title: Caveats in interpreting and applying pharmacoeconomic data.
abstract: Cautions in the interpretation and application of pharmacoeconomic data are discussed. Cost containment is driving outcomes research and can cause pharmacoeconomic study methods to be manipulated to support preordained conclusions. The usual tactic is to adopt a narrow perspective in assessing benefits and costs. For example, many calculations ignore financial and physical pain borne by the patient. Before the results of any pharmacoeconomic analysis are embraced, the perspective adopted should be carefully examined. Each provider must look at a product or service from all relevant angles and in the context of its own standards. Although outcomes research may indeed make it possible to provide high-quality care for less money in the long term, in the short term these studies are devoted largely to the goal of spending less, even if some patients may suffer. In such circumstances, legal issues unavoidably arise. Principal among them is tort liability, the risk of being deemed negligent either in providing care or in obtaining informed consent. Any topic pressing enough to be included in outcomes research agendas and debates is going to require decisions that consider (1) the positions of national medical specialty societies, (2) the relevant catchment area or other defining cohort, (3) the specific institution, and (4) the professionals practicing in that institution. The inhouse professional who disagrees with rationing can become a credible whistle blower, and the judiciary may go to extraordinary lengths to empower patients, even without whistle blowers. Complete honesty in obtaining informed consent can help avoid legal actions. Pharmacoeconomic research can be useful in describing value for money spent. It is important to remember, however, that perspective matters in any analysis and that honesty is vital in policymaking and in sharing information with patients.
authors.affiliation: McDermott, Will & Emery, Chicago, IL 60606-5096, USA.
authors.forename: N E
authors.initials: NE
authors.lastname: Cahill
mesh_terms: D003627:Data Interpretation, Statistical; D017850:Economics, Pharmaceutical / Q000706:statistics & numerical data; D006801:Humans; D017063:Outcome Assessment, Health Care