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International Journal of Health Care Quality Assurance Customer perceived service quality, satisfaction and loyalty in Indian private healthcare Rama Koteswara Rao Kondasani Rajeev Kumar Panda

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Customer perceived service quality, satisfaction and loyalty in Indian private healthcare Rama Koteswara Rao Kondasani and Rajeev Kumar Panda School of Management, National Institute of Technology, Rourkela, Rourkela, India


Received 19 January 2015 Revised 4 February 2015 Accepted 11 March 2015

Abstract Purpose – The purpose of this paper is to analyse how perceived service quality and customer satisfaction lead to loyalty towards healthcare service providers. Design/methodology/approach – In total, 475 hospital patients participated in a questionnaire survey in five Indian private hospitals. Descriptive statistics, factor analysis, regression and correlation statistics were employed to analyse customer perceived service quality and how it leads to loyalty towards service providers. Finding – Results indicate that the service seeker-service provider relationship, quality of facilities and the interaction with supporting staff have a positive effect on customer perception. Practical implications – Findings help healthcare managers to formulate effective strategies to ensure a better quality of services to the customers. This study helps healthcare managers to build customer loyalty towards healthcare services, thereby attracting and gaining more customers. Originality/value – This paper will help healthcare managers and service providers to analyse customer perceptions and their loyalty towards Indian private healthcare services. Keywords Customer satisfaction, Loyalty, Perceived service quality, Private healthcare service quality Paper type Research paper

International Journal of Health Care Quality Assurance Vol. 28 No. 5, 2015 pp. 452-467 © Emerald Group Publishing Limited 0952-6862 DOI 10.1108/IJHCQA-01-2015-0008

Introduction Health and healthcare need to be distinguished from each other for no better reason than that the former is often incorrectly seen as a direct function of the latter (Srinivisan, 2010). Healthcare systems are complex; i.e., customer care, quality, insurance, healthcare providers and legal issues, etc., often interact. Healthcare is one of India’s largest service sectors, which can be viewed as a glass half empty or half full. The Indian healthcare sector’s positive point is low-cost medical treatment. The challenges the sector faces are substantial: the need to improve physical infrastructure, poor awareness about health insurance and insufficient trained medical personnel. Under the Indian Constitution, health is a state subject. Each state, therefore, has its own healthcare delivery system in which both public and private (profit and non-profit) staff operate. The 12th five-year plan (2012-2017) aims to increase public health investment in healthcare infrastructure, services and human resources from 1.1 per cent in the 11th five-year plan (2007-2012) to 2-3 per cent of gross domestic product (GDP). The Indian healthcare sector is divided into three categories: public; private and solely operated. The sector is large and well established. Ironically, India has one of the largest private health sectors in the world, with over 80 per cent of ambulatory care and 65 per cent of admissions supported through out-of-pocket expenses. The services sector, with around 57 per cent contribution to the GDP, has made rapid strides in the last few years and emerged as the economy’s largest and fastest-growing sector (Ministry of Finance, 2013-2014). India is positioning itself as the world’s medical tourism hub; fast becoming a main choice for healthcare tourists, but is behind established medical tourism locations such as Malaysia,


Singapore and Thailand. Many Indian private hospitals now offer several medical services that have special arrangements for foreign customers. The Indian healthcare industry, growing at a CAGR of 15 per cent is expected to reach US $250 billion by 2020 (PriceWaterhouseCoopers, 2012). Service quality has become an important topic in relationship to profit, cost saving and market share (Devlin and Dong, 1994). Health and economic development are so closely related that it is impossible to achieve one without the other. While the economic development in India has gained momentum over the past few decades, its health system is at a cross-road (Ramani and Dileep, 2006). Research links service quality to customer satisfaction (Taylor and Baker, 1994) and purchaser intentions (Zeithaml et al., 1996). Researchers suggest that customer service quality perception is a key determinant in the healthcare organisation’s success owing to its primary role in achieving patient satisfaction and hospital profitability (Donabedian, 1966). Thus, our main objective is to analyse perceived service quality, customer satisfaction and loyalty in Indian private hospitals. In today’s highly competitive healthcare, public and private organisation managers need to measure their financial and non-financial performance to improve function and increase their competitiveness. Service quality therefore interests service marketing researchers. Superior service quality helps differentiate itself from its competition, gain a sustainable competitive advantage and enhance efficiency. Many empirical studies have investigated the relationships among service quality, customer satisfaction and loyalty in many service sectors. Grönroos (1984) defined service quality as a perceived judgement resulting from an evaluation process where customers compare their service expectations with what they perceive to have received. Dabholkar (1995) suggested that service quality and satisfaction antecedents are situation specific and if a consumer is cognitive oriented then s/he will perceive the relationship as service quality causing satisfaction, whereas if a consumer is affective oriented then s/he will perceive the relationship as satisfaction causing service quality. There is ample evidence that service quality affects perceived value, customer satisfaction and behaviour intentions including word-of-mouth, loyalty, personal recommendation and willingness to pay more (Baker and Crompton, 2000). Literature review Premium service quality enables hospital managers to differentiate the hospital and gain a sustainable competitive advantage and enhance efficiency (Olorunniwo et al., 2006). Grönroos (1984) defined perceived quality as evaluation process, where the consumer compares his/her expectations with his/her service perceptions. Eleuch (2011) showed that health service quality perception is a judgement about whether the service performed for a patient and was the most appropriate to produce the best result that could be reasonably expected by the patient. According to O’Connor et al. (1994), the customer perspective is increasingly being viewed as a meaningful health services quality indicator that represents the most important perspective. According to Aagja and Garg (2010) hospital service quality is the discrepancy between customer perceptions and their expectations about hospitals offering such services. Some studies on patient perception conducted in developing countries show that customers are able to assess and evaluate service structure, process and outcome (Haddad et al., 1998; Andaleeb, 2001; Baltussen et al., 2002). Anbori et al. (2010) and that service quality improvements were required to achieve high-quality services in the private hospitals to

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increase loyalty among patients. Peer and Mpinganjira (2011) found that service quality is an important factor in ensuring patient overall satisfaction and loyalty towards a private medical practice. Jakobsson and Holmberg (2012), indicate that physician- and nurse-provided information supplement each other and both should be targeted to improve service quality. Manimay (2014) suggest that providing effective training to nurses, doctors and support staff on interpersonal skills and effective communication leads to inpatient satisfaction. There is growing evidence that perceived service quality is the most important variable that influences customer perceptions and intention to adopt more services (Zeithaml et al., 1996). According to (Parasuraman et al., 1991) service quality attributes are not expected to be equally important across service industries. Including importance weights in the service quality measurement scales, therefore, is important. Healthcare service quality perception Service quality is generally viewed as an outcome, especially in healthcare. According to Bitner and Hubbert (1994, p. 77) service quality is “the consumer’s overall impression of the relative inferiority/superiority of the organization and its services”. Service quality assessments are not one-dimensional (Choi et al., 2004) and are defined as how well the service meets or exceeds customer expectations on a consistent basis (Parasuraman et al., 1985). Service consistency varies between regions and sectors. Unlike product quality, service quality is hard to define and measure as interrelationships between user expectation and the impact on specific features in service such as intangibility, inseparability, heterogeneity and perishability (Parasuraman et al., 1985; Zeithaml et al., 2006). The Service Quality Gaps Model and SERVQUAL scales proposed by Parasuraman et al. (1985, 1988) are widely accepted tools for measuring service quality (Sohail, 2003; Ladhari, 2008). Hardeep and Madhu (2012) find that perceived quality and loyalty have positive influence on brand equity in healthcare sector. In healthcare, the two tools are also popular for assessing service quality in various categories such as an acute care hospital, independent dental offices, AIDS service agencies, with physicians and nurses and hospitals (Taner and Antony, 2006). Perceived quality is the consumer’s evaluative judgement regarding superior service performance (Zeithaml, 2000). Thus, perceptions provide the basic measurement tool in which individuals evaluate product or service attractiveness and/or desirability. Loyalty Our study’s dependent variable was loyalty, which indicates whether a customer will return or not. Customers frequently develop an attitude towards purchasing based on a prior service experience. They also undergo a cognitive decision-making process about whether to stay with or leave a service (Zeithaml, 2000). Oliver (1997) referred to loyalty as the stated likelihood to engage in a particular behaviour. Loyalty is considered to include a willingness to recommend, revisit and positive word-of-mouth (WOM) intentions. Zeithaml et al. (1996) grouped behavioural intentions into favourable: positive feedback, recommending, remaining loyal and paying more, and unfavourable loyalty as negative feedback, switching to another organisation, complaining to external agencies and doing less business with a company. Positive WOM is proven to be the strongest predictor for shaping future behaviour and attitudes, which includes oral, person-to-person communication between a receiver and a communicator whom the receiver perceives as non-commercial, regarding a brand product or service (Buttle, 1998). Willingness to pay more is the customer’s intention to pay a higher price than


competitors charge for the benefits that the customer currently receives from the service provider. Zeithaml et al. (1996) use willingness to pay as a behavioural proxy for value. A customer who has a stronger bond with a specific provider (e.g. loyal customer) will be willing to pay (WPM) higher prices based on value provided by that provider’s products and services (Bigné et al., 2008). Several studies investigated service quality and satisfaction’s direct effect on loyalty. Findings indicate that service quality and satisfaction has a direct relationship with WOM and WPM (Ladhari, 2009; Hanzaee and Shojaei, 2011) (Figure 1).


Methodology Our major concern is to identify the important parameters affecting private healthcare patients’ service quality perceptions. To determine the healthcare dimensions and their relationships with loyalty, a questionnaire survey was conducted. The questionnaire was finalised using focus group discussion with healthcare users and a detailed discussion with hospital managers. The questionnaire had two parts: first, six questions concerning the respondent’s demography; and second, 55 questions exploring respondents’ perceived service quality, customer satisfaction and loyalty towards service quality in private healthcare. In total, 550 respondents were randomly selected from Bhubaneswar and Hyderabad (Odisha, eastern India and Andhra Pradesh, southern India to collect perceived service quality, customer satisfaction and loyalty data. Out of 550 questionnaires distributed in the private hospitals (110 each); 86.4 per cent responded. The sampling unit was a patient or patient attendant in a private hospital. A five-point Likert scale was used: 5 ¼ strongly agree, 3 ¼ neutral and 1 ¼ strongly disagree (Appendix). Scale development Developing a scale for analysing perceived service quality, customer satisfaction and loyalty involved these steps: perceived service quality, customer satisfaction and loyalty variables or items taken from previous studies (Parasuraman et al., 1988; Boulding et al., 1993; Taylor and Baker, 1994; Youssef et al., 1996; Lam, 1997; Andaleeb, 2001; Sower et al., 2001; Sureshchandar et al., 2002; White and Yu, 2005; Olorunniwo et al., 2006; Bigné et al., 2008; Ramsaran-Fowdar, 2008; Aagja and Garg, 2010). The questionnaire was pre-tested several times to ensure that the format, total questions and sequence were appropriate. During each successive pre-test, feedback was obtained from staff in five private hospitals (Table I).

Customer Loyalty

Perceived Service Quality

Physical Environment, Reliability, Customer Friendly Staff, Communication, Responsiveness, Privacy & Safety, Customer Satisfaction, Loyalty

Customer Satisfaction

Figure 1. Perceived service quality, customer satisfaction and loyalty

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Table I. Demographic characteristics

Variable

Frequency

Gender Male Female

266 209

56 44

Treatment Inpatient Outpatient

224 251

47.16 52.84

Residence Rural Urban

214 261

45.05 54.95

Education Primary level Secondary level Graduates Above post graduation

52 92 155 176

10.95 19.37 32.63 37.05

Hospital visit First visit Repeat visit

172 303

36.21 63.79

22 48 87 229 31 58

4.62 10.11 18.31 48.21 6.54 12.21

Employment status Unemployed House wife Government employee Private employee Self-employed Retired Note: n ¼ 475

%

Data analysis Data were subjected to various statistics such as factor, regression and correlation analyses using SPSS version 20. Cronbach’s α statistic and factor analysis reduce total items. Before the factor analysis, two tests were performed: Bartlett’s sphericity and Kaiser-Meyer-Olkin (KMO) sampling adequacy (Table II). Item reliability was assessed by computing the coefficient α (Cronbach, 1951), which measures the internal consistency. Coefficient α should be above 0.7 (Nunnally, 1978). In our study, Cronbach’s α was 0.91, which indicates good consistency among items (Tables III-V). Factor analysis used the principal component extraction method with varimax rotation. In the initial application, variables were reduced from 58 to 44. In the second application, 44 variables were classified under eight dimensions based on their factor loadings. Factor loadings ⩽0.45 were not considered and were dropped as redundant variables (Table III). Based on the factor analysis, the variables were classified into

Table II. KMO and Bartlett’s test

Kaiser-Meyer-Olkin measure of sampling adequacy Bartlett’s test of sphericity Approx. χ2 df Sig.

0.815 16,164.613 990 0.000


Variable no.

F1

F2

F3

Component F4 F5

V1 0.637 V2 0.628 V3 0.518 V4 0.512 V5 0.502 V6 0.501 V7 0.498 V8 0.481 V9 0.462 V10 0.459 V11 0.451 V12 0.757 V13 0.746 V14 0.628 V15 0.611 V16 0.516 V17 0.502 V18 0.500 V19 0.723 V20 0.714 V21 0.689 V22 0.664 V23 0.504 V24 0.727 V25 0.618 V26 0.605 V27 0.510 V28 0.501 V29 0.493 V30 0.478 V31 V32 V33 V34 V35 V36 V37 V38 V39 V40 V41 V42 V43 V44 Notes: Extraction method: principal component analysis; normalisation. aRotation converged in 16 iterations

F6

F7

F8


0.714 0.623 0.522 0.441 0.778 0.703 0.515 0.502 0.694 0.599 0.573 0.612 0.512 0.500 rotation method: varimax with Kaiser

eight dimensions, which are suitably named as physical environment, reliability, customer friendly staff, communication, responsiveness, privacy and safety, customer satisfaction and customer loyalty. Generally, factor loading represents how much a factor explains a variable. High loading indicates that the factor strongly influences

Table III. Rotated component matrixa

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the variable. A factor loading W 0.7 has a high impact on the variables. Table III indicates that some variables o 0.7 need attention re-grading perceived service quality improvement in Indian private hospital contexts. Results Physical environment Factor 1 refers to physical facilities, infrastructure, hospital functions, medical apparatus, devices and instruments, medical staff appearance, etc. It includes neatness, cleanliness and environmental tranquillity, important for the patient’s health condition. Since a patient has to stay until discharge, to address his/her food and auxiliary service requirements, tangibles – menus and related service is also added to the physical environment. High factor loading, −0.637 (hospital is well equipped with medical equipment), indicates that this factor strongly influences perceived service quality. Reliability Reliability refers to medical personnel’s capability to deliver desired/promised services systematically, accurately and dependably. The reliability criterion resides on issues like speed, registration time and doctor availability in real-time, treatment, effectiveness, medicines, etc. An appropriate diagnosis and adequate nursing time are essential. In this dimension’s high factor loading, −0.757 (hospital staff maintain error-free medical records, fee receipt, etc.), indicates that the factor strongly influences the variable. This variable needs to be properly addressed in the private healthcare sector.

Dimensions

Table IV. Dimensions and variables

Physical environment (X1) Reliability (X2) Customer friendly staff (X3) Communication (X4) Responsiveness (X5) Privacy and safety (X6) Satisfaction (X7) Loyalty (X8)

Dimensions

Table V. Dimension variances

Variables

Physical environment Reliability Customer friendly staff Communication Responsiveness Privacy and safety Customer satisfaction Loyalty

1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 12, 13, 14, 15, 16, 17, 18 19, 20, 21, 22, 23 24, 25, 26, 27, 28, 29, 30 31, 32, 33, 34 35, 36, 37, 38 39, 40, 41 42, 43, 44

Eigenvalue

% Variation

Cumulative %

15.609 3.411 2.468 1.811 1.648 1.400 1.213 1.359

31.816 7.153 6.416 5.024 4.611 3.601 3.211 3.020

31.816 38.969 45.385 50.409 55.020 58.621 61.832 64.852


Customer friendly staff Customer friendly staff refers to employee dedication, customer caring and hard work. It also shows hospital staff’s commitment to providing a friendly environment, superior-quality and compassionate care. This dimension’s high factor loading, −0.723 (provides services at convenient times), indicates that the private hospital staff provide services at customer preferred times. This variable indicates that Indian private hospital staff are more concerned about treatment times. Communication Communication is about keeping customers well informed, acknowledging and listening to their problems in an observant and effective manner. It includes counselling by staff and the reciprocal response (customer friendly language/layman language) involved in the treatment mechanism. Doctors should attempt to understand the patient’s problem or his/her disease and the patient should be able to clearly spell out his/her problem/disease. This is possible through effective two-sided communication. In this dimension, a high factor loading, −0.727 (doctors give adequate information on treatment), indicates that private hospital doctors are communicating to customers using layman language. It helps to increase customer perception and positive behaviour towards private hospitals. Responsiveness Responsiveness aims to develop the technical tools to assess, monitor and raise awareness of how people are treated and the environment in which they are treated when seeking healthcare. It upholds a particular focus on inequitable treatment associated with social status. Responsiveness can be defined as the outcome that can be achieved when institutions and institutional relationships are designed in such a way that they are cognisant and respond appropriately to the universally legitimate expectations. Responsiveness can be viewed from two angles: first, the user is often portrayed as a consumer, with greater responsiveness being perceived as a means to attract consumers; or second, responsiveness is related to safeguarding customer rights to adequate and timely care. In this dimension, a high factor loading, −0.714 (staff are courteous), is the highest factor loading. This variable indicates that service providers are highly responsive, attentive and loyal. Privacy and safety Privacy and safety has been defined as avoiding or reducing to acceptable limits, actual or potential harm from healthcare. Patient safety practices have been defined (Institute of Medicine, 2004), as those that reduce adverse events risk, related to exposure to medical care across diagnoses or conditions. In this dimension, a high factor loading, −0.778 (hospital provides confidential medical treatment), indicated that services are private and safe. Customer satisfaction Customer satisfaction is overall satisfaction that immediately follows a service encounter. Satisfaction is an outcome, which is an evaluation and an emotion-based response to any service. Customer satisfaction’s high factor loading, −0.694 (satisfied with my decision to visit the hospital), indicates that customers feel their



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decision was correct by choosing the particular private hospital, which leads to customer loyalty towards.

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Correlation analysis To find associations between dimensions, a correlation analysis was applied (Table VI). The highest significant positive correlation was between loyalty (X8) and customer satisfaction (X7). A high significant positive correlation is also observed between communication (X4) and loyalty (X8), physical environment (X1) and loyalty (X8), responsiveness (X5) and loyalty (X8). There was no negative correlation between variables. Regression analysis We used a regression analysis to gain a deeper understanding about the relationship between service quality perception, loyalty and Indian private hospital care. Independent variables (X) The proposed seven dimensions are treated as independent variables in the regression equation: physical environment (X1), reliability (X2), customer friendly staff (X3), communication (X4), responsiveness (X5), privacy and safety (X6) and customer satisfaction (X7). Dependent variable (Y) Customer loyalty is treated as a dependent variable. The mathematical representation can be written as follows: Y ¼ b0 þ b1 X 1 þ b2 X 2 þ b3 X 3 þ b4 X 4 þ b5 X 5 þ b6 X 6 þ b7 X 7

(1)

where b0 is constant, it gives the dependent variable a value when all independent variables are zero; b0 is also called an intercept because it determines where the regression line meets the Y-axis; b1, …, b7 are coefficients that represent the estimated change in dependent variable’s mean value for each unit change in independent variable values. Using Table VII and VIII, the regression equation will be: Y ¼ 0:442 þ 0:348X 1 –0:008X 2 þ 0:318X 3 þ 0:149X 4 þ 0:217X 5 – 0:028X 6 þ 0:413X 7 (2) Table IX shows that the relationship between loyalty (Y) and various dimensions (X1, …, X7) are statistically significant (p o 0.05). Also, the adjusted R2 value, 0.711, indicates that the relationship is statistically significant. Five dimensions: physical environment (X1), customer friendly staff (X3), communication (X4), responsiveness (X5) and customer satisfaction (X7) are statistically significant (p o 0.05). Additionally, the physical environment (X1) dimension has the greatest influence on loyalty followed by customer friendly staff (X3), responsiveness (X5) and customer satisfaction (X7). However, two dimensions, reliability (X2), privacy and safety (X6) are not statistically significant, which calls for concrete action from healthcare managers to improve these important areas.

X2

Pearson correlation 1 Sig. (2-tailed) X2 Pearson correlation 0.591** 1 Sig. (2-tailed) 0.000 X3 Pearson correlation 0.425** 0.532** Sig. (2-tailed) 0.000 0.000 X4 Pearson correlation 0.524** 0.484** Sig. (2-tailed) 0.000 0.000 X5 Pearson correlation 0.567** 0.368** Sig. (2-tailed) 0.000 0.000 X6 Pearson correlation 0.405** 0.286** Sig. (2-tailed) 0.000 0.000 X7 Pearson correlation 0.750** 0.553** Sig. (2-tailed) 0.000 0.000 X8 Pearson correlation 0.810** 0.713** Sig. (2-tailed) 0.000 0.000 Note: **Correlation is significant at the 0.01 level (two-tailed)

X1

X1

0.416** 0.000 0.393** 0.000 0.398** 0.000 0.596** 0.000 0.622** 0.000

1

X3

0.467** 0.000 0.363** 0.000 0.623** 0.000 0.598** 0.000

1

X4

0.472** 0.000 0.665** 0.000 0.614** 0.000

1

X5

1

X6

0.439** 0.000 0.472** 0.000


0.419** 0.000

1

X7

1

X8


Table VI. Correlation analysis

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Conclusions We briefly describe Indian private hospital patients’ service quality perceptions from a loyalty perspective. A seven-dimension model, using regression analysis, was developed to analyse customer perceived service quality and loyalty in Indian private hospitals. The result indicates that two dimensions: reliability, and privacy and safety are not contributing significantly towards loyalty. This implies that service providers fail to provide these in healthcare services. Therefore, the insight gained in this study may offer a foundation for future service quality perception and loyalty research. Our research also provides useful recommendations to healthcare service providers for improving their services. However, our research is limited to private hospitals, so our results may not be generalised to all healthcare services. Our small sample may not represent the population, so, in future, research can be conducted with a larger sample to facilitate a robust examination of service quality perception and loyalty. Future studies can also be conducted to identify each dimension’s relative importance. Extending this study can include the service providers’ perspective to understand these issues in private hospitals. Extending this study and model to other sectors are other directions.

Model Table VII. Model summary

1

Model

R 0.835

a

R2

Adjusted R2

SE of the estimate

0.721

0.711

0.34811

Sum of squares

df

1

Table VIII. ANOVAa

Regression 158.925 7 Residual 57.066 468 Total 215.992 474 Note: aDependent variable: loyalty; bsignificant at 0.05 level

Model 1

Table IX. Coefficientsa

Unstandardised coefficients B SE

Mean square

F

Sig.

25.311 0.113

213.125

0.000b

Standardised coefficients β

Constant 0.442 0.119 X1 0.348 0.031 0.412 X2* −0.008 0.029 −0.012 X3 0.318 0.027 0.213 X4 0.149 0.019 0.184 X5 0.217 0.022 0.335 X6* −0.028 0.052 −0.018 X7 0.413 0.021 0.451 Note: aDependent variable: loyalty. *Predictors (Constant), X1, X2, …X7

t

Sig.

3.841 10.915 −0.127 7.918 6.171 7.512 −0.501 9.176

0.000 0.000 0.809 0.000 0.000 0.000 0.690 0.000


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Further reading Liselotte, J. and Leif, H. (2012), “Quality from the patient’s perspective: a one year trial”, International Journal of Health Care Quality Assurance, Vol. 25 No. 3 pp. 177-188.

(See Appendix follows overleaf.)


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Table AI. Questionnaire

Appendix

No.

Variable

V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21 V22 V23 V24 V25 V26 V27 V29 V29 V30 V31 V32 V33 V34 V35 V36 V37 V38 V39 V40 V41 V42 V43 V44 V45 V46 V47

Hospital is well equipped with all necessary medical equipment Physical facilities are visually appealing Staff are neat in appearance Materials related to outpatient services are visually appealing The different departments, divisions and labs are easily recognised Hospital canteen is good Hospital staff and public can be easily differentiated Hospital wards, cabins, corridors and toilets/washrooms are regularly cleaned Hospital provides holistic environment Sufficient visitor waiting rooms The hospital environment, as a whole, generates a favourable impression Hospital staff maintain error-free records (e.g. medical records, fee receipt) Appointment system in the hospital was easy (phone/internet/other type) Gives prompt services to customers Hospital staff are always willing to help Staff are never too busy to respond to customer requests Customers made to feel safe in their interaction with staff The time it took to meet doctor is not too long Provides services at convenient times Staff depends on managers to handle customers Prompt service without appointment Competent in providing accurate service Medical staff that instil confidence in customers Doctors give adequate information on treatment Tests are adequately explained Physicians are willing to listen and answering questions Health condition information/reports are timely Medical staff effectively listening to patient requests/problems Hospital personnel explain the discharge process to the patient and family It was difficult to connect with the doctor Staff are courteous Staff have a warm and caring attitude Doctors and staff handle peak hospital traffic Operating hours are convenient to customers Hospital provides confidentiality Hospital not misusing customers information Hospital located in safe and secured place Customers feel safe in the hospital premises Satisfied with my decision to visit this hospital Choosing this hospital was a wise My experience in the hospital was good I will recommend this private hospital to others If I feels sick, I will go to the same private hospital again Encourage my friends and relatives for treatment in private hospitals Hospital staff give accurate medical bills to customers Hospital staff are able to answer customer questions Sufficient parking is available in the hospital premises

(continued )


No.

Variable

V48 V49 V50 V51 V52 V53 V54 V55 V56 V57 V58

Hospital provide services without delay Doctors are available whenever customers need medical services Hospital staff ask for feedback from the customers after treatment Hospital staff handle their customers gently Hospital maintain error-free services every time Staff perform services right first time Customers feel some risk when doctors treat them Hospital offers all medical services Hospital provides exact and precise service delivery There are sufficient staff available in the hospital Hospital staff properly handle any problem that arise

Corresponding author Rama Koteswara Rao Kondasani can be contacted at: [email protected]

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Table AI.