A multilevel analysis of mortality following acute myocardial infarction in Norway: do municipal health services make a difference?

Socioeconomic disparities in the management and outcomes of acute myocardial infarction

BACKGROUND

Patients from lower socioeconomic status areas have poorer outcomes following acute myocardial infarction (AMI); however, how ethnicity modifies such socioeconomic disparities is unclear.

METHODS

Using the UK Myocardial Ischaemia National Audit Project (MINAP) registry, we divided 370 064 patients with AMI into quintiles based on Index of Multiple Deprivation (IMD) score, comprising seven domains including income, health, employment and education. We compared white and 'ethnic-minority' patients, comprising Black, Asian and mixed ethnicity patients (as recorded in MINAP); further analyses compared the constituents of the ethnic-minority group. Logistic regression models examined the role of the IMD, ethnicity and their interaction on the odds of in-hospital mortality.

RESULTS

More patients from the most deprived quintile (Q5) were from ethnic-minority backgrounds (Q5; 15% vs Q1; 4%). In-hospital mortality (OR 1.10, 95% CI 1.01 to 1.19, p=0.025) and major adverse cardiovascular event (MACE) (OR 1.07, 95% CI 1.00 to 1.15, p=0.048) were more likely in Q5, and MACE was more likely in ethnic-minority patients (OR 1.40, 95% CI 1.00 to 1.95, p=0.048) versus white (OR 1.05, 95% CI 0.98 to 1.13, p=0.027) in Q5. In subgroup analyses, Black patients had the highest in-hospital mortality within the most affluent quintile (Q1) (Black: 0.079, 95% CI 0.046 to 0.112, p<0.001; White: 0.062, 95% CI 0.059 to 0.066, p<0.001), but not in Q5 (Black: 0.065, 95% CI 0.054 to 0.077, p<0.001; White: 0.065, 95% CI 0.061 to 0.069, p<0.001).

CONCLUSION

Patients with a higher deprivation score were more often from an ethnic-minority background, more likely to suffer in-hospital mortality or MACE when compared with the most affluent quintile, and this relationship was stronger in ethnic minorities compared with White patients.

Socioeconomic environment and survival in patients after ST-segment elevation myocardial infarction (STEMI): a longitudinal study for the City of Vienna

OBJECTIVES

This study investigates the relationship between socioeconomic environment (SEE) and survival after ST-segment elevation myocardial infarction (STEMI) separately for women and men in the City of Vienna, Austria.

DESIGN

Hospital-based observational data of STEMI patients are linked with district-level information on SEE and the mortality register, enabling survival analyses with a 19-year follow-up (2000-2018).

SETTING

The analysis is set at the main tertiary care hospital of the City of Vienna. On weekends, it is the only hospital in charge of treating STEMIs and thus provides representative data for the Viennese population.

PARTICIPANTS

The study comprises a total of 1481 patients with STEMI, including women and men aged 24-94 years.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary outcome measures are age at STEMI and age at death. We further distinguish between deaths from coronary artery disease (CAD), deaths from acute coronary syndrome (ACS), and other causes of death. SEE is proxied via mean individual gross income from employment in each municipal district.

RESULTS

Results are based on Kaplan-Meier survival probability estimates, Cox proportional hazard regressions and competing risk models, always using age as the time scale. Descriptive findings suggest a socioeconomic gradient in the age at death after STEMI. This finding is, however, not supported by the regression results. Female patients with STEMI have better survival outcomes, but only for deaths related to CAD (HR: 0.668, 95% CIs 0.452 to 0.985) and other causes of deaths (HR: 0.627, 95% CIs 0.444 to 0.884), and not for deaths from the more acute ACS.

CONCLUSIONS

Additional research is necessary to further disentangle the interaction between SEE and age at STEMI, as our findings suggest that individuals from poorer districts have STEMI at younger ages, which indicates vulnerability in regard to health conditions in these neighbourhoods.

Hospital Variation in 30-Day Mortality for Patients With Stroke; The Impact of Individual and Municipal Socio-Demographic Status

Background

Thirty‐day mortality after hospitalization for stroke is commonly reported as a quality indicator. However, the impact of adjustment for individual and/or neighborhood sociodemographic status (SDS) has not been well documented. This study aims to evaluate the role of individual and contextual sociodemographic determinants in explaining the variation across hospitals in Norway and determine the impact when testing for hospitals with low or high mortality.

Methods and Results

Patient Administrative System data on all 45 448 patients admitted to hospitals in Norway with an incident stroke diagnosis from 2005 to 2009 were included. The data were merged with data from several databases to obtain information on vital status (dead/alive) and individual SDS variables. Logistic regression models were compared to estimate the predictive effect of individual and neighborhood SDS on 30‐day mortality and to determine outlier hospitals. All individual SDS factors, except travel time, were statistically significant predictors of 30‐day mortality. Of the municipal variables, only the municipal variable proportion of low income was statistically significant as a predictor of 30‐day mortality. Including sociodemographic characteristics of the individual and other characteristics of the municipality improved the model fit. However, performance classification was only changed for 1 (out of 56) hospital, from “significantly high mortality” to “nonoutlier.”

Conclusions

Our study showed that those stroke patients with a lower SDS have higher odds of dying after 30 days compared with those with a higher SDS, although this did not have a substantial impact when classifying providers as performing as expected, better than expected, or worse than expected.

Acute myocardial infarction: Does survival depend on geographical location and social background?

AIMS

This study described the interplay between geographical and social inequalities in survival after incident acute myocardial infarction (AMI) and examined whether geographical variation in survival exists when accounting for sociodemographic characteristics of the patients and their neighbourhood.

METHODS

Ringmap visualization and generalized linear models were performed to study post-AMI mortality. Three individual-level analyses were conducted: immediate case fatality, mortality between days 1 and 28 after admission and 365-day survival among patients who survived 28 days after admission.

RESULTS

In total, 99,013 incident AMI cases were registered between 2005 and 2014 in Denmark. Survival after AMI tended to correlate with sociodemographic indicators at the municipality level. In individual-level models, geographical inequality in immediate case fatality was observed with high mortality in northern parts of Jutland after accounting for sociodemographic characteristics. In contrast, no geographical variation in survival was observed among patients who survived 28 days. In all three analyses, odds and rates of mortality were higher among patients with low educational level (odds ratio (OR) (95% credible intervals) of 1.20 (1.12-1.29), OR of 1.12 (1.01-1.24) and mortality rate ratio of 1.45 (1.30-1.61)) and low income (OR of 1.24 (1.15-1.33), OR of 1.33 (1.20-1.48) and mortality rate ratio of 1.25 (1.13-1.38)).

CONCLUSION

Marked geographical inequality was observed in immediate case fatality. However, no geographically unequal distribution of survival was found among patients who survived 28 days after AMI. Results additionally showed social inequality in survival following AMI.

Effects of introducing a fee for inpatient overstays on the rate of death and readmissions across municipalities in Norway

The Norwegian healthcare coordination reform (Samhandlingsreformen) was implemented from January 1, 2012. In addition to providing municipalities with funding to strengthen their health infrastructure, it required municipalities to pay hospitals a daily fee for patients who, having been declared ready for discharge and in need of municipal health services, were not received by the municipalities on time. This study examines the effects of the reform on the rate of death and readmissions occurring within 60 days of hospitalization. We use aggregated municipal data for years 2009, 2010, 2012-2014 (N = 1646) for Norwegian patients (age 18+) hospitalized in the same years for COPD/asthma, heart failure, hip fracture, and stroke. We stratify our analyses of the municipal data by these patient groups. Our linear regression models test for moderated (interaction) effects whereby associations between the reform and the rate of death and readmissions vary by whether or not patients were classified as ready for discharge and in need of follow-up care in the municipality. The models adjust for municipal sociodemographic and health characteristics. We found no statistically significant moderated effects of the reform across the patient groups, except for patients with stroke (b = .027, SE = 0.109, p < .05). Specifically, compared to the pre-reform period (2009-2010), the post-reform period (2012-2014) was associated with a higher rate of readmissions at high predicted values of needing follow-up care. Even though our analyses of municipal data suggest that patients with stroke are vulnerable to the reform and its incentive scheme, there is no strong evidence overall to suggest that the Norwegian healthcare coordination reform is functioning in a manner that exacerbates the risk of death and readmissions.