BHU Full Paper

Impact of marketing mix tools on Physicians prescribing behaviour- An exploratory study

Ms. Neeti Kasliwal

Assistant Professor,

Faculty of Management Studies,

Banasthali Vidyapith,

C-62, Sarojini Marg,

C-Scheme,

Jaipur,

Rajasthan

Contact No: 9829166007

Email id: [email protected]

Dr. Ipshita Bansal

Professor,

Faculty of Management Studies,

WISDOM,

Banasthali Vidyapith,

Banasthali,

Rajasthan

Contact No: 9414642479

Email id: [email protected]

Track: Strategic Marketing Initiatives

Impact of marketing mix tools on General Physicians prescribing behaviour- An exploratory study

Introduction

Pharmaceutical companies in India are directing their marketing efforts towards physicians as

they play a pivotal role in influencing their patients pattern of selecting and administering drugs,

hence making them the most important player in the pharmaceutical marketing system.

Therefore the intermediary role played by the doctors cannot be ignored as they are the key

decision makers who choose among array of drug alternatives but it is the patient who takes the

drug and ends up paying for the choices made by the physician (Gonul et al 2001).

Pharmaceutical companies try to influence prescription pattern of doctors in favour of their

drugs by offering various kinds of product attributes, pricing considerations, distribution and

logistics management and promotional inputs.

The pharmaceutical companies are spending a lot of money on marketing their products to

doctors. While the industry is driven by innovation, it spends an enormous amount of money on

marketing. It is estimated that the promotional and marketing expenditure on an average is 20-

30% of sales turnover or about two or three times the average expenditure on research and

development (Lancet 1993). The term promotion means those informational and marketing

activities, the purpose of which is to induce prescribing, supply or administration of medical

products (Walker G 1993). Hence an attempt to describe how and what doctors think while

prescribing is therefore an important part of enhancing the quality of the prescription process.

Thus regular, continuous study of the prescribing behaviour of doctors is essential for

pharmaceutical marketer so that the companies can draft their marketing plans according to the

characteristics and criterion of each physician market segment. Being able to identify prescribing

patterns through medical representatives’ (MRs) is very powerful tool for the companies. If a

certain doctor is given free samples of a drug, these MRs’ then track over the next weeks or

months whether the doctor has written new prescriptions for the drug. If the doctor doesn’t, then

they go in and try to modify their behaviour. If they know a doctor has recently switched and is

prescribing more of a rival drug, then they go in and say something negative about the rival drug

and persuade the doctors to switch to their company drug (Hopper et al 1997).

Review of Literature

Past studies have shown that the physicians’ prescribing behaviour can be influenced and

multiple factors are involved in physicians’ decision to change their prescribing habits

(Hartzema et al 1983, Armstrong et al 1996, Waheed Abdul Kareem et al 2007, Rahmer et al

2008, Crowe et al 2009, Suggs et al 2009, Theodorou et al 2009, Kotwani et al 2010, Karayanni

et al 2010, Neyaz et al 2011). Various studies have shown that doctors get influenced in their

prescription behaviour due to factors like trust, or the quality image of the pharmaceutical

manufacturer (Moss et al 2011), prioritize safety and efficacy over cost aspects while prescribing

(Rahmner et al 2008). A good number of studies have concluded that the physicians have a

positive attitude towards the pharmaceutical sales representatives (PSR) and they have an impact

on the prescribing of the physicians (Caudill et 1996, Wazana 2000, Prosser T et al 2003,

Watkins et al 2003, Chimonas et 2007, Lieb et al 2010, Saito et al 2010). The past studies have

also investigated that the promotional activities by the drug companies are ethical and

appropriate and also the doctors perceive that these interactions would affect the prescribing

behaviour of their colleagues more than their prescribing behaviour (Bhat AD 1993, Gonul et al

2001, Brett et al 2003, Verma SK 2004, Sierles F et al 2005, Saito et al 2010). The studies done

to explore the impact of gifts on prescribing behaviour have concluded that the gifts given by

pharmaceutical companies are considered gesture of interaction (Madhavan et al 1997, Gibbons

et al 1998, Pinto et al 2007) and GPs considered them as appropriate if these gifts are of

relatively lower costs and are benefitting the patients (Sharma et al 2010). Waheed Abdul

Kareem et al 2007 concluded that the tangible rewards to the physicians by the pharmaceutical

companies lead to prescription loyalty. The studies investigating the effect of marketing tools

and prescription behaviour have linked a positive correlation between the two (Girdharwal 2007,

Jayakumar 2008, Stros et al 2009). Karande et al 2005, Kotwani et al 2010 identified through

their study that there was lot of scope to improve rational drug use in India as over prescriptions

of antibiotics and poly pharmacy is the norm of the day. Mirza et al 2009 in their study also

found that the average medicines prescribed per patient in India was much higher as compared to

economically developed western countries. . Duerden Martin et al 2010 concluded in their study

that generic substitution would result in cost savings if generic and therapeutic substitution

would be adopted as a standard practice in secondary care by the prescribers.

Objectives of the study

In the light of the above review of literature and the issues raised the objectives of the present

study are to identify factors influencing General Physicians (GPs) prescribing behaviour with

respect to marketing mix tools used by the pharmaceutical companies. To fulfill the above

objective following hypothesis are proposed:

H1: Product Mix variables will have a significant influence on prescribing behaviour of GPs of

Rajasthan.

H2: Price Mix variables will have a significant influence on prescribing behaviour of GPs of

Rajasthan.

H3: Place Mix variables will have a significant influence on prescribing behaviour of GPs of

Rajasthan.

H4: Promotion Mix variables will have a significant influence on prescribing behaviour of GPs

of Rajasthan.

Research Methodology

For the purpose of the study, questionnaire was formulated and pretested among 10 GPs and was

revised to remove ambiguities in the process and then revised questionnaire was tested for

reliability and validated using Split Half Method and Reliability Coefficient Method which was

used to calculate the correlation coefficient among 2 split halves from reliability coefficient,

difficulty index, validity index and variance. The reliability coefficient was found to be 0.7648,

for product mix, 0.7229 for price mix and 0.7811 for promotion mix. The place mix reliability

coefficient was not performed as there were only two questions devoted for this P.

This standardized questionnaire was then administered to 300 General Physicians’ of Rajasthan.

The respondents (GPs) were selected from Rajasthan Medical Directory using convenience

sampling. They were first contacted through telephone and permission was taken to send them

the postal questionnaire. Then questionnaires were either emailed or posted to the doctors as

desired by them after the telephonic conversation. A covering letter explaining the purpose of

the study and reassuring that the responses given by them would be kept confidential and would

be used only for research work was sent along with a self stamped envelope which was also

included with each questionnaire. Respondents had the option of replying anonymously.

The total of 209 questionnaires were returned but 11 questionnaires were found to be incomplete

in their responses and were therefore rejected. Remaining questionnaires i.e. 198 were selected

for analysis, making a response rate of 66%. Descriptive statistics were used for examining the

perception of GPs across all demographic groups. The data was checked for normality and then

ANOVA and Z test were applied to examine the significance of difference between the mean

scores of different groups.

Findings and Analysis

Table 1: Demographic Profile of the Sample

Respondents Characteristic N Percentage

Employment status of the doctors

Government Sector Doctor

Private Sector Doctor

Self Employed Doctor

71

63

64

36%

32%

32%

Years of experience of the doctors

1-5 years of exp

6-10 years of exp

11-20 years of exp

21-30 years of exp

31-40 years of exp

41 & above years of exp

10

12

47

63

35

31

5%

6%

24%

32%

18%

16%

Age of the doctors

25-35years of age

36-40 years of age

41-45 years of age

46-50 years of age

51-60 years of age

61 & above years

9

16

21

29

68

55

5%

8%

11%

15%

34%

28%

City of doctors

City 1(pop>1 million)

City 2(pop within 0 .5 million -1 million)

City3(pop within 0.1 -0.5 million)

City4(pop < 0.1 million)

90

38

60

10

45%

19%

30%

5%

As depicted in Table 1, out of total of 198 GPs, 71 (36%) GPs were practicing in Government

Sector; 63(32%) in private sector and 64 (32%) were self employed. The GPs age in the study

was categorized into six categories and 9 (5%) GPs were found to be in 25 -35 years of age, 16

(8%) GPs were in age group of 36-40 years, 21 (11%) in 41-45 years, 29 (15%) of GPs in 46-50

years, 68 (34%) in 51-60 years and 55 (28%) in 61 &above years of age. Also the work

experience of the doctors was categorized in six categories and 10 (5%) GPs had 1-5 years of

experience followed by 12 (6%) GPs with 6-10 years of experience, then 47 (24%) GPs had 11-

20 years of experience, 63 (32%) had 21-30 years of experience, 35 (18%) GPs had 31-40 years

of experience and 31 (16%) GPs had 41 &above years of experience. The total number of GPs

who were practicing in cities having a population more than 1 million was 90 accounting to 45%

while 38 (19%) GPs were practicing in cities having a population within 0.5 – 1.0 million, 60

(30%) GPs were practicing in cities where the population was within 0.5-0.5 million and 10

(5%) doctors were practicing from cities having a population of less than 0.1 million accounting

to .9% of the total sample. Table 2, 3 4 5 depicts the results of ANOVA and Table 6,7,8,9

showing the results of Z-test used for hypothesis testing.

ANOVA results:

Table 2a: ANOVAs for Product Mix as City as a factor

Source of variations Sum of Squares

dfMean Square

F Sig.

Sharing of research feedback by company

Between Groups 6.515 3 2.172 3.907 .010**

Within Groups 107.828 194 .556

Total 114.343197

**p<=0.01

The results of one way ANOVA shows that all the General Physicians with different

demographic profiles demonstrated different responses for the product attributes, price attributes,

place attributes and promotional attributes of the drug.

As shown in Table 2a, the difference in importance given to sharing of feedback of research by

the company and research and development status of the company was found to be significant

among GPs of different cities. The difference was found to be statistically highly significant

(p<=.01). The GPs of Rajasthan practicing in different cities showed their preference towards

that company’s drug which shares the research feedback with the general physicians. The

importance attached to this factor pertaining to the product mix suggests that the companies

should focus their attention by giving the appropriate and timely research feedback to the GPs to

get the mind share of the GPs practicing in different cities of Rajasthan state. The other factors

like efficacy of the dug, drug delivery mode, recommended daily schedule, safety profile,

palatability, US FDA approval status, previous experience with the drug, peer group//colleagues

advice and trust on the company medicine were the other factors where the variations in the

prescribing was found to be insignificant.

Table 2b: ANOVAs for Product Mix as Year of experience as a factor

Source of variations

Sum of Squares

dfMean Square

F Sig.

Packaging quality and shelf life

Between Groups 7.547 5 1.509 2.978 .013*

Within Groups 97.327 192 .507

Total 104.874 197

*p<.05

The above Table 2b, depicts the variation in factor of packaging quality and shelf life of the drug

was also found to be significant (p<.05) among different years of experience of GPs. This means

that different years of experience of GPs considered packaging quality and shelf life of the drug

as the variations was found to be statistically significant factor while prescribing a drug to their

patients as compared to other GPs who did not show much variance in packaging quality and

shelf life of the drug while prescribing.

Table 3a: ANOVAs for Price mix as age as a factor


Sum of Squares dfMean Square

F Sig.

Financial status of patient

Between Groups

9.327 5 1.865 2.451 .035*

Within Groups 146.128 192 .761 Total 155.455 197

*p<0.05

Table 3a, shows that in the study, the variation in influence of price attributes of the drug

particularly affordability (financial status of the patient) was found to be significantly different

(p<.05) among GPs in different age groups. Different age groups of GPs considered cost to the

patient which is price of the drug as the prime criteria of variations in behaviour thereby

influencing the choice of the drug.

Table 3b: ANOVAs for Price mix as Years of experience as a factor



F Sig.

Insurance status of the patient

Between Groups

11.379 5 2.276 2.256 .050*

Within Groups 193.677 192 1.009 Total 205.056 197

*p<=0.05

Further, variation of influence of insurance status of the patient was found to significantly

different (p<=.05) among GPs with different numbers of years of practice depicted in Table 3b.

As the insurance status of patient is one of the factor showing differences in prescribing

behaviour among GPs with different work experience this means that the GPs they tend to

affected by price variable of the drug when it comes to prescribing the drugs for their patients for

which the third party is bearing the cost of the medical treatment.

Table 3c: ANOVAs for Price mix as Employment Status as a factor



F Sig.

Education status of patient

Between Groups

9.779 2 4.889 4.937 .008**


**p<0.01

Further it was also observed that the variation in education level of the patient was found to be

highly significant factor (p<.01) influencing the GPs with different employment status as

depicted in Table 3c. Since the clientele significantly varies when it comes to the government

sector doctors as compared to private and self employed and the education status of the patient

was given the maximum weight age by the private sector GPs (Mean =3.7)

Table 4a: ANOVAs for Promotion Mix as Age as a factor



F Sig.

MR Product Knowledge

Between Groups

17.302 5 3.460 2.369 .041*


Frequency of prescribing OTC drug

Between Groups

14.018 5 2.804 2.987 .013*


*p<0.5

As shown in Table 4a, interestingly the perception of promotion attributes relating the medical

representatives product knowledge and frequency of prescribing OTC (over the counter) drug

were found to be significantly different across specific categories of age of the GPs with age as

an important profile getting influenced by the above factors. Also shown in Table 4b the effect

of samples provided by MRs and frequency of prescribing OTC drug were found to be

statistically significant among GPs with different years of experience thereby showing variations

in preference towards samples and OTC drug, but it was only single factor which is frequency of

prescribing of OTC drug which was found to be significant factor influencing among GPs with

different city of practice as shown in Table 4c.

Table 4b: ANOVAs for Promotion Mix as years of experience as a factor



F Sig.

Samples provided by MR

Between Groups

15.871 5 3.174 2.853 .016*



Between Groups

11.586 5 2.317 2.436 .036*


*p<0.05

Table 4c: ANOVAs for Promotion Mix as City as a factor



F Sig.


Between Groups

8.982 3 2.994 3.136 .027*


*p<0.05

Table 5a: ANOVAs for Place Mix as years of experience as a factor

Source of variations Sum of Squares

dfMean Square

F Sig.

Availability of drug in the vicinity of the patient

Between Groups

4.437 5 .887 2.584 .027*

Within Groups

65.927 192 .343

Total 70.364 197 *p<0.05

Moreover the study also revealed that the influence of place attributes which corresponds to the

availability of the drug in the vicinity of the patient was also found to be significantly different

among GPs with different years of experience thereby affecting their prescribing decisions.

Z-results:

Table 6: PRODUCT MIX

Sample criteria N Mean SD Z p-value

36-40 years of age

Others

16

182

51.75

49.24

3.316

4.941

2.77 <.05

6-10 years of exp

Others

12

186

51.50

49.31

2.812

4.951

2.46 <.05

31-40 years of exp 63 48.27 5.903 -2.07 <.05

Others 135 49.90 4.223

City4(pop < 0.1 million)

Others

4

194

45.00

49.53

2.582

4.869

-3.38 <.01

As seen in Table 6, we can see that GPs with age group of 36-40 years of age considered product

attribute of the drug more important (mean =51.75) as compared to other GPs as in starting of

their career, the drug attributes have to play a significant role in prescribing it as we can see that

GPs with a work experience of 6- 10 years also gave more importance to product attributes of the

drug while prescribing as compared to other GPs. We can see from the above table that GPs with

an experience of 31-40 years were negatively influenced by the product mix attributes of the drug.

This means that as the work experience increases the importance attached to the product attributes

decreases. While not only work experience but also the practicing city of the GPs i.e. GPs who are

practicing in cities having a population of less than 0.1 million were also found to be negatively

influenced with the product attributes of the drug. This means that there are some other factors

which are considered more important by these GPs other than product attributes. Hence H1 is

accepted.

Table 7: PRICE MIX


25-35 years of age

Others

9

189

16.44

14.96

1.878

2.647

2.26 <.05

1-5 years of exp

Others

10

188

16.55

14.95

2.223

2.634

2.13 <.05

21-30 years of exp

Others

35

163

13.89

15.27

3.141

2.452

-2.45 <.05

Private Sector

Others

63

135

15.56

14.78

2.168

2.795

2.13 <.05

As depicted in Table 7, the effect of price mix on 25-35 years of age of the GPs and 1-5 years of

experience among the GPs were found to be statistically significant and this segment of GPs were

more influenced by the price factor of the drug while prescribing. Similarly, the price mix of the

drug was found to be affecting the private sector GPs more than the others as they considered their

patients financial and insurance status before prescribing. It was also observed that the GPs from

21-30 years of experience were negatively influenced by the price attribute of the drug and this

negative influence was statistically significant. This means that these practitioners were less price

sensitive as compared to their colleagues. Therefore H2 is accepted.

Table 8: PROMOTION MIX


25-35 years of age

Others

9

189

16.44

14.96

1.878

2.647

2.26 <.05

31-40 years of experience

Others

35

163

24.11

26.84

6.110

6.138

-2.39 <.05

Table 8 shows the influence of promotion mix on the prescription behaviour of the GPs of

Rajasthan and contrary to the perception that it was only the GPs of 25-35 years of age were

strongly influenced by the promotional tactics done by the pharmaceutical industry. This could be

because at this age the GPs are young and are more receptive to pharmaceutical promotions and

get easily influenced by the promotional tactics of the companies. The table also shows the

negative influence of drug promotions (Z=-2.39) on GPs with 31-40 years of work experience as

compared to others GPs. One of the reason can be that the because of such vast and rich

experience in the industry they consider these activities as unethical having a latent desire to sell

the company’s product rather than benefitting the patient and the health care industry. So H3 is

accepted.

Table 9: PLACE MIX


61 & above years of age

Others

55

143

5.44

5.07

.957

1.208

2.23 <.05

41 &above years of exp

Others

31

167

5.58

5.10

.958

1.173

2.49 <.05

Table 9 depicts a significant influence of place mix on the prescribing behaviour of senior GPs

of age group of 61 &above years with an experience of 41& above years of practicing. The

readily available drug in the market within the vicinity of the patient was considered an

important factor by the senior most doctors of the study as they know through their experience

that convenience and urgency are the two most important criteria patient considers before buying

the prescription drug otherwise they rate the doctors as not the competent enough to solve their

problem. Henceforth H4 is accepted.

Discussion

One of the major findings of the study is that the GPs prescribing behaviour can be influenced

and there are major factors involved in influencing the behaviour. Moreover the physician’s

characteristics also have a major role to play in identifying the stimuli from the external

variables which results in changing in prescribing pattern. The result of the study goes in line

with the past studies done by Hartzema Abraham et al., 1983 where it was identified that several

non medical factors are important predictors of total prescribing volume among the physicians in

the study. The study done by Armstrong et al., 1996 identified factors like reading and advice

from professional colleagues were involved in GPs decision to change their prescribing habits.

Wun et al., 2002 also considered demographical variables’ like physicians practicing status,

gender, higher qualifications, years in primary care as global characterises influencing

prescribing. In our study also we found that demographic variables like age of the doctor,

employment of the doctor, years of practice of the doctor and city of the doctor were responding

differently to the marketing stimuli of product, price, place and promotional variables of the

pharmaceutical marketing system which led to variations in the prescribing behaviour of the GPs

of Rajasthan. The physicians prescribing behaviour in our study was more effected by the

product , price, promotion, and place attribute of the drug which goes in line with the studies

done by Girdharwal,2007 where similar factors were found to be influencing the physicians

prescribing behaviour. Similar to the studies of Chew LD et al., 2000, Morgan et al., 2006,

Warrier et al., 2010 where drug samples led the prescribers to prescribe them even if they were

not their preferred choice, our study also shows that the years of practice of the GPs showed a

significant difference in importance attached to free samples given by the MRs of the

companies. But demographic profile pertaining to city of the GPs, age of GPs and employment

status of GPs did not show any significant difference with reference to samples provided by the

companies. But distribution of leaflets and brochures, academic sponsorships by the companies,

source of information of new drugs received through colleagues were found to be non significant

factors among GPs of Rajasthan which equates to past studies results where the information

presented in brochures and materials distributed to the doctors by the companies were found to

be untrue and claims were found to be unsubstantiated and did not comply with FDA regulations

(Stryer et a.,1994, Gitanjali et al., 1997, Cardarelli et al., 2006, Othman et al., 2009) while study

results are contrary to the study done by Saito et al., 2010 where doctors meet with MRs and

value information they receive from them, Oshikoya et al., 2011 where majority of the doctors

relied on the information from pharmaceutical companies in the form of drug promotion forums

and launches although the validity of such kind of information was a big question in the doctor’s

mind. The drug promotion has a significant effect on the prescribing behaviour of the GPs in our

study which has a mixed bag of results pertaining to literature review. The medical

representatives product knowledge were found to be significantly different across specific age

categories of GPs in our study which can be linked with the past studies of Caudill et al., 1996,

Lagerlov Per et al., 2000 where a positive correlation was found prescribing behaviour and

information provided by the PSR (pharmaceutical sales representatives) and were considered

preferable promotional tool by doctors as compared to free camps and samples (Arora et al.,

2006).

Further the study showed that the influence of price attributes of the drug particularly

affordability (financial status of the patient) was found to be significantly different (p<.05)

among GPs in different age groups. Moreover the study also revealed that the influence of place

attributes which corresponds to the availability of the drug was also found to be significantly

different among GPs with different years of practice thereby affecting their prescribing decisions

was in line with the study done by Ijaoma et al., 2010 where doctors admitted that despite the

promotional strategies employed by the companies the most influencing factor was the economic

status of the patient followed by drug availability.

Conclusion

GPs with different demographic profiles in our study have exhibited a significant effect of

product mix, price mix, place mix and promotion mix parameters on their prescribing behaviour

thereby giving an input to the pharmaceutical marketers to focus their marketing efforts to a

segment of doctors with the appropriate marketing mix. Marketing of pharmaceuticals is of

crucial importance from an economic and social welfare perspective. The relationship between

doctors and drug companies have come under intense scrutiny in recent years as there is a

widespread scepticism about the intent of industry and concern for the vulnerability of doctors in

the relationship. This study provides a framework for marketers so that wasteful expenditure on

the marketing of drugs should be cured thereby increasing the overall quality of healthcare

profession.

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