Impact of observability period on the classification of COPD diagnosis timing among Medicare beneficiaries with lung cancer

Background: Investigators often use claims data to estimate the diagnosis timing of chronic conditions. However, misclassification of chronic conditions is common due to variability in healthcare utilization and in claims history across patients. Objective: We aimed to quantify the effect of various Medicare fee-for-service continuous enrollment period and lookback period (LBP) on misclassification of COPD and sample size. Methods: A stepwise tutorial to classify COPD, based on its diagnosis timing relative to lung cancer diagnosis using the Surveillance Epidemiology and End Results cancer registry linked to Medicare insurance claims. We used 3 approaches varying the LBP and required continuous enrollment (i.e., observability) period between 1 to 5 years. Patients with lung cancer were classified based on their COPD related healthcare utilization into 3 groups: pre-existing COPD (diagnosis at least 3 months before lung cancer diagnosis), concurrent COPD (diagnosis during the -/+ 3months of lung cancer diagnosis), and non-COPD. Among those with 5 years of continuous enrollment, we estimated the sensitivity of the LBP to ascertain COPD diagnosis as the number of patients with pre-existing COPD using a shorter LBP divided by the number of patients with pre-existing COPD using a longer LBP. Results: Extending the LBP from 1 to 5 years increased prevalence of pre-existing COPD from ~ 36% to 51%, decreased both concurrent COPD from ~ 34% to 23% and non-COPD from ~ 29% to 25%. There was minimal effect of extending the required continuous enrollment period beyond one year across various LBPs. In those with 5 years of continuous enrollment, sensitivity of COPD classification (95% CI) increased with longer LBP from 70.1% (69.7% to 70.4%) for one-year LBP to 100% for 5-years LBP. Conclusion: The length of optimum LBP and continuous enrollment period depends on the context of the research question and the data generating mechanisms. Among Medicare beneficiaries, the best approach to identify diagnosis timing of COPD relative to lung cancer diagnosis is to use all available LBP with at least one year of required continuous enrollment. Author summary: Healthcare data such as electronic health records and health insurance claims is a rich resource to study outcomes of chronic medical conditions such as chronic obstructive pulmonary disease (COPD). However, it can be tricky to determine the optimal period of searching the claims to identify the first diagnosis time of a chronic condition. In this study, we explored three approaches to optimize classification of COPD diagnosis based on a variety of Medicare claims search periods and observability (required continuous periods of enrollment) periods. We used a large dataset of Medicare claims linked to SEER cancer registry including more than 158,000 Medicare beneficiaries to identify diagnosis timing of COPD relative to lung cancer diagnosis. We observed that the most efficient approach to classify COPD diagnosis timing is to use all available historical claims data while requiring a minimum of one year of Medicare continuous enrollment. Our findings will help researchers concerned about accuracy of diagnosis timing of chronic conditions such as COPD and loss in sample size, especially when long periods of continuous insurance enrollment isn’t feasible.