Home-based exacerbation management programs have been proposed as an approach to reducing the clinical and financial burden of COPD. We demonstrate a framework to evaluate such programs in order to guide program design and performance decisions towards optimizing cost and clinical outcomes. This study models the impact of hypothetical exacerbation management programs through probabilistic Markov simulations. Patients were stratified by risk using exacerbation rates from the ECLIPSE study and expert opinion. Three scenarios were modeled, using base, worst and best case parameters to suggest potential telehealth program performance. In these scenarios, acute exacerbations could be detected early, with sensitivity and specificity ranging from 60-90%. Detected acute exacerbations could be diverted to either a sub-Acute pathway (12.5-50% probability), thus entirely avoiding hospitalization, or a lower cost pathway through length-of-stay reduction (14-28% reduction). For a cohort of patients without prior hospitalization, the base case telehealth scenario results in a cumulative per-patient lifetime savings of 2.9K over ∼12 years. For a higher risk cohort of patients with a prior admission and 1 to 2 acute exacerbations per year, a cumulative 16K per patient was saved during the remaining ∼3 life-years. Acceptable prices for home-based exacerbation detection testing were highly dependent on patient risk and scenario, but ranged from 290-1263 per month for the highest risk groups. These results suggest the economic viability of exacerbation management programs and highlight the importance of risk stratification in such programs. The presented model can further be adapted to model specific programs as trial data becomes available.
|Original language||English (US)|
|Number of pages||10|
|Journal||COPD: Journal of Chronic Obstructive Pulmonary Disease|
|State||Published - Dec 2013|
ASJC Scopus subject areas
- Pulmonary and Respiratory Medicine