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Changes in daily mental health service use and mortality at the commencement and lifting of COVID-19 ‘lockdown’ policy in 10 UK sites: a regression discontinuity in time design

Ioannis Bakolis, Robert Stewart Orcid Logo, David Baldwin, Jane Beenstock, Paul Bibby, Matthew Broadbent, Rudolf Cardinal Orcid Logo, Shanquan Chen, Karthik Chinnasamy, Andrea Cipriani Orcid Logo, Simon Douglas, Philip Horner, Caroline A Jackson Orcid Logo, Ann John Orcid Logo, Dan W Joyce, Sze Chim Lee, Jonathan Lewis, Andrew McIntosh Orcid Logo, Neil Nixon, David Osborn, Peter Phiri, Shanaya Rathod, Tanya Smith, Rachel Sokal, Rob Waller, Sabine Landau

BMJ Open, Volume: 11, Issue: 5, Start page: e049721

Swansea University Authors: Ann John Orcid Logo, Sze Chim Lee

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DOI (Published version): 10.1136/bmjopen-2021-049721

Abstract

Objectives To investigate changes in daily mental health (MH) service use and mortality in response to the introduction and the lifting of the COVID-19 ‘lockdown’ policy in Spring 2020.Design A regression discontinuity in time (RDiT) analysis of daily service-level activity.Setting and participants...

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Published in: BMJ Open
ISSN: 2044-6055 2044-6055
Published: BMJ 2021
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URI: https://cronfa.swan.ac.uk/Record/cronfa60382
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Abstract: Objectives To investigate changes in daily mental health (MH) service use and mortality in response to the introduction and the lifting of the COVID-19 ‘lockdown’ policy in Spring 2020.Design A regression discontinuity in time (RDiT) analysis of daily service-level activity.Setting and participants Mental healthcare data were extracted from 10 UK providers.Outcome measures Daily (weekly for one site) deaths from all causes, referrals and discharges, inpatient care (admissions, discharges, caseloads) and community services (face-to-face (f2f)/non-f2f contacts, caseloads): Adult, older adult and child/adolescent mental health; early intervention in psychosis; home treatment teams and liaison/Accident and Emergency (A&E). Data were extracted from 1 Jan 2019 to 31 May 2020 for all sites, supplemented to 31 July 2020 for four sites. Changes around the commencement and lifting of COVID-19 ‘lockdown’ policy (23 March and 10 May, respectively) were estimated using a RDiT design with a difference-in-difference approach generating incidence rate ratios (IRRs), meta-analysed across sites.Results Pooled estimates for the lockdown transition showed increased daily deaths (IRR 2.31, 95% CI 1.86 to 2.87), reduced referrals (IRR 0.62, 95% CI 0.55 to 0.70) and reduced inpatient admissions (IRR 0.75, 95% CI 0.67 to 0.83) and caseloads (IRR 0.85, 95% CI 0.79 to 0.91) compared with the pre lockdown period. All community services saw shifts from f2f to non-f2f contacts, but varied in caseload changes. Lift of lockdown was associated with reduced deaths (IRR 0.42, 95% CI 0.27 to 0.66), increased referrals (IRR 1.36, 95% CI 1.15 to 1.60) and increased inpatient admissions (IRR 1.21, 95% CI 1.04 to 1.42) and caseloads (IRR 1.06, 95% CI 1.00 to 1.12) compared with the lockdown period. Site-wide activity, inpatient care and community services did not return to pre lockdown levels after lift of lockdown, while number of deaths did. Between-site heterogeneity most often indicated variation in size rather than direction of effect.Conclusions MH service delivery underwent sizeable changes during the first national lockdown, with as-yet unknown and unevaluated consequences.
College: Faculty of Medicine, Health and Life Sciences
Funders: Regarding relevant background infrastructure funding, RSt was part funded by: (1) the National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) at the South London and Maudsley NHS Foundation Trust and King’s College London; (2) a Medical Research Council (MRC) Mental Health Data Pathfinder Award to King’s College London; (3) an NIHR Senior Investigator Award and (4) the NIHR Applied Research Collaboration South London (NIHR ARC South London) at King’s College Hospital NHS Foundation Trust. IB and SL were supported by the NIHR BRC at South London and Maudsley NHS Foundation Trust and King’s College London and by the NIHR Applied Research Collaboration South London (NIHR ARC South London) at King’s College Hospital NHS Foundation Trust. RC’s research was funded by the MRC (grant MC_PC_17213) and the NIHR Cambridge BRC. AC was supported by the NIHR Oxford Cognitive Health Clinical Research Facility, by an NIHR Research Professorship (grant RP-2017-08-ST2-006), by the NIHR Oxford and Thames Valley Applied Research Collaboration and by the NIHR Oxford Health BRC (grant BRC-1215-20005). AJ was part funded by MQ ADP and an MRC Mental Health Data Pathfinder Award to Swansea University. AJ and SCL were part funded by Health and Care Research Wales National Centre for Mental Health. DO was supported by the NIHR BRC at University College London Hospitals and by the National Institute for Health Research ARC North Thames. Additional infrastructure funding was provided by the MRC Mental Health Data Pathfinder Award to University of Edinburgh (MC_PC_17209). The collaboration providing Wales data was led by the Swansea University Health Data Research UK team under the direction of the Welsh Government Technical Advisory Cell and includes the following groups and organisations: the Secure Anonymised Information Linkage Databank, Administrative Data Research Wales, NHS Wales Informatics Service, Public Health Wales, NHS Shared Services and the Welsh Ambulance Service Trust and MRC grant MR/V028367. This study was additionally supported by the NIHR Mental Health Translational Research Collaboration. The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR or the UK Department of Health.
Issue: 5
Start Page: e049721

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