Advertisement

Evaluating the Impact of Treatment Effectiveness and Side Effects in Prescribing Choices

  • Tat Chan
  • Chakravarthi Narasimhan
  • Ying Xie
Chapter
Part of the International Series in Quantitative Marketing book series (ISQM, volume 20)

Abstract

Drugs can be effective in curing an illness or relieving a symptom but can have harmful side effects. The value of a drug, among others, depends on the trade-off between treatment effectiveness and side effects. There has been a long history that treatment effectiveness and safety are used as two of the most important attributes to determine the value of a drug. This chapter provides an overview of research on evaluating effectiveness and side effects of prescription drugs. We first briefly review the standard industry practice of using clinical trials data to measure the effectiveness and side effects of a drug. We then discuss how researchers may utilize clinical trials to gauge participants’ preferences. After that, we provide a literature review on studying treatment effectiveness and side effects using post-marketing prescription choice data. Lastly, we close the chapter with suggestions on future research questions, for both practitioners and academic researchers.

Keywords

Clinical Trial Data Discrete Choice Experiment Marketing Communication Prior Uncertainty Prescription Decision 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Berry S, Levinsohn J, Pakes A (2004) Differentiated products demand systems from a combination of micro and macro data: the new vehicle market. J Polit Econ 112(1):68–104CrossRefGoogle Scholar
  2. Bombardier C, Laine L, Reicin A, Shapiro D, Burgos-Vargas R, Davis B, Day R, Ferraz M, Hawkey C, Hochberg M, Kvien T, Schnitzer T (2000) Comparison of upper gastrointestinal toxicity of rofecoxib and naproxen in patients with rheumatoid arthritis. N Engl J Med 343(21):1520–1528CrossRefGoogle Scholar
  3. Bordeleau L, Pritchard KI, Loprinzi CL, Ennis M, Jugovic O, Warr D, Haq R, Goodwin PJ (2010) Multicenter, randomized, cross-over clinical trial of venlafaxine versus gabapentin for the management of hot flashes in breast cancer survivors. J Clin Oncol 28(35):5147–5152CrossRefGoogle Scholar
  4. Bresalier R, Sandler R, Quan H, Bolognese J, Oxenius B, Horgan K, Lines C, Riddell R, Morton D, Lanas A, Konstam M, Baron J (2005) Cardiovascular events associated with rofecoxib in a colorectal adenoma chemoprevention trial. N Engl J Med 352(11):1092–1102CrossRefGoogle Scholar
  5. Camacho N, Donkers B, Stremersch S (2011) Predictably non-Bayesian: quantifying salience effects in physician learning about drug quality. Mark Sci 30(2):305–320CrossRefGoogle Scholar
  6. Cannon CP, Braunwald E, McCabe C, Rader D, Rouleau J, Belder R, Joyal S, Hill K, Preffer M, Skene A (2004) Intensive and moderate lipid lowering with statins after acute coronary syndromes. N Engl J Med 350(15):1495–1504CrossRefGoogle Scholar
  7. Carey J, Capell K (2005) Side effects of the drug scares. BusinessWeek, 7 MarGoogle Scholar
  8. Chan T, Hamilton B (2006) Learning, private information and the economic evaluation of randomized experiments. J Polit Econ 115(6):997–1040CrossRefGoogle Scholar
  9. Chan T, Narasimhan C, Xie Y (2013) An empirical model of physician learning on treatment effectiveness and side effects. Manag Sci 59(6):1309–1325Google Scholar
  10. Ching A (2010) Consumer learning and heterogeneity: dynamics of demand for prescription drugs after patent expiration. Int J Ind Organ 28(6):619–638CrossRefGoogle Scholar
  11. Ching A, Ishihara M (2010) The effects of detailing on prescribing decisions under quality uncertainty. Qual Mark Econ 8(2):123–165.CrossRefGoogle Scholar
  12. Ching A, Ishihara M (2012) Measuring the informative and persuasive roles of detailing on prescribing decisions. Manag Sci 58(7):1374–1387Google Scholar
  13. Chintagunta PK, Jiang R, Jin GZ (2009) Information, learning, and drug diffusion: the case of Cox-2 inhibitors. Quant Mark Econ 7(4):399–443CrossRefGoogle Scholar
  14. Crawford G, Shum M (2005) Uncertainty and learning in pharmaceutical demand. Econometrica 73:1137–1174CrossRefGoogle Scholar
  15. Cutting Edge Information (2011) Per-patient clinical trial costs rise 70% in three years. http://www.cuttingedgeinfo.com/2011/per-patient-clinical-trial-costs/. Accessed 11 Feb 2012
  16. Efron B, Feldman D (1991) Compliance as an explanatory variable in clinical trials. J Am Stat Assoc 86:9–17CrossRefGoogle Scholar
  17. Frangakis CE, Rubin DB (1999) Addressing complications of intention-to-treat analysis in the combined presence of all-or-none treatment-noncompliance and subsequent missing outcomes. Biometrika 86:365–379CrossRefGoogle Scholar
  18. Hammer SM, Katzenstein DA, Hughes MD, Gundacker H, Schooley RT, Haubrich RH, Keith Henry W, Lederman MM, Phair JP, Niu M, Hirsch MS, Merigan TC (1996) A trial comparing nucleoside monotherapy with combination therapy in HIV-infected adults with CD4 cell counts from 200 to 500 per cubic millimeter. N Engl J Med 335:1081–1090CrossRefGoogle Scholar
  19. Hiatt WR (2006) Observational studies of drug safety—aprotinin and the absence of transparency. N Engl J Med 355(21):2171–2173CrossRefGoogle Scholar
  20. King MT, Hall J, Lancsar E, Fiebig D, Hossain I, Louviere J, Reddel HK, Jenkins CR (2007) Patient preferences for managing asthma: results from a discrete choice experiment. Health Econ 16(7):703–717CrossRefGoogle Scholar
  21. Lamiraud K, Geoffard P (2007) Therapeutic non-adherence: a rational behavior revealing patient preferences? Health Econ 16(11):1185–1204CrossRefGoogle Scholar
  22. Manchanda P, Xie Y, Youn N (2008) The role of targeted communication and contagion in new product adoption. Mark Sci 27(6):950–961CrossRefGoogle Scholar
  23. Manski C (2004) Measuring expectations. Econometrica 72(5):1329–1376CrossRefGoogle Scholar
  24. Narayanan S, Manchanda P (2009) Heterogeneous learning and the targeting of marketing communication for new products. Mark Sci 28(3):424–441CrossRefGoogle Scholar
  25. Narayanan S, Manchanda P, Chintagunta P (2005) Temporal differences in the role of marketing communication in new product categories. J Mark Res 42(3):278–290CrossRefGoogle Scholar
  26. Okie S (2005) Safety in numbers—monitoring risk in approved drugs. N Engl J Med 352:1173–1176CrossRefGoogle Scholar
  27. Venkataraman S, Stremersch S (2007) The debate on influencing doctors’ decisions: are drug characteristics the missing link? Manag Sci 53(11):1688–1701CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Washington University in St. LouisSt. LouisUSA
  2. 2.University of Texas at DallasRichardsonUSA

Personalised recommendations