Client Service Receipt Inventory

The second-phase interview also deployed the Client Service Receipt Inventory (CSRI; Reference Knapp and BeechamKnapp & Beecham, 1993). This gathers information from participants about accommodation and income, use of hospital in-patient services, other hospital services, community services, medication and informal care, with reference to the 6 months preceding the interview. We used the data from the CSRI in three ways. First, we grouped the number of contacts under four headings:

1. (a) Primary healthcare: general practitioner and community nurse;

2. (b) Generic healthcare (i.e. specialist, non-psychiatric): psychiatric): physiotherapy, chiropody, in-patient and out-patient accident and emergency services and day hospital;

3. (c) Psychiatric care: community mental health team, community psychiatric nurse, psychiatrist, psychologist, inpatient and out-patient care, accident and emergency services and day hospital;

4. (d) Social care: care: social services and voluntary day centres, drop-in, social worker, home-help or care worker, befriender, advice and counselling.

Use of psychotropic medication, including antidepressants, was examined separately.

Second, we combined all the CSRI data into a three-level ordinal hierarchy:

1. (a) no service use;

2. (b) primary care only, with or without antidepressant use;

3. (c) all other services, with or without primary care.

Third, we ascribed standardised costs to service and medication use. Service costs were based on the Unit Costs of Health and Social Care (Reference Netten and CurtisNetten & Curtis, 2000). Drug costs were derived from the British National Formulary (British Medical Association & Royal Pharmaceutical Society of Great Britain, 2000). Service and medication use was therefore costed in sterling irrespective of the country from which the data were collected. This has the advantage of facilitating cost comparisons between countries but does not allow discussion on the affordability of services, either privately by the individual or publicly by the state, as this was not one of the aims of the study. The costings used were current at the time the data were collected, in line with standard practice in health economics studies.

Analysis

Extent of service use could not be modelled as there were high percentages of no service use. Instead, logistic regression was used to examine the dichotomy of service use or not both overall and for the four groups of services mentioned above (primary care, generic, psychiatric and social). Ordinal logistic regression was used to model the dependent variable, hierarchy of use. Multiple linear regression was used to model cost of service use and of psychotropic drug use.

The same independent variables were used in each analysis in line with the Anderson model. Participants' predisposition to use services was measured by age, gender, marital status and number of people able to provide support. Enabling factors were urban/rural environment, country and centre, which were taken as proxies for health-care supply. Level of need was taken as scores from the SF-36 domains for social functioning, general health, physical functioning, pain, mental health and energy/vitality, number of life events, and a variable that combined life events and perceived level of help with those events and baseline BDI scores. Our decision to use standardised rather than site-specific costs (Reference Chisholm, Diehr and KnappChisholm et al, 2003) enhanced the analytical power of the study, allowing analysis to be pooled. All analyses were conducted using Stata statistical software release 8.0.

Sample description

In the first phase of the survey we contacted 14 387 people, and had an overall effective response rate of 65%. A second-phase interview was offered to 1767 people, of whom 1135 (64%) accepted. Non-responders at each stage were more likely to be male, young, socio-economically disadvantaged and from rural Ireland (Reference Ayuso-Mateos, Vázquez-Barquero and DowrickAyuso-Mateos et al, 2001). We identified 427 people with a diagnosis of ICD-10 or DSM-IV depressive or adjustment disorders, and defined them as study participants. Table 1 shows the national distribution of key characteristics for these people. There was no significant national difference according to gender, marital status or age. Significant national differences existed in mean BDI score, with Finland and Norway having a mean score 4.6 points lower than Ireland and the UK (95% CI 2.6-6.6).

Service use

Ordinal hierarchy of use

In the 6 months prior to interview, 77 (18%) study participants had no contact with any service (lowest level of use), 132 (31%) contacted only their general practitioner or community nurse (mid level), and the remaining 218 (51%) contacted one or more of the other services (highest level of use). Lower levels of service use were more likely with higher social function scores, higher general health scores and living in Norway. Higher levels of service use were more likely with an increase in the number of people offering informal social support.

Cost of service use

National patterns

Variations in patterns of service use were apparent across the five different national centres involved in this study. Participants from Norway and Spain were least likely to have used any service in the previous 6 months, whereas those from Ireland and the UK were most likely to have done so. Participants from Ireland were more likely to have received direct psychiatric care, and less likely to report taking psychotropic medication, than those from other countries. Participants from the UK were more likely to have been in contact with primary care, and reported greater use of social care, particularly counselling. Those from Spain were most likely to have been in contact with generic care services, and also most likely to report using psychotropic medication.

The ODIN study cannot be taken as a direct indication of national patterns in the use of health services by people diagnosed with depressive adjustment disorders: the urban and rural communities surveyed were not representative of their national populations and there were systematic demographic biases in response rates. Those who did not respond were younger, male and socio-economically disadvantaged: since these groups are less likely to be in contact with health and social care services, our findings are likely to have overestimated mean service use among the populations we surveyed. We considered alternative methods of accounting for random and non-random response bias (Reference Rubin, Schenker and SchaferRubin et al, 1988; Reference Schafer and GrahamSchafer & Graham, 2002), but concluded that their application to the data-set would not significantly enhance our results. Importantly, this diverse pattern of healthcare use by people with depressive and adjustment disorders is comparable with the results of other European studies.

The Eurobarometer study (European Opinion Research Group, 2003) found considerable national variation in help-seeking for mental health problems, being highest in Belgium and The Netherlands and lowest in Italy and Spain. The European Study of the Epidemiology of Mental Disorders (ESEMeD) survey (Reference Alonso, Angermeyer and BernertAlonso et al, 2004; Reference Kovess-Masfety, Alonso and BrughaKovess-Masfety et al, 2006) assessed life-time prevalence of mental disorder and healthcare use in France, Germany, Italy, Belgium, The Netherlands and Spain (the last being the only one to overlap with the ODIN set of countries). In relation to mood disorders, this survey found that respondents from Italy had the lowest consultation rates for mood disorders, and those from The Netherlands the highest. In relation to psychotropic medication, the survey confirmed our findings that the highest levels of prescribing were in Spain.

We found that overall costs of care in the ODIN study were similar in four of the five countries, ranging from £531 per person in Norway and Finland to £667 per person in Spain. However, they were substantially higher in Ireland, with a mean of £1036 per person. Given that 6- and 12-month outcomes for ODIN study participants in Ireland were no better than those in the other study centres (Reference Dowrick, Dunn and DalgardDowrick et al, 2000) there may be implications for health policy, particularly whether the additional costs of specialist psychiatric care can be justified with this group.

Costs of care in the ODIN study cannot be directly compared with those published from the Longitudinal Investigation of Depression Outcomes (LIDO) study (Reference Chisholm, Diehr and KnappChisholm et al, 2003), although both used the CSRI as the core data collection instrument. The LIDO team investigated a more heterogenous psychiatric population - cases of subclinical and clinical depression, with or without medical comorbidity - than that in ODIN, and LIDO only reported costs of untreated depression. The two studies also made different decisions about how to analyse their CSRI data-sets: LIDO combined medical out-patient and primary care service use, took a 3-month rather than a 6-month perspective, and calculated costs primarily in national currency units. Nevertheless, it is of interest to note that differences in overall costs of care were less than two-fold between the five ODIN centres, whereas LIDO found a twenty-fold variation between their highest-cost centre (Seattle, USA) and the lowest-cost centre (St Petersburg, Russia).

Predictors of health service use

In our study these national or centre differences in patterns of service use were mostly explained by other variables, when analysed in combination with other factors of relevance on the basis of the Anderson model.

Social support and health service use

Our working assumption was that people who had less access to informal social support would make greater use of health and social care services. We were aware of the Dutch study conducted by Ten et al (Reference Ten, Vollebergh and Bijl2002), who found that low levels of social support were associated with increased healthcare use by people with mental health problems. However, we found the opposite to be the case: the presence of social support, as measured by the number of people to be counted on for help, was associated with more rather than less service use.

The impact of social support on patterns of service use by people with mental health problems has rarely been studied, and published findings are ambiguous or contradictory. The findings of McGrady et al (Reference McGrady, Lynch and Nagel2003) are consistent with the model proposed by Ten et al (Reference Ten, Vollebergh and Bijl2002): among family practice patients in Ohio, negative affect increased but social support decreased the likelihood of service use. However, Abe-Kim et al (Reference Abe-Kim, Takeuchi and Hwang2002) found no relationship between family support and service use in a cohort of Chinese Americans experiencing emotional distress, a result partly explained by specific cultural norms in this community against use of formal health and social services.

Two studies provide partial, indirect support for our findings. In a survey of ageing families of adults with severe and enduring mental illness in Ohio, Smith (Reference Smith2003) noted a positive association between service use and extent of social support. An Australian study of predictors of service use by older people found that women (but not men) with anxiety were more likely to access primary care services, whereas men (but not women) who lacked social support were less likely to access these services (Reference Korten, Jacomb and JiaoKorten et al, 1998).

Why might an increased level of social support increase healthcare use by people with depression? Such people by definition lack motivation and self-esteem. This combination may lead many to conclude that they have neither the energy nor the right to seek professional help for their problems (Reference Gask, Rogers and OliverGask et al, 2003). Family and friends may well encourage people with depression to seek help, motivated either by altruistic desire for the individual's improvement, or else by a felt need to reduce their own burden of care (Reference Watson and AndrewsWatson & Andrews, 2002).

Sørgaard (Reference S⊘rgaard1999) points to a ‘Greek chorus’ effect of social networks in encouraging help-seeking. Social networks can contribute ideas and information about help-seeking, passing on experiences of health services and different kinds of help-seeking strategies. For people with first-episode psychosis, Cole et al (Reference Cole, Leavey and King1995) have documented the importance of having family members who could negotiate help, and Rickwood & Braithwaite (Reference Rickwood and Braithwaite1994) found that young people with emotional problems were more likely to seek professional help if they knew someone else who had already done so.

Our finding of a direct association between social support and healthcare use may be important for health and social care providers. It needs replication in other studies. It will also be important to establish whether this combination of factors has an impact on outcome. Those without informal support - who we already know are at greater risk of becoming and remaining depressed - are also less likely to receive services and interventions that might be of benefit to them. Informal and professional support do not tend towards a zero-sum, but rather appear to act additively.

If our findings are replicated, and if they are shown to have an adverse effect on health outcomes, then there would be a demonstrable need for active identification of individuals with depression who have fewer people to count on for support, followed by concerted efforts to offer the former effective interventions. Such activity could be considered either as a stand-alone programme, or as an additional component within established quality improvement initiatives (Reference Dietrich, Oxman and WilliamsDietrich et al, 2004).