Mm. Burgess et al., DILEMMAS OF ANONYMOUS PREDICTIVE TESTING FOR HUNTINGTON DISEASE - PRIVACY VS OPTIMAL CARE, American journal of medical genetics, 71(2), 1997, pp. 197-201
Some persons at risk for Huntington disease (HD) seek predictive testi
ng under the protection of anonymity to reduce the risk of insurance d
iscrimination for themselves and their families. While Canadian and Eu
ropean health care systems seem to limit insurance discrimination to l
ife and disability insurance, U.S. residents do not have national heal
th insurance and are concerned about health insurance discrimination.
Two persons residing outside Canada requested predictive testing anony
mously. Their primary reason for doing so was to avoid the risks of me
dical insurance discrimination, After a detailed preparatory session a
nd agreement to counselling and to receipt of results in person, we ag
reed to provide anonymous testing to these persons. One participant, w
hose psychological assessment was unremarkable, coped well with the pr
edictive testing process and did not have the CAG expansion. The other
participant had considerable emotional problems prior to testing, whi
ch necesitated postponement of discussion of results and referral for
psychiatric assessment and support, Both participants had difficulty m
aintaining anonymity. The provision of anonymous predictive testing ra
ises several problems. With anonymous testing, clinicians cooperate wi
th participants to exclude insurance companies from information, This
may invalidate the contract with insurance companies. A policy respons
e by insurance companies or a universal health care system to protect
individuals is preferable, Individuals who request anonymous testing m
ay be precisely those most vulnerable and in need of additional suppor
t and counselling. However, the preservation of anonymity is a burden
to participants and may frustrate the clinicians' ability to establish
rapport in counselling and to provide appropriate follow-up typically
available through genetic counselling in predictive testing programs.
(C) 1997 Wiley-Liss, Inc.