cardiology · Other

Preferences for Antihypertensive Prescribing in Older Adults: A Discrete Choice Experiment.

O'Hagan Edel E, Livingstone Ann A, Gadsden Thomas T, Usherwood Timothy T, Nguyen Tu T, Schutte Aletta E AE et al.
Journal of the American College of Cardiology · May 12, 2026 · PMID 41778956 · DOI 10.1016/j.jacc.2026.01.044

Abstract (English)

BACKGROUND: Understanding which attributes influence blood pressure (BP) prescribing, and the magnitude of their effects, could inform strategies to reduce clinical inertia in older adults. OBJECTIVES: The purpose of this study was to examine doctors' preferences and trade-offs when deciding to intensify antihypertensive treatment in adults aged ≥65 years with uncontrolled BP. METHODS: We conducted a discrete choice experiment with Australian doctors, presenting hypothetical patient profiles varying by age, frailty, fall history, residual cardiovascular risk, and availability of digital health monitoring. Doctors chose between 2 systolic BP targets: intensive (≤130 mm Hg) or standard (131-150 mm Hg). A mixed multinomial logit model was used to estimate attribute effects, and latent class analysis to explore heterogeneity in preferences. RESULTS: Overall, doctors favored the intensive treatment target (OR: 2.70; 95% CI: 1.84-9.96) but this preference decreased with increasing patient age (eg, age 80; OR: 0.05; 95% CI: 0.03-0.07), recent falls (OR: 0.22; 95% CI: 0.16-0.29), and moderate frailty (OR: 0.24; 95% CI: 0.12-0.46). Higher residual cardiovascular risk reduced the likelihood of intensive treatment, whereas digital health availability increased it (OR: 1.50; 95% CI: 1.05-2.15). Latent class analysis identified 2 groups: risk tolerant, digitally engaged (64%), who preferred intensive treatment and were responsive to digital data, and risk-averse (36%), with no overall preference and were unaffected by digital information. CONCLUSIONS: Clinicians' decisions to intensify antihypertensive treatment in older adults are influenced by age, falls, frailty, perceived benefit, and access to digital monitoring data. Use of digital health interventions may reduce clinical inertia and should be evaluated in clinical trials.

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