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World Health Systems Facts

Healthcare Access and Quality Index: Methodology

HAQ Index Overview
HAQ Index Results

HAQ Index Methodology
HAQ Index Limitations


“Drawing from methods established in GBD 2015,20 our analysis involved four steps: mapping the Nolte and McKee cause list to GBD causes; constructing MIRs for cancers and risk-standardising non-cancer deaths to remove variations in mortality not directly amenable to health care; calculating the HAQ Index on the basis of principal components analysis (PCA), providing an overall score of personal health-care access and quality on a scale of 0–100; and examining associations between national HAQ Index scores and potential correlates of performance.

“Our study draws from GBD 2016 results,31–33 which entail several improvements since GBD 2015, including 169 new country-years of vital registration data, 528 new cancer-registry years with a total of 92 countries’ cancer registries,31 five new risk factors,32 and cause-specific mortality modelling updates (eg, cancers, tuberculosis).31 Further information can be found in the appendix (pp 12–89) and the GBD 2016 capstone series.31–33

“In addition to national and aggregated HAQ Index results, we report estimates at the subnational level for Brazil (26 states and the Federal District), China (33 provinces and special administrative regions), England (nine regions and 150 local government areas), India (31 states and union territories), Japan (47 prefectures), Mexico (32 states), and the USA (50 states and the District of Columbia).

“As with all GBD revisions, GBD 2016 HAQ Index estimates for the full time series published here supersede previous iterations. This analysis complies with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER);34 additional information is found in the appendix (pp 5–7).

“Mapping the Nolte and McKee amenable cause list to GBD causes
“We mapped 32 of 33 causes from the Nolte and McKee cause list6–9 to GBD causes in accordance with International Classification of Diseases codes (table 1; appendix p 156). GBD includes thyroid diseases within a larger residual category, and only non-fatal outcomes are estimated for benign prostatic hyperplasia; consequently, these causes were not included in our analyses. GBD provides separate estimates for diphtheria and tetanus, so we disaggregated these causes from the original Nolte and McKee list.

“Mortality-to-incidence ratios for cancers
“GBD cancer mortality estimates are informed by MIRs, which are derived from incidence and mortality data recorded in cancer registries; more detail on MIR estimation is in the appendix (pp 41–49).31 MIRs provide a good approximation of cancer survival and have been used to identify countries with higher or lower cancer mortality relative to incidence.22,35 Because of the improved quantity and quality of cancer registry data from GBD 2016, we used cancer-specific MIRs instead of risk-standardised death rates. As detailed in the appendix (pp 10–11), cancer-specific MIRs were more strongly correlated with the Socio-demographic Index (SDI), a measure of overall development, than were risk-standardised death rates. These results, and the distribution of MIRs by SDI quintile (appendix pp 96–111), showed that cancer MIRs provide a more robust signal of cancer care access and quality than do risk-standardised death rates.

“Risk-standardisation of death rates for non-cancer causes
“To better isolate differences in mortality associated with health-care access and quality from differences associated with underlying risk exposure, we risk-standardised cause-specific deaths to global levels of risk exposure.32 We did not risk-standardise differences in exposure to three metabolic risk factors (high systolic blood pressure, high total cholesterol, and high fasting plasma glucose) given their amenability to health care (eg, diagnosis and treatment of hypertension in primary care). For the 24 non-cancer causes, we risk-standardised deaths by removing the joint effects of location-specific behavioural and environmental risk exposure, and replaced these estimates with the global level of joint risk exposure (appendix pp 9–10).

“Joint population attributable fraction (PAF) estimation accounts for effects of multiple risks combined, including the mediation of different risk factors through each other. More detail on the PAF calculations and risk-standardisation is provided in the appendix (pp 9–10). Since GBD 2015,36 five risk factors were added, most notably low birthweight and short gestation,32 which enabled the risk-standardisation of neonatal disorder deaths. Risk-standardised deaths equalled observed deaths for causes in which no risk–outcome pairs have met evidence thresholds for inclusion in GBD (eg, diphtheria, appendicitis).”

Source: GBD 2016 Healthcare Access and Quality Collaborators. “Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016.” Lancet (London, England) vol. 391,10136 (2018): 2236-2271. doi:10.1016/S0140-6736(18)30994-2


Health Systems Facts is a project of the Real Reporting Foundation. We provide reliable statistics and other data from authoritative sources regarding health systems in the US and sixteen other nations.


Page last updated August 7, 2022 by Doug McVay, Editor.

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