US Value Evidence and Outcomes, GlaxoSmithKline plc, Research Triangle Park, NC, USA.
Health Economics and Outcomes Research, Optum, MN, USA.
COPD. 2020 Oct;17(5):499-508. doi: 10.1080/15412555.2020.1817357. Epub 2020 Sep 23.
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 (≥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 ( = 243,998), the algorithm detected ≥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 ( = 301), with an incremental average cost of USD 607 ( = 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.
据估计，约有一半的慢性阻塞性肺疾病（COPD）加重情况被患者不准确报告、在医疗记录中不一致记录，或由于行政索赔中固有的编码错误而未被测量。这项回顾性观察性研究旨在开发一种能够在医疗保健索赔中检测急性 COPD 加重（AECOPD）的算法，并估计在 12 个月期间与 AECOPD 相关的成本。从美国医疗保健索赔数据库中确定了有 COPD 证据的商业和医疗保险优势计划成员（≥40 岁）。为了完善索赔数据中检测 AECOPD 的算法，进行了敏感性和阳性预测值计算，以比较医疗保健索赔中与医疗记录中 AECOPD 的识别。还进行了分析，以检查新索赔算法加上错过的事件识别的总加重相关成本。最终算法的敏感性为 84.9%，阳性预测值为 67.5%。为 402 名患者提取了医疗记录。在整个医疗保健索赔样本（n=243998）中，该算法在 61.3%的患者中检测到≥1 次 AECOPD 事件。最终算法确定的 AECOPD 发作期间每位患者的平均费用为 6760 美元（n=301），在图表样本中，“未观察到”（未在索赔数据中报告）的发作中，平均额外成本为 607 美元（n=122）。经过多变量建模，预测每年的加重费用转化为每位患者 1.12 亿美元（每位患者 12000 美元），其中 3576 万美元与未观察到的加重有关。虽然最终算法需要进一步验证和研究，但这些发现突出了未观察到的 AECOPD 及其经济负担。
