A comprehensive framework to estimate the frequency, duration and risk factors for diagnostic delays using simulation-based methods
Miller, A. C.; Cavanaugh, J. E.; Arakkal, A. T.; Koeneman, S. H.; Polgreen, P. M.
Show abstract
The incidence of diagnostic delays is unknown for many diseases and particular healthcare settings. Many existing methods to identify diagnostic delays are resource intensive or inapplicable to various diseases or settings. In this paper we propose a comprehensive framework to estimate the frequency of missed diagnostic opportunities for a given disease using real-world longitudinal data sources. We start by providing a conceptual model of the disease-diagnostic, data-generating process. We then propose a simulation-based method to estimate measures of the frequency of missed diagnostic opportunities and duration of delays. This approach is specifically designed to identify missed diagnostic opportunities based on signs and symptoms that occur prior to an initial diagnosis, while accounting for expected patterns of healthcare that may appear as coincidental symptoms. Three different simulation algorithms are described for implementing this approach. We summarize estimation procedures that may be used to parameterize the simulation. Finally, we apply our approach to the diseases of tuberculosis, acute myocardial infarction, and stroke and evaluate the estimated frequency and duration of diagnostic delays for these diseases. Our approach can be customized to fit a range of disease and we summarize how the choice of simulation algorithm may impact the resulting estimates.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Bias reduction and inference for electronic health record data under selection and phenotype misclassification: three case studies 94%
- Evaluating the ALERT algorithm for local outbreak onset detection in seasonal infectious disease surveillance data 94%
- A Double Machine Learning Approach for the Evaluation of COVID-19 Vaccine Effectiveness under the Test-Negative Design: Analysis of Québec Administrative Data 93%
Similar papers in this journal
Similar papers in this journal
- The Epidemiological Implications of Jails for Community, Corrections Officer, and Incarcerated Population Risks from COVID-19 92%
- Sensitivity and Uncertainty Analysis for Two-Stream Capture-Recapture Methods in Disease Surveillance 92%
- Incorporating data from multiple endpoints in the analysis of clinical trials: example from RSV vaccines 91%
Similar papers in this journal
- A Bayesian Susceptible-Infectious-Hospitalized-Ventilated-Recovered Model to Predict Demand for COVID-19 Inpatient Care in a Large Healthcare System 95%
- Time-to-event estimation of birth year prevalence trends: a method to enable investigating the etiology of childhood disorders including autism 94%
- A Stacked ensemble method for forecasting influenza-like illness visit volumes at emergency departments 92%
Similar papers in this journal
- Obtaining prevalence estimates of COVID-19: A model to inform decision-making 91%
- Performance of Existing and Novel Symptom- and Antigen Testing-Based COVID-19 Case Definitions in a Community Setting 90%
- Potential Biases in Test-Negative Design Studies of COVID-19 Vaccine Effectiveness Arising from the Inclusion of Asymptomatic Individuals 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.