PRIVATE HEALTH INSURANCE IN AUSTRALIA, 1990
Deborah Schofield
Discussion Paper No. 17 May 1997
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THE DISTRIBUTION AND
DETERMINANTS OF
PRIVATE HEALTH INSURANCE
IN AUSTRALIA, 1990
Deborah Schofield
Discussion Paper No. 17 May 1997
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Abstract
Private health insurance is an important source of health funding in Australia and interest in identifying who has private health insurance has grown since the mid-1980s.
The first part of the study analyses data from the 1989-90 national health survey to examine the distribution of private health insurance across different subpopulations in Australia. The second part of the study identifies the important determinants of private health insurance. In doing so, it was found that there were substantial differences not only in who has private health insurance, but also in the type of insurance
purchased, across a broad range of analysis groups identified by income, family type, age, health services used, health status, health risk factors, ethnicity and region of residence.
Author note
Deborah Schofield was a Research Fellow at the National Centre for Social and Economic Modelling. She now works for the Australian Institute of Health and Welfare, Canberra.
Acknowledgments
The author would like to thank Professor Dick Scotton for refereeing the paper. Thanks also go to Richard Percival, Jonathan Baldry, Geoff Sims and Anthony King for providing helpful comments on an earlier draft and to Ralph Lattimore for his assistance in preparing a spreadsheet version of the author’s model in chapter 5.
General caveat
NATSEM research findings are generally based on estimated character-istics of the population. Such estimates are usually derived from the application of microsimulation modelling techniques to microdata based on sample surveys.
These estimates may be different from the actual characteristics of the population because of sampling and nonsampling errors in the
microdata and because of the assumptions underlying the modelling techniques.
The microdata do not contain any information that enables identification of the individuals or families to which they refer.
Contents
Abstract ... iii
Author note ...iv
Acknowledgments ...iv
General caveat ...iv
1 Introduction ... 1
2 Private health insurance in Australia ... 3
3 Methodology ... 4
3.1 The data source ...4
3.2 Variables used in the analysis ...5
4 Distribution of private health insurance ... 7
4.1 Distribution of private health insurance by type of private health insurance ...8
4.2 Distribution of single rate private health insurance among families ...25
5 Determinants of private health insurance ... 28
5.1 Multivariate models of private health insurance ...28
5.2 Identifying significant determinants of private health insurance ...31
5.3 Using scenarios to examine the probability of insurance ...34
5.4 Ranking variables in order of importance within the models ...39
6 Summary ... 40
Appendix A Coefficients, significance levels and standard errors for logit regressions ... 44
1
Introduction
This paper describes an analysis of the distribution of private health insurance and of which characteristics are most important in
determining who had private health insurance in Australia in 1990.
The study uses data from the 1989-90 national health survey (NHS) (ABS 1990). The NHS included information on private health insurance,
expenditure on private health insurance, information on health and health service use, and a wide range of socioeconomic characteristics. Knowledge of the distribution and determinants of private health insurance is crucial for planning public health service delivery and funding, and for analysing existing or new private health insurance policy, particularly as the public and private health systems are so interdependent (Cameron et al. 1988). Since the introduction in 1984 of Medicare, a universal public insurance system, there has been a quite rapid shift in the socioeconomic characteristics of Australians who have private health insurance and, accordingly, interest in the distribution of health insurance has increased (Private Insurance Taskforce 1993;
Schofield et al. 1996; Willcox 1991).
There have been several studies that have included an analysis of the distribution of private health insurance (ABS 1995a; Burrows, Brown and Gruskin 1993; Hopkins and Kidd 1993). However, these have generally limited their analysis to whether a person (or family) is insured. This study extends previous analyses of the distribution of private health insurance by including a specific analysis of the type of health insurance held by contributors. It also includes analysis of a wider range of
variables than earlier studies did — including, for example, the use of health services, ethnicity and region of residence. In addition, there is an examination of the characteristics of families who choose to insure only one family member.
There have also been several Australian studies reporting on the determinants of private health insurance. However, some of these studies are limited by their use of pre-Medicare data (Cameron et al. 1988; Cameron and Trivedi 1991; Ngui, Burrows and Brown 1989), their small selection of variables (Burrows et al. 1993; Willcox 1991) or their reliance on a relatively small sample (Burrows et al. 1993).
Hopkins and Kidd (1993) completed a more comprehensive study of the determinants of private health insurance using post-Medicare data. They confirmed that economic, demographic and health status variables were important predictors of who held private health insurance. In addition, they established that a further demographic variable (education), the use of some health services (hospitalisation and doctor visits) and a single health risk factor (smoking) were also important determinants of private health insurance.
More recently, the Australian Bureau of Statistics (ABS 1995a) undertook a larger study which, in addition to the variables reported in studies such as that of Hopkins and Kidd, found that health concession card status as well as several interaction terms — state of residence and income, state of residence and health concession card status, age and health concession card status, and income and health concession card status — were significant predictors of private health insurance. The ABS identified age and income as being strongly related to the likelihood of having private health insurance, while health status was found to be less significant.
This study adds to the earlier work on the determinants of private health insurance by providing an analysis of a considerable number of
determinants of private health insurance that have not previously been reported. These are measures of a broader range of health service usage and additional health risk factors, demographic variables and interaction terms. In addition, it identifies determinants specifically associated with various types of insurance. The importance of analysing the type of private health insurance purchased was identified by Hopkins and Kidd who observed: ‘It is possible that the determinants of the decision to purchase private health insurance varies across the type of policy’. However, Hopkins and Kidd were unable to distinguish between different types of private health insurance in their study because of the structure of their data.
2
Private health insurance in Australia
Since 1984, Medicare has provided universal public health insurance through which the cost of medical services and public hospital treatment is subsidised. Private health insurance is available in Australia as a
supplement to Medicare rather than as an alternative.
Although the introduction of Medicare has seen a rapid decline in the number of Australians with private health insurance — from 63.9 per cent in 1983 to 43.0 per cent in 1992 (ABS 1995a, p. 2) — private health insurance remains an important source of health funding, covering 39 per cent of all hospital admissions in 1991-92 (Private Insurance
Taskforce 1993, p. 1). In 1992-93, 12.2 per cent of all current health expenditure was financed from private health insurance contributions (Australian Institute of Health and Welfare 1995).
While there are many variations on the types of private health insurance (for example, cheaper policies for people who wish to limit their
insurance cover by excluding specific treatments such as hip replace-ments and policies that reduce the premium by charging an ‘excess’ when a claim is made), there are only three broad types of private health insurance — basic hospital insurance, supplementary hospital insurance and ancillary insurance.
Basic hospital insurance covers the full cost of shared ward accommo-dation as a private patient in a public hospital. It also covers part of the fee for private hospital accommodation and the 25 per cent gap between Medicare benefits and the schedule fee for medical services. Private patients with basic hospital insurance being treated in either a private or public hospital can choose their treating doctor.
Supplementary hospital insurance provides all the benefits of basic hospital cover plus higher benefits for private hospital accommodation and
covers additional private hospital costs (such as theatres, intensive care units and labour wards). Private health insurance companies are able to choose which additional services and benefits they offer with
Ancillary insurance contributes towards the cost of services not covered by Medicare such as dentistry, optical, chiropractic, podiatry, home nursing, speech therapy, physiotherapy, clinical psychology and home nursing. Ancillary insurance can be purchased with hospital insurance or separately.
Government regulations require that health insurance costs are governed by community rating, such that health funds must offer any of their
policy options at the same rate irrespective of factors that would be expected to influence health service use such as age, sex or health status (Willcox 1991, p. 12).
3
Methodology
3.1 The data source
The source of data used in this study is the 1989-90 national health survey conducted by the Australian Bureau of Statistics (ABS 1990). The NHS is a particularly useful data source for analysing the
determinants of private health insurance because of its comparatively large size (about 55 000 persons) and the large number of important socioeconomic, health insurance, health risk and health service usage variables it contains.
The NHS is available as a unit record dataset — that is, it provides a single record containing information about each respondent to the
survey. Each record has a weight attached, indicating how many similar Australians (of the same age, sex and state of residence) the record
represents.
The information in the survey was obtained from residents of private dwellings (houses, flats, etc.) and non-private dwellings (hotels, motels, caravan parks, etc.). Households were selected from all states and
territories. The only exclusions were non-Australian diplomatic personnel, members of non-Australian defence forces, persons holidaying in Australia, students at boarding schools and institutionalised persons (ABS 1993, p. 125).
3.2 Variables used in the analysis
The NHS provides more than four hundred variables describing the health insurance status, health status, health service use, health risk factors and socioeconomic and demographic characteristics of
respondents.
Most of the characteristics selected for the distributional analysis and models of the determinants of private health insurance were directly available as variables from the NHS. Some, however, had to be derived from other NHS variables. These are now described.
Family income
The definition of income provided in the NHS is annual gross income. Gross income includes regular income from any source including wages and earnings, investments, compensation payments and cash payments such social security payments.
However, the finances available to individuals to purchase private health insurance are generally determined by family1 rather than
individual income. Therefore, family rather than individual income was used in this study, with family income being defined as the sum of the income of both adults for couples with or without children.2
Health concession card
The definition of a health concession card that was adopted was based on whether an individual was covered by a Social Security health concession card and/or a Veteran’s Affairs health concession card. In accordance with the way health concession cards apply in practice, a
1 For the purposes of this study a family was defined as an income unit. An income
unit is defined by the ABS as ‘one person, or a group of related persons, within a household, whose command over income is shared’ (ABS 1995b, pp. 26–7) — that is, a single person, a couple (married or de facto) with or without dependent children, or a sole parent and dependent children. Family units differ from income units in that nondependent children (who are employed or on social security benefits, for example) form their own independent income unit.
2 Incomes in the NHS were in $5000 ranges. In calculating family income, the
health concession card reported by one member of the family in the survey was considered to cover all family members (that is, partner and dependent children).
Private health insurance
The analysis of private health insurance for this study was undertaken at the person level. However, in the NHS, family private health insurance was sometimes reported by only one or two family members (for
example, the two parents but not the children). In these cases, all members of the family were considered to be insured.
Occupation
The definition of occupation for this study was generally based on occupation as specified in the NHS. However, one of the occupation categories combined people in the armed forces, the unemployed, people out of the labour force and the group for whom an occupation was not applicable (children and the retired). Accordingly, analysis by
occupation for this category was combined with information on labour force status to separately identify the unemployed and those in the
armed forces and to exclude children and persons not in the labour force. Pharmaceuticals used
The use of pharmaceuticals was estimated from the total number of medications reported in the two weeks prior to interview for the NHS. Pharmaceuticals in the survey were categorised as vitamins, cough medicines, medication for allergies, skin treatments, laxatives, heart medication, sleeping tablets, pain killers, tranquillisers, and other medications. Use of more than one type of medication was, however, recorded only for vitamins, sleeping tablets, pain killers and
tranquillisers. Smoking
The incidence of smoking was based on whether respondents to the NHS smoked cigarettes, a pipe or a cigar at the time of the survey.
Alcohol consumption
The measure of alcohol consumption was based on the number of milli-litres of alcohol consumed in the week prior to the interview for the NHS.
Once these additional variables had been derived, the resulting data were used to undertake an analysis of the distribution of private health insurance (chapter 4) and an examination of the determinants of private health insurance (chapter 5).
4 Distribution of private health insurance
The distribution of private health insurance is examined to identify which Australians have private health insurance in the 1990s. The examination is in two parts. In the first part, the analysis considers the distribution of private health insurance by the three major insurance categories — hospital and ancillary insurance, hospital-only insurance and ancillary-only insurance. It was considered important to separate people with only one type of insurance from those with the more comprehensive hospital and ancillary insurance as it was anticipated that the incidence of the more comprehensive cover would be associated with higher income. In addition, the purchase of only one type of
insurance was seen as a potentially useful indicator of the perceived need for the services covered by the insurance type. The results of this analysis were later also used to suggest which characteristics might be significant determinants of private health insurance.
The second part focuses specifically on the distribution of the choice to insure only a single family member within families of two or more
persons. It is important to focus on this subpopulation to determine how the insured family member differs from the uninsured family members, and how families who choose to insure only one member differ from other families where the whole family is either insured or uninsured.
4.1 Distribution of private health insurance by type of private health insurance
Private health insurance by income
Analysis of private health insurance type by income found that the proportion of individuals without private health insurance decreased as incomes increased. About 76 per cent of people from families with
incomes of $10 000 to $19 999 a year were uninsured compared with 16 per cent of people from families with incomes of $70 000 or more a year (table 1).3 These findings are similar to those reported by other
research-ers (ABS 1995a; Cameron and Trivedi 1991; Hopkins and Kidd 1993). The probability of individuals reporting the top level of health insurance cover — that is, insurance for both hospital and ancillary services — also increased with income. Individuals from high income families were three times as likely to have hospital and ancillary insurance as those with the lowest incomes. The proportions of families with hospital-only or ancillary-only insurance showed less variation with income (12 per
3 Incomes are for 1989-90. The lowest income range presents some difficulties for
interpreting health insurance trends as it is composed of both low income earners as well as families whose principal income source is a private business. Private business income for a family might have been zero or negative in the reported financial year yet the business may have performed well in other years and allowed the accumulation of assets.
Table 1 Individuals by type of private health insurance and by family
income, Australia, 1989-90
Family income Uninsured Ancillary-only Hospital-only Hospital and ancillary Total % % % % % $0–9999 64.8 2.1 9.4 23.7 100.0 $10 000–19 999 76.2 2.9 9.0 21.0 100.0 $20 000–29 999 53.7 3.9 8.0 34.5 100.0 $30 000–39 999 40.8 4.5 9.0 45.6 100.0 $40 000–49 999 32.9 5.3 9.6 52.2 100.0 $50 000–59 999 27.7 4.1 9.3 58.9 100.0 $60 000–69 999 21.6 4.0 9.3 65.1 100.0 $70 000 or more 16.3 1.7 10.9 71.2 100.0 Source: ABS (1990).
cent of families with incomes of less than $10 000 a year and 13 per cent with incomes of more than $70 000).
However, when only individuals with private health insurance are con-sidered (table 2), about 27 per cent of insured individuals with family incomes of less than $20 000 a year had hospital-only insurance, com-pared with about 13 per cent for individuals with family incomes of more than $50 000 a year. This finding indicates that insured individuals with low family incomes more often choose cheaper health insurance. Table 2 Insured individuals with
hospital-only private health insurance, by family income, Australia, 1989-90
Family income Hospital-only
% $0–9999 26.7 $10 000–19 999 27.4 $20 000–29 999 17.2 $30 000–39 999 15.2 $40 000–49 999 14.3 $50 000–59 999 12.9 $60 000–69 999 11.9 $70 000 or more 12.7 Source: ABS (1990).
Measures that are closely related to income produce similar results. For example, when an analysis is undertaken by equivalent family income4
individuals with the highest equivalent family incomes were substan-tially more likely to be insured than those on lower incomes. The major difference was that, after adjusting for income, about 90 per cent of families in the income group with the lowest rate of insurance (that is, families in the second decile of equivalent income) were reported as uninsured. By contrast, when non-equivalent income measures had been used, about 75 per cent of the income group with the lowest rate of
insurance were reported as uninsured (table 1).
4 The equivalent income measure in the NHS ranked family income by deciles after
adjusting family income to account for the size of the family. Equivalent income was defined on the basis of Henderson simplified equivalence scales (Mathers 1994).
Similarly, an analysis by access to the benefits of a health concession card indicated that about 70 per cent of card holders, who have low incomes, were uninsured, compared with 40 per cent of people who did not have health concession cards.
When the source of income was considered, individuals whose main source of income was a pension or benefit reported the lowest incidence of private health insurance (65 per cent uninsured) (table 3). (This
outcome is to be expected as this group also had the lowest average income.) Notably, people who derived their income primarily from their own business reported a higher incidence of private health insurance than those whose main income source was wages and salaries. People who have their own business may regard a health crisis as posing a greater financial risk since they may not only face considerable health care costs, but are also likely to lose income for the period they are unable to work.
Individuals whose primary income source was superannuation or investments reported the highest incidence of private health insurance, with almost 70 per cent of this group insured. (This group also reported the highest proportion of individuals choosing hospital-only insurance.) This is an important finding as about 75 per cent of people with super-annuation as their main source of income were aged 60 years or more. As a result, with an increasing number of the aged relying on super-annuation rather than the age pension as their main income source over
Table 3 Individuals by type of private health insurance and by main
source of family income, Australia, 1989-90
Main source of family income
Uninsured Ancillary-only Hospital-only Hospital and ancillary
Total
% % % % %
Pension or benefit 65.3 3.0 8.3 23.5 100.0
Wages and salaries 45.6 3.9 7.8 42.8 100.0
Own business 38.7 3.4 10.1 47.9 100.0
Superannuation 32.5 2.9 15.9 48.8 100.0
Investment 31.5 3.3 14.5 50.7 100.0
the next 20–30 years, it might be expected that health insurance coverage among the aged will increase.
The incidence of private health insurance was also found to vary considerably with occupation and labour force status. This is to be expected as average income is closely related to occupation.
Professionals and managers reported the highest incidence of private health insurance (73 per cent and 71 per cent respectively) declining to less than 50 per cent for trades people and labourers (table 4). The lowest incidence of private health insurance was among the unemployed, with only 27 per cent of this group insured. This finding would suggest that the rapid growth in the ranks of the unemployed in the past decade — with the number of recipients of unemployment benefits rising from about 373 000 in 1982 to a peak of approximately 890 000 in 1993 (Department of Social Security 1993) — might well have had a major impact on the decline in the total number of Australians with private health insurance. It is also possible that if the longer term unemployed find that Medicare provides adequate health care they may be less
inclined to take up private health insurance when they are re-employed. Table 4 Working age adults by type of private health insurance and by
occupation and labour force status, Australia, 1989-90
Occupation and labour force status
Uninsured Ancillary-only Hospital-only Hospital and ancillary Total % % % % % In paid employment Professional 27.0 3.8 10.3 58.9 100.0 Manager 28.5 3.3 11.3 56.8 100.0 Paraprofessional 32.0 5.4 10.2 52.4 100.0 Armed services 33.4 1.3 0.0 65.3 100.0 Clerical 34.5 4.5 8.2 52.8 100.0 Sales 44.7 4.2 7.3 43.8 100.0 Plant operator/driver 50.5 3.4 7.3 38.9 100.0 Trades 50.8 4.3 7.6 37.4 100.0 Labourer 58.4 3.8 6.4 31.4 100.0
Not in paid employment
Out of the labour force 50.8 3.0 9.2 36.9 100.0
Unemployed 73.3 2.7 3.9 20.1 100.0
Private health insurance by family type
Individuals from a family consisting of a couple with children reported the highest incidence of private health insurance — 61 per cent (table 5). Individuals from sole parent families reported the lowest incidence of private health insurance — 24 per cent. These findings are similar to those reported by the ABS (1995a). The low incidence of private health insurance among sole parent families compared with couples with children is probably determined, at least in part, by the difference in average incomes between the two family types.
However, even accounting for income, there was still a considerable difference in the incidence of private health insurance between the two family types. For example, for families with incomes under $20 000 a year, about 60 per cent of individuals from couple with children families reported being insured, compared with only about 20 per cent of
individuals from sole parent families.
Single people reported an incidence of private health insurance (38 per cent) that was substantially lower than for couple families with or without children. However, their incidence of insurance was still substantially higher than that of individuals from sole parent families. Interestingly, while couples without children reported an incidence of insurance similar to couples with children (60 per cent and 61 per cent respectively), they reported a higher incidence of hospital-only insurance (13 per cent compared with 8 per cent of couples with children).
Table 5 Individuals by type of private health insurance and by family
type, Australia, 1989-90
Family type Uninsured Ancillary-only Hospital-only Hospital and ancillary
Total
% % % % %
Couple with children 38.6 4.5 8.5 48.5 100.0
Couple without children 40.1 2.7 13.4 43.7 100.0
Sole parent 75.5 4.0 3.3 17.2 100.0
Single 62.1 2.8 7.5 27.6 100.0
Private health insurance by age
The age distribution of private health insurance has become a key area of interest, as the ageing of the population and a reduction in the number of younger people with private health insurance have resulted in an
increasing pool of insured who are 60 years of age or over — increasing from 13 per cent in 1983 to 22 per cent in 1990 (Willcox 1991).
Despite concerns about the growing pool of elderly insured, it is still the group aged 35–59 years who report the highest incidence of private health insurance — about 60 per cent insured (table 6). In fact, it was the age group of 80 years and over who reported the lowest incidence of private health insurance — 38 per cent insured.
An examination of the distribution of private health insurance by age revealed some interesting results. About 55 per cent of children aged 0– 14 years were covered by health insurance. People aged 15–29 years, by contrast, had the second lowest incidence of private health insurance, with 40 per cent of 20–24 year olds reported as insured. The incidence of Table 6 Individuals by type of private health insurance and by age,
Australia, 1989-90
Age Uninsured Ancillary-only Hospital-only Hospital and ancillary Total years % % % % % 0–4 45.4 4.3 9.5 40.8 100.0 5–9 46.5 4.7 7.4 41.5 100.0 10–14 44.8 4.6 5.3 45.3 100.0 15–19 51.3 3.6 6.6 38.5 100.0 20–24 59.3 3.5 5.2 32.0 100.0 25–29 52.1 4.5 6.6 36.8 100.0 30–34 44.2 4.3 8.4 43.2 100.0 35–39 41.7 4.4 7.5 46.4 100.0 40–44 37.9 4.0 9.0 49.1 100.0 45–49 37.3 3.4 9.0 50.3 100.0 50–54 37.0 2.8 11.6 48.6 100.0 55–59 41.1 2.8 11.4 44.8 100.0 60–64 44.2 2.4 13.7 39.7 100.0 65–69 53.4 1.5 16.0 29.1 100.0 70–74 55.2 1.1 18.1 25.4 100.0 75–79 50.0 0.8 17.1 23.1 100.0 80 or more 62.3 1.0 17.3 19.5 100.0 Source: ABS (1990).
private health insurance then increased with age, to a high of 63 per cent for 50–54 year olds. From this age onwards, the incidence of private health insurance declined to a low of 38 per cent for people aged 80 or more years.
The elderly reported the highest incidence of hospital-only insurance (about 17 per cent for people aged 65 years and over), around double the incidence for people aged 25–44 years (about 8 per cent).
An analysis by family type and age established that sole parents aged 25–34 years were the most likely to be uninsured (over 80 per cent) (table 7). By contrast, couples with or without children aged 30–60 years were the least likely to be uninsured (about 35 per cent). Of both singles and couples without children, the youngest and oldest age groups were the most likely to be uninsured (78 per cent of 15–19 year olds in couples without children and 66 per cent of single persons aged 80 years and over).
Table 7 Individuals without private health insurance, by age and by
family type, Australia, 1989-90
Age Couples with
children
Couples without children
Sole parent Single persons
years % % % % 15–19 33.5 77.9 66.6 66.2 20–24 59.1 44.8 76.1 62.0 25–29 48.0 37.1 85.2 62.7 30–34 38.6 33.1 81.8 60.2 35–39 36.4 36.6 74.3 59.6 40–44 32.8 32.9 68.4 56.4 45–49 31.2 34.7 56.4 57.3 50–54 31.2 32.7 54.3 56.2 55–59 38.6 35.6 – 58.9 60–64 41.4 39.0 – 56.6 65–69 – 47.4 – 65.4 70–74 – 49.6 – 62.8 75–79 – 54.7 – 63.6 80 or more – 55.4 – 66.0
– Fewer than 5000 persons. Source: ABS (1990).
Private health insurance by use of health services
Individuals with hospital-only insurance or hospital and ancillary insurance had only a slightly higher probability of being admitted to hospital in the previous year than individuals without hospital
insurance, while the uninsured had a higher probability of visiting a general practitioner than the insured (table 8). (Hopkins and Kidd (1993) explained similar findings by suggesting that the difference lies in
hospital use being covered by private health insurance while doctor visits outside hospitals were covered by Medicare and, as a result, doctor visits and private health insurance status were not subject to the same moral hazard.) By contrast individuals with hospital-only or hospital and ancillary insurance were about twice as likely to have seen a specialist as the uninsured were, raising the possibility that the
uninsured may rely more on general practitioners for treatment while the insured are more often treated by specialists.
Individuals with ancillary-only or hospital and ancillary insurance had a higher incidence of optician, chiropractic and physiotherapy treatment than individuals without ancillary insurance. This might suggest that individuals with ancillary insurance have insured against a perceived higher need of ancillary services and/or that private health insurance improves access to ancillary services.
Dental visits in the three months prior to the survey were reported more frequently by individuals with ancillary insurance (22 per cent of those
Table 8 Individuals who used selected health services, by type of private
health insurance, Australia, 1989-90
Health service Uninsured Ancillary-only Hospital-only Hospital and ancillary
% % % %
Hospital (past 12 months) 13.4 11.6 14.8 14.0
General practitioner (past 2 weeks) 18.7 15.7 17.9 15.6
Specialist (past 2 weeks) 2.0 1.5 3.8 3.6
Optician (past 2 weeks) 1.4 2.3 1.4 1.9
Chiropractor (past 2 weeks) 0.7 2.3 1.1 1.2
Physiotherapist (past 2 weeks) 1.2 1.4 1.2 1.6
with ancillary-only and 20 per cent of those with hospital and ancillary) than by individuals without ancillary insurance (14 per cent of those with hospital-only and 12 per cent of the uninsured) (table 9). By con-trast, individuals without ancillary insurance reported about double the incidence of not having visited a dentist for more than two years (41 per cent of the uninsured compared with 20 per cent of those with ancillary-only insurance).
Table 9 Individuals by type of private health insurance and by period
since the most recent dental visit, Australia, 1989-90
Most recent dental visit Uninsured Ancillary-only Hospital-only Hospital and ancillary
% % % %
Less than 3 months 12.2 22.3 14.4 19.6
3–6 months 9.3 16.4 10.8 14.7
6 months to 2 years 29.1 34.5 31.4 34.6
More than 2 years 40.6 19.8 36.0 24.1
Note: Rows do not add to 100 per cent as the NHS categories NA and never visited were excluded (about 5 per cent of total responses).
Source: ABS (1990).
While there were substantial differences in the use of a number of health services by the insured relative to the uninsured, it is also of interest to know whether the use of health services and the health status of the insured also varied with income. In particular, it is important to deter-mine whether the use of hospital services varied with income for the insured as these are the most costly services for private health insurance companies to cover.
Analysis of hospital admittance in the twelve months prior to the survey (by income) suggested that persons from low income families with
private health insurance had a higher rate of hospital admittance than individuals from high income families. About 18 per cent of individuals from families with incomes of $10 000 to $19 999 a year and hospital insurance reported being admitted to hospital in the previous year (table 10) while about 11 per cent of individuals from families with annual incomes of $70 000 or more reported an admittance. The difference could be a result of people on low incomes insuring against a perceived need for hospital services or it could be a result of people on lower incomes generally having poorer health.
Table 10 Individuals with private hospital
insurance admitted to hospital in the 12 months prior to the survey, by income, Australia, 1989-90
Family income Hospital-only or
hospital and ancillary insurance % $0–9999 16.3 $10 000–19 999 18.3 $20 000–29 999 15.3 $30 000–39 999 14.3 $40 000–49 999 12.9 $50 000–59 999 11.8 $60 000–69 999 13.3 $70 000 or more 10.7 Source: ABS (1990).
Similarly, the difference between the number of chronic conditions reported by individuals without hospital insurance and those with insurance was greater for individuals from low income families than for those from high income families. The difference was 0.8 for those with family incomes of $10 000 to $19 000 but 0.3 for those with family incomes of $70 000 or more (table 11).
Table 11 Average number of chronic conditions
reported by individuals with private hospital-only insurance, by income, Australia, 1989-90
Family income Hospital-only (A)
Uninsured (B)
Difference (A-B)
no. no. no.
$0–9999 2.1 2.0 0.2 $10 000–19 999 2.5 1.7 0.8 $20 000–29 999 1.7 1.2 0.5 $30 000–39 999 1.3 1.0 0.3 $40 000–49 999 1.2 1.1 0.2 $50 000–59 999 1.2 1.1 0.1 $60 000–69 999 1.2 1.1 0.1 $70 000 or more 1.4 1.1 0.3 Source: ABS (1990).
Private health insurance by health status indicators
There have been a number of studies that have considered the relation-ship between health status and private health insurance. Authors relying on the 1983 national health survey reported that health status played only a small role in the decision to insure (Cameron et al. 1988; Cameron and Trivedi 1991). However, using the 1989-90 national health survey, the ABS identified that income units with the best self-reported health status were the most likely to have private health insurance (ABS 1994). This result was said to be confounded by income that was positively correlated with health status. However, when the number of chronic illnesses were used as a measure of health status, the incidence of private health insurance for income units was highest for income units with the most chronic conditions (ABS 1995a).
These apparently contradictory findings reported by the ABS were further explored in this study by analysing the relationship between health status and income. Two measures of health status were used — self-reported health status and number of chronic conditions.
An analysis of private health insurance holders by their self-reported health status indicated that, of the poorest families, those with the poorest health were the most likely to be uninsured (table 12). For
example, in families with incomes of less that $10 000 a year, 78 per cent of people in poor health were uninsured, compared with only 58 per cent who reported being in excellent health. By contrast, in the
wealthiest families, those with the best health were the most likely to be Table 12 Individuals without private health insurance, by income and
self-reported health status, Australia, 1989-90
Family income Excellent health Poor health
% % $0–9999 57.6 77.5 $10 000–19 999 62.5 72.9 $20 000–29 999 50.2 47.4 $30 000–39 999 38.6 41.0 $40 000–49 999 30.2 29.3 $50 000–59 999 26.3 27.3 $60 000–69 999 20.9 13.9 $70 000 or more 15.4 7.2
uninsured. It was found that, of families with incomes of more than $70 000 a year, 7 per cent of individuals who reported poor health were uninsured, compared with 15 per cent of those reporting excellent
health. This may be due, at least in part, to a clustering of the aged in the lowest income groups since the aged were found to have a relatively low incidence of private health insurance (section 4.1).
It was also notable that individuals with poor health and in families with the lowest incomes were much less likely to have private health
insurance than were individuals with poor health and in families with the highest incomes (78 per cent with family incomes of less than $10 000 a year were uninsured compared with only 7 per cent with family
incomes of more than $70 000 a year).
However, some of the patterns seen in the analysis using self-reported health status were reversed when the number of chronic conditions reported were used as the measure of individual health status.
The analysis indicated that, in the poorest families, individuals with the poorest health were more likely to be insured (table 13). For example, of people with family incomes of $10 000 to $19 999 a year, 65 per cent who had one or more chronic conditions were uninsured, compared with 74 per cent with no chronic conditions. Similarly, in the wealthiest families, those with the poorest health were more likely to be insured. For individ-uals with family incomes of more than $70 000 a year, 14 per cent with one or more chronic conditions were uninsured, compared with 20 per cent with no chronic conditions.
Table 13 Individuals without private hospital insurance, by income and
number of chronic illnesses, Australia, 1989-90
Family income None One or more
% % $0–9999 66.4 64.2 $10 000–19 999 73.5 64.7 $20 000–29 999 61.1 49.4 $30 000–39 999 45.8 37.6 $40 000–49 999 35.1 31.5 $50 000–59 999 30.7 26.0 $60 000–69 999 25.0 19.7 $70 000 or more 20.5 14.3 Source: ABS (1990).
The finding that people reporting one or more chronic conditions are more likely to be insured than those with none, regardless of whether their incomes are low or high, seems to be inconsistent with the previous finding that people reporting poor health and on low family incomes are less likely to be insured than those on low family incomes who report excellent health. This may be a result of the inclusion of conditions such as hay fever that might not be associated with serious illness in the definition of chronic illness in the NHS.
Despite this contradictory finding there was, however, one consistent element in the pattern. Regardless of the measure of individual health status used, individuals with poorer health and on the lowest incomes were much less likely to have private health insurance than individuals with poorer health and on the highest incomes. When the number of chronic conditions was used as the health status measure, 64 per cent of individuals with family incomes of less than $10 000 a year were un-insured, compared with only 14 per cent of individuals with family incomes of more than $70 000 a year (table 13).
Private health insurance by selected health risk factors
The relationship between three important indicators of disease, disability and death were considered — smoking, alcohol consumption and body weight (ABS 1992, p. 79; 1994, p. 60).
It was found that a higher proportion of the uninsured reported that they smoked than did individuals with private health insurance — 35 per cent compared with around 20 per cent (table 14). Hopkins and Kidd (1993) interpreted a similar finding as evidence that smoking can be considered a measure of risk aversion, and that smokers being less risk
Table 14 Individuals by type of private health insurance, by selected
health risk factors, Australia, 1989/90
Unit Uninsured Ancillary-only Hospital-only Hospital and ancillary
Smoker % 35.2 28.2 17.6 21.8
Body weight indexa mean 2.3 2.2 2.3 2.3
Alcohol consumption mean mL 109.3 100.9 86.3 104.8
averse are individuals who are also less likely to purchase health insurance.
The uninsured also reported higher average alcohol consumption than did the insured.
However, a comparison of a body weight index indicated no measurable difference in body weight between the uninsured and insured (table 14). Private health insurance by ethnicity
The relationship between ethnicity and private health insurance was examined by looking at the language spoken at home, the country of birth and the year of migration.
On average, individuals who spoke a language other than English at home reported a lower incidence of private health insurance than did those who spoke English only — 38 per cent insured compared with 55 per cent insured (table 15). This result is consistent with findings based on the 1983 national health survey reported by Ngui et al. (1989).
Table 15 Individuals by type of private health insurance and by language
spoken at home, Australia, 1989-90
Uninsured Ancillary-only Hospital-only Hospital and ancillary Total % % % % % Language other than English 62.1 3.1 7.5 27.3 100.0 English only 45.4 3.7 9.3 41.7 100.0 Source: ABS (1990).
Although individuals who spoke a language other than English at home reported a lower average incidence of private health insurance, an
analysis by country of birth revealed that immigrants from southern Asia reported a higher incidence of private health insurance than individuals born in Australia — 58 per cent insured compared with 56 per cent insured (table 16). Immigrants from New Zealand and Greece reported the lowest incidence of private health insurance (33 per cent and 31 per cent respectively).
Immigrants from Greece and Italy reported the highest proportion of insured individuals holding hospital-only insurance (30 per cent and 26 per cent respectively), compared with only 17 per cent of Australian-born individuals with private health insurance.
The analysis also revealed that there was an observable relationship between the purchase of private health insurance and the period of time immigrants had lived in Australia. The most recently arrived immi-grants, those who had arrived between 1985 and 1990, were the least likely to have private health insurance — over 70 per cent of this group were uninsured (table 17). The number of uninsured declined to 50 per cent for immigrants who had lived in Australia for at least 10 years. Table 16 Individuals by type of private health insurance and by country
of birth, Australia, 1989-90
Uninsured Ancillary-only Hospital-only Hospital and ancillary Total % % % % % Southern Asia 42.3 3.6 5.2 48.9 100.0 Australia 44.3 3.5 9.7 42.5 100.0 Western Europe 45.8 3.9 8.5 41.8 100.0 Italy 46.8 1.1 14.0 37.9 100.0 UK or Ireland 52.2 5.3 7.4 35.1 100.0 Other Europe 55.9 4.8 6.6 32.7 100.0 Southern Europe 58.4 2.9 8.4 30.3 100.0 Middle East 62.7 2.6 5.3 29.4 100.0 South-East Asia 62.9 5.2 4.0 27.9 100.0 New Zealand 66.5 3.0 3.8 26.6 100.0 Greece 68.5 2.7 9.6 19.2 100.0
Note: 'Other' countries were excluded (about 2.5 per cent of total responses). Source: ABS (1990).
Table 17 Individuals by type of private health insurance and by year of
migration, Australia, 1989-90
Uninsured Ancillary-only Hospital-only Hospital and ancillary Total % % % % % Australian-born 44.33 3.52 9.65 42.50 100.0 Before 1980 50.22 3.65 9.03 37.10 100.0 1980–84 60.31 6.49 3.10 30.11 100.0 1985–90 71.46 3.45 3.19 21.90 100.0
However, even immigrants who had been in Australia for 10 years or more, on average, were about 6 per cent less likely to have private health insurance than Australian-born individuals.
Private health insurance by health region
Analysis of private health insurance by health region indicated a sub-stantial difference in the proportion of individuals insured by region with about 25 per cent fewer individuals insured in the region reporting the lowest incidence of private health insurance than in the region
reporting the highest. (Health regions are the geographic areas defined for the purpose of administering area health services and were con-sidered to be a proxy for perceived access to and adequacy of free public health care.)
Individuals residing in the health region of North Sydney reported the highest incidence of private health insurance (70 per cent) followed by the metropolitan regions of Adelaide, Perth, Tasmania and Melbourne (table 18). The regions with the lowest rate of private health insurance were Brisbane South (34 per cent) followed by the Sunshine Coast Queensland, South Coast Queensland, West Morton Queensland and North Coast NSW. This finding is best explained by a tradition of free public hospital care in Queensland.
Melbourne health regions reported a high proportion of hospital-only insurance among the insured, with West Metropolitan Melbourne reporting the highest at 36 per cent (compared with 15 per cent for the region of North Sydney).
An analysis of the distribution of private health insurance in
metro-politan and nonmetrometro-politan areas was undertaken by defining residents of capital cities as being metropolitan residents and the remainder of Australians as nonmetropolitan residents. On average, residents of metropolitan areas reported a higher incidence of private health
in-surance than residents of nonmetropolitan areas — 55 per cent compared with 50 per cent (table 19). As indicated in table 18, the six health regions with the highest incidence of private health insurance were all
metropolitan areas. However, the metropolitan areas of Queensland differ from this general pattern, in that they appear among the regions with a lower incidence of private health insurance, South Brisbane being the health region with the lowest incidence of private health insurance.
Table 18 Individuals by type of private health insurance and by health
region, Australia, 1989-90
Uninsured Ancillary-only Hospital-only Hospital and ancillary
Total
% % % % %
North Sydney 30.2 1.7 10.2 57.9 100.0
South Metropolitan Adelaide 30.7 8.1 4.0 57.3 100.0
East Metropolitan Adelaide 32.9 6.9 2.7 57.6 100.0
North Metropolitan Perth 34.3 7.5 4.8 53.4 100.0
Metropolitan Tasmania 35.9 2.1 3.7 58.3 100.0
North East Melbourne 38.0 1.8 18.7 41.6 100.0
Central Highlands NSW 38.1 3.1 17.2 41.7 100.0
Hunter NSW 38.6 3.2 5.6 52.6 100.0
East country SA 39.5 12.6 2.3 45.6 100.0
Barwon – South West Victoria 41.0 3.7 8.9 46.5 100.0
Southern Sydney 41.4 2.0 12.3 44.4 100.0
WA country regions 41.4 8.2 2.4 48.1 100.0
Loddon – Mallee Vic. 42.9 0.3 16.6 40.4 100.0
South Metropolitan Perth 43.7 6.8 3.8 45.8 100.0
North Metropolitan Adelaide 44.3 7.2 2.4 46.2 100.0
South West NSW 44.5 2.9 10.6 42.1 100.0
West Metropolitan Adelaide 44.5 7.2 4.7 43.6 100.0
New England NSW 44.6 1.4 9.6 44.4 100.0
ACT 45.2 2.5 12.5 40.0 100.0
Illawarra NSW 45.2 2.9 5.9 46.1 100.0
Eastern Sydney 45.2 4.5 5.9 44.4 100.0
West Country SA 45.6 11.6 3.8 38.8 100.0
South East Melbourne 46.3 1.8 14.8 37.1 100.0
Western Sydney 47.2 3.2 7.9 41.8 100.0
Orana – Far West NSW 47.6 1.5 10.7 40.3 100.0
East Metropolitan Perth 47.8 3.8 1.9 46.5 100.0
Tas. nonmetropolitan 47.9 6.4 3.9 41.8 100.0
NT 48.1 3.8 1.1 47.1 100.0
Central Coast NSW 49.2 3.2 15.7 31.9 100.0
Wentworth NSW 49.8 3.2 7.9 41.8 100.0
Gippsland Victoria 50.5 3.1 9.7 36.7 100.0
West Metropolitan Perth 50.6 6.4 1.3 41.8 100.0
South West Sydney 51.0 2.5 8.3 38.2 100.0
Central Qld 51.2 2.8 5.2 40.8 100.0
West Metropolitan Melbourne 52.0 2.3 17.2 28.5 100.0
Brisbane North 52.1 4.9 8.9 34.1 100.0
Goulburn – North East Vic. 52.3 4.3 8.0 35.4 100.0
South West Qld 52.5 0.8 13.3 33.7 100.0 Peninsula – North Qld 53.5 2.6 10.5 33.4 100.0 South Eastern NSW 54.5 0.9 9.9 34.7 100.0 Central Sydney 54.7 4.3 7.8 33.2 100.0 Central West NSW 57.3 1.8 7.5 33.4 100.0 North Coast NSW 61.4 2.0 7.0 29.6 100.0 West Morton Qld 62.7 2.6 8.2 26.4 100.0 South Coast Qld 63.2 3.6 7.0 26.2 100.0 Sunshine Coast Qld 65.0 5.4 6.6 23.0 100.0 Brisbane South 65.9 4.3 3.9 25.9 100.0 Source: ABS (1990).
Table 19 Individuals by type of private health insurance and by type of
health region, Australia, 1989-90
Uninsured Ancillary-only Hospital-only Hospital and ancillary
Total
% % % % %
Metropolitan 44.9 3.5 10.0 41.7 100.0
Nonmetropolitan 49.5 3.7 7.9 38.8 100.0
Note: The Northern Territory was defined as nonmetropolitan while the ACT was defined as metropolitan. Source: ABS (1990).
4.2 Distribution of single rate private health insurance among families
This section presents findings on the characteristics of families of two or more people who choose to purchase private health insurance for only one of the family members.
Single person private health insurance by family type
Most of the individuals living in a family with single rate insurance were in couple families without children — 82 per cent (table 20). Of this
family type, 85 per cent of adult females held the single rate private health insurance compared with only 15 per cent of the adult male
partners. In couples with children that held single rate health insurance, there was an approximately equal split between the number of adult males and adult females insured, with the child being the single insured family member only about 9 per cent of the time. Similarly, in sole parent Table 20 Single person private health insurance among families, by
family type and person type, Australia, 1989-90
Unit Female adult Male adult Child
Couple with children % 44.5 46.9 8.6
no. 6 000 6 000 1 000
Couple without children % 84.6 15.4 0
no. 108 000 20 000 0
Sole parent % 91.4 1.8 6.8
no. 15 000 0 1 000
families, the adult female was usually the single family member with private health insurance (91 per cent), with children representing only 7 per cent of the holders of single rate private health insurance for this family type.
Where the adult female was the single insured family member, there was a much higher rate of hospital-only insurance than among families with all family members insured — 36 per cent compared with 17 per cent (table 21). It would seem that couples chose to insure only the adult female where her risk of hospitalisation was relatively high, as these females had almost double the incidence of hospitalisation in the 12 months prior to the survey that all other persons with private health insurance had — 24 per cent compared with 14 per cent.
The insurance of adult females with children may well be a result of families taking out private health insurance prior to the birth of a child, as about 85 per cent of these women were between 20 and 44 years of age. However, for couples without children, about 50 per cent of the women with single rate insurance were 60 years or older, suggesting that other health reasons may also be important in explaining adult female single rate insurance within families.
Table 21 Private health insurance type of persons in families where only
the adult female is insured and of persons in families where all members are insured, Australia, 1989-90
Ancillary-only Hospital-only Hospital and ancillary
Total
% % % %
Adult female only insured 11.2 36.4 52.3 100.0
All family members insured 6.8 17.1 76.1 100.0
Source: ABS (1990).
Insuring only the adult female within a family seems to be an option most often taken by low income families. Over 50 per cent of women with single rate health insurance reported a family income below $30 000 a year (table 22). Insuring the adult female in a family was most fre-quently reported in the family income range of $10 000 to $19 999 a year. At 34 per cent the incidence was more than four times the incidence of single rate insurance reported for women from families with an income of $70 000 or more (8 per cent).
Table 22 Women in families who have single
rate private health insurance, by income, Australia, 1989-90
Single rate insurance % $0–9999 5.7 $10 000–19 999 33.8 $20 000–29 999 13.9 $30 000–39 999 9.8 $40 000–49 999 13.9 $50 000–59 999 8.4 $60 000–69 999 6.7 $70 000 or more 7.8 Total 100.0 Source: ABS (1990).
Single person private health insurance by health service use
Where a family insured only a single family member, the reported use of medical services was, on average, higher for the insured person than for the uninsured family members (table 23). The incidence of hospitalis-ation was about 50 per cent higher for the insured family member than for the uninsured family members (22 per cent compared with 15 per cent). The difference in the incidence of general practitioner attendance was much lower than for hospital admittance as the incidence for the insured family member was 21 per cent while for the uninsured family members it was 20 per cent.
Table 23 Use of health services by single rate
insured family members and uninsured family members, Australia, 1989-90
Uninsured Insured
% %
Hospital (past 12 months) 14.8 22.0
General practitioner 19.7 21.1
Specialist 1.3 7.0
Optician 1.9 4.2
Physiotherapist 0.7 1.4
There was a substantial difference in the incidence of specialist attend-ance, being 7.0 per cent for the insured family member and only 1.3 per cent for uninsured family members. The insured family member was also about twice as likely to have visited an optician or physiotherapist as the uninsured family members were.
5
Determinants of private health insurance
5.1 Multivariate models of private health insuranceIn this part of the analysis the findings of the distributional analysis are used to test possible determinants of private health insurance within three multivariate regression models.
A binomial logit model was developed to identify the significant
determinants of private health insurance (any of the three types of health insurance coverage considered in this study). A second was used to identify the determinants associated with insurance for hospital services only, and a third to identify the determinants of insurance for ancillary services only. Each of these three models compared the insured sub-population with the uninsured subsub-population. Logit models are appropriate for deriving econometric estimates to predict who has private health insurance as they simulate a binary choice, such as whether to buy private health insurance or not. Logit models allow an examination of the effect of each variable while controlling for each of the other variables. Although such models are commonly used to identify ‘determinants’ of private health insurance, like all regression models, logit models can identify an association between variables but not causality (Hair et al. 1992, pp. 60–2).
In deriving an econometric model of private health insurance the
researcher must decide at what level to develop the model (for individ-uals or groups of individindivid-uals). A number of similar studies have
reported modelling the determinants of private health insurance at a variety of levels. Some were at the level of the health insurance con-tributor unit (approximately the same as a family) (ABS 1995a), while others undertook the analysis at the person level (Burrows et al. 1993; Cameron et al. 1988; Cameron and Trivedi 1991; Hopkins and Kidd 1993). Surprisingly, it has not been customary to undertake analysis at
the person level for the entire population. For example, Hopkins and Kidd included only the head and the spouse of each family, while Cameron et al. and Cameron and Trivedi included only single persons over the age of 18 years. The reason given for excluding much of the population in these analyses has been that the data structure of the surveys used (typically the national health surveys) has not facilitated linking information on members within each family (Cameron et al. 1988) or that health insurance information has not been stored consist-ently across all persons within each family (Hopkins and Kidd 1993). In this study these data constraints were overcome (as described in section 3.2), allowing the analysis to be undertaken at the person level for all Australians rather than for a particular subpopulation.
As noted, this study also extends the analysis of previous authors who reported the determinants of private health insurance (since the
introduction of Medicare) by including a number of additional variables in the econometric estimates that seemed to be important in the cross-sectional analysis in chapter 4.
Previous studies included a wide range of demographic variables — age (ABS 1995a; Burrows et al. 1993), family type or marital status and
presence of dependent children (ABS 1995a; Hopkins and Kidd 1993), state of residence sometimes with an indicator of metropolitan or non-metropolitan (ABS 1995a; Hopkins and Kidd 1993), gender (Hopkins and Kidd 1993) and education (Hopkins and Kidd 1993). Of these, increasing age, being a family with children and having a higher level of education were considered to be positive indicators of private health insurance as they were related to a higher need for services, based on earlier studies and the cross-sectional analysis in chapter 4 of this study. Gender and location of residence seemed to have a lesser effect, although women were slightly more likely to be covered by private health insurance than were men, and people in metropolitan areas were also slightly more likely to be covered than were those in nonmetropolitan areas.
In this study three measures of ethnicity that were likely determinants of private health insurance in the distributional analysis were also
included. These were country of birth, year of arrival and language spoken at home. These were seen as possibly limiting the access of
individuals to services, particularly for recent arrivals who did not speak English, thereby reducing the probability of these people purchasing
private health insurance. In addition, a more detailed measure of location of residence was added — region of residence5 — which may
reflect perceived availability and adequacy of public and private hospital care. These variables were selected because they have been found to affect both health status and the use of health services (Mathers 1994). Economic variables such as income and eligibility for a health concession card were also included in most previously reported models of private health insurance. The ABS (1995a) cited income as the most significant determinant of private health insurance. In addition to these economic variables two other potentially important economic determinants of private health insurance were added — main source of income and occupation. It was considered that apart from income, being a member of occupations requiring higher education might be a positive indicator of private health insurance coverage, while receiving income mainly from a pension or benefit might be a negative indicator.
It was less common to include measures of health service use in earlier multivariate models of private health insurance. The measures that were included were limited to doctor and hospital services (Hopkins and Kidd 1993). Measures of the use of health services might be expected to be useful determinants of private health insurance in that they may be a proxy for an individual’s or family’s expected need of medical treatment or it may be that private health insurance increases access to some
medical services. For these reasons a number of measures of health service use were included in addition to the use of doctor and hospital services. In particular, a range of ancillary services were included that might be expected to have a stronger association with hospital and ancillary and ancillary-only insurance. The services included were dental, chiropractic, pharmaceutical, physiotherapy, optical, dietary, podiatry and psychology. In addition, an indication of the type of doctor —general practitioner or specialist — was included. Treatment by a specialist was seen as an indicator of the severity of medical conditions. Hopkins and Kidd (1993) included a smoking indicator in their model, suggesting that it may be a proxy for expected health services use or of
5 Cameron et. al. (1988) and Cameron and Trivedi (1991) also included a number of
the additional variables tested in the model reported in this paper — such as country of birth, type of doctor used, occupation and health status measures. However, these studies, which used data collected in 1978, are now quite dated.
risk aversion in the insurance decision. Variables for smoking, alcohol consumption and body weight were included in this study.
The two measures of health status used in this study — self-reported health status and the number of chronic conditions — were also reported by the ABS (1995a). It was considered that, in a multivariate model,
where all other factors are held constant, poor health might have a positive relationship with private health insurance cover.
Finally, the ABS (1995a) found that several interaction terms were significant determinants of private health insurance. These were state and income, state and health concession card status and income and health concession card status. In this study, interaction terms suggested by the distributional analysis (family type and age) and a range of inter-actions with income were included. As income had been reported as the principal determinant of private health insurance (ABS 1995a) it was considered important to examine whether it had significant interactions with other determinants.
5.2 Identifying significant determinants of private health insurance The anticipated relationships between private health insurance and the variables that were included in the three regression models are
summarised in table 24.
Table 24 Theoretical model of expected relationships between variables
and private health insurance
Positive relationship Negative relationship 1 High health service use — hospital
admittance, ancillary services
1 Low health service use — hospital admittance, ancillary services 2 Poor access to services without insurance
— location of residence
2 Poor access to services regardless of insurance — immigrant, limited English 3 Perceived high need of health services —
health status indicators of good health
3 Perceived low need of health services — health status indicators of poor health
4 Old age 4 Young age
5 High income, high education, income from wages and salaries or own business
5 Low income, low education, health concession card, pensioner
6 Family with children 6 Family without children 7 Low risk aversion — not smoking, drinking,
normal body mass
7 High risk aversion — smoking, drinking, high or low body mass
The definition of each of the variables included in the models is provided in table 25.
Table 25 Definition of variables Variables Definition
AGE Five year age group: 0–4 years, 5–9 years, through to 80 plus years AGEINC Interaction term: age and income
CHIRWT Whether visited a chiropractor in the previous fortnight COB1_INC Interaction term: born in Australia and income
COB2_INC Interaction term: born in New Zealand and income COB3_INC Interaction term: born in UK or Ireland and income COB4_INC Interaction term: born in Italy and income
COB5_INC Interaction term: born in Greece and income
COB6_INC Interaction term: born in Southern Europe and income COB7_INC Interaction term: born in Western Europe and income COB8_INC Interaction term: born in other Europe and income COB9_INC Interaction term: born in the Middle East and income COB10INC Interaction term: born in South-East Asia and income COB11INC Interaction term: born in Southern Asia and income
CTYBIRTH Country of birth: 1 = Australia, 2 = New Zealand, 3 = UK or Ireland, 4 = Italy, 5 = Greece, 6 = Southern Europe, 7 = Western Europe, 8 = other Europe, 9 = Middle East, 10 = South-East Asia, 11= Southern Asia, 12 = other
DENSINCE Time since last attended the dentist: 0 = not applicable, 1 = less than 2 weeks, 2 = 2 weeks to 3 months, 3 = 3–6 months, 4 = 6 months to 1 year,
5 = 1 year to 2 years, 6 = more than 2 years, 7 = never visited DIET12MT Whether visited an optician in the previous year
DOCTYPE Type of doctor last attended: 0 = not applicable, 1 = GP, 2 = specialist FAMINCOM Family income in dollar values
FAT Body mass: 0 = not applicable, 1 = underweight, 2 = acceptable, 3 = overweight, 4 = obese
FHTHCARD Whether have access to health concession card
H_STATUS 0 = not applicable, 1 = poor, 2 = fair, 3 = good, 4 = excellent HLTHREG 47 health regions as labelled in table 19
HOSPWT12 Whether admitted to hospital in the last year HST_1INC Interaction term: poor health and income HST_2INC Interaction term: fair health and income HST_3INC Interaction term: good health and income HST_4INC Interaction term: excellent health and income
INCMSRC Income source: 0 = NA, 1 = Wages/salaries, 2 = Own business, 3 = Pension/benefit, 4 = Superannuation, 5 = Investment, 6 = Other IUT1_AGE Interaction term: couple with children and age
IUT1_INC Interaction term: couple with children and income IUT2_AGE Interaction term: couple without children and age IUT2_INC Interaction term: couple without children and income
Table 25 Definition of variables (continued) Variables Definition
IUT3_AGE Interaction term: sole parent and age IUT3_INC Interaction term: sole parent and income IUT4_AGE Interaction term: single and age
IUT4_INC Interaction term: single and income
IUTYPE Family type: 1 = couple with children, 2 = couple without children, 3 = sole parent, 4 = single and 5 = other
NUMCONDC Number of chronic conditions
OCCA Occupation: 0 = armed services, 1 = manager, 2 = professional, 3 = paraprofessional, 4 = trade, 5 = clerk, 6 = sales, 7 = plant/driver, 8 = labourer, 10 = unemployed, 11 = out of the labour force,
12 = not applicable
OPTIWTHR Whether visited an optician in the previous fortnight PHARMNR Number of pharmaceuticals taken in the previous fortnight PHYSWTHR Whether attended physiotherapy in the last fortnight PODIWTHR Whether visited a podiatrist in the previous fortnight PSYCHWTH Whether visited a psychologist in the previous fortnight SEX 0 = female, 1 = male
SMOKING Whether regularly smoke: 0 = no, 1 = yes WEEKALCH Weekly alcohol consumption in mL
YOARR Year of arrival: 0 = not applicable, 1 = before 1980, 2 = 1980–84, 3 = 1985–90 Each of the variables found to have a significant association with the likelihood of a person having or not having private health insurance, ancillary-only insurance or hospital-only insurance are identified in table 26.
Most notably, it was found that a range of ancillary health services were significant determinants of ancillary-only insurance — dental,
chiropractic, pharmaceutical, physiotherapy, optometry, dietary, podiatry and psychology services. Of these, dietary, podiatry and psychology services were not significant determinants of hospital and ancillary insurance, while optometry, podiatry and psychology services were not significant determinants of hospital-only insurance. This was an important finding as other studies had not identified these services as significant determinants of private health insurance, or their particular importance as determinants of ancillary-only insurance.
The coefficients, significance level and standard errors for the logit equations derived to estimate the probability of having private health insurance, ancillary-only insurance or hospital-only insurance are presented in appendix A.
