Clinical guidelines in both the United States and the United Kingdom emphasize ambulatory blood pressure (BP) monitoring for individuals suspected of hypertension to ensure accurate diagnosis. This approach is crucial in minimizing misdiagnosis caused by white coat hypertension. However, it often overlooks individuals with masked hypertension who could significantly benefit from timely treatment. The Predicting Out-of-Office Blood Pressure (PROOF-BP) algorithm offers a solution by predicting both masked and white coat hypertension based on patient characteristics and routine clinic BP readings. This innovative tool enhances diagnostic accuracy and reduces the reliance on extensive ambulatory BP monitoring. This study rigorously evaluated the cost-effectiveness of implementing the PROOF-BP algorithm in the diagnosis of hypertension within primary care settings.
A detailed Markov cost-utility cohort model was developed to compare different diagnostic strategies. The PROOF-BP approach, which includes ambulatory BP monitoring guided by the algorithm for patients with clinic BP ≥130/80 mm Hg, was compared against current standard diagnostic strategies. These standard strategies typically involve further monitoring for individuals with clinic BP ≥140/90 mm Hg, including ambulatory BP monitoring as the reference standard, alongside clinic and home monitoring methods. The model was designed with a lifetime horizon, employing 3-month cycles and adopting a UK Health Service/Personal Social Services perspective.
The findings of the study demonstrated that the PROOF-BP algorithm is a cost-effective strategy when used to screen all patients with clinic BP ≥130/80 mm Hg, compared to current strategies that primarily screen those with clinic BP ≥140/90 mm Hg. This cost-effectiveness holds true provided healthcare providers are willing to invest up to £20 000 ($26 000) per quality-adjusted life year gained. Both deterministic and probabilistic sensitivity analyses strongly supported these base-case findings, reinforcing the robustness of the results.
In conclusion, the PROOF-BP algorithm presents a cost-effective alternative to conventional BP diagnostic options within primary care. Integrating this algorithm into routine clinical practice is highly likely to contribute to a significant reduction in cardiovascular disease, mortality rates, and disability, ultimately leading to improved patient outcomes and a more efficient healthcare system.
