- Top of page
- SUBJECTS AND METHODS
Current economic evaluations in the field of rheumatic diseases underline the need to include economic data in outcome assessment of clinical trials on rheumatoid arthritis (RA) and other musculoskeletal disorders (1–3). Since many evolving new therapies, such as biologic therapies, are costly, it is important to capture not only clinical data but additionally data on costs and their changes under therapy in order to render information on health economic effectiveness (1).
Reduction or prevention of RA consequences due to therapeutic interventions might lead to indirect cost savings by decreasing productivity losses related to work disability and sick leave. Since these indirect cost components make up >50% of the overall cost of illness in patients with RA (3), their assessment is of special importance.
Studies on original costing data are scarce; hence, most of the current economic analyses are based on mathematic modeling. Valid and easily employable assessment methods are needed to obtain comprehensive direct and indirect cost data covering at least the societal and the patient's perspective in different study settings (e.g., piggy back design).
Cost data assessment has mostly been performed by patient questionnaires so far (4). Different frequently used economic questionnaires in rheumatic conditions have been evaluated in terms of psychometric characteristics (4), showing a wide range of lengths, recall periods, cost units, and the cost domains covered. Only 4 of these (5–8) address the validity of the patient-derived data. Since all studies aim at investigating specific aspects of direct costs, there still is no information on validity and reliability of comprehensive RA cost questionnaires and on indirect cost components in particular.
A recent publication has addressed the validity of patient-derived costing data concerning health care utilization in patients with RA by cross checking information by the health economic patient questionnaire (HEQ-RA) with the database of the health care insurance covering the health care expenses (i.e., direct costs of these patients) (9). Costs for medication and inpatient care accounting for 68% of overall direct costs are reported adequately by the patients. Other cost components showed moderate association of patient- and payer-derived data.
The objective of the present economic investigation is to render information on the validity of patient-reported indirect cost data, as assessed by the HEQ-RA, compared with patient- and payer-derived data on a patient-by-patient basis concerning disease-related productivity losses in RA over a period of 18 months.
- Top of page
- SUBJECTS AND METHODS
Assessment of objective cost data by using registers and databases of health insurers is considered the gold standard of measurement of disease-related health care utilization and productivity losses in terms of sick leave and work disability (9). The major drawback of these data sources is their limited accessibility. Difficulties occur due to varying health care payers and insurances of an RA cohort, maintenance of data security, or matching of data sources (clinical and economic). These facts make the assessment of objective cost data a challenge of RA outcome evaluation. The development of valid tools based on patient-derived data for cost assessment plays an important role to integrate economic outcomes in RA outcome studies. The validity of patient-reported productivity losses in patients with rheumatic conditions has not yet been investigated in other studies.
The present economic investigation reveals that productivity cost estimations according to the patient questionnaire HEQ-RA and the health insurer database render comparable results. Regarding the health insurer data as the gold standard, the HEQ-RA underestimates overall costs by 17%. This deviation is lower than expected because the current literature shows a wide range of results concerning indirect cost estimation of RA (19), leading to the assumption that productivity losses might represent a very foggy component of disease-related costs. Analyzing exactly defined cost components such as productivity losses due to sick leave and work disability with a standardized methodology and a defined economic perspective reveals a strong relation between patient- and insurer-derived data considering both cost components. These results indicate that the diverging indirect costs measured in prior cost-of-illness studies can partly be explained by missing standardization of assessment methodology and assessment tools, but not by inadequate patient reports (19). Because patients seem to report their productivity losses adequately, more effort should be made to develop comparable assessment tools and to provide transparency of the assessment methodology applied in future costing studies.
In the present study, a focus was put on components of productivity losses that can be validated by an objective data source (sick leave and work disability), reducing the perspective to societal relevant indirect costs. The productivity losses experienced by housewives or retirees due to impaired daily activities are important components of individual indirect costs (20), but the inclusion of these aspects was not intended in the present investigation. However, the patients not gainfully employed are included in the present analysis, because the adequacy of their reports concerning the components of productivity costs investigated are relevant to determine the validity of patient-reported cost data.
The real overall productivity losses might be underestimated to a certain extent because the questionnaire focuses on sick leave periods that are certified by a physician. Sick leave periods <3 consecutive days do not have to be certified by a physician. However, according to the objective of the present investigation, the data collection is aimed at assessing clearly defined and comparable cost components to evaluate the adequacy of patient-reported data.
The patient′s consent to obtain data from the health insurer was given prior to the study and prior to the completion of the questionnaires. It is quite unlikely that while answering the questionnaires, the patients were aware that the data collected by the questionnaire were to be compared with the insurer data because the economic data assessment was only a part of the complete clinical outcomes assessment. Still, a reporting bias cannot completely be ruled out.
For the comparison of overall productivity costs due to sick leave and work disability with earlier cost-of-illness studies applying the human capital approach and the societal perspective, a detailed discussion of the samples and the methodology is necessary. In the present study, overall productivity costs amount to ∼€2,500 applying the human capital approach. McIntosh (21) reports ∼€3,500, and Kobelt et al (22) report €5,600 per patient and year. Because both other studies have applied models or assumptions for cost estimation based on average data, the differences might be explained by this methodologic reason. Cost estimation of productivity losses based on patient data has been carried out by Clarke et al (23), Magnusson (24), and Merkesdal et al (25), and renders annual indirect costs of €1,330, €17,860, and €10,590, respectively. The result of the study of Clarke et al (23) is extremely low due to the fact that the sample had a high average age of >60 years. Magnusson (24) employed a higher valuation standard compared with the study by Merkesdal et al (25), leading to higher overall indirect costs, but comparing the number of lost productivity days and the sample characteristics, the results of these studies are comparable. In the present study, the amount of productivity losses is lower. This might be related to the fact that all of the patients received optimal specialist treatment before and throughout the study. However, there might be several other reasons leading to deviations of cost estimations, such as different social security systems or different characteristics of study samples.
According to recent methodologic work on indirect cost assessment (19), the friction cost method is recommended. For a better comparability with existing cost-of-illness studies, the human capital approach has been employed alternatively. The productivity losses counted by each approach are reported separately in order to render physical units that can directly be compared with other indirect cost evaluations.
The comparison of patient and insurer data on overall productivity costs and correlation analyses shows that patients are reporting their productivity losses adequately. Only minor deviations can be detected; these have been investigated separately. Identification of systematic failures of the patients′ estimate of productivity losses might help to further improve the assessment methodology.
Although the productivity losses appear to be reported adequately by means of the HEQ-RA in general, there are some limitations of the questionnaire. It has become obvious that patients tend to underestimate the length and number of sick leave periods due to RA (3). In the present investigation, the major reason for this underestimation is sick leave cases not mentioned by the patients. Underestimation of the length of these periods is of minor relevance. Cross checking the data of the HEQ-RA and the insurer's statements about the changes of work disability status within the observation period reveals that 2 patients are reporting RA-related work disability though being gainfully employed. Because both patients reporting work disability did so within the last 3 months of the observation period, a possible reason for the differing data might be that they recently stated disability claims that have not been decided on.
Further improvement of the assessment of productivity losses due to sick leave might be achieved by shortening the recall period. But because the recall period of the HEQ-RA is very short already (3 months), an increase of effectiveness by more frequent data assessment could only be achieved by patient diaries. Such diaries have been employed in other studies, but accompanying problems of this method have to be taken into account. The transfer of the patients′ answers into physical cost units in a database becomes more complicated.
To improve the data on work disability status, a more detailed question about different reasons for work disability and an additional item to check whether work disability was claimed should be added to the HEQ-RA and should be explained to the respondent. Improvement of these 2 issues would probably lead to closer corresponding results.
In summary, the assessment of indirect cost data by the patient questionnaire HEQ-RA has proven to be a valid method to assess disease-related productivity losses in RA because the patients report their productivity losses adequately. Additional assessment of productivity losses and health care utilization should be considered in future RA outcome studies because valid cost estimation is feasible.