Comparative morbidities and the share of emergencies in hospital admissions in deprived areas: a method and evidence from English administrative data

What can hospital emergency admissions prior to cancer diagnosis tell us about socio-economic inequalities in cancer diagnosis? Evidence from population-based data in England

BACKGROUND

More deprived cancer patients are at higher risk of Emergency Presentation (EP) with most studies pointing to lower symptom awareness and increased comorbidities to explain those patterns. With the example of colon cancer, we examine patterns of hospital emergency admissions (HEAs) history in the most and least deprived patients as a potential precursor of EP.

METHODS

We analysed the rates of hospital admissions and their admission codes (retrieved from Hospital Episode Statistics) in the two years preceding cancer diagnosis by sex, deprivation and route to diagnosis (EP, non-EP). To select the conditions (grouped admission codes) that best predict emergency admission, we adapted the purposeful variable selection to mixed-effects logistic regression.

RESULTS

Colon cancer patients diagnosed through EP had the highest number of HEAs than all the other routes to diagnosis, especially in the last 7 months before diagnosis. Most deprived patients had an overall higher rate and higher probability of HEA but fewer conditions associated with it.

CONCLUSIONS

Our findings point to higher use of emergency services for non-specific symptoms and conditions in the most deprived patients, preceding colon cancer diagnosis. Health system barriers may be a shared factor of socio-economic inequalities in EP and HEAs.

Measuring Health Equity in Emergency Care Using Routinely Collected Data: A Systematic Review

Introduction: Achieving equity in health care remains a challenge for health care systems worldwide and marked inequities in access and quality of care persist. Identifying health care equity indicators is an important first step in integrating the concept of equity into assessments of health care system performance, particularly in emergency care.

Methods: We conducted a systematic review of administrative data-derived health care equity indicators and their association with socioeconomic determinants of health (SEDH) in emergency care settings. Following PRISMA-Equity reporting guidelines, Ovid MEDLINE, EMBASE, PubMed, and Web of Science were searched for relevant studies. The outcomes of interest were indicators of health care equity and the associated SEDH they examine.

Results: Among 29 studies identified, 14 equity indicators were identified and grouped into four categories that reflect the patient emergency care pathway. Total emergency department (ED) visits and ambulatory care-sensitive condition-related ED visits were the two most frequently used equity indicators. The studies analyzed equity based on seven SEDH: social deprivation, income, education level, social class, insurance coverage, health literacy, and financial and nonfinancial barriers. Despite some conflicting results, all identified SEDH are associated with inequalities in access to and use of emergency care.

Conclusion: The use of administrative data-derived indicators in combination with identified SEDH could improve the measurement of health care equity in emergency care settings across health care systems worldwide. Using a combination of indicators is likely to lead to a more comprehensive, well-rounded measurement of health care equity than using any one indicator in isolation. Although studies analyzed focused on emergency care settings, it seems possible to extrapolate these indicators to measure equity in other areas of the health care system. Further studies elucidating root causes of health inequities in and outside the health care system are needed.

Reducing inequality in avoidable emergency admissions: Case studies of local health care systems in England using a realist approach

OBJECTIVE

People in disadvantaged areas are more likely to have an avoidable emergency hospital admission. Socio-economic inequality in avoidable emergency hospital admissions is monitored in England. Our aim was to inform local health care purchasing and planning by identifying recent health care system changes (or other factors), as reported by local health system leaders, that might explain narrowing or widening trends.

METHODS

Case studies were undertaken in one pilot and at five geographically distinct local health care systems (Clinical Commissioning Groups, CCGs), identified as having consistently increasing or decreasing inequality. Local settings were explored through discussions with CCG officials and stakeholders to identify potential local determinants. Data were analysed using a realist evaluation approach to generate context-mechanism-outcome (CMO) configurations.

RESULTS

Of the five geographically distinct CCGs, two had narrowing inequality, two widening, and one narrowing inequality, which widened during the project. None of the CCGs had designed a large-scale package of service changes with the explicit aim of reducing socio-economic inequality in avoidable emergency admissions, and local decision makers were unfamiliar with their own trends. Potential primary and community care determinants included: workforce, case finding and exclusion, proactive care co-ordination for patients with complex needs, and access and quality. Potential commissioning determinants included: data use and incentives, and targeting of services. Other potential determinants included changes in care home services, national A&E targets, and wider issues - such as public services financial constraints, residential gentrification, and health care expectations.

CONCLUSIONS

We did not find any bespoke initiatives that explained the inequality trends. The trends were more likely due to an interplay of multiple health care and wider system factors. Local decision makers need greater awareness, understanding and support to interpret, use and act upon inequality indicators. They are unlikely to find simple, cheap interventions to reduce inequalities in avoidable emergency admissions. Rather, long-term multifaceted interventions are required that embed inequality considerations into mainstream decision making.

Are more GPs associated with a reduction in emergency hospital admissions? A quantitative study on GP referral in England

BACKGROUND

Recent studies have found an association between access to primary care and accident and emergency attendances, with better access associated with fewer attendances. Analyses of an association with emergency admissions, however, have produced conflicting findings.

AIM

This study investigated whether emergency admission rates in an area are associated with 1) the number of GPs, and 2) mean size of GP practice.

DESIGN AND SETTING

Analysis was conducted utilising Hospital Episode Statistics, the numbers of GPs and GP practices, Office for National Statistics population data, Quality and Outcomes Framework prevalence data, and Index of Multiple Deprivation data, from 2004/2005 to 2011/2012, for all practices in England.

METHOD

Regression analysis of panel data with fixed effects to address 1) a potential two-way relationship between the numbers of GPs and emergency admissions, and 2) unobservable characteristics of GP practices.

RESULTS

There is not a statistically significant relationship between the number of GPs in a primary care trust area and the number of emergency admissions, when analysing all areas. In deprived areas, however, a higher number of GPs is associated with lower emergency admissions. There is also a lower emergency admission rate in areas in which practices are on average larger, holding GP supply constant.

CONCLUSION

An increase in GPs was found to reduce emergency admissions in deprived areas, but not elsewhere. Areas in which GPs are concentrated into larger practices showed reduced levels of emergency admissions, all else being equal.

Measuring geographical disparities in England at the time of COVID-19: results using a composite indicator of population vulnerability

OBJECTIVES

The growth of COVID-19 infections in England raises questions about system vulnerability. Several factors that vary across geographies, such as age, existing disease prevalence, medical resource availability and deprivation, can trigger adverse effects on the National Health System during a pandemic. In this paper, we present data on these factors and combine them to create an index to show which areas are more exposed. This technique can help policy makers to moderate the impact of similar pandemics.

DESIGN

We combine several sources of data, which describe specific risk factors linked with the outbreak of a respiratory pathogen, that could leave local areas vulnerable to the harmful consequences of large-scale outbreaks of contagious diseases. We combine these measures to generate an index of community-level vulnerability.

SETTING

91 Clinical Commissioning Groups (CCGs) in England.

MAIN OUTCOME MEASURES

We merge 15 measures spatially to generate an index of community-level vulnerability. These measures cover prevalence rates of high-risk diseases; proxies for the at-risk population density; availability of staff and quality of healthcare facilities.

RESULTS

We find that 80% of CCGs that score in the highest quartile of vulnerability are located in the North of England (24 out of 30). Here, vulnerability stems from a faster rate of population ageing and from the widespread presence of underlying at-risk diseases. These same areas, especially the North-East Coast areas of Lancashire, also appear vulnerable to adverse shocks to healthcare supply due to tighter labour markets for healthcare personnel. Importantly, our index correlates with a measure of social deprivation, indicating that these communities suffer from long-standing lack of economic opportunities and are characterised by low public and private resource endowments.

CONCLUSIONS

Evidence-based policy is crucial to mitigate the health impact of pandemics such as COVID-19. While current attention focuses on curbing rates of contagion, we introduce a vulnerability index combining data that can help policy makers identify the most vulnerable communities. We find that this index is positively correlated with COVID-19 deaths and it can thus be used to guide targeted capacity building. These results suggest that a stronger focus on deprived and vulnerable communities is needed to tackle future threats from emerging and re-emerging infectious disease.