~ Pergamon Soc. Sci. Med. Vol. 38, No. 5, pp. 711-716. 1994

Copyright © 1994 Elsevier Science Ltd Printed in Great Britain. All rights reserved

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G E N E R A L PRACTITIONER UTILISATION IN IRELAND: THE ROLE OF SOCIO-ECONOMIC FACTORS

BRIAN NOLAN

The Economic and Social Research Institute, Dublin 4, Ireland

Abstract--Substantial variation across socio-economic groups in general practitioner utilisation patterns is observed in Ireland. This may reflect both the influence of socio-economic factors on health and on the demand for health care, and the fact that lower income groups are entitled to free GP care whereas the remainder of the population must pay on a fee-per-item basis. The paper analyses the influence of economic incentives and socio-economic factors on GP utilisation using data obtained in a large-scale household survey. This allows the different utilisation patterns of different social classes/income groups, and those with entitlement to free care vs the remainder of the population, to be documented. The importance of attempting to control for health status is shown, and the difficulties in trying to disentangle the effects of incentives from those of social class or income illustrated.

Key words--utilisation, socio-economic, charges, Ireland

i. INTRODUCTION

In Ireland as elsewhere, substantial variation across socio-economic groups in the patterns of utilisation of general practitioner services is observed. In the Irish case, the observed differentials may reflect both the influence o f socio-economic factors on health and the demand for health care, and the fact that lower income groups are entitled to free GP care whereas the remainder of the population must pay for these services on a fee-per-item basis. Based on a large sample of Irish households, this paper analyses the determinants of GP utilisation, focusing on economic incentives and socio-economic characteristics. The importance of attempting to control for health status, and the difficulties faced in trying to disentangle the effects of social class, economic incentives, and health status, are shown.

We begin with a brief description of the Irish health care system insofar as it relates to GP care. The sample on which the analysis is based is described. An overview of the pattern of GP utilisation is then presented, followed by a more detailed analysis of utilisation and health status by social class. Finally, the main findings are summarised.

2. THE IRISH HEALTH CARE SYSTEM AND GP CARE

The Irish public health care system provides a complex set of entitlements to free or subsidised medical care, with entitlements depending on income [1, 2]. Those in what is termed 'Category I', with 'Medical Card Cover ' , are entitled to free GP care, doctors treating these patients being paid by the State. Up to 1989 this was on a fee-for-service basis. In 1989 a capitation system was introduced, but the data analysed here predate that change. Doctors treating Category I patients also generally treat other

patients, being paid privately by those patients on a fee-for-service basis. People in Category I are also entitled to free prescription medicines. Category I status is determined on the basis of a means test, applying to the current income of the family (rather than the individual). About 35% of the population are in Category I.

'Private' health insurance--which is in fact pro- vided by a state-backed monopoly insurer, the Volun- tary Health Insurance Board---also covers about one-third of the population, mostly towards the top of the income distribution. However, the cover pro- vided is predominantly for hospital in-patient care, with out-patient expenditure covered only after a relatively high annual deductible. Expenditure on GP visiting and on prescription medicines would exceed the ceiling in only a small proport ion of cases, and even then it is only that element of expenditure which is above the ceiling which is reimbursed. As far as GP visiting and prescription medicines are concerned, then, in most cases it is public entitlement status rather than the presence or absence of health in- surance which determines whether one has to pay or not.

Thus the analysis of the impact of income and social class on GP utilisation in the Irish case is considerably complicated by the fact that many of those on low current incomes and in the lower social classes can obtain GP care free of charge, while the rest of the population have to pay out of pocket. Not only would this difference in 'price' facing patients be expected to influence demand directly, it may also affect provider behaviour. Tussing [3, 4], in analysing survey data for 1980, noted that there was a substan- tially higher rate of GP visiting for Category I than the remainder of the population, even having con- trolled for differences in age, sex and some other

711

712 BRIAN NOLAN

characteristics. He suggested that inducement of de- mand by doctors was a contributory factor, doctors standing to gain since they were paid for each visit, and patients in Category I being less resistant because they did not have to pay.

It is also relevant that most of the population outside Category I, while they have to pay for GP care, could (in 1987) visit hospital outpatient depart- ments free of charge. The fact that prescription medicines were available free to Category I but not to the rest of the population, on the other hand, means that visits to renew prescriptions etc. were common and costless for that g roup~a visit to the GP being required for repeat prescriptions.

3. THE DATA

The data used here were gathered in a large-scale household survey carried out by the Economic and Social Research Institute in 1987 [5]. The sampling frame was the Register of electors, from which a random multi-stage cluster sample was drawn. A sample of 3294 households was obtained, represent- ing an effective response rate of 64%, comparable with that in other large-scale surveys covering par- ticularly sensitive topics such as incomes. Infor- mation on age, sex, marital status, income, education, occupation, industry, unemployment experience and a range of other characteristics was obtained. On health services utilisation, the number of GP visits, prescriptions, outpatient visits and hospital nights in the past 12 months was sought for each individual. In addition, respondents were asked whether they were in Entitlement Category I and whether they had health insurance.

The survey also gathered some limited infor- mation on health status. On physical health status, adults (who completed a separate questionnaire) were asked "Do you have any major illness, physical disability or infirmity that has troubled you for at least the past year or that is likely to go on troubling you in the future?" A 12-item variant of the widely-used General Health Questionnaire (GHQ), adapted for interviewer rather than self- completion, was used to examine psychological health status [6]. This information on health is used here to distinguish

(i) those who reported a major illness, etc., who are termed 'chronically ill', and

(ii) those who scored at or above a threshold value of 2 on an index constructed from the GHQ responses, who are termed 'psychologically distressed'.

Since these health status indicators are available only for adults, the analysis is confined to them.

4. THE OVERALL PATTERN OF GP UTILISATION AND HEALTH STATUS

About 61% of the adults in the sample reported at least one GP visit in the previous 12 months. We provide in this section an overview of the extent of variation in visiting rates, and of self-reported ill- health, across characteristics of interest. First of all, as would be expected, visiting rates vary markedly with age. The average number of visits increases from about 2 for the 15-24 age group to 3.5 for those aged between 35-44 and over 6 for those aged 55 74, reaching almost 8 for those aged 75 or over. There is also a substantial differential between males and females, men having on average 3.8 visits and women having 4.7. (This is partly but not entirely attributable to differences for the age-groups where women would have visits related to child-bearing.)

There is a very substantial overall differential be- tween Category I and the rest of the population, the former reporting an average of 6.8 visits compared with 2.8 for the latter.

Turning to the relationship between visiting pat- terns and social class, Table 1 shows the average number of visits for individuals categorised into the 6 social classes used by the Irish Central Statistics Office. The number of visits rises consistently as one moves down the social class ranking, from 2.3 for those in the hgher professional/managerial class up to 6.3 for those in the unskilled manual class. (It is worth noting that in this social class categorisation, farmers are distributed among the classes on the basis of farm size: when persons living in farm households are distinguished as a group, they have a particularly low GP visiting rate.)

Clearly the bivariate relationship between visiting rates and social class may reflect, inter alia, differ- ences in composition of the classes in terms of the other variables--age, sex and Entitlement Cat- egory--given the variation in visiting rates across these characteristics which we have seen. We explore these inter-relationships in the next section, but first look here at what one might expect to be even more important, namely the relationship between GP visit- ing and health status. As would be expected, GP visiting is very strongly related to reported health status in the sample. Those reporting a serious physi- cal illness had an average of 11 GP visits in the year, compared with only 3 for those not reporting such an illness. The differential for those above/below the GHQ threshold was less, but still considerable those

Table I. GP visits by social class, Ireland 1987

Average number of Social class GP visits

Higher Professional/Managerial 2.3 Lower Professional/Managerial 2.6 Intermediate Non-Manual 3.2 Skilled Manual 4.6 Semi-skilled Manual 4.7 Unskilled Manual 6.3

GP utilisation in Ireland 713

Table 2. Percentage reporting serious physical illness and percentage above G H Q threshold by age group

% % above Age group reporting illness G H Q threshold

15-24 5.8 13.0 25-34 7.9 18.0 35-44 11.2 14.1 45-54 18.6 20.9 55~o4 31.1 17.3 65-74 32.9 16.2 75 or over 37.3 15.9 All 16.9 16.5

above the threshold had an average of 7½ visits, compared with 3½ for the rest of the population.

The percentage reporting physical illness is itself strongly related to age, as Table 2 shows--only 6-8% of those aged under 35, compared with 30% or more of those aged 55 or over, reported having such an illness. For psychological distress, on the other hand, the relationship with age is not pronounced.

We are particularly interested here in the relation- ship between illness and social class, and its impact on visiting rates. Table 3 shows that incidence of both physical illness and psychological distress is consider- ably higher in the lower social classes. The percentage reporting physical illness and the percentage above the GHQ threshold both rise consistently moving down the social class ranking. Disaggregation by age shows that these differentials persist even when focus- ing on particular age groups, they are not simply a product of differences in age composition. Since physical health status is being measured on the basis of self-reporting, it should be noted that there could be differences across the social classes in the way people respond to the question.* However, Blaxter [7] reports that where comparisons of self-reported health status with doctors' assessments or medical records have been made, the level of agreement has been high. Differentials in morbidity across social

Table 3. Percentage reporting serious physical illness and percentage above G H Q threshold by social class

% reporting % above G H Q Social class illness threshold

Higher Professional/ Managerial I 1.1 7.9

Lower Professional/ Managerial I 0.8 I 0.5

Intermediate Non- Manual 13.3 12.2

Skilled Manual 16.8 18.4 Semi-skilled Manual 17.9 18.6 Unskilled Manual 24.7 22. I All 16.9 16.5

*For example, those in the lower social classes might be more likely to perceive themselves as disabled by certain conditions if they are more of a handicap for someone with a manual than a non-manual job. While the question on self-reported health status here refers to chronic illness rather than disability, there could still be some such differences in response patterns across the classes.

classes and socio-economic groups on the basis of clinical evaluations have been widely documented elsewhere. (Mortality differentials across socio- economc groups in Ireland, documented in Nolan [8], are also consistent with such morbidity patterns.) While the measure of health status is a limited one and the relationship between self-reported health status and utilisation of health services might differ across the classes, having such a measure of health is crucial to interpreting visiting patterns.

There are also substantial differences between Category I and the rest of the population in the percentages reporting physical illness and above the GHQ threshold. In Category I, 28% reported physi- cal illness, compared with 10 per cent for the rest of the population. Likewise, 24% of those in Category I are above the GHQ threshold, compared with 12% for the rest of the population. Once again, disaggre- gation by age shows that these differentials persist even when focusing on particular age groups.

It is clear that the incidence of illness would in itself be expected to produce differences in GP visiting rates across social classes and Entitlement Categories, hav- ing controlled for age (and sex). What we want to explore in the next section, then, is the extent to which differences in visiting rates between the social classes are attributable to differences in their composition in terms of age and age, to differences in the proportion entitled to free care, and to differences in the inci- dence of ill-health. While income, social class and Eligibility Category are related, it is worth emphasis- ing that they are far from perfectly correlated--if they were, it would of course be impossible to distinguish their effects. The degree of overlap may be illustrated by the fact that only 57% of persons in Category I are in the bottom two social classes, and over half those in the semi-skilled manual class and 30% of the unskilled manual class are not in Category I. Simi- larly, a substantial proportion of those in Category I are not at the bottom of the household income distribution, while social class ranking by no means corresponds directly with position in the current income distribution. The interrelationships between these variables mean that caution is required, but we can nonetheless assess the extent to which differences in visiting rates across the classes could plausibly be attributed to differences in their age/sex composition or the proportion entitled to free care.

5. ANALYSIS OF GP VISITING

There are in fact significant differences between the social classes in age/sex composition, with a relatively high proportion of elderly people in the lower social classes and also a slightly higher than average pro- portion of women. The most straightforward way to see the extent to which such differences in age and sex composition could account for differences in GP visiting across the social classes is to calculate stan- dardised visiting rates for each class. That is, we

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714 BRIAN NOLAN

Table 4. Standardised GP visiting rates by social class

Standardised Standardised by Actual GP by age and age, sex and

Social class visits sex Category I/not

Higher Professional/ Managerial 2.33 2.39 2.7 I

Lower Professional/ Managerial 2.65 2.76 ~. 19

Intermediate Non- Manual 3.26 3.43 3.78

Skilled Manual 4.57 4.87 4.76 Semi-skilled Manual 4.74 4.98 4.72 Unskilled Manual 6.30 5.76 4.77

Table 5. Use/need ratios by social class

Visiting rate Illness rate ( 100 = sample ( 100 = sample Use/

Social class average) average) need ratio

Higher Professional/ Managerial 56 70 8 I

Lower Professional Managerial 64 67 96

Intermediate Non- Manual 78 82 96

Skilled Manual 110 103 107 Semi-skilled Manual 114 1 I I 103 Unskilled Manual 151 151 100

calculate what the visiting rate for a class would have been if it had the same composit ion as the overall sample in terms of age/sex groups with its own visiting rates for each group. We therefore categorise individuals into 16 groups- -8 age groups for males and for females--and apply the class-specific visiting rates for each group to the proportions in each group in the overall sample. Column (1) of Table 4 shows the actual visiting rate for each social class, and column (2) shows the age/sex standardised rate calcu- lated in this way. We can see that the standardisation does reduce the rate for the unskilled manual class, which falls from 6.3 to 5.8, and slightly increase those for the higher social classes, but the effect on the differentials is rather marginal: most of the gap between top and bot tom remains.

This does not take into account, though, the fact that the lower social classes also contain a relatively high proport ion of those entitled to free GP care and prescription medicines, that is those in Entitlement Category I. A more disaggregated standardisation can therefore be carried out, categorising into 32 groups- - the eight age groups, male and female, and those in/not in Category I. Again, the class-specific visiting rates for each of these groups can be com- bined with the sample proportions in each group to

*For this reason, it would not be possible to carry out a more disaggregated standardisation taking income group as well as Category I/not into account, but the Category I/not distinction should pick up the most important income-related effects on visiting.

tCalculating 'use" and 'need' indices standardised by, for example, age and sex and then constructing use/need ratios would show the same pattern.

calculate a standardised rate lbr each class. (It should be noted that there are relatively small numbers in some of the cells for this analysis.*) The results, shown in column (3) of Table 4. show that this now has a considerably greater effect on differentials. The standardised rate for the unskilled manual social class has now fallen to 4.8, and is little different from those for the semi-skilled and skilled manual classes. The rates for the top three classes have risen, and the gap between top and bottom is considerably narrower. However, a considerable gap does remain: the stan- dardised rates for the manual social classes are still about 75% above that lk~r the higher pro- fessional/managerial class.

The standardisation procedure suggests, therefore, that while differences in composition and in entitle- ment to free care may play an important part in producing differences in GP visiting patterns across the social classes, they do not fully account l\)r them or "explain them away". This highlights the import- ance of the relationship between visiting rates and 'need': do the differentials across the classes in visiting patterns reflect differences in the need for care? A crude but useful way of examining the relationship is to follow Brotherstone [9] in calculating use/need ratios, here using the measure of self-reported chronic illness in the sample as the indicator of need. The most direct calculation is simply to take the visiting rate and the proprotion ill in the sample as a whole as each equal to 100, so the visiting and illness rates for each class relative to these base levels represent the levels of 'use' and "need' respectively. The use/need ratio is then simply the ratio of one index to another, and the indices and ratios are shoran in Table 5.t

GP utilisation in Ireland 715

These suggest that, in fact, the variation in visiting rates across the social classes does reflect quite closely the variation in 'need', as proxied by rate of chronic illness. The 'excess' visiting by the lower social classes corresponds to their 'excess' rate of illness, and the use/need ratio for the unskilled manual class is in fact exactly 100. The ratios for the semi-skilled and skilled manual classes are slightly above 100, and those for the higher social classes below 100, but the general pattern of utilisation does not differ greatly from that of ill-health.

The implications of the observed variation in visiting rates across social classes, or Entitlement Categories, cannot therefore be reliably assessed in the absence of information about health status. An alternative methodological approach illustrates this even more directly. Regression analysis may be em- ployed to analyse the relationship between GP visits and the range of characteristics on which infor- mation is available. On the basis of this type of analysis using an earlier Irish survey, Tussing [4, 5] concluded that having entitlement to free GP care was a major factor in explaining the relatively high visiting rates of those in Category I. However, he did not have available any measures of health status. With the information available here, a more com- plete set of explanatory variables, including age, sex, income, social class, entitlement category, and health status, can be included.* Estimation results fully reported elsewhere [2] show that although being in Entitlement Category I is a significant positive influ- ence on the predicted number of visits in the full model, if the health status measures are omitted the estimated effects of Category I membership are con- siderably higher. Thus, where no such measures are available, some of the effects of morbidity differen- tials may be attributed to economic incentives.

6. CONCLUSIONS

In this paper, GP visiting patterns among a large sample of Irish households have been analysed. The interactions of social class, income, health status and economic incentives are particularly complex in the Irish case, because those on low incomes are entitled to free GP care (including prescription medicines) whereas the remainder of the population must pay

*Because a significant proportion of the sample had no GP visits, estimating the relationship by Ordinary Least Squares with number of GP visits as dependent variable could be subject to bias because of the clustering of observations on zero. The relationship is therefore mod- elled in two stages. The first looks at the determinants of whether the individual had any GP visits, fitting a logit model where the dependent variable is a dichoto- mous one---0 for those with no visit, I for those with at least one visit. The second stage takes the number of GP visits as dependent variable, but is only estimated for those who did have at least one visit.

for these services. It is therefore particularly difficult to disentangle the impact of the various factors on visiting behaviour. There is a very substantial differ- ential in overall average visiting rates between those with entitlement to free GP care and those who have to pay, and between the upper and lower social classes.

Standardising for age and sex composition re- duces the differentials in visiting rates across the social classes only marginally. Further standardising for the percentage entitled to free GP care does substantially reduce these differentials, but the stan- dardised visiting rates for the manual social classes continue to be considerably higher than those for the professional/managerial classes.

These differences in visiting rates may however reflect underlying differences in the need for care. Using self-reported chronic illness as a crude indi- cator of need, use/need ratios were calculated for the social classes. These were all quite close to 1, indicat- ing that the pattern of visiting corresponded quite closely to that of chronic illness. Regression analysis also shows the importance of controlling for health status in attempting to distinguish the influence of, for example, entitlement to free care.

These findings must be carefully interpreted. Clearly, the measures of health status available may not fully control for actual health status differentials across socio-economic groups. What appear to be the product of differences in economic incentives faced, or in income/social class, may partly reflect such unmeasured differences in health status. How- ever, the analysis marks a significant improvement on previous Irish research on utilisation, where no measures of health status were available. The results illustrate the importance of controlling for health status; they also suggest that such differences are unlikely to account fully for the substantial differen- tial in visiting rates between those who receive GP care free of charge and those who must pay for these services.

REFERENCES

1. Report of the Commission on Health Funding. Station- ery Office, Dublin, 1989.

2. Nolan B. The Utilisation and Financing of Health Services in Ireland. General Research Series Paper 155. The Economic and Social Research Institute, December, 1991.

3. Tussing A. D. Irish Medical Care Resources: An Econ- omic Analysis, General Research Series Paper 126. The Economic and Social Research Institute, Dublin, 1985.

4. Tussing A. D. and Wojtowycz M. Physician induced demand by Irish GPs. Soc. Sci. Med. 23, 851-860, 1986.

5. Callan T., Nolan B., Whelan B. J., Hannan D. F. and Creighton S. Poverty, Income and Welfare in Ireland. General Research Series Paper 146. The Economic and Social Research Institute, Dublin, 1989.

6. Whelan C. T., Hannan D. F. and Creighton S. Unem- ployment, Poverty and Psychological Distress. General

716 BRIAN NOLAN

Research Series Paper 150. The Economic and Social Research Institute, Dublin, 1991.

7. Blaxter M. A comparison of measures of inequality in morbidity. In Health Inequalities in European Countries (Edited by Fox A. J.). Gower, Aldershot, 1989.

8. Nolan B. Socio-economic mortality differentials in Ire- land. Econ. Soc. Rev. 21, 193-208, 1990.

9. Brotherstone J. Inequality: is it inevitable? In Equalities and Inequalities in Health (Edited by Carter C. O. and Peel J.). Academic Press, London, 1975.