Meta-analytic estimation of measurement variability and assessment of its impact on decision-making: the case of perioperative haemoglobin concentration monitoring.

ABSTRACT:

Background

As a part of a larger Health Technology Assessment (HTA), the measurement error of a device used to monitor the hemoglobin concentration of a patient undergoing surgery, as well as its decision consequences, were to be estimated from published data.

Methods

A Bayesian hierarchical model of measurement error, allowing the meta-analytic estimation of both central and dispersion parameters (under the assumption of normality of measurement errors) is proposed and applied to published data; the resulting potential decision errors are deduced from this estimation. The same method is used to assess the impact of an initial calibration.

Results

The posterior distributions are summarized as mean ± sd (credible interval). The fitted model exhibits a modest mean expec

SUBMITTER: Charpentier E 

PROVIDER: S-EPMC4717612 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature