1. Measuring the Informative and Persuasive Roles of Detailing on Prescribing Decisions Andrew Ching Masakazu Ishihara Rotman School of Management University of Toronto

2. Pharmaceutical Detailing Detailing: sales reps from drug manufacturers visit doctors to discuss compliance information, side-effects, and efficacy studies. In 2003, detailing costs 8 billion dollars; journal advertising costs 0.46 billion dollars; direct-to-consumer (DTC) advertising costs 3.2 billion dollars. How does detailing affects demand? –Informative and reminding roles of detailing –Persuasive roles or “bribery” role

3. Motivation Whether detailing is persuasive or informative is a hotly debated topic. If detailing is mainly persuasive, policies of restricting detailing activities may be justified. If detailing is mainly informative, then it simply helps physicians to make informed choices. In general, it is hard to separately identify them with product level data. We propose a new identification strategy to separate them out.

4. Identification strategy Sometimes two drug companies sign a co-marketing agreement to market a drug - the same chemical is marketed by two companies under two different brand- names. Identification assumption: The informative component of detailing is chemical specific, while the persuasive component is brand-specific. Their relative demand of these two drugs and their relative detailing efforts should allow us to identify the persuasive component of detailing. The total demand for these two drugs and their total detailing efforts will then allow us to identify the informative component.

5. Research Objectives Provide new evidence on the relative importance of the informative and persuasive roles of detailing. To model persuasive detailing, allow a brand specific persuasive detailing goodwill stock to enter physicians’ utility functions (Nerlove and Arrow (1962)). Use two structural models to capture the informative roles: (i) Ching and Ishihara (2008), (ii) Narayanan, Manchanda and Chintagunta (2005).

6. Model First describe Model CI (Ching and Ishihara (2008)). Model NMC (Narayanan et al. (2005)), is a “special” case of Model CI. Informative effect: –Learning; –Informative detailing goodwill stock reminds physicians of the most updated information about drugs.

7. Model CI Agents: physicians, patients, and a representative opinion leader. There are J brands, and an outside alternative (0). There are K chemicals. Two product characteristics: price (p j ), and quality (q k ). Let I(t) = (I 1 (t),…,I K (t)), be the information sets for q. It is maintained by the representative opinion leader (captures peers in the field). Physicians are either well-informed about chemical k (I k (t)), or uninformed about chemical k (I k ), where I k is the initial prior for q k. The information set is chemical specific, not brand specific.

8. Bayesian updating of the public information set Experience signal: q ikt = q k + δ ikt, where δ ikt ~ N(0, σ 2 δ ). Initial prior for q k : N(q k, σ 2 ). Expected quality: E[q k |I(t+1)] = E[q k |I(t)] + λ k (t)(q kt – E[q k |I(t)]), where q kt is the sample mean of experiences signals revealed for chemical k in period t. Perception variance: σ 2 k (t+1) = 1 / (1/σ 2 k (t) + κn kt /σ 2 δ ), where n kt is the total quantity sold for brands that are made of chemical k at time t; 0<κ<1, is a scaling factor.

9. Physicians’ Choice Patient i’s utility of consuming brand j made of chemical k: u ijt = α 1 - exp(-rq ikt ) - π p p jt + e ijt. If physician h is well-informed about chemical k, his expected utility of choosing brand j for patient i will be: E[U hij |I k (t)] = α j - exp(-rE[q k |I k (t)]- 1/2r 2 (σ 2 δ +σ k 2 (t))) - π p p jt + γ G jt p + e ijt, where G jt p =(1- Φ I ) G jt-1 p + D jt,is the persuasive detailing goodwill stock. G jt p is brand specific.

10. Physicians’ Choice (cont’d) If physician h is uninformed about chemical k, E[U hij |I k ] = α 1 - exp(-rq k -1/2r 2 (σ 2 δ + σ 2 )) - π p p jt + γ G jt p + e ijt. First choose inside goods vs. outside good, and then choose one of the inside goods.

11. Measure of well-informed physicians Let M kt be the measure of well-informed physicians about chemical k at time t. Let G kt I be the detailing goodwill stock, and Φ I be the depreciation rate. G kt I = (1- Φ I ) G kt-1 I + D kt. M kt = exp(β 0 + β 1 G kt I ) / (1+exp(β 0 + β 1 G kt I )). D kt is the sum of detailing efforts of brands that are made of chemical k.

12. Model NMC Model NMC could be interpreted as a “special” case of Model CI. M kt = 1, for all k and t. Informative detailing provides noisy signals about the true quality of the drug (implicitly assume that drug manufacturers know the true quality of their own drugs when they introduce their drugs).

13. Data Monthly Canadian data on detailing, revenue and number of prescriptions from March 93 to Feb 99 for ACE-inhibitor with diuretic from IMS Canada. Why Canada? –Subject to price regulation. Why ACE-inhibitor with diuretic? –Only three dominant drugs (Vaseretic, Zestoretic and Prinzide). –Merck and AstraZeneca sign a co-marketing agreement to market Prinzide and Zestoretic, respectively. Prinzide and Zestoretic use exactly the same chemicals. –No Direct-to-consumer advertising. Market size: ACE-inhibitors, ACE-inhibitors w/ diuretic, and Diuretics, Thiazide.

16. Results Estimate a 2-brand version and a 3-brand version of each model. 2-brand version: Vaseretic and Zestoretic. 3-brand version: Vaseretic, Zestoretic and Prinzide. Because of the time constraint, I only report the results for Model CI. The results for Model NMC are similar.

17. Preference parameters estimates 2-brand3-brand Estimatess.e.Estimatess.e. alpha (vaseretic)-3.79*0.06-3.44*0.07 alpha (zestoretic)-3.83*0.02-3.29*0.09 alpha (prinzide)n.a.-3.31*0.09 gamma (persuasive effect) -1.53e-05*3.9e-062.29e-06*3.39e-07 r0.06*0.0020.03*0.0005

18. Estimates of learning parameters 2-brand3-brand Estimates.e.Estimates.e. Initial prior mean q 1 (vaseretic) -7.61*1.27-33.812.18 Initial prior mean q 2 (zestoretic/prinzide) -15.35*0.50-38.672.04 Initial prior variance σ 2 3.46*0.354.740.46 True mean quality, q 1 00 True mean quality, q 2 27.83*2.4814.561.38 σδ2σδ2 8.45*0.507.550.92

19. Detailing stock parameters 2-brand3-brand Estimatess.e.Estimatess.e. Persuasive depreciation, Φ p 0.194*0.0390.103*0.014 Informative depreciation, Φ I 0.043*0.0080.004*0.001 Beta_0 -2.09*0.31-1.07*0.15 Beta_1 (informative effect) 9.5e-05*1.5e-51.5e-05*1.1e-06

21. Two counterfactual experiments What happens to the diffusion rate –(i) if we eliminate the informative component of detailing (i.e., set β 1 = 0). –(ii) if we eliminate the persuasive component of detailing (i.e., set γ=0).

26. Conclusion We find evidence that both persuasive and informative effects of detailing are presence and important in ACE- inhibitor with Diuretic market. The informative component of detailing is responsible for market expansion for chemicals. The persuasive component is mainly responsible for brand switching. Public policy implications: If we restrict detailing activities (put a cap on how much drug companies can spend on detailing), we may slow down the rate of learning for physicians. Managerial implications: There is an informational externality problem. Need to take this into account when set up the contract for their co-marketing agreements.

27. “Many serious Adverse Drug Reactions (ADRs) are discovered only after a drug has been on the market for years. Only half of newly discovered serious ADRs are detected and documented in the Physicians’ Desk Reference within 7 years after drug approval.” Lasser et al. (2002) Journal of American Medical Association.

28. Number of active drugs in Cardiovasculars It is hard for physicians to keep track of the latest information about all the drugs. Some physicians may be busy and rely on the information provided by detailing. Some physicians rely on opinion leaders.

29. Literature Review Detailing can influence demand (reduced-form models) –Leffler (1981), Hurwitz and Caves (1988), Berndt, Bui, Lucking- Reiley and Urban (1997), Rizzo (1999), Gonul et al. (2001), Wosinska (2002), Azoulay (2002), etc. Models on choice under uncertainty: Erdem and Keane (1996) assume consumers learn via their own experience signals, firms know the true quality and use advertising to provide consumers with an alternative source of noisy signals. Papers related to E&K: Ackerberg(2003), Israel(2004), Crawford and Shum(2006) and Ching(2000), etc. Pharmaceutical Marketing: Mukherji (2003), Narayanan, Manchanda, and Chintagunta (2005).

38. Summary Statistics

39. Marginal return of detailing Three factors that affect the marginal return of detailing: 1)Effectiveness of detailing on building the measure of well-informed physicians 2)Changes in the choice probability of physicians who switch from uninformed to informed – depends on I(t) 3)Measure of well-informed physicians for opponent drug.