While the insurance incentives substantially increased the proportion of the
population with supplementary private insurance, the impact on the use of the public
system by new entrants appears to be quite modest. They conclude that using financial
PHI incentives is not a cost-effective way of reducing pressure on public hospital
systems.
Feibig et al 2007 analysed private health insurance behaviours among respondents to
the 2001 NHS to identify insurance ‘types’ according to stated reasons for buying
health insurance. They found considerable evidence of unexplained heterogeneity
among the privately insured population and that insurance type is significantly
associated with hospital utilisation, particularly the probability of being admitted as a
public or private patient. The government’s insurance incentives were more attractive
to particular types of the insured population and this limits their effectiveness in
reducing pressure on the public hospital system.
In this paper we use the HILDA data to further explore heterogeneity of private health
insurance choices. We investigate demographic, family, health and income factors
related to respondent’s private health insurance decisions in the light of recent policy
changes. We focus on whether these policy changes attracted a different demographic
to purchase private health insurance than previously. We are also interested in
describing those who have dropped private health insurance since the introduction of
LHC. Since the policies only apply to the purchase of hospital cover, we have
excluded ancillary cover only from our definition of private health insurance.
We identify six distinct groups: those who purchased private hospital cover before
LHC; those who reported they took up private hospital cover in 2000 in response to
the LHC deadline; those who took up private hospital cover after 2000 (i.e. after the
LHC premiums were in place); those who dropped private hospital cover after 2000;
those who had dropped private hospital cover prior to 2000 and remained uninsured;
those who had never purchased private hospital cover. We model the insurance
decisions using a multinomial probit model which allows for heterogeneity of choice
and correlation across alternatives. We use our preferred model to simulate predicted
probabilities for each alternative outcome. To illustrate our results we constructed a
series of hypothetical index individuals for each outcome alternative of interest,
setting the levels of the explanatory variables to give a high simulated probability of
choice for that alternative. We then use the index individual as a base to examine the
effect of a change in the level of each explanatory variable on the probability of
choice for the alternative of interest, keeping all other variables at the level of the
index individual.
These results focus on the three groups whose decisions would be affected by
Lifetime Health Cover: those who joined PHI because of the lifetime Health cover
deadline, those who joined after the deadline and those who dropped hospital cover
since the introduction of the policy.
2. Data
The Household Income and Labour Dynamics of Australia (HILDA) study is a
longitudinal population survey which commenced in 2001. HILDA is a representative
sample of Australian households. In the baseline 2001 survey all members of 7,682
selected households were enumerated and members aged 15 years and over were