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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
Source of variations
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
Source of variations
Sum of Squares dfMean Square
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
Source of variations
Sum of Squares dfMean Square
F Sig.
Education status of patient
Between Groups
9.779 2 4.889 4.937 .008**
Within Groups 193.110 195 .990 Total 202.889 197
**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
Source of variations
Sum of Squares dfMean Square
F Sig.
MR Product Knowledge
Between Groups
17.302 5 3.460 2.369 .041*
Within Groups 280.421 192 1.461 Total 297.722 197
Frequency of prescribing OTC drug
Between Groups
14.018 5 2.804 2.987 .013*
Within Groups 180.189 192 .938 Total 194.207 197
*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
Source of variations
Sum of Squares dfMean Square
F Sig.
Samples provided by MR
Between Groups
15.871 5 3.174 2.853 .016*
Within Groups 213.584 192 1.112 Total 229.455 197
Frequency of prescribing OTC drug
Between Groups
11.586 5 2.317 2.436 .036*
Within Groups 182.621 192 .951 Total 194.207 197
*p<0.05
Table 4c: ANOVAs for Promotion Mix as City as a factor
Source of variations
Sum of Squares dfMean Square
F Sig.
Frequency of prescribing OTC drug
Between Groups
8.982 3 2.994 3.136 .027*
Within Groups 185.225 194 .955 Total 194.207 197
*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
Sample criteria N Mean SD Z p-value
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
Sample criteria N Mean SD Z p-value
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
Sample criteria N Mean SD Z p-value
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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