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Healthcare Utilisation of 282,080 Individuals with Long COVID Over Two Years: A Multiple Matched Control Cohort Analysis

29 Pages Posted: 19 Oct 2023

See all articles by Yi Mu

Yi Mu

University College London

Ashkan Dashtban

University College London - Institute of Health Informatics

Mehrdad A. Mizani

University College London - Institute of Health Informatics

Christopher Tomlinson

University College London - Institute of Health Informatics

Mohamed Mohamed

University College London

Mark Ashworth

King’s College London - ESRC Centre for Society and Mental Health

Mamas Mamas

Keele University - Research Institute for Primary Care and Health Sciences

Rouven Priedon

Health Data Research UK

Steffen E. Petersen

Government of the United Kingdom - Barts Health NHS Trust

Evan Kontopantelis

The University of Manchester

Christina Pagel

University College London

Mevhibe Hocaoglu

University of London, Kings College London, African Leadership Centre, Students

Kamlesh Khunti

University of Leicester - Leicester Diabetes Centre

Johan Hilge Thygesen

University College London - Institute of Health Informatics

Paula Lorgelly

University of Auckland

Manuel Gomes

University College London

Melissa Heightman

University College London - University College London Hospitals NHS Foundation Trust

Amitava Banerjee

University College London - Institute of Health Informatics

Richard Williams

University College London

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Abstract

Background: In the UK alone, long Covid(LC) has affected over 2 million individuals, yet health system burden is poorly characterised. Understanding healthcare utilisation will inform clinical, service and policy planning for current and future LC care.

Methods: Using the British Heart Foundation/NHS England Secure Data Environment, we identified individuals ≥18 years of age, diagnosed with LC between January 2020 and January 2023, and age-, sex-, ethnicity-, deprivation-, region-, and comorbidity- matched control groups: (i)COVID only, no LC; (ii)pre-pandemic; (iii)contemporary non-COVID; and (iv)pre-LC(self-controlled, pre-COVID pandemic). Healthcare utilisation (number of consultations/visits per person: primary care (GP), secondary care (outpatient[OP], inpatient[IP] and emergency department[ED], investigations and procedures) and inflation-adjusted cost(£) were estimated for LC and control populations per month, calendar year and pandemic year for each category. 

Findings: 282,080 individuals(median[IQR] age 48.0[36.1, 58.9] years; female:62.4%) with LC were included between January 2020 and January 2023. The control groups were COVID only, no LC(n=1,112,370), pre-pandemic(n=1,031,285), contemporary non-COVID(n=1,118,360) and pre-LC(n=282,080). Healthcare utilisation per person (per month/year) was higher in LC than controls across GP and OP. For IP and ED, LC had higher healthcare utilisation than all controls but the COVID only, no LC group(all p<0.0001). Healthcare utilisation of the LC group increased progressively between 2020 and 2023, compared to controls. Cost per patient/year was also higher in individuals with LC(£3,350) than all control groups: pre-pandemic: £1,210(average excess cost: -£2,235 95% CI [-£2,284 -£2,187]), COVID only, no LC: £1,283(-£2,035 [-2,081 -£1,989]) and pre-LC: £870 (-£2,465 [-£2,554 -£2,376]), except for COVID and no LC: £5,961(£2,683 [£2,593 £2,774])(all p<0.0001).

Interpretation: LC has been associated with substantial, persistent healthcare utilisation and cost over the last 3 years. Future funding, resources and staff for LC prevention, treatment and research must be prioritised to reduce sustained primary and secondary healthcare utilisation and costs.

Funding: The British Heart Foundation Data Science Centre (grant No SP/19/3/34678, awarded to Health Data Research (HDR) UK) funded co-development (with NHS England) of the Secure Data Environment service for England, provision of linked datasets, data access, user software licences, computational usage, and data management and wrangling support, with additional contributions from the HDR UK Data and Connectivity component of the UK Government Chief Scientific Adviser’s National Core Studies programme to coordinate national COVID priority research. Consortium partner organisations funded the time of contributing data analysts, biostatisticians, epidemiologists, and clinicians. This work is part of a National Institute for Health Research (NIHR: COV-LT2-0043)-funded LC research programme (STIMULATE-ICP) with epidemiologic and mixed methods studies, including care inequalities and transferability to other LTCs and this complex intervention trial. It was also partially funded by NHS England (7130937).

Declaration of Interest: No competing interest relevant to this publication.

Ethical Approval: The North East - Newcastle and North Tyneside 2 research ethics committee provided ethical approval for the CVD-COVID-UK/COVID-IMPACT research programme (REC No 20/NE/0161) to access, within secure trusted research environments, unconsented, whole-population, de- identified data from electronic health records collected as part of patients’ routine healthcare.

Keywords: Long COVID, COVID, healthcare utilisation, cost, health policy

Suggested Citation

Mu, Yi and Dashtban, Ashkan and Mizani, Mehrdad A. and Tomlinson, Christopher and Mohamed, Mohamed and Ashworth, Mark and Mamas, Mamas and Priedon, Rouven and Petersen, Steffen E. and Kontopantelis, Evan and Pagel, Christina and Hocaoglu, Mevhibe and Khunti, Kamlesh and Thygesen, Johan Hilge and Lorgelly, Paula and Gomes, Manuel and Heightman, Melissa and Banerjee, Amitava and Williams, Richard, Healthcare Utilisation of 282,080 Individuals with Long COVID Over Two Years: A Multiple Matched Control Cohort Analysis. Available at SSRN: https://ssrn.com/abstract=4598962 or http://dx.doi.org/10.2139/ssrn.4598962

Yi Mu

University College London ( email )

Gower Street
London, WC1E 6BT
United Kingdom

Ashkan Dashtban

University College London - Institute of Health Informatics ( email )

United Kingdom

Mehrdad A. Mizani

University College London - Institute of Health Informatics ( email )

United Kingdom

Christopher Tomlinson

University College London - Institute of Health Informatics ( email )

United Kingdom

Mohamed Mohamed

University College London ( email )

Gower Street
London, WC1E 6BT
United Kingdom

Mark Ashworth

King’s College London - ESRC Centre for Society and Mental Health ( email )

Mamas Mamas

Keele University - Research Institute for Primary Care and Health Sciences ( email )

Rouven Priedon

Health Data Research UK ( email )

London
United Kingdom

Steffen E. Petersen

Government of the United Kingdom - Barts Health NHS Trust ( email )

Evan Kontopantelis

The University of Manchester ( email )

United Kingdom

Christina Pagel

University College London ( email )

Mevhibe Hocaoglu

University of London, Kings College London, African Leadership Centre, Students ( email )

London, England
United Kingdom

Kamlesh Khunti

University of Leicester - Leicester Diabetes Centre ( email )

Leicester
United Kingdom

Johan Hilge Thygesen

University College London - Institute of Health Informatics ( email )

United Kingdom

Paula Lorgelly

University of Auckland ( email )

Private Bag 92019
Auckland Mail Centre
Auckland, 1142
New Zealand

Manuel Gomes

University College London ( email )

Gower Street
London, WC1E 6BT
United Kingdom

Melissa Heightman

University College London - University College London Hospitals NHS Foundation Trust ( email )

United Kingdom

Amitava Banerjee (Contact Author)

University College London - Institute of Health Informatics

United Kingdom

Richard Williams

University College London

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