Long term sustainability of SSN pharmaceutical coverage in Italy
description
Transcript of Long term sustainability of SSN pharmaceutical coverage in Italy
© Henley Business School 2008
Dr. Giampiero Favato
Henley Business School University of Reading
SEFAP University of Milan
Long term sustainability of SSN pharmaceutical coverage in ItalyA twenty year outlook (2005-2025)
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Long term sustainability of current SSN level of pharmaceutical coverage
Source: OSMED data 2007
?
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Key determinants of demand for pharma in public healthcare systems*
• Ageing– Increase Rx
volume
• Price– Generic
substitution– Shift to more
expensive alternatives
– Shift in demand• Morbidity• Mortality• Chronic illness rate• Physicians’
prescribing behaviour• Disposable income• Education• Access to healthcare* Majeed A, Malcom I (1999)
Source: OSMED data 2007
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Study objective
• To determine the long term impact of age and generic substitution on the Italian public pharmaceutical spending.
• Key assumptions:– Base year: 2005– Fundamental level of SSN pharmaceutical coverage
unchanged– No drastic shifts in pharmaceutical demand– All other determinants unchanged– Generics price = 40% of branded off-patent
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Quantifying the impact of ageing:the ASSET study (2007)
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ASSET outcomes• Patient and cost data were
obtained directly from computerised prescription records for a two year period, from January 2004 to December 2005.
• The ASSET sample totalled 3,175,691 residents.
• The ASSET mean costs were applied to the Istat projections of the Italian population (intermediate scenario)
* Favato G, Mariani P, Mills RW, Capone A, Pelagatti M, et al (2007) ASSET
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Impact of ageing on demand:+24% over twenty years (2005-2025)
0
20
40
60
80
100
120
2005
= 1
00
Ageing
Ageing 100 101 103 104 105 106 107 109 110 111 112 114 115 116 117 118 119 120 121 122 124
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
124
100
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Goodness of fit
Polynomial regression model:y = -0.0055x2 + 1.2906x + 98.759R2 = 0.9999
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20
40
60
80
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120
2005
= 1
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Ageing Poly. (Ageing)
Ageing 100 101 103 104 105 106 107 109 110 111 112 114 115 116 117 118 119 120 121 122 124
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
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Quantifying the impact of generics• Population: ISTAT projections 2005-2025 (intermediate
scenario) at year end.
• Impact of generic substitution: 40% price reduction, calculated at year end for each molecule going off patent on its average cost by age group (source: ASSET)
• The calculated reduction is then carried forward to the following year.
Patent expiration date2006 start A02BA03 A02BC03 A10BB12 C09BA01 G04CA02 J01CR01 J01CR02 M01AC02 M05BA04 N03AX09 N06AB06 Total 40% off end 2006
0-14 38.64 0.0000% 0.0471% 0.0032% 0.0021% 0.0251% 0.0187% 6.1652% 0.0003% 0.0079% 0.3506% 0.0408% 6.6610% 3.9966% 37.6115-24 42.98 0.0010% 0.8133% 0.0279% 0.0199% 0.1512% 0.0524% 5.8104% 0.0081% 0.0988% 1.2858% 1.7045% 9.9733% 5.9840% 41.2725-34 57.70 0.0012% 0.6058% 0.0208% 0.0148% 0.1126% 0.0390% 4.3280% 0.0060% 0.0736% 0.9578% 1.2697% 7.4293% 4.4576% 55.9935-44 85.64 0.0045% 0.7995% 0.0546% 0.0240% 0.1231% 0.0315% 3.1438% 0.0089% 0.0741% 0.5814% 1.2909% 6.1365% 3.6819% 83.5445-54 147.93 0.0109% 0.8867% 0.1702% 0.0595% 0.2999% 0.0226% 1.8354% 0.0114% 0.1578% 0.2755% 0.9277% 4.6576% 2.7946% 145.1755-64 288.84 0.0112% 0.8788% 0.2366% 0.1546% 1.0469% 0.0175% 0.9953% 0.0121% 0.4379% 0.1241% 0.5823% 4.4973% 2.6984% 283.6465-74 465.95 0.0100% 0.9625% 0.2342% 0.2460% 1.5817% 0.0162% 0.6080% 0.0135% 0.7837% 0.0555% 0.4978% 5.0091% 3.0054% 456.6175> 546.61 0.0088% 1.3595% 0.1699% 0.3137% 1.4274% 0.0156% 0.4676% 0.0127% 0.9847% 0.0390% 0.5816% 5.3804% 3.2282% 534.85
01/09/2006 01/04/2006 01/08/2006 01/12/2006 01/09/2006 01/10/2006 01/07/2006 01/02/2006 01/12/2006 01/08/2006 01/01/2006
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Time distribution of patent expiration
0
11
20
28
22
13
20
15
8 87
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0 0 0 0 0 0 0 00
5
10
15
20
25
30
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
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Expected impact of patent expirationby ATC class 2006-2017*
ATC Number of Cost savedclass products %
1st level off-patent classC 40 25.3%J 23 7.3%A 16 7.3%N 27 5.6%G 8 3.2%L 9 2.7%M 7 2.0%R 10 1.9%B 3 0.9%S 7 0.8%H 2 0.5%V 1 0.1%D 6 0.1%P 1 0.0%
Total 160 24.3%
* Patent expiration dates provided by AIFA
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Top ten molecules off patent by 2017
2005 % total cost 2025 % total costC10AA05 2.2777% atorvastatin 1 C10AA05 2.3445%C10AA01 2.2215% simvastatin 2 C10AA01 2.3165%C08CA01 1.9977% amlodipine 3 C08CA01 2.0945%A02BC01 1.9350% omeprazole 4 A02BC01 2.0054%A02BC05 1.2734% esomeprazole 5 C10AA03 1.2868%C10AA03 1.2387% pravastatin 6 A02BC05 1.2496%C09A05 1.1438% ramipril 7 L02BB03 1.2093%L02BB03 1.0975% bicalutamide 8 C09A05 1.1991%G04CA02 1.0468% tamsulosin 9 G04CA02 1.1138%C02CA04 1.0095% doxazosin 10 C02CA04 1.0515%A02BC03 0.9855% lansoprazole 11 C09DA04 1.0515%C09DA04 0.8762% irbesartan and diuretics 12 A02BC03 1.0240%Top 10 15.24% Top 10 15.8709%40% saved 6.10% 40% saved 6.3484%
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Generic substitution to offset theimpact of ageing population
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2005
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Ageing Ageing & generics Poly. (Ageing & generics) Poly. (Ageing)
Ageing 100 101 103 104 105 106 107 109 110 111 112 114 115 116 117 118 119 120 121 122 124
Ageing & generics 100 99 96 94 93 92 91 91 91 92 93 94 94 95 96 97 98 99 100 101 101
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
100
124
101
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Goodness of fit
0
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60
80
100
120
2005 =
100
Ageing Ageing & generics Poly. (Ageing & generics) Poly. (Ageing)
Ageing 100 101 103 104 105 106 107 109 110 111 112 114 115 116 117 118 119 120 121 122 124
Ageing & generics 100 99 96 94 93 92 91 91 91 92 93 94 94 95 96 97 98 99 100 101 101
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
Polynomial regression model:y = 0.0846 x2 – 1.6324x + 100.19R2 = 0.8854
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Sensitivity to generics’ price
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2005
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Generic price 20% off Base case (40% off) Generic price 80% off
Generic price 20% off 100 100 100 99 99 99 99 100 100 101 102 103 104 105 106 107 108 109 110 111 112
Base case (40% off) 100 99 96 94 93 92 91 91 91 92 93 94 94 95 96 97 98 99 100 101 101
Generic price 80% off 100 97 91 84 82 80 77 76 76 76 76 77 77 78 78 79 80 81 81 82 83
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
112
101
83
124
No generics
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The actual trend 2005-2008E* seems to confirm the ageing generic model
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2005
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Ageing Ageing & generics Actual
Ageing 100 101 103 104 105 106 107 109 110 111 112 114 115 116 117 118 119 120 121 122 124
Ageing & generics 100 99 96 94 93 92 91 91 91 92 93 94 94 95 96 97 98 99 100 101 101
Actual 100 100 95 93
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
* 2008 estimates based on Jan-Jun (-1.4% vs. 2007). Source: Il Sole 24 Ore
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Net effect of generic substitution:2001-2004 equilibrium
• ATC4 class growing:– 32.6% of drugs off-patent UP
leaders– 18.6% of drugs off-patent DOWN shift
• ATC4 class declining– 13.9% of drugs off-patent UP low impact– 34.5% of drugs off-patent DOWN shift
47%
53% sustainablecost reduction
potentialcost increase(therapy shift)
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Conclusions• Ageing and price are key determinants of pharmaceutical
demand in a state funded, open access social healthcare system like the Italian SSN.
• All else equal, by 2025 the expected ageing of the Italian population would increase the cost of the current public pharmaceutical coverage by 24%.
• Generic substitution could offset the upward trend driven by ageing.
• Cholesterol inhibitors and anti hypertensive agents could reduce the total cost of cardiovascular treatments by 25% .
• Due to time to patent expiration, the next couple of years would provide critical indications about the sustainability of the current pharmaceutical coverage provided by the SSN in Fascia A.
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All else equal… a major limitationof the age/generic substitution model
CHANGE
• Shift in pharmaceutical demand
• Accelerated shift to more expensive treatment options
• Physicians behaviour
• Patients behaviour
POLICY IMPLICATIONS
• Redefine levels of SSN coverage
• Outcome based prescribing guidelines
• Rationale prescribing
• Reduce moral hazard:– Link reimbursement to
compliance– Education: health as
capital