Almost half of chronic obstructive pulmonary disease (COPD) exacerbations are estimated to be inaccurately reported by patients, inconsistently recorded in medical records, or not measured due to coding errors inherent to administrative claims. This retrospective observational study aimed to develop an algorithm capable of detecting acute COPD exacerbations (AECOPD) in healthcare claims and estimate costs associated with AECOPD over a 12-month period. Commercial and Medicare Advantage healthcare plan members (&#8805;40 years old) with evidence of COPD were identified from US healthcare-claims database. To refine the algorithm detecting AECOPD in claims data, sensitivity and positive-predictive value calculations were performed to compare AECOPD identification in healthcare claims versus medical charts. Analyses were also performed to examine total exacerbation-related costs for events identified with the new claims algorithm plus events missed. The final algorithm had a sensitivity of 84.9%, with a positive-predictive value of 67.5%. Medical records were abstracted for 402 patients. In the overall sample of healthcare claims (n = 243,998), the algorithm detected &#8805;1 AECOPD event in 61.3% of patients. The mean cost per patient during an AECOPD episode, identified by the final algorithm, was USD 6,760 (n = 301), with an incremental average cost of USD 607 (n = 122) to 'unobserved' episodes (not reported in claims data) among the chart sample. After multivariate modeling, predicted yearly exacerbation costs translated to USD 1.12 billion per 100,000 patients (USD 12,000 per patient), with 35.76 million associated with unobserved exacerbations. While the final algorithm warrants further validation and study, these findings highlight unobserved AECOPD and their economic burden.
The Identification and Cost of Acute Chronic Obstructive Pulmonary Disease Exacerbations in a United States Population Healthcare Claims Database