DIGITIZATION OF HEALTHCARE
INDUSTRY
MARKET RESEARCH REPORT
DEPARTMENT OF MANAGEMENT STUDIES
IIT ROORKEE
ii
TEAM MEMBERS
Jatin Dhawan
15810026
Harsh Bhushan
15810024
Aayush Rastogi
15810001
Ankush Partap Singh
15810005
Baljeet Singh
15810012
UNDER GUIDANCE
Dr. Jogendra Kumar Nayak
Assistant Professor, IIT Roorkee
iii
he authors of this report are highly grateful to Dr. J.K. Nayak, Assistant
Professor, Department of Management Studies, IIT Roorkee for providing this
opportunity to conduct a market research. The constant guidance and
encouragement received from him has been of great help for carrying out this
research work. Without his wise counsel, it would have been impossible to
complete the research work in this manner.
We would also like to express a deep sense of gratitude and thanks to all our
colleagues from IIT Roorkee who took out their precious time to respond to the
questionnaire which was designed to carry out this research work.
Finally, we are indebted to all the respondents of our survey from all over India
who contributed to our work.
Aayush Rastogi
Ankush Partap Singh
Baljeet Singh
Harsh Bhushan
Jatin Dhawan
T
ACKNOWLEDGEMENT
iv
his research aims at understanding the awareness about the online healthcare
services among the people of India. The research was conducted taking the
sample of population from various different states of India.
The research has demonstrated that most of the people in India are not aware
about the online healthcare consulting services. This indicates that there is a
communication gap between the consumers and the service providers. Those
who are aware of these services, most of them have never availed these services
online. Only a very small proportion of people have availed these services and
most of those belong to tier 1 cities like New Delhi, Mumbai or Pune. Also mostly
young generation was familiar with this sector while the elderly people were
unaware.
An interesting outcome of the research was that around 90% of the people who
have never availed these services would like to use such services in the future.
This indicates that there is a bright future for the Digital Healthcare sector in
India.
The research also indicated that non readiness of people to adopt such platform is
one of the reasons for low usage of these services and the biggest de-
motivational factor for people to use these services is the fear of false
recommendation and reviews. The study revealed that there is a perception
among the people that these online platforms are meant for the advertisement of
the doctors.
The major customer preferences for using the online healthcare services came
out to be; Online appointment booking, searching a nearby service/doctor,
storing health records and speedy resolution of queries. So, the overall study
indicates that there is a lot of scope in the Online Healthcare Industry if these
services are provided as per the customer preferences and customer satisfaction.
T
EXECUTIVE SUMMARY
v
Title Page No.
Team Details ii
Acknowledgement iii
Executive Summary iv
INTRODUCTION 1
LITERATURE REVIEW 2-3
RESEARCH PROCESS
I. RESEARCH OBJECTIVE 4
II. RESEARCH METHOD 5-8
FINDINGS
I. RESULTS 9-13
II. ANALYSIS OF RESULTS 14-20
CONCLUSION 21
TABLE OF CONTENTS
1
ealthcare is one of the most important industry in India. It has become one of the
largest sector, both in terms of revenue as well as employment. According to IEBF,
the Indian healthcare market is worth US $100 billion and is expected to grow to US $280
billion by the year 2020. With the emergence of the Digital technology as well as the
government initiatives such as Digital India, the Healthcare industry is paving its way
towards digitization.
The main purpose of digitization of Healthcare Industry is to provide one stop solution
for all the customers as well as to reach to the remote areas within India where a huge
potential for this industry could be exploited. Some of the services which are being
provided by some of the players in this Industry are; online appointment booking,
searching a nearby doctor, online storage of health records, price comparison for nearby
services, health related queries, prediction of check-up need with proper analytics
report, online payment gateway, video chat with industry specialist, etc.
In India, many of the companies have entered the digital healthcare segment and also
many new start-ups are coming up with innovating solutions in this segment. Some of
the popular companies offering online healthcare services are; Lybrate, Practo, Doc
Engage, Healthiply, Liv Health, Praxify, etc.
H
INTRODUCTION
2
here are three levels of health delivery systems in India which are categorized as
Primary level, Secondary level and Tertiary level. All these level are having either
Public system or Private system.
We have categorized the Primary level, Secondary Level and Tertiary level as below.
Level Public Systems Private Systems Primary Level Public health centres and
its sub-centres come under this section.
Private doctors or practitioners come under this section.
Secondary Level Public Hospitals in various districts are the part of this level.
Private nursing homes and hospitals being operated by private bodies.
Tertiary Level Government Medical colleges and Institutions.
Corporate hospitals and Private medical colleges.
Government of India have taken many initiatives in recent years for digitalization of
healthcare sector and going with the programs like e-Health etc. Many companies like
TCS, Wipro etc. are providing support to government in establishing these projects in
country.
Electronic Medical record Hospital automation and telemedicine is coming into picture
and making an impact in healthcare industry of India. Apart from these many private
players are also coming with Digital health care solutions for the society. Center for
Development of Advanced Computing (CDAC) is working for the automation in large
hospitals this will also bring a change in perception of people about digital health care
services being provided by some private players in our country.
T
LITERATURE REVIEW
3
In electronic medical record system database of medical history of any individual will be
kept safe and secure for generations which will help individuals as well as government
for analysing and monitory status of health in the country. Private players will also be
benefitted by it as they will also get some edge for them in this system. People will get
idea about these kinds of services by government campaign and these private players
can provide some high quality services and turn those customers into their direction.
Many hospitals have also implemented these kinds of technologies into their
departments. Hospital SGPGIMS, Lucknow have implemented Tele-health care and
Distant Education in Medicine and Tele-mentoring into their system. Amrita Institute of
Medical Sciences, Kochi has 36 telemedicine centres all over India.
All these kinds of initiatives in health care sector in country will give a boom to Digital
health care services in India; all these kinds of initiatives give a right indication about the
bright future of Online Health care consulting market in India.
Department of Information technology is going with R & D projects. Center for
Development of Advance Computing is working on a telemedicine software and Media
lab Asia Initiatives is working in collaboration with many hospitals.
4
Research Objective
“Perception of Digitalization in Healthcare Industry”
Objective:-The objective of this marketing research is to assess the perception of
people towards digitalization of healthcare industry and to predict its future.
There are many online health care services in market these days so we need to analyse
the market that how much penetration is in the market by these kinds of services on the
basis of the data we have to predict about the future of these services whether these
services will work in future or they need to have some modifications.
What is the perception of customers those who have availed these services and
the features liked or disliked by these users?
What is perception of the customer who never availed but they are aware about
these kinds of services and if they would use these services than what should be
their expectations from these kinds of services?
What are the demographics of user using or want to use these services in the
future?
Which kind of feature people would like to have in these kind of online healthcare
services?
RESEARCH PROCESS
5
Research Method
Research Approach
Our main goal was to target a specific number of people within the boundaries of
country; we targeted Indian citizens with specific number of relevant questions related
to our study. We selected questions on the basis of study to be carried out so that we get
the right findings from the data. We believed that questions are specific to our study and
can bring out real perception of individuals towards the services.
To speed up the process of collecting data we employed an online survey which very
much common these days. Google forms are used for surveys which are reliable and free
source for collecting data.
To speed up the process for collection of data we used the social networks, emails etc. to
deliver the survey form. Research team analysed data using various tools and methods
for accurate results.
Data Collection
We have taken the help of Google forms to collect the data. This platform was used as it
is speedy, accurate and has no cost involved to collect data. Data is collected in excel
format in this platform which gives the advantage while make analysis of data.
We divided the geographies and circulated the form to those which have potential and
future customers for our study.
Data collection is the most tedious task in any marketing research project; it takes long
time for the collection of data. Since most of the people are not willing to give responses
and many gives the wrong responses, so it’s very important that survey form should be
sent to right kind of people.
6
Questionnaire
We designed the questionnaire which contains two parts to get the data from the
desired individuals. First part contained the questions related to demography and about
the awareness of digital healthcare services.
If person is not aware about these services than further questions were not asked from
that person.
Scales used in questionnaire was the LIKERT, nominal scales.
Q-1:- Are you aware of online Health care consulting services?
O Yes O No
Q-2:- Have you ever availed any health Care service online?
O Yes O No
Q-3:- Will you use it in future?
O Yes O No
Q-4:- How was your experience of accessing the online service?
1 Highly Satisfactory
2 Satisfactory
3 Neutral
4 Dissatisfactory
5 Highly Dissatisfactory
Q-5:- Which online platform do you prefer the most? (Choose only one)
Lybrate
Practo
Doc Engage
Healthiply
Liv Health
Plaxify
Other _______________________________
7
Q-6:- Was there any difference between the service which you availed online and that of
offline?
Yes
No
Can’t Say
Q-7:- Rate on a scale of importance, the availability of following services from an online
healthcare service platform? (Scale of 1 to 5)
Searching a nearby service
Storing your Health Records
Avail discount and monetary benefits
General suggestion on common diseases
Comparison of prices of available health services nearby
Speedy resolution of queries
Ratings or feedback of services
Regular notification or reminders of booking, important information, etc.
Calculation of expenditure relating to a particular health condition.
Prediction of checkup need with proper analytics report.
Online payment gateway
Video chats with industry specialists
Networking with people having same issues or interests
Healthcare related jobs
Q-8:- How important to you are the following aspects in deciding which online healthcare
service platform to use? (Scale of 1 to 5)
o End User interface
o Number of Doctors listed
o Most Economical
o Provision of other complimentary services like Health Insurance, Tele-Medicine etc.
8
Q-9:- Rate on the degree of likeliness, how each of the factors may de-motivate users to
use online healthcare service platform? (Scale of 1 to 5)
Perception of Inflated Rates
Perceived biasness for some Doctors, Products etc.
False Recommendations and Reviews
Less Information Available Online
Fear of other hidden charges
Non Readiness of users to use such platform
Q.10:- How do you think can online healthcare service platform can penetrate into rural
or semi urban parts of India? (Scale of 1 to 5)
Integrating with Government Healthcare benefits
Setting periodical Health checkup camps
Offering provision of transportation like Ambulances, PVT Transport etc.
Dedicated personal assistance to rural users throughout the transaction.
Offering economical services like non specialist doctors, Registered Medical
Practitioners etc.
Collaborating with NGO’s and volunteer groups
Providing insurance covers
Scale Defined- 1= Not at all important
2= Slightly Important
3= Important
4= Fairly Important
5= Very Important
Analysis Overview
To accomplish we used factor analysis and correlation we want to analyse which all
factors are affecting consumer in same way. We also want to observe how factors are
affecting them to use services in future.
9
RESULTS
The survey results are shown below.
We got total responses 173 responses.
Fig-1 Awareness of people about the healthcare services
FINDINGS
10
Out of 173 respondents only 73 were aware about these online healthcare services,
further data is about the people who were aware.
Fig-3 Respondents who availed online health care services.
Fig-4 Willingness to use services in future
Fig-5 Experience of accessing the online service
11
Fig-7 Preferred online services
Fig-8 Difference between the service availed online and that of offline
12
Fig-9 Preferences for availability of services from an online healthcare service platform
13
Fig-10 Aspects in deciding which online healthcare service platform to use
Fig-11 Factors that may de-motivate to use online healthcare service platform
14
ANALYSIS OF RESULTS
For purpose of analysis we used factor analysis and correlation between variables.
Important findings of same are tabulated below.
Correlation matrix
Above are findings of correlation among the different variables that are used to determine the
perception of consumers about online healthcare services.
After finding correlation we found KMO and Cronbach’s Alpha as below.
Eigen values for factors and respective variability and cumulative %.
Correlation matrix (Pearson (n)):
Variables
Online
Appoint
ment
Nearby
Service
Storing
Health
Records
Discou
nt
General
Suggesti
ons
Price
Comparis
on
Speedy
Resolutio
n
Feed
back
Reminde
rs
Expendit
ure
Calculati
on
Predictio
n of
Checkup
Online
Payment
Gateway
Video
Chats
Networki
ng with
Patients
Healthcare
Jobs
Online Appointment 1 0.555 0.386 0.249 0.247 0.288 0.363 0.372 0.292 0.327 0.224 0.332 0.165 0.139 0.122
Nearby Service 0.555 1 0.551 0.397 0.568 0.575 0.560 0.520 0.284 0.451 0.410 0.471 0.309 0.275 0.255
Storing Health Records 0.386 0.551 1 0.453 0.605 0.589 0.637 0.623 0.540 0.534 0.662 0.318 0.324 0.338 0.209
Discount 0.249 0.397 0.453 1 0.403 0.613 0.404 0.409 0.575 0.525 0.532 0.394 0.368 0.396 0.383
General Suggestions 0.247 0.568 0.605 0.403 1 0.634 0.630 0.509 0.407 0.566 0.572 0.400 0.514 0.435 0.273
Price Comparison 0.288 0.575 0.589 0.613 0.634 1 0.594 0.570 0.595 0.578 0.592 0.499 0.631 0.492 0.327
Speedy Resolution 0.363 0.560 0.637 0.404 0.630 0.594 1 0.543 0.506 0.524 0.594 0.518 0.500 0.287 0.250
Feedback 0.372 0.520 0.623 0.409 0.509 0.570 0.543 1 0.529 0.594 0.568 0.477 0.542 0.457 0.372
Reminders 0.292 0.284 0.540 0.575 0.407 0.595 0.506 0.529 1 0.658 0.579 0.412 0.561 0.516 0.493
Expenditure Calculation 0.327 0.451 0.534 0.525 0.566 0.578 0.524 0.594 0.658 1 0.800 0.685 0.504 0.429 0.429
Prediction of Checkup 0.224 0.410 0.662 0.532 0.572 0.592 0.594 0.568 0.579 0.800 1 0.579 0.500 0.323 0.376
Online Payment Gateway 0.332 0.471 0.318 0.394 0.400 0.499 0.518 0.477 0.412 0.685 0.579 1 0.534 0.312 0.345
Video Chats 0.165 0.309 0.324 0.368 0.514 0.631 0.500 0.542 0.561 0.504 0.500 0.534 1 0.586 0.454
Networking with Patients 0.139 0.275 0.338 0.396 0.435 0.492 0.287 0.457 0.516 0.429 0.323 0.312 0.586 1 0.626
Healthcare Jobs 0.122 0.255 0.209 0.383 0.273 0.327 0.250 0.372 0.493 0.429 0.376 0.345 0.454 0.626 1
Eigenvalues:
F1 F2 F3 F4 F5 F6 F7 F8 F9
Eigenvalue 7.191 1.092 0.621 0.384 0.308 0.187 0.158 0.029 0.004
Variability (%) 47.941 7.277 4.143 2.561 2.055 1.245 1.051 0.193 0.027
Cumulative % 47.941 55.219 59.361 61.922 63.977 65.222 66.273 66.466 66.493
KMO 0.867
Cronbach's alpha: 0.927
15
With the help of tables containing Eigen values we developed scree plot for the factors
Fig-Scree plot for the factors and respective Eigen values
Technique we used for rotation of factors is Varimax rotation results of which are
tabulated below
Factor pattern after Varimax rotation:
D1 D2 D3
Online Appointment 0.134 0.056 0.537
Nearby Service 0.158 0.149 0.856
Storing Health Records 0.486 0.157 0.580
Discount 0.437 0.365 0.295
General Suggestions 0.403 0.300 0.533
Price Comparison 0.451 0.433 0.509
Speedy Resolution 0.479 0.191 0.578
Feedback 0.424 0.374 0.487
Reminders 0.540 0.512 0.217
Expenditure Calculation 0.741 0.340 0.296
Prediction of Checkup 0.860 0.204 0.271
Online Payment Gateway 0.497 0.282 0.337
Video Chats 0.383 0.597 0.235
Networking with Patients 0.111 0.863 0.164
Healthcare Jobs 0.226 0.648 0.065
Values in bold correspond for each variable to the factor for which the squared cosine is the largest
16
Online Appointment
Nearby Service Storing Health Records
Discount
General Suggestions
Price Comparison
Speedy Resolution
Feedback
Reminders
Expenditure Calculation
Prediction of Checkup
Online Payment Gateway
Video Chats
Networking with Patients
Healthcare Jobs
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
-0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
D2
(1
7.7
1 %
)
D1 (21.88 %)
Factor loadings (axes D1 and D2: 39.59 %) after Varimax rotation
17
Values in bold correspond for each observation to the
factor for which the squared cosine is the largest.
41 0.250 0.071 1.177
42 -1.895 -0.768 1.644
43 0.476 0.032 0.610
44 0.015 1.408 1.015
45 0.776 -1.538 1.117
46 1.387 1.544 -1.091
47 1.296 -0.352 0.067
48 1.353 -1.673 0.196
49 -1.096 -0.518 -0.558
50 -0.617 -0.507 0.610
51 0.620 0.082 0.103
52 0.573 -0.284 0.464
53 0.402 0.216 -0.268
54 -0.597 -0.026 0.034
55 0.874 -0.095 -1.614
56 -0.487 0.689 -0.258
57 -0.348 0.347 0.910
58 -1.817 0.109 0.896
59 -0.584 0.908 1.125
60 0.164 1.116 0.693
61 0.429 -0.081 0.391
62 0.815 -1.372 0.168
63 1.330 -0.425 0.067
64 -0.599 1.020 0.172
65 0.483 0.828 0.345
66 -1.096 0.286 0.348
67 0.312 -0.141 -0.107
68 1.904 -1.849 0.150
69 -0.473 1.394 0.059
70 0.774 -0.848 0.631
71 -0.528 -0.029 -1.296
72 -0.096 1.204 0.722
73 -0.506 -0.783 -0.197
Factor scores after Varimax rotation:
D1 D2 D3
1 0.075 -0.343 0.719
2 0.647 0.906 -0.818
3 -0.745 -1.363 -0.526
4 0.013 -0.163 -0.339
5 0.449 0.025 -0.656
6 -0.451 -0.171 1.109
7 -1.260 -0.732 0.914
8 0.296 0.716 -0.146
9 1.515 -1.334 0.341
10 -1.224 0.263 1.269
11 0.892 1.011 0.732
12 0.726 -0.796 0.718
13 -0.943 -0.154 -1.596
14 -0.354 0.042 -0.931
15 0.406 0.808 0.922
16 -1.119 0.400 -1.694
17 1.159 0.509 0.690
18 0.945 1.390 0.640
19 -0.578 0.859 -1.056
20 -0.350 0.346 0.526
21 1.035 -2.145 -1.044
22 1.385 0.780 -0.158
23 -0.234 -0.535 -1.842
24 -1.466 -1.098 -2.264
25 0.875 1.523 0.422
26 -1.517 -0.062 -1.029
27 -0.019 -1.279 1.501
28 -1.309 -1.023 -0.657
29 -0.736 -0.198 1.353
30 1.484 1.506 -0.964
31 0.553 -0.914 -0.173
32 0.497 0.384 -0.742
33 -1.652 -1.307 -2.501
34 -0.859 1.098 -0.669
35 -0.780 0.653 0.048
36 -1.226 -0.760 0.441
37 -0.354 0.042 -0.931
38 0.340 0.820 -0.348
39 1.184 1.356 -0.142
40 -0.798 -1.020 0.552
18
Findings from factor analysis
From all the different variables, for the desirability of a specific feature in an online healthcare
service the users could be classified into three major factors.
Factor 1- Money wise
o Desirability for- Discount Timely reminders Expenditure calculations (budgeted) Check-up with proper analysis report Online payment gateway.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16 17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49 50
51
52
53
54 55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
-2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
-3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 3
D2
(1
7.7
1 %
)
D1 (21.88 %)
Observations (axes D1 and D2: 39.59 %) after Varimax rotation
19
Factor 2- The socialist
o Desirability for- Video chat Option for networking with patients. Seeking healthcare jobs
Factor 3- The convenience seekers
o Desirability for- Online appointment Nearby service Health records on the cloud General suggestions Price comparisons Speedy resolution feedback
Findings from P-Value based test
Before this study we assumed that people who had used this service will surely use in future, to test this assumption we conducted a P-value based test with the same assumptions.
Test Summary
Summary statistics:
Variable Observations Obs. with missing data Obs. without missing data Minimum Maximum Mean Std. deviation
Used or Not? 72 0 72 0.000 1.000 0.361 0.484
Will Use it or Not? 72 0 72 0.000 1.000 0.917 0.278
Correlation matrix (Pearson):
Variables Used or Not? Will Use it or Not?
Used or Not? 1 0.122
Will Use it or Not? 0.122 1
Values in bold are different from 0 with a significance level alpha=0.1
20
P-Values for the test
As P-Value is greater than our significance level (0.307>0.1) we reject our hypothesis hence we can’t say that people who had used this service will surely use in future.
By factor analysis and P-test we had findings about the online healthcare services that will be giving us great edge in concluding about the research.
p-values:
Variables Used or Not? Will Use it or Not?
Used or Not? 0 0.307
Will Use it or Not? 0.307 0
Values in bold are different from 0 with a significance level alpha=0.1
21
rom all the users the most sought after service from an online health care
service platform was found to be locating a nearby doctor, so the companies
in this field shall focus on providing these kinds of nearby doctor locating
services to capture the more market share.
In deciding amongst which online health care platform service to be used,
according to our research most people tend to go for the most economical
service.
As findings also suggest that there is huge lack of awareness regarding these kinds
of services in market, so companies are recommended to make people aware
about these online services by better campaigns.
There is good market share for these services in future if they are channelized and
implemented in more customer friendly manner.
For setting up online health care services in rural or semi urban part of India we will the
companies for setting periodical health check-up and providing transportation facilities
like ambulances.
F
CONCLUSION