Working Paper: NBER ID: w15032
Authors: Anupam Jena; Tomas Philipson
Abstract: Increased health care spending has been argued to be largely due to technological change. Cost-effectiveness analysis is the main tool used by private and public third-party payers to prioritize adoption of the new technologies responsible for this growth. However, such analysis by payers invariably reflects prices set by producers rather than resources used to produce treatments. This implies that the "costs" in cost-effectiveness assessments depend on endogenous markups which are, in turn, influenced by demand factors of patients, doctors, and payers. Reimbursement policy based on endogenous cost-effectiveness levels may therefore bear little relationship to efficient use of scarce medical resources. Using data on technology appraisals in the United Kingdom, we test for conditions under which adoption based on endogenous cost-effectiveness may lead to adoption of more inefficient treatments in terms of resource use.
Keywords: Cost-effectiveness analysis; Health care technology; Adoption; Inefficiency
JEL Codes: I01; I11; I18
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| observed cost-effectiveness levels (D61) | prices charged to payers (P22) |
| prices charged to payers (P22) | potential inefficiencies in resource allocation (D61) |
| demand factors (J23) | prices charged to payers (P22) |
| prices charged to payers (P22) | treatment adoption decisions (D91) |
| demand-side factors (J23) | perceived cost-effectiveness of treatments (Q51) |
| prices charged to payers (P22) | reversals in cost-effectiveness rankings (D61) |
| lower production costs (D24) | reversals in cost-effectiveness rankings (D61) |
| endogenous cost-effectiveness measures (D61) | misguidance in healthcare resource allocation (I18) |
| self-interest in adoption policies (J18) | less efficient healthcare outcomes (I14) |