Hôpitaux Universitaires de Genève. Utilités des tableaux de bord. Nathalie Vernaz Pharmacienne adjointe Responsable secteur Achat/Distribution

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1 Hôpitaux Universitaires de Genève Utilités des tableaux de bord Nathalie Vernaz Pharmacienne adjointe Responsable secteur Achat/Distribution Séminaire MAS Etre «FINANCEMENT les premiers pour DE LA SANTÉ, MÉDICO-ÉCONOMIE vous ET FLUX DU MÉDICAMENT» 24 septembre 2013

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3 Big Data Historique des Big Data Caractéristiques des Big Data From Big Data to Big Impact Utilités des tableaux de bord TB des écarts benchmarking Part de marché en DDD Modélisation 3

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6 Caractéristiques des Big Data Structurées Non structurées Tachymètre Diagramme polaire radar Texte Vidéo Audio Réseau sociaux Evolution des dépenses 300'000 des antibiotiques à l'hoger en Frs 200' ' histogramme ATC - Niveau 5 Libellé class. ATC niveau 5 Montan t 2008 Montan Ecart t 2009 Frs J01AA02 Doxycycline J01BA02 Thiamphénico l J01CA04 Amoxicilline 3'470 6'040 2'571 J01CA12 Pipéracilline 9' '669 6

7 Caractéristiques des Big Data Protection des données personnelles: challenge 7 IBM: Big Data

8 From Big Data to Big Impact 12 technologies qui vont révolutionner le monde -> McKinsey Global Institute 24 may 2013

9 Knowledge workers 9 McKinsey Global Institute 24 may 2013

10 From Big Data to Small Data 10 Akeu and Acker, 2013, p. 551

11 Objectif du Tableau de bord Diminution de l incertitude Diminution de la prise de risque Mesure des données de la vraie vie Synthétiser l information Mesurer la performance Mesurer la qualité Outil d aide à la décision 11

12 Utilités des tableaux de bord Utilité => comprendre de la demande => Réponse financière Réponse non financière Utilité => adapter la réponse: pertinence 12

13 networking Demande Modélisation Simulations techniques Time series analysis Spillover effect Evergreening extra costs Résistance antibiotique Hygiène des mains Intérêt Temps Offre 13 Aurich consulting: Business Intelligence

14 Outil pour synthétiser l information: Classification des médicaments WHO DDD: (Defined Daily Dose) -Dose usuelle journalière pour un adulte de 70kg -Limites pour la pédiatrie -Limites pour la dermatologie, l oncologie, l opthtalmologie 14 Interpharma (2008). «Le marché du médicament en Suisse.»

15 Outil de synthèse financier : Analyse des écarts: Montant = P * Q Causes externes aux HUG modification de la loi sur les produits thérapeutique modification prix lié à la concurrence Causes internes aux HUG coûts 1 patient Frs : 10 % des dépenses augmentations des consommations nouvelles pratiques 15

16 Analyse des écarts Montant = P * Q Période 1: P 1 et Q 1 Période 2: P 2 et Q 2 Ecart Q: (Q 2 - Q 1 ) * P 1 Ecart P: (P 2 - P 1 ) * Q 2 Montant = (Q 2 - Q 1 ) * P 1 + (P 2 - P 1 ) * Q 2 16

17 Tableau des écarts au niveau du code ATC ATC - Niveau 5 J06BA02 Libellé class. ATC niveau 5 Immunoglobulines humaines non spécifiques, application intravasculaire Montant (y) Montant (y+1) Ecart Mnt Art non renou v Art nouvea u Cause Prix Cause Q 520' ' ' '416-25'765 J05AR03 Ténofovir disoproxil et emtricitabine 375' ' ' '392 3'853 L04AB02 Infliximab 467' '211 58' '122 5'246 L01XC03 Trastuzumab - anticorps monoclonal contre HER-2 436' '758 51' '943 13'476 L01XC02 Rituximab - anticorps monoclonal anti-cd20 450' '576-40' '102-18'858 N02BE01 Paracétamol 110'405 96'091-14' '061-8'253 17

18 Tableau des écarts au niveau d un code ATC Int_Art_Ach Qté Qté Montan t Montant Ecart Mnt Art non renou v Art nouve au en Cause Prix Cause Qté Perfalgan fiol 1g=100ml (1 x 12) 1'626 1'433 71'513 63'176-8' '488 Dafalgan cpr 500mg (1 x 100) 2'862 2'816 15'935 11'372-4' ' Dafalgan cpr 1g (1 x 16) 3'423 4'617 6'309 7'806 1' '201 Perfalgan fiol Nour/Enf 500mg=50ml (1 x 12) '817 5'885-1' '786 Dafalgan Odis cpr sucer 500mg (1 x 16) 1'021 1'292 3'024 3' Dafalgan cpr eff 1g (1 x 20) 1'733 1'495 3'355 2' Dafalgan sir enf 30mg=1ml 90ml (pce) Dafalgan cpr eff 500mg (1 x 16) Dafalgan cpr 500mg (1 x 16) Dafalgan supp ad 600mg (1 x 10) Dafalgan supp 150mg (1 x 10) Dafalgan supp enf 300mg (1 x 10) Dafalgan supp bébé 80mg (1 x 10) Panadol cpr 500mg (1 x 20) '405 96'091-14' '061-8'253 18

19 Analyse longitudinale indicateur Frs vs g (DDD) Consommation du paracetamol en g Consommation du paracetamol en francs '000 7'000 6'000 5'000 4'000 3'000 2'000 1' Dafalgan Odis cpr sucer 500mg (1 x 16)g160.5 Perfalgan fiol 1g=100ml (1 x 12)g121 Dafalgan Odis cpr sucer 500mg (1 x 16)g160.5 Perfalgan fiol 1g=100ml (1 x 12)g121 19

20 Outil de comparaison: Benchmarking: % vs tot DDD indicateur: % DDD_meropenem par % DDD_(meropenem+imipenem) Période: décembre 2007 à mai 2008 au cumul 100% 90% 80% tot_ddd 70% % % % % % % 100 0% 0 PE - US/MED-A1 PE - US/MED-B2 DSP-sect.privé9FL NS-neuro 2FL PEUS/CHIRURGIE ME - 7EL AP-Clin.soins inten. NS - neurologie 2DL ME - 6FL RG-Unité 2 AK BS ME - 6DL DSP-Privés 8BL/8CL indicateur DDD_tot 20

21 Modélisation Simulations techniques Time series analysis Spillover effect Evergreening extra costs Résistance antibiotique Hygiène des mains 21 Aurich consulting: Business Intelligence

22 Hierarchy of Evidence for Assessing Effectiveness Level Description Example 22 I Strong evidence from at least ONE systematic review of well designed RCT II Evidence from at least one properly designed RCT of appropriate size III Evidence from well designed trials without randomization: cohort study, timeseries or matched case control studies IV Evidence from well designed nonexperimental studies from more than one centre or research group V Opinions from respected authorities, based on clinical evidence, descriptive studies or reports from committees VI Views of colleagues / peers Meta-Analysis The Cochrane Collaboration Articles published in peerreviewed journals Articles published in peerreviewed journals Articles published in peerreviewed journals Evidence based local procedures and care pathways Colleagues or members of the multidisciplinary team

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24 Spillover effect Financial impact of listing drugs in hospital restrictive drug formularies on the healthcare system as a whole Evergreening strategies Financial impact of the evergreening strategies on overall healthcare costs Swiss Canton of Geneva 24

25 1)Drug company invent a new drug a patent ( 20 years) 3 categories monopoly of drugs marketed make at different profit prices at the same time 2) After 20 years - the generic initially patented companies drug prices competition - the generic version of the brand 3)Patent drug and market slightly modified drugs - the follow-on maximise drug: their the profit brand? drug to which an evergreening strategy is applied Combination formulations alendronic acid combined with colecalciferol - alendronic acid alone, simvastatin combined with ezetimibe - simvastatin alone Structural analogues pregabalin for gabapentin Active metabolic desloratadine for loratadine Slow-release forms zolpidem extended release Single enantiomer omeprazole esomeprazole citalopram escitalopram cetirizine levocetirizine Hughes DA, Ferner RE (2010) New drugs for old: disinvestment and NICE. BMJ 340: c572

26 Costs of brand, follow-on, generic, and total prescriptions in millions of Euros In millions of euros Total Generic Brand Follow-on

27 Assume the replacement with the corresponding generic equivalent when available for prescriptions of 1) all brand drugs 2) all follow-on drugs 3) all brand & follow-on drugs 27

28 Extras costs of brand, follow-on, generic, and total prescriptions in millions of Euros ) 15.9 (95% CI 15.5; 16.2) In millions of euros 4 3 Scenario 1: no brand Scenario 2: no follow-on 2) 14.4 (95% CI 14.1; 14.7) 2 Scenario 3: no follow-on, no brand ) 30.3 (95% CI 29.8; 30.8) 28

29 Restrictive drug formularies Hospitals: - to minimise acquisition costs - to limit the number of medications available Pharmaceutical companies: - to buy and use their drug - spillover effect Hypothesis Hospital prescription patterns may influence prescription patterns in the community Tribune de Genève, 4 mars Wang YR, Pauly MV (2005) Spillover effects of restrictive drug formularies: a case study of PacifiCare in California. Am J Manag Care 11:

30 (1)inpatient setting (during hospitalisation) (2)community setting (3)hospital spillover setting: medications prescribed by HUG physicians but dispensed by community pharmacies Different rules (1)the inpatient setting a) drug prices are negotiated b) prescriptions are restricted (2)hospital spillover setting & community setting a) prices are fixed b) prescriptions unrestricted The Federal Authorities of the Swiss Confederation (1994) Loi fédérale du 18 mars 1994 sur l'assurance-maladie (LAMal).

31 100% Esomeprazole market share 90% 80% 70% 60% 50% 40% 30% inpatient model inpatient hospital spillover model hospital spillover community model community 20% 10% 0% switch to esomeprazole at HUG generic omeprazole % follow-on follow-on, generic, brand 100% levocetirizine market share 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% inpatient hospital spillover hospital spillover model community community model euros [95% CI ; ] Muijrers PE et al. Fam Pract 22: Helfenstein U (1996) Box-Jenkins modelling in medical research. Stat Methods Med Res 5: generic cetirizine switch to generic cetirizine at HUG

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33 Quantity and trends of antibiotic use in the canton of Geneva and at HUG. January 2000 to December 2007 Surrounding community University of Geneva Hospitals WHO Average monthly % of Average monthly use % of J01 classification Antimicrobial use use (min-max) a J01 use Trend P (min-max) b use Trend P J01 Total antibiotic use ( ) 100% upward ( ) 100% upward J01C amoxicillin/clavulanat 9.4 ( ) 17% 3.32 ( ) 23% upward < e downward 0.04 amoxicillin 1.55 ( ) 11% upward < ( ) 11% no piperacillin/tazobacta 0.46 (0-1.83) 1% < % upward m J01D cefazolin 0 0% 0.84 ( ) 2% downward < nd generation < ( ) 7% < cephalosporins c 1.3 ( ) 9% downward upward 3 rd generation < ( ) 10% < cephalosporins d 0.61 ( ) 4% upward upward cefepime 0 0% 2.51 (0-4.13) 5% downward < carbapenems 0 0% 2.55 ( ) 5% upward J01M fluoroquinolones 2.6 ( ) 18% upward < ( ) 14% no ofloxacin 0.1 ( ) 1% no ( ) 1% no ciprofloxacin 1.24 ( ) 9% upward < ( ) 9% upward norfloxacin 0.7 ( ) 5% upward < ( ) 3% downward < levofloxacin 0.26 ( ) 2% downward < ( ) 2% no moxifloxacin 0.28 (0-0.54) 2% upward < (0-0.65) 0% upward < J01FA macrolides e 2.13 ( ) 15% no (1.87-8) 7% no J01EE01 trimethoprim-sulfa 0.4 ( ) 3% downward < ( ) 3% upward J01XA glycopeptides 0 0% 1.61 ( ) 3% no a Quantities of antimicrobials expressed in DDD per inhabitants b Quantities of antimicrobials expressed in DDD per 100 patient-days 33 J Antimicrob Chemother Apr;66(4):

34 Antibiotic prescribing Quality indicator: outpatient fluoroquinolone use 34 - outside de Box-Plot: 18% at Geneva surrounding community - excess usage of fluoroquinolones can be associated with the development of resistance ESF EMRC EXPLORATORY WORKSHOP Antwerp, Belgium, 7-9 September Antibiotic Prescribing Quality Indicators.

35 Multivariate transfer function model of antibiotic use in both setting and temporal relation with the incidence of nonduplicate clinical isolates of E. coli resistant to cefepime per 100 patient-days. HUG January 2002 to December Variable Constant Lag a (months) Parameter b (SE) t-statistic P ceftriaxone HUG (0.0017) ciprofloxacin HUG (0.0013) (0.0014) cefepime HUG (0.0016) piperacilline/tazobactam HUG (0.0042) ciprofloxacin GE (0.0080) Autoregressive term c ( ) J Antimicrob Chemother Apr;66(4):

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37 Vigigerme launched in spring 2003 Clean care is safer care in autumn

38 Transfer function on MRSA incidence Variable Lag (month s) Parameter (SE) t- Statistic Constant (0.030) Fluoroquinolones (0.004) Macrolides (0.004) 3.61 < Macrolides (0.004) rd generation cephalosporins (0.006) rd generation cephalosporins (0.007) Cefepime (0.006) Piperacillin/tazobactam (0.014) P Clean Care is safer care campaign (0.005) < Autoregressive term (0.168) Moving average term (0.164)

39 Conclusion You can use all the quantitative data you can get, but you still have to distrust it and use your own intelligence and judgment. Alvin Toffler 39