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Cost-effectiveness of antihypertensive deprescribing in primary care: a Markov modelling study using data from the OPTiMISE trial

Cost-effectiveness of antihypertensive deprescribing in primary care: a Markov modelling study using data from the OPTiMISE trial
Cost-effectiveness of antihypertensive deprescribing in primary care: a Markov modelling study using data from the OPTiMISE trial

BACKGROUND: Deprescribing of antihypertensive medications for older patients with normal blood pressure is recommended by some clinical guidelines, where the potential harms of treatment may outweigh the benefits. This study aimed to assess the cost-effectiveness of this approach.

METHODS: A Markov patient-level simulation was undertaken to model the effect of withdrawing one antihypertensive compared with usual care, over a life-time horizon. Model population characteristics were estimated using data from the OPTiMISE antihypertensive deprescribing trial, and the effects of blood pressure changes on outcomes were derived from the literature. Health-related quality of life was modeled in Quality-Adjusted Life Years (QALYs) and presented as costs per QALY gained.

RESULTS: In the base-case analysis, medication reduction resulted in lower costs than usual care (mean difference £185), but also lower QALYs (mean difference 0.062) per patient over a life-time horizon. Usual care was cost-effective at £2975 per QALY gained (more costly, but more effective). Medication reduction resulted more heart failure and stroke/TIA events but fewer adverse events. Medication reduction may be the preferred strategy at a willingness-to-pay of £20 000/QALY, where the baseline absolute risk of serious drug-related adverse events was ≥7.7% a year (compared with 1.7% in the base-case).

CONCLUSIONS: Although there was uncertainty around many of the assumptions underpinning this model, these findings suggest that antihypertensive medication reduction should not be attempted in many older patients with controlled systolic blood pressure. For populations at high risk of adverse effects, deprescribing may be beneficial, but a targeted approach would be required in routine practice.

Antihypertensive Agents/adverse effects, Cost-Benefit Analysis, Deprescriptions, Humans, Primary Health Care, Quality of Life, Quality-Adjusted Life Years
0194-911X
1122-1131
Jowett, Sue
eb42c651-c828-4b5d-b144-d766a8bac7a0
Kodabuckus, Shahela
cd0649b4-de7a-46aa-b560-ab04f05e14ca
Ford, Gary A
c03a4c65-e4ef-4d39-a8be-dbdc20cfef0b
Hobbs, F D Richard
9a0f0240-ff92-43ed-882a-2c3be3472559
Lown, Mark
4742d5f8-bcf3-4e0b-811c-920e7d010c9b
Mant, Jonathan
cb9dbdd7-7e9a-43e3-b977-266ad88a082f
Payne, Rupert
7942b13c-a1a6-4f55-8ce5-37c875a8ec33
McManus, Richard J
481f6284-d599-4c77-8869-d1c6b63b9b02
Sheppard, James P
5468331c-e231-4103-b407-28c8161cc6d7
OPTiMISE investigators
Jowett, Sue
eb42c651-c828-4b5d-b144-d766a8bac7a0
Kodabuckus, Shahela
cd0649b4-de7a-46aa-b560-ab04f05e14ca
Ford, Gary A
c03a4c65-e4ef-4d39-a8be-dbdc20cfef0b
Hobbs, F D Richard
9a0f0240-ff92-43ed-882a-2c3be3472559
Lown, Mark
4742d5f8-bcf3-4e0b-811c-920e7d010c9b
Mant, Jonathan
cb9dbdd7-7e9a-43e3-b977-266ad88a082f
Payne, Rupert
7942b13c-a1a6-4f55-8ce5-37c875a8ec33
McManus, Richard J
481f6284-d599-4c77-8869-d1c6b63b9b02
Sheppard, James P
5468331c-e231-4103-b407-28c8161cc6d7

OPTiMISE investigators (2022) Cost-effectiveness of antihypertensive deprescribing in primary care: a Markov modelling study using data from the OPTiMISE trial. Hypertension (Dallas, Tex. : 1979), 79 (5), 1122-1131. (doi:10.1161/HYPERTENSIONAHA.121.18726).

Record type: Article

Abstract

BACKGROUND: Deprescribing of antihypertensive medications for older patients with normal blood pressure is recommended by some clinical guidelines, where the potential harms of treatment may outweigh the benefits. This study aimed to assess the cost-effectiveness of this approach.

METHODS: A Markov patient-level simulation was undertaken to model the effect of withdrawing one antihypertensive compared with usual care, over a life-time horizon. Model population characteristics were estimated using data from the OPTiMISE antihypertensive deprescribing trial, and the effects of blood pressure changes on outcomes were derived from the literature. Health-related quality of life was modeled in Quality-Adjusted Life Years (QALYs) and presented as costs per QALY gained.

RESULTS: In the base-case analysis, medication reduction resulted in lower costs than usual care (mean difference £185), but also lower QALYs (mean difference 0.062) per patient over a life-time horizon. Usual care was cost-effective at £2975 per QALY gained (more costly, but more effective). Medication reduction resulted more heart failure and stroke/TIA events but fewer adverse events. Medication reduction may be the preferred strategy at a willingness-to-pay of £20 000/QALY, where the baseline absolute risk of serious drug-related adverse events was ≥7.7% a year (compared with 1.7% in the base-case).

CONCLUSIONS: Although there was uncertainty around many of the assumptions underpinning this model, these findings suggest that antihypertensive medication reduction should not be attempted in many older patients with controlled systolic blood pressure. For populations at high risk of adverse effects, deprescribing may be beneficial, but a targeted approach would be required in routine practice.

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Accepted/In Press date: 23 February 2022
Published date: 10 May 2022
Keywords: Antihypertensive Agents/adverse effects, Cost-Benefit Analysis, Deprescriptions, Humans, Primary Health Care, Quality of Life, Quality-Adjusted Life Years

Identifiers

Local EPrints ID: 475337
URI: http://eprints.soton.ac.uk/id/eprint/475337
ISSN: 0194-911X
PURE UUID: ba10ba9d-7436-4d71-99c4-5a6e885503c6
ORCID for Mark Lown: ORCID iD orcid.org/0000-0001-8309-568X

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Date deposited: 15 Mar 2023 17:45
Last modified: 17 Mar 2024 03:37

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Contributors

Author: Sue Jowett
Author: Shahela Kodabuckus
Author: Gary A Ford
Author: F D Richard Hobbs
Author: Mark Lown ORCID iD
Author: Jonathan Mant
Author: Rupert Payne
Author: Richard J McManus
Author: James P Sheppard
Corporate Author: OPTiMISE investigators

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