Transferability of health cost evaluation across locations in oncology: cluster and principal component analysis as an explorative tool

BMC Health Services Research

Isabelle Ray-Coquard⁵  Jean-Yves Blay²  Dominic Cellier¹  Olivier Collard³  Vincenzo Baldo^1,13  Mathieu Laramas⁷  Fadila Farsi⁴  Bertrand Favier^1,14  Amaury Martin⁸  François Noël Gilly^1,12  Carlo Riccardo Rossi^1,10  Petrus J Pauwels⁸  Françoise Ducimetière⁵  Patrick Sylvestre Baron^1,11  Giuseppe Mastrangelo⁶  Alessandra Buja^1,13  Lionel Perrier⁹ 

[1]Department Cancer and Environnement, Cancer Centre Léon Bérard, 28 rue Laennec, Lyon Cedex 08, 69373, France

[2]University of Lyon, Department of Medical Oncology, Cancer Centre Léon Bérard, 28 rue Laennec, Lyon Cedex 08, 69373, France

[3]Department of Medical Oncology, Institut de Cancérologie Lucien Neuwirth, 108 B Avenue Albert Raimond, Saint-Priest-en-Jarez, 42270, France

[4]Réseau Espace Santé Cancer, Rhône-Alpes, 60 avenue Rockefeller, Lyon, 69008, France

[5]Cancer Centre Léon Bérard, INSERM EAM 4128 Santé-Individu-Société, University of Lyon, 28 rue Laënnec, Lyon Cedex 08, 69373, France

[6]Department of Cardiac Thoracic and Vascular Sciences, University of Padova, Padova, 35122, Italy

[7]Department of Medical Oncology, University Hospital of Grenoble, Grenoble cedex 09, 217 38043, BP, France

[8]Cancéropôle Lyon Auvergne Rhône-Alpes, 60 avenue Rockefeller, Lyon, 69008, France

[9]Clinical Research and Innovation Direction (DRCI), Cancer Centre Léon Bérard, 28 rue Laënnec, Lyon, 69008, France

[10]Melanoma and Sarcomas Unit, Veneto Institute of Oncology, IOV, IRCCS, University of Padova, Padova, 35128, Italy

[11]Economics Department, University of Lyon, Lyon, 69007, France

[12]University of Lyon, Department of Digestive Surgery, University Hospital Lyon Sud, 165 Chemin du Grand Revoyet, Pierre Bénite, 69310, France

[13]Department of Molecular Medicine, Laboratory of Public Health and Populations Studies, University of Padova, Padova, 35122, Italy

[14]Pharmacy, Cancer Centre Léon Bérard, 28 rue Laënnec, Lyon Cedex 08, 69373, France

关键词: Variability;    Transferability;    Sarcoma;    Principal component analysis;    Oncology;    Economic evaluation;    Cost;    Cancer network;    Cluster analysis;   

Others  :  1091653
DOI  :  10.1186/s12913-014-0537-x

 received in 2014-01-27, accepted in 2014-10-17,  发布年份 2014

【 摘 要 】

Background

The transferability of economic evaluation in health care is of increasing interest in today’s globalized environment. Here, we propose a methodology for assessing the variability of data elements in cost evaluations in oncology. This method was tested in the context of the European Network of Excellence “Connective Tissues Cancers Network”.

Methods

Using a database that was previously aimed at exploring sarcoma management practices in Rhône-Alpes (France) and Veneto (Italy), we developed a model to assess the transferability of health cost evaluation across different locations. A nested data structure with 60 final factors of variability (e.g., unit cost of chest radiograph) within 16 variability areas (e.g., unit cost of imaging) within 12 objects (e.g., diagnoses) was produced in Italy and France, separately. Distances between objects were measured by Euclidean distance, Mahalanobis distance, and city-block metric. A hierarchical structure using cluster analysis (CA) was constructed. The objects were also represented by their projections and area of variability through correlation studies using principal component analysis (PCA). Finally, a hierarchical clustering based on principal components was performed.

Results

CA suggested four clusters of objects: chemotherapy in France; follow-up with relapse in Italy; diagnosis, surgery, radiotherapy, chemotherapy, and follow-up without relapse in Italy; and diagnosis, surgery, and follow-up with or without relapse in France. The variability between clusters was high, suggesting a lower transferability of results. Also, PCA showed a high variability (i.e. lower transferability) for diagnosis between both countries with regard to the quantities and unit costs of biopsies.

Conclusion

CA and PCA were found to be useful for assessing the variability of cost evaluations across countries. In future studies, regression methods could be applied after these methods to elucidate the determinants of the differences found in these analyses.

【 授权许可】

   
2014 Perrier et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

【 参考文献 】

• [1]Nixon J, Rice S, Drummond M, Boulenger S, Ulmann P, de Pouvourville G: Guidelines for completing the EURONHEED transferability information checklists. Eur J Health Econ 2009, 10:157-165.
• [2]Eldessouki R, Smith MD: Health care system information sharing: a step toward better health globally. Value Health Regional Issues 2012, 1:118-129.
• [3]Drummond M, Manca A, Sculpher M: Increasing the transferability of economic evaluations: recommendations for the design, analysis, and reporting of studies. Int J Technol Assess Health Care 2005, 21:165-171.
• [4]Sculpher MJ, Pang FS, Manca A, Drummond MF, Golder S, Urdahl H, Davies LM, Eastwood A: Generalisability in economic evaluation studies in healthcare: a review and case studies. Health Technol Assess 2004, 8:1-192.
• [5]Drummond MF, Bloom BS, Carrin G, Hillman AL, Hutchings HC, Knill-Jones RP, de Pouvourville G, Torfs K: Issues in the cross-national assessment of health technology. Int J Technol Assess Health Care 1992, 8:671-682.
• [6]Goeree R, He J, O’Reilly D, Tarride JE, Xie F, Lim M, Burke N: Transferability of health technology assessments and economic evaluations: a systematic review of approaches for assessment and application. Clinicoecon Outcomes Res 2011, 3:89-104.
• [7]Drummond M, Barbieri M, Cook J, Glick HA, Lis J, Malik F, Reed SD, Rutten F, Sculpher M, Severens J: Transferability of economic evaluations across jurisdictions: ISPOR good research practices task force report. Value Health 2009, 12:409-418.
• [8]Manca A, Sculpher MJ, Goeree R: The analysis of multinational cost-effectiveness data for reimbursement decisions: a critical appraisal of recent methodological developments. Pharmacoeconomics 2010, 28:1079-1096.
• [9]Rice N, Jones A: Multilevel models and health economics. Health Econ 1997, 6:561-575.
• [10]Grieve R, Nixon R, Thompson SG, Normand C: Using multilevel models for assessing the variability of multinational resource use and cost data. Health Econ 2005, 14:185-196.
• [11]Grieve R, Nixon R, Thompson SG, Cairns J: Multilevel models for estimating incremental net benefits in multinational studies. Health Econ 2007, 16:815-826.
• [12]Pinto EM, Willan AR, O’Brien BJ: Cost-effectiveness analysis for multinational clinical trials. Stat Med 2005, 24:1965-1982.
• [13]Willan AR, Pinto EM, O’Brien BJ, Kaul P, Goeree R, Lynd L, Armstrong PW: Country specific cost comparisons from multinational clinical trials using empirical Bayesian shrinkage estimation: the Canadian ASSENT-3 economic analysis. Health Econ 2005, 14:327-338.
• [14]Manca A, Lambert PC, Sculpher M, Rice N: Cost-effectiveness analysis using data from multinational trials: the use of bivariate hierarchical modeling. Med Decis Making 2007, 27:471-490.
• [15]Thompson SG, Nixon RM, Grieve R: Addressing the issues that arise in analysing multicentre cost data, with application to a multinational study. J Health Econ 2006, 25:1015-1028.
• [16]Pang F: The application of multilevel modeling and cluster analysis to multinational economic evaluation data [abstract]. Value Health 1999, 2:s138.
• [17]Perrier L, Buja A, Mastrangelo G, Vecchiato A, Sandonà P, Ducimetière F, Blay JY, Gilly FN, Siani C, Biron P, Ranchère-Vince D, Decouvelaere AV, Thiesse P, Bergeron C, Dei Tos AP, Coindre JM, Rossi CR, Ray-Coquard I: Clinicians’ adherence versus non adherence to practice guidelines in the management of patients with sarcoma: a cost-effectiveness assessment in two European regions. BMC Health Serv Res 2012, 28:82. BioMed Central Full Text
• [18][http:/ / www.has-sante.fr/ portail/ upload/ docs/ application/ pdf/ 2011-11/ guide_methodo_vf.pdf] webcite Haute autorité de santé (HAS): Choix Méthodologiques Pour l'évaluation économique à la HAS. []
• [19]Ray-Coquard I, Montesco MC, Coindre JM, Dei Tos AP, Lurkin A, Ranchère-Vince D, Vecchiato A, Decouvelaere AV, Mathoulin-Pélissier S, Albert S, Cousin P, Cellier D, Toffolatti L, Rossi CR, Blay JY: Sarcoma: concordance between initial diagnosis and centralized expert review in a population-based study within three European regions. Ann Oncol 2012, 23:2442-2449.
• [20]Mastrangelo G, Fadda E, Cegolon L, Montesco MC, Ray-Coquard I, Buja A, Fedeli U, Frasson A, Spolaore P, Rossi CR: A European project on incidence, treatment, and outcome of sarcoma. BMC Public Health 2010, 12; 10:188. BioMed Central Full Text
• [21]Welte R, Feenstra T, Jager H, Leidl R: A decision chart for assessing and improving the transferability of economic evaluation results between countries. Pharmacoeconomics 2004, 22:857-876.
• [22]Manca A, Rice N, Sculpher MJ, Briggs AH: Assessing generasibility by location in trial-based cost-effectiveness analysis: the use of multilevel models. Health Econ 2005, 14:471-485.
• [23]Barbieri M, Drummond M, Willke R, Chancellor J, Jolain B, Towse A: Variability of cost-effectiveness estimates for pharmaceuticals in Western Europe: lessons for inferring. Value Health 2005, 8:10-23.
• [24]Birch S, Gafni A: Economics and the evaluation of health care programmes: generalisability of methods and implications for generalisability of results. Health Policy 2003, 64:207-219.
• [25]Breiman L, Friedman J, Olshen R, Stone C: Classification and Regression Trees. Chapman & Hall, Boca Raton; 1993.
• [26]Cox TF, Cox MA: Multidimensional Scaling. Chapman & Hall, Boca Raton; 2001.
• [27]Statistics toolbox. The Math Works, Inc. User’s Guide (Version 3); 2000.
• [28]Halkidi M, Batistakis Y, Vazirgiannis M: On clustering validation techniques. J Intell Inform Syst 2001, 17:107-145.
• [29]Subhash S, Kumar A: Cluster Analysis and Factor Analysis. The Handbook of Marketing Research, Chapter 18 2006.
• [30]Jolliffe I: Principal Component Analysis. Springer Verlag, Series in statistics, New York; 2010.
• [31]Jackson JE: A User’s Guide to Principal Components. Wiley & Son, Series in Probability and Statistics, New York; 2003.
• [32][http://factominer.free.fr/docs/HCPC_husson_josse.pdf] webcite Husson F, Pagès JJ: Principal component methods, hierarchical clustering, partitional clustering: why would we need to choose for visualizing data? []
• [33]Glickman SW, Boulding W, Roos JM, Staelin R, Peterson ED, Schulman KA: Alternative pay-for-performance scoring methods: implications for quality improvement and patient outcomes. Med Care 2009, 47:1062-1068.
• [34]Latry P, Martin-Latry K, Labat A e, Molimard M, Peter C: Use of principal component analysis in the evaluation of adherence to statin treatment: a method to determine a potential target population for public health intervention. Fundam Clin Pharmacol 2011, 25:528-533.
• [35]Berdeaux G, Viala M, Roborel De Climens A, Arnould B: Patient-reported benefit of ReSTOR® multi-focal intraocular lenses after cataract surgery: results of principal component analysis on clinical trial data. Health Qual Life Outcomes 2008, 6:1-9. BioMed Central Full Text
• [36]Barbieri M, Drummond M, Rutten F, Cook J, Glick HA, Lis J, Reed SD, Sculpher M, Severens JL: What do international pharmacoeconomics guidelines say about economic data transferability? Value Health 2010, 13:1028-1037.
• [37]Burn: 37 del 17/04/2007,(Codice interno: 196263) Deliberazione della giunta regionale n°734 del 20 marzo. Prestazioni di chemioterapia e radioterapia; 2007.
• [38][http://www2.arssveneto.it/html_pages/documents/Quaderno_3.pdf] webcite I quaderni dell’ARSS del Veneto: Totomographia ad emissione di positroni (PET): Valutazione del fabbisogno e piano di investimento per la Regione Veneto. Rapporto di Health Technology Assessement; []
• [39]Stiller CA, Trama A, Serraino D, Rossi S, Navarro C, Chirlaque MD, Casali PG: Descriptive epidemiology of sarcomas in Europe: report from the rarecare project. Eur J Cancer 2013, 49:684-695.
• [40]Standards, Options et Recommandations pour la prise en charge des patients adultes atteints de sarcome des tissus mous, de sarcome utérin ou de tumeur stromale gastro-intestinale. 1995.
• [41][http://progettooncologia.cnr.it/bridge/attivita-direzione.html] webcite Italian National Research Council in Italy. []
• [42]Guo JJ, Jing Y, Nguyen K, Fan H e, Kelton CM: Principal components analysis of drug expenditure and utilisation trends for major therapeutic classes in US Medicaid programmes. J Med Econ 2008, 11:671-694.
• [43]Holmes GM, Pink GH: Adoption and perceived effectiveness of financial improvement strategies in critical access hospitals. J Rural Health 2012, 28:92-100.
• [44]Ding C, He X: K-Means Clustering Via Principal Component Analysis. In Proceeding ICML’04: Proceedings of the 21th International Conference on Machine Learning. ACM, New York; 2004.