
Taking a count: the evaluation of genetic testing
Author(s) -
Hall Jane,
Viney Rosalie,
Haas Marion
Publication year - 1998
Publication title -
australian and new zealand journal of public health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.946
H-Index - 76
eISSN - 1753-6405
pISSN - 1326-0200
DOI - 10.1111/j.1467-842x.1998.tb01488.x
Subject(s) - genetic testing , affect (linguistics) , risk analysis (engineering) , value (mathematics) , intervention (counseling) , cost–benefit analysis , actuarial science , medicine , computer science , psychology , business , nursing , biology , ecology , communication , machine learning
While some forms of genetic testing have been available for decades, the progress of the Human Genome Project will expand the possibilities for testing. Evaluation of genetic testing is warranted because health care services have an opportunity cost and thus the benefits of testing must be assessed against the costs. However, genetic testing raises new methodological difficulties in taking into account the full range of costs, benefits and risks. The conventional approach to evaluating new technologies is to assess their benefits in terms of health outcomes only, and to consider the effects on the individuals being tested. Like any test, the product of genetic testing is information. Any subsequent health outcome gain depends on the effectiveness of any intervention which results from the information. Assessing the benefits in terms of health outcomes only excludes consideration of any value, both positive and negative, attached to information. The special feature of genetic testing is that the information obtained has implications for family members. This information may have value to relatives individually and may affect family interactions. Information also has value at a social level; it may affect social relationships and interactions. As the possibilities for genetic testing expand, it is likely that testing programs will be subject to economic evaluation. Until the methods and measures used can validly take this range of effects into account (and into a count of benefits), then the results of evaluation studies will be, at best, incomplete and, at worst, misleading.