A Study on the Medical Service Quality and its Influence upon Level of Patient’s Satisfaction with Special Reference to Selected Major Multispeciality Hospitals, Chennai City

The increasing literacy rate and awareness and increasing levels of income and the evolution of the media, has brought the Indian consumer closer to demand quality health care. In the light of these developments, health care providers need to have a closer look at the perception of their patients and try to provide quality medical and health services to meet their expectations. In this study the researcher tries to identify the Service Quality Gap for the Multispecialty hospitals in Chennai City. Servqual instrument is the used to measure the patient satisfaction. Five dimensions in service quality (Servqual), tangibility, reliability, responsiveness, empathy, and assurance (Parasuraman, Zeithamal, & Berry, 1985) is considered for this research. Using Multi stage sampling method, the samples were selected. The data required was collected through the structured SERVQUAL questionnaire and then it was analyzed using SPSS with Chi-square test, Multiple Regressions, Paired t Test, Reliability test. The results showed that patient’s expectations had not been met in any of the examined dimensions and their consent has not been achieved. It seemed that necessary for managers and relevant authorities to plan and pay special attention to this important issue.

for measuring the nature of administration in healing centers of Jalandhar area. An organized poll has been framed utilizing the five measurements (unwavering quality, confirmation, physical assets, responsiveness, and compassion) including 25 factors as given by Parasuraman. The information has been gathered from the healing centers in Jalandhar district in light of irregular testing approach; the model has been approved through both corroborative and exploratory factor investigation approach. The consequences of the examination did not bolster the five measurements of Parasuraman SERVQUAL in India and consequently, are decreased to four components (measurements) for measuring administration nature of healing centers in Jalandhar, India. They recommended that the strategy creators and healing facility executives should concentrate on these our variables for quality change and fulfilment of their clients 3. Research Methodology: 3.1 Population of the Study: The population considered for present study is all persons of Chennai who was admitted in the private hospitals or those who had taken treatment from private hospitals. The sample was drawn from Chennai, chosen carefully for their widely accepted characteristics.

Objectives of the Study:
 To assess the perceived service quality and patients' satisfaction of the selected multi-specialty hospitals offering medical services,  To analyze the patients expectation on service quality of the selected multi specialty hospitals offering medical services  To examine the gap between the expected services and perceived services (P-E), and  To offer suggestions as to the types of the services that is needed for the enhancement of service quality and satisfaction 3.  1  MIOT  2500  2  Global  1500  3  Kasthuri  1200  4 Hindu mission Hospital 1000 5 Bethesda Hospital 1000 (Source: Records of the Hospitals) All the above hospitals are functioning on 24 x 7 basis. The data are obtained from the patients, who visit the hospital for treatment in the time period between 9-10 AM, 3-5.30 PM and 7-10 PM. 80% of the patient arrivals are in these timings. (7200*80%=5760) Among this 5% of the population is chosen as sample.
The questionnaires are issued to 365 patients and they are asked to report their perception on the service quality experienced, out of which only 300 filled in questionnaires could be collected. 60 questionnaires from all the five hospitals are taken evenly.
Through hospital visits and interviews, a team of research assistants carried out the distribution of the questionnaire and explained the purpose of the study to participants. They were present at all times when the participants were filling the questionnaires.

Data Source:
This research is descriptive and exploratory in nature. It is descriptive since data has been collected through the questionnaire that was distributed. It is also exploratory because it explores the association between perception and expectation on service quality and patient satisfaction in major Multispecialty hospitals, Chennai. a) Primary Data Collection Instrument: The data collection instrument used in this study was structured, closed ended questionnaire. The questionnaire contained questions to measure service quality in private hospitals. Modifications were made to the wording of the SERVQUAL items taken from Parasuraman, Zeithmal and Berry (1985) was added. Here Forty Five (45) statements were asked to respondents, first to know their expectation and then their perception. The statements were divided into five dimensions of service quality which are "Tangibility", "Reliability", "Responsiveness", "Assurance" and "Empathy". b) Secondary Data: The secondary data pertaining to the study was gathered from well equipped libraries in Chennai and Coimbatore and from Internet web resources. Further, the secondary data were also collected from Based on the reliability test results, the "perception of" questions or variables in the questionnaire distributed, the cronbach alpha value α = 0.944 which is greater than 0.7. Hence the questionnaire used in this research is expressed reliable. In all the 45 items of the five dimensions of service quality patient's expectations exceed their perceptions. The gap exists in all the factors /dimensions. The gap value for the "Reliability" is (-5.53), "Responsiveness" (-4.31), "Assurance" (-4.05), "Tangibility" (-2.21) and Empathy (-2017). The most serious shortfalls are on dimensions "Reliability" is (-5.53), "Responsiveness" (-4.31), "Assurance" (-4.05).

Chi Square Test: 4.3.1 Chi Square Test for the Association of Demographic Variables and Patient Perception:
The relationship between Socio demographic profile of the respondents and Patient's perception on Service Quality of Multispecialty hospitals is analysed using Chi-Square analysis. The demographic profiles of the respondents considered are Gender, Age, Monthly Family income, Education, Occupation, and Area of Residence.   The above table shows the relationship between Socio demographic factors of the respondents and with Patient's perception towards various Service Quality Dimension of Multispecialty Hospitals, Chennai. There is no significant association between Age and Tangibility, Gender and Responsiveness dimensions of multispecialty hospitals and there is significant association between other personal factors and perception towards various service quality dimensions of Multispecialty hospitals, Chennai.

Chi Square Test for the Association of Socio Demographic Profile of the Respondents and Patient's Expectation Towards Various Service Quality Dimensions of Multispecialty Hospitals:
The relationship between Socio demographic profile of the respondents and Patient's expectation towards various Service Quality dimensions of Multispecialty hospitals is analysed using Chi-Square analysis. The above table shows the relationship between Socio demographic factors of the respondents and with Patient's expectation towards various Service Quality Dimension of Multispecialty Hospitals, Chennai. There is no significant association between Age and Assurance, Gender and Reliability, Assurance, Empathy, Income and Tangibility, Empathy dimensions of multispecialty hospitals and there is significant association between other personal factors and expectation towards various service quality dimensions of Multispecialty hospitals, Chennai.

Multiple Regression Analysis:
In order to measure the interdependence of independent factors and their level of satisfaction, the results were subjected to multiple regression analysis. The results of multiple regression analysis are shown in Table 7. 762.048 1% Level The t and Sig (p) values give a rough indication of the impact of each predictor variable, namely, Ptansum (t-17.049, p-0.000, p< 0.01), Prelsum (t-6.195 p-0.000, p< 0.01), Pressum (t-7.931, p-0.000, p< 0.01), Passsum (t-12.435, p-0.000, p< 0.01) and pempsuum (t-6.823, p-0.000, p< 0.01). It is found that p value suggests that a predictor variable is having a large impact on the criterion variable. From the above ANOVA value, it was found that all the variables are significantly contribute to overall opinion about Service Quality of Hospitals, as the F-value 762.048, p value 0.00 which are also statistically significant 4.1 Factor Analysis: 4.1.1 Kaiser-Meyer-Olkin (KMO) Test: Kaiser-Meyer-Olkin (KMO) Test is a measure of how suited your data is for Factor Analysis. The statistic is a measure of the proportion of variance among variables that might be common variance. The lower the proportion, the more suited your data is to Factor Analysis. If the KMO Value is greater than >0.6 then that indicates the sampling is adequate. .000 Here the KMO Value for perception is 0.885which indicates the sampling is adequate to run the factor analysis. Factor Analysis exhibits the rotated factor loadings for the 45 statements (Variables/items) of quality of service rendered by the Multispecialty hospitals, Chennai. Now that from the Table 4.142 it is shown that out of 45 variables only 28 have high factor loadings whereas 17 variables has low factor loadings which are eliminated. Now the 28 variables are grouped in to four factors namely FC1, FC2, FC3, FC4.  When factor analysis is used to analyze the data, 45 variables were reduced to 5 factors. These five factors were named as Customer relations, professional competence, infrastructure and hygiene. The Eigen values and total variance explained were obtained from this.  To test the internally consistency of the factors, cronbach's coefficient alpha reliabilities were calculated and it is proved that the factors are consistent internally which proves that the items within the factors are homogenous and consistent internally  Factors are rotated after factor extraction. Principal component analysis with orthogonal varimax rotation is used to identify the significant set of quality system factors. Out of 45 variables only 28 have high factor loadings whereas 17 variables has low factor loadings which are eliminated. Now the 28 variables are grouped in to four factors namely FC1-Customer relations, FC2-Professional competence, FC3-Infrastructure, FC4-Hygiene

Conclusion:
Quality has become an sign for customers while undergoing any service or buying a product or service, and it is also a strategic advantage for the organizations to gain success and remain competitive in the market, by delivering superior quality of services or products, based on customer requirements. This study provides a good insight into the Multispecialty hospital sector in Chennai. Thereby, they can recognize their Strength, Weakness, Opportunity and Challenges using the different constructs used in this study. To compete in the prevailing fierce industry, every hospital in private sector should introduce an innovative practice to attract more patients through delivering the highest service quality.
The Servqual analysis helps to find out in what constructs the hospitals have to improve and in what constructs they have succeeded in meeting the expectation of the patient or its customers. The negative quality gap in service quality dimensions can be used as a guideline for planning and allocation of resources. The service quality in the areas Cost of Services, Feedback mechanism, Nurses are reliable and provide accurate information, Services provided by Hospital nurses are within promised time frame, Nurses show their interest in solving patients' basic problems, Nurses are willing to help at all times needed a lot of improvement as the negative gap score is higher in those constructs. Due to the emergence of new hospitals in every nook and corner, the resource availability is the major concern. Does all the doctors employed are highly skilled is the question arise among the population. 7. References: