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CHAPTER – IV

ANALYSIS AND

INTERPRETATION

87

CHAPTER - IV

ANALYSIS AND INTERPRETATION

4.1 Introduction

This chapter provides data analysis and interpretation. It provides the socio

economic back ground of selected patients came from foreign countries to Chennai

for medical tourism. Consideration of Chennai as medical tourism hub was

enumerated by descriptive analysis and the influence of demographics on factors that

made to select Chennai for medical tourism is also established. Factors of satisfaction

towards care facilities provided by the hospitals to the medical tourists are identified

and the interrelationships between the factors are also measured.

Further the influence of patients demographics over the factors of satisfaction

towards care facilities were assessed in detail. Variation between expectation and

satisfaction level among the patients were also assessed. Problems faced by the

patients are also discussed by cross tabulation. Predicator variables of satisfaction

towards services provided by the hospitals in Chennai to medical tourists were also

identified.

The last section is dealt with the proposed model for satisfaction towards

services provided by the hospitals in Chennai to medical tourists. The information

about the background of 303 patients came abroad for medical tourism to Chennai is

explored. Well structured questionnaire is prepared to collect the relevant responses.

This chapter explores as follows:

Section 4.1 : Profile of the medical tourist

Section 4.2 : Information pertaining to medical tourism

Section 4.3 : Descriptive analysis for considering Chennai for medical tourism

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Section 4.4 : Influence of patients demographics on factors that made to select

Chennai for medical tourism

Section 4.5 : Factors of satisfaction towards care facilities provided by the

hospitals in Chennai

Section 4.6 : Relationships between factors of satisfaction towards the services

provided by the hospitals in Chennai to medical tourists

Section 4.7 : Influence of patients demographics on factors of satisfaction

towards care facilities provided by the hospitals in Chennai

Section 4.8 : Assessing the variation between expectation and satisfaction level

among the patients came as medical tourists to Chennai

Section 4.9 : Assessing the association between patients demographics and

problems

Section 4.10 : Predictor variables of satisfaction towards services provided by the

hospitals in Chennai to medical tourists

Section 4.11 : Model for satisfaction towards services provided by the hospitals in

Chennai to medical tourists

4.2 Profile of the medical tourists

Medical tourists traveled from foreign countries to India for medical tourism

were selected for the Study. Patients are classified according to their gender, age,

marital status, educational qualification, employment status and annual income. Table

4.1 shows the details of socioeconomic background of the selected medical tourists

traveled from foreign countries to India for medical tourism.

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Table 4.1

Profile of the patients

Particulars Classification Number of patients Percentage

Gender Male 189 62.40

Female 114 37.60

Age

18 - 30 years 91 30.00

31 - 40 years 92 30.40

More than 40 years 120 39.60

Marital Status Married 188 62.00

Single 115 38.00

Educational Qualification

School level 42 13.90

Graduates 129 42.60

Post graduates 87 28.70

Professionals 45 14.90

Employment status

Employed with temporary contract 92 30.40

Firms Employees 64 21.10

Business Owners 78 25.70

Professionals 69 22.80

Annual income

Below 10,000$ 79 26.10

10,001 - 30,000$ 133 43.90

30,001 - 60,000$ 51 16.80

Above 60,000$ 40 13.20 Source: Primary data

Patients travelled from foreign countries to India for medical tourism was

selected for the Study. Out of 303 patients, 62.40 % of the patients are males and the

remaining 37.60 % of the patients are females. It is observed that most of the patients

(62.40%) travelled from foreign countries to India for medical tourism is males.

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Out of 303 patients, 39.60 % of the patients are in the age group of more than

40 years, 30.40% of the patients are having age between 31– 40 years and 30.00 % of

the patients are in the age group of 18 – 30 years. It is observed that majority of the

patients (39.60%) travelled from foreign countries to India for medical tourism are in

the age group of more than 40 years.

Out of 303 patients, 62.00% of the patients were married and the remaining

38.00% of the patients are living as single. It is observed that most of the selected

patients (62.00%) travelled from foreign countries to India for medical tourism was

married.

Out of 303 patients, 42.60% of the patients are possessing graduation as their

educational qualification, 28.70% of the patients possess post graduation as their

educational qualification, 14.90% of the patients are professionals and 13.90% of the

selected patients are having school level education. It is observed that majority of the

patients (42.60%) travelled from foreign countries to India for medical tourism are

possessing graduation as their educational qualification.

Out of 303 patients, 30.40 % of the selected patients are employed with

temporary contract, 25.70% of the patients are running their own business, 22.80% of

the selected patients are professionals and 21.10 % of the selected patients are

working as firms employees. It is observed that most of the patients (30.40%)

travelled from foreign countries to India for medical tourism is employed with

temporary contract.

Out of 303 patients, 43.90% of the selected patients were earning annual

income of 10,001 - 30,000$, 26.10% of the patients are earning annual income below

10,000$, 16.80% of the selected patients are earning 30,001 - 60,000$ and 13.20% of

the selected patients are earning above 60,000$ as their annual income. It is observed

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that majority of the patients (43.90%) travelled from foreign countries to India for

medical tourism are earning 10,001 to 30,000$ as their annual income.

4.3 Information pertaining to medical tourism

4.3.1 Reasons for interest in traveling abroad for medical treatments

Patients travelled from foreign countries to Chennai for medical tourism was

selected for the Study. Patients have expressed their interest behind the medical

tourism. The reasons for the interest behind the traveling abroad for medical

treatments are displayed in the table 4.2

Table 4.2

Reasons for interest in traveling abroad for medical treatments

Particulars Number of patients Percentage

To cure an illness 92 30.40

To improve health 49 16.20

For cosmetic surgery 74 24.40

To have a medical check up 88 29.00

Total 303 100 Source: primary data

It is understood from the table 4.2 that 30.40 per cent of the patients were

travelled abroad to cure the illness, 29.00 per cent of the patients were travelled for

medical check-up, 24.40 per cent of the patients were travelled for cosmetic surgery

and 16.20 per cent of the patients were travelled to improve health. It is observed that

most of the patients (30.40%) travelled abroad for medical tourism to Chennai for

curing illness.

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4.3.2 Treatment available in your country of residence

Patients travelled from foreign countries to Chennai for medical treatments

were selected for the Study. Patients have expressed their opinion regarding the

treatment available in their country of residence for which they have travelled abroad

and the same is displayed in the table 4.3

Table 4.3

Treatment available in your country of residence


Yes 205 67.70

No 98 32.30


It is observed from the table 4.3 that 67.70 per cent of the patients expressed

that the treatments for which they have travelled abroad are available in their country

of residence and 32.30 per cent of the patients expressed that the treatment for which

they have travelled abroad are not available in their country of residence. It is

observed that majority of the patients (67.70%) travelled abroad for medical

treatments expressed that the treatments are available in their country of residence.

4.3.3 Treatment covered by current health plan

Patients travelled from foreign countries to Chennai for medical treatments

were selected for the Study. Patients have expressed their views regarding the

coverage of treatment in their current health plan and the same is explored in the

table 4.4

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Table 4.4

Treatment covered by current health plan


Fully covered 11 3.60

Partially covered 43 14.20

Not covered 249 82.20


From the table 4.4 it is observed that, 82.20 per cent of the patient expressed

that the present treatment are not covered in their current health plan, 14.20 per cent

of the patient expressed that the present treatment is partially covered by the current

health plan and 3.60 per cent of the patients expressed that the present treatment is

covered by the current health plan. It is observed that most of the patients (82.20%)

have expressed that their treatment are not covered with their current health plan.

4.3.4 Information about the hospital and its services and charges

Patients travelled abroad for medical treatments were selected for the Study.

Patients have expressed their views regarding the sources of information they got

about the hospitals in Chennai. The sources of information about the hospitals in

Chennai are displayed in the table 4.5.

Table 4.5

Information about the hospital and its services, and charges


Advertisement 76 25.10 Private practioners 48 15.80 Health camp 64 21.10 Internet 115 38.00 Total 303 100

Source: primary data

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Table 4.5 depicts the source of information they got about the hospitals in

Chennai for medical tourism. 38.00 per cent of the patients expressed that they got the

information about the hospital and its services and the charges through internet, 25.10

per cent of the patients got the information regarding the hospital through

advertisements, 21.10 per cent of the patients got the information through health

camps and 15.80 per cent of the patients have got information through private

practioners. It is observed that majority of the patients (38.00%) have got the

information about the hospitals, services and charges through Internet.

4.3.5 Treatment undergone earlier in Chennai

Patients travelled abroad for medical treatments to Chennai were selected for

the Study. Patients have given the information regarding they have undergone

treatment earlier in Chennai. Table 4.6 displays the information regarding earlier

treatment undergone in Chennai.

Table 4.6

Treatment undergone earlier in Chennai


Yes 245 80.90

No 58 19.10


It is understood from the table 4.6 that 80.90 per cent of the patient expressed

that they have undergone treatments in Chennai already and 19.10 per cent of the

patient expressed that they have not undergone any treatment earlier in Chennai. It is

observed that majority of the patients (80.90%) have already undergone treatments in

Chennai.

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4.3.6 Recommend the hospital to the friends

Patients travelled abroad for medical treatments to Chennai were selected for

the Study. Patients have expressed their opinion towards the recommendation to their

friends regarding the hospitals where they undergone treatment and the same are

explored in the table 4.7

Table 4.7

Recommend the hospital to the friends


Yes 216 71.30

No 87 28.70


From the table 4.7 it is observed that 71.30 per cent of the patients expressed

that they will recommend the hospitals in Chennai where they undergone treatment to

their friends and 28.70 per cent of the patient expressed that they won’t refer the

hospitals where they undergone treatment to any of their friends. It is observed that

majority of the patients (71.30%) are willing to refer and recommend the hospitals in

Chennai where they undergone treatment to their friends.

4.3.7 Important factors of Health consciousness of the patients traveling

abroad for medical treatment

Health conscious is very important for every human being. Selected patients

travelled from foreign countries to Chennai for medical tourism has expressed their

views regarding various factors of Health consciousness.

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Testing the significance of various factors of Health consciousness of patients

came for medical tourism to Chennai, Friedmans test for k related samples was

applied to Study the relationship between various factors of health consciousness.

Null hypothesis H0 1(a): All the factors of health consciousness plays equal

role among the patients came to hospitals in Chennai for medical tourism.

Table 4.8

Factors of health consciousness

Particulars Mean Rank Chi square value

Healthier behavior leads to good health 7.45

401.289** (p<.001)

Imperfect health happened by chance 6.58

Regular checkups, less health problems 6.43

Good or bad health, own responsibility 5.39

Doctors advice to keep healthy 4.88

Health condition is a result of the choices 4.76

Full control of how health can be improved 4.97

Destined to health problems 4.72

Health condition is of unhealthy behavior 4.73

Regarding health, do what doctors tell 5.10 ** Significant at 1% level

The results in the table 4.8 show that the null hypothesis H0 1(a) is rejected at

1% level. All the factors of health consciousness do not play equal role among the

patients came to hospitals in Chennai for medical tourism. Further the mean ranks in

the table 4.8 shows clearly that “Healthier behavior leads to good health” and

“Imperfect health happened by chance” are the main factors of health consciousness

and “Destined to health problems” and “Health condition is of unhealthy behavior”

are the least factors of health consciousness among the patients came to Chennai for

medical tourism.

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4.3.8 Important factors of overseas preferences of the patients traveling abroad

for medical treatment

Selected patients travelled from foreign countries to Chennai for medical

tourism has expressed their views regarding various factors of overseas preferences.

Testing the significance of various factors of overseas preferences of the

patients came for medical tourism to Chennai; Friedmans test for k related samples

was applied to Study the relationship between various factors of overseas preferences.

Null hypothesis H01 (b): All the factors of overseas preferences plays equal

role among the patients came to hospitals in Chennai for medical tourism.

Table 4.9

Factors of Overseas preferences


Treatments cost is very high 4.2

54.934** (p<.001)

Health care plan does not cover treatments 3.68

Spend a fortune to receive treatments 4.12

For illness, partially pay for treatments 4.11

Waiting time is too long 4.31

lot of paper work 3.48

Too many steps to receive the treatment 4.10 ** Significant at 1% level

The results in the table 4.9 show that the null hypothesis H0 1(b) is rejected at

1% level. All the factors of overseas preferences do not play equal role among the


the table 4.9 shows clearly that “Waiting time is too long” and “Treatments cost is

very high” are the main factors of overseas preferences and “lot of paper work” and

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“Health care plan does not cover treatments” are the least factors of overseas

preferences among the patients came to Chennai for medical tourism.

4.3.9 Level of familiarity of the patients traveling abroad for medical treatment


tourism has expressed their views regarding their level of familiarity on various

aspects.

Testing the significance of various aspects and their level of familiarity

among the patients came for medical tourism to Chennai; Friedmans test for k related

samples was applied to Study the relationship between various aspects and their

familiarity.

Null hypothesis H01(c): All the aspects of familiarity carry equal importance

among the patients came to hospitals in Chennai for medical tourism.

Table 4.10

Level of familiarity

Particulars Mean Rank Chi square value Procedures involved with treatment 4.58

210.942** (p<.001)

Chennai as a medical destination 3.91

Cost for the treatment 4.08

Doctors profile 3.76

Hospital reputation 4.62

Health insurance coverage 3.10

Travel indications 3.94 ** Significant at 1% level

The results in the table 4.10 show that the null hypothesis H0 1(c) is rejected

at 1% level. All the factors of health consciousness do not play equal role among the


the table 4.10 shows clearly that “Hospital reputation” and “Procedures involved with

99

treatment” are the main aspects of patients level of familiarity and “Health insurance

coverage” and “Doctors profile” are the least aspects of patients level of familiarity

among the patients came to Chennai for medical tourism.

4.3.10 Important factors of risk in making decisions about overseas travel for

medical treatment


tourism have expressed their views regarding various risks in making decisions about

overseas travel for medical treatment.

Testing the significance of various risks in making decisions about overseas

travel for medical treatment to Chennai, Friedmans test for k related samples was

applied to Study the relationship between various risks in making decisions about

overseas travel for medical treatment.

Null hypothesis H01 (d): All the risks in making decisions about overseas

travel for medical treatment plays equal role among the patients.

Table 4.11

Risk in making decisions about overseas travel for medical treatment

Particulars Mean Rank Chi square value Treatment does not turn out as expected 4.25

315.389** (p<.001)

Treatment cost does not provide savings 5.80

Destination choice affect others opinion 4.97

Traveling abroad will take much time 5.13

Health will get worse due to travel 4.56

Physical danger or injury due to accidents 3.88

Treatment leads unsatisfactory outcome 3.61

Treatments does not match myself image 3.80 ** Significant at 1% level

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The result in the table 4.11 shows that the null hypothesis H0 1(d) is rejected

at 1% level. All the risks in making decisions about overseas travel for medical

treatment do not play equal role among the patients.

Further the mean ranks in the table 4.11 shows clearly that “Treatment cost

does not provide savings” and “Traveling abroad will take much time” are the main

risks in making decision for overseas travel and “Treatment leads unsatisfactory

outcome” and “Treatments does not match myself image” are the least risks in

making decision for overseas travel for medical treatment among the patients.

4.3.11 Importance of information sources for deciding travel for medical

treatment


tourism has expressed their views regarding information sources for deciding travel

for medical treatment.

Testing the significance of various information sources for deciding travel for

medical treatment for medical tourism to Chennai, Friedman’s test for k related

samples was applied to Study the relationship between various information sources.

Null hypothesis H01 (e): All the information sources for deciding travel for

medical treatment plays equal role among the patients.

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Table 4.12

Information sources for deciding travel for medical treatment


Brochures from tourism authorities 6.70

351.725**

(p<.001)

Advertising campaigns 5.70

Health insurance policy providers 4.85

Information from non commercial websites 5.71

Reports about medical industries and tourism 6.94

Articles about medical industries and tourism 5.97

Personal doctors 4.56

Brochures from medical care providers 5.94

Personal selling by staff of travel agencies 4.30

Friends and Family 4.35 ** Significant at 1% level

The result in the table 4.12 shows that the null hypothesis H0 1(e) is rejected

at 1% level. All the factors of health consciousness do not play equal role among the

patients came to hospitals in Chennai for medical tourism.

Further the mean ranks in the table 4.12 shows clearly that “Reports about

medical industries and tourism” and “Brochures from tourism authorities” are the

main information sources for deciding travel for medical treatment and “Personal

selling by staff of travel agencies” and “Friends and Family” are the least information

sources for deciding travel for medical treatment.

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4.4 Descriptive analysis for considering Chennai for Medical Tourism


tourism have expressed their views regarding hospital image in making decisions

about overseas travel for medical treatment and the same are explored in the table

4.13.

Table 4.13

Hospitals image

S. No Statements Mean SD

1 International standard hospitals 4.16 0.850

2 Hospitals affiliated with medical institutions 3.82 0.983

3 Accredited by JCIO 3.94 0.910

4 Multi specialty Hospitals 3.82 1.004

5 Accredited by NABH 3.92 0.706

6 Guarantee the treatment and abide by laws 3.66 0.698 Source: primary data

Table 4.13 displays the mean responses given by the patients towards Hospital

image. The mean response for “International standard hospitals” is 4.16. The mean

response given by the patients for “Hospitals affiliated with medical institutions” is

3.82. The mean response given by the patients for “Accredited by JCIO” is 3.94. The

mean response given by the patients for “Multi specialty Hospitals” is 3.82. The mean

response given by the patients for “Accredited by NABH” is 3.92. The mean response

given by the patients for “Guarantee the treatment and abide by laws” is 3.66. Since

all the mean responses of the patients are above the average level, it is observed that

patients are considering all the aspects of Hospital image.


tourism have expressed their views regarding cost in making decisions about overseas

travel for medical treatment and the same are explored in the table 4.14.

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Table 4.14

Cost


1 Accessed from my home country at low cost 3.77 0.740

2 Treatment at a lower cost compared to other destinations 3.64 0.803

3 Health care providers which are compatible 3.84 0.711

4 Accommodation costs low 3.56 0.829

5 Transportation cost low 3.69 0.637 Source: primary data

Table 4.14 displays the mean responses given by the patients towards Cost.

The mean response given by the patients for “Accessed from my home country at low

cost” is 3.77. The mean response given by the patients for “Treatment at a lower cost

compared to other destinations” is 3.64. The mean response given by the patients for

“Health care providers which are compatible” is 3.84. The mean response given by

the patients for “Accommodation costs low” is 3.56. The mean response given by the

patients for “Transportation cost low” is 3.69. Since all the mean responses of the

patients are above the average level, it is observed that patients are considering all the

aspects of Cost.


tourism have expressed their views regarding safety and security in making decisions

about overseas travel for medical treatment and the same are explored in the

table 4.15.

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Table 4.15

Safety and security


1 Good security systems in buildings 3.72 0.763

2 Not target for terrorists attacks 3.69 0.753

3 Professionals are fluent in languages 3.52 0.902

4 Politically stable 3.49 0.788

5 Low crime rates 3.60 0.893 Source: primary data

Table 4.15 displays the mean responses given by the patients towards Safety

and security. The mean response given by the patients for “Good security systems in

buildings” is 3.72. The mean response given by the patients for “Not target for

terrorists attacks” is 3.69. The mean response given by the patients for “Professionals

are fluent in languages" is 3.52. The mean response given by the patients for

“Politically stable” is 3.49. The mean response given by the patients for “Low crime

rates” is 3.60. Since all the mean responses of the patients are above the average level,

it is observed that patients are considering all the aspects of Safety and security.


tourism have expressed their views regarding Hygiene in making decisions about

overseas travel for medical treatment and the same are explored in the table 4.16.

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Table 4.16

Hygiene


1 Low incidence of natural disasters 4.10 0.626

2 General environment hazards 3.92 0.659

3 Environment hazards 3.96 0.710

4 No epidemic diseases 3.71 0.714

5 Indoor and outdoor air pollution 3.63 0.752 Source: primary data

Table 4.16 displays the mean responses given by the patients towards

Hygiene. The mean response given by the patients for “Low incidence of natural

disasters” is 4.10. The mean response given by the patients for “General environment

hazards” is 3.92. The mean response given by the patients for “Environment hazards”

is 3.96. The mean response given by the patients for “No epidemic diseases” is 3.71.

The mean response given by the patients for “Indoor and outdoor air pollution” is

3.63. Since all the mean responses of the patients are above the average level, it is

observed that patients are considering all the aspects of Hygiene.


tourism has expressed their views regarding tourism in making decisions about


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Table 4.17

Tourism


1 Beautiful beaches 3.49 0.718

2 Authentic historical sites 4.36 0.624

3 Museums 4.01 0.772

4 Temples 4.06 0.750

5 Hill stations 3.72 0.665 Source: primary data


Tourism. The mean response given by the patients for “Beautiful beaches” is 3.49.

The mean response given by the patients for “Authentic historical sites” is 4.36. The

mean response given by the patients for “Museums” is 4.01. The mean response given

by the patients for “Temples” is 4.06. The mean response given by the patients for

“Hill stations” is 3.72. Since all the mean responses of the patients are above the

average level, it is observed that patients are considering all the aspects of Tourism.


tourism have expressed their views regarding travel in making decisions about


Table 4.18

Travel


1 Safe to travel to by oneself 3.72 0.684

2 Direct flights from residence 3.70 0.702

3 Safe transportation system (buses, trains) 4.16 0.644

4 Convenient proximity 3.91 0.734

5 Safe travel modes (taxis, auto) 3.95 0.731 Source: primary data

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Table 4.18 displays the mean responses given by the patients towards Travel.

The mean response given by the patients for “Safe to travel to by oneself” is 3.72. The

mean response given by the patients for “Direct flights from residence” is 3.70. The

mean response given by the patients for “Safe transportation system (buses, trains)” is

4.16. The mean response given by the patients for “Convenient proximity” is 3.91.

The mean response given by the patients for “Safe travel modes (taxis, auto)” is 3.95.

Since all the mean responses of the patients are above the average level, it is observed

that patients are considering all the aspects of Travel.


tourism has expressed their views regarding entertainment in making decisions about


Table 4.19

Entertainment


1 Good bars 3.82 0.631

2 Good shopping facilities 3.63 0.760

3 Browsing centres 3.55 0.748

4 Nightclubs 3.59 0.757

5 Malls, theatres 3.54 0.708 Source: primary data


Entertainment. The mean response given by the patients for “Good bars” is 3.82. The

mean response given by the patients for “Good shopping facilities” is 3.63. The mean

response given by the patients for “Browsing centres” is 3.55. The mean response

given by the patients for “Nightclubs” is 3.59. The mean response given by the

patients for “Malls, theatres” is 3.54. Since all the mean responses of the patients are

above the average level, it is observed that patients are considering all the aspects of

Entertainment.

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4.5 Influence of patients demographics on factors that made to select Chennai

for Medical tourism

4.5.1 Influence of patients gender on factors that made to select Chennai for

Medical tourism

To test the significant influence of patients gender on factors that made to

select Chennai for Medical tourism (Hospital image, Cost, Safety and security,

Hygiene, Tourism, Travel and Entertainment), independent samples t-test was applied

to ascertain if there is any significant influence of patients gender on factors that made

to select Chennai for Medical tourism. The following null hypotheses were framed:

H0 2: There is no significant influence of patients gender on (a) Hospital

image (b) Cost (c) Safety and security d) Hygiene (e) Tourism (f) Travel (g)

Entertainment in Chennai for medical tourism.

Table 4.20 shows the results of t-test for influence of patients gender on

factors that made to select Chennai for Medical tourism.

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Table 4.20

t-test for influence of patients gender on factors to select

Chennai for Medical tourism

Factors Gender N Mean S D t-value

Hospital image Male 189 24.22 3.426 5.773**

(p<.001) Female 114 21.80 3.753

Cost Male 189 18.95 2.796 3.722**

(p<.001) Female 114 17.77 2.456

Safety and security Male 189 18.64 3.181 4.740**

(p<.001) Female 114 16.96 2.640

Hygiene Male 189 19.80 2.818 4.242**

(p<.001) Female 114 18.50 2.199

Tourism Male 189 20.20 2.461 5.070**

(p<.001) Female 114 18.68 2.645

Travel Male 189 19.91 2.534 4.092**

(p<.001) Female 114 18.69 2.464

Entertainment Male 189 18.53 2.125 4.100**

(p<.001) Female 114 17.45 2.254 ** Significant at 1% level

Hospital Image

The obtained t value is 5.773 and it is significant at 1% level. The value

indicates that there is significant influence of patients gender on Hospital image.

Further, the mean table 4.20 indicates that the male patients have scored

higher mean value of 24.22 than the female patients (21.80). This shows that the male

patients are keener than the female patients towards Hospital image for selecting

Chennai for medical tourism.

110

Therefore, the formulated hypothesis H0 2(a) that “there is no significant

influence of patients gender on hospital image” is rejected.

Cost


indicates that there is significant influence of patients gender on cost.



patients are more specific about the cost of the treatment for selecting Chennai for

medical tourism.

Therefore, the formulated hypothesis H0 2(b) that “there is no significant

influence of patients gender on Cost” is rejected.

Safety and security


indicates that there is significant influence of patients gender on safety and security.



patients are more specific than female patients towards Safety and Security in


Therefore, the formulated hypothesis H0 2(c) that “there is no significant

influence of patients gender on safety and security” is rejected.

Hygiene


indicates that there is significant influence of patients gender on hygiene.

111



patients are concentrating more towards Hygienic conditions of the hospitals in

Chennai than female patients for medical tourism.

Therefore, the formulated hypothesis H0 2(d) that “there is no significant

influence of patients gender on hygiene” is rejected.

Tourism


indicates that there is significant influence of patients gender on tourism.



patients are more concentrated on Tourism in Chennai than the females for selecting


Therefore, the formulated hypothesis H0 2(e) that “there is no significant

influence of patients gender on tourism” is rejected.

Travel


indicates that there is significant influence of patients gender on travel.



patients are more concentrating towards Traveling than female patients for selecting


Therefore, the formulated hypothesis H0 2(f) that “there is no significant

influence of patients gender on travel” is rejected.

112

Entertainment


indicates that there is significant influence of patients gender on entertainment.



patients are keener towards entertainment than the female patients for selecting


Therefore, the formulated hypothesis H0 2(g) that “there is no significant

influence of patients gender on entertainment” is rejected.

4.5.2 Influence of patients age on factors that made to select Chennai for

Medical tourism

To test the significant influence of patients age on factors that made to select

Chennai for Medical tourism (Hospital image, Cost, Safety and security, Hygiene,

Tourism, Travel and Entertainment), one way ANOVA was applied to ascertain if

there is any significant influence of patients age on factors that made to select

Chennai for Medical tourism.

The following null hypotheses were framed:

H0 3: There is no significant influence of patients age on (a) Hospital image

(b) Cost (c) Safety and security d) Hygiene (e) Tourism (f) Travel (g) Entertainment

in Chennai for medical tourism.

Table 4.21 shows the results of one way ANOVA for influence of patients age

on factors that made to select Chennai for Medical tourism.

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Table 4.21

One way ANOVA for influence of patients age on factors to select


Factors Age N Mean S D F value

Hospital image

18 - 30 years 91 21.62 3.985 15.119** (p<.000)

31 - 40 years 92 23.72 3.950

More than 40 years 120 24.27 2.866

Cost

18 - 30 years 91 18.91 3.677 1.250

(p=.085) 31- 40 years 92 19.07 2.681

More than 40 years 120 18.52 1.634

Safety and security

18 - 30 years 91 17.24 3.531 6.986** (p=.001)

31 - 40 years 92 17.78 2.819

More than 40 years 120 18.77 2.775

Hygiene

18 - 30 years 91 18.46 3.429 7.547** (p=.001)

31 - 40 years 92 19.45 2.195

More than 40 years 120 19.85 2.170

Tourism

18 - 30 years 91 18.96 3.167 5.633** (p=.004)

31 - 40 years 92 19.58 2.325

More than 40 years 120 20.17 2.288

Travel

18 - 30 years 91 19.07 2.785 1.578

(p=.208) 31 - 40 years 92 19.48 2.279

More than 40 years 120 19.70 2.603

Entertainment

18 - 30 years 91 18.10 2.316 0.075

(p=.928) 31 - 40 years 92 18.21 2.881

More than 40 years 120 18.10 1.488 ** Significant at 1% level

Hospital Image

The obtained F value is 15.119 and it is significant at 1% level. The value

indicates that there is significant influence of patients age on Hospital image.

114

Further, the mean table 4.21 indicates that the patients with age more than 40

years have scored higher mean value of 24.27 and the lowest mean was scored by the

patients with age 18 - 30 years (21.62). This shows that the patients with age more

than 40 years are concentrating more on Hospital image to select Chennai for medical

tourism and the patients with age 18 - 30 years are less concentrating on Hospital

image to select Chennai for medical tourism.


influence of patients age on hospital image” is rejected.

Cost

The obtained F value is 1.250 and it is not significant at 5% level. The value

indicates that there is no significant influence of patients age on cost.


influence of patients age on Cost” is accepted.

Safety and security


indicates that there is significant influence of patients age on safety and security.




than 40 years are more concentrating on Safety and Security to select Chennai for

medical tourism and the patients with age 18 - 30 years are less concentrating on

Safety and Security to select Chennai for medical tourism.


influence of patients age on safety and security” is rejected.

115

Hygiene


indicates that there is significant influence of patients age on hygiene.




than 40 years are keener towards Hygiene to select Chennai for medical tourism and

the patients with age 18 - 30 years are less keen towards Hygiene to select Chennai

for medical tourism.


influence of patients age on hygiene” is rejected.

Tourism


indicates that there is significant influence of patients age on tourism.




than 40 years are more concentrating on Tourism to select Chennai for medical

tourism and the patients with age 18 - 30 years are less concentrating on Tourism to

select Chennai for medical tourism.


influence of patients age on tourism” is rejected.

116

Travel

The obtained F value is 1.578 and it is not significant at 5 % level. The value

indicates that there is no significant influence of patients age on travel.


influence of patients age on travel” is accepted.

Entertainment


indicates that there is no significant influence of patients age on entertainment.


influence of patients age on entertainment” is accepted.

4.5.3 Influence of patients marital status on factors that made to select


To test the significant influence of patients marital status on factors that made

to select Chennai for Medical tourism (Hospital image, Cost, Safety and security,

Hygiene, Tourism, Travel and Entertainment), independent samples t-test was applied

to ascertain if there is any significant influence of patients marital status on factors

that made to select Chennai for Medical tourism.


H0 4: There is no significant influence of patients marital status on (a)

Hospital image (b) Cost (c) Safety and security d) Hygiene (e) Tourism (f) Travel (g)


Table 4.22 shows the results of t-test for influence of patients marital status on

factors that made to select Chennai for Medical tourism.

117

Table 4.22

t-test for influence of patients marital status on factors to select Chennai for

Medical tourism

Factors Marital status N Mean S D t-value

Hospital image Married 188 23.79 3.070 2.889**

(p=.004) Single 115 22.53 4.527

Cost Married 188 18.52 1.833 0.106

(p=.916) Single 115 18.48 3.772

Safety and security Married 188 18.30 2.805 2.136*

(p=.033) Single 115 17.53 3.475

Hygiene Married 188 19.51 2.133 1.617

(p=.107) Single 115 19.00 3.366

Tourism Married 188 19.78 2.243 1.229

(p=.195) Single 115 19.38 3.163

Travel Married 188 19.59 2.368 1.197

(p=.232) Single 115 19.22 2.871

Entertainment Married 188 18.01 1.867 1.311

(p=.191) Single 115 18.35 2.718

** Significant at 1% level * significant at 5% level

Hospital Image


indicates that there is significant influence of patients marital status on Hospital

image.

118

Further, the mean table 4.22 indicates that the married patients have scored

higher mean value of 23.79 than the patients living as single (22.53). This shows that

the married patients are more concentrating on Hospital Image than the patients living

as single to select Chennai for medical tourism.


influence of patients marital status on hospital image” is rejected.

Cost

The obtained t value is 0.106 and it is not significant at 5% level. The value

indicates that there is no significant influence of patients marital status on cost.


influence of patients marital status on Cost” is accepted.

Safety and security


indicates that there is significant influence of patients marital status on safety and

security.

Further, the mean table 4.22 indicates that the married patients have scored

higher mean value of 18.30 than the patients living as single (17.53). This shows that

the married patients are keener than the patients living as single towards the Safety

and security in Chennai to select Chennai for medical tourism.


influence of patients marital status on safety and security” is rejected.

119

Hygiene


indicates that there is no significant influence of patients marital status on hygiene.


influence of patients marital status on hygiene” is accepted.

Tourism


indicates that there is no significant influence of patients marital status on tourism.


influence of patients marital status on tourism” is accepted.

Travel


indicates that there is no significant influence of patients marital status on travel.


influence of patients marital status on travel” is accepted.

Entertainment


indicates that there is no significant influence of patients marital status on

entertainment.


influence of patients marital status on entertainment” is accepted.

120

4.5.4 Influence of patients educational qualification on factors that made to

select Chennai for Medical tourism

To test the significant influence of patients educational qualification on factors

that made to select Chennai for Medical tourism (Hospital image, Cost, Safety and

security, Hygiene, Tourism, Travel and Entertainment), one way ANOVA was

applied to ascertain if there is any significant influence of patients educational

qualification on factors that made to select Chennai for Medical tourism. The

following null hypotheses were framed:

H0 5: There is no significant influence of patients educational qualification on

(a) Hospital image (b) Cost (c) Safety and security d) Hygiene (e) Tourism (f) Travel

(g) Entertainment in Chennai for medical tourism.

Table 4.23 shows the results of one way ANOVA for influence of patients

educational qualification on factors that made to select Chennai for Medical tourism.

121

Table 4.23

One way ANOVA for influence of patients educational qualification on factors to

select Chennai for Medical tourism

Factors Education Qualification N Mean S D F- value

Hospital image

School level 42 22.14 3.879 15.699** (p<.001)

Graduates 129 24.49 3.633 Post graduates 87 23.52 3.375 Professionals 45 20.60 2.831

Cost

School level 42 17.69 4.158 3.771*

(p=.011) Graduates 129 18.65 2.486 Post graduates 87 19.06 2.089 Professionals 45 17.77 2.583

Safety and security

School level 42 17.14 3.632 7.445** (p<.001)


Hygiene

School level 42 18.11 4.434 7.195** (p<.001)


Tourism

School level 42 18.73 3.709 1.767


Travel

School level 42 18.54 3.617 8.114** (p<.001)


Entertainment

School level 42 18.35 2.506 2.508



122

Hospital Image


indicates that there is significant influence of patients educational qualification on

Hospital image.

Further, the mean table 4.23 indicates that the patients with educational

qualification of graduation have scored higher mean value of 24.49 and the lowest

mean was scored by the patients with professional education (20.60). This shows that

the patients with educational qualification of graduation are more concentrating on

Hospital image to select Chennai for medical tourism and the patients with

professional education less concentrating on Hospital image to select Chennai for

medical tourism.


influence of patients educational qualification on hospital image” is rejected.

Cost



cost.

Further, the mean table 4.23 indicates that the patients with post graduate

education have scored higher mean value of 19.06 and the lowest mean was scored by

the patients with school level education (17.69). This shows that the patients with post

graduate education are more concentrating on Cost to select Chennai for medical

tourism and the patients with school level education are less concentrating on Cost to

select Chennai for medical tourism.

123


influence of patients educational qualification on Cost” is rejected.

Safety and security



safety and security.



mean was scored by the patients with school level education (17.14). This shows that


safety and security towards Chennai for medical tourism and the patients with school

level education less concentrating on safety and security towards Chennai for medical

tourism.


influence of patients educational qualification on safety and security” is rejected.

Hygiene



hygiene.





Hygienic condition in the hospitals to select Chennai for medical tourism and the

124

patients with school level education are less concentrating on Hygienic condition in

the hospitals to select Chennai for medical tourism.


influence of patients educational qualification on hygiene” is rejected.

Tourism


indicates that there is no significant influence of patients educational qualification on

tourism.


influence of patients educational qualification on tourism” is accepted.

Travel



travel.




the patients with educational qualification of graduation are more concentrating

towards Travel to select Chennai for medical tourism and the patients with school

level education are less concentrating towards Travel to select Chennai for medical

tourism.


influence of patients educational qualification on travel” is rejected.

125

Entertainment



entertainment.


influence of patients educational qualification on entertainment” is accepted.

4.5.5 Influence of patients employment status on factors that made to select


To test the significant influence of patients employment status on factors that

made to select Chennai for Medical tourism (Hospital image, Cost, Safety and


applied to ascertain if there is any significant influence of patients employment status

on factors that made to select Chennai for Medical tourism. The following null

hypotheses were framed:

H0 6: There is no significant influence of patients employment status on (a)




employment status on factors that made to select Chennai for Medical tourism.

126

Table 4.24

One way ANOVA for influence of patients employment status on factors to select


Factors Employment status N Mean S D F - value

Hospital image

Temporary contract 92 22.16 4.095 13.623** (p<.001)

Firms Employees 64 23.92 2.668 Business Owners 78 25.17 3.258 Professionals 69 22.17 3.666

Cost

Temporary contract 92 18.53 3.047 0.139

(p=.937) Firms Employees 64 18.67 2.261 Business Owners 78 18.46 2.680 Professionals 69 18.37 2.787

Safety and security



Hygiene



Tourism

Temporary contract 92 19.07 2.665 5.884** (p=.001)


Travel



Entertainment



** Significant at 1% level

127

Hospital Image


indicates that there is significant influence of patients employment status on Hospital

image.

Further, the mean table 4.24 indicates that the patients running their own

business have scored higher mean value of 25.17 and the lowest mean was scored by

the patients with temporary contract employment (22.16). This shows that the patients

running their own business are more concentrating on Hospital image for selecting

Chennai for medical tourism and the patients with temporary employment contract are

less concentrating on Hospital image for selecting Chennai for medical tourism.


influence of patients employment status on hospital image” is rejected.

Cost


indicates that there is no significant influence of patients employment status on cost.


influence of patients employment status on Cost” is accepted.

Safety and security


indicates that there is significant influence of patients employment status on safety

and security.

128

Further, the mean table 4.24 indicates that the patients employed as firm

employees have scored higher mean value of 19.20 and the lowest mean was scored

by the patients working as professionals (17.14). This shows that the patients

employed in firms are more concentrating on Safety and security for selecting

Chennai for medical tourism and the patients working as professionals are less

concentrating on Safety and security for selecting Chennai for medical tourism.


influence of patients employment status on safety and security” is rejected.

Hygiene


indicates that there is significant influence of patients employment status on hygiene.



the patients working as professionals (18.66). This shows that the patients running

their own business are more concentrating on Hygiene to select Chennai for medical

tourism and the patients employed as professionals are less concentrating on Hygiene

to select Chennai for medical tourism.


influence of patients employment status on hygiene” is rejected.

Tourism


indicates that there is significant influence of patients employment status on tourism.

129

Further, the mean table 4.24 indicates that the patients running own business

have scored higher mean value of 20.53 and the lowest mean was scored by the

patients employed in temporary contract (19.07). This shows that the patients running

their own business are more concentrating on Tourism to select Chennai for medical

tourism and the patients unemployment status of employed with temporary contract

are less satisfied on Chennai for medical tourism.


influence of patients employment status on tourism” is rejected.

Travel


indicates that there is no significant influence of patients employment status on travel.


influence of patients employment status on travel” is accepted.

Entertainment


indicates that there is no significant influence of patients employment status on

entertainment.


influence of patients employment status on entertainment” is accepted.

130

4.5.6 Influence of patients annual income on factors that made to select


To test the significant influence of patients annual income on factors that

made to select Chennai for Medical tourism (Hospital image, Cost, Safety and


applied to ascertain if there is any significant influence of patients annual income on

factors that made to select Chennai for Medical tourism. The following null

hypotheses were framed:

H0 7: There is no significant influence of patients annual income on (a)




annual income on factors that made to select Chennai for Medical tourism.

131

Table 4.25

One way ANOVA for influence of patients annual income on factors to select


Factors Annual Income N Mean S D F-value

Hospital image

Below 10,000$ 79 22.07 4.310 9.208** (p<.001)

10,001 - 30,000$ 133 23.45 3.329 30,001 - 60,000$ 51 23.00 2.884 Above 60,000$ 40 25.70 3.680

Cost

Below 10,000$ 79 17.87 3.603 2.005

(p=.113) 10,001 - 30,000$ 133 18.66 2.183 30,001 - 60,000$ 51 18.84 2.737 Above 60,000$ 40 18.80 2.209

Safety and security

Below 10,000$ 79 17.16 3.364 5.202** (p=.002)

10,001 - 30,000$ 133 17.93 3.066 30,001 - 60,000$ 51 18.43 2.736 Above 60,000$ 40 19.40 2.529

Hygiene

Below 10,000$ 79 18.24 3.567 18.557

(p<.001) 10,001 - 30,000$ 133 19.23 2.051 30,001 - 60,000$ 51 19.25 1.671 Above 60,000$ 40 21.80 1.856

Tourism

Below 10,000$ 79 18.93 3.231 14.261*** (p<.001)

10,001 - 30,000$ 133 19.28 2.278 30,001 - 60,000$ 51 19.84 2.043 Above 60,000$ 40 21.90 1.780

Travel

Below 10,000$ 79 19.10 2.643 13.247** (p<.001)

10,001 - 30,000$ 133 19.17 2.356 30,001 - 60,000$ 51 18.96 2.553 Above 60,000$ 40 21.70 2.028

Entertainment

Below 10,000$ 79 18.26 2.055 0.965

(p=.410) 10,001 - 30,000$ 133 17.90 2.562 30,001 - 60,000$ 51 18.27 2.164 Above 60,000$ 40 18.50 1.219


132

Hospital Image


indicates that there is significant influence of patients annual income on Hospital

image.

Further, the mean table 4.25 indicates that the patients earning annual income

above 60,000$ have scored higher mean value of 25.70 and the lowest mean was

scored by the patients earning annual income below 10,000$ (22.07). This shows that

the patients earning annual income above 60,000$ are more concentrating on

Infrastructure facilities in Hospitals in Chennai to select Chennai for medical tourism

and the patients with annual income below 10,000$ are less concentrating on

Infrastructure facilities in Hospitals in Chennai to select Chennai for medical tourism.


influence of patients annual income on hospital image” is rejected.

Cost


indicates that there is no significant influence of patients annual income on cost.


influence of patients annual income on cost” is accepted.

Safety and security


indicates that there is significant influence of patients annual income on safety and

security.



133


the patients earning annual income above 60,000$ are more concentrating on Safety

and security in hospitals in Chennai for medical tourism and the patients earning

annual income below 10,000$ are less concentrating on Safety and security in

hospitals in Chennai for medical tourism.


influence of patients annual income on safety and security” is rejected.

Hygiene


indicates that there is significant influence of patients annual income on hygiene.




the patients earning annual income above 60,000$ are more concentrating on

Hygienic conditions in Chennai for medical tourism and the patients earning annual

income below 10,000$ are less concentrating on Hygienic conditions in Chennai for

medical tourism.


influence of patients annual income on hygiene” is rejected.

Tourism


indicates that there is significant influence of patients annual income on tourism.



134


the patients earning annual income above 60,000$ are more concentrating on Tourism

to select Chennai for medical tourism and the patients earning annual income below

10,000$ are less concentrating on Tourism to select Chennai for medical tourism.


influence of patients annual income on tourism” is rejected.

Travel


indicates that there is significant influence of patients annual income on travel.



scored by the patients earning annual income 30,001 - 60,000$ (18.96). This shows

that the patients earning annual income above 60,000$ are more concentrating on

Travel to select Chennai for medical tourism and the patients with annual income of

30,001 - 60,000$ are less concentrating on Travel to select Chennai for medical

tourism.


influence of patients annual income on travel” is rejected.

Entertainment


indicates that there is no significant influence of patients annual income on

entertainment.


influence of patients annual income on entertainment” is accepted.

135

4.6 Factors of satisfaction towards care facilities provided by the hospitals in

Chennai.

For measuring the satisfaction towards care facilities provided by the

hospitals in Chennai for the patients coming for medical tourism, forty variables were

measured. Based on the responses given by the selected patients came for medical

tourism in Chennai, factor analysis was done to group the variables in to factors.

Table 4.26

Initial Eigen values of satisfaction of care facilities provided by hospitals in

Chennai

Factors Initial Eigen values

Eigen Value

Percentage of Variance

Cumulative Percentage

1 3.234 38.81 38.81

2 2.151 9.18 47.99

3 1.985 7.19 55.18

4 1.732 6.86 62.04

5 1.587 5.55 67.59

6 1.341 5.21 72.80

7 1.054 4.68 77.48

Principal Component analysis with varimax rotation is used to group the

factors. Forty variables are reduced into fewer factors by analyzing correlation

between variables (opinions regarding the satisfaction towards care facilities provided

by the hospitals in Chennai). In this case forty variables are reduced in to seven

factors which explain the much of the original data. From the cumulative percentage

column, the seven factors extracted together accounts for 77.48 per cent of the total

variance (information contained in forty variables).

136

Table 4.27

Factor scores of problems faced by the medical tourists

Factors Statements Factor Scores

Infrastructure factor

Availability of rooms 0.851 Cleanliness of the rooms 0.821 Sanitation of the hospital 0.784 Hygienic conditions of the room 0.732 Ventilation of the rooms 0.701 Drinking water facility 0.685 Provisions in rooms 0.604 Provisions for security 0.534

Emergency services factor

Response of the doctors 0.754 Explanation about patients 0.713 Speed of work 0.658 Formalities for registration 0.602 Intensive care space availability 0.598 Facility availability intensive care 0.524 Availability of specialist 0.501

Diagnostic services factor

Availability of latest technology 0.741 Waiting time 0.701 Cost of service 0.662 Time consumed for report 0.635 Response by staff in charge 0.605 Staff availability 0.571

Dietary services factor

Hygienic conditions of the canteen 0.714 Cost of the food 0.684 Quality of the food 0.662 Taste of the food 0.621 Room services 0.537 Delivery time 0.502

Diagnosing factor

Time taken in consultation 0.649 Answering the question promptly 0.631 Counseling by the doctors 0.587 Explanation given for ailment 0.547 Approach of the doctors 0.509

Nursing factor

Approach taken in consultation 0.678 Assistance by the nurses 0.645 Medication given by the staff nurses 0.531 Availability of the nurses 0.511

Registration factor

Information provided on registration 0.654 Waiting time in registration 0.612 Formalities in registration 0.546 Approach of the receptionist 0.507

137

From the table 4.27 it is inferred that factor 1 is a combination of eight original

variables such as Availability of rooms, Cleanliness of the rooms, Sanitation of the

hospital, Hygienic conditions of the room, Ventilation of the rooms, Drinking water

facility, Provisions in rooms and Provisions for security which is named as

Infrastructure factor.

Factor 2 is a combination of seven original variables such as Response of the

doctors, Explanation about patients, Speed of work, Formalities for registration,

Intensive care space availability, Facility availability intensive care and Availability

of specialist which is named as Emergency services factor.

Factor 3 is a combination of six original variables such as Availability of latest

technology, waiting time, Cost of service, Time consumed for report, Response by

staff in charge and Staff availability which is named as Diagnostic services factor.

Factor 4 is a combination of six original variables such as Hygienic conditions

of the canteen, Cost of the food, Quality of the food, Taste of the food, Room services

and Delivery time which is named as Dietary services factor.

Factor 5 is a combination of five original variables such as Time taken in

consultation, answering the question promptly, Counseling by the doctors,

Explanation given for ailment and Approach of the doctors which is named as

Diagnosing factor.

Factor 6 is a combination of four original variables such as Approach taken in

consultation, Assistance by the nurses, Medication given by the staff nurses and

Availability of the nurses which is named as nursing factor.

Factor 7 is a combination of four original variables such as Information

provided on registration, waiting time in registration, Formalities in registration and

Approach of the receptionist which is named as Registration factor.

138

4.7 Relationships between factors of satisfaction towards the services

provided by the Hospitals in Chennai to medical tourists

Factors of satisfaction are interrelated, the researcher made a valiant attempt to

identify the degree of relationship between the factors. To test the significant

relationship between factors of satisfaction (Infrastructure, Emergency services,

Diagnostic services, Dietary services, Diagnosing, Nursing and Registration) towards

the services provided by the hospitals in Chennai to medical tourists. Bivariate

correlation was applied to ascertain if there were any significant relationships between

factors of satisfaction.

Table 4.28

Relationship between factors of satisfaction

Factors

Infr

astr

uctu

re

Em

erge

ncy

serv

ices

Dia

gnos

tic

serv

ices

Die

tary

se

rvic

es

Dia

gnos

ing

Nur

sing

Reg

istr

atio

n

Infrastructure 1 r =.568** r =.472** r =.556** r =.481** r =.331** r =.466**

p<.001 p<.001 p<.001 p<.001 p<.001 p<.001

Emergency services

1 r =.543** r =.617** r =.489** r =.565** r =.563**

p<.001 p<.001 p<.001 p<.001 p<.001

Diagnostic services

1 r =.683** r =.712** r =.319** r =.639**

p<.001 p<.001 p<.001 p<.001

Dietary services

1 r =.685** r =.543** r =.619**

p<.001 p<.001 p<.001

Diagnosing 1 r =.355** r =.627**

p<.001 p<.001

Nursing 1 r =.405**

p<.001

Registration 1


139

Positive significant correlation is observed between Infrastructure and

Emergency service (r =.568). Significant correlation is observed between

Infrastructure and Diagnostic service (r =.472), which is positive.

Positive significant correlation is observed between Infrastructure and Dietary

services (r =.556). Significant correlation is observed between Infrastructure and

Diagnosing (r =.481), which is positive.

Positive significant correlation is observed between Infrastructure and Nursing

(r =.331). Significant correlation is observed between Infrastructure and Registration

(r=.466), which is positive. Significant correlation is observed between Emergency

service and Diagnostic service (r =.543), which is positive.

Positive significant correlation is observed between Emergency service and

Dietary services (r =.617). Significant correlation is observed between Emergency

service and Diagnosing (r =.489), which is positive.

Positive significant correlation is observed between Emergency service and

Nursing (r =.565). Significant correlation is observed between Emergency service and

Registration (r =.563), which is positive.

Positive significant correlation is observed between Diagnostic service and

Dietary services (r =.683). Significant correlation is observed between Diagnostic

service and Diagnosing (r =.712), which is positive.

Positive significant correlation is observed between Diagnostic service and

Nursing (r =.319). Significant correlation is observed between Diagnostic service and

Registration (r =.639), which is positive. Significant correlation is observed between

Dietary services and Diagnosing (r =.685), which is positive.

140

Positive significant correlation is observed between Dietary services and

Nursing (r =.543). Significant correlation is observed between Dietary services and


Positive significant correlation is observed between Diagnosing and Nursing

(r =.355).Significant correlation is observed between Diagnosing and Registration

(r =.627), which is positive. Significant correlation is observed between Nursing and


4.8 Influence of patients demographics on factors of satisfaction towards care

facilities provided by the hospitals in Chennai

4.8.1 Influence of patients gender on factors of satisfaction towards care


To test the significant influence of patients gender on factors of satisfaction

(Infra structure, Emergency service, Diagnostic services, Dietary services, Diagnosis,

Nursing and Registration) towards care facilities provided by the hospitals in Chennai,

independent samples t-test was applied to ascertain if there is any significant influence

of patients gender on factors of satisfaction towards care facilities provided by the

hospitals in Chennai.


H0 8: There is no significant influence of patients gender on satisfaction

towards (a) Infra structure (b) Emergency service (c) Diagnostic services (d) Dietary

services (e) Diagnosis (f) Nursing (g) Registration in Chennai hospitals.

Table 4.29 shows the results of t-test for influence of patients gender on

factors of satisfaction towards care facilities provided by the hospitals in Chennai.

141

Table 4.29

t-test for influence of patients gender on factors of satisfaction towards care


Factors Gender N Mean S D t-value

Infrastructure Male 189 30.30 3.402 2.618**

(p=.009) Female 114 29.29 2.977

Emergency services

Male 189 26.14 3.270 2.175* (p=.030) Female 114 25.27 3.545

Diagnostic services

Male 189 24.04 3.025 4.444** (p< .001) Female 114 22.55 2.492

Dietary services Male 189 39.17 3.410 3.579**

(p< .001) Female 114 37.78 3.002

Diagnosing Male 189 20.33 2.243 5.396**

(p< .001) Female 114 18.91 2.204

Nursing Male 189 15.31 2.001 1.174

(p=.241) Female 114 15.06 1.530

Registration Male 189 16.34 2.206 2.599*

(p=.010) Female 114 15.71 1.827 ** Significant at 1% level * significant at 5% level

Infrastructure


indicates that there is significant influence of patients gender on infrastructure.



patients are more satisfied on Infrastructure facilities available in the hospitals in

Chennai than the female patients.

142


influence of patients gender on infrastructure” is rejected.

Emergency services


indicates that there is significant influence of patients gender on emergency services.



patients are more satisfied with Emergency services in the hospitals in Chennai than

the female patients.


influence of patients gender on emergency services” is rejected.

Diagnostic services


indicates that there is significant influence of patients gender on diagnostic services.



patients are more satisfied with Diagnostic service provided by the hospitals in



influence of patients gender on diagnostic services” is rejected.

Dietary services


indicates that there is significant influence of patients gender on Dietary services.

143



patients are more satisfied with the Dietary services provided by the hospitals in



influence of patients gender on Dietary services” is rejected.

Diagnosing


indicates that there is significant influence of patients gender on Diagnosing.



patients are more satisfied with Diagnosis provided by the hospitals in Chennai than

the female patients.


influence of patients gender on Diagnosing” is rejected.

Nursing


indicates that there is no significant influence of patients gender on nursing.


influence of patients gender on nursing” is accepted.

Registration


indicates that there is significant influence of patients gender on Registration.

144



patients are more satisfied with the registration in hospitals in Chennai than the

female patients.


influence of patients gender on Registration” is rejected.

4.8.2 Influence of patients age on factors of satisfaction towards care facilities

provided by the hospitals in Chennai

To test the significant influence of patients age on factors of satisfaction

(Infra structure, Emergency service, Diagnostic services, Dietary services, Diagnosis,

Nursing and Registration) towards care facilities provided by the hospitals in Chennai,

one way ANOVA was applied to ascertain if there is any significant influence of

patients age on factors of satisfaction towards care facilities provided by the hospitals

in Chennai.


H0 9: There is no significant influence of patients age on satisfaction towards

(a) Infra structure (b) Emergency service (c) Diagnostic services (d) Dietary services

(e) Diagnosis (f) Nursing (g) Registration in Chennai hospitals.

Table 4.30 shows the results of one way ANOVA for influence of patients age

on factors of satisfaction towards care facilities provided by the hospitals in Chennai.

145

Table 4.30

ANOVA for influence of patients age on factors of satisfaction towards care


Factors Age N Mean S D F-value

Infrastructure

18 - 30 years 91 29.62 4.026 5.569** (p=.004)

31 - 40 years 92 30.85 3.575

More than 40 years 120 29.44 2.073

Emergency services

18 - 30 years 91 25.83 3.865 0.327

(p=.722) 31 - 40 years 92 26.02 3.564

More than 40 years 120 25.64 2.866

Diagnostic services

18 - 30 years 91 22.76 2.687 4.148*

(p=.017) 31 - 40 years 92 23.92 3.145

More than 40 years 120 23.69 2.842

Dietary services

18 - 30 years 91 38.41 3.918 2.064

(p=.129) 31 - 40 years 92 39.23 3.806

More than 40 years 120 38.38 2.238

Diagnosing

18 - 30 years 91 19.19 2.276 4.856** (p=.008)

31 - 40 years 92 20.21 2.435

More than 40 years 120 19.94 2.212

Nursing

18 - 30 years 91 15.02 2.323 1.422

(p=.243) 31 - 40 years 92 15.14 1.745

More than 40 years 120 15.43 1.447

Registration

18 - 30 years 91 15.59 2.210 4.505*

(p=.012) 31 - 40 years 92 16.17 1.687

More than 40 years 120 16.45 2.214 ** Significant at 1% level * significant at 5% level

146

Infrastructure


indicates that there is significant influence of patients age on infrastructure.

Further, the mean table 4.30 indicates that the patients with age of 31 - 40


patients with age more than 40 years (29.44). This shows that the patients with age of

31 - 40 years are more satisfied with the Infrastructure facilities available in the

hospitals in Chennai and the patients with age more than 40 years are less satisfied

with the Infrastructure facilities available in the hospitals in Chennai.


influence of patients age on infrastructure” is rejected.

Emergency services

The obtained F value is 0.327 and it is not significant at 5 % level. The value

indicates that there is no significant influence of patients age on emergency services.


influence of patients age on emergency services” is accepted.

Diagnostic services


indicates that there is significant influence of patients age on diagnostic services.

Further, the mean table 4.30 indicates that the patients with age 31 - 40 years


patients with age 18 - 30 years (22.76). This shows that the patients with age 31 - 40

years are more satisfied with the Diagnostic services and the patients with age 18 - 30

147

years are less satisfied with the Diagnostic services provided by the hospitals in

Chennai.


influence of patients age on diagnostic services” is rejected.

Dietary services


indicates that there is no significant influence of patients age on Dietary services.


influence of patients age on Dietary services” is accepted.

Diagnosing


indicates that there is significant influence of patients age on Diagnosing.

Further, the mean table 4.30 indicates that the patients with age 31 - 40 years


patients with age 18 - 30 years (19.19). This shows that the patients with age of 31- 40

years are more satisfied on Diagnosis in the hospitals in Chennai and the patients with

age 18 - 30 years are less satisfied on Diagnosis in the hospitals in Chennai.


influence of patients age on Diagnosing” is rejected.

Nursing


indicates that there is no significant influence of patients age on nursing.

148


influence of patients age on nursing” is accepted.

Registration


indicates that there is significant influence of patients age on Registration.

Further, the mean table 4.30 indicates that the patients with age of more than

40 years have scored higher mean value of 16.45 and the lowest mean was scored by

the patients with age 18 - 30 years (15.59). This shows that the patients with age more

than 40 years are more satisfied on Registration formalities in the hospitals in Chennai

and the lowest mean was scored by the patients with age 18 - 30 years are less

satisfied with the Registration formalities in the hospitals in Chennai.


influence of patients age on Registration” is rejected.

4.8.3 Influence of patients marital status on factors of satisfaction towards care


To test the significant influence of patients marital status on factors of

satisfaction (Infra structure, Emergency service, Diagnostic services, Dietary services,

Diagnosis, Nursing and Registration) towards care facilities provided by the hospitals

in Chennai, independent samples t-test was applied to ascertain if there is any

significant influence of patients marital status on factors of satisfaction towards care

facilities provided by the hospitals in Chennai.

149


H0 10: There is no significant influence of patients marital status on

satisfaction towards (a) Infra structure (b) Emergency service (c) Diagnostic services

(d) Dietary services (e) Diagnosis (f) Nursing (g) Registration in Chennai hospitals.

Table 4.31 shows the results of t-test for influence of patients marital status

on factors of satisfaction towards care facilities provided by the hospitals in Chennai.

Table 4.31

t-test for influence of patients marital status on factors of satisfaction towards

care facilities provided by the hospitals in Chennai

Factors Marital status N Mean S D t-value

Infrastructure Married 188 29.78 2.726 0.987

(p=.324) Single 115 30.16 4.028

Emergency services Married 188 25.88 2.998 0.444

(p=.658) Single 115 25.70 3.975

Diagnostic services Married 188 23.64 2.750 1.248

(p=.213) Single 115 23.21 3.181

Dietary services Married 188 38.43 2.669 1.456

(p=.146) Single 115 39.00 4.174

Diagnosing Married 188 19.82 2.223 0.265

(p=.791) Single 115 19.75 2.504

Nursing Married 188 15.25 1.522 0.349

(p=.727) Single 115 15.17 2.272

Registration Married 188 16.22 2.009 1.276

(p=.203) Single 115 15.91 2.214

150

Infrastructure



infrastructure.


influence of patients marital status on infrastructure” is accepted.

Emergency services


indicates that there is no significant influence of patients marital status on emergency

services.


influence of patients marital status on emergency services” is accepted.

Diagnostic services


indicates that there is no significant influence of patients marital status on diagnostic

services.


influence of patients marital status on diagnostic services” is accepted.

Dietary services


indicates that there is no significant influence of patients marital status on Dietary

services.

151


influence of patients marital status on Dietary services” is accepted.

Diagnosing


indicates that there is no significant influence of patients marital status on Diagnosing.


influence of patients marital status on Diagnosing” is accepted.

Nursing


indicates that there is no significant influence of patients marital status on nursing.


influence of patients marital status on nursing” is accepted.

Registration



Registration.


influence of patients marital status on Registration” is accepted.

152

4.8.4 Influence of patients educational qualification on factors of satisfaction


To test the significant influence of patients educational qualification on

factors of satisfaction (Infra structure, Emergency service, Diagnostic services,

Dietary services, Diagnosis, Nursing and Registration) towards care facilities

provided by the hospitals in Chennai, one way ANOVA was applied to ascertain if

there is any significant influence of patients educational qualification on factors of

satisfaction towards care facilities provided by the hospitals in Chennai.


H0 11: There is no significant influence of patients educational qualification

on satisfaction towards (a) Infra structure (b) Emergency service (c) Diagnostic

services (d) Dietary services (e) Diagnosis (f) Nursing (g) Registration in Chennai

hospitals.


educational qualification on factors of satisfaction towards care facilities provided by

the hospitals in Chennai.

153

Table 4.32

ANOVA for influence of patients educational qualification on factors of

satisfaction towards care facilities provided by the hospitals in Chennai

Factors Education Qualification N Mean S D F - value

Infrastructure

School level 42 30.45 4.654 1.923


Emergency services

School level 42 25.61 4.515 1.883


Diagnostic services

School level 42 22.92 3.142 7.381** (p< .001)


Dietary services

School level 42 38.28 4.665 1.032


Diagnosing

School level 42 19.61 2.458 5.823** (p=.001)


Nursing

School level 42 14.28 2.634 5.448** (p=.001)


Registration

School level 42 15.64 2.583 7.949** (p< .001)



154

Infrastructure



infrastructure.


influence of patients educational qualification on infrastructure” is accepted.

Emergency services



emergency services.


influence of patients educational qualification on emergency services” is accepted.

Diagnostic services



diagnostic services.




the patients with educational qualification of graduation are more satisfied on

Diagnostic services provided by the hospitals in Chennai and the patients with

professional education are less satisfied on Diagnostic services provided by the


155


influence of patients educational qualification on diagnostic services” is rejected.

Dietary services



Dietary services.


influence of patients educational qualification on Dietary services” is accepted.

Diagnosing



Diagnosing.




the patients with educational qualification of graduation are more satisfied on

Diagnosis in the hospitals in Chennai and the patients with educational qualification

of graduation are less satisfied on Diagnosis in the hospitals in Chennai.


influence of patients educational qualification on Diagnosing” is rejected.

Nursing



nursing.

156




the patients with educational qualification of graduation are more satisfied on nursing

facilities provided by the hospitals in Chennai and the lowest mean was scored by the

patients with school level education are less satisfied with the Nursing facilities

provided by the hospitals in Chennai.


influence of patients educational qualification on nursing” is rejected.

Registration



Registration.




the patients with educational qualification of graduation are more satisfied with

Registration formalities in the hospitals in Chennai and the lowest mean was scored

by the patients with professional education are less satisfied on Registration

formalities in the hospitals in Chennai.


influence of patients educational qualification on Registration” is rejected.

157

4.8.5 Influence of patients employment status on factors of satisfaction towards


To test the significant influence of patients employment status on factors of



in Chennai, one way ANOVA was applied to ascertain if there is any significant

influence of patients employment status on factors of satisfaction towards care

facilities provided by the hospitals in Chennai.


H0 12: There is no significant influence of patients employment status on




employment status on factors of satisfaction towards care facilities provided by the


158

Table 4.33

ANOVA for influence of patients employment status on factors of satisfaction


Factors Employment status N Mean S D F value

Infrastructure



Emergency services



Diagnostic services



Dietary services



Diagnosing

Temporary contract 92 19.36 2.115 16.107** (p< .001)


Nursing



Registration

Temporary contract 92 15.65 2.186 13.183** (p< .001)



159

Infrastructure


indicates that there is significant influence of patients employment status on

infrastructure.

Further, the mean table 4.33 indicates that the patients working as firm

employees have scored higher mean value of 31.06 and the lowest mean was scored

by the patients running their own business (29.29). This shows that the patients

working as firm employees are more satisfied on Infrastructure facilities provided by

the hospitals in Chennai and the patients running their own business are less satisfied

with the Infrastructure facilities provided by the hospitals in Chennai.


influence of patients employment status on infrastructure” is rejected.

Emergency services



emergency services.


influence of patients employment status on emergency services” is accepted.

Diagnostic services



diagnostic services.

160



the patients employed as professionals (22.52). This shows that the patients running

their own business are more satisfied on Diagnostic services provided by the hospitals

in Chennai and the patients employed as professionals are less satisfied on Diagnostic

service provided by the hospitals in Chennai.


influence of patients employment status on diagnostic services” is rejected.

Dietary services



Dietary services.


influence of patients employment status on Dietary services” is accepted.

Diagnosing



Diagnosing.




their own business are more satisfied with the Diagnosis in the hospitals in Chennai

and the patients with employment status of professionals are less satisfied with the

Diagnosis in the hospitals in Chennai.

161


influence of patients employment status on Diagnosing” is rejected.

Nursing



nursing.


influence of patients employment status on nursing” is accepted.

Registration



Registration.




their own business are more satisfied with the registration formalities in the hospitals

in Chennai and the patients employed as professionals are less satisfied with the

registration formalities in the hospitals in Chennai.


influence of patients employment status on Registration” is rejected.

162

4.8.6 Influence of patients annual income on factors of satisfaction towards


To test the significant influence of patients annual income on factors of



in Chennai, one way ANOVA was applied to ascertain if there is any significant

influence of patients annual income on factors of satisfaction towards care facilities



H0 13: There is no significant influence of patients annual income on




annual income on factors of satisfaction towards care facilities provided by the


163

Table 4.34

ANOVA for influence of patients annual income on factors of satisfaction


Factors Annual Income N Mean S D F-value

Infrastructure

Below 10,000$ 79 30.12 3.649 4.072** (p=.007)

10,001 - 30,000$ 133 29.81 3.450 30,001 - 60,000$ 51 30.94 2.9893 Above 60,000$ 40 28.60 1.296

Emergency services

Below 10,000$ 79 26.30 4.201 2.399

(p=.068) 10,001 - 30,000$ 133 25.23 3.450 30,001 - 60,000$ 51 26.35 2.726 Above 60,000$ 40 26.10 1.464

Diagnostic services

Below 10,000$ 79 23.17 2.570 8.166**

(p< .001) 10,001 - 30,000$ 133 23.43 3.048 30,001 - 60,000$ 51 22.58 2.779 Above 60,000$ 40 25.40 2.570

Dietary services

Below 10,000$ 79 38.37 4.051 1.601

(p=.189) 10,001 - 30,000$ 133 38.58 3.576 30,001 - 60,000$ 51 38.43 2.402 Above 60,000$ 40 39.70 0.911

Diagnosing

Below 10,000$ 79 19.24 2.237 10.789** (p< .001)

10,001 - 30,000$ 133 19.71 2.330 30,001 - 60,000$ 51 19.49 1.932 Above 60,000$ 40 21.60 2.181

Nursing

Below 10,000$ 79 15.07 1.953 3.475*

(p=.011) 10,001 - 30,000$ 133 14.94 1.974 30,001 - 60,000$ 51 15.70 1.640 Above 60,000$ 40 15.80 .992

Registration

Below 10,000$ 79 15.82 2.263 10.749** (p< .001)

10,001 - 30,000$ 133 15.72 1.931 30,001 - 60,000$ 51 16.29 1.676 Above 60,000$ 40 17.70 2.028


164

Infrastructure


indicates that there is significant influence of patients annual income on infrastructure.


of 30,001 - 60,000$ have scored higher mean value of 30.94 and the lowest mean was

scored by the patients earning annual income of above 60,000$ (28.60). This shows

that the patients earning annual income of 30,001 - 60,000$ are more satisfied with

the Infrastructure facilities in the hospitals in Chennai and the patients earning annual

income of above 60,000$ are less satisfied with the Infrastructure facilities in the



influence of patients annual income on infrastructure” is rejected.

Emergency services


indicates that there is no significant influence of patients annual income on emergency

services.


influence of patients annual income on emergency services” is accepted.

Diagnostic services


indicates that there is significant influence of patients annual income on diagnostic

services.


of above 60,000$ have scored higher mean value of 25.40 and the lowest mean was

165

scored by the patients earning annual income of 30,001 - 60,000$ (22.58). This shows

that the patients earning annual income of above 60,000$ are more satisfied on

Diagnostic services provided by the hospitals in Chennai and the patients earning

annual income of 30,001 - 60,000$ are less satisfied with the Diagnostic services



influence of patients annual income on diagnostic services” is rejected.

Dietary services


indicates that there is no significant influence of patients annual income on Dietary

services.


influence of patients annual income on Dietary services” is accepted.

Diagnosing


indicates that there is significant influence of patients annual income on Diagnosing.



scored by the patients earning annual income of below 10,000$ (19.24). This shows


Diagnosing abilities of the hospitals in Chennai and the patients earning annual

income of below 10,000$ are less satisfied on Diagnosing abilities of the hospitals in

Chennai.

166


influence of patients annual income on Diagnosing” is rejected.

Nursing


indicates that there is significant influence of patients annual income on nursing.



scored by the patients earning annual income of 10,001 - 30,000$ (14.94). This shows


Nursing facilities provided by the hospitals in Chennai and the patients earning annual

income of 10,001 - 30,000$ are less satisfied with Nursing facilities provided by the



influence of patients annual income on nursing” is rejected.

Registration


indicates that there is significant influence of patients annual income on Registration.



scored by the patients earning annual income of 10,001 to 30,000$ (15.72). This

shows that the patients earning annual income of above 60,000$ are more satisfied

with the Registration formalities in the hospitals in Chennai and the lowest mean was

scored by the patients earning annual income of 10,001 to 30,000$ are less satisfied

with the Registration formalities in the hospitals in Chennai.

167


influence of patients annual income on Registration” is rejected.

4.9 Assessing the variation between expectation and satisfaction level among

the patients came as medical tourists to Chennai

Paired samples t-test was applied to ascertain if there was any significant

variation between the expectation and satisfaction towards the services provided by

the hospitals in Chennai for the patients came for medical tourism.

The following null hypothesis is framed:

Null hypothesis H0 (14): There is no significant variation between expectation

and satisfaction towards the services provided by the hospitals in Chennai for the

patients came for medical tourism.

Table 4.35 shows the results of the comparison of the expectation level with

the satisfaction level towards the services provided by the hospitals in Chennai to the

medical tourists.

168

Table 4.35 Comparison of expectation and satisfaction level of patients

Statements Factors Mean S.D t-value

Less hospital charges Expectation 3.59 0.654

3.218** Satisfaction 3.77 0.727

Good treatment Expectation 3.69 0.663

3.826** Satisfaction 3.83 0.682

Good nursing care Expectation 3.67 0.735

1.992* Satisfaction 3.78 0.759

Good infra structure Expectation 3.54 0.712

4.105** Satisfaction 3.76 0.679

Less waiting time Expectation 3.65 0.701

3.238** Satisfaction 3.83 0.685

Good canteen facility Expectation 3.72 0.781

2.074* Satisfaction 3.61 0.717

Good ambience Expectation 3.59 0.739

3.291** Satisfaction 3.77 0.596


The obtained t values are all significant. Significant variation is observed

between expectation level and satisfaction level towards “Less hospital charges”,

“Good Treatment”, Good infra structure”, “Less waiting time” and “Good ambience”

at 1% level. Significant variation is observed between expectation level and

satisfaction level towards “Good nursing care” and “Good canteen facility” at 5%

level. Further on comparing the mean values of expectation and satisfaction, it is

understood that the satisfaction level is more than the expected level except in “Good

canteen facility”. This shows that patients came from foreign countries to hospitals in

Chennai as medical tourists are satisfied with the services provided by the hospitals.

However the satisfaction is lesser than the expected level in “Canteen facilities”. This

shows that hospitals have to concentrate to improve the canteen facilities.

169

4.10 Assessing the association between patients demographics and problems

4.10.1 Assessing the association between gender and hospital problems.

Null hypothesis H0 15(a): There is no significant relationship between gender

and hospital problems.

To assess the relationship between gender and hospital problems, Chi-square

test was performed to identify the relationship between gender and hospital problems.

The results are shown in table 4.36

Table 4.36

Association between gender and hospital problems

Factors Gender

Total Chi square

Value Male Female

Hospital problems

Low N 65 74 139

26.772** (p < .001)

% 21.5% 24.4% 45.9%

Medium N 69 21 90

% 22.8% 6.9% 29.7%

High N 55 19 74

% 18.2% 6.3% 24.4%

Total N 189 114 303

% 62.4% 37.6% 100.0% ** Significant at 1% level

From the table 4.36 it is observed that there is significant association between

gender and hospital problems. Chi square value (26.772) shows that the null

hypothesis is rejected at 1% level. It is found from the analysis that there is a close

association between gender and hospital problems. From the table 4.36 it is evident

that most of the females (24.4%) are facing low level problems in hospitals.

170

4.10.2 Assessing the association between age and hospital problems.

Null hypothesis H0 15(b): There is no significant relationship between age and

hospital problems.

To assess the relationship between age and hospital problems, Chi-square test

was performed to identify the relationship between age and hospital problems. The

results are shown in table 4.37.

Table 4.37

Association between age and hospital problems

Factors Age

Total Chi-square

Value 18-30 years

31 - 40 years

More than 40 years

Hospital problems

Low N 45 38 56 139

37.699** (p < .001)

% 14.9% 12.5% 18.5% 45.9%

Medium N 21 16 53 90

% 6.9% 5.3% 17.5% 29.7%

High N 25 38 11 74

% 8.3% 12.5% 3.6% 24.4%

Total N 91 92 120 303

% 30.0% 30.4% 39.6% 100.0% ** Significant at 1% level


age and hospital problems. Chi square value (37.699) shows that the null hypothesis is

rejected at 1% level. It is found from the analysis that there is a close association

between age and hospital problems. From the table 4.37 it is evident that most of the

patients with age more than 40 years (18.5%) are facing low level problems in

hospitals.

171

4.10.3 Assessing the association between marital status and hospital problems.

Null hypothesis H0 15(c): There is no significant relationship between marital

status and hospital problems.

To assess the relationship between marital status and hospital problems, Chi

square test was performed to identify the relationship between marital status and

hospital problems. The results are shown in table 4.38.

Table 4.38

Association between marital status and hospital problems

Factors Marital status

Total Chi-square

Value Married Single

Hospital problems

Low N 90 49 139

11.717** (p = .003)

% 29.7% 16.2% 45.9%

Medium N 64 26 90

% 21.1% 8.6% 29.7%

High N 34 40 74

% 11.2% 13.2% 24.4%

Total N 188 115 303



marital status and hospital problems. Chi square value (11.717) shows that the null


association between marital status and hospital problems. From the table 4.38 it is

evident that most of the married patients (29.7%) are facing low level problems in

hospitals.

172

4.10.4 Assessing the association between education and hospital problems.

Null hypothesis H0 15(d): There is no significant relationship between

education and hospital problems.

To assess the relationship between education and hospital problems,

Chi-square test was performed to identify the relationship between education and

hospital problems. The results are shown in table 4.39.

Table 4.39

Association between education and hospital problems

Factors Education

Total Chi-square

Value School level Graduates Post

graduates Professionals

Hospital problems

Low N 18 50 39 32 139

18.993** (p = .004)

% 5.9% 16.5% 12.9% 10.6% 45.9%

Medium N 12 50 22 6 90

% 4.0% 16.5% 7.3% 2.0% 29.7%

High N 12 29 26 7 74

% 4.0% 9.6% 8.6% 2.3% 24.4%

Total N 42 129 87 45 303

% 13.9% 42.6% 28.7% 14.9% 100.0% ** Significant at 1% level


education and hospital problems. Chi square value (18.993) shows that the null


association between education and hospital problems. From the table 4.39 it is evident

that most of the graduates (16.5%) are facing low level problems in hospitals.

173

4.10.5 Assessing the association between treatment undergone earlier and

hospital problems.

Null hypothesis H0 15(e): There is no significant relationship between

treatment undergone earlier in Chennai and hospital problems.

To assess the relationship between treatment undergone earlier and hospital

problems, Chi square test was performed to identify the relationship between

treatment undergone earlier and hospital problems. The results are shown in

table 4.40.

Table 4.40

Association between treatment undergone earlier and hospital problems

Factors Treatment undergone

earlier in Chennai Total Chi square

Value Yes No

Hospital problems

Low N 116 23 139

1.124 (p = .570)

% 38.3% 7.6% 45.9%

Medium N 71 19 90

% 23.4% 6.3% 29.7%

High N 58 16 74

% 19.1% 5.3% 24.4%

Total N 245 58 303

% 80.9% 19.1% 100.0%

From the table 4.40 it is observed that there is no significant association

between treatment undergone earlier and hospital problems. Chi square value (1.124)

shows that the null hypothesis is accepted at 5% level. It is found from the analysis

that there is no relationship between treatment undergone earlier and hospital

problems.

174

4.10.6 Assessing the association between gender and payment problems

Null hypothesis H0 15(f): There is no significant relationship between gender

and payment problems.

To assess the relationship between gender and payment problems, Chi-square

test was performed to identify the relationship between gender and payment problems.

The results are shown in table 4.41.

Table 4.41

Association between gender and payment problems

Factors Gender

Total Chi square

Value Male Female

Payment problems

Low N 99 51 150

2.035 (p = .361)

% 32.7% 16.8% 49.5%

Medium N 43 27 70

% 14.2% 8.9% 23.1%

High N 47 36 83

% 15.5% 11.9% 27.4%

Total N 189 114 303

% 62.4% 37.6% 100.0%


between gender and payment problems. Chi square value (2.035) shows that the null

hypothesis is accepted at 5% level. It is found from the analysis that there is no

relationship between gender and payment problems.

175

4.10.7 Assessing the association between age and payment problems.

Null hypothesis H0 15(g): There is no significant relationship between age and

payment problems.

To assess the relationship between age and payment problems, Chi-square test

was performed to identify the relationship between age and payment problems. The


Table 4.42

Association between age and payment problems

Factors Age

Total Chi-square

Value 18 - 30 years

31 - 40 years

More than 40 years

Payment problems

Low N 31 45 74 150

22.801** (p < .001)

% 10.2% 14.9% 24.4% 49.5%

Medium N 24 17 29 70

% 7.9% 5.6% 9.6% 23.1%

High N 36 30 17 83

% 11.9% 9.9% 5.6% 27.4%

Total N 91 92 120 303



age and payment problems. Chi square value (22.801) shows that the null hypothesis

is rejected at 1% level. It is found from the analysis that there is a close association

between age and payment problems. From the table 4.42 it is evident that most of the

patients with age more than 40 years (24.4%) are facing low level payment problems

in hospitals in Chennai.

176

4.10.8 Assessing the association between marital status and payment problems.

Null hypothesis H0 15(h): There is no significant relationship between marital

status and payment problems.

To assess the relationship between marital status and payment problems, Chi

square test was performed to identify the relationship between marital status and

payment problems. The results are shown in table 4.43.

Table 4.43

Association between marital status and payment problems


Total Chi square


Payment problems

Low N 108 42 150

20.386** (p < .001)

% 35.6% 13.9% 49.5%

Medium N 45 25 70

% 14.9% 8.3% 23.1%

High N 35 48 83

% 11.6% 15.8% 27.4%

Total N 188 115 303



marital status and payment problems. Chi square value (20.386) shows that the null


association between marital status and payment problems. From the table 4.45 it is

evident that most of the married patients (35.6%) are facing low level payment

problems in hospitals in Chennai.

177

4.10.9 Assessing the association between education and payment problems.

Null hypothesis H0 15(i): There is no significant relationship between

education and payment problems.

To assess the relationship between education and payment problems, Chi-

square test was performed to identify the relationship between education and payment

problems. The results are shown in table 4.44.

Table 4.44

Association between education and payment problems

Factors Education

Total Chi

square Value School

level Graduates Post graduates Professional

Payment problems

Low N 19 66 41 24 150

15.608* (p = .016)

% 6.3% 21.8% 13.5% 7.9% 49.5%

Medium N 7 40 18 5 70

% 2.3% 13.2% 5.9% 1.7% 23.1%

High N 16 23 28 16 83

% 5.3% 7.6% 9.2% 5.3% 27.4%

Total N 42 129 87 45 303

% 13.9% 42.6% 28.7% 14.9% 100.0% * Significant at 5% level

From the 4.44 it is observed that there is significant association between

education and payment problems. Chi square value (15.608) shows that the null


association between education and payment problems. From the table 4.44 it is

evident that most of the patients possessing graduations (21.8%) are facing low level

payment problems in hospitals in Chennai.

178

4.10.10 Assessing the association between Employment status and payment

problems.

Null hypothesis H0 15(j): There is no significant relationship between

Employment status and payment problems.

To assess the relationship between Employment status and payment problems,

Chi square test was performed to identify the relationship between Employment status

and payment problems. The results are shown in table 4.45.

Table 4.45

Association between Employment status and payment problems

Factors

Employment status

Total Chi

square Value

Employed with

temporary contract

Firms Employees

Business Owners Professionals

Payment problems

Low N 42 25 54 29 150

54.899**(p < .001)

% 13.9% 8.3% 17.8% 9.6% 49.5%

MediumN 22 27 17 4 70

% 7.3% 8.9% 5.6% 1.3% 23.1%

High N 28 12 7 36 83

% 9.2% 4.0% 2.3% 11.9% 27.4%

Total N 92 64 78 69 303



Employment status and payment problems. Chi square value (54.899) shows that the

null hypothesis is rejected at 1% level. It is found from the analysis that there is a

close association between Employment status and payment problems. From the table

179

4.44 it is evident that most of the patients running their own business (17.8%) are

facing low level payment problems in hospitals in Chennai.


payment problems.

Null hypothesis H0 15 (k): There is no significant relationship between

treatment undergone earlier and payment problems.

To assess the relationship between treatment undergone earlier and payment


treatment undergone earlier and payment problems. The results are shown in

table 4.46.

Table 4.46

Association between treatment undergone earlier and payment problems



Value Yes No

Payment problems

Low N 126 24 150

1.947 (p = .378)

% 41.6% 7.9% 49.5%

Medium N 55 15 70

% 18.2% 5.0% 23.1%

High N 64 19 83

% 21.1% 6.3% 27.4%

Total N 245 58 303

% 80.9% 19.1% 100.0%


between treatment undergone earlier and payment problems. Chi square value (1.947)


180

that there is no relationship between treatment undergone earlier and payment

problems.

4.10.12 Assessing the association between gender and other problems.

Null hypothesis H0 15 (l): There is no significant relationship between gender

and other problems.

To assess the relationship between gender and other problems, Chi square test

was performed to identify the relationship between gender and other problems. The


Table 4.47

Association between gender and other problems

Factors Gender

Total Chi square

Value Male Female

Other problems

Low N 105 57 162

1.337 (p = .512)

% 34.7% 18.8% 53.5%

Medium N 59 37 96

% 19.5% 12.2% 31.7%

High N 25 20 45

% 8.3% 6.6% 14.9%

Total N 189 114 303

% 62.4% 37.6% 100.0%


between gender and other problems. Chi square value (1.337) shows that the null

hypothesis is accepted at 5% level. It is found from the analysis that there is no

relationship between gender and other problems.

181

4.10.13 Assessing the association between age and other problems.

Null hypothesis H0 15 (m): There is no significant relationship between age

and other problems.

To assess the relationship between age’s and other problems, Chi-square test

was performed to identify the relationship between age and other problems. The


Table 4.48

Association between age and other problems

Factors Age

Total Chi square

Value 18 - 30 years

31 - 40 years

More than 40 years

Other problems

Low N 36 32 92 160

63.668** (p < .001)

% 11.9% 10.6% 30.36% 52.8%

Medium N 28 45 23 96

% 9.2% 14.9% 7.6% 31.7%

High N 27 15 5 47

% 8.9% 4.95% 1.65% 15.5%

Total N 91 92 120 303



age and other problems. Chi square value (63.668) shows that the null hypothesis is

rejected at 1% level. It is found from the analysis that there is a close association

between age and other problems. From the table 4.48 it is evident that most of the

patients with age more than 40 years (30.36%) are facing low level other problems in


182

4.10.14 Assessing the association between marital status and other problems.

Null hypothesis H0 15(n): There is no significant relationship between marital

status and other problems.

To assess the relationship between marital status and other problems, Chi

square test was performed to identify the relationship between marital status and other

problems. The results are shown in table 4.49.

Table 4.49

Association between marital status and other problems


Total Chi square


Other problems

Low N 121 41 162

35.841** (p < .001)

% 39.9% 13.5% 53.5%

Medium N 55 41 96

% 18.2% 13.5% 31.7%

High N 12 33 45

% 4.0% 10.9% 14.9%

Total N 188 115 303



marital status and other problems. Chi square value (35.841) shows that the null


association between marital status and other problems. From the table 4.49 it is

evident that most of the married patients (39.9%) are facing low level other problems

in hospitals in Chennai.

183

4.10.15 Assessing the association between education and other problems.

Null hypothesis H0 15(o): There is no significant relationship between

education and other problems.

To assess the relationship between education and other problems, Chi square

test was performed to identify the relationship between education and other problems.

The results are shown in table 4.50.

Table 4.50

Association between education and other problems

Factors

Education

Total Chi

square Value

School level

Graduates Post graduates Professionals

Other problems

Low N 23 74 38 27 162

29.137** (p < .001)

% 7.6% 24.4% 12.5% 8.9% 53.5%

Medium N 9 40 42 5 96

% 3.0% 13.2% 13.9% 1.7% 31.7%

High N 10 15 7 13 45

% 3.3% 5.0% 2.3% 4.3% 14.9%

Total N 42 129 87 45 303



education and other problems. Chi square value (29.137) shows that the null


association between education and other problems. From the table 4.50 it is evident

that most of the patients possessing graduation as their educational qualification

(24.4%) is facing low levels other problems in hospitals in Chennai.

184

4.10.16 Assessing the association between employment status and other

problems.

Null hypothesis H0 15(p): There is no significant relationship between

employment status and other problems.

To assess the relationship between employment status and other problems, Chi

square test was performed to identify the relationship between employment status and

other problems. The results are shown in table 4.51.

Table 4.51

Association between employment status and other problems

Factors

Employment status

Total Chi

square Value

Employed with

temporary contract

Firms Employees

Business Owners Professionals

Other problems

Low N 37 37 38 50 162

22.146** (p < .001)

% 12.2% 12.2% 12.5% 16.5% 53.5%

Medium N 34 17 32 13 96

% 11.2% 5.6% 10.6% 4.3% 31.7%

High N 21 10 8 6 45

% 6.9% 3.3% 2.6% 2.0% 14.9%

Total N 92 64 78 69 303



employment status and other problems. Chi square value (22.146) shows that the null


association between employment status and other problems. From the table 4.51 it is

185

evident that most of the patients working as professionals (16.5%) are facing low

level other problems in hospitals in Chennai.


other problems.

Null hypothesis H0 15(q): There is no significant relationship between

treatment undergone earlier and other problems.

To assess the relationship between treatment undergone earlier and other


treatment undergone earlier and other problems. The results are shown in table 4.52

Table 4.52

Association between treatment undergone earlier and other problems



Value Yes No

Other problems

Low N 128 34 162

1.921 (p = .383)

% 42.2% 11.2% 53.5%

Medium N 82 14 96

% 27.1% 4.6% 31.7%

High N 35 10 45

% 11.6% 3.3% 14.9%

Total N 245 58 303

% 80.9% 19.1% 100.0%


between treatment undergone earlier and other problems. Chi square value (1.921)


that there is no relationship between treatment undergone earlier and other problems.

186

4.11 Predictor variables of satisfaction towards services provided by the

hospitals in Chennai to medical tourists

Multiple regression analysis was conducted by taking patients satisfaction

towards the services provided by the hospitals in Chennai for medical tourists as

dependent variable and Infrastructure, Emergency services, Diagnostic services,

Dietary services, Diagnosing, Nursing, Registration and Problems faced as medical

tourists were taken as independent variable (shown in the table 4.53).

Table 4.53

Regression analysis for satisfaction towards services provided by the hospitals in

Chennai

Factors R2 Standard Beta

F t value

Infrastructure Emergency services Diagnostic services Dietary services Diagnosing Nursing Registration Problems faced as medical tourists

0.476

0.851 0.743 0.665 0.123 0.533 0.411 0.003 0.085

33.361**

4.097** 3.583** 2.402* 1.645

2.491* 2.495* 0.055 1.262

Adjusted R2

0.462


It is observed from the table 4.53, the regression models F value is 33.361 and

it is significant at 1% level. The regression models coefficient of determination (R2)

is 0.476 and its adjusted R2 is 0.462, which is a healthy coefficient. One unit increase

in Infrastructure increases the patients satisfaction towards the services provided by

the hospitals in Chennai by 0.851 units. This shows that Infrastructure is one of the

main factors to bring satisfaction among patients.

187

Emergency services serves as a significant predictor by increasing satisfaction

towards services provided by the hospitals in Chennai by 0.743 units. One unit

increase in Diagnostic services improves satisfaction towards service provided by the

hospitals in Chennai by 0.665 units. One unit increase in the Diagnosing and Nursing

improves satisfaction towards the services provided by the hospitals in Chennai by

0.533 and 0.411 units. Dietary services, Registration and Problems faced as medical

tourists are not serving as significant predictors for satisfaction towards services

provided by the private insurance companies.

The regression equation of satisfaction towards services provided by the

hospitals in Chennai is:

Satisfaction towards hospital services = 5.073 + 0.851 (Infrastructure) + 0.743

(Emergency services) + 0.665 (Diagnostic services) + 0.533 (Diagnosing) + 0.411

(Nursing)

Hence Infrastructure, Emergency services, Diagnostic services, Diagnosing

and Nursing serves as significant predictors of satisfaction towards services provided

by the hospitals in Chennai for medical tourists.

4.12 Model for satisfaction towards services provided by the hospitals in

Chennai to medical tourists

Structural equation modeling (SEM) is a statistical technique for testing and

estimating causal relations using a combination of statistical data and qualitative

causal assumptions. This definition of SEM was articulated by the geneticist Sewall

Wright (1921), the economist Trygve Haavelmo (1943) and the cognitive scientist

Herbert Simon (1953), and formally defined by Judea Pearl (2000) using a calculus of

counterfactuals.

188

SEM allows both confirmatory and exploratory modeling, meaning they are

suited to both theory testing and theory development. Confirmatory modeling usually

starts out with a hypothesis that gets represented in a causal model. The concepts used

in the model must then be operationalized to allow testing of the relationships

between the concepts in the model. The model is tested against the obtained

measurement data to determine how well the model fits the data. The causal

assumptions embedded in the model often have falsifiable implications which can be

tested against the data.

With an initial theory SEM can be used inductively by specifying a

corresponding model and using data to estimate the values of free parameters. Often

the initial hypothesis requires adjustment in light of model evidence. When SEM is

used purely for exploration, this is usually in the context of exploratory factor analysis

as in psychometric design.

A model was developed by using analysis of moment structure (AMOS 16.1).

A model is fit to ensure the satisfaction level of the medical tourist came to Chennai.

In this model factors such as Infrastructure, Emergency service, Diagnostic services,

Diagnosing and Nursing (measured through variables and reduced as factors) and

Satisfaction towards the hospital services is unobserved variable. e1, e2, e3, e4 and e5

are error terms (residuals) for Infrastructure, Emergency service, Diagnostic services,

Diagnosing and Nursing.

Null Hypothesis H015: The model fitted for satisfaction towards the services

provided by the hospitals in Chennai to medical tourists is good.

189

Figure 4.1

Model for satisfaction towards services provided by the hospitals in Chennai

to medical tourists

190

Model fit Summary

The model fit Chi square 2 = 2.134 and the models p value is .096 which is

insignificant at 5% level, which shows that the null hypothesis “The model fitted for

satisfaction towards the services provided by the hospitals in Chennai to medical

tourists is good” is accepted. The goodness of fit index (GFI) is .918 of the model,

shows reasonably good fit, and its adjusted goodness of fit (AGFI) is .907. The Root

Mean Square Error of Approximation (RMSEA) is .094, a smaller value indicates

better model, and Expected Cross Validation Index (ECVI) is .109, which are within

the acceptable range indicating a better model fit.

4.13 Summary

This chapter has delineated data analysis within the study as well as the pilot

study conducted before the main study. Once some modifications are made as a result

of the pilot study, data collection for the substantive study primarily concerned a

survey employing a structured questionnaire.

Data from a total of 303 valid questionnaires were included within the

analysis. All variables were tested for validity and reliability before continuing to the

testing of the hypotheses. Hypotheses, those were tested by applicable statistical

methods for the variables concerned are explored during this chapter.

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