Assessing the Effect of Clinical Inertia on Diabetes Outcomes: a Modeling Approach.

J Gen Intern Med

Center for Remote Health Technologies and Systems, Texas A&M University, College Station, TX, USA.

Published: March 2019

AI Article Synopsis

Article Abstract

Background: There are an increasing number of newer and better therapeutic options in the management of diabetes. However, a large proportion of diabetes patients still experience delays in intensification of treatment to achieve appropriate blood glucose targets-a phenomenon called clinical inertia. Despite the high prevalence of clinical inertia, previous research has not examined its long-term effects on diabetes-related health outcomes and mortality.

Objective: We sought to examine the impact of clinical inertia on the incidence of diabetes-related complications and death. We also examined how the impact of clinical inertia would vary by the length of treatment delay and population characteristics.

Design: We developed an agent-based model of diabetes and its complications. The model was parameterized and validated by data from health surveys, cohort studies, and trials.

Subjects: We studied a simulated cohort of patients with diabetes in San Antonio, TX.

Main Measures: We examined 25-year incidences of diabetes-related complications, including retinopathy, neuropathy, nephropathy, and cardiovascular disease.

Key Results: One-year clinical inertia could increase the cumulative incidences of retinopathy, neuropathy, and nephropathy by 7%, 8%, and 18%, respectively. The effects of clinical inertia could be worse for populations who have a longer treatment delay, are aged 65 years or older, or are non-Hispanic whites.

Conclusion: Clinical inertia could result in a substantial increase in the incidence of diabetes-related complications and mortality. A validated agent-based model can be used to study the long-term effect of clinical inertia and, thus, inform clinicians and policymakers to design effective interventions.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6420509PMC
http://dx.doi.org/10.1007/s11606-018-4773-3DOI Listing

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