Measuring blood pressure for decision making and quality reporting: where and how many measures?

Abstract

Background

The optimal setting and number of blood pressure (BP) measurements that should be used for clinical decision making and quality reporting are uncertain.

Objective

To compare strategies for home or clinic BP measurement and their effect on classifying patients as having BP that was in or out of control.

Design

Secondary analysis of a randomized, controlled trial of strategies to improve hypertension management. (ClinicalTrials.gov registration number: NCT00237692)

Setting

Primary care clinics affiliated with the Durham Veterans Affairs Medical Center.

Patients

444 veterans with hypertension followed for 18 months.

Measurements

Blood pressure was measured repeatedly by using 3 methods: standardized research BP measurements at 6-month intervals; clinic BP measurements obtained during outpatient visits; and home BP measurements using a monitor that transmitted measurements electronically.

Results

Patients provided 111,181 systolic BP (SBP) measurements (3218 research, 7121 clinic, and 100,842 home measurements) over 18 months. Systolic BP control rates at baseline (mean SBP<140 mm Hg for clinic or research measurement; <135 mm Hg for home measurement) varied substantially, with 28% classified as in control by clinic measurement, 47% by home measurement, and 68% by research measurement. Short-term variability was large and similar across all 3 methods of measurement, with a mean within-patient coefficient of variation of 10% (range, 1% to 24%). Patients could not be classified as having BP that was in or out of control with 80% certainty on the basis of a single clinic SBP measurement from 120 mm Hg to 157 mm Hg. The effect of within-patient variability could be greatly reduced by averaging several measurements, with most benefit accrued at 5 to 6 measurements.

Limitation

The sample was mostly men with a long-standing history of hypertension and was selected on the basis of previous poor BP control.

Conclusion

Physicians who want to have 80% or more certainty that they are correctly classifying patients' BP control should use the average of several measurements. Hypertension quality metrics based on a single clinic measurement potentially misclassify a large proportion of patients.

Primary funding source

U.S. Department of Veterans Affairs Health Services Research and Development Service.

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.7326/0003-4819-154-12-201106210-00005

Publication Info

Powers, Benjamin J, Maren K Olsen, Valerie A Smith, Robert F Woolson, Hayden B Bosworth and Eugene Z Oddone (2011). Measuring blood pressure for decision making and quality reporting: where and how many measures?. Annals of internal medicine, 154(12). pp. 781–788. 10.7326/0003-4819-154-12-201106210-00005 Retrieved from https://hdl.handle.net/10161/30096.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.

Scholars@Duke

Olsen

Maren Karine Olsen

Professor of Biostatistics & Bioinformatics

Health services research, longitudinal data methods, missing data methods

Smith

Valerie A. Smith

Associate Professor in Population Health Sciences

Valerie A. Smith, DrPH, is an Associate Professor in the Duke University Department of Population Health Sciences and Senior Research Director of the Biostatistics Core at the Durham Veterans Affairs Medical Center's Center of Innovation. Her methodological research interests include: methods for semicontinuous and zero-inflated data, economic modeling methods, causal inference methods, observational study design, and longitudinal data analysis. Her current methodological research has focused on the development of marginalized models for semicontinuous data.

Dr. Smith works largely in collaboration with a multidisciplinary team of researchers, with a focus on health policy interventions, health care utilization and expenditure patterns, program and policy evaluation, obesity and weight loss, bariatric surgery evaluation, and family caregiver supportive services.

Areas of expertise: Biostatistics, Health Services Research, Health Economics, and Health Policy


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