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Ethnicity and acute hospital admissions: Multi-center analysis of routine hospital data.

ABSTRACT: Background: The effects of ethnic and social inequalities on patient outcomes in acute healthcare remain poorly understood. Methods: Prospectively-defined analysis of registry data from four acute NHS hospitals in east London including all patients ≥ 18 years with a first emergency admission between 1st January 2013 and 31st December 2018. We calculated adjusted one-year mortality risk using logistic regression. Results are presented as n (%), median (IQR), and odds ratios (OR) with 95% confidence intervals. Findings: We included 203,182 patients. 43,101 (21%) patients described themselves as Asian, 21,388 (10.5%) Black, 2,982 (1.4%) Mixed, 13,946 (6.8%) Other ethnicity, and 100,065 (49%) White. We excluded 21,700 (10.7%) patients with undisclosed ethnicity. 16,054 (7.9%) patients died within one year. Non-white patients were younger (Asian: 43 [31-62] years; Black: 48 [33-63] years; Mixed 36 [26-52] years) than White patients (55 [35-75] years), with a higher incidence of comorbid disease. In each age-group, non-white patients were more likely to be admitted to hospital. This effect was greatest in the ≥ 80 years age-group (32% non-white admitted to hospital versus 23% non-white in community population). Deprivation was associated with increased mortality in all ethnic groups (OR 1.41 [1.33-1.50]; p < 0.001). However, when adjusted for age, Asian (0.69 [0.66-0.73], p < 0.0001) and Black patients (0.79 [0.74-0.85]; p < 0.0001) experienced a lower mortality risk than White patients. Interpretation: Ethnic and social disparities are associated with important differences in acute health outcomes. However, these differences are masked by statistical adjustment because patients from ethnic minorities present at a younger age. Funding: None.

SUBMITTER: Wan YI

PROVIDER: S-EPMC8478677 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionNeurological conditions are a major and increasing cause of hospitalisation among children and young people, but little is known about the impact of neurological conditions on hospital services in England, nor the factors that influence length of stay and bed days per year.ObjectivesTo quantify the hospital usage in children and young people related to neurological conditions, trends over time and variation by ethnicity and deprivation status.MethodsAn ICD10 coding framework identified a cohort of individuals aged 0-19 years with neurological conditions from linked routinely collected healthcare data from England (The Hospital Episode Statistics Admitted Patient Care dataset), from 1 April 2003 to 31 March 2015. Linked outpatient and accident and emergency data were used to supplement missing demographic data. Length of stay and bed days per year per person were calculated. These were separately modelled using random intercept multivariable negative binomial regressions with gender, age, ethnic group, diagnostic group, region of residence and deprivation category as predictors.Results524,442 individuals were identified over the study period, increasing from 49,928 in 2003/04 to 102,840 in 2014/15. Neurological conditions account for 8.8% of inpatient bed days in the 0-14 year old age group. Length of stay and bed days per year vary primarily by age group - e.g. Under 1 year olds had 1.85 times (95%CI 1.83-1.86%) longer stays and over double (2.36 times, 95%CI 2.34-2.37 times) the number of bed days per person per year compared to 5 to 9 year olds - and main diagnostic group, with smaller variations by ethnic group, deprivation and region.ConclusionsNeurological conditions in children and young people have a significant and increasing impact on the NHS in England. Falls in length of stay and bed days per person are more than offset by increasing numbers of children and young people with neurological diagnoses. Variations in length of stay and bed days per year by diagnostic group, ethnic group, age group, deprivation category and region should be taken into account in resource planning.

Project description:BackgroundThe Hospital Frailty Risk Score (HFRS) has been widely but inconsistently applied in published studies, particularly in how diagnostic information recorded in previous hospital admissions is used in its construction. We aimed to assess how many previous admissions should be considered when constructing the HFRS and the influence of frailty risk on long length of stay, in-hospital mortality, and 30-day readmission.MethodsThis is a retrospective observational cohort study of patients aged 75 years or older who had at least one emergency admission to any of 49 hospital sites in the Yorkshire and Humber region of England, UK. We constructed multiple versions of the HFRS for each patient, each form incorporating diagnostic data from progressively more previous admissions in its construction within a 1-year or 2-year window. We assessed the ability of each form of the HFRS to predict long length of stay (>10 days), in-hospital death, and 30-day readmission.FindingsBetween April 1, 2013, and March 31, 2017, 282 091 patients had 675 155 hospital admissions. Regression analyses assessing the different constructions of HFRS showed that the form constructed with diagnostic information recorded in the current and previous two admissions within the preceding 2 years performed best for predicting all three outcomes. Under this construction, 263 432 (39·0%) of 674 615 patient admissions were classified as having low frailty risk, for whom 33 333 (12·7%) had a long length of stay, 10 145 (3·9%) died in hospital, and 45 226 (17·2%) were readmitted within 30 days. By contrast with those patients with low frailty risk, for those with intermediate frailty risk, the probability was 2·5-times higher (95% CI 2·4 to 2·6) for long length of stay, 2·17-times higher (2·1 to 2·2) for in-hospital death, and 0·7% higher (0·5 to 1) for readmission. For patients with high frailty risk, the probability was 4·3-times higher (4·2 to 4·5) for long length of stay, 2·48-times higher (2·4 to 2·6) for in-hospital death, and -1% (-1·2 to -0·5) lower for readmission than those with low frailty risk. The intermediate and high frailty risk categories were more important predictors of long length of stay than any of the other rich set of control variables included in our analysis. These categories also proved to be important predictors of in-hospital mortality, with only the Charlson Comorbidity Index offering greater predictive power.InterpretationWe recommend constructing the HFRS with diagnostic information from the current admission and from the previous two admissions in the preceding 2 years. This HFRS form was a powerful predictor of long length of stay and in-hospital mortality, but less so of emergency readmissions.FundingNational Institute of Health Research.

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Ethnicity and acute hospital admissions: Multi-center analysis of routine hospital data.

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