significance, suggesting the long-term nature of medical cost-offset. It should also be

noted that the study sample was derived from HMO clinics, which has implications for

cost offset effects. That is, to the extent that managed care restrictions reduce length of

treatment, dramatic cost offsets would also be reduced (Otto, 1999).

 There are several limitations to cost offset studies and this study was an attempt to

address these limitations. First, when studies compare the costs of treated and untreated

patients, there may be a selection bias in which samples are not comparable (Sturm,

2001). That is, patients who received treatment may have different characteristics than

patients who did not receive treatment. If there is limited case-mix information in the

data, the selection bias is particularly pronounced. This is particularly problematic with

administrative datasets. In this study, the use of a large comprehensive dataset allowed

for greater control of potential confounding variables, such as illness severity and

comorbid medical conditions.

 Second, cost offsets have traditionally been referred to as a general phenomenon

applying to all medical populations. Past cost offset research has not yet teased apart

which medical populations benefit from psychological interventions. This study is a

preliminary effort to identify specific cost offset effects in particular populations. The

populations of interest were pulmonary and cardiac patients who had comorbid

depression or anxiety. The dataset was a nationally representative sample, which allowed

for greater generalizability for the populations in question.

 Rapid changes in healthcare financing and spending patterns necessitates frequent

review of offset effects refelcting current pricing in pharmacological and medical

treatments (Hunsley, 2003). It is difficult to generalize cost offset effects from one year