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Geriatric medicine
Research
Predictors of care home and hospital admissions and their costs for older people with Alzheimer's disease: findings from a large London case register
  1. Martin Knapp1,
  2. Kia-Chong Chua2,
  3. Matthew Broadbent3,
  4. Chin-Kuo Chang4,
  5. Jose-Luis Fernandez1,
  6. Dominique Milea5,
  7. Renee Romeo2,
  8. Simon Lovestone6,
  9. Michael Spencer7,
  10. Gwilym Thompson7,
  11. Robert Stewart4,
  12. Richard D Hayes4
  1. 1Personal Social Services Research Unit, London School of Economics and Political Science, London, UK
  2. 2Health Services and Population Research Department, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
  3. 3South London and Maudsley National Health Service Foundation Trust, London, UK
  4. 4Psychological Medicine Department, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
  5. 5Lundbeck Singapore PTE Ltd, Singapore, Singapore
  6. 6Department of Psychiatry, University of Oxford, Oxford, UK
  7. 7Janssen-Cilag Ltd, High Wycombe, UK
  1. Correspondence to: Martin Knapp; m.knapp{at}lse.ac.uk

Abstract

Objectives To examine links between clinical and other characteristics of people with Alzheimer's disease living in the community, likelihood of care home or hospital admission, and associated costs.

Design Observational data extracted from clinical records using natural language processing and Hospital Episode Statistics. Statistical analyses examined effects of cognition, physical health, mental health, sociodemographic factors and living circumstances on risk of admission to care home or hospital over 6 months and associated costs, adjusting for repeated observations.

Setting Catchment area for South London and Maudsley National Health Service Foundation Trust, provider for 1.2 million people in Southeast London.

Participants Every individual with diagnosis of Alzheimer's disease seen and treated by mental health services in the catchment area, with at least one rating of cognition, not resident in care home at time of assessment (n=3075).

Interventions Usual treatment.

Main outcome measures Risk of admission to, and days spent in three settings during 6-month period following routine clinical assessment: care home, mental health inpatient care and general hospital inpatient care.

Results Predictors of probability of care home or hospital admission and/or associated costs over 6 months include cognition, functional problems, agitation, depression, physical illness, previous hospitalisations, age, gender, ethnicity, living alone and having a partner. Patterns of association differed considerably by destination.

Conclusions Most people with dementia prefer to remain in their own homes, and funding bodies see this as cheaper than institutionalisation. Better treatment in the community that reduces health and social care needs of Alzheimer's patients would reduce admission rates. Living alone, poor living circumstances and functional problems all raise admission rates, and so major cuts in social care budgets increase the risk of high-cost admissions which older people do not want. Routinely collected data can be used to reveal local patterns of admission and costs.

  • alzheimer's disease
  • nursing home
  • hospital
  • costs

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

https://doi.org/10.1136/bmjopen-2016-013591

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    Footnotes

    • MP and K-CC joint first authors.

    • RS and RDH joint last authors.

    • Contributors All the authors listed have made substantial contributions to the preparation of this paper. RS, SL and MK, with input from DM, MS and GT, designed the study. MB designed and carried out the data extraction and processing. C-KC, RDH, MK, RR, K-CC and J-LF designed the data analysis strategy and K-CC conducted the statistical analyses. MK wrote the first draft of the manuscript and led subsequent redrafting; all authors commented on each draft of the manuscript. Each author has given final approval to the manuscript. The corresponding author had access to all data and had complete freedom to direct the analysis and reporting without influence, editorial direction or censorship from the sponsors. The authors thank the reviewers for their helpful comments on an earlier version of this paper.

    • Funding This study was supported by the Clinical Records Interactive Search (CRIS) system funded and developed by the National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London and a joint infrastructure grant from Guy's and St Thomas’ Charity and the Maudsley Charity. We appreciated the technical support from informatics personnel in the Biomedical Research Centre. The analyses were specifically funded by a pre-competitive consortium between King's College London, Pfizer, J&J and Lundbeck. RH is funded by a Medical Research Council (MRC) Population Health Scientist Fellowship. RS, C-KC and MB receive salary support from theNIHR Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. K-CC and RR receive salary support from King's College London. MK and J-LF receive salary support from the London School of Economics and Political Science. DM receives salary support from Lundbeck. MS receives salary support from Jannsen-Cilag Ltd. GT receives salary support from Janssen. The views expressed are those of the author, and not necessarily those of the NHS, the NIHR, the Department of Health or any of the organisations employing the authors.

    • Competing interests  RH, C-KC, MB and RS have received research funding from Roche, Pfizer, J&J and Lundbeck; MK has received research or consultancy funding from Roche, Pfizer, J&J, Lundbeck and Takeda; DM is a full-time employee of Lundbeck; GT is a full-time employee of J&J; MS is a full-time employee of Janssen-Cilag Ltd. Other authors have no conflicts to report. The work described in this paper originated from a grant, formed from a pre-competitive consortium between King's College London and three companies (Pfizer, Lundbeck, J&J). The products manufactured by the consortium partners were not analysed as covariates in the study.

    • Ethics approval The SLAM case register was approved as a data resource for secondary analysis by Oxford C Research Ethics Committee (Ref: 08/H0606/71+5) and all CRIS projects are reviewed and approved by a patient-led Oversight Committee reporting to the SLAM Caldicott Guardian.

    • Disclamer MK affirms that the manuscript is an honest, accurate and transparent account of the study being reported. No important aspects of the study have been omitted. Any discrepancies from the study as planned have been explained.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data sharing statement Data from the SLAM case register are required to remain within the SLAM NHS firewall and access is governed by its research ethics approval; however, within these constraints, data can be made available on request and application.