Abstract
Background
In Italy, the project on the social burden and quality of life (QoL) of patients with haemophilia investigates costs from a society perspective and provides an overview of their quality of life. Moreover, as life expectancy increased in recent years along with new treatment strategies implemented in the last decades, it analyses trends of costs other than drugs simulating impacts during patient whole life.
Material and methods
We ran a web-based cross-sectional survey supported by the Italian Federation of Haemophilia Societies in recruiting patients with haemophilia and their caregivers. We developed a questionnaire to collect information on demographic characteristics, healthcare and social services consumption, formal and informal care utilisation, productivity loss and quality of life. In particular, quality of life was assessed through the EuroQoL tool. Last, we applied the illness cost method from a society perspective.
Results
On average, quality of life is worse in adult patients compared to child and caregivers: more than 75% of adult patients declare physical problems, 43% of adult patients and 54% of their parents have anxiety problems. Assuming a society perspective, the estimated mean annual total cost per patient in 2012 is 117,732 €. Drugs represent 92% of total costs. Focusing on costs other than drugs, each additional point of EuroQoL tool implies a costs’ reduction of 279 €. The impact of age varies across age groups: each added year implies a total decrease of costs up to 46.6 years old. Afterwards, every additional year increases costs.
Discussion
Quality of life of patients with haemophilia and their caregivers improved and it influences positively on consumed resources and on their contribution to the social-economic system. Costs other than drugs for patients with haemophilia follow the same trends of general population.
Keywords: quality of life, cost of illness, haemophilia
Introduction
Haemophilias are a group of inherited bleeding disorders caused by an X-chromosome linked deficiency in coagulation factors VIII (FVIII) (in haemophilia A) or IX (FIX) (in haemophilia B). The disorders are rare affecting approximately 1 in 10,000 births1.
The prevalence in Italy, according to the most recent report (2012) of the Italian Association of Haemophilia Centres that operates a national registry, consists of 3,690 patients with haemophilia A and 750 with haemophilia B2,3. The use of factor replacements has significantly decreased the mortality and morbidity of patients with haemophilia: life expectancy has increased from 40 years old in the 1960s to 60–70 years today4,5. Quality of life (QoL) has become an important measure of the health improvements in haemophilic patients brought about by therapeutic progress in this field, although it remains significantly poorer as compared with QoL of general population6,7. Specifically, QoL is viewed as a measure of the outcome of care for individuals with haemophilia that can inform disease management and policy decision making8. It is not known, however, whether changes in QoL can have an impact on costs trend in the case of haemophilia9. Last, while there are several studies on QoL in haemophilia10–12, there have been very few on caregivers QoL13–15.
On the other hand, the diffusion of new treatment strategies, based not only on factor replacement therapy, but also on a switch from the on demand to prophylaxis treatment, has also an economic impact. Actually, it requires a dramatic increase of economic resources’ consumption by a small portion of the population affected by a rare condition and therefore the third-payers interest on this disease is also increased. In particular, it is an example of the socioeconomic impact of biotechnology in rare diseases16. Hence, the scientific literature considering economic aspects has focused mainly on the cost-effectiveness of prophylaxis vs on-demand treatment in patients with a severe haemophilia17,18 or with inhibitors19. A further set of manuscripts implements a cost of illness approach on haemophilia in different countries and in some cases the economic and the social burden of this disease is included20–23. Moreover, amongst the latter ones, only one study21 have addressed in some way the relationship between age and QoL on one side, and costs on the other side. This is, actually, a new perspective arisen from the life expectancy increase in these last years.
In the early 2000s, seminal contributions concerning the Italian context provided direct healthcare costs evaluation for patients with haemophilia complicated by inhibitors in the Cost of Care Inhibitors Study16 and the first estimation of the QoL of patients without inhibitors in the Cost of Care of Hemophilia Study24.
The Burden and Health-Related Quality of Life in Patients with Rare Diseases - BURQoL-RD Study was a 3 year project under the 2nd Programme of Community Action in the Field of Public Health, that commenced in April 2010 and was promoted by the Directorate General Health and Consumers of European Commission. The main aim of BURQoL-RD was to generate a model to quantify the socio-economic costs and QoL of both patients and caregivers, for up to 10 rare diseases (RD) in different European countries. According to this goal, the evaluation of the economic and social impact of haemophilias has been one of the objects of BURQoL-RD Study.
Therefore, the BURQoL-RD Study on haemophilia in Italy investigates costs of this disease from a society perspective (using a cost of illness approach) for the first time and it provides an update of this group of patients’ QoL. Moreover, considering the increase of life expectancy occurring in these last years, it analyses the impact of this trend on costs other than drug, simulating the whole life cycle. Last, as the expensive switch of treatment strategies implemented in the last decade has provided an increased QoL, we are going to test this improvement’s impact on costs other than drugs.
Materials and methods
We conducted a web-based cross-sectional study. The target sample were Italian patients diagnosed with haemophilia A and B and their caregivers. Cases were recruited from the Italian Federation of Haemophilia Societies (Federazione delle Associazioni Emofilici, FedEmo, www.fedemo.it). All patients and caregivers were informed about the study objectives and data confidentially, and were asked to indicate their understanding of the study conditions and agreement to participate. The survey was anonymous, as the patients were contacted by their patient organisation and their responses, without any identification data, were sent directly to the researchers. The fieldwork was carried out between March 2012 and October 2012. The questionnaires were administrated by e-mail through patient organisations and patients were asked to provide information on demographic characteristics, consumed healthcare and non healthcare resources related to the disease and QoL information in the six months preceding the enrolment (12 months for hospital admissions).
Costs’ materials and methods
To measure the burden of haemophilia, we have applied the cost of illness approach from a society perspective25. Therefore, both direct and indirect costs were included, and a bottom-up approach was used for their calculation: we valued the average unit cost of each set of resources consumed by enrolled patients.
Direct costs include health and non-healthcare resources directly consumed by the surveyed Italian patients with type A and type B haemophilia in 2012.
Direct health care costs include drugs, outpatient and inpatient care, and all range of primary care services. As far as their data source, we used services’ fees because Italy does not have a national healthcare services’ costs data set and we could not run specific costs’ survey. However, we applied region Lombardy’s fees as this region has updated nearly regularly its tariff set, surveying its providers’ costs26. Moreover, as far as drugs, we have considered Italian Medicines Agency ‘s drugs national formulary, reducing by 30% the price of drugs distributed only by hospitals once they bought them through tenders. Considering the co-payment of drugs and outpatient care, we estimated a national average of regional fees. Last, according to the following strategy, we estimated the healthcare services fees out of Italian National Health Service (INHS), paid out of pocket by patients: we selected a small and a big town in Northern, Centre and Southern Italy and then we ran a pricing market analysis.
Direct non healthcare costs comprise social-healthcare and social services managed at city-council level: the resulting high fragmentation of these services’ provision has led us to implement again the above described strategy to collect information on this setting without national or regional standards. This cost’s set includes not only the formal care (i.e. provided by contracted professionals), but also the informal care provided by relatives and friends. We have applied the proxy good approach to value these resources, then we have considered if he/she did not provide these services, he/she would need to be replaced by another person who could provide the necessary care, applying the average hour wage of contracted professionals27.
According to evidences provided by literature on different amount of consumed resources by adults and children, we have differentiated costs analysis between these two populations.
Indirect costs refer to the output lost by society because of cessation or reduction of productivity (i.e. productivity loss) resulting from morbidity, or disability brought on by the disease. We have collected the following information about patients and caregivers through the questionnaire: i. the working days and the hours per day lost because of disease, and ii. the age of their possible early retirement. Therefore, we have estimated the productivity loss of both patients and caregivers, considering both the sick leaves of both patient and caregiver as well as the economic impact of an early retirement. We have applied the human capital approach28, valuing the amounts of days and hours of sick leaves by the per hour Italian average wage, according to 2012 Eurostat estimation. Moreover, we have estimated the charge of early retirement by valuing the lost gain from retirement contributions of the working years out of the job market according to Eurostat, and the public expenditure because of the early pension’s provision based on National Social Insurance Agency (INPS - Istituto Nazionale della Previdenza Sociale) data set.
QoL’s materials and methods
EuroQoL (EQ-5D) was adopted to evaluate the QoL. EQ-5D is applicable to a wide range of medical conditions and treatment and generates a health profile (EQ profile) consisting of 5 domains (mobility, self-care, anxiety/depression, usual activities, and pain/discomfort). For adult and caregivers EQ-5D-5L with 5 levels (“no problem”, “some or moderate problems”, “extreme problems/impossible to do”) was administrated. For children (under 18 years old), the EQ-5D-Y-3L (children version) with 3 level was used (“no problems”, “some problems”, “extreme problems”). A visual analogue scale (EQ-VAS) scores the overall QoL from 0 (the worst imaginable health status) to 100 (the best imaginable health status). Results from the EQ profile can be converted to utility index, suitable for economic evaluations, by means of an algorithm that uses population-based (social) values. Because specific conversion values for the Italian population are not available yet, we have converted our EQ profile results in EQ utility index, running the algorithm with values from Spain29.
Statistical analysis
Since it was planned to enrol all patients with haemophilia registered in FedEmo’s patients organisations, no sample size calculation was performed. For cost analysis we used means and central tendency parameters, generally expressed as mean cost per patient per year, because this parameter can be easily used for policy maker. We reported the standard deviations as a variability measure. Costs were stratified according to their categories. Descriptive analyses were applied also to define health status measurements variables and QoL separately for adult, children and caregivers. It was convenient to reclassify the EQ-5D-5L and EQ-5D-Y-3L levels into ‘no problems’ (i.e. level 1) and “problems” (i.e. levels 2 to 5 for EQ-5D-5L and level 2 to 3 for EQ-5D-Y-3L). For categorical measures, statistical significance was determined by using chi-squared test. The one-way analysis of variance (ANOVA) was used to determine whether there were any significant differences between the means of two or more independent (unrelated) groups. Intra class correlation between ranked (ordinal) data, such as EQ-5D, was determined by means of Spearman’s correlation coefficients (correlations >r=0.4 were considered relevant).
A multiple linear regression was ran in order to assess the relationship between the patients’ total costs without drugs (dependent variable) and patients’ age and EQ-5D. We tested a possible non-linear (quadratic) relationship for both independent variables and we controlled for drugs costs and age of diagnosis. Moreover, based on estimation results, we ran a two-way simulation analysis to evaluate the joint impact of every pair of age and EQ-5D on costs, all other things being equal. We let both independent variables to range between 0 and 100 in order to capture every possible combination of the two, also including out-of-sample values. Descriptive analyses were performed using SPSS version 21.0 software. Regression analysis and two-way simulation analysis were performed using Stata, release 12. Statistical significance was set up at p<0.05 where sample size permitted.
Results
Characteristics of the sample
A total of 134 questionnaires were collected, 45 of which were excluded because of insufficient or inadequate provided information. The valid sample consisted of 89 patients and 17 caregivers.
The mean age was 42.3 (SD±13.0;) years old for adults, 8.0 (SD±4,6) for children and 40.7 (SD±16.0) for careers. Only 3 patients more than 65 years old were enrolled in this study. The main characteristics of patients are shown in Table I.
Table I.
Socio-demographical sample characteristics of patients.
| Patient sample (n=89) | Value |
|---|---|
| Age, n (%) | |
| Child (2–17 years old) | 22 (24.7) |
| Adult (≥18 years old) | 67 (75.3) |
|
| |
| Frequency, n (%)1 | |
| Patients with Haemophilia A | 71 (79.8) |
| Patients with Haemophilia B | 15 (16.9) |
|
| |
| Married/with a partner2 | 60 (90.9) |
|
| |
| Education level | |
| Medium-high (for adult patients) | 55 (82.1) |
| Schooled in an ordinary centre (for children 7–17 years) | 13 (100) |
|
| |
| Need for career n (%) | 21 (23.3) |
|
| |
| Employment status (for adult patients) n (%) | 40 (59.7) |
Three values were missing;
Calculation is made only for adult.
The majority of patients were adults (75.3%) with haemophilia A (79.8%). Ninety-nine per cent of adult patients were married. 82% of patients had a medium-high educational level. Sixty percent of adult patients were employed at the moment of the survey (Table I).
QoL results
On average, QoL was worse in adult patients compared to child and career according to EQ-VAS (ANOVA; p=0.000) (Table II).
Table II.
EQ-VAS value and EQ utility index by different study group categories.
| N. | Mean EQ-VAS (DS) | EQ utility index (DS) | P value | |
|---|---|---|---|---|
| Child | 13 | 92.8 (7.5) | 0.78 (0.43) | 0.0000 |
| Adult | 60 | 68.7 (18.8) | 0.69 (0.25) | |
| Caregivers | 16 | 83.1 (14.9) | 0.95 (0.62) | |
| Total | 891 | 74.8 (19.2) | 0.70 (0.28) |
17 values are missing.
For adult patients with haemophilia, EQ-VAS score was lower than in general population (Mean=75.8; SD±16.6; Catalonian conversion values29). For children patients non value sets are available for comparison.
QOL domains by adult, caregivers and child subjects were examined at a descriptive level (Table III). More than 75% of adult patients had problems in the physical sphere, specifically for mobility (75%) and pain/discomfort (76.7%). 43.3% of adult patients and 53.9% of parents had anxiety problems. For mobility, usual activities and pain/discomfort, the proportions were significantly different between study group. No differences were verified in self-care and anxiety dimension (Table III).
Table III.
Proportion of “problem” and “no problem” by EQ dimensions and by adults, children and caregivers.
| Adult | Child | Caregivers | p value | |||||
|---|---|---|---|---|---|---|---|---|
|
|
||||||||
| n. | % | n. | % | n. | % | |||
| Mobility | No problems | 15 | 25.0 | 10 | 76.9 | 5 | 38.5 | 0.000 |
| Problems | 45 | 75.0 | 3 | 23.1 | 8 | 61.5 | ||
| Self-care | No problems | 36 | 60.0 | 12 | 92.3 | 7 | 53.8 | 0.1 |
| Problems | 24 | 40.0 | 1 | 7.7 | 6 | 46.2 | ||
| Usual activities | No problems | 22 | 36.7 | 12 | 92.3 | 7 | 53.8 | 0.001 |
| Problems | 38 | 63.3 | 1 | 7.7 | 6 | 46.2 | ||
| Pain/discomfort | No problems | 14 | 23.3 | 11 | 84.6 | 6 | 46.1 | 0.000 |
| Problems | 46 | 76.7 | 2 | 15.4 | 7 | 53.9 | ||
| Anxiety/depression | No problems | 34 | 56.7 | 11 | 84.6 | 6 | 46.1 | 0.3 |
| Problems | 26 | 43.3 | 2 | 15.4 | 7 | 53.9 | ||
Costs results
Assuming a society perspective, the estimated average annual total cost per person in 2012 is 117,731.72 € (Table IV).
Table IV.
Total and percent distribution of direct health care, non health care and indirect costs per patient with haemophilia by adult and paediatric populations, in 2012, in Italy.
| Total | Adult | Children | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
|
||||||||||||||||||
| Mean | SD | % cost category | % per total costs | Mean | SD | % cost category | % per total costs | Mean | SD | % cost category | % per total costs | |||||||
| Direct health care costs | ||||||||||||||||||
|
| ||||||||||||||||||
| Drugs | € | 107,728.30 | € | 95,866.80 | 98.14% | 91.50% | € | 100,649.80 | € | 96,513.22 | 97.58% | 92.55% | € | 130,649.40 | € | 92,257.03 | 99.57% | 88.99% |
| Tests | € | 52.89 | € | 160.56 | 0.05% | 0.04% | € | 61.91 | € | 182.30 | 0.06% | 0.06% | € | 23.67 | € | 30.45 | 0.02% | 0.02% |
| Specialistic visits | € | 880.17 | € | 1,556.10 | 0.80% | 0.75% | € | 995.99 | € | 1,747.58 | 0.97% | 0.92% | € | 505.14 | € | 479.63 | 0.38% | 0.34% |
| Primary care | € | 600.65 | € | 1,582.75 | 0.55% | 0.51% | € | 786.15 | € | 1,772.65 | 0.76% | 0.72% | € | - | € | - | 0.00% | 0.00% |
| Acute hospitalization | € | 448.72 | € | 1,510.65 | 0.41% | 0.38% | € | 587.29 | € | 1,707.27 | 0.57% | 0.54% | € | - | € | - | 0.00% | 0.00% |
| Devices | € | 54.46 | € | 137.38 | 0.05% | 0.05% | € | 59.51 | € | 139.51 | 0.06% | 0.05% | € | 38.10 | € | 132.20 | 0.03% | 0.03% |
| Healthcare transportation | € | 3.51 | € | 21.32 | 0.00% | 0.00% | € | 4.59 | € | 24.34 | 0.00% | 0.00% | € | - | € | - | 0.00% | 0.00% |
|
| ||||||||||||||||||
| Subtotal | € | 109,768.70 | € | 96164.64 | 100% | 93.24% | € | 103,145.24 | € | 103,145.24 | 100% | 94.85% | € | 131,216.30 | € | 92,400.97 | 100% | 89.38% |
|
| ||||||||||||||||||
| Direct non healthcare costs | 0.00% | 0.00% | 0.00% | |||||||||||||||
|
| ||||||||||||||||||
| Social services | € | 158.72 | € | 535.39 | 3.04% | 0.13% | € | 191.26 | € | 601.42 | 5.82% | 0.18% | € | 53.33 | € | 185.08 | 0.46% | 0.04% |
| Caregiver’s time costs (informal care) | € | 4,959.92 | € | 22,419.95 | 94.96% | 4.21% | € | 2,961.57 | € | 21,092.40 | 90.15% | 2.72% | € | 11,430.80 | € | 20,629.49 | 99.41% | 7.79% |
| Main caregivers | € | 4,534.76 | € | 20,153.44 | 86.82% | 3.85% | € | 2,961.57 | € | 21,092.40 | 90.15% | 2.72% | € | 9,628.92 | € | 16,157.54 | 83.74% | 6.56% |
| Secondary caregivers | € | 425.16 | € | 2,266.51 | 8.14% | 0.36% | € | - | € | - | 0.00% | 0.00% | € | 1,801.88 | € | 4,471.95 | 15.67% | 1.23% |
| No healthcare transportation | € | 104.43 | € | 231.59 | 2.00% | 0.09% | € | 132.24 | € | 258.96 | 4.03% | 0.12% | € | 14.40 | € | 14.52 | 0.13% | 0.01% |
|
| ||||||||||||||||||
| Subtotal | € | 5,223.08 | € | 20,815.10 | 100% | 4.44% | € | 3,285.07 | € | 21,237.26 | 100% | 3.02% | € | 11,498.54 | € | 18,475.38 | 100% | 7.83% |
|
| ||||||||||||||||||
| Total direct costs (Direct HC Costs and Direct Non HC costs) | € | 114,991.78 | 97.67% | € | 106,430.31 | 97.87% | € | 142,714.84 | 97.21% | |||||||||
|
| ||||||||||||||||||
| Indirect costs | 0.00% | 0.00% | 0.00% | |||||||||||||||
|
| ||||||||||||||||||
| Loss of labour productivity patients (sick leave and early retirement) | € | 1,748.56 | € | 4,495.55 | 63.82% | 1.49% | € | 2,288.55 | € | 5,028.93 | 98.64% | 2.10% | € | - | € | - | 0.00% | 0.00% |
| Loss of labour productivity carers (sick leave and early retirement | € | 991.38 | € | 5,904.85 | 36.18% | 0.84% | € | 31.46 | € | 259.42 | 1.36% | 0.03% | € | 4,099.70 | € | 11,828.46 | 100% | 2.79% |
|
| ||||||||||||||||||
| Subtotal | € | 2,739.94 | € | 7,241.01 | 100% | 2.33% | € | 2,320.01 | € | 5,132.52 | 100% | 2.13% | € | 4,099.70 | € | 11,828.46 | 100% | 2.79% |
|
| ||||||||||||||||||
| Total costs | € | 117,731.72 | € | 98,013.37 | 100% | € | 108,750.30 | € | 96,133.36 | 100% | € | 146,814.60 | € | 100,733.90 | 100% | |||
The set of direct healthcare costs is the main driver requiring yearly in average 109,768.70 € per person: specifically, the item drugs is the 98% of this latest and the 92 % of the whole cost in absolute value. The children annual average costs of drugs is higher than adults (130,649.40 € vs 100,649.80 €). Moreover, as we have a very high standard deviation, we have set classes of average annual costs: in this perspective, the 55% of children patients have a drugs cost greater than 200,000 € vs the 38% of adult patients.
Excluding haematologic visits, adults (29% is 49 years old over) required an average of 3.89 specialist visits in six months while children needed 2.04 specialist visits in the same period of time. Adults most often required specialist visit by cardiologist, surgeon, orthopedist and dentist. Both adults and children shared a high level of access to physiotherapy sessions (data not shown).
Direct non healthcare costs (in average 5,223.08 €) represent the 4.4% of the total costs -in absolute values- and the most relevant category is the informal care (95%). Specifically, the 23.6% of hemophilic patients surveyed state a need of care and -except one- all of them have an informal care: specifically, the 57% of children require this service vs the 13% of adult patients, moreover these latest do not need a secondary caregiver. As not all caregivers of adult patients provided the required data to value their time, the related results give poor information. Therefore, we focus on children informal care: in this case, the annual average cost of the main caregiver is 9,628.92 € and that one of secondary caregivers is 1,801.88 €.
As far as the other items of non healthcare costs, these include social services and non healthcare transport which represent respectively the 3% and the 2% of total costs. In this case, adults are the greater consumer of these services.
Lastly, indirect costs include the loss of productivity by patients and caregivers because of sick leave or early retirement. Thirty-four percent of the patients interviewed stated that their labour productivity had decreased in the previous six months because of the disease: specifically, they had an average 38 days of sick leaves a/o they worked in average two hours less per day. Moreover, the 58% of the retired patients did it earlier than the proper retirement age. As far as caregivers, the average number of lost working days was 78 in the previous six months and the average lost working hours were daily 4. Therefore, the annual average value of productivity loss is 2,739.94 € (2% of total costs). This aggregated value requires also to be differentiated between adults and children as the main cost driver of the earliest group is the productivity loss of patients (98%) while the main one of children is of course the productivity loss of caregivers equal to the annual average value of € 4,099.70.
The regression of costs without the drugs item on a set of independent variables already described allows us to investigate on the relationship running between the total costs and patients’ age and Qol, controlling for drugs’ costs and age of diagnosis (Table V).
Table V.
Correlation between EQ 5D, total costs, patients’ age, age of diagnosis, and total costs other than drugs: multilinear-regression model (n=68)*.
| Independent variable | Coefficient | Standard error | t | P value | 95% Confidence Interval |
|---|---|---|---|---|---|
| EQ 5D | −279.4714 | 64.77232 | −4.31 | 0.000 | −408.9916; −149.9511 |
| Drugs costs | .0004994 | .0093903 | 0.05 | 0.958 | −.0182777; .0192765 |
| Patients’ age | −618.0774 | 208.6071 | −2.96 | 0.004 | −1035.213; 200.9416 |
| Squared patients’age | 6.636786 | 2.776952 | 2.39 | 0.020 | 1.083927; 12.18964 |
| Age of diagnosis | −154.6141 | 138.5862 | −1.12 | 0.269 | −431.7343; 122.506 |
Prob>F=0.0000; Root MSE=6682.3; F(6, 61)=7.56; R-squared=0.3102
The relationship between EQ-5D and costs without drugs is linear (the quadratic term is not significant) while the quadratic hypothesis is supported for age. In particular, whatever the age, each additional point of EQ-5D implies a reduction in costs of 279 €. A within-sample simulation based on this regression shows that in our sample the 95% confidence interval of EQ-5D is 68.39–77.55, implying a cost-variability of 2,556 €, after controlling for age. Considering the impact of age, whatever the level of EQ-5D, the effect varies across age levels. Starting from an age of 0, an increase by one year implies a cost reduction of 618 €. However this impact is attenuated by 13.27 € every additional year of starting. Therefore the effect of an additional year between an age of 3 and 4 is obtainable from the first order derivative calculated at 3 year and which is −618 € +(3 years×13.27 €)= −578 € (where 13.27 = 2×6.64, the coefficient of the squared term). The minimum point of the parabola is found at the age of 46.6 years old. After that point the impact of age becomes positive, i.e. every additional age makes costs increase. For example, the impact of an additional year between the ages of 55 and 56 is −618 €+(55 years×13.27 €)= +112 € (Figure 1).
Figure 1.
Trend of costs other than drugs correlated to QoL and age.
Discussion
The BURQoL-RD study on haemophilia provides an update of patients’ QoL, and for the first time in Italy offers an estimation of average total unit cost in the society perspective. This study also shows that there is a significant relationship between both age and QoL, and costs other than drugs. Moreover, our results are consistent with literature on drugs as the main cost driver of haemophilic patients’ expenses.
These results are relevant because they contribute to further analyse two evidences highlighted by the scientific literature: the treatment strategy’s change that occurred in these last years (i.e. the switch from on-demand to prophylaxis based treatment and the factor replacement) and the increase of patients’ QoL and life expectancy provided by a greatly improved patient’s management.
We have used the overall costs other than drugs because of three reasons. Firstly, the BURQoL-RD project provides data on drugs consumption and their valorisation, however information on patients’ severity and the related treatment plans are not available, restricting the possible interpretation of drugs’ data. Secondly, the core of the treatment strategy’s change is the switch from on-demand to prophylaxis based treatment along with new drugs’ use: this substitution may imply that the patient’s consumption of drugs does not change for long whiles, making drugs’ cost no more a fully variable cost over time. Last, even if costs other than drugs represent a small quota of total costs, they have been poorly investigated up to now and their analysis allows to enlighten relevant aspects with respect to the trends we are addressing.
The first evidence to consider is the positive impact of new treatment’s strategies on patients’ QoL: this is a consolidated evidence in both type A and B haemophilia30,31 even if it implies a relevant increase of costs and the debate on the related cost-effectiveness, usually in a third-payer perspective, is still open32. Hence, as we have in hand both direct and indirect costs of this Italian patients’ sample, we have tested the impact of a possible QoL improvement on this set of costs, excluding the drug ones: this is a step towards estimating how much the new drugs’ greater costs are offset by a decrease of other costs’ items33,34. The result is that every EQ-5D point added implies a quota of decreased total costs other than drugs: therefore, an improved QoL has an impact not only on the patient’s life, but also on consumed healthcare and non healthcare resources related to the disease by these patients and on their capacity to contribute positively to the social-economic system where they live.
The second evidence concerns the increased life expectancy that also Italian haemophilic population has experienced2. Specific guidelines and clinical pathways to manage the comorbidities, complications and management aspects are needed now that haemophiliac patients’ are getting older35–37. However, it seems that poor attention has been paid to the impact on costs of this aging process. Hence, we have found a significant relationship between age and total costs other than drugs and moreover we have simulated the trend of this set of costs over the patients’ whole life cycle. The main finding is that costs other than drugs for haemophilic population follow the same trend of the general population38 or people with diabetes39: costs are at their highest level in the very first years of life and then they decrease up to the age of nearly 46 years old when they start to increase again. Moreover, we have identified the main driver of costs other than drugs according to the population age: as far as children, the most relevant item of cost is the informal care provided by parents and their related productivity loss that it had never been estimated previously in Italy. In adults, the driver is not only hospitalisation, but also specialist visits including a significant quota of cardiology, dentist and ophthalmologist visits, and these results are consistent with the literature above mentioned.
Although this study provides valuable insights into the QoL and the costs of patients with haemophilia and their caregivers, there are some limitations that warrant mention. Both the sample and the recruitment process limit the external validity of the study. A limit of this study is the costs’ data source. As far as healthcare services provided by INHS, we have valued them by tariffs which are a costs’ proxy, however we have selected the Region Lombardy’s ones as they are the most regularly updated according to costs’ surveyed at providers. A further problem has been to identify the fees of services provided out of INHS coverage: unfortunately, there are not updated price lists determined by professionals associations and then we resorted to a sort of market survey. A similar difficulty has risen about the social services supplied by the city councils and possibly by Local Healthcare Units when an healthcare expertise is required: the fragmentation level prevents to provide any national or regional average. Therefore, we have implemented a spot survey considering the geographical variability and the size of the city council involved.
A further drawback of the study is that the disease severity and treatment were not recorded, limiting our ability for additional stratification by variables of interest. We categorize participants only in terms of disability level. Considering the low level of disability, probably our sample reflects a more motivated and less disabled patient/caregiver population.
As BURQoL-RD project comprised other RDs and aimed to possible comparison with general population, to measure the QoL we did not use disease specific instruments for haemophilia.
Conclusions
The BURQoL study on Italian haemophilic patients provides the first estimation of total costs in the society’s perspective that can be of value to policy-makers. The QoL increase in haemophilic patients implies both a life’s improvement and a decrease in the overall costs other than drugs: even if we do not have yet evidence that the new drugs’ increased costs may be offset by the other costs’ reduction, the drugs’ costs extent over the total ones suggests that only a partial offset might be possible. A second evidence concerns the charge’s level of informal care supplied to haemophilic children and the related loss of productivity of informal carers that has to be considered. Finally, the ageing of haemophilic population beyond previous life expectancy limits is posing new challenges to the health care systems requiring planning of resources and health care provisions.
Footnotes
The Authors declare no conflict of interest.
Funding and resources
This deliverable arises from the project “Social Economic Burden and Health Related Quality of Life in Patients with Rare Diseases in Europe” which has received funding under the 2nd Programme of Community Action in the Field of Public Health.
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