Total costs and predictors of costs in individuals with early inflammatory polyarthritis: a community-based prospective study

N. J. Cooper, M. Mugford1, D. P. M. Symmons2, E. M. Barrett3 and D. G. I. Scott1

Department of Epidemiology and Public Health, University of Leicester, Leicester,
1 School of Health Policy and Practice, University of East Anglia, Norwich,
2 ARC Epidemiology Unit, University of Manchester, Manchester and
3 Norfolk Arthritis Register, St Michael's Hospital, Aylsham, UK


    Abstract
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Objective. To estimate the health service, non-health service and total costs and predictors of costs in individuals with early inflammatory polyarthritis (IP).

Methods. We conducted a prospective longitudinal study over a 6-month period. The participants were a random sample of 133 individuals who had enrolled with the community-based Norfolk Arthritis Register (NOAR) database between 1994 and 1999. The main outcome measures were the mean (per person) 6-month health service cost, non-health-service cost and total cost associated with IP.

Results. One hundred and fifteen of the 133 individuals who were recruited into the study completed 6 months of follow-up. The mean 6-month total cost was estimated to be £2800 per person, of which 14% was health service costs and the remainder non-health-service costs. Higher total costs were associated with lower health status and rheumatoid factor positivity.

Conclusions. Early IP has a considerable impact on both the health-care system and, more importantly, society. Non-health-service costs (i.e. costs incurred by the individual with the disease, their family and friends) account for a substantial proportion (86%) of the total costs associated with early IP.

KEY WORDS: Inflammatory polyarthritis, Cost of illness, Economics, Health-care costs, Non-health-care costs, Costs.


    Introduction
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
The rapid increase in health-care expenditure in all countries has increased interest in the economic impact of individual diseases or disease categories. The economic burden of rheumatoid arthritis (RA) is thought to be substantial for both the person with the disease and the health services. Evidence from US-based studies has shown that people with RA face three times the cost of medical care, twice the rate of hospitalization and four times the number of ambulatory visits to physicians compared with an age- and sex-matched non-arthritic population [1]. Findings suggest that the total and per capita lifetime economic costs of RA are similar to those incurred by stroke and coronary heart disease patients in the USA [2].

The majority of studies published to date have been US-based and focused on long-term (established) RA in a hospital (clinic) setting [3]. There have been few studies (practical or theoretical) on the costs of RA based in Europe [47] and there is also a lack of studies reporting the costs of early RA, which are increasing in importance since the change in clinical practice to prescribe more aggressive treatment regimes earlier in the disease process [8]. Also, community-based studies are likely to be more representative of the wider disease population.

In 1989 the community-based Norfolk Arthritis Register (NOAR) was set up with the primary aim of identifying and studying all new cases of inflammatory polyarthritis (IP), of which RA is a subset, in the former Norwich Health Authority by notification from general practitioners and hospital clinics [9, 10]. Since the register was established, approximately 250 people each year have agreed to take part in the project. From NOAR data and national population statistics, it can be estimated that there are approximately 22 700 new cases of IP each year in the UK [9].

This paper reports the results of a 6-month longitudinal study designed to estimate the health service, non-health-service and total costs of early IP, using data for a cohort of people from NOAR (i.e. a representative population sample). It provides informative data about how the burden of disease is distributed among not only the health-care system and the individual with the disease, but also other parts of the public sector, such as the individuals’ family and friends, and society as a whole. This study aimed to assist the decision-making process at policy and planning levels by documenting the extent of resource use in current practice and identifying where the major burden of cost lies in the treatment and care of these people. It also intended to identify the subgroups of people who incur the highest costs. It was not a primary aim of this study to inform choices about which treatment or therapy is the most cost-effective option for people with IP and RA, although we expect that data collected during the study will prove useful for such exercises.


    Methods
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Study design
This was a prospective, prevalence-based, longitudinal study conducted from a societal perspective and designed to capture the 6-month costs associated with early IP.

Study population
The study population consisted of 133 people with early IP (i.e. with disease duration of 5 yr or less) who were enrolled in the community-based NOAR between 1994 and 1999. The study was conducted between June 1999 and May 2000. NOAR inclusion criteria are as follows: (i) age over 16 yr; (ii) swelling of two or more joints; (iii) symptom duration more than 4 weeks; and (iv) symptom onset after January 1990.

Full details of the NOAR study method are published elsewhere [9, 10].

Sources of resource-use data
Resource-use data were collected from participants at three different time points—baseline, 3 months and 6 months from the time of recruitment into the study—by the use of self-completion postal questionnaires including the EuroQol [11], which measures health status on a scale from 0=worst imaginable health state to 1=best imaginable health state. The content and structure of the data collection instruments were informed by data extracted from the transcripts of two focus groups conducted on individuals with IP to obtain a better understanding of the types of costs people with IP and their families have to bear as a direct consequence of their illness. Prior to this study, the questionnaires were pilot-tested on two cohorts of individuals from different geographical settings (rural and urban) as a test of external validity, and the response data were validated against an alternative data source, where available, as a test of internal validity.

To minimize recall bias, study participants were provided with a memory aid in the form of a diary in which to record their resource use and expenditure over the 3-month follow-up intervals. Completion of the diary was voluntary, and the diary was for the participants’ personal use only (i.e. it was not collected from them).

The questionnaires were designed to obtain information regarding the utilization of health-care services and resources, out-of-pocket expenses, time lost from usual activities and household help from family and friends. The NOAR database provided sociodemographic data (age, sex, smoking status, social class and ethnic group) [social class was assigned using the Registrar General's system [41], based on the occupation of the individual] and self-reported functional disability data measured annually using the Health Assessment Questionnaire (HAQ) (scored on a scale from 0=without difficulty to 3=unable to perform) [12].

Sources of unit cost data
Unit costs to supplement the resource-use data were obtained from a number of different sources (Table 1Go). All costs were expressed in 1998/1999 UK prices.


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TABLE 1.  Sources of unit costs

 

Cost analysis
The costing methods used are presented in Table 2Go. The total 6-month cost per person was estimated by combining resource-use data with unit costs using the following general costing formula:


(001)
where i is the ith individual (i=1, ... n) and j is the jth service received or resource used (j=1, ... m).


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TABLE 2.  Costing methods

 
The mean 6-month costs to the health service, the individual, their family and friends, and employer were also calculated.

Statistical analysis
The main descriptive statistics presented are the arithmetic mean, standard deviation (S.D.), median and interquartile range (IQR) [13]. Exploratory data analysis was used to study the distribution of costs. The study population was categorized into three age groups (16–39, 40–59 and 60 yr and over) and their HAQ and EuroQol scores were categorized into tertiles.

A multiple linear regression model was fitted to the log-transformed cost data and parameters were estimated using forward stepwise regression to identify which sociodemographic and clinical characteristics influenced cost.

Sensitivity analysis
The sensitivity of the costs estimated in the main analysis to changes in the following variables were investigated.

Health service costs
In-patient care costs were varied by ±40% and out-patient care costs by ±15% to make allowances for variation in provider costs across the UK, as illustrated in the NHS reference costs [14].

Non-health service costs
The cost per mile travelled was varied from 45 to 185 pence [15], the cost per hour of paid help was increased from 770 pence (weekday rate) to 1200 pence (weekend rate) [16], and the cost of non-working/leisure time was varied from 24.7% of working time cost for the main analysis [17, 18] to 40% (600 pence per hour) [17].


    Results
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Out of the 133 people who enrolled in the study at baseline, 115 (86%) completed both the 3-month and the 6-month follow-up questionnaires. From Table 3Go it can be observed that approximately 70% of the study population were female, the mean age was 57 yr and mean disease duration 47 months. It can also be observed that 50% of the study population were classified as having RA using the ACR criteria cumulatively [19, 20].


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TABLE 3.  Characteristics of study participants at baseline

 
Cost analysis
Over the 6-month study period, the mean total cost for the cohort of individuals under observation was £2791 per person [95% confidence interval (CI) £2080 to £3713] (Table 4Go). Only 14% of the total cost was incurred by the health-care service in the form of health-professional visits, in-patient stays and medication. The remaining 86% of total costs were non-health costs incurred by ‘other agents’ [i.e. participant (46%), family and friends (35%) and employers (5%)]. Figure 1Go presents a histogram of the 6-month costs for all 115 participants who completed both follow-up questionnaires. As is often the case with cost data, the distribution is heavily skewed due to a small number of individuals incurring high costs while the majority incur low costs. Health service and non-health service 6-month costs were found to be positively associated (Spearman's rank correlation coefficient rS=0.177; P=0.06).


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TABLE 4.  Mean 6-month cost (n=115) (£ sterling, 1998/9)

 


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FIG. 1.  A histogram of 6-month cost (UK £).

 
To investigate whether costs changed over time, the cohort was categorized into three subgroups depending on the number of years a subject had been registered with NOAR (0 to <2, 2 to <4, >=4 yr). The boxplot in Fig. 2Go shows that there was no statistically significant cost difference between subgroups.



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FIG. 2.  Box plot of total 6-month costs vs disease duration. Thick lines represent the median, boxes 25–75% of values (IQR), thin lines 10–90% of values and asterisks and 0 the extreme values.

 
The largest proportion of costs incurred by the health service was for in-patient stays and day-unit visits. Despite there being only three reported in-patient stays (mean length 21 days) and nine day-unit visits, these accounted for 33% of the health service costs incurred by the whole cohort (Fig. 3Go). Visits by other health professionals (consultant, GP, nurse, therapists) accounted for 37% of the total cost to the health service. Only 16 out of the 327 (5%) out-patient visits were private consultations paid for by the participant. Prescribed medication accounted for 30% of the total health-service costs. Almost two-thirds of the study participants were taking non-steroidal medications and approximately half were taking second-line medications.



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FIG. 3.  Pie chart of costs incurred by the health service.

 
Non-health-service costs were incurred by the participants, their family and friends, and their employers (where applicable). The largest proportion of estimated cost was for household help (34%) (Fig. 4Go). This was mainly unpaid help from family and friends. Only 2.5% of all help was paid for by the participant. The mean number of hours of help per week required by participants was approximately 4.5. A large proportion of non-health-service costs were accounted for by time lost by participants from their usual activities—either work (24%) or leisure (25%). The majority of time lost to work was unpaid work such as housework. This was to be expected, given the large proportion of the study cohort who were either female and/or retired.



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FIG. 4.  Pie chart of non-health-service costs.

 
To enable cost comparisons with the results of earlier studies, the cost estimates above may also be expressed using the broader definitions of direct (health-care and non-health-care) and indirect (lost productivity) costs (a categorization previously favoured by health economists). Lost productivity costs are defined here as costs associated with production loss and replacement costs due to illness, disability and death of productive persons, both paid and unpaid [21]. Thus the indirect cost category includes forgone work (paid and unpaid), forgone leisure activities and the replacement cost of household (informal) care, whilst direct costs comprise the remainder. The mean direct and indirect costs were £794 and £1997 respectively.

Statistical analysis
To determine which sociodemographic and clinical characteristics influenced cost, a multiple linear regression model was fitted to the log-transformed cost data. Note that the cost data were transformed to obtain a more symmetrical distribution (Fig. 5Go). The sociodemographic and clinical variables considered for inclusion in the model are listed in Table 5Go. Note that, for the purposes of this analysis, the EuroQol and HAQ scores were categorized into tertiles. It can be observed from Table 5Go that the mean cost appeared to increase with HAQ score and decrease with EuroQol score, as would be expected. There also appeared to be a difference between the mean costs for individuals who were positive and negative for rheumatoid factor. Note that the EuroQol score was not included in the regression model as it was found to be highly correlated with the HAQ score (rS=-0.414, P<0.005). The final model included three of the seven variables, all of which were simultaneously significantly associated with cost (P<0.05): rheumatoid factor, HAQ score (level 1 and 2) and age (Table 6Go). The adjusted r2 value for this model was 29%, indicating that the variability in cost is only partly explained by the predictor variables in the model.



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FIG. 5.  Histogram of the log-transformed 6-month cost (UK £).

 

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TABLE 5.  Mean (S.D.) 6-month costs split by sociodemographic and clinical factors

 

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TABLE 6.  Linear regression model with log-transformed cost data

 

Sensitivity analysis
The uncertain parameters in the analysis of health service costs were the secondary care costs, which were based on generic unit costs for out-patient visits and in-patient stays. Such costs vary greatly from hospital to hospital across the UK and therefore the health service costs were reworked. The lower extreme for the mean 6-month cost (i.e. reducing out-patient costs by 15% and in-patient and day-unit costs by 40%) was £330 and the upper extreme (i.e. increasing out-patient costs by 15% and in-patient and day-unit costs by 40%) was £449. This was a change in health service costs of ±15%. Similarly, the uncertain parameters in the analysis of non-health-service costs were unit cost of household help, cost per mile and cost per hour of non-working/leisure time. The mean 6-month cost for the main analysis was £2406. When all of the above parameters were varied within the ranges defined in the Methods section, the lower extreme was £2176 and the upper extreme £3582.


    Discussion
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 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
In the UK, most health-care is free at the point of use and funded from general taxation. However, much of the costs of illness still fall on other agents, such as patients and their families. Such costs are often not studied explicitly in health services research despite their importance in representing the part of total resources society devotes to health-care. Considering health service costs in isolation would have explained the costs associated with early IP (14%) only partially, and may lead to misallocation of resources if it places extra costs on other agents. For example, centralizing clinics may result in patients having to travel further to visit health professionals.

As with the effects of disease course and treatment, costs also show vast variability between individuals with IP. Whilst the aggregated results of such a heterogeneous group are of limited value for decision-making, the mean cost (for the average individual) may be used to inform budget-setting for a new cohort of individuals. As can be observed from Fig. 1Go, a relatively small number of individuals incur high costs, which skews the distribution of cost data to the right and inflates the mean value above the median value. Although total costs cannot be derived from it, the median value does provide useful information on the most ‘typical’ cost for an individual subject. Due to random variation, the number of high-cost individuals may vary considerably between years and rheumatology departments. Clearly, such variability may have substantive effects on tight budgets. In this cohort, 10% of the individuals incurred 50% of the total 6-month costs.

The main component of health-service costs was in-patient stays and day care followed by prescribed medication, which accounted for 33 and 30% of total health-service costs respectively. The minority of study individuals who incurred an in-patient stay or day-care visit (6%) accounted for a large proportion of the total 6-month health-service costs (42%). These findings were similar to those for asthma [22, 23] and multiple sclerosis [24].

Overall, average (per person) health service costs were considerably lower than previous study findings. Reasons for this include differences in (i) the population under surveillance (e.g. early IP vs established disease); (ii) the classification of the disease (IP vs RA); (iii) the availability of a day-care unit; (iv) the base year of the study (i.e. change in clinical practice over time); (v) the availability of routine cost data for health-care; and (vi) study setting (community vs clinic).

Only the studies by van Jaarsveld et al. [6] from The Netherlands and Newhall-Perry et al. [25] from the USA were concerned with the costs of early disease. The former study investigated the costs of RA over the first 6 yr after onset whereas the latter study concentrated on the first year after onset. In both studies the participants were, on average, more functionally disabled (mean HAQ 1.25) than in the present study (mean HAQ 0.89). The health-care costs that were estimated by van Jaarsveld et al. [6] greatly exceeded those reported in the present paper, which reflects the clinic setting of the study of van Jaarsveld et al. and the case mix of the population of interest. However, the study of Newhall-Perry et al. [25] was community-based, like this study, and therefore provided similar cost estimates.

It is important to remind the reader that this was an evaluation of early IP and therefore costs to the health service are likely to increase still further as the disease becomes more progressive (e.g. surgery costs, especially total knee or total hip arthroplasty, combined with postoperative infections and other surgical complications) [26, 27].

The costs incurred by individuals as a result of their IP were found to be substantial [46% of total 6-month cost per person, equivalent to 17% of average income ({approx}£1300 per person)]. In this study, only a small percentage of all household help was paid for (between 0.9 and 3.7%), which agrees with the findings of Medeiros et al. [28]. The cost of informal (unpaid) care is likely to vary depending on household and social capital available; for example, structures of society that provide help (e.g. self-help groups) and public resources, which may increase the potential of society (e.g. social services). Medeiros et al. [28] reported that low socio-economic level and lack of social support resulted in reduced quality of life of caregivers. Therefore, it is important for future research to investigate and, if necessary, refine social support provisions to ensure greater quality of life for caregivers.

Costs incurred by friends and family as a result of an individual's IP are often omitted from studies investigating the economic impact of IP/RA. This is a sizeable omission as friends and family costs accounted for a substantial proportion (35%) of total 6-month cost per person (£983, 95% CI £678–1338). The majority of this cost was attributable to informal care around the home (30% of total cost), a result also found in multiple sclerosis research (26% of total cost) [24]. In later, more established disease, one of the major components of cost is reported to be long-term care in residential or nursing home accommodation, which is linked to deterioration in functional disability and quality of life [29].

In this study, time lost from work as a consequence of an individual's IP, which was covered by a statutory sick-pay scheme, was considered to be a cost to the employer and government. However, in some cases, especially short-time sickness absence, the employer may not incur the cost if it is possible for the work to be made up on an individual's return to work or absorbed by other workers at no extra cost.

Other agents who incurred costs as a result of an individual's IP were social services and/or voluntary organizations, in the form of household help and providers of aids and home adaptations. Although such costs were minimal (0.03% of total 6-month cost per person) in this economic study of early IP, it is reasonable to assume that the role of social services and voluntary organizations will increase as an individual's IP progresses over time, especially for individuals without informal social support. Therefore, there is a need for future studies of more established IP to measure the extent of these costs to assist the planning of services for individuals without informal social support.

Overall, there was no statistically significant association between total 6-month cost and the number of years registered with NOAR. Individuals with high health-service costs also tended to encounter higher non-health-service costs. The results from the multiple linear regression model showed cost to have a positive association with rheumatoid factor and HAQ score and a negative association with age. These results agreed with the findings of van Jaarsveld et al. [6].

The change in the treatment regime, together with the development of a new generation of therapies [for example, cyclo-oxygenase-2 (COX-2) inhibitors [30, 31] and tumour necrosis factor {alpha} drugs] will have major effects on the cost of treating RA. Therefore, it is important that the efficacy and cost-effectiveness of these new therapies are investigated from the perspective both of the health provider and of society. It is important that future cost-effectiveness analyses are based on good-quality primary research on costs and cost behaviour of the type presented above. Such detailed cost data can then be used to inform the cost side of decision analysis models designed to assess the cost-effectiveness of new treatment regimes at an early stage, in order to assess the desirability of further research. In addition to the above, new expensive therapies also require considerable clinical judgement to enable them to be used effectively [32].


    Acknowledgments
 
We thank the NOAR team and Nicola Wiles (University of Manchester), Shirley Pearce (University of East Anglia) and Julia Dossor (Norfolk and Norwich Healthcare Trust) for all their help and support. We also thank all the study participants, without whom this research would not have been possible. This research was funded by an Arthritis Research Campaign PhD Studentship awarded to NJC.


    Notes
 
Correspondence to: N. Cooper, Department of Epidemiology and Public Health, University of Leicester, 22–28 Princess Road West, Leicester LE1 6TP, UK. Back


    References
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 

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Submitted 25 July 2001; Accepted 17 February 2002