Measuring the Informative and Persuasive Roles of Detailing on Prescribing Decisions

Measuring the Informative and Persuasive Roles of Detailing on

Prescribing Decisions

Andrew ChingMasakazu Ishihara

Rotman School of ManagementUniversity of Toronto

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

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.

Research Objectives

• Develop a structural model of physician demand that incorporates both informative and persuasive effects of detailing.

• Provide evidence on the relative importance of these two effects.

• Use the model to understand how the effectiveness of demand changes with the information set.

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 should allow us to identify the persuasive component of detailing.

• The total demand for these two drugs will then allow us to identify the informative component.

How to model the effect of detailing

• Persuasive effect: detailing goodwill stock in physicians’ utility function.

• Informative effect: – Learning; – Detailing goodwill stock reminds physicians

the most updated information about drugs.

• “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.

Mar. 93 Mar. 95 Mar. 97 Feb. 99Number of drugs 215 239 284 294

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.

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).

Model• Agents: physicians, patients, and a representative

opinion leader. There are J products.• There are J products and one outside alternative

(0).• Two product characteristics: price (pj), and quality

(qj).• Let I(t) = (I1(t),…,IJ(t)), be the information sets for q.

It is maintained by the representative opinion leader.

• Physicians are either well-informed about drug j (Ij(t)), or uninformed about drug j (Ij), where Ij is the initial prior for qj.

Bayesian updating of the public information set

• Experience signal: qijt = qj + δijt,where δijt ~ N(0, σ2

δ).• Initial prior for qj: N(qj, σ2).• Expected quality:

E[qj|I(t+1)] = E[qj|I(t)] + λj(t)(qjt – E[qj|I(t)]),where qjt is the sample mean of experiences signals revealed for product j in period t.

• Perception variance:σ2

j(t+1) = 1 / (1/σ2j(t) + κnjt/σ2

δ),where njt is the quantity sold for drug j in time t; 0<κ<1, is a scaling factor.

Physicians’ Choice• Patient i’s utility of consuming drug j:

uijt = α1 - exp(-rqijt) - πppjt + eijt.• If physician h is well-informed about drug j, his

expected utility of choosing drug j for patient i will be:E[Uhij|Ij(t)]= αj - exp(-rE[qj|Ij(t)]-1/2r2(σ2

δ+σj2(t))) - πppjt

+ γ Gjtp+ eijt,

where Gjtp =(1- ΦI) Gjt-1

p + Djt ,is the persuasive goodwill stock.

Physicians’ Choice (cont’d)

• If physician h is uninformed about drug j,E[Uhij|Ij]= α1 - exp(-rqj-1/2r2(σ2

δ+ σ2)) - πppjt + γ Gjt

p + eijt.

• First choose inside goods vs. outside good, and then choose one of the inside goods.

Measure of well-informed physicians

• Let Mjt be the measure of well-informed physicians about drug j at time t.

• Let GjtI be the detailing goodwill stock, and

ΦI be the depreciation rate.

• GjtI = (1- ΦI) Gjt-1

I + Djt.• Mjt = exp(β0 + β1 Gjt

I) / (1+exp(β0 + β1 GjtI)).

Marginal return of detailing

• Three factors that affect the marginal return of detailing:1) Effectiveness of detailing on building the

measure of well-informed physicians2) 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.

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 – Patented Medicine Prices

Review Board.• Why ACE-inhibitor with diuretic?

– No Direct-to-consumer advertising.– Merck and AstraZeneca sign a co-marketing agreement to

market Prinzide and Zestoretic, respectively. Prinzide and Zestoretic use exactly the same chemicals.

– Only three dominant drugs (Vaseretic, Zestoretic and Prinzide).

• Market size: ACE-inhibitors, ACE-inhibitors w/ diuretic, and Diuretics, Thiazide.

Brand Mean Standard deviation Max Min

Vaseretic 4,007.63 676.80 5,446 2,429

Zestoretic 6,388.75 4,900.28 16,330 322

Prinzide 1,814.82 1,168.92 4,447 131

Vaseretic 1,018.49 699.77 3,240 0

Zestoretic 1,603.68 850.52 4,203 0

Prinzide 512.75 650.67 3,566 0

Vaseretic 40.54 8.76 69.21 24.45

Zestoretic 34.29 8.65 61.48 15.74

Prinzide 38.68 15.60 87.46 16.15

Number of prescriptions

Detailing Minutes

Price

Summary Statistics

Estimates of learning parameters

Estimate s.e.Initial prior meanq1(vaseretic)

-23.94* 3.35

Initial prior meanq2(zestoretic/prinzide)

-24.88* 3.92

Initial prior variance σ2 0.45* 0.15True mean quality, q1 0

True mean quality, q2 14.29* 0.52

σδ2 0.84* 0.21

Preference parameters estimates

Estimates s.e.

alpha(vaseretic) -0.03 0.08

alpha(zestoretic) 0.04* 0.01

alpha(prinzide) 0

alpha(outside) 2.83* 0.18

gamma (persuasive effect)

2.6e-06* 3.4e-07

r 0.04* 0.004

Detailing stock parameters

Estimates s.e.

Persuasive depreciation, Φp

0.077* 0.005

Informative depreciation, ΦI

0.013* 0.006

Beta_0 -2.04* 0.06

Beta_1(informative effect)

1.5e-05* 3.0e-6

Two counterfactual experiments

• What happens to the diffusion rate – (i) if we eliminate the informative component

of detailing (i.e., set β1 = 0).– (ii) if we eliminate the persuasive component

of detailing (i.e., set γ=0).

Conclusion

• We find evidence that both persuasive and informative effects of detailing are presence and important in ACE-inhibitor with Diuretic market.

• The depreciation rate of the persuasive goodwill stock appear to be higher than that of informative goodwill stock.

• Detailing could be endogenous. Need to check robustness.