HAS THE SERVICE QUALITY IN PRIVATE CORPORATE HOSPITALS MEET THE PATIENT EXPECTATIONS? A STUDY ABOUT HOSPITAL QUALITY IN CHENNAI

HAS THE SERVICE QUALITY IN PRIVATE CORPORATE HOSPITALS MEET THE PATIENT EXPECTATIONS? A STUDY ABOUT HOSPITAL QUALITY IN CHENNAI S.SHARMILA*; DR.JAYASREE KRISHNAN** * Research Scholar Sathyabama University, Chennai. ** St.Josephs College of Engineering, Chennai. ABSTRACT This paper seeks to present an analysis of the literature examining objective information concerning the subject of patient satisfaction, as it applies to the current medical practices. The study in this paper carries information about patients as customers, current understanding of the patient satisfaction and its determinants, measurement issues and present medical practices. Hopefully, this information will be synthesized to generate a cogent approach to correlate patient satisfaction with quality. As the empirical setting this study concerns five dimensions of hospitals in Chennai city. The survey instrument in a questionnaire form was designed to achieve the research objectives. A total of 385 questionnaires consisting of namely 22 items were given to the higher/officers level employees working in different organization out of which only replies were absolute and useful to the study. A five point scale was used to find out the result. Health-care services quality should be exclusively evaluated by the patients. The patients in the hospital found many good and bad issues among the stated items. The patients were more comfortable with the physicians than the nurses. Many other items were found to be moderate. Results show that in private hospitals doctors are genuinely concerned for their patients, doctors and nurses has attentions to care their patients and private hospitals are putting their maximum efforts in order to provide comforts to their patients. This result can be used by the hospital to redesign and to improve their quality management processes and for the future direction of their more effective healthcare quality strategies in hospitals. This paper also identifies some discomfort in the patient services quality of the hospital. At the same time, patients are changing their attitudes towards health-care, becoming much more concerned and demanding of health services. This paper reveals the importance of quality evaluation of patient services in few items for their repeated visits and increased patient satisfaction. KEYWORDS: Health-care industry, patient satisfaction, quality of patient services, physicians and nursing care. 19

INTRODUCTION The healthcare industry has to cope with environmental pressures such as demographic changes and ageing of populations as well as emergence of new treatments and technologies and increased insistence on greater quality of service in order to remain competitive (Ingram and Desombre, 1999; Andaleeb, 1998). Competitiveness among the healthcare organizations also depends upon patient s satisfaction. Patient s satisfaction is created through a combination of responsiveness to the patient s views and needs, and continuous improvement of the healthcare services, as well as continuous improvement of the overall doctor-patient relationship. Determining the factors associated with patients satisfaction is important topic for the healthcare provider to understand what is valued by patients, how the quality of care is perceived by the patients and to know where, when and how service change and improvement can be made. Most of the studies in the services sector have looked only at the link between services quality and satisfaction (e.g. Kelly and Davis, 1994; Parasuraman et al., 1994; Bettencourt, 1997; Zineldin, 2000a). Few studies have been conducted to investigate the link between technical and functional quality dimensions and the level of patient s satisfaction in the healthcare sector. None of the studies have empirically examined how the atmosphere, interaction and infrastructure might impact the overall patient s quality expectations and satisfaction. In this study the researcher would like to bring out the fact that a patient s satisfaction is a cumulative construct summing satisfaction with various facts of the hospital, such as technical, functional, infrastructure, interaction and atmosphere variables or items. So in this study the researcher has brought different constructs under five variables to measure the patients expectations and satisfaction. It is based on these variables a study was conducted and with those constructs a sequential equation model has been designed to evaluate the quality of service in the hospitals in Chennai city. This research attempt to contribute the previous academic studies in quality management in healthcare sector by, designing a SEM model towards the quality of service in Chennai hospitals. This study involves the respondents only at the officers level at various service organizations with various educational backgrounds and hence will reveal the fact of different opinion among the quality care in hospitals, and hence summing up all the opinions will bring the study towards the goal of patient satisfaction in service quality. The result can be used by the hospitals to reengineer and redesign creatively their quality management processes and the future direction of their more effective healthcare quality strategies. HEALTHCARE IN INDIA: A growing healthcare sector: Healthcare is one of India s largest sectors, in terms of revenue and employment, and the sector is expanding rapidly. During the 1990s, Indian healthcare grew at a compound annual rate of 16%. Today the total value of the sector is more than $34 billion. This translates to $34 per 20

capita, or roughly 6% of GDP. By 2013, India s healthcare sector is projected to grow to nearly $40 billion. The private sector accounts for more than 80% of total healthcare spending in India. Unless there is a decline in the combined federal and state government deficit, which currently stands at roughly 9%, the opportunity for significantly higher public health spending will be limited. The healthcare divide: When it comes to healthcare, there are two India s: the country with that provides high-quality medical care to middle-class Indians and medical tourists, and the India in which the majority of the population lives a country whose residents have limited or no access to quality care. Today only 25% of the Indian population has access to Western (allopathic) medicine, which is practiced mainly in urban areas, where two-thirds of India s hospitals and health centers are located. Many of the rural poor must rely on alternative forms of treatment, such as ayurvedic medicine, unani and acupuncture. The federal government has begun taking steps to improve rural healthcare. Among other things, the government launched the National Rural Health Mission 2005-2012 in April 2005. The aim of the Mission is to provide effective healthcare to India s rural population, with a focus on 18 states that have low public health indicators and/or inadequate infrastructure. Through the Mission, the government is working to increase the capabilities of primary medical facilities in rural areas, and ease the burden on to tertiary care centers in the cities, by providing equipment and training primary care physicians in how to perform basic surgeries, such as cataract surgery. Deteriorating infrastructure India s healthcare infrastructure has not kept pace with the economy s growth. The physical infrastructure is woefully inadequate to meet today s healthcare demands, much less tomorrows. While India has several centers of excellence in healthcare delivery, these facilities are limited in their ability to drive healthcare standards because of the poor condition of the infrastructure in the vast majority of the country. Of the 15,393 hospitals in India in 2002, roughly two-thirds were public. After years of under-funding, most public health facilities provide only basic care. With a few exceptions, such as the All India Institute of Medical Studies (AIIMS), public health facilities are inefficient, inadequately managed and staffed, and have poorly maintained medical equipment. The number of public health facilities also is inadequate. For instance, India needs 74,150 community health centers per million populations but has less than half that number. In addition, at least 11 Indian states do not have laboratories for testing drugs, and more than half of existing laboratories are not properly equipped or staffed. The principal responsibility for public health funding lies with the state governments, which provide about 80% of public funding. The federal government contributes another 15%, mostly through national health programs. However, the total healthcare financing by the public sector is dwarfed by private sector spending. In 2003, fee-charging private companies accounted for 82% of India s $30.5 billion expenditure on healthcare. This is an extremely high proportion by international standards. Private firms are now thought to provide about 60% of all outpatient care in India and as much as 40% of all in-patient care. It is estimated that nearly 70% of all hospitals and 40% of hospital beds in the country are in the private sector. 21

Healthcare units in India: The below chart shows the total number of healthcare units in India. Source: RHS bulletin Ministry of health and family welfare India s Population, Decennial Growth Rate and Population Density 2011 q Decennial Growth Rate [%] Population Density 1991-2001 [2001] Persons/Sq. Km Rural Urban Total Rural Urban Total India 18.10 31.48 21.54 238 3663 312 Source: Population Census of India, Office of the Registrar General, India Rise of disease: Another factor driving the growth of India s healthcare sector is a rise in both infectious and chronic degenerative diseases. While ailments such as poliomyelitis, leprosy, and neonatal tetanus will soon be eliminated, some communicable diseases once thought to be under control, such as dengue fever, viral hepatitis, tuberculosis, malaria, and pneumonia, have returned in force or have developed a stubborn resistance to drugs. This troubling trend can be attributed in part to substandard housing, inadequate water, sewage and waste management systems, a crumbling public health infrastructure, and increased air travel. In addition to battling infectious diseases, India is grappling with the emergence of diseases such as AIDS as well as food- and water-borne illnesses. And as Indians live more affluent lives and adopt unhealthy western diets that are high in fat and sugar, the country is experiencing a rise in lifestyle diseases such as hypertension, cancer, and diabetes, which is reaching epidemic 22

proportions. Over the next 5-10 years, lifestyle diseases are expected to grow at a faster rate than infectious diseases in India, and to result in an increase in cost per treatment. Wellness programs targeted at the workplace, where many sedentary jobs are contributing to an erosion of employees health, could help to reduce the rising incidence of lifestyle diseases. India and Tamil nadu Health Infrastructure: A comparison: Tamil Nadu is the eleventh largest state in India by area and the seventh most populous state. It is the second largest state economy in India as of 2012, after overtaking Uttar Pradesh and Andhra Pradesh in the two years since 2010 when it was the fourth largest contributor to India's GDP. The state ranked among the top 5 states in India in Human Development Index as of 2006.Tamil Nadu is also the most urbanised state in India. The state has the highest number (10.56%) of business enterprises and stands second in total employment (9.97%) in India, compared to the population share of about 6%.The below chart shows the total number of public healthcare centres available in Tamilnadu. Figure 1: Healthcare units in Tamilnadu Vs India 23

Though we have so many number of health care centres provided by the government we have still deficiency in the quality of the health care in general. So, there are numerous private hospitals in the capital city Chennai. Shortfall in health infrastructure as per 2001 population in India (as on March 2010) TOTAL POPULA TION IN RURAL AREAS TRIBAL POPULAT ION IN RURAL AREAS SUB CENTRES PUBLIC HEALTH CENTRES COMMUNITY HEALTH CENTRES R P S R P S R P S TAMI L NAD U 37921681 55143 7057 8706 * 117 3 128 3 * 293 256 37 INDIA 74249063 9 77338597 1587 92 1470 69 195 90 260 22 236 73 425 2 649 1 453 5 21 15 R-Required. P- In position. S- Short fall. *- Surplus. Source: RHS bulletin Ministry of health and family welfare Quality: Quality could be defined as the ability to meet or exceed customer expectations. This definition reflects a shift in thinking from one of quality as defined by producers to one being customer driven. It is crucial to be able to measure healthcare service quality because increased competition has forced healthcare organizations to become more market-oriented (Vandamme and Leunis, 1992). In the healthcare industry, most service providers offer similar services but often varying levels of service quality (Youssef et al., 1996). OBJECTIVE OF THE STUDY: The study was undertaken to assess the patient s perception about the quality of services in private hospitals in Chennai city. This study aims to find the quality of the doctors, nurses, staffs, hygiene condition, cleanliness, pharmacy services, lab facilities and the emotional aspects of the services received by the patients in private hospitals. 24

LITERATURE REVIEW: Bergh performed an interim analysis to suggest that patients expressed a mean of 6.5 diagnostic possibilities compared to 2.8 potential diagnoses in the physicians differential diagnosis (Bergh, 1998). This illustrates the fact that patients often have idiosyncratic unpredictable diagnostic concerns often expressed indirectly and founded in prior experience with family illness. Patients often have unvoiced agendas regarding their presentations for primary illness. Barry evaluated 35 patients in which only four (11 percent) patients voiced all their concerns (Barry et al., 2000). The most common unvoiced agenda items includes worries about the possible diagnosis, patient thoughts about what is wrong, medicine side effects, or not wanting a prescription. This disconnects between expectation and outcome was found in 100 percent of complaints resulting in misunderstanding, unwanted prescriptions, medication and treatment noncompliance. Bell evaluated 909 patients where 9% had at least one unvoiced desire specifically for specialilty physician referral (16.5%) and physical therapy 8.2%. Those with unvoiced desires tended to be young, uneducated and less likely to trust the physician. This behavior was associated with a decreased likelihood of symptom improvement, and less positive evaluation of physician and the visit. The ability for physicians to predict the patient s reason for the health care visit was evaluated by Boland in 458 patients. Agreement was excellent with only 20% disagreement found which was more common with female gender, multiple complaints and previous evaluations which were for the same complaint, which were independent predictors of low agreement. Interestingly, this discrepancy between the physicians understanding of the reason for the patients visit, and the patients actual chief complaint was not associated with patient satisfaction (Boland et al,). METHODOLOGY This research was conducted at local level in Chennai, the capital city of the Indian state of Tamil Nadu in India. Chennai is the sixth most populous city in India with 4.68 million residents as on census 2011.A questionnaire was developed using SERVQUAL instrument consisting of 22 items representing five service quality dimensions empathy, assurance, tangible, timeliness and responsiveness. These service quality dimensions are considered as construct: empathy contains 4 items, assurance constrains 6 items, tangible contains 6 items, timeliness contains 3 items and responsiveness contains 3 items. The target population of this study was the employees working at officer level in the service organizations and availing healthcare services including consultation and inpatient from the best private hospitals in the city, Chennai. A total 387 questionnaire was send to the different service organizations and total questionnaires were returned back, which represents an effective response rate of 82.69%. Five-point Likert Scale from strongly disagrees to the strongly agrees was used for empirical analysis. The coding of the Likert scale was made as [1 = strongly disagree], [2 = disagree], [3 = neither agree nor disagree], [4 = agree], [5 = strongly agree]. The descriptive statistics of the respondents of this study is given below. 25

Table: 1 Gender Frequency Percentage Cumulative percentage Male 198 61.87 61.87 Female 122 38.13 100.00 Total 100 Table.1 shows the frequency distribution of the gender comprised of male and female. There were total participants in this study and 198 participants were male representing 61.87 % of the total population and 122 participants were female representing 38.13% of the total population. Table. 2 show the frequency distribution of qualification of the respondent. Out of respondents, 21.87% of the respondents were graduates, 51.25% of the respondents were having masters degree and 26.88% were MS/Ph.D. Table: 2 Education Frequency Percentage Cumulative percentage Graduate 70 21.87 21.87 Master 164 51.25 73.12 MS/PhD 86 26.88 100 100 DATA ANALYSIS To measure the service quality of the private hospitals, data was analyzed using SPSS 16.0 and AMOS 16.0 was used. Structural equation modeling (SEM) is most frequently and commonly used method to test the validity of the models that are path analytic with mediating variables and it includes latent variables (Agresti, 2002; Hair et al., 2008; Luna-Arocas & Camps, 2008) and it is also a powerful tool in investigating causal relationships between categorical variables (Bollen, 1989; Bollen & Long, 1993; Mels, 2004). Due to this reason SEM is used in this study to analyze the results and hypothesis. 26

RESULTS OF THE ANALYSIS The theoretical service quality model is presented in Figure 1, using AMOS 16.0 for windows. A significant Chi-square having p-value less than 0.05 and the value of normed-chi-square between 1 and 3 indicates that proposed model is providing a sufficient presentation of the relationship among the studied variables (Seo, Han, & Lee, 2005). The goodness of fit indices (GFI) (Bentrler, 1990) having values greater than 0.70 in case of complex models (Judge & Hulin, 1993), the comparative fit index (CFI) traces the relative improvement of the assessed model over a null where observed variables are assumed uncorrelated and it value from 0.00 to 1.00 and the value close to zero indicates a well fit model and its value close to 1.00 indicate a very good fit (Bentler, 1990; Hu & Bentler, 1999). Root mean squared error of approximation (RMSEA) (Bowne and Cudeck, 1993) and for RMSEA a value of less than 0.05 indicates a close fit and value less than 0.08 represents a good model (Browne & Cudeck, 1993; Byrne, 2001). Table 3, shows the variable used in the study and their brief description, factor loading and measurement coefficient Cronbach alpha of each construct. To check the validity of the instrument is another important factor during statistical analysis. According to Gatewood and Field (1990), reliability of the instrument helps to provides consistency in the results and the Cronbach alpha is used to measure the reliability of the data (Green et al., 2000). Twenty two items of this study has provided acceptable values of Cronbach alpha (0.911), as a value of alpha greater than 0.70 is acceptable (Nunnally, 1978). Secondly, the reliability of the individual constructs is also calculated and it provides us acceptable values as mentioned by Nunnally (1978). The first construct of the study was empathy comprises of 4 items and the measurement coefficient Cronbach alpha for this construct is has (0.82) providing an acceptable value. The second construct is tangible, contains 6 items. The second construct is tangible, contains 6 items and the measurement coefficient Cronbach alpha for this construct is (0.77) providing an acceptable value of alpha. The third construct was assurance contains 6 items and the measurement coefficient Cronbach alpha for this construct is (0.82), fourth construct contains 3 items and the value of Cronbach alpha is (0.73) and fifth construct contains 3 items having Cronbach alpha (0.75). Therefore all the constructs used in this study have an acceptable value of alpha. 27

TABLE 3: DIMENSIONS OF THE SERVQUAL INSTRUMENT Factor Variables and Constructs Loading Empathy (α =0.82) EMP1 Doctors have genuine concern about patients 0.57 EMP2 Doctor care their patients 0.63 EMP3 Staff and nurses care the patient 0.58 EMP4 Hospital put their best efforts to provide comfort to patients 0.66 Tangible (α=0.77) TNG1 Hygienic conditions at hospital 0.59 TNG2 Waiting facilities for attendants and patients 0.53 TNG3 Healthy environment at hospital 0.51 TNG4 Cleanliness of toilets/bathrooms 0.66 TNG5 Cleanliness in wards/rooms (sheets, floor) 0.69 TNG6 Lab and pharmacy facilities within the hospital 0.57 Assurance (α=0.82) ASS1 Doctor s expertise and skills 0.50 ASS2 Thorough investigations of the patient 0.68 ASS3 Doctors almost make right diagnoses 0.64 ASS4 Doctors go for expert opinion in critical cases 0.59 ASS5 Accuracy in lab reports 0.53 ASS6 Special attention to emergency patients 0.58 Timeliness (α=0.73) TIM1 Patients are observed according to appointment 0.48 TIM2 In time delivery of reports/services 0.65 TIM3 Doctors/Staff observe the promised time 0.53 Responsiveness (α =0.75) RES1 Doctors/staff efficiently respond to the patients 0.62 RES2 Doctors/Staff are willing to help/facilitate the patients 0.52 RES3 Feedback mechanism 0.57 28

Model fit summary of the variable studied provides that chi-square value is 517.316, degree of freedom is 209 and the p-value is 0 and normed-chi square is 2.561. As the values of normed-chi square between 1 and 3 indicate that proposed model is providing a sufficient presentation of the relationship among the studied variables (Seo, Han, & Lee, 2005). The value of goodness of fit index for this model (GFI) is 0.78 and therefore, the values greater than 0.70 provides a good fit (Judge & Hulin, 1993). Value of the comparative fit (CFI) for this model is 0.76, therefore, this value lies between 0 and 1, so value from 0.00 to 1.00 and the value close to zero indicates a well fit model and its value close to 1.00 indicate a very good fit (Bentler, 1990; Hu & Bentler, 1999). Root mean squared error of approximation (RMSEA) for this model is 0.07 indicates a good model, as value of RMSEA 0.05 indicates a close fit and value less than 0.08 represents a good model (Browne & Cudeck, 1993; Byrne, 2001). According to the above discussion we can say that overall proposed structural model is a fair representation of patient perception about service quality. Figure 1: Proposed Model 29

EMP1 EMP2 EMP3 Empathy `EMP4 TANG1 TANG2 TANG3 Tangibles TANG4 TANG5 TANG6 ASSU1 ASSU2 ASSU3 ASSU4 ASSU5 ASSU6 Assurance Servi ce Quali ty TIME1 TIME2 TIME3 Timeliness RESP1 RESP2 RESP3 Responsiveness 30

With respect to the first construct, empathy has a direct positive effect on service quality and the factors like doctor s genuine concern for their patients (0.57*0.82 =0.47). The factors like doctor care their patients (0.63*0.82=0.52), nurses and supporting staff care their patients (0.58*0.82=0.48), hospital put their best effort to provide comfort to their patients (0.66*0.82=0.54) has direct positive effect on service quality. The standardized regression weight of the construct empathy is 0.81. Therefore, these results support the hypothesis H1 that patient perception about empathy has a positive impact on service quality. With respect to the 2nd construct, tangible has a direct positive effect on service quality, as all the variables representing this construct also has a direct positive impact on service quality. The regression weight for this construct is 0.77 which support our hypothesis H2 that the level of tangible has a positive impact on service quality. With respect to the third construct, assurance all the items has a positive direct impact on the service quality. The regression weight for this construct is 0.82 which support our hypothesis H3 that assurance has a positive impact on service quality. With respect to the fourth construct, timeliness all the items representing this construct are depicting positive values, therefore timeliness has a positive direct impact on the service quality. The regression weight for this construct is 0.87 which support our hypothesis H4 that assurance has a positive impact on service quality. Last construct responsiveness, all the items representing this construct are depicting positive values, therefore, responsiveness has a direct positive impact on service quality. The regression weight for this construct is 0.72 which support our hypothesis H5 that responsiveness has a positive impact on service quality. 31

TABLE 4: Correlation among the service quality Dimensions Empat hy Tangibl e Assuran ce Timeliness Responsive ness Empathy correlation Sig.2 tailed N Pearson 1.674.607.541.656 Tangible correlation Sig.2 tailed N Pearson.674 1.623.617.668 Assurance correlation Sig.2 tailed N Pearson.607.623 1.629.583 Timeliness Pearson correlation.541.617.629 1.582 Sig.2 tailed N Responsiveness Pearson correlation Sig.2 tailed N.656.668.583.582 1 32

Table 4 provides information regarding correlation between the five service quality dimensions namely; empathy, tangibles, assurance, timeliness and responsiveness. The highest correlation between the variables among all the variables (constructs) is between empathy and tangible and is 69.7%, which indicates that there is a positive and strong correlation among the two variables. It means that infrastructure and sufficient facilities available to human resource (like doctors, nurses and supporting staff) at hospitals helps to increase the empathy level among them which creates a positive impact on increased quality of services to the patients. It is also observed that p-value between these two variables is 0 indicates that there is a strong correlation among these variables. Since p-value between two variables is 0 so it can be conclude that at 1% level of significant the correlation between tangible and empathy is significant and it is the strongest correlation among all the variables. The weakest correlation is 53.1% among timeliness and empathy, however, the correlation is positive among them and the p-value among the variables is 0 indicating a significant correlation among them at 1% level of significant. DISCUSSIONS From the above results generated from Amos 16.0 and path diagram, shows that patient perceive that private hospital are delivering quality healthcare services to the patients. All the service quality constructs empathy, tangible, assurance, timeliness and responsiveness has a positive impact on service quality of private hospitals. It is also concluded that service quality is a latent exogenous variable, which is represented by five observed endogenous variables namely, empathy, tangible, assurance, timeliness and responsiveness. Results of the five factors showed that the measurement model for service quality constructs had a good fit and the model is valid and reliable. Results show that in private hospitals doctors are genuinely concerned for their patients, doctors and nurses has attentions to care their patients and private hospitals are putting their maximum efforts in order to provide comforts to their patients. These variables are representing the first construct empathy and all of these variables have a positive impact on service quality. Hygienic conditions, cleanliness, hospital environment and availability of the lab and pharmacy facilities have a positive impact on the service quality and these variables were representing the second construct tangible. Doctors and supporting staff are highly qualified and expert in their field and labs are highly equipped and generating accurate results also have a positive impact on service quality. Similarly, observation of patients according to appointment, in time delivery of reports and doctors also observe promised time also have a positive impact on service quality and finally, efficiently response to patients calls, willingness to help and facilitate the patients and feedback mechanism also have a positive impact on service quality. The above results indicate that service quality in private hospitals is meeting patients satisfactions. It is evident from the literature that private hospitals in Egypt are delivering better quality of services as compare to public hospitals (Mostafa, 2005). Similarly, the hospitals in Bangladesh are providing better healthcare services as compare to public hospitals and foreign hospitals are far better than public and private hospitals (Andaleeb, 2000). These results also validate our study, that private hospitals are delivering better healthcare services. 33

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