Dataset Information

The association between dementia severity and hospitalisation profile in a newly assessed clinical cohort: the South London and Maudsley case register.

ABSTRACT: OBJECTIVES:To evaluate the risk and common causes of hospitalisation in patients with newly diagnosed dementia and variation by severity of cognitive impairment. SETTING:We used data from a large London mental healthcare case register linked to a national hospitalisation database. PARTICIPANTS:Individuals aged ?65 years with newly diagnosed dementia with recorded cognitive function and the catchment population within the same geography. OUTCOME MEASURES:We evaluated the risk and duration of hospitalisation in the year following a dementia diagnosis. In addition we identified the most common causes of hospitalisation and calculated age-standardised and gender-standardised admission ratios by dementia severity (mild/moderate/severe) relative to the catchment population. RESULTS:Of the 5218 patients with dementia, 2596 (49.8%) were hospitalised in the year following diagnosis. The proportion of individuals with mild, moderate and severe dementia who had a hospital admission was 47.9%, 50.8% and 51.7%, respectively (p= 0.097). Duration of hospital stay increased with dementia severity (median 2 days in mild to 4 days in severe dementia, p 0.0001). After excluding readmissions for the same cause, the most common primary hospitalisation discharge diagnoses among patients with dementia were urinary system disorders, pneumonia and fracture of femur, accounting for 15%, 10% and 6% of admissions, respectively. Overall, patients with dementia were hospitalised 30% more than the catchment population, and this trend was observed for most of the discharge diagnoses evaluated. Standardised admission ratios for urinary and respiratory disorders were higher in those with more severe dementia at diagnosis. CONCLUSIONS:Individuals with a dementia diagnosis were more likely to be hospitalised than individuals in the catchment population. The length of hospital stay increased with dementia severity. Most of the common causes of hospitalisation were more common than expected relative to the catchment population, but standardised admission ratios only varied by dementia stage for certain groups of conditions.

SUBMITTER: Gungabissoon U

PROVIDER: S-EPMC7200045 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The association between dementia severity and hospitalisation profile in a newly assessed clinical cohort: the South London and Maudsley case register.

Gungabissoon Usha U Perera Gayan G Galwey Nicholas W NW Stewart Robert R

BMJ open 20200412 4

<h4>Objectives</h4>To evaluate the risk and common causes of hospitalisation in patients with newly diagnosed dementia and variation by severity of cognitive impairment.<h4>Setting</h4>We used data from a large London mental healthcare case register linked to a national hospitalisation database.<h4>Participants</h4>Individuals aged ≥65 years with newly diagnosed dementia with recorded cognitive function and the catchment population within the same geography.<h4>Outcome measures</h4>We evaluated ...[more]

PMID: 32284392

Similar Datasets

Project description:The South London and Maudsley National Health Service (NHS) Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register and its Clinical Record Interactive Search (CRIS) application were developed in 2008, generating a research repository of real-time, anonymised, structured and open-text data derived from the electronic health record system used by SLaM, a large mental healthcare provider in southeast London. In this paper, we update this register's descriptive data, and describe the substantial expansion and extension of the data resource since its original development.Descriptive data were generated from the SLaM BRC Case Register on 31 December 2014. Currently, there are over 250,000 patient records accessed through CRIS.Since 2008, the most significant developments in the SLaM BRC Case Register have been the introduction of natural language processing to extract structured data from open-text fields, linkages to external sources of data, and the addition of a parallel relational database (Structured Query Language) output. Natural language processing applications to date have brought in new and hitherto inaccessible data on cognitive function, education, social care receipt, smoking, diagnostic statements and pharmacotherapy. In addition, through external data linkages, large volumes of supplementary information have been accessed on mortality, hospital attendances and cancer registrations.Coupled with robust data security and governance structures, electronic health records provide potentially transformative information on mental disorders and outcomes in routine clinical care. The SLaM BRC Case Register continues to grow as a database, with approximately 20,000 new cases added each year, in addition to extension of follow-up for existing cases. Data linkages and natural language processing present important opportunities to enhance this type of research resource further, achieving both volume and depth of data. However, research projects still need to be carefully tailored, so that they take into account the nature and quality of the source information.

Project description:BackgroundAlthough stroke is acknowledged as a long-term condition, population estimates of outcomes longer term are lacking. Such estimates would be useful for planning health services and developing research that might ultimately improve outcomes. This burden of disease study provides population-based estimates of outcomes with a focus on disability, cognition, and psychological outcomes up to 10 y after initial stroke event in a multi-ethnic European population.Methods and findingsData were collected from the population-based South London Stroke Register, a prospective population-based register documenting all first in a lifetime strokes since 1 January 1995 in a multi-ethnic inner city population. The outcomes assessed are reported as estimates of need and included disability (Barthel Index <15), inactivity (Frenchay Activities Index <15), cognitive impairment (Abbreviated Mental Test < 8 or Mini-Mental State Exam <24), anxiety and depression (Hospital Anxiety and Depression Scale >10), and mental and physical domain scores of the Medical Outcomes Study 12-item short form (SF-12) health survey. Estimates were stratified by age, gender, and ethnicity, and age-adjusted using the standard European population. Plots of outcome estimates over time were constructed to examine temporal trends and sociodemographic differences. Between 1995 and 2006, 3,373 first-ever strokes were registered: 20%-30% of survivors had a poor outcome over 10 y of follow-up. The highest rate of disability was observed 7 d after stroke and remained at around 110 per 1,000 stroke survivors from 3 mo to 10 y. Rates of inactivity and cognitive impairment both declined up to 1 y (280/1,000 and 180/1,000 survivors, respectively); thereafter rates of inactivity remained stable till year eight, then increased, whereas rates of cognitive impairment fluctuated till year eight, then increased. Anxiety and depression showed some fluctuation over time, with a rate of 350 and 310 per 1,000 stroke survivors, respectively. SF-12 scores showed little variation from 3 mo to 10 y after stroke. Inactivity was higher in males at all time points, and in white compared to black stroke survivors, although black survivors reported better outcomes in the SF-12 physical domain. No other major differences were observed by gender or ethnicity. Increased age was associated with higher rates of disability, inactivity, and cognitive impairment.ConclusionsBetween 20% and 30% of stroke survivors have a poor range of outcomes up to 10 y after stroke. Such epidemiological data demonstrate the sociodemographic groups that are most affected longer term and should be used to develop longer term management strategies that reduce the significant poor outcomes of this group, for whom effective interventions are currently elusive. Please see later in the article for the Editors' Summary.

Project description:BackgroundAcute stroke impairments often result in poor long-term outcome for stroke survivors. The aim of this study was to estimate the trends over time in the prevalence of these acute stroke impairments.Methods and findingsAll first-ever stroke patients recorded in the South London Stroke Register (SLSR) between 2001 and 2018 were included in this cohort study. Multivariable Poisson regression models with robust error variance were used to estimate the adjusted prevalence of 8 acute impairments, across six 3-year time cohorts. Prevalence ratios comparing impairments over time were also calculated, stratified by age, sex, ethnicity, and aetiological classification (Trial of Org 10172 in Acute Stroke Treatment [TOAST]). A total of 4,683 patients had a stroke between 2001 and 2018. Mean age was 68.9 years, 48% were female, and 64% were White. After adjustment for demographic factors, pre-stroke risk factors, and stroke subtype, the prevalence of 3 out of the 8 acute impairments declined during the 18-year period, including limb motor deficit (from 77% [95% CI 74%-81%] to 62% [56%-68%], p < 0.001), dysphagia (37% [33%-41%] to 15% [12%-20%], p < 0.001), and urinary incontinence (43% [39%-47%) to 29% [24%-35%], p < 0.001). Declines in limb impairment over time were 2 times greater in men than women (prevalence ratio 0.73 [95% CI 0.64-0.84] and 0.87 [95% CI 0.77-0.98], respectively). Declines also tended to be greater in younger patients. Stratified by TOAST classification, the prevalence of all impairments was high for large artery atherosclerosis (LAA), cardioembolism (CE), and stroke of undetermined aetiology. Conversely, small vessel occlusions (SVOs) had low levels of all impairments except for limb motor impairment and dysarthria. While we have assessed 8 key acute stroke impairments, this study is limited by a focus on physical impairments, although cognitive impairments are equally important to understand. In addition, this is an inner-city cohort, which has unique characteristics compared to other populations.ConclusionsIn this study, we found that stroke patients in the SLSR had a complexity of acute impairments, of which limb motor deficit, dysphagia, and incontinence have declined between 2001 and 2018. These reductions have not been uniform across all patient groups, with women and the older population, in particular, seeing fewer reductions.

Dataset Information

The association between dementia severity and hospitalisation profile in a newly assessed clinical cohort: the South London and Maudsley case register.

Publications

The association between dementia severity and hospitalisation profile in a newly assessed clinical cohort: the South London and Maudsley case register.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets