Cited by 75Blood Pressure and Hypertension StudiesHealth Systems, Economic Evaluations, Quality of LifeClinical practice guidelines implementation

Cost–Benefit Analysis of Home Blood Pressure Monitoring in Hypertension Diagnosis and Treatment: An Insurer Perspective

Arrieta, Alejandro, Woods, John R., Qiao, Nan, Jay, Stephen J.·2014·Hypertension

Abstract

Home blood pressure (BP) monitoring has been shown to be more effective than clinic BP monitoring for diagnosing and treating hypertension. However, reimbursement of home BP monitoring is uncommon in the United States because of a lack of evidence that it is cost beneficial for insurers. We develop a decision-analytic model, which we use to conduct a cost–benefit analysis from the perspective of the insurer. Model inputs are derived from the 2008 to 2011 claims data of a private health insurer in the United States, from 2009 to 2010 National Health and the Nutrition Examination Survey data, and from published meta-analyses. The model simulates the transitions among health states from initial physician visit to hypertension diagnosis, to treatment, to hypertension-related cardiovascular diseases, and patient death or resignation from the plan. We use the model to estimate cost–benefit ratios and both short- and long-run return on investment for home BP monitoring compared with clinic BP monitoring. Our results suggest that reimbursement of home BP monitoring is cost beneficial from an insurer’s perspective for diagnosing and treating hypertension. Depending on the insurance plan and age group categories considered, estimated net savings associated with the use of home BP monitoring range from $33 to $166 per member in the first year and from $415 to $1364 in the long run (10 years). Return on investment ranges from $0.85 to $3.75 per dollar invested in the first year and from $7.50 to $19.34 per dollar invested in the long run.

Integrity signals

Registry

Crossref · 10.1161/hypertensionaha.114.03780

Cites

29 of 29 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

1 of the 30 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Arrieta, A., Woods, J. R., Qiao, N., & Jay, S. J.
Affiliations
Indiana University Health (US)
Venue
Hypertension
Published
2014-10
Volume
64
Issue
4
Pages
891-896
ISSN
  • 0194-911X (ISSN-L)
  • 1524-4563
OpenAlex
W2102547927
Cited by
75
References
30
Citations by year
2026: 2 · 2025: 3 · 2024: 6 · 2023: 10 · 2022: 4 · 2021: 6 · 2020: 15 · 2019: 8 · 2018: 4 · 2017: 10 · 2016: 1 · 2015: 6
FWCI
3.87
Type
journal article
Language
en
Open access
closed
Locations
  • Hypertension (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Indiana Clinical and Translational Sciences Institute
  • Indiana University Health
  • School of Medicine, Indiana University
Topics
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Blood Pressure and Hypertension Studies
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
Keywords
home blood pressure monitoring, hypertension diagnosis, antihypertensive therapy, cost-benefit analysis, insurance reimbursement, return on investment, decision-analytic model, cardiovascular disease, health state transitions
MeSH terms
Adult, Aged, Cost-Benefit Analysis, Female, Humans, Hypertension, Insurance Carriers, Insurance, Health, Reimbursement, Male, Middle Aged, United States, Blood Pressure Monitoring, Ambulatory, Models, Economic, Young Adult

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review