Obtaining evidence for use by healthcare payers on the success of chronic obstructive pulmonary disease management

Abstract

Healthcare payers make decisions on funding for treatments for diseases, such as chronic obstructive pulmonary disease (COPD), on a population level, so require evidence of treatment success in appropriate populations, using usual routine care as the comparison for alternative management approaches. Such health outcomes evidence can be obtained from a number of sources. The 'gold standard' method for obtaining evidence of treatment success is usually taken as the randomized controlled prospective clinical trial. Yet the value of such studies in providing evidence for decision-makers can be questioned due to the restricted entry criteria limiting the ability to generalize to real life populations, narrow focus on individual parameters, use of placebo for comparison rather than usual therapy and unrealistic intense monitoring of patients. Evidence obtained from retrospective and observational studies can supplement that from randomized clinical trials, providing that care is taken to guard against bias and confounders. However, very large numbers of patients must be investigated if small differences between drugs and treatment approaches are to be detected. Administrative databases from healthcare systems provide an opportunity to obtain observational data on large numbers of patients. Such databases have shown that high healthcare costs in patients with COPD are associated with co-morbid conditions and current smoking status. Analysis of an administrative database has also shown that elderly patients with COPD who received inhaled corticosteroids within 90 days of discharge from hospital had 24% fewer repeat hospitalizations for COPD and were 29% less likely to die during the 1-year follow-up period. In conclusion, there are a number of sources of meaningful evidence of the health outcomes arising from different therapeutic approaches that should be of value to healthcare payers making decisions on resource allocation.