), and vaccination rates for diphtheria tetanus toxoid and pertussis (DTP3) and measles (MCV) among children aged around 1 (2019). This dashboard does not split countries and territories across income groups due to data coverage limitations for the five-year net survival rates.
The five indicators used to compare health care resources are health expenditure per capita in USD international (2017), the share of out-of-pocket (OOP) spending in total current health spending (2017), the number of doctors per 1 000 population (latest year available), the number of nurses per 1 000 population (latest year available), and the number of hospital beds per 1 000 population (latest year available). Given the nature of the indicators presented, whereas they cannot be classified as better or worse performance, the arrows simply imply that the values are significantly higher or lower than the median.