Advancing the Responsible Use of Medicines in Belgium

Transcription

IMS Health Report
Advancing the Responsible Use
of Medicines in Belgium
Applying Levers for Change
Executive Summary
Pharmaceutical innovation is an obvious and important contributor to the health of a society, but in
times of economic constraint, payers often have difficulty taking full advantage of it. According to an
IMS Health analysis (data on file), Belgium has thus far been able to maintain the levels of spending
on innovative drugs that it enjoyed prior to the economic crisis that began in 2008. The analysis
covered spending per capita over the periods 2005 to 2009, and from 2010 to 2014.
Indeed, over the past five years, Belgium has maintained its position as one of the four EU countries
spending the most on innovative drugs per capita. Meanwhile countries where the economic crisis has
had a major impact (such as Spain, Ireland, Greece, and even France) have slipped in the ranking.
Yet, ensuring that Belgium continues to be able to offer innovation to its people will require the
efforts of all stakeholders.
Within the current economic climate, promoting responsible use of medicines should be a key priority
for health policymakers. In this context, IMS Health calculated the potential for savings that could
be realized from how drugs are used—savings that could then be reinvested in covering innovative
drugs. A clear and simple methodology was used to analyse the potential for cost savings in four areas:
•• ➢Low adherence to statins therapy
•• ➢Inappropriate and over-prescribing of antidepressants
•• ➢Over-prescribing of antibiotics
•• ➢Hospitalizations due to medication errors
Note that the analysis was limited to these four topics because the methodology was simple and
straightforward; this is by no means an exhaustive list of the areas where savings might be achieved.
This report should serve to open a dialogue on the subject and to spur other stakeholders to
investigate additional potential sources of potential savings.
Overall, the study revealed that potential savings could reach
an estimated 1.5 - 1.6% of Belgium’s total annual healthcare
spending. In absolute values, this represents over €400Mn
annually that could be invested in funding innovative treatments,
broadening access restrictions to specific drugs, implementing
prevention programs, and modernizing hospital infrastructures, etc.
IMS Health Report: Advancing the Responsible Use of Medicines in Belgium
Page i
EXECUTIVE SUMMARY
Low adherence to statins therapy
It is generally accepted that drugs are less efficacious when patients do not adhere to the prescribed
treatment regimen, leading to more medical complications and greater costs. For example, poor
adherence to cardiovascular treatment has been shown to contribute to poor health outcomes with a
faster onset of co-morbid conditions. This, in turn, increases the economic burden of disease since
other medical resources are consumed at higher rates (e.g. hospitalizations for acute events) (Sokol,
2005; McDonnell, 2002; Senst, 2001). We estimated that €126Mn to €151Mn in annual hospitalization
costs could be avoided in Belgium simply by increasing compliance levels to 90% in the statins
market. The cost of treatment with statins would increase an estimated €68Mn a year, so the real
savings are between €57Mn and €82Mn. This point is illustrated with statins, but a similar case could
be made for improving adherence to antihypertensives as well as all other chronic treatments.
Inappropriate and over-prescribing of antidepressants
Western societies tend to have common issues around properly diagnosing and treating mental
illness. While the use of antidepressive medication is increasing worldwide, it is particularly high in
Belgium, where suicide rates are among the highest compared to the other European countries. Yet,
the country’s utilization rates of antidepressants may reflect a combination of underuse, miss-use,
and even over-use. By comparing Belgium’s prescription patterns to those of neighbouring countries,
France and the Netherlands, we estimated that the potential avoidable cost from antidepressant
miss-use/over-use is approximately €67Mn to €70Mn annually.
Given this insight, national policies should be focused on the quality of prescribing in depression,
on controlling the inappropriate use of antidepressants, and on providing alternative solutions to
drug therapies. As an example, occupational therapy and physical activities could be integrated into
nursing homes and community service centres to promote the wellbeing and mental health of elderly
individuals. Additionally, psychotherapy performed by psychologists could also be reimbursed to
support the improvement of mental health indicators.
Over-prescribing of antibiotics
The misuse of, and resulting resistance to, antibiotics has been identified as a major, worldwide
public health concern. In Belgium, where several national programs have been launched since 2000,
outpatient antibiotic use has decreased by 36% in terms of the number of packages sold. However,
Belgians still consume many more antibiotics as outpatients than do their counterparts in other
EU countries. We calculated that each individual in Belgium takes, on average, 12.66 antibiotic pills
per year, which is twice the amount in the Netherlands. Our research showed that were prescribing
behavior in Belgium to mirror that in the Netherlands, the country’s drug bill would be reduced by
more than €70Mn a year. This estimate does not take into account the additional health and cost
consequences of antibiotics resistance related to the overuse of antibiotics.
Hospitalizations due to medication errors
Medication errors are a preventable event that may lead to patient harm, and consequently, to costs.
We estimated that based on Dutch sources, medication errors in Belgium could have been the cause
of over 42,000 hospital admissions each year. The projected economic annual burden of avoidable
medication errors was more than €200Mn. Measures to avoid medication errors are needed, however,
it should be acknowledged that not all errors can be avoided.
Page ii
List of Abbreviations
Abbreviation
Description
ACE-inhibitor
Angiotensin-converting-enzyme inhibitor
APR-DRG All Patient Refined Diagnosis Related Groups
ARHAI
Antimicrobial Resistance and Healthcare-associated Infections
ATC
Anatomical Therapeutic Chemical Classification System
CBIP/BCFICentre Belge d’Information Pharmacothérapeutique/Belgisch Centrum voor
Farmacotherapeutische Informatie
BAPCOC
Belgian Antibiotic Policy Coordination Committee
CDC
Centers for Disease Control and Prevention
COPD
Chronic obstructive pulmonary disease
CVD
Cardio-vascular
DALYs
Disability-adjusted life years
DDD
Defined Daily Dose
EARS-Net
European Antimicrobial Resistance Surveillance Network
ECDC
European Centre for Disease Prevention and Control.
EMA
European Medicines Agency
EPIS
Epidemic Intelligence Information System
ESAC-Net
European Surveillance of Antimicrobial Consumption Network
EU
European Union
EUROASPIREEuropean Action on Secondary and Primary Prevention by Intervention to
Reduce Events
GIS
Great Influenza Survey
HARM
Hospital Admissions Related to Medication
ICD
International Classification of Diseases
IHME
Institute for Health Metrics and Evaluation
ILI
Influenza like illness
LDL Low-density lipoprotein
MRSA
Meticillin resistant Staphylococcus aureus
NSIPH
National Scientific Institute of Public Health
QALY
Quality Adjusted Life Year
REACH
Reduction of Atherothrombosis for Continued Health
RIZIV/INAMI RijksInstituut voor Ziekte- en InvaliditeitsVerzekering/Institut National
d’Assurance Maladie-Invalidité
UK
United Kingdom
US
United States
WHO
World Health Organization
YLDs
Years of healthy life lost due to disability
YLLs
Years of life lost due to premature mortality
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Contents
1 Introduction.................................................................................................................................................................................. 1
2Report........................................................................................................................................................................................................3
2.1 Low adherence to statins therapy............................................................................................3
2.1.1Background............................................................................................................................................................................................... 3
2.1.2 Methods: quantification approach................................................................................................................................................... 4
2.1.3 Results: estimated avoidable costs................................................................................................................................................. 5
2.1.4Conclusions.............................................................................................................................................................................................. 7
2.2 Inappropriate and over-prescribing of antidepressants......................................................7
2.2.1Background............................................................................................................................................................................................... 7
2.2.2 Methods: quantification approach.................................................................................................................................................. 10
2.2.3 Results: estimated avoidable costs................................................................................................................................................. 11
2.2.4Conclusions..............................................................................................................................................................................................14
2.3 Over-prescribing of antibiotics................................................................................................15
2.3.1Background...............................................................................................................................................................................................15
2.3.2 Methods: quantification approach...................................................................................................................................................16
2.3.3 Results: estimated avoidable costs.................................................................................................................................................17
2.3.4Conclusions.............................................................................................................................................................................................20
2.4 Hospitalizations due to medication errors............................................................................20
2.4.1Background..............................................................................................................................................................................................20
2.4.2 Methods: quantification approach...................................................................................................................................................21
2.4.3 Results: estimated avoidable costs................................................................................................................................................22
2.4.4Conclusions.............................................................................................................................................................................................23
3 General conclusions.......................................................................................................................................... 24
4Authors................................................................................................................................................................................................26
5References................................................................................................................................................................................ 27
6Annex..................................................................................................................................................................................................... 37
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List of Tables
Table
Description
Page
Table 1Estimated avoidable costs of hospitalizations due to non-adherence compared to 80-100% patient adherence
6
Table 2Estimated anti-depressants prescription costs in Belgium, France and The Netherlands
11
Table 3Estimated additional costs of anti-depressants use in Belgium
12
Table 4
Antibiotics consumption in Belgium and Netherlands in 2013
17
Table 5
Estimated avoidable costs due to medication errors in Belgium
22
List of Figures
Figure
Description
Page
Figure 1Adherence and risk of hospitalization on non-compliant patients
on lipid-lowering drugs
6
Figure 2
Avoidable hospital costs, higher and lower estimates
7
Figure 3
Number of patients with reimbursement for antidepressant per age category
9
Figure 4
Estimated anti-depressants cost/person
11
Figure 5
Main diagnosis and % of prescriptions for antidepressants use in Belgium, 2013
12
Figure 6
Indications for antidepressant prescription and percentage being of short duration
13
Figure 7
Antibiotics consumption in 2013, cost per person
17
Figure 8
Total antibiotics used in 2011, expressed in number of DDD per 1,000 inhabitants per day in 12 European countries and Kosovo
as compared to 29 ESAC-Net countries
17
Figure 9
Percentage of invasive (blood and cerebrospinal fluid) isolates
18
Figure 10
Indications for which antibiotics are prescribed in Belgium
19
Figure 11
Reasons for preventable hospital admissions
22
Page v
Introduction
Context
In 2012, the IMS Institute for Healthcare Informatics published a global report entitled “Advancing
the responsible use of medicines - Applying levers for change.” It had been prepared for the
Ministers’ Summit organized by the Dutch Ministry of Health, Welfare, and Sport held on
October 3, 2012. The Summit, which was themed: “The benefits of responsible use of medicines:
setting policies for better and cost-effective healthcare,” was part of a wider policy engagement
agenda driven by the Dutch Ministry of Health that had been initiated in 2004 during the Dutch
Presidency of the Council of the European Union. Also, the World Health Organization (WHO)
commissioned a second report from the IMS Institute as an update to the WHO publication,
“Priority Medicines for Europe and the World - A Public Health Approach to Innovation.”
The WHO report was focused on key priorities for public health as identified in the organization’s
2004 report and updated to incorporate the latest advances in diagnostic technologies and treatments
available. Some of the key, global public health issues identified in this report were the high burden
of an aging population, coupled with the substantial health and cost burden of chronic,
non-communicable diseases1 as well as the alarming rates of increased antibacterial resistance,
tobacco use, alcohol abuse and obesity.
The IMS Institute report, on the other hand, aimed to identify key healthcare spending areas where
substantial cost savings could be achieved through better, more responsible use of medicines.
Six areas were proposed as primary levers for change:
•• Non-adherence to medicines
•• Suboptimal generic use
•• Medication errors
•• Antibiotic misuse/overuse
•• Mismanaged polypharmacy
•• Untimely medicine use
The study found that by optimizing the use of medicines, about 8% of the total (Global) healthcare
spend, or about USD $500Bn could be avoided annually and re-directed to other sectors of healthcare.
Using a similar methodology, The IMS Institute produced a follow-up report in June 2013 on the
“Avoidable Costs in U.S. Healthcare.” The quantified missed opportunity costs in the U.S. were
estimated at USD $200Bn annually. Analysts in IMS Health France have also studied non-adherence
in six chronic diseases, estimating that about €9Bn could be saved in France by improving adherence.2
1These include: ischaemic heart and ischaemic cerebro-vascular disease, depression, osteoarthritis, Alzheimer disease, hearing loss, low back
pain, chronic obstructive pulmonary disease (COPD) and alcoholic liver disease (mostly in Europe).
2http://www.imshealth.com/portal/site/imshealth/menuitem.c76283e8bf81e98f53c753c71ad8c22a/?vgnextoid=5150d58bed2a9410VgnVCM100000
76192ca2RCRD&vgnextchannel=5ec1e590cb4dc310VgnVCM100000a48d2ca2RCRD&vgnextfmt=default
Page 1
INTRODUCTION
Pharmaceutical innovation is an obvious and important contributor to the health of a society, but in
times of economic constraint, payers often have difficulty taking full advantage of it. According to an
IMS Health analysis (data on file), Belgium has thus far been able to maintain the levels of spending
on innovative drugs that it enjoyed prior to the economic crisis that began in 2008. The analysis
covered spending per capita over the periods 2005 to 2009, and from 2010 to 2014.
Over the past five years, Belgium has maintained its position as one of the four EU countries spending
the most on innovative drugs per capita. Meanwhile, countries where the economic crisis had a
major impact (such as Spain, Ireland, Greece, and even France) have slipped in the ranking. Ensuring
that Belgium continues to be able to offer innovation to its people will require the efforts of all
stakeholders.
With the present study, we aimed to give some robust, yet simple examples how substantial funds
can be freed for other healthcare interventions and to initiate a debate in the public health arena,
engaging policy makers, payers, prescribers, and patients together. We built upon the methodology
and findings of the above mentioned studies, focusing our analyses on avoidable costs through the
appropriate use of medicines in the Belgian healthcare arena.
“Appropriate use of medicines” was defined as the cost-conscious and cost-effective prescribing of
medicines through:
•• ➢Improving adherence to drugs
•• ➢Adequate prescribing of antidepressants and antibiotics
•• ➢Avoidance of medication errors
We tackled the appropriate use of medicines from a patient perspective (for example the
non-adherence on cholesterol-lowering drugs, specifically statins) as well as from a public payer
(government) perspective, recognizing that savings can have an impact on both.
This focus was one limitation of our study in that we did not factor in some potentially important
external cost elements, such as work productivity gains, savings from informal care, or gains in other
industry areas. Nonetheless, the findings point to some important public costs that could be saved
through immediate, easily-implementable programs aimed at improving medication prescribing
and use.
This does not mean, however, that there are no other areas where savings can be found. We encourage
other stakeholders to investigate other areas where there may be similar or even greater savings that
can be re-directed to pay for innovation.
For each chapter of the report—one for each of the four areas of study—we present the background,
methodology, and research findings where a great potential for cost savings was identified
Conclusions and suggested means by which the policy and behavioural issues might be addressed
are outlined at the end of each chapter.
Page 2
Report
2.1 Low adherence to statins therapy
2.1.1Background
“Drugs don’t work in patients who don’t take them” (Koop, 2009).
Medication adherence has been clearly described by Vrijens et al (2012), as the process by
which patients take their medication as prescribed. The process is composed of “initiation,”
“implementation,” and “discontinuation.” Initiation occurs when the patient takes the first dose
of a prescribed medication; discontinuation occurs when the patient stops taking the prescribed
medication, and implementation is the extent to which a patient’s actual dosing corresponds to the
prescribed dose regimen, from initiation until the last dose. Persistence is the length of time between
initiation and the last dose, which precedes discontinuation.
Medication non-adherence, mostly in chronic treatment, is of increasing concern to clinicians as it is
now well established that non-adherence to medication contributes to poorer or even adverse health
outcomes, both in the short and long term (e.g., faster progression to co-morbid conditions, contribution
to increased risk of mortality). Further, the issue is now of growing concern among other healthcare
stakeholders, such as payers and policymakers, due to the increasing evidence that non-adherence can
result in higher costs of care, seldom offsetting the “savings” from not taking the respective medication.
In Europe, cardiovascular disease has been ranked as the first contributor to the total burden
of disease (measured in disability-adjusted life years) by the WHO, accounting for 21.4% of the
total disease burden3 in 2012 (WHO, 2012). In the same report, having high cholesterol and being
overweight (or obese) were listed among the five main modifiable risk factors to the total burden
of disease in Europe, together with tobacco use, alcohol consumption, and high blood pressure.
Clinical guidelines have repeatedly reinforced the need for adequate management of risk factors
as contributors to major adverse outcomes of cardiovascular disease in patients who are at risk4.
The evidence that reducing plasma LDL cholesterol reduces the risk of cardiovascular disease is
unequivocal (Reiner et al, 2011; Baigent et al, 2010). Despite this, adequate control of physiological
risk factors is still far below the recommended targets in many countries. The EUROASPIRE (European
Action on Secondary and Primary Prevention by Intervention to Reduce Events) has shown that the
integration of cardiovascular disease prevention into daily clinical practice is still highly inadequate in
Europe (EUROASPIRE, 1997; EUROASPIRE II, 2001; Kotseva et al, 2009).
In Belgium, 15% of the adult population with established coronary heart disease currently smokes,
80.3% are overweight, 25.5% are obese, 51.5% have elevated blood pressure, respectively 44.5% and
22.5% have elevated total and decreased HDL cholesterol, 22.5% have elevated triglycerides levels,
and 29.6% have co-morbid diabetes. Only 55% of these patients achieve the indicated target for
cholesterol control (serum total cholesterol < 4.5 mmol/l), despite the fact that over 80% are being
3Total burden of disease is expressed as disability-adjusted life years (DALYs); DALYs is a time-based measure that combines years of life lost due
to premature mortality (YLLs) and years of life lost due to time lived in states of less than full health, or years of healthy life lost due to disability (YLDs); cardio-vascular disease burden is the summary of ischaemic heart disease and stroke.
4e.g. high-risk individuals: hypertensive, with established cardiovascular disease, with type 2 diabetes, with occlusive arterial disease of the
lower limbs and carotid artery disease
Page 3
treated with lipid-lowering drugs (Kotseva et al, 2009). Poor medication adherence may explain the
gap between treatment levels and adequate control of risk factors.
Poor adherence to cardiovascular therapy is increasingly demonstrated to contribute to poor health
outcomes. A recent meta-analysis of adverse cardiovascular events and mortality showed that
individuals with sub-optimal level of compliance to statin therapy (defined as compliance level <80%)
have a +15% higher risk5 of cardiovascular events (any fatal or non-fatal coronary heart disease, stroke
or sudden cardiac death) and a +45% higher risk6 of all-cause mortality (Chowdhury, 2013).
An analysis of data from the Reduction of Atherothrombosis for Continued Health (REACH) Registry,
one of the largest contemporary outpatient worldwide registries, provides further evidence of the
impact of non-adherence. Patients who were non-adherent with any evidence-based secondary
prevention medication at study entry (medications studied were antiplatelets, lipid-lowering
drugs, or antihypertensive agents) demonstrated an 18% higher hazard of the primary outcome of
cardiovascular death/myocardial infarction/stroke at four years compared with patients who were
adherent (17.4% vs. 13.4%; HR, 1.18; 95% CI, 1.11-1.25) (Kumbhani et al, 2013).
A few studies have illustrated the possible economic implications of medication non-adherence in
various disease areas (Sokol, 2005; McDonnell, 2002; Senst, 2001). Sokol et al (2005) found that for
the different studied chronic medical conditions (diabetes, hypertension, hypercholesterolemia,
and congestive heart failure), hospitalization rates were significantly lower for patients with high
medication adherence. The higher medication costs were more than offset by medical cost reductions.
Clearly, important savings can be obtained in these conditions when medication adherence is improved.
In our analysis, we aimed to quantify the potential economic implications for Belgium of
non-adherence to cholesterol-lowering drugs (statins) from a payer perspective. We opted to study
statins because the dosing is normally one tablet per day, so it is possible to calculate adherence
accurately. This is this is not always the case with oral antidiabetics and antihypertensive drugs
where the daily dose prescribed can vary greatly between patients.
2.1.2 Methods: quantification approach
In a study of 137,277 patients in the U.S., Sokol et al (2005) showed that patients who maintained
an 80% to 100% medication adherence were significantly less likely to be hospitalized compared to
patients with lower levels of adherence. The analysis was conducted across four medical conditions:
diabetes, hypertension, hypercholesterolemia, and congestive heart failure. Hospitalization rates
were reported for five levels of medication adherence, and the research explored the additional
likelihood of being hospitalized in the respective year, should medication adherence be lower than
80-100%. For statins, the risk of hospitalization for the levels of adherence of 1-19% and 40-59%
was assumed to be 15%, and for accuracy the 20-29% level was assumed to have the same risk.
Hospitalization risk was 14% for the 60-79% level and 12% for the 80-100% level.
To estimate the impact of non-adherence, we first determined adherence levels to statins therapy
based on IMS Health LifeLink Treatment Dynamics (see explanation in annex). Specifically, we
selected all patients in the IMS Health LifeLink Treatment Dynamics panel with a first or followup prescription for statins during the period January 2010-January 2013. From the time of first
prescription and up to either December 2013 or loss of the patient from the panel, we counted the
5RR 95%CI for good vs. poor adherence 0.85, 0.81-0.89
6RR95%CI for good vs. poor adherence 0.55, 0.46-0.67
Page 4
number of prescription re-fills and total days covered by prescriptions. Total days covered were
determined as the number of days between two prescription fills in which the patient could be
assumed to use at least one pill per day, based on the pack size of the last prescription. Dividing
the total number of days covered by the number of follow-up days for each patient resulted in a
%-adherence level.
Next, we determined the number of avoidable hospitalizations corresponding to each adherence level as:
•• The difference between the risk of hospitalizations in patients at 80-100% adherence and the risk
of hospitalizations in patients with less than 80% adherence (reported Sokol, 2005);
•• Multiplied by the number of Belgium patients in statins in each of the five adherence levels where
a statistically significant risk difference was observed. To estimate the number of patients in each
of the five adherence levels to the Belgium population, a multiplication factor was determined
between the total number of patients in statins from the IMS Health LifeLink Treatment Dynamics
(=310,601) and the total number of patients in statins in Belgium (=1,439,276) reported in
Pharmanet report (INAMI, 2013).
Finally, we estimated the total avoidable cost attributable to non-adherence by multiplying the
number of avoidable hospitalizations due to non-adherence, by the average cost of a hospitalization
in Belgium in 2014 (average cost over all APR-DRGs). We applied two costs. One was the real, average
hospitalization cost for Belgium based on all Patients Refined Diagnosis Related groups (APR-DRGs €4,886). The other was the cost of hospitalizations related to cardiovascular disease—what could be
considered as the hospitalizations to be avoided by adherence to statins (i.e., APR-DRGs codes
160-180, 190-207 - €5,865).
Apart from this cost, we also included the extra treatment cost that results from increasing the adherence
level to 80-100% from its initial level (we applied 90% adherence level as the average between 80 and
100%). For that, the annual number of tablets of statins consumed and the yearly treatment costs were
estimated for all levels of adherence. It was assumed that each patient would receive one tablet per day.
The cost of a tablet was estimated using data from IMS Health Belgian National Retail Database (see
explanation in annex), by dividing the total annual expenditure for statins by the total number of tablets
consumed in 2014 (on average 0.4€ per tablet). The additional cost due to increasing the adherence levels
was defined as the cost difference between the current level of adherence and 80-100% adherence.
Hence, the total amount that could be avoided by increasing the adherence is given as the difference
between the total avoidable cost and the additional treatment cost required to raise the adherence levels.
2.1.3 Results: estimated avoidable costs
The average duration of follow-up in the panel was 871 days. Sixty-five percent of the anonymized
patients in the panel were below the acceptable 80% adherence level (Table 1). Linking adherence
levels in our panel with the additional risk of hospitalizations as reported by Sokol et al (2005)
(Figure 1), we estimated that 25,716 hospitalizations in Belgium across all causes were possibly
attributable to the lack of optimal adherence to statins therapy. With the average cost per
hospitalization in Belgium varying between €4,886 and €5,865, the total avoidable costs related to
hospitalization would be between €126Mn and €151Mn (Table 1, Figure 2). However, to avoid this cost,
if all patients were to raise their levels of adherence to 80-100%, treatment costs with statins would
increase €68,475,301. Thus, the estimated total amount of savings would vary between €57Mn and
€82Mn (Table 1).
Page 5
Note that in their study, Sokol et al (2005)
considered annual risk of hospitalization across
all causes. In turn, by quantifying only the
additional risk versus an adherence level of 80100%, we attempted to disentangle the incidence
of hospitalizations attributable to causes other
than poor adherence. A potential caveat of our
analysis stems from the limitations inherent in
using a prescription database. Cases in which
patients received a first prescription but who
never purchased that medication within an
appropriate period of time (considered primary
non-adherence) are not captured.
Figure 1: Adherence and risk of hospitalization in
non-compliant patients on lipid-lowering drugs
30%
25%
Risk of hospitalization
These estimated cost savings are conservative,
since in addition to the acute costs (acute
hospitalization) savings, there would also be
savings on the follow-up costs for rehabilitation,
physician consults, additional drug regimens,
etc., which are not taken into account here.
20%
p<0.05
p<0.05
15%
p<0.05
10%
5%
0%
01-19%
20-39%
40-59%
60-79%
80-100%
Level of compliance
Source: Sokol et al, 2005
Table 1: Estimated avoidable costs of hospitalizations due to non-adherence compared to 80-100%
patient adherence
Adherence No. of pts.
Level
**
No. of
Hosp. Avoidable avoidable
risk
hosp.
hosp.
Total cost avoidable hosp.
Lower
estimate
Higher
estimate
Number
of days
on
treatment
Extra
numb.
of days
to reach
optimal
adherence
Drug cost
related to
current
adherence
Extra drug cost
to reach optimal
adherence
01-19%
240,209
15%*
3%
7,206
35,209,851
42,264,793
36
285
3,475,729
27,805,829
20-39%
243,935
15%∆
3%
7,318
35,755,951
42,920,314
107
214
10,588,910
21,177,820
40-59%
227,902
15%*
3%
6,837
33,405,820
40,099,291
178
143
16,488,222
13,190,577
60-79%
217,735
14%*
2%
4,355
21,277,062
25,540,312
249
71
22,053,759
6,301,074
80-100%
509,496
12%∆
0%
N/A
0
0
321
0
66,349,755
Total
1,439,276
25,716
68,475,301
Savings due to fewer hospitalizations
125,648,684
150,824,709
Total savings taking into account hosp
savings and extra drug
57,173,382
82,349,408
* P values indicate that the outcome is significantly greater than the outcome for the 80-100% compliance level at P < 0.05
** Patients were extrapolated to Belgium population;
∆ No significant difference vs. optimal compliance level
Sources: IMS Health LifeLink Treatment Dynamics; IMS Health Belgian National Retail Database; Banque Nationale de DonnéesDiagnostic
médical; Sokol et al, 2005
Page 6
An additional limitation of this analysis is the
fact that, while we assume a dose of one pill
per day to determine adherence levels in our
panels, in real life, patients may be taking more
Figure 2: Avoidable hospital costs,
higher and lower estimates
40
Higher
Lower
30
Cost €Mn
Yet, these patients might be at the highest risk
of adverse health outcomes. We could therefore
only quantify the impact of adherence on
continuation of medication (so called secondary
non-adherence).
20
10
than one pill per day, or they may be dividing
0
pills. It was not possible to assess the impact
01-19%
20-39%
40-59%
60-79%
of this limitation, but likely this does not occur
Adherence Level
frequently with statin therapy, as most regimens
Sources: IMS Health LifeLink Treatment Dynamics; IMS Health
and standard doses are specified as one pill per
Belgian National Retail Database; Banque Nationale de Données
Diagnostic médical; Sokol et al, 2005
day. Besides, the two situations might offset
one another. Another limitation is that although
we know the type and the strength of the statin
used, we don’t know whether that was the appropriate type and strength for the patient.
2.1.4Conclusions
Poor adherence to medication prevents the therapy from achieving its purpose, and exposes patients
to the risk of adverse health events. In the case of lipid-lowering drugs, lack of adherence can result
in cerebrovascular events, such as stroke, with possible associated lifetime disability; myocardial
infarction; angina; and the possibility of developing heart failure, renal disease, peripheral vascular
disease, and premature death. Consequently, these patients are at high risk of requiring acute and
long-term care in hospitals and specialized centres, leading to an additional burden to the healthcare
system. These analyses on statins serve as a clear example that can be extrapolated to other drugs
and disease areas. However, each specific disease area should be evaluated individually, taking into
account the defined daily dose.
All relevant stakeholders—most particularly physicians and pharmacists—should commit to
delivering education programs for patients aimed at increasing awareness of the risks associated with
not adhering to medication as prescribed.
2.2 Inappropriate and over-prescribing of antidepressants
2.2.1Background
Depression is recognized as a major public health issue worldwide, although primarily in developed
countries. The “2012 Report on Global Burden of Diseases Study” published by the Institute for
Health Metrics and Evaluation (IHME), showed that major depressive disorders accounted for 3.23%
of disability-adjusted life years (DALY). This metric was introduced by the WHO to quantify the sum
of the Years of Life Lost (YLL) due to premature mortality and the Years Lost due to Disability (YLD).
Self-harm accounted for 2.7% of DALYs. The contributions of major depressive disorders (MDD) and
Page 7
self-harm to total DALYs in France, for example, were 4.11% and 2.68% respectively, and 7.1% and
1.46% respectively, in the Netherlands. The corresponding numbers for Belgium were 3.23% for MDD
and 2.7% for self-harm.
In economic terms, the Mental Health Economics European Network estimated that the percentage of
the health budget devoted to mental health in 17 western European countries appeared to vary between
4 and 13% (Knapp et al. 2006b). In the European Union (EU), this accounts for 3–4% of the gross
national product (GNP) (Gabriel and Liimatainen 2000). The most important contributor to direct costs
of depression is hospitalization, accounting for around half of the total in the U.K. and three-quarters
in the U.S. (Berto et al. 2000). The indirect costs (from unemployment, increases in absenteeism, and
decreased productivity) attributable to mental disorders outweigh the direct treatment costs by two to
six times in developed market economies (Greenberg et al. 1993; Kind and Sorensen 1993).
In most countries, families bear a significant proportion of these economic costs because of the
absence of publicly funded, comprehensive mental health service networks. As a result, governments
and societies ultimately pay a price in terms of reduced national income and increased expenditure
on social welfare programmes. Thus, the economic logic for societies and countries is simple: treating
and preventing mental disorders is expensive, but leaving them unattended can be more so (Knapp
et al. 2007). According to the WHO Regional Committee for Europe – 63rd session, about half of all
mental disorders start before the age of 14. Cost-effective interventions exist, but less than 1% of
mental health budgets are spent on prevention.
Set against this background, the rates of antidepressant drug use have been increasing worldwide,
backed by numerous activities aimed at raising awareness of the disease, the acceptance that it can
be treated, the economic crisis, and patients’ and prescribers’ increasing confidence in the available
treatments. From 2000 to 2012, the rate of antidepressant users more than doubled in EU countries,
from 31 to 66 daily defined doses (DDD) per 1,000 individuals per day (OECD eLibrary, 2014). For
Belgium, this rate increased from 39 to 70 per 1,000 individuals from 2000 to 2012 (OECD eLibrary,
2014). Still, in comparison with some neighbouring countries, figures are high in Belgium: in the
Netherlands, the DDD for antidepressants increased from 30 to 42 per 1,000 individuals per day, and
for France this rate increased from 41 to 50.
According to the Itinera Institute, mental illnesses are the primary cause of invalidity in Belgium, 27%
of long-term absenteeism is related to mental issues, and life expectancy of psychiatric patients is on
average 15 years shorter. Each day, three individuals commit suicide and 20% of the population uses
psycho-pharmaceutical drugs. Due to under-diagnosis or misdiagnosis, care is often provided too
late, and only 25% receive appropriate care.
Data from the RIZIV/INAMI (infospot – antidepressiva April/May/June 2014) show that the number
of patients in Belgium having received reimbursement for an antidepressant increased from 1.02
million (1,027,287) in 2005 to 1.17 million in 2012 (1,169,208) and 1.18 million in 2013 (RIZIV/INAMI,
Farmaceutische Kengetallen 2013). Antidepressants are also more frequently prescribed in older
patient groups (Figure 3).
The fact that antidepressants are more frequently prescribed in Belgium in older patient groups—
and most frequently in residents of nursing homes—is confirmed by media coverage in recent years.
(see also: http://www.ouderenhart.be/ARTS-VERPLEGING/MEDICATIE/medicatie.htm). Marc Justaert
(Christian Sickness Fund) reported that more than 40% of residents in nursing homes are receiving
antidepressants. On the other hand, under-diagnosis and under-treatment of depression in this
Page 8
Figure 3: Number of patients with reimbursement
for antidepressants per age category
Cost €m
Dr. Els Licht (GP, epidemiologist, the Netherlands,
2008) reported that GPs miss the diagnosis of
depression in two out of three elderly people.
Under-diagnosis leads to under-treatment
with increased risk for morbidity, suicide,
decreased cognitive and social functioning,
and early death (Fiske et al, 2009). This will,
consequently, have an economic impact.
500K
11.0%
400K
Number of Patients
older age group is also a crucial problem. (http://
www.ouderenhart.be/PSYCHISCH_WELBEHAGEN/
DEPRESSIE_ZELFDODING/depressie-en-zelfdodingbij-ouderen.htm)
300K
23.7%
200K
17.1%
100K
2.8%
According to official RIZIV/INAMI data, about
16.5%
0
22% of Belgian patients receiving
15-24
25-54
55-64
65-74
75+
antidepressants received only one package,
Age Category (Years)
and 11% received less than 30 daily doses on an
Source: RIZIV/INAMI, infospot April/May/June 2014
annual basis (RIZIV/INAMI, Farmaceutische
Kengetallen 2013). One explanation for this
high percentage of short duration treatments might be intolerance to the drug, but it does raise a
question about the treatment indications, as these drugs only start to have a therapeutic effect after
two to three weeks.
Additional data from the RIZIV/INAMI (RIZIV/INAMI, Farmaceutische Kengetallen 2013) show that in
2013, approximately 300 million daily defined doses (DDD’s) (292,282,176) of antidepressants were
prescribed, meaning approximately 800,000 DDD’s per day. The most frequently prescribed were
selective serotonin re-uptake inhibitors, followed by “other antidepressants.”
Are the right medicines reaching the right patients?
Most antidepressants in Europe are approved and recommended for treating moderately and severely
depressed patients (NICE CG 28, 2005). Furthermore, there is general agreement in the medical
literature that antidepressants are not effective in mild forms of depression and should not be used in
these patients (Committee on Safety of Medicines’ Expert Working Group, 2003; NICE CG28, 2005). Yet,
prescribing patterns show that about 67% of antidepressants prescribed in general practice in the U.K.
are used in patients with mild depression, 30% in moderate depression, and 3% in severe depression
(Martinez, 2005). Another study, from the U.S., showed that in 44% of cases, antidepressants were used
for mild depression or other disorders (Elkin, 1995). The issue of inappropriate prescribing has been
pointed out by Jureidini and colleagues who have argued that antidepressants are greatly misused, e.g.,
given in patient populations who do not benefit from them, or where the risks outweigh the benefits7,
or given for an appropriate duration of time, in excessive doses. Conversely, the patients who most
likely would benefit from these treatments remain under treated and under diagnosed (Jureidini, 2006).
The level of antidepressant consumption depends on the prevalence of depression in a country, the
prevalence of diagnosed depression, and the frequency of drug treatments within the context of
other treatments, especially psychotherapy (Grandfils & Sermet, 2009). In Belgium, psychologists are
7 T
hese populations include children, the elderly, mild depressive patients, and patients with indications where the effects of antidepressives
have not been studied or have not been proven.
Page 9
not incorporated in the RIZIV/INAMI nomenclature, meaning that no reimbursement is granted for
psychotherapy given by psychologists (http://users.myonline.be/allemeesch/KlinPsy/Terugbetaling.htm).
Psychotherapy provided by psychiatrists is reimbursed in Belgium, although not all psychiatrists
provide psychotherapy. Due to the fact that psychotherapy is, for the most part, not reimbursed
in Belgium, Belgian GP’s currently do not have many alternatives to prescribing reimbursed
antidepressants. Meanwhile, the Belgian recommendations for treating depression (Heyrman et al,
2008), center primarily on non-drug treatments, stating that antidepressants should be prescribed
only for severe depression, along with referral to specialized psychotherapy.
In France, psychotherapy from a psychiatrist is reimbursed, and under certain conditions, it is reimbursed
if performed by a psychologist. (http://psychotherapie.comprendrechoisir.com/comprendre/remboursementconsultation-psychologue) In the Netherlands, healthcare insurers stopped reimbursing for almost all
psychotherapists in 2013/2014 (http://www.europsyche.org/contents/14284/netherlands). This decision will most
likely have an impact on the consumption of antidepressants, which will be observable in the coming years.
In this analysis, we aimed to evaluate the current use of antidepressant medication in Belgium as
compared to France and the Netherlands, and to evaluate whether current prescribing levels in
Belgium correspond to patients’ needs.
The first step in this analysis was to determine current spending levels for antidepressant and mood
stabilizer prescriptions (ATC class N6A) in Belgium, the Netherlands, and France. Volume and value
sales were determined in each country (i.e., the average number of pills sold per capita, and cost/pill
respectively) based on IMS Health Belgian National Retail Database available to IMS Health in the
three countries via the IMS MIDAS platform (2013 data). (See annex for further details.)
We were able to estimate potential country-level prescription costs in Belgium by:
1. Multiplying the average number of pills/person in the Netherlands and in France, respectively,
with the cost/pill in Belgium
2. Extrapolating the result to the total population in Belgium, assuming that prescribing levels in
Belgium were equal to those in France or the Netherlands and using Belgian prices.
The difference between the current spending and potential spending represented additional costs for
antidepressants and mood stabilizers prescriptions in Belgium (vs. the Netherlands and France).
In order to determine whether the additional costs were justified by better health outcomes or by
savings in other healthcare resources, a number of epidemiological or resource-use outcomes related
to depression were reviewed in the literature to date. In addition, we looked at medical diagnoses for
which antidepressant prescriptions were used in Belgium. These were available from the IMS Health
Medical Prescriptions database (see explanation in annex). In Belgium, the IMS Medical Prescriptions
data are based on prescriptions written by a sample of 520 doctors (including GPs and psychiatrists)
offering medical services in locations other than hospitals; this represents a coverage of 1.8% of the
total number of practicing physicians in Belgium (data for 2014).
Over the last decade, mental health policy recommendations from the WHO, (The European Mental
Health Action Plan, 2013) have provided guidance supporting deinstitutionalization. This entails
developing community-based mental health services and expanding the role of primary care and
mental health staff to provide care and treatment in local settings. Accordingly, we performed an
additional analysis using the IMS Health Longitudinal Patients database (IMS Health LPD, see annex
Page 10
for further details). In this database, information on diagnosis and prescriptions is available for a set
of 360 GPs covering about 300,000 patients. Thus, we searched for the reason behind, and duration of,
antidepressant prescriptions.
Based on the IMS Health Belgian National Retail Data (2013) (see annex for further details),
Belgium’s per capital pill use of antidepressants was 45% and 48% higher than that of France and the
Netherlands, respectively. If we compare these figures with the DDD per 1,000 individuals per day
(OECD Library 2014) from 2012, the Belgian rate is 40% higher than in France (70 in Belgium versus 50
in France) and 66% higher than in the Netherlands (70 in Belgium versus 42 in the Netherlands).
These figures confirm the fact that antidepressant use is higher in Belgium than in France and the
Netherlands. This results in much higher spending on antidepressants in Belgium. With a 30%
smaller population than the Netherlands, spending in Belgium is four times higher, and the
per-person cost is six times higher.
Table 2: Estimated anti-depressants prescription costs in Belgium, France and The Netherlands
Pills/
Person
Cost/
person
€218,417,001
34.17
€19.61
1,551,696,977
€684,917,502
23.62
€10.42
388,295,877
€55,665,682
23.15
€3.32
Total
population
Total pills
consumed
Belgium
11,140,000
380,633,117
France
65,700,000
Netherlands
16,770,000
Total costs
Source: IMS Health MIDAS; IMS Health Belgian National Retail Data
Next, we estimated the additional spending on
antidepressants that might exist in Belgium due
to misuse and over prescribing. We compared the
current “mental health status” of the Belgian
population with that of neighbouring countries,
France and the Netherlands.
The estimated prescription cost difference, based
on usage (pill/person) in Belgium vs. France
and current cost/pill in Belgium was €67Mn,
which represented 31% of current spending in
Belgium.This is the estimated difference between
the current total cost of antidepressant use in
Belgium and the potential cost, at prescribing
levels in France.
Figure 4: Estimated anti-depressants cost/person
€19.61
€10.42
€3.32
Netherlands
Belgium
France
Page 11
Table 3: Estimated additional costs of anti-depressants use in Belgium
Cost in Belgium
Estimated
cost difference
Total cost
% Cost difference
of actual costs
Using France consumption
€150,975,544
€67,441,457
31%
Using Netherlands consumption
€148,011,267
€70,405,734
32%
The estimated prescription cost difference in Belgium vs. the Netherlands was €70Mn, representing
32% of current spending in Belgium (Table 3).
An examination of the indications for which antidepressants were prescribed, based on the IMS
Health Medical Prescriptions Database, shows that in Belgium, most are for depression, but almost
4% of prescriptions are for sleep disturbance (Figure 5). Trazolan® is often prescribed in this case.
The use of antidepressant medications for sleep problems is currently not supported by pharmacotherapeutic recommendations in Belgium (CBIP/BCFI, 2014). The proportion of antidepressants
prescriptions for sleep disturbances in France and Netherlands was around 1%.
Figure 5: Main diagnosis and % of prescriptions for antidepressants use in Belgium, 2013
% of all Prescriptions
F20 Schizophrenia
1%
Z76 Persons encountering health
services in other circumstances
1%
I10 essential primary
hypertension
1%
F43 reaction to severe stress,
and adjustment disorders
2%
M79 other soft tissue
disorder non-classified
2%
F42 obsess/compulsory
disorders
2%
F33 recurrent
depressive disorders
2%
F34 persist mood-affective
disorders
2%
F60 spec personality disorders
2%
G47 sleep disorders
4%
F41 other anxiety disorders
5%
15%
Other
54%
F32 Depressive Episode
F31 Bipolar affective disorders
7%
Source: IMS Health Medical Prescriptions Database
17%
As mentioned before, depression is currently often diagnosed and treated at the primary-care level.
Using the IMS Health longitudinal patient database (see annex for further details), we performed an
analysis of GPs’ antidepressant prescribing by diagnosis and duration of treatment. As explained before,
antidepressant drugs are only effective in patients suffering from moderate to severe depression, and
they are not indicated to treat sleeping and anxiety disorders. What is more, a treatment effect is only
seen after three weeks. Thus, to assess whether antidepressants were accurately provided in primary
care settings, prescribing data of antidepressants from 300 Belgian general practitioners were collected
from the Longitudinal Patient Data (LPD) database. The chart above shows the percentage of patients
Page 12
Figure 6: Indications for antidepressant prescription and percentage being of short duration
Euro (public Prices, 2013)
%
1 pack of ≤30 units
59.9%
Depression
15.9%
17.8%
Sleep Disorders
30.3%
Anxiety Disorder
7.5%
27.7%
13.6%
All Patients
22.2%
Source: IMS Health Longitudinal Patient Database
receiving antidepressive drugs by the most important indication and treatment duration. We looked at
patients treated in 2014 that had no prescription with antidepressants in 2013.
The results presented in Figure 6 show that only 60% of patients receiving antidepressants are
diagnosed with depression; the remaining patients have anxiety or sleeping disorders. Moreover,
16% of patients with depression received their medication for less than a month, which is insufficient
according the mode of action of these drugs. Note that this percentage is a bit overestimated given
that patients who received a prescription in November or December of 2014 might have received
new prescriptions in 2015. Nonetheless, our findings are in line with the Farmaceutische kengetallen
(2013) report stating that 11% of patients received only a 30-day supply.
Further, a study on antidepressants use in Belgian nursing homes for the elderly showed that 34.2%
(95 % CI 32.0, 36.4) of the residents were diagnosed with depression, and that 80.9% of these patients
were treated with an antidepressant. Antidepressants were prescribed for depression in 66.2%
of patients, for insomnia in 13.4% of patients, for anxiety 6.2%, and for neuropathic pain in 1.6%
(Bourgeois, 2012).
In the same context, 2010 statistics from the WHO’s Regional Office for Europe showed suicide rates
and self-inflicted injuries to be much higher in Belgium compared to the Netherlands and France,
with a rate of 16.85 suicides and self-inflicted injuries per 100,000 person-years. In France and in the
Netherlands, the corresponding rates were 14.76/100,000 person-years and 8.84/100,000 personyears, respectively (WHO Regional Office for Europe, 2014).
Depression
Sleep Disorders
Anxiety Disorder
All Patients
Belgium appears to have almost double the number of psychiatric beds/100,000 individuals vs.
France (178.52 beds/100,000 in Belgium, 91.24 beds/100,000 in France) and 28% more than in the
Netherlands (139.26 beds/100,000 in the Netherlands (WHO Regional Office for Europe, 2014).
This evidence shows that while Belgium spends more on antidepressive medication, parameters of
system performance (suicidal rates, resource use in other related areas) suggest that further mental
health policy measures are needed.
Page 13
2.2.4Conclusions
Set against the increasing recognition of depression as a major public health issue, prescriptions of
antidepressants have increased substantially over the past decade (Evans E. A et al 2014). Since 2000,
the rate of antidepressants users more than doubled in the EU countries. In Belgium alone, the rate of
antidepressants users soared from 39 to 70 per 1,000 individuals (OECD eLibrary, 2014).
The medical community recognizes that antidepressants do not benefit all patients. However
evidence from the literature shows that:
•• Almost half of antidepressants are prescribed to patients in whom the risks do not outweigh the
benefits, and
•• Patients who could actually benefit from treatment may be underserved.
There are, thus, high opportunity-costs associated with inadequate prescribing of antidepressants—
costs that include the utilization of services to diagnose and treat individuals in real need, or the use
of these resources elsewhere in the system.
Misuse of antidepressants9 should be contained by quality prescribing protocols and regulated by
strict recommendations in clinical care guidelines, or as part of the National depression program.
Note that the largest percentage of antidepressant prescriptions are written for the correct indications
(Figure 8, Figure 9), although a considerable percentage are not. Yet, even when they are prescribed for
the right diagnosis, antidepressants are often misused (for too short a duration), as described above.
Parameters of system performance (suicidal rates, resource use in other related areas) suggest that
further mental health policy measures are needed, and that the money saved from reducing overuse
could be re-invested in mental health prevention and in reimbursing for psychotherapy rather than
in more pharmacological treatment.
The value of psychotherapy in reducing the levels of depression and anxiety has been widely
demonstrated (Dezetter A et al 2013). However, in Belgium, the practice is not reimbursed,
except if performed by psychiatrists, only a limited number of whom are professionally trained in
psychotherapy. Mental health indicators might be improved by promoting this type of therapy within
the Belgium Health care system, such as has been done in the U.K. in a program, “Improving Access
to Psychological Therapies” (http://www.iapt.nhs.uk/).
Subsequent measures should focus on promoting the wellbeing of patients, considering the higher
consumption of antidepressants within the elderly population and residents of nursing homes on one
hand, and the under diagnosis and under treatment of depression on the other. As such, occupational
therapy and physical activities should be introduced into patients’ daily lives, either in nursing homes or in
community service locations. Patients could benefit from sessions of moderate-intensity activities (such
as swimming, walking, and dancing); advice to exercise safely for 30 minutes for five or more days a week,
using examples of everyday activities such as shopping, housework, and gardening; and participation in
local walking schemes as a way of improving mental wellbeing and social activities (NICE, 2008).
An educative program should be implemented and targeted to mental health professionals
and GPs, providing instruction on the strict medical indications and guidelines for prescribing
psychiatric drugs. Health authorities should understand that the limited time available for patient
consultations—one of the pitfalls of the health system—may compromise physicians’ ability to
accurately diagnose common mental health disorders.
8 Misuse in this context means prescribing to children and the elderly; for mild depression, sleep disorders, or other indications where safety and
efficacy has not been studied or proven; or at inappropriate doses or for inadequate duration.
Page 14
2.3 Over-prescribing of antibiotics
2.3.1Background
Antibiotics resistance is the situation in which antibiotics lose their ability to kill or stop the growth
of a specific bacterium. Antibiotics resistance may occur naturally as a result of mutations in a
bacteria’s genes (acquired resistance). However, excessive and inappropriate use of antibiotics may
accelerate the emergence and spread of antibiotic-resistant bacteria. Multi-drug resistant bacteria
can cause a wide range of infections, such as urinary tract infections, pneumonia, diarrhea, skin
infections, and bloodstream infections, etc. Patients in hospitals are at risk of infections unrelated
to the reason for admission; hospital-acquired infections include bloodstream infections caused
by Enterobacteriaceae, surgical-site infections caused by Staphylococcus aureus), or heart-valve
infections caused by Enteroccocci resistant to vancomycin, and surgical-site and wound infections
caused by Acinetobacter baumannii resistant to carbapenems.
Excessive and inappropriate use of antibiotics represent the use of antibiotics against colds and flu
caused by viruses, where antibiotics are not effective, or in cases when patients do not take antibiotics
as prescribed (e.g., they shorten the duration of use, take lower doses or do not comply with the
right frequency). In such situations, the bacteria may survive and develop resistance. The resistant
bacteria may spread, and cause infections in other individuals (Belgian Antibiotic Policy Coordination
Committee (BAPCOC), 2015).
Antibiotics resistance has been identified as a major public health concern in the Priority Medicines
for Europe and the World Project, commissioned by the Dutch Government in preparation of its
presidency of the European Union (EU) in 2004. Antibiotics resistance was identified as a public
health concern for the following reasons:
•• The increasing resistance to antibiotics of gram-negative bacteria, such as escherichia coli and
klebsiella pneumonia
•• The low rate at which novel antibiotics are approved and registered for use in Europe and the U.S.;
there have been no novel mechanism agents for Gram-negative organisms in decades
•• The reduced possibility, if at all, to reverse acquired antibiotic resistance
•• The growing evidence of the economic and social burden of antimicrobial resistance: increases in
hospital stays, additional discharge costs to facilities, extra medical care needed, and productivity
loss. The societal costs in the European Union, Norway and Iceland due to antimicrobial resistance
in 2007 were estimated to be in excess of €1.5Bn per year (Norrby, 2006).
Various activities have been initiated to create public awareness of this major public health threat.
Examples include:
•• The creation of the European Antibiotic Awareness Day (November 2010)
•• The establishment of the European Antimicrobial Resistance Surveillance Network (EARS-Net),
a network of national surveillance systems, coordinated and funded by the European Centre for
Disease Prevention and Control, which provides reference data on antimicrobial resistance in Europe
•• The establishment of the Epidemic Intelligence Information System (EPIS) module for
Antimicrobial Resistance and Healthcare-associated Infections (ARHAI) in Warsaw 2011
Page 15
Three major publications have been issued recently, providing a comprehensive overview of the threat
posed by antimicrobial resistance in the U.S., Europe and worldwide:
•• The U.S. Centers for Disease Control and Prevention (CDC) report on antibiotic resistance threats (2013)
•• The “2013 Report Priority Medicines” for Europe and the World
•• The World Health Organization “Antimicrobial resistance report: global report on surveillance 2014”
In Belgium, several national programs have been launched since 2000 in order to increase the
awareness of incorrect antibiotic use and problems of bacterial resistance. Since then, outpatient
antibiotic use (based on the number of packages) decreased by 36%. Despite this reduction, outpatient
use of antibiotics is still high in Belgium compared to other European countries. And, the use has not
declined since 2006-2007. Meanwhile, between 2007 and 2013, the use of antibiotics in hospitals
increased by 5.6%. The 14th national program was recently launched by the Belgian Antibiotic Policy
Coordination Committee (BAPCOP).
Set against this background, our aim was to determine whether antibiotics are over-prescribed in
Belgium, and if so, what the costs and health consequences of this are. As shown in a number of
studies, the prevalence of antibiotics resistance is strongly related to consumption. We compared
current consumption of antibiotics in Belgium (expressed in number of pills/person/year) with
antibiotics consumption and spending in the Netherlands, as well as rates of antibiotics resistance
reported for the two countries. The Netherlands was chosen for comparison because the climate in both
countries is the same, and as such the number of viral and bacterial infections is comparable (as we will
show). We also looked at the indications for which antibiotics are prescribed for outpatients in Belgium.
The total antibiotics consumption (number of sold pills) was determined using IMS Health Belgian
National Retail Data for the year 2013. The ATC classes selected were: J1, J3, J4, A7A, D6A, G1C, and
S3A. The corresponding total spending was determined taking into account public prices. We divided
the total number of pills sold by the total country population to determine the number of pills
consumed per inhabitant.
In order to eliminate the impact of differences in unit prices between countries, we calculated a
cost per pill in Belgium by dividing the total public spending by the total number of pills consumed.
Multiplying the price per pill in Belgium by the number of pills per person consumed in the
Netherlands and the total Belgian population, we estimated the potential public spending under
a lower use of antibiotics. The difference between current and estimated spending represented
potential cost savings through more conscious prescribing and use of antibiotics.
Based on the IMS Health LPD data collected from 360 GPs covering about 300,000 patients, we
checked the diagnosis, in ICD-10 coding, for which antibiotics were prescribed.
Page 16
Table 4: Antibiotics consumption in Belgium and Netherlands in 2013
Total
population
Total pills
consumed
Total costs
Pills/
Person
Cost/
Person
Belgium
11,140,000
141,000,070
€134,524,191
12.66
€12.08
Netherlands
16,770,000
99,476,775
€43,046,397
5.93
€2.57
Figure 7: Antibiotics consumption in 2013,
cost per person
In 2013, individual consumption of antibiotics
was 5.93 pills per person in the Netherlands and
approximately two times higher than that in
Belgium (12.66 pills/person, Table 4, Figure 7).
€12.08
€2.57
The low antibiotics use in the Netherlands
compared to Belgium was confirmed by a WHO
Netherlands
report (“Four-fold difference in antibiotics
consumption across the European region”
Belgium
– new WHO report, available on website WHO:
http://www.euro.who.int). In this report, the total
antibiotics use for 2011 was listed (expressed in
number of DDD per 1,000 inhabitants per day) for European countries and Kosovo as compared to
29 ESAC-Net (European Surveillance of Antimicrobial Consumption Network) countries. Results are
shown in the Figure 8. The lowest antibiotics consumption was observed in the Netherlands.
Figure 8: Total antibiotics used in 2011, expressed in number of DDD per 1,000 inhabitants per day in
12 European countries and Kosovo as compared to 29 ESAC-Net countries
Other antibacterials (J01X)
Aminoglycosides (J01G)
Sulfonamides and trimethoprim (J01E)
Quinolones (J01M)
Other beta-lactam antibacterials, cephalosporins (J01D)
Antibacterial combinations (J01R)
Amphenicols (J01B)
Tetracyclines (J01A)
Macrolides, lincosamides and streptogramins (J01F)
Beta-lactam antibacterials, penicillins (J01C)
40
35
30
25
20
15
10
5
0
Turkey*
Montenegro
Greece
Tajikistan
Cyprus
Belgium
France
Italy
Luxembourg
Kosovo
Serbia
Kyrgyzstan
Malta
Portugal
Ireland
Slovakia
Finland
Iceland
Poland*
Croatia
Moldova
Georgia*
Bulgaria
Spain*
Denmark
Lithuania
United Kingdom*
Czech Republic*
Bosnia & Herzegovina
Norway
Belarus
Azerbaijan
Romania
Slovenia
Sweden
Latvia
Armenia
Hungary*
Austria*
Germany*
Estonia
Netherlands
DDD/1000 Inhabitants Per Day
45
* countries reporting only outpatient antibiotic use
Source: “Four-fold difference in antibiotics consumption across the European region”
– new WHO report, available on website WHO: http://www.euro.who.int
Page 17
In contrast, Belgium antibiotics use, at more than double that of the Netherlands, fell into the high
usage category—a result that agrees with our own findings.
The status of antibiotics resistance in both Belgium and the Netherlands was also evaluated using
the most recent data on the prevalence of acquired bacterial resistance in Europe available from the
“2013 Report Priority Medicines for Europe and the World.” The figures below illustrate prevalence of
invasive bacterial isolates with acquired multidrug resistance. Rates (ranges, exact percentages were
not available in the report) of antibiotic resistant pseudomonas aeruginosa and staphylococcus aureus
are higher in Belgium (10-25%) compared to the Netherlands (1-5%), while the prevalence of resistant
escherichia coli and klebsiella pneumonia were comparable (Figure 9).
Figure 9: Percentage of invasive (blood and cerebrospinal fluid) isolates
A1
A2
< 1%
1% to < 5%
5% to < 10%
10% to < 25%
25% to < 50%
≥ 50%
No data reported
or less than 10 isolates
< 1%
1% to < 5%
5% to < 10%
10% to < 25%
25% to < 50%
≥ 50%
No data reported
Not included
Not included
Non-visible countries
Liechtenstein
Luxembourg
Malta
B1
Liechtenstein
Luxembourg
Malta
B2
< 1%
1% to < 5%
5% to < 10%
10% to < 25%
25% to < 50%
≥ 50%
No data reported
< 1%
1% to < 5%
5% to < 10%
10% to < 25%
25% to < 50%
≥ 50%
No data reported
Not included
Not included
Liechtenstein
Luxembourg
Malta
Liechtenstein
Luxembourg
Malta
Source: EARS-Net; A1: Escherichia coli percentage (%) of invasive (blood and cerebrospinal fluid) isolates resistant to third generation cephalosporins,
EU/EEA, 2011; A2: Klebsiella pneumoniae with multidrug resistance (resistant to third-generation cephalosporins, fluoroquinolones and aminoglycosides),
EU/EEA, 2011; B1: Pseudomonas aeruginosa resistant to carbapenems, EU/EEA, 2011
B2: Staphylococcus aureus resistant to meticillin (MRSA), EU/EEA, 2011.
Despite the high use of antibiotics outside of hospitals in Belgium, a high number of hospitalizations
attributable to inflammations and infections were recorded (2011, data from RIZIV/INAMI, Technische
Cell, https://tct.fgov.be/webetct/etct-web):
•• 17,514 hospitalizations attributable to renal and urinary tract infections (APR-DRG 463)
•• 6,523 hospitalizations attributable to inflammations and infections in the respiratory system
(APR-DRG 137)
•• 34,456 hospitalizations attributable to non-viral pneumonia (APR-DRG 139)
Page 18
Additional data show that the incidence of hospital-acquired bacterial infections within internal care
units in Belgium was 1.4 per 1,000 patient days for primary bloodstream infections, and 17.9 per 1000
intubation days for ventilation-associated pneumonia (NSIH, 2012).
The Great Influenza Survey (GIS) was implemented in several European countries to assess the
influenza like illness (ILI) incidence level in the community. GIS is an internet-based monitoring
system that collects data from individuals voluntarily participating in an internet survey. Participants
are asked to complete an electronic symptom questionnaire weekly, documenting any symptoms
experienced since their last visit. Figures from the influenza season 2013-2014 indicate that ILIincidence in both countries is comparable. One might postulate that antibiotics are still being
prescribed in these patients to speed their cure, despite several media campaigns to discourage this.
To analyze general practitioners’ prescription trends for antibiotics, we used data available from the
IMS Health LPD. Figure 10 below shows the indications for which antibiotics were mainly used by
GPs. Almost 50% of antibiotic use was in indications where antibiotics are most often not needed
because the condition is of a viral nature.
Figure 10: Indications for which antibiotics are prescribed in Belgium
Other
17%
Bronchitis
17%
Tonsilitis
Nasopharyngitis
(common cold)
Laryngitis and Tracheitis
6%
14%
6%
Pharyngitis
8%
Upper airway infections
Sinusitis
12%
8%
Cystitis
12%
Source: IMS Health Longitudinal Patient Database
Finally, looking at infection-related death rates, there were 22.9 deaths per 100,000 inhabitants
in Belgium due to infectious and parasitic diseases (ICD10 A00-B99), compared to an average of
13.9/100,000 in the European Union, and a rate of 12.7/100,000 in the Netherlands (Eurostat data for
2010, Causes of Deaths by Region).
The evidence reported above (higher antibiotics consumption in Belgium compared to the
Netherlands; a high number of infection-related hospitalisations in Belgium; comparable ambulatory
infections in Belgium & the Netherlands (ILI), and higher infection-related death rates in Belgium
compared to the Netherlands) suggest that antibiotics are likely misused and over prescribed in
Belgium. Based on the current antibiotics consumption in the Netherlands, potentially €71Mn
(€71,478,576) in costs could be avoided annually in Belgium if antibiotics were to be prescribed more
conscientiously. The additional health and cost implications of antibiotics resistance are not taken
into account here, but could lead to additional savings.
Page 19
2.3.4Conclusions
The increasing resistance of gram-negative bacteria to antibiotics, coupled with low rates of novel
antibiotics discovery and the reduced (or non-existent) possibility of reversing antibiotic-acquired
resistance, has led the European Centre for Disease Prevention and Control to declare antibiotics
resistance a major public health priority. The prevalence of antibiotics resistance is strongly related
to higher consumption. Yet, antibiotics continue to be highly prescribed and used in Belgium—at
more than double the rate in the Netherlands. This intensifies the rate of anti-microbial resistant
isolates and, as a consequence, the possibly of contributing to higher infection-associated mortality.
As such, immediate measures to increase patient and prescriber awareness that antibiotics don’t work
in viral infections (and that rest and analgetics are sufficient) could decrease the use and prescribing
of antibiotics. Furthermore, the risks of misusing antibiotics and the consequences of antibiotics
resistance warrant programs at local and national levels.
2.4 Hospitalizations due to medical errors
2.4.1Background
Medication errors are unintentional errors in how medicines are prescribed, dispensed, administered,
or monitored while controlled by a healthcare professional, patient, or consumer. They are the most
common, single preventable cause of adverse events in medical practice. As the problem is gaining
increased awareness, local strategies have been implemented in healthcare centers, such as, for
example, automating and computerizing medication-use processes.
Several studies have been conducted in order to measure the burden of medication errors within and
across countries, as well as the impact on patient safety and on hospital and societal costs. Most of
them are single-centre studies and are limited in the information they offer with regard to patients’
follow-up and the description of risk factors. Other studies do not report the additional costs
resulting from re-admissions or the treatments administered in these cases.
According to the WHO, in 8% to 12% of hospitalizations in Europe, medical errors and healthcarerelated adverse events occur; 23% of European Union citizens claim to have been directly affected by
medical errors; 18% claim to have experienced a serious medical error in a hospital, and 11% claim
to have been prescribed the wrong medication. Fifty to 70% of harmful medication errors could be
prevented through comprehensive and systematic patient safety approaches. Also, strategies to reduce
the rate of adverse events could lead to the prevention of more than 750,000 harm-inflicting medical
errors per year, leading in turn to over 3.2 million fewer hospitalization days, 260,000 fewer incidents
of permanent disability, and 95,000 fewer deaths per year (WHO Regional Office for Europe, 2014).
European health authorities have identified the need for reducing medications errors, and, as a result,
new EU pharmacovigilance legislation was established in July 2012. Adverse drug reactions resulting
from medication errors in the EU must now be reported to the EudraVigilance (the EU database of
adverse drug reactions). The European Medicines Agency (EMA) is responsible for facilitating the
reporting of adverse drug reactions due to medication errors. The agency is also responsible for
facilitating coordination between medicine regulatory authorities in the Member States, national
pharmacovigilance centers and national patient–safety authorities.
Page 20
Hospitalizations due to medical errors
The goal is to enable the mutual exchange of information on the adverse reactions due to
medications errors and to coordinate effective reporting to EudraVigilance. As this policy is still very
recent, figures on the incidence, risk factors, and follow-up treatments across the EU Member States
are scarce.
In the present analysis, we set out to estimate the avoidable costs that are due to medication errors
that lead to avoidable hospitalizations in Belgium.
Leendertse et al (2008) analysed data from a prospective multi-centre “Hospital Admissions
Related to Medication (HARM) Study.” The study determined the frequency and patient outcomes of
medication-related hospital admissions in the Netherlands. A case-control (matched on age and sex)
was used to determine risk factors for potential preventable admissions. A total of 13,000 unplanned
admissions in 21 hospitals in the Netherlands were assessed during 40 days. Medication-related
hospitalizations were defined as hospitalizations due to adverse drug effects (i.e., harm due to adverse
effects of medication use, as defined by the WHO) or due to medication errors (i.e., preventable
medication-related hospitalizations). A medication error was defined as any error made in the process
of prescribing, dispensing, or administering the medication.
An estimated 5.6% of acute hospital admissions in the study were medication-related, and 46.5% of
these were assessed as potentially preventable. The most common medication errors found were:
lack of a clear indication for the medication, non-adherence to the medication regimen, inadequate
monitoring, and drug-drug interactions. The most common reasons for hospitalization were
gastrointestinal tract problems, cardiovascular symptoms, respiratory symptoms, and poor glycaemic
control. In 70.2% of the cases, the patient recovered completely, but in 6.3% of cases, the patient died,
and in 9.3% of cases the patient experienced a disability after discharge.
We used the incidence of preventable acute hospital admissions due to medication errors from this
study (assuming the same incidence for Belgium and the Netherlands; specific figures for Belgium
were not found) and applied it to the total hospital admissions in Belgium in 2011 (data from the
National Hospital Stay Statistics, Belgian Institute for Health and Disability Insurance (RIZIV/INAMI)).
In this way, we determined the number of hospital admissions due to avoidable medication errors in
Belgium. Next, we multiplied the estimated number of avoidable hospitalizations with the average
cost of a hospital stay, to produce an estimate of the total avoidable costs attributable to medication
errors. The average cost of a hospital stay in Belgium was determined as the weighted average of all
APR-DRG-related stays and the cost per APR-DRG stay, including in-hospital pharmacy, procedure,
laboratory measures, and other costs (data from 2011). Costs were inflated to 2014 values using the
observed annual trend in cost per APR-DRG between 2001 and 2011 (Table 5).
Page 21
Table 5: Estimated avoidable costs due to medication errors in Belgium
Indicators
Figures
Reference
Number of hospital admissions in Belgium, 2011
1,643,518
RIZIV/INAMI 2011
Incidence of hospital admissions medication-related
5.6%
Leendertse, 2008
% of hospital admissions estimated as potentially preventable
46.5%
Leendertse, 2008
% hospital admissions attributable to medication errors
2.6%*
calculated
Total number of hospital admissions due to medication errors
that could have been avoided
42,797
calculated
Average cost of a hospital stay
€4,886
RIZIV/INAMI 2011
Total hospital avoidable hospitalization costs due to
medications errors
€209
million
calculated
* 5.6% (medication-related hospital admissions) * 46.5% (potentially preventable admissions)
The average cost of a hospital stay in Belgium
(2014) was estimated to be €4,886 (calculations
and assumptions are explained in section 2.2.2
of this document). Based on an incidence of
2.6% of total hospital admissions attributable to
medication errors, the estimated avoidable cost
was around €200Mn per year.
Figure 11 displays the most common reasons for
avoidable hospital admissions required due to
medication errors (Leendertse A. J. et al, 2008).
Figure 11: Reasons for preventable hospital
admissions
16%
14%
12%
10%
8%
6%
4%
To bring this possible savings into perspective,
2%
we investigated codes for hospitalizations due
0%
to drug use. In Belgium, the APR-DRG code 812
GastroCirculatory Respiratory
GastroEndocrine
intestinal
systems
symptoms
intestinal
system
represents hospitalizations due to intoxication
bleeding
symptoms
caused by medication. In 2011, representing the
Source: Leendertse A. J. et al, 2008
latest data available online, 12,167 patients were
coded under this APR-DRG with a mean cost of
€2,713. Thus, the total expenditure due to drug intoxication was estimated at more than €33Mn—a
figure obviously much lower than the €200Mn reported above. It should be noted that not all cases
of intoxication can be avoided, since this classification also includes deliberate intake of an overdose.
Also, since the reason for hospital admission is not always straightforward, medication errors
reported by hospitals will be under reported.
Page 22
A very common medication error leading to hospitalization is insulin overdosing which leads to
hypoglycaemia (Smith et al 2005). While insulin overdosing is not always an error, it can be the
result of difficulty in finding the right dosage or poor self-monitoring. Projecting data extracted
from the IMS Health Hospital Disease database to Belgium there are about 11,000 hospitalizations
for hypoglycemia with an average cost of €10,000. Note that hypoglycemia can be the cause of car
crashes and fractures due to falls, which explains the high hospitalization costs. The total expenditure
for hospitalizations due to hypoglycaemia is around €110Mn. Again, not all hospitalizations can be
avoided by better patient education, but the examples shown above put in perspective the €200Mn
that was estimated.
2.4.4Conclusions
Preventable medication errors, occurring as a result of lack of clear indication for the medication,
non-adherence to the medication regimen, inadequate monitoring, and drug-drug interactions, may
be the source of 2.6% of annual hospital admissions (Leendertse, 2008).
Given the enormous cost and health burden of preventable medication errors, a synergic approach
is warranted nationally and across borders. This would entail communicating with and involving
all the different stakeholders (medical doctors, pharmacists, hospitals, national and international
pharmacovigilance organizations) in the provision and delivery of care. A synergic approach is also
warranted through patient-focused activities aimed to educate patients on the importance of taking
medication as prescribed (at the correct dose and time, for the prescribed indication), declaring
multi-medication, and reporting adverse drug reactions.
Introduction of healthcare policies to avoid medication errors is highly recommended.
Page 23
General conclusions
Belgium has, thus far, retained its place among the top four EU countries spending the most on
innovative drugs per capita—a fact critically important to maintaining the health and welfare of the
country’s population. However, a country’s ability to guarantee the best possible treatment for as
many patients as possible is clearly tied to the economic climate; those EU countries hardest hit by
the recent economic crisis have had to compromise when it comes to providing access to innovative
therapy. The experience in these countries serves as a clarion call to Belgium, underscoring the need
to trim avoidable costs, thereby preserving funding for innovation.
Yet, before moneys can be freed to support innovative interventions, it must be clear which current
costs can be avoided. In this study, we analysed four possible areas where cost-savings could be
achieved to avoid jeopardizing patients’ health and to actually improve it.
The four areas for potential cost savings were: medication non-adherence, misuse of
antidepressants, misuse of antibiotics, and medication errors. We want to stress again that we
chose these areas because of the robust, simple, and straightforward nature of the methodology
available. Other areas can and should be identified and studied to maintain the current internationally
accepted good care that is provided to Belgian inhabitants.
In each area, we identified the potential cost savings that could be used to support better healthcare
interventions and health policy measures that generate opportunities to invest in better public
healthcare in Belgium.
On the matter of medication non-adherence, cardiovascular disease related to non-adherence to
statins was analysed. Observational, outcomes studies have shown that treatment goals are still
much below the recommended levels. Fifty-five percent of individuals with established coronary
heart disease in Belgium do not reach the recommended target cholesterol levels, despite a
wide-spread use of lipid-lowering therapy in more than 80% of the population at risk (Kotseva et al,
2009). According to Chowdhury (2013), low adherence to lipid-lowering drugs was associated with a
+15% higher risk of cardiovascular events and a +45% higher risk of all-cause mortality.
This, in turn, contributes to an increased economic burden of the disease (as a consequence of higher
rates of adverse events and co-morbid conditions) (Sokol, 2005; McDonnell, 2002; Senst, 2001). We
estimated that from €57Mn to 82Mn in annual costs of hospitalizations in Belgium could be avoided
simply by increasing compliance levels to 80-100% in the statins market. Note, there is tremendous
potential for further cost savings in all the other chronic medical conditions and drug classes.As such,
various stakeholders (INMAI, sickness funds, physicians, pharmacists, etc.) should be focusing on
how to increase adherence to drugs in chronic diseases, applying programs that have shown to be
cost-effective.
High consumption of antidepressive medication and the under diagnosis of depression,
most frequently in the elderly, leads to misuse of antidepressants in Belgium. About 17.4% of
antidepressants in the country are prescribed for sleep disorders, against current national
pharmaco-therapeutic guidelines. And,in at least 15% of patients, the treatment duration was too
short (IMS Health LPDs, 2014 and CBIP/BCFI 2014). This study estimated a potential annual avoidable
cost due to antidepressants misuse/overuse in Belgium of approximately €67Mn to €70Mn, based
Page 24
General conclusions
on prescription patterns in France and the Netherlands. On the other hand, health indicators have
shown that depression is not always diagnosed and that suicide rates are high. We outlined several
possible directions that could be taken to reduce the inadequate use of antidepressants in Belgium.
Antibiotics resistance has been identified as a major worldwide public health concern; numerous
activities have been initiated to create public awareness at both international and European
levels. High prevalence of multi-drug resistant pseudomonas aeruginosa, staphylococcus aureus,
escherichia coli, and klebsiella pneumonia are noted in Belgium (10-25% of the specific bacterial
isolates). The prevalence of antibiotics resistance is strongly related to higher consumption. This
study estimated that on average an individual takes 12.66 antibiotic pills per year in Belgium—twice
the amount in the Netherlands. Despite the high consumption of antibiotics in Belgium, in 2011,
over 58 thousand hospitalizations in the country were due to urinary tract infections, respiratory
infections, or pneumonia. This study estimated a potential for more than €71Mn in savings in annual
treatment costs, through more conscious prescribing of antibiotics. This estimate did not take into
account the additional health and cost consequences of antibiotics resistance. Several programs to
reduce the use of antibiotics in Belgium have met with some success, but it is clear that more has to
be done to reach patients and physicians.
Eight to twelve percent of hospitalizations in the European Union may be attributable to
medication errors and healthcare-related adverse events (WHO, 2014). Of these, 50-70% could
be prevented through comprehensive, systematic patient safety approaches. Various measures have
been implemented recently to increase vigilance across the Member States. This study estimated
that in Belgium, medication errors may have been the cause of over 42,000 hospital admissions each
year. The projected annual economic burden of avoidable medication errors was more than €209Mn
per year.
Medication errors was the only area in which we tallied the totality of avoidable costs; in the other
subject areas, we focused on single or specific therapeutic areas. Based on the four scenarios explored
here, over €405 million could be saved annually, representing 1.5-1.6% of the total public health expenditure.
(Note that there may be some overlap between the four areas and that the effects of one might impact
the other.) This budget could be invested in other areas of healthcare, such as: funding innovative
treatments, broadening access restrictions to specific drugs, implementing prevention programs, and
modernizing hospital infrastructures, etc. It could also be valuable to re-invest the freed funds into
efforts to organize primary care and provide in-home aid to patients.
A number of key policy measures have been suggested (see the specific chapters), with immediate
application and relatively low implementation costs.
Page 25
Authors
This report has been prepared by:
Mark Lamotte, MD
Cardiologist, Senior Principal, Real-World Evidence Solutions, IMS Health
Mark Lamotte is leading the Belgian IMS Health Economic and Outcomes Research team.
He is a Medical Doctor, specialized in cardiology. After six years in medical practice (invasive
and non-invasive cardiology), he joined Rhône-Poulenc Rorer, where he was Cardiovascular
Medical Advisor (antithrombosis area) for 1.5 years. He then joined HEDM, which was later
acquired by IMS Health, in January 2000 and has since then worked as project manager
and scientific director. Mark has been responsible for the project management and quality
assurance of the Belgium HEOR team since 2007 and began leading the team in December 2008.
Since March 2012, Mark has been leading the global IMS Health HEOR Centre of Excellence
on health economic modeling. Mark also leads the development of IMS Health’s Core Diabetes Model, the most
referenced online model in type 1 and 2 diabetes.
Over the years Mark Lamotte has worked on more than 400 cardiovascular, pulmonary, diabetes, urology and
oncology projects, including expert interviews, patient record review, modeling (more than 100), and report
writing. Many of those projects resulted in peer reviewed publications (list available on request).
Mark is fluent in Dutch (mother tongue), French, English, and Spanish, and he understands German.
Karin Caekelbergh
Consultant, Real-World Evidence Solutions, North Europe & Africa, IMS Health
Karin Caekelbergh is a Master in Biomedical Science and works as a consultant in the IMS
Health Real-World Evidence Solutions team, collaborating in health economic evaluations.
After an interim-function (one year) as administrative collaborator at the Flemish
Parliament, she worked for Msource (CRO) as a clinical data co-ordinator/clinical research
associate in the pharmaceutical industry for 2.5 years. She joined HEDM in September 2000
and HEDM was acquired by IMS Health in 2004.
Karin is very knowledgeable in all aspects of conducting observational studies including:
literature review, protocol & case report development, data collection (patient chart review,
expert surveys), data analysis, and report writing.
She has been working on a broad range of local and international projects in the following
domains: schizophrenia, diabetes, febrile neutropenia, asthma/COPD, neuropathic pain, AIDS, dialysis, oncology,
dermatology, cardiology, hepatitis, and burn injuries.
Karin’s mother tongue is Dutch and she speaks French and English fluently. Her comprehension of German and
Spanish is good.
Mafalda Ramos, MSc, MEng
MEng, Consultant, Real-World Evidence Solutions, IMS Health
Mafalda Ramos holds an Integrated Master degree in Biomedical Engineering from the
Technical University of Lisbon and an International Master degree in Health Economics
and Pharmacoeconomics from Universitat Pompeu Fabra of Barcelona. Prior to joining IMS
Health, she performed modelling work in academia in mental health, and gained business
consulting and medical devices industry experience.
Mafalda joined HEOR IMS Health Spain in April 2012 and, in January 2014, she joined the
HEOR and RWE Solutions team in Brussels.
She has been developing health economic models (at a local and a global level) in several
therapeutic areas and recently she also conducts analyses based on the IMS Health Hospital Disease database
to collect key health economic data. Mafalda is experienced in several modelling tools: TreeAge, Excel, Core
Diabetes Model, SAS and STATA. Mafalda’s mother tongue is Portuguese, and she also speaks English and
Spanish fluently.
Page 26
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2014”
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McDonagh T, Moulin C, Poldermans D, Popescu BA, Sechtem U, Sirnes PA, Tendera M, Torbicki A, Vardas P, Widimsky P,
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(ESC) and the European Atherosclerosis Society (EAS),” Eur Heart J, 2011;32:1769–1818Senst BL, Achusim LE, Genest RP,
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Smith W. D. , Winterstein A. G., Johns T, Rosenberg E., Sauer B. C., “Causes of hyperglycemia and hypoglycemia in adult
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http://www.cdc.gov/drugresistance/threat-report-2013/index.html; accessed: September 2014.
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Page 29
Annex
IMS Health Databases
Description
IMS Health Belgian
National Retail Data
Is a national global and complete view on the Belgian pharmaceutical
market in sales and volume for registered products in retail (100%
wholesaler coverage). This DB includes parallel importers and covers
indirect and direct sales.
IMS Health MIDAS
database
Is an ethical pharmaceutical product sales database that captures more
than 95 percent of the value and volume of the global market. Coverage
of over 70 countries around the world.
IMS Health LifeLink
Treatment Dynamics
Delivers real-world patient information (non-longitudinal- captures
an anonymized unique patient code which allows to build longitudinal
patient profiles based on their retail (prescription) drug history
IMS Health Hospital
Disease database
Delivers real-world evidence at the hospital stay level. Twenty percent
of the hospital beds in Belgium are captured in the HDD database
for 2011-2012. The coverage reaches about 25% in 2013. The beds are
equally distributed within Belgium and according to the characteristics
of the hospital (university / non university).
Specific data regarding the patient, medical information, products
(both costs and numbers of units used, per product pack), the amount
invoiced to the sickness fund and to the patient himself. Products are
classified using the ATC-classification (EPhMRA version). Finally, the
database includes the INAMI procedure codes corresponding to the acts
that were performed on the patients.
IMS Health Medical
Prescriptions Database
Delivers critical qualitative insights into patient, disease, treatment
and prescribing profiles for all registered products and is based on a
doctor panel of 520 doctors in total GP (170) + 15 different Specialties
(depending the specialty between 20-30 per specialty)
IMS Health Longitudinal
Patient Database
Patient and prescription information collected through a constant
panel of office-based primary and secondary care physicians equipped
with Electronic Medical Records (EMR) software. Over 70 million active
patients are continuously tracked with LPD.
Page 30
IMS Health
HQ
Medialaan 38
83 Wooster Heights Road
1800 Vilvoorde
Danbury, CT 06810
Brussels
United States
Belgium
T: +32 2 627 32 11
About IMS Health
IMS Health is a leading global information and technology services company providing clients in the healthcare
industry with comprehensive solutions to measure and improve their performance. End-to-end proprietary
applications and configurable solutions connect 10+ petabytes of complex healthcare data through the IMS OneTM
cloud-based master data management platform, providing comprehensive insights into diseases, treatments,
costs and outcomes. The company’s 15,000 employees blend global consistency and local market knowledge across
100 countries to help clients run their operations more efficiently. Customers include pharmaceutical, consumer
health and medical device manufacturers and distributors, providers, payers, government agencies, policymakers,
researchers and the financial community.
As a global leader in protecting individual patient privacy, IMS Health uses anonymous healthcare data to deliver
critical, real-world disease and treatment insights. These insights help biotech and pharmaceutical companies,
medical researchers, government agencies, payers and other healthcare stakeholders to identify unmet treatment
needs and understand the effectiveness and value of pharmaceutical products in improving overall health
outcomes. Additional information is available at www.imshealth.com.
Mobile
A mobile version of this publication is available through the IMS Health Insights thought leadership app.
Access a range of healthcare white papers and material from IMS Health, providing insights on a myriad of
healthcare topics on key therapies and diseases, real-world evidence, commercial effectiveness and more.
Insights
Insights
©2015 IMS Health Incorporated and its affiliates. All rights reserved.
Trademarks are registered in the United States and in various other countries.
ORB1199

Advancing the Responsible Use of Medicines in Belgium

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