Screening for chronic diseases: optimizing lead time through balancing prescribed frequency and individual adherence

Screening for chronic diseases, such as cancer, is an important public health priority, but traditionally only the frequency or rate of screening has received attention. In this work, we study the importance of adhering to recommended screening policies and develop new methodology to better optimize...

Full description

Saved in:
Bibliographic Details
Published in:Lifetime data analysis 2022-10, Vol.28 (4), p.605-636
Main Authors: Rice, John D., Johnson, Brent A., Strawderman, Robert L.
Format: Article
Language:English
Subjects:
Breast cancer
Chronic illnesses
Diagnosis
Economics
Finance
Health Sciences
Insurance
Lead time
Management
Mathematics and Statistics
Medical screening
Medicine
Operations Research/Decision Theory
Optimization
Policies
Public health
Quality Control
Reliability
Safety and Risk
Statistics
Statistics for Business
Statistics for Life Sciences
Stochastic screening
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Screening for chronic diseases, such as cancer, is an important public health priority, but traditionally only the frequency or rate of screening has received attention. In this work, we study the importance of adhering to recommended screening policies and develop new methodology to better optimize screening policies when adherence is imperfect. We consider a progressive disease model with four states (healthy, undetectable preclinical, detectable preclinical, clinical), and overlay this with a stochastic screening–behavior model using the theory of renewal processes that allows us to capture imperfect adherence to screening programs in a transparent way. We show that decreased adherence leads to reduced efficacy of screening programs, quantified here using elements of the lead time distribution (i.e., the time between screening diagnosis and when diagnosis would have occurred clinically in the absence of screening). Under the assumption of an inverse relationship between prescribed screening frequency and individual adherence, we show that the optimal screening frequency generally decreases with increasing levels of non-adherence. We apply this model to an example in breast cancer screening, demonstrating how accounting for imperfect adherence affects the recommended screening frequency.
ISSN:1380-7870
1572-9249
DOI:10.1007/s10985-022-09563-7