Heterogeneity in action: The role of passive personalization in comparative effectiveness research

Health Economics (United Kingdom)

Volumn 23, Issue 3, 2014, Pages 359-373

  Basu, Anirban ^a   Jena, Anupam B ^b   Goldman, Dana P ^c   Philipson, Tomas J ^d   Dubois, Robert ^e  

^a UNIVERSITY OF WASHINGTON   (United States)

^b HARVARD MEDICAL SCHOOL   (United States)

^c UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^d UNIVERSITY OF CHICAGO   (United States)

^e National Pharmaceutical Council   (United States)

Author keywords

antipsychotic drugs; comparative effectiveness; heterogeneity; passive personalization; schizophrenia

Indexed keywords

NEUROLEPTIC AGENT;

ADULT; COMPARATIVE EFFECTIVENESS; FEMALE; HEALTH CARE POLICY; HUMAN; MALE; MEDICAID; PERSONALIZED MEDICINE; PSYCHOLOGY; SCHIZOPHRENIA; STANDARDS; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; TREATMENT OUTCOME; UNITED STATES;

ADULT; ANTIPSYCHOTIC AGENTS; COMPARATIVE EFFECTIVENESS RESEARCH; FEMALE; HEALTH POLICY; HUMANS; MALE; MEDICAID; MODELS, ECONOMETRIC; PRECISION MEDICINE; SCHIZOPHRENIA; TREATMENT OUTCOME; UNITED STATES;

EID: 84894247800     PISSN: 10579230     EISSN: 10991050     Source Type: Journal    
DOI: 10.1002/hec.2996     Document Type: Article

References (34)

1. Basu A,. 2011a. Economics of individualization in comparative effectiveness research and a basis for a patient-centered health care. Journal of Health Economics 30 (3): 549-559.
2. Basu A,. 2011b. Estimating decision-relevant comparative effects using instrumental variables. Statistics in Biosciences 3 (1): 6-27.
3. Basu A,. 2013. Person-centered treatment (PeT) effects using instrumental variables. National bureau of economic research working paper No w18056. Journal of Applied Econometrics (In press).
4. Basu A, Rathouz P,. 2005. Estimating marginal and incremental effects on health outcomes using flexible link and variance function models. Biostatistics 6 (1): 93-109.
5. Basu A, Heckman J, Navarro-Lozano S, Urzua S,. 2007. Use of instrumental variables in the presence of heterogeneity and self-selection: an application to treatments of breast cancer patients. Health Economics 16 (11): 1133-1157.
6. Basu A, Jena AB, Philipson TJ,. 2011. The impact of comparative effectiveness research on health and health care spending. Journal of Health Economics 30 (4): 695-706.
7. Brookhart MA, Schneeweiss S,. 2007. Preference-based instrumental variable methods for the estimation of treatment effects: assessing validity and interpreting results. International Journal of Biostatistics 3 (1): 14.
8. Bruen B, Ghosh A,. 2004. Medicaid prescription drug spending and use. Kaiser Commission on Medicaid and the Uninsured Issue Paper. http://www.kff.org/medicaid/upload/Medicaid-Prescription-Drug-Spending-and-Use. pdf, accessed December 21, 2009.
9. Carniero P, Lee S,. 2009. Estimating distribution of potential outcomes using local instrumental variables with an application to changes in college enrollment and wage inequality. Journal of Econometrics 149: 191-208.
10. Clancy C, Collins FS,. 2010. Patient-centered outcomes research institute: the intersection of science and health care. Science Translational Medicine 2 (37): 37cm18.
11. Conway PH, Clancy C,. 2010. Charting a path from comparative effectiveness funding to improved patient-centered health care. Journal of the American Medical Association 303 (10): 985-986.
12. Gabler NB, Duan N, Liao D, et al,. 2009. Dealing with heterogeneity of treatment effects: is the literature up to the challenge? Trials 10: 43.
13. Garber AM, Tunis SR,. 2009. Does comparative-effectiveness research threaten personalized medicine? New England Journal of Medicine 360 (19): 1925-1927.
14. Gautschi O, Mack PC, Davies AM, Jablons DM, Rosell R, Gandara DR,. 2008. Pharmacogenomic approaches to individualizing chemotherapy for non-small-cell lung cancer: current status and new directions. Clinical Lung Cancer 9 (3): S129-S138.
15. Heckman JJ,. 1997. Instrumental variables: a study of implicit behavioral assumptions used in making program evaluations. Journal of Human Resources 32 (3): 441-462.
16. Heckman JJ,. 2001. Accounting for heterogeneity, diversity and general equilibrium in evaluating social programmes. The Economic Journal 111: F654-F699.
17. Heckman JJ, Vytlacil E,. 1999. Local instrumental variables and latent variable models for identifying and bounding treatment effects. Proceedings of the National Academy of Sciences 96 (8): 4730-4734.
18. Heckman JJ, Vytlacil E,. 2001. Local instrumental variables. In Nonlinear Statistical Modeling: Proceedings of the Thirteenth International Symposium in Economic Theory and Econometrics: Essays in the Honor of Takeshi Amemiya, Hsiao C, Morimue K, Powell JL, (eds.), Cambridge University Press: New York, 1-46.
19. Heckman JJ, Vytlacil E,. 2005. Structural equations, treatment effects and econometric policy evaluation. Econometrica 73 (3): 669-738.
20. Imbens G, Angrist J,. 1994. Identification and estimation of local average treatment effects. Econometrica 62 (2): 467-475.
21. Insel TR,. 2011. Rethinking schizophrenia. Director's Blog, National Institute of Mental Health. http://www.nimh.nih.gov/about/director/publications/ rethinking-schizophrenia.shtml, Accessed Sep 14, 2011.
22. Institute of Medicine. 2009. Initial national priorities for comparative effectiveness research: committee on comparative effectiveness research prioritization board on health care services http://www.iom.edu/CMS/3809/63608. aspx. Accessed May 21, 2009.
23. Jones PB, Barnes TR, Davies L, et al,. 2006. Randomized controlled trial of the effect on quality of life of second- vs first-generation antipsychotic drugs in schizophrenia: cost utility of the latest antipsychotic drugs in schizophrenia study (cutlass 1). Archives of General Psychiatry 63: 1079-1087.
24. Kantoff PW, Higano CS, Shore ND, et al,. 2010. Sipuleucel-T immunotherapy for castration-resistant prostate cancer. New England Journal of Medicine 363: 411-422.
25. Kaplan SH, Billimek J, Sorkin D, Ngo-Metzger Q, Greenfield S,. 2010. Who can respond to treatment?: Identifying patient characteristics related to heterogeneity of treatment effects. Medical Care 48 (6): S9-S16.
26. Kravitz RL, Duan N, Braslow J,. 2004. Evidence-based medicine, heterogeneity of treatment effects, and the trouble with averages. Milbank Quarterly 82 (4): 661-687.
27. Kreamer HC, Glick I, Klein DF,. 2009. Clinical trial design lessons from the CATIE study. American Journal of Psychiatry 166: 1222-1228.
28. Lieberman JA, Stroup TS, McEvoy JP, et al,. 2005. Effectiveness of antipsychotic drugs in patients with chronic schizophrenia. New England Journal of Medicine 353: 1209-1223.
29. Meltzer HY,. 1986. Novel approaches to the pharmacotherapy of schizophrenia. Drug Development Research 9 (1): 23-40.
30. Meltzer D, Basu A, Meltzer HY,. 2009. Comparative effectiveness research for antipsychotic medications: how much research is enough? Health Affairs 28 (5): w794-w808.
31. Rosenheck RA, Lieberman JA,. 2007. Cost-effectiveness measures, methods, and policy implications from the clinical antipsychotic trials of intervention effectiveness (CATIE) for schizophrenia. Journal of Clinical Psychiatry 68: e05.
32. Trusheim MR, Brendt ER, Douglas FL,. 2007. Stratified medicine: strategic and economic implications of combining drugs and clinical biomarkers. Nature Reviews Drug Discovery 6: 287-293.
33. Vytlacil E,. 2002. Independence, monotonicity, and latent index models: An equivalence result. Econometrica 70 (1): 331-341.
34. Wu AW, Snyder C, Clancy CM, et al,. 2010. Adding the patient perspective to comparative effectiveness research. Health Affairs 29 (10): 1863-1871.