A comprehensive framework to estimate the frequency, duration, and risk factors for diagnostic delays using bootstrapping-based simulation methods.

ABSTRACT: The incidence of diagnostic delays is unknown for many diseases and specific healthcare settings. Many existing methods to identify diagnostic delays are resource intensive or difficult to apply to different diseases or settings. Administrative and other real-world data sources may offer the ability to better identify and study diagnostic delays for a range of diseases. We propose a comprehensive framework to estimate the frequency of missed diagnostic opportunities for a given disease using real-world longitudinal data sources. We provide a conceptual model of the disease-diagnostic, data-generating process. We then propose a bootstrapping method to estimate measures of the frequency of missed diagnostic opportunities and duration of delays. This approach identifies diagnostic opportuniti

SUBMITTER: Miller AC 

PROVIDER: S-EPMC10103428 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature