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Impact of frailty in older people on health care demand: simulation modelling of population dynamics to inform service planning

Impact of frailty in older people on health care demand: simulation modelling of population dynamics to inform service planning
Impact of frailty in older people on health care demand: simulation modelling of population dynamics to inform service planning

Background: as populations age, frailty and the associated demand for health care increase. Evidence needed to inform planning and commissioning of services for older people living with frailty is scarce. Accurate information on incidence and prevalence of different levels of frailty and the consequences for health outcomes, service use and costs at population level is needed. 

Objectives: to explore the incidence, prevalence, progression and impact of frailty within an ageing general practice population and model the dynamics of frailty-related healthcare demand, outcomes and costs, to inform the development of guidelines and tools to facilitate commissioning and service development. 

Study design and methods: a retrospective observational study with statistical modelling to inform simulation (system dynamics) modelling using routine data from primary and secondary health care in England and Wales. Modelling was informed by stakeholder engagement events conducted in Hampshire, England. Data sources included the Royal College of General Practitioners Research and Surveillance Centre databank, and the Secure Anonymised Information Linkage Databank. Population prevalence, incidence and progression of frailty within an ageing cohort were estimated using the electronic Frailty Index tool, and associated service use and costs were calculated. Association of frailty with outcomes, service use and costs was explored with multistate and generalised linear models. Results informed development of a prototype system dynamics simulation model, exploring population impact of frailty and future scenarios over a 10-year time frame. Simulation model population projections were externally validated against retrospective data from Secure Anonymised Information Linkage. 

Study population: The Royal College of General Practitioners Research and Surveillance Centre sample comprised an open cohort of the primary care population aged 50 + between 2006 and 2017 (approx. 2.1 million people). Data were linked to Hospital Episode Statistics data and Office for National Statistics death data. A comparable validation data set from Secure Anonymised Information Linkage was generated. 

Baseline measures: Electronic Frailty Index score calculated annually and stratified into Fit, Mild, Moderate and Severe frailty categories. Other variables included age, sex, Index of Multiple Deprivation score, ethnicity and Urban/rural. 

Outcomes: frailty transitions, mortality, hospitalisations, emergency department attendances, general practitioner visits and costs. 

Findings: frailty is already present in people aged 50-64. Frailty incidence was 47 cases per 1000 person-years. Frailty prevalence increased from 26.5% (2006) to 38.9% (2017). Older age, higher deprivation, female sex, Asian ethnicity and urban location independently predict frailty onset and progression; 4.8% of 'fit' people aged 50-64 years experienced a transition to a higher frailty state in a year, compared to 21.4% aged 75-84. Individual healthcare use rises with frailty severity, but Mild and Moderate frailty groups have higher overall costs due to larger population numbers. Simulation projections indicate frailty will increase by 7.1%, from 41.5% to 48.7% between 2017 and 2027, and associated costs will rise by £5.8 billion (in England) over an 11-year period. 

Conclusions: simulation modelling indicates that frailty prevalence and associated service use and costs will continue to rise in the future. Scenario analysis indicates reduction of incidence and slowing of progression, particularly before the age of 65, has potential to substantially reduce future service use and costs, but reducing unplanned admissions in frail older people has a more modest impact. Study outputs will be collated into a commissioning toolkit, comprising guidance on drivers of frailty-related demand and simulation model outputs. 

Study registration: this study is registered as NCT04139278 www.clinicaltrials.gov. 

Funding: this award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 16/116/43) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 44. See the NIHR Funding and Awards website for further award information.

AGEING POPULATION, COHORT STUDY, COMPUTER SIMULATION MODELLING, FRAILTY, HEALTH, INCIDENCE, OLDER PEOPLE, PREVALENCE, SERVICE COSTS, SERVICE USE, SYSTEM DYNAMICS, TRANSITIONS
2755-0079
Walsh, Bronagh
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Fogg, Carole
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England, Tracey
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Brailsford, Sally
634585ff-c828-46ca-b33d-7ac017dda04f
Roderick, Paul
dbb3cd11-4c51-4844-982b-0eb30ad5085a
Harris, Scott
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Fraser, Simon
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Clegg, Andrew
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de Lusignan, Simon
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Zhu, Shihua
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Lambert, Francesca
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Barkham, Abigail
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Patel, Harnish
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Windle, Vivienne
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Walsh, Bronagh
5818243e-048d-4b4b-88c5-231b0e419427
Fogg, Carole
42057537-d443-462a-8944-c804252c973b
England, Tracey
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Brailsford, Sally
634585ff-c828-46ca-b33d-7ac017dda04f
Roderick, Paul
dbb3cd11-4c51-4844-982b-0eb30ad5085a
Harris, Scott
19ea097b-df15-4f0f-be19-8ac42c190028
Fraser, Simon
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Clegg, Andrew
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de Lusignan, Simon
ff8f6923-47a6-4c8e-8f12-c0517e6e3724
Zhu, Shihua
13511f9c-151c-483c-9dfd-2da13421db5c
Lambert, Francesca
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Barkham, Abigail
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Patel, Harnish
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Windle, Vivienne
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Walsh, Bronagh, Fogg, Carole, England, Tracey, Brailsford, Sally, Roderick, Paul, Harris, Scott, Fraser, Simon, Clegg, Andrew, de Lusignan, Simon, Zhu, Shihua, Lambert, Francesca, Barkham, Abigail, Patel, Harnish and Windle, Vivienne (2024) Impact of frailty in older people on health care demand: simulation modelling of population dynamics to inform service planning. Health and Social Care Delivery Research, 12 (44). (doi:10.3310/LKJF3976).

Record type: Article

Abstract

Background: as populations age, frailty and the associated demand for health care increase. Evidence needed to inform planning and commissioning of services for older people living with frailty is scarce. Accurate information on incidence and prevalence of different levels of frailty and the consequences for health outcomes, service use and costs at population level is needed. 

Objectives: to explore the incidence, prevalence, progression and impact of frailty within an ageing general practice population and model the dynamics of frailty-related healthcare demand, outcomes and costs, to inform the development of guidelines and tools to facilitate commissioning and service development. 

Study design and methods: a retrospective observational study with statistical modelling to inform simulation (system dynamics) modelling using routine data from primary and secondary health care in England and Wales. Modelling was informed by stakeholder engagement events conducted in Hampshire, England. Data sources included the Royal College of General Practitioners Research and Surveillance Centre databank, and the Secure Anonymised Information Linkage Databank. Population prevalence, incidence and progression of frailty within an ageing cohort were estimated using the electronic Frailty Index tool, and associated service use and costs were calculated. Association of frailty with outcomes, service use and costs was explored with multistate and generalised linear models. Results informed development of a prototype system dynamics simulation model, exploring population impact of frailty and future scenarios over a 10-year time frame. Simulation model population projections were externally validated against retrospective data from Secure Anonymised Information Linkage. 

Study population: The Royal College of General Practitioners Research and Surveillance Centre sample comprised an open cohort of the primary care population aged 50 + between 2006 and 2017 (approx. 2.1 million people). Data were linked to Hospital Episode Statistics data and Office for National Statistics death data. A comparable validation data set from Secure Anonymised Information Linkage was generated. 

Baseline measures: Electronic Frailty Index score calculated annually and stratified into Fit, Mild, Moderate and Severe frailty categories. Other variables included age, sex, Index of Multiple Deprivation score, ethnicity and Urban/rural. 

Outcomes: frailty transitions, mortality, hospitalisations, emergency department attendances, general practitioner visits and costs. 

Findings: frailty is already present in people aged 50-64. Frailty incidence was 47 cases per 1000 person-years. Frailty prevalence increased from 26.5% (2006) to 38.9% (2017). Older age, higher deprivation, female sex, Asian ethnicity and urban location independently predict frailty onset and progression; 4.8% of 'fit' people aged 50-64 years experienced a transition to a higher frailty state in a year, compared to 21.4% aged 75-84. Individual healthcare use rises with frailty severity, but Mild and Moderate frailty groups have higher overall costs due to larger population numbers. Simulation projections indicate frailty will increase by 7.1%, from 41.5% to 48.7% between 2017 and 2027, and associated costs will rise by £5.8 billion (in England) over an 11-year period. 

Conclusions: simulation modelling indicates that frailty prevalence and associated service use and costs will continue to rise in the future. Scenario analysis indicates reduction of incidence and slowing of progression, particularly before the age of 65, has potential to substantially reduce future service use and costs, but reducing unplanned admissions in frail older people has a more modest impact. Study outputs will be collated into a commissioning toolkit, comprising guidance on drivers of frailty-related demand and simulation model outputs. 

Study registration: this study is registered as NCT04139278 www.clinicaltrials.gov. 

Funding: this award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 16/116/43) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 44. See the NIHR Funding and Awards website for further award information.

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Accepted/In Press date: March 2024
Published date: 1 October 2024
Keywords: AGEING POPULATION, COHORT STUDY, COMPUTER SIMULATION MODELLING, FRAILTY, HEALTH, INCIDENCE, OLDER PEOPLE, PREVALENCE, SERVICE COSTS, SERVICE USE, SYSTEM DYNAMICS, TRANSITIONS

Identifiers

Local EPrints ID: 496943
URI: http://eprints.soton.ac.uk/id/eprint/496943
ISSN: 2755-0079
PURE UUID: 882cf114-8480-4daa-a773-aee7bf5361d1
ORCID for Bronagh Walsh: ORCID iD orcid.org/0000-0003-1008-0545
ORCID for Carole Fogg: ORCID iD orcid.org/0000-0002-3000-6185
ORCID for Tracey England: ORCID iD orcid.org/0000-0001-7565-4189
ORCID for Sally Brailsford: ORCID iD orcid.org/0000-0002-6665-8230
ORCID for Paul Roderick: ORCID iD orcid.org/0000-0001-9475-6850
ORCID for Simon Fraser: ORCID iD orcid.org/0000-0002-4172-4406
ORCID for Francesca Lambert: ORCID iD orcid.org/0000-0003-0327-4325
ORCID for Harnish Patel: ORCID iD orcid.org/0000-0002-0081-1802

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Date deposited: 08 Jan 2025 15:05
Last modified: 22 Aug 2025 02:26

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Contributors

Author: Bronagh Walsh ORCID iD
Author: Carole Fogg ORCID iD
Author: Tracey England ORCID iD
Author: Paul Roderick ORCID iD
Author: Scott Harris
Author: Simon Fraser ORCID iD
Author: Andrew Clegg
Author: Simon de Lusignan
Author: Shihua Zhu
Author: Abigail Barkham
Author: Harnish Patel ORCID iD
Author: Vivienne Windle

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