Sentinel Amenable Mortality: A New Way to Assess the Quality of Healthcare by Examining Causes of Premature Death for Which Highly Efficacious Medical Interventions Are Available

Assessing performance of the Healthcare Access and Quality Index, overall and by select age groups, for 204 countries and territories, 1990-2019: a systematic analysis from the Global Burden of Disease Study 2019

BACKGROUND

Health-care needs change throughout the life course. It is thus crucial to assess whether health systems provide access to quality health care for all ages. Drawing from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019), we measured the Healthcare Access and Quality (HAQ) Index overall and for select age groups in 204 locations from 1990 to 2019.

METHODS

We distinguished the overall HAQ Index (ages 0-74 years) from scores for select age groups: the young (ages 0-14 years), working (ages 15-64 years), and post-working (ages 65-74 years) groups. For GBD 2019, HAQ Index construction methods were updated to use the arithmetic mean of scaled mortality-to-incidence ratios (MIRs) and risk-standardised death rates (RSDRs) for 32 causes of death that should not occur in the presence of timely, quality health care. Across locations and years, MIRs and RSDRs were scaled from 0 (worst) to 100 (best) separately, putting the HAQ Index on a different relative scale for each age group. We estimated absolute convergence for each group on the basis of whether the HAQ Index grew faster in absolute terms between 1990 and 2019 in countries with lower 1990 HAQ Index scores than countries with higher 1990 HAQ Index scores and by Socio-demographic Index (SDI) quintile. SDI is a summary metric of overall development.

FINDINGS

Between 1990 and 2019, the HAQ Index increased overall (by 19·6 points, 95% uncertainty interval 17·9-21·3), as well as among the young (22·5, 19·9-24·7), working (17·2, 15·2-19·1), and post-working (15·1, 13·2-17·0) age groups. Large differences in HAQ Index scores were present across SDI levels in 2019, with the overall index ranging from 30·7 (28·6-33·0) on average in low-SDI countries to 83·4 (82·4-84·3) on average in high-SDI countries. Similarly large ranges between low-SDI and high-SDI countries, respectively, were estimated in the HAQ Index for the young (40·4-89·0), working (33·8-82·8), and post-working (30·4-79·1) groups. Absolute convergence in HAQ Index was estimated in the young group only. In contrast, divergence was estimated among the working and post-working groups, driven by slow progress in low-SDI countries.

INTERPRETATION

Although major gaps remain across levels of social and economic development, convergence in the young group is an encouraging sign of reduced disparities in health-care access and quality. However, divergence in the working and post-working groups indicates that health-care access and quality is lagging at lower levels of social and economic development. To meet the needs of ageing populations, health systems need to improve health-care access and quality for working-age adults and older populations while continuing to realise gains among the young.

FUNDING

Bill & Melinda Gates Foundation.

Neighbourhood Social Determinants of Health and Geographical Inequalities in Premature Mortality in Taiwan: A Spatiotemporal Approach

Geographical inequalities in premature mortality and the role of neighbourhood social determinants of health (SDOH) have been less explored. This study aims to assess the geographical inequalities in premature mortality in Taiwan and how neighbourhood SDOH contribute to them and to examine the place-specific associations between neighbourhood SDOH and premature mortality. We used township-level nationwide data for the years 2015 to 2019, including age-standardized premature mortality rates and three upstream SDOH (ethnicity, education, and income). Space-time scan statistics were used to assess the geographical inequality in premature mortality. A geographical and temporal weighted regression was applied to assess spatial heterogeneity and how neighbourhood SDOH contribute to geographic variation in premature mortality. We found geographical inequality in premature mortality to be clearly clustered around mountainous rural and indigenous areas. The association between neighbourhood SDOH and premature mortality was shown to be area-specific. Ethnicity and education could explain nearly 84% variation in premature mortality. After adjusting for neighbourhood SDOH, only a handful of hotspots for premature mortality remained, mainly consisting of rural and indigenous areas in the central-south region of Taiwan. These findings provide empirical evidence for developing locally tailored public health programs for geographical priority areas.

[Avoidable childhood deaths: an analysis by department and municipality in Colombia (2000-2018)Mortalidade infantil por causas evitáveis: uma análise por departamento e município na Colômbia (2000-2018)]

OBJECTIVE

To determine the proportion of potentially avoidable deaths in children under five in Colombia, by department and municipality of residence, during the period from 2000 through 2018.

METHODS

A multi-group and longitudinal ecological study was conducted in 33 departments and 1 118 municipalities over a period of 19 years. The deaths were classified as probably unavoidable or avoidable; the latter were then identified as treatable, preventable, or mixed; and a proportion was calculated relative to the total. Finally, clusters were created by municipality and by department and depicted in coropleth maps.

RESULTS

Between 2000 and 2018, Colombia reported 228 942 deaths of children under five, of which 91.4% were avoidable (68.2% treatable, 6.8% preventable, and 16.5% mixed) with no difference by sex. At the national level, the proportion of avoidability declined from 93.5% to 88.5% during this period. César was the department with the largest proportion of avoidable deaths (94.1%), compared with Santander, which had the smallest (89.0%). At the municipal level, all the deaths were potentially avoidable in 99 municipalities, whereas Palmar (Santander) had the least (33.3%).

CONCLUSIONS

Nine out of 10 of the deaths that occurred in children under five in Colombia during 2000-2018 could have been avoided, mainly through early and better quality medical care. Sizable differences were observed between subnational territories.

Investigating the Geographic Disparities of Amenable Mortality and Related Ambulance Services in Hungary

The aim of this study was to investigate how amenable mortality and related ambulance services differ on a county level in Hungary. The differences in mortality rates and ambulance services could identify counties where stronger ambulance services are needed. The datasets for 2018 consisted of county level aggregated data of citizens between the ages 15–64. The study examined how both the mortality rates and the ambulance rescue deliveries differ from the national average. The analyses were narrowed down to disease groups, such as acute myocardial infarction, hemorrhagic and ischemic stroke. Inequalities were identified regarding the distribution of number of ambulance deliveries, several counties had rates more than double that of the national average. For both mortality and ambulance services some of the counties had significantly better results and others had significantly worse compared to the national average. In Borsod-Abaúj-Zemplén county’s case, hemorrhagic stroke mortality was significantly higher (1.73 [1.35–2.11]), while ambulance deliveries were significantly lower (0.58 [0.40–0.76]) compared to the national average. The research has shown that regarding the investigated mortality rates and ambulance services there are considerable differences between the counties in Hungary. In this regard policy makers should implement policies to tackle these discrepancies.

Investigating improvements in premature death in two rural, majority-minority counties in the south

This exploratory study investigates counties in the southeast United States with mortality outcomes that were better than might be expected given their sociodemographic profiles (i.e., positive deviance). This study seeks to understand the community characteristics with the potential to moderate the negative health outcomes typically associated with social, geographic, or economic disadvantages. This article describes the process used to identify positive deviants and reports on the findings from key informant interviews in positive deviant counties to identify community factors or practices that might contribute to positive deviance in the observed outcomes. County Health Rankings and Roadmaps 2015 data and mortality trends were examined to identify positive deviant counties. The inclusion criteria were median household incomes in the lowest tertile of their state, ≥ 33% African American, and premature mortality rankings (as measured by Years of Potential Life Lost-YPLL) in the top quartile within their state. After benchmarking county rates against national figures and retaining counties with significant improvement trends, two counties emerged as positive deviants, Dooly County, Georgia and Washington County, North Carolina. Key informant interviews (n = 11) were conducted with community stakeholders in the study counties to better understand the community characteristics that could lead to the observed outcomes. Interview data were analyzed using qualitative methods. Key informant interviews revealed three emergent themes: 1. accessibility and availability of healthcare, 2. the provision of a robust EMS system, and 3. coordination of county-funded services targeting vulnerable populations. The positive deviance framework provides a foundation for the identification of community factors or practices with the potential to create a 'culture of health' in communities at the greatest risk for adverse health outcomes. Our findings suggest that healthcare supported by the coordination of non-emergency transportation and health and social services across numerous stakeholders may have contributed to observed outcomes in the study counties.