How can the spatial equity of health services be defined and measured? A systematic review of spatial equity definitions and methods

Whitehead, Jesse; Pearson, Amber L.; Lawrenson, Ross; Atatoa‐Carr, Polly

doi:10.1177/1355819619837292

Cited by 39 publications

(23 citation statements)

References 51 publications

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“…Some authors argued that there is no single direct and objective way to define or measure spatial equity (Whitehead et al., 2019), so two spatial analysis followed with two statistical methods are used to assess whether and to what extent horizontal and vertical equity is upheld for accessibility among people reside in the study area, categorized in three social classes. The Gini Index, Pearson correlation coefficient, and spatial autocorrelation analysis, such as hot spot analysis, are employed to have a closer look at the pattern of accessibility values distribution regarding horizontal and vertical equity assessment.…”

Section: Methodsmentioning

confidence: 99%

Proposing an integrated accessibility-based measure to evaluate spatial equity among different social classes

Azmoodeh

Haghighi

Motieyan

2021

Environment and Planning B: Urban Analytics and City Science

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Fair spatial distribution of services has always been a challenge for urban planners to supply sufficient accessibility for individuals and to consider the needs of vulnerable social groups. Nevertheless, equity assessment literature has mostly focused on measuring the accessibility through distance-based variables, and social stratification based on just income, as well. Accordingly, this study intends to employ an accessibility measure that considers non-distance-based variables along with distance-based ones. It uses multi-criteria decision-making to propose an accessibility index to assess vertical and horizontal equity of residents’ accessibility to a range of public facilities, in the district 6 of Tehran, Iran. Therefore, using the integration of geographical information system-based spatial analysis, wider people specification, and the Gini coefficient, this measure proposes a novel framework to examine the equity level of individuals belonging to the lower, middle, and upper social classes. Results imply a 0.228 Gini index for horizontal equity, which indicates a low level of inequity among residents. Besides, for vertical equity evaluation, Gini index of 0.097, 0.249, and 0.167, respectively, for lower, middle, and upper groups show people in the lower class experience very low levels of inequity, therefore higher accessibility is well distributed among groups with higher social needs. This approach can help planners to choose the right analysis method and prioritize urban decisions toward the equitable distribution of facilities.

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Section: Methodsmentioning

confidence: 99%

Proposing an integrated accessibility-based measure to evaluate spatial equity among different social classes

Azmoodeh

Haghighi

Motieyan

2021

Environment and Planning B: Urban Analytics and City Science

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“…The three steps to spatial equity analysis involve defining, estimating and quantifying spatial equity. 41 Although spatial equity has a range of definitions that vary with context, 42 it has been referred to as a fair distribution of resources relative to need. 43 This recognises that in order to achieve equitable health outcomes, some populations with higher needs or underlying vulnerabilities should be prioritised and have better access to services.…”

Section: Methodsmentioning

confidence: 99%

Spatial inequity in distribution of COVID-19 vaccination services in Aotearoa

Whitehead

Carr

Scott

et al. 2021

Preprint

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Aim: This research examines the spatial equity, and associated health equity implications, of the geographic distribution of Covid-19 vaccination services in Aotearoa New Zealand. Method: We mapped the distribution of Aotearoa's population and used the enhanced-two-step-floating-catchment-method (E2SFCA) to estimate spatial access to vaccination services, taking into account service supply, population demand, and distance between populations and services. We used the Gini coefficient and both global and local measures of spatial autocorrelation to assess the spatial equity of vaccination services across Aotearoa. Additional statistics included an analysis of spatial accessibility for priority populations, including Māori (Indigenous people of Aotearoa), Pacific, over 65-year-olds, and people living in areas of high socioeconomic deprivation. We also examined vaccination service access according to rurality, and by District Health Board region. Results: Spatially accessibility to vaccination services varies across Aotearoa, and appears to be better in major cities than rural regions. A Gini coefficient of 0.426 confirms that spatial accessibility scores are not shared equally across the vaccine-eligible population. Furthermore, priority populations including Māori, older people, and residents of areas with socioeconomic constraint have, on average, statistically significantly lower spatial access to vaccination services. This is also true for people living in rural areas. Spatial access to vaccination services, also varies significantly by District Health Board (DHB) region as does equality of access, and the proportion of DHB priority population groups living in areas with poor access to vaccination services. A strong and significant positive correlation was identified between average spatial accessibility and the Māori vaccination rate ratio of DHBs. Conclusion: Covid-19 vaccination services in Aotearoa are not equitably distributed. Priority populations, with the most pressing need to receive Covid-19 vaccinations, have the worst access to vaccination services.

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“…Access to health care can be inequitable and, according to Hart's Inverse Care Law, inversely proportionate to population need 2 . Spatial equity is recognized as a fair distribution of services proportionate to need 3 . To achieve health equity, places and populations with higher needs should receive appropriately higher access to resources 4 .…”

mentioning

confidence: 99%

“…To achieve health equity, places and populations with higher needs should receive appropriately higher access to resources 4 . Spatial equity research compares levels of health care access with estimates of health need using a variety of spatial techniques and indicators of health need 3 . In New Zealand, primary care is funded to promote health equity, and the Primary Health Care Strategy aims to reduce health inequalities between groups 5 .…”

mentioning

confidence: 99%

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Selecting Health Need Indicators for Spatial Equity Analysis in the New Zealand Primary Care Context

Whitehead

Pearson

Lawrenson

et al. 2020

The Journal of Rural Health

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Purpose To examine potential indicators of health need for primary care in spatial equity research, and evidence of the Inverse Care Law in the Waikato region of New Zealand. Methods A cross‐sectional analysis of 7 health need indicators (ambulatory sensitive hospitalizations; cancer rate; mortality rate; New Zealand index of multiple deprivation‐health domain; age; New Zealand index of deprivation; smoking rate) that were identified through a systematic review was carried out. Values of indicators were mapped and analyzed using geographic information systems (GIS). Spearman's correlations were calculated between indicators, and clusters of high need were identified through spatial autocorrelation. The impact of incorporating indicator‐based weightings into an accessibility model was tested using analysis of variance and Spearman's correlations. General practice service spatial equity was assessed by comparing clusters of high access versus need, and quantified through the Gini coefficient. Findings Ambulatory sensitive hospitalization (ASH) rates were significantly correlated with all indicators. Health needs were significantly clustered, but incorporating indicator weightings into the spatial accessibility analysis did not impact accessibility scores. A misalignment of access and need, and a Gini coefficient of 0.281 suggest that services are not equitably distributed. Conclusion ASH rates seem a robust indicator of health need. However, data access issues may restrict their use. Area‐level socioeconomic deprivation measures incorporate some social determinants of health, and they have potential for wider use. High need clusters vary spatially according to the indicator used. GIS techniques can identify “hot‐spots” of need, but these can be masked in accessibility models.

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How can the spatial equity of health services be defined and measured? A systematic review of spatial equity definitions and methods

Cited by 39 publications

References 51 publications

Proposing an integrated accessibility-based measure to evaluate spatial equity among different social classes

Proposing an integrated accessibility-based measure to evaluate spatial equity among different social classes

Spatial inequity in distribution of COVID-19 vaccination services in Aotearoa

Selecting Health Need Indicators for Spatial Equity Analysis in the New Zealand Primary Care Context

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