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Population Health Management to identify and characterise ongoing health need for high-risk individuals shielded from COVID-19: a cross-sectional cohort study.

Authors :
Kenward C
Pratt A
Creavin S
Wood R
Cooper JA
Source :
BMJ open [BMJ Open] 2020 Sep 28; Vol. 10 (9), pp. e041370. Date of Electronic Publication: 2020 Sep 28.
Publication Year :
2020

Abstract

Objectives: To use Population Health Management (PHM) methods to identify and characterise individuals at high-risk of severe COVID-19 for which shielding is required, for the purposes of managing ongoing health needs and mitigating potential shielding-induced harm.<br />Design: Individuals at 'high risk' of COVID-19 were identified using the published national 'Shielded Patient List' criteria. Individual-level information, including current chronic conditions, historical healthcare utilisation and demographic and socioeconomic status, was used for descriptive analyses of this group using PHM methods. Segmentation used k-prototypes cluster analysis.<br />Setting: A major healthcare system in the South West of England, for which linked primary, secondary, community and mental health data are available in a system-wide dataset. The study was performed at a time considered to be relatively early in the COVID-19 pandemic in the UK.<br />Participants: 1 013 940 individuals from 78 contributing general practices.<br />Results: Compared with the groups considered at 'low' and 'moderate' risk (ie, eligible for the annual influenza vaccination), individuals at high risk were older (median age: 68 years (IQR: 55-77 years), cf 30 years (18-44 years) and 63 years (38-73 years), respectively), with more primary care/community contacts in the previous year (median contacts: 5 (2-10), cf 0 (0-2) and 2 (0-5)) and had a higher burden of comorbidity (median Charlson Score: 4 (3-6), cf 0 (0-0) and 2 (1-4)). Geospatial analyses revealed that 3.3% of rural and semi-rural residents were in the high-risk group compared with 2.91% of urban and inner-city residents (p<0.001). Segmentation uncovered six distinct clusters comprising the high-risk population, with key differentiation based on age and the presence of cancer, respiratory, and mental health conditions.<br />Conclusions: PHM methods are useful in characterising the needs of individuals requiring shielding. Segmentation of the high-risk population identified groups with distinct characteristics that may benefit from a more tailored response from health and care providers and policy-makers.<br />Competing Interests: Competing interests: None declared.<br /> (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)

Details

Language :
English
ISSN :
2044-6055
Volume :
10
Issue :
9
Database :
MEDLINE
Journal :
BMJ open
Publication Type :
Academic Journal
Accession number :
32988953
Full Text :
https://doi.org/10.1136/bmjopen-2020-041370