Examining patient perceptions of service quality in Turkish hospitals: The SERVPERF model

Total Quality Management & Business Excellence ISSN: 1478-3363 (Print) 1478-3371 (Online) Journal homepage: http://www.tandfonline.com/loi/ctqm20 Examining patient perceptions of service quality in Turkish hospitals: The SERVPERF model Mesut Akdere, Mehmet Top & Sabahattin Tekingündüz To cite this article: Mesut Akdere, Mehmet Top & Sabahattin Tekingündüz (2018): Examining patient perceptions of service quality in Turkish hospitals: The SERVPERF model, Total Quality Management & Business Excellence, DOI: 10.1080/14783363.2018.1427501 To link to this article: https://doi.org/10.1080/14783363.2018.1427501 Published online: 21 Jan 2018. Submit your article to this journal Article views: 112 View Crossmark data Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalinformation?journalcode=ctqm20

Total Quality Management, 2018 https://doi.org/10.1080/14783363.2018.1427501 Examining patient perceptions of service quality in Turkish hospitals: The SERVPERF model Mesut Akdere a *, Mehmet Top b and Sabahattin Tekingündüz c a Department of Technology Leadership & Innovation, Purdue University, West Lafayette, IN, USA; b Department of Health Care Management, Faculty of Economics and Administrative Sciences, Hacettepe University, Ankara, Turkey; c Department of Health Care Management, School of Health, Mersin University, Mersin, Turkey Patient perceptions of service quality have become a critical component in measuring quality of care and healthcare services. The SERVPERF model of measurement for customer perception was used to measure hospital service quality in Turkey to study patients perceived level of quality of services offered and to analyze the predictors of service quality in terms of the dimensions and items of the SERVPERF model. The five dimensions considered were tangibles, reliability, responsiveness, empathy, and assurance. Cross-sectional surveys were completed by 972 inpatients to determine perceived quality. Positive and significant relations were identified among the service quality dimensions. The most significant correlation was between reliability and responsiveness. The logistic regression model used indicated that all dimensions of SERVPERF were a significant predictor for high levels of overall service quality. In this study, service quality and its measures were analyzed in a state hospital located in a development priority area in Turkey. The findings indicate all 5 dimensions of SERVPERF model are significantly related to overall service quality as well as the indicators of high service quality. The findings present several measurement implications of service quality in healthcare. The study is limited to the sample from in-inpatient care departments in a single public hospital in Turkey. However, the results of this study provide significant applications for the government procedures in measuring service quality in hospitals. Keywords: hospital service quality; service quality measurement; Turkish hospitals; perceived service quality; SERVPERF Introduction The concept of quality has been transformed from focusing on goods without much emphasis on services to focusing primarily on services and considering the goods received only as components of those services (Dobrzykowski, McFadden, & Vonderembse, 2016; Southard, 2016). This shift demonstrates the growing importance of service quality in service industries including healthcare. As a result, the topic of quality of service as perceived by customers has become a significant issue for healthcare quality. Ghobadian, Speller, and Jones (1994) define service quality as the degree to which offered services meet customer expectations. Parasuraman, Zeithaml, and Berry (1988), similarly, define service quality as the ability of an organisation to meet and exceed customer expectations which is measured by the discrepancy between a customer s expectations for a service offering and the customer s perceptions of the service received. With a growing shift on patientfocus in healthcare, service organizations have begun focusing on customer perceptions *Corresponding author. Email: makdere@purdue.edu 2018 Informa UK Limited, trading as Taylor & Francis Group

2 M. Akdere et al. of service quality because it helps in developing strategies that lead to customer satisfaction (Saravanan & Rao, 2007, p. 437). Turkish hospitals lack a reliable instrument to systematically study customer perceptions of service quality, which hinders their ability to engage in continuous improvement to achieve business excellence. In this study, we examine perceptions of quality of care among patients from in-patient department in a public hospital in Turkey. Initial studies on service quality emerged toward the end of the 1970s (Oliver, 1977). Practitioners and researchers have conducted numerous studies on service quality in the last twenty years (Karl, Peluchette, & McIntyre Hall, 2016; Topp & Chipukuma, 2016). The service quality concept gained more importance with increased competition in the service sector (Burch, Rogers, & Underwood, 1995). High service quality provides the strategic benefits of cost reduction, return on investment, and increased productivity (Gijsenberg, Van Heerde, & Verhoef, 2015). Improving healthcare quality has become an important objective for all health systems and organisations across the world to address the need to improve poor health services, manage costs, and meet increasing patient expectations for quality of care and healthcare services. Existing literature as well as organisational practices in healthcare support the notion of improving hospital quality and patient safety through implementing quality measurement systems (Drotz & Poksinska, 2014; Maria Kristina Gustavsson, 2014; WHO, 2003). Patient expectations and perceptions about the quality of the services delivered by hospitals is an important factor affecting patient outcomes, profitability, effectiveness, and performance. Consequently, measuring services delivered by hospitals operating in today s rapidly transforming and increasingly competitive healthcare industry has become a necessity. In 2015, 1,533 hospitals operated in Turkey, 971 were public with a 166,003 bed capacity, and 562 were privately owned providing 43,645 bed capacity (Turkish Ministry of Health, 2017, p. 93). This suggest a 27.46% increase in the number of hospitals between 2002 and 2015 and a 32.61% increase in the bedding capacity for the same years (p.93). As the number of hospitals as well as their bed capacity significantly increased over a decade, focus on hospital service quality has become even more important. Using the SERVPERF measurement approach, we examine patient perceptions of service quality in a public hospital in Turkey and analyze the predictors of service quality. This is appropriate because the focus was only on hospital quality performance as perceived by patients. Literature review As the emphasis and attention paid to patient expectations of care received increases, healthcare organisations need to add a new dimension of assessment into their quality management processes that would go beyond simply measuring customer satisfaction. The new concept that has emerged is known as service quality. Ghobadian et al. (1994), for example, define service quality as the degree of offered services to meet customer expectations. Similarly, Parasuraman et al. (1988) define service quality as the ability of an organisation to meet and exceed customer expectations. In other words, service quality is the difference or gap between customer expectations and customer perceptions of the services received. Service organisations have begun focusing on customer perceptions of service quality because it helps them develop strategies that lead to customer satisfaction (Saravanan & Rao, 2007). The service quality concept has gained more importance with increased competition in the service sector. The SERVQUAL model developed by Parasuraman, Zeithaml, and Berry (1985, 1988) is the most frequently cited (Smith, Smith, & Clarke, 2007) model of service quality. The

Total Quality Management 3 term Perceived Service Quality is used instead of service quality in the model. Perceived Service Quality is the comparison between the customers service quality expectations and their actual experience with the service. Expectations refer to the requests or desires of customers about the service. Specifically, literature focuses on customer satisfaction, service quality, and factors influencing the buying and using behaviours of consumers/users; however, the SERVQUAL model does not illustrate service gaps (Lee, 2017; Ponsignon, Smart, Williams, & Hall, 2015). With the rapid growth and necessity of hospitals and health care services, it becomes vital to know patient expectations of service delivery s reliability, responsiveness, assurance, and empathy (Solayappan, Jayakrishnan, & Velmani, 2011). The SERVPERF model The SERVQUAL model, which compares customers expectations before and after delivery of the service (Parasuraman et al., 1988) evolved to align itself with the management trend of integrating performance measures. Parasuraman et al. (1985) argued that the position of a consumer s perception of service quality on the continuum depends on the nature of the discrepancy between the expected service (ES) and perceived service (PS) (p. 48). Cronin and Taylor (1992) offered the first theoretical justification for discarding the expectations portion of SERVQUAL and supplementing it with measures of performance. They developed a performance-based measurement instrument namely, SERVPERF to only focus on the service quality perception. The SERVPERF model represents performanceonly measures, or service quality measurements focused only on organisational performance as perceived by consumers rather than focusing on the difference between the consumers perceptions of performance versus their expectations of service quality (Ali, Ali, & Radam, 2010). Furthermore, service quality is measured only through the dimensions of customer perceptions rather than their expectations. Although many empirical studies have been performed to evaluate quality of health services in the Turkish health care system, in terms of SERVPERF, there is little research on service quality in Turkish hospitals especially in underdeveloped regions of Turkey (Akdere, Top, & Tekingündüz, 2016). This study aims to further advance healthcare quality literature in Turkey by investigating the perceived level of quality of services offered to in-patients in a public hospital located in an underdeveloped city. Methods Cronin and Taylor (1992) suggest that while customers have service performance expectations, these expectations do not constitute their perceptions of service quality (p. 57). They conclude that perceived performance is the most appropriate measure of service quality and that the performance minus expectations construct is an inappropriate basis for the measurement of service quality (Cronin & Taylor, 1994, p. 125). The model uses performance perceptions as measures of service quality instead of measuring it by assessing the difference between customer expectations and perceptions of services received. Cronin and Taylor (1994) demonstrated that the SERVPERF model has a better fit (as measured by chi square statistic and the model s adjusted goodness of fit) than SERVQUAL. They further asserted that SERVPERF has greater construct validity based on the review of relevant literature and the fact that SERVPERF measures also exhibit convergent and discriminant validity (p. 129). In this study, we adopted Cronin

4 M. Akdere et al. and Taylor s (1994) SERVPERF model which includes the following perception dimensions (15 items): a) Tangibles: physical facilities, equipment, and appearance of personnel. b) Reliability: the ability to perform the promised service dependably and accurately. c) Responsiveness: the willingness to help customers and provide prompt service. d) Assurance: knowledge and courtesy of employees and their ability to inspire trust and confidence in customers. e) Empathy: caring about others and providing individualised attention to customers. Using the SERVPERF model, this cross-sectional quantitative study measured patients perceptions of service quality in a Turkish hospital and explored implications for healthcare quality in Turkey. Data collection This study surveyed 2,595 inpatients in the only public hospital located in an Eastern province in Turkey. The province is listed as one of the poorest regions in the country, ranking 76th among 81 provinces (Turkish Ministry of Development, 2011). We received 972 usable responses (response rate of 37.45%). Although using a single public hospital may be a limitation, however, the socio-economic background of the hospital patients is critical for exploring potential variation in the perception of service quality based on participant demographics. Furthermore, periodicity among the months was not considered nor were demographic or medical differences of the patients. First, a list of patients to be discharged during the day was obtained from the hospital records. In order to increase the rate of response, surveys were distributed and received in the hospital environment prior to the discharge of the patients. Psychiatry, pediatrics, intensive care unit patients, those with a short length of stay (less than 2 days), unconscious patients, and minors (under the age of 18) were excluded from the study. Instrument We used SERVPERF scale with five-level Likert items (5 = strongly agree, 3 = neither agree nor disagree, 1 = strongly disagree) design to measure patient perceptions of quality of healthcare services. The SERVPERF scale was translated from English into Turkish. A pilot study was conducted to assess whether the translated items of the scale were easy to comprehend by the target population. Participants from a convenience sample of 25 healthcare professionals were asked to complete the instrument and provide feedback on each item. Upon collection of the feedback, a final version of the SERVPERF scale in Turkish was developed. Reliability analysis reported alpha coefficients above 0.7 for each of the five constructs of the scale. Ethical approval The study was approved by the Ethics Review Boards of the hospital and survey was conducted on site. Data analysis In reliability analysis of the scale used in this study, alpha coefficient was calculated as 0.964 for 15 items in the instrument. We also computed reliability scores (Cronbach s

Total Quality Management 5 Alpha) for subscales. All reliability analysis results were illustrated in Table 2. Descriptive statistics were calculated for all dimensions of perceived service quality to provide information about the demographic variables. Correlation and binary logistical regression analysis were conducted to determine relationships among scale items and the dimensions of service quality and to explain the effects of the dimensions of service quality. For the purposes of logistic regression, the perceptions of service quality scores were transformed to 0 or 1. From the overall SERVPERF score, the low or high level of service quality was determined using logistic regression analysis. Therefore, a value of 0 was given if the overall score was between 1.00 and 3.00 indicating a low service quality level. If the overall score was between 3.01 and 5.00, a value of 1 was given, which indicated a high level of service quality. Using the Likert scale of 1 5, the minimum standard measure for service quality was determined to be above 3.0 (Huang & Li, 2010). Results Table 1 illustrates the descriptive statistics on inpatients demographics. 48% of the participants were males while females comprised 52% of the participants. Over 45% of the participants were between the ages of 26 and 47 with an overall mean age of 26.7. Over 65% of the respondents graduated from primary and secondary schools, and 67.7% had a government-sponsored healthcare coverage. Table 2 displays reliability analysis items in the SERVPERF model including means, standard deviations, and reliability scores of dimensions of SERVPERF. According to the analysis of the SERVPERF measure, the highest levels of perception of service quality were associated with hospital medical staff being knowledgeable (4.06 ± 0.995); patients feelings of being safe when interacting with the staff (3.97 ± 1.033); being neat (3.97 ± 1.062); being sympathetic and reassuring (3.94 ± 1.060); being polite (3.94 ± 1.075); and being willing to always help patients (3.93 ± 1.087), respectively. On the other hand, perceptions of the patients regarding the tangibles of the hospital including the hospital s having visually attractive physical facilities (interior and exterior buildings, decor, lighting, furniture, etc.) (2.88 ± 1.355); and the hospital being equipped with modern tools and equipment (2.94 ± 1.351) were ranked as the lowest items. The mean score of the tangibles was the lowest (3.26) among the five perceived service quality constructs while all other items were above average. Overall, SERVPERF mean was calculated at 3.76. The service quality dimensions identified by the patients to be the most important were responsiveness (3.93 ± 0.907); assurance (3.90 ± 0.867); reliability (3.85 ± 0.885); Table 1. Demographics of Participants (n = 972). Characteristics Frequency Percentage (%) Gender Female 506 52.05 Male 466 47.95 Age Under 26 Years Old 246 25.31 26 36 Age Group 265 27.26 37 47 Age Group 179 18.42 Over 47 Years Old 282 29.01 Level of Education Primary + Secondary School 636 65.43 High School or equivalent 244 25.11 College or Graduate School 92 9.46

6 M. Akdere et al. Table 2. Means, Standard Deviations, Reliabilities Items and Dimensions of SERVPERF. Items in Each Dimension Mean Std. Deviation Tangibles (α =.707) 3.26 1.003 P1. The hospital has up-do-date equipment 2.94 1.351 P2. The hospital s physical facilities are visually appealing 2.88 1.355 P3. The hospital s employees appear neat 3.97 1.062 Reliability (α =.758) 3.85.885 P4. The hospital provides its services at the time it promises to do so 3.83 1.085 P5. When patients have problems, the hospital s employees are sympathetic 3.94 1.060 and reassuring P6. The hospital is accurate in its billing 3.79 1.090 Responsiveness (α =.826) 3.93.907 P7. The hospital employees tell patients exactly when services will be 3.96 1.011 performed P8. Patients receive prompt service from the hospital s employees 3.91 1.062 P9. The hospital s employees are always willing to help patients 3.93 1.087 Assurance (α =.819) 3.90.867 PI0. Patients feel safe in their interactions with the hospital s employees 3.97 1.033 PI1. The hospital s employees are knowledgeable 4.06.995 P12. The hospital s employees are polite 3.94 1.075 P13. Employees get adequate support from the hospital to do their jobs well 3.65 1.197 Empathy (α =.756) 3.83 1.046 P14. The hospital s employees give patients personal attention 3.80 1.165 P15. The hospital has patients best interests at heart 3.87 1.171 Overall Scale (α =.964) 3.76.786 empathy (3.83 ± 1.046); and tangibles (3.26 ± 1.003), respectively. In this study, the tangible dimension was found to be of least importance to the patients. Pearson s correlation coefficients for the five dimensions of SERVPERF are listed in Table 3. Significant positive correlations were found in the significance level of 99% among all dimensions. For example, the highest correlations among the variables were the dimensions of assurance and responsiveness (r =.804), which indicates the patients favourably perceive assurance and responsiveness as their measures of service quality in healthcare. This, in turn, would enhance their perceptions of service quality. In addition, there were significant positive relationships between the dimensions of empathy and assurance (r =.765); responsiveness and reliability (r =.729); and, empathy and responsiveness Table 3. Service Quality Correlation Matrix: Dimensions of SERVPERF. Dimensions of SERVPERF Tangibles Reliability Responsiveness Assurance Empathy Overall Service Quality Tangibles r 1 Reliability r.526* 1 Responsiveness r.483*.729* 1 Assurance r.520*.729*.804* 1 Empathy r.493*.671*.707*.765* 1 Overall Service Quality r.725*.861*.880*.912*.842* 1 *Correlation is significant at the 0.01 level (2-tailed).

Total Quality Management 7 Table 4. Predictors (dimensions of SERVPERF) for high or low service quality. Dimensions of SERVPERF β Std. Error. Wald Sig. Exp (β) Tangibles 1.319.243 29.362 <.00001* 3.740 Reliability 1.232.259 22.686 <.00001* 3.428 Responsiveness 1.229.298 16.971 <.00001* 3.417 Assurance 1.867.352 28.181 <.00001* 6.469 Empathy.945.208 20.650 <.00001* 2.573 Constant 19.075 2.025 88.773 <.00001*.000 Model Summary 2 Log likelihood: 222.445 Cox & Snell R Square:.428 Nagelkerke R Square:.785 Omnibus Tests of Model Coefficients Model s Chi-square: 542.410 Sig.(p): 0.000 *Significant predictor at 0.01. (r =.707). The correlations between the other dimensions were of high level. Similarly, there were significant correlations among overall perceived service quality scores of assurance, responsiveness, reliability, empathy and tangibles, respectively. Table 4 lists results of binary logistic regression for high and low overall service quality scores in terms of latent constructs of SERVPERF. The Chi-square test scores of the model indicated that the model is a good fitting model. In the case model, chi-square has a value of 542.410 and a probability of p < 0.0001. Cox & Snell R-Square indicates that 42.8% of the variation in the perception of service quality (high or low) is explained by the logistic model. In our case, Nagelkerke R-Square is 0.785, indicating a moderately strong relationship of 78.5% between the predictors of SERVPERF dimensions and the prediction (of overall service quality score (high or low). This model indicated that all dimensions of SERVPERF were significant predictors of high levels of perceived overall service quality. EXP (B) value indicates that when assurance dimension score is raised by one unit the highest odds ratio is 6.469 times as large. On the other hand, when empathy dimension score is raised by one unit the lowest odds ratio is 6.469 times as large. Thus, this study indicates that all dimensions of SERVPERF are significant predictors for high overall service quality. The results of binary logistic regression for high and low overall service quality scores in terms of the individual items of the SERVPERF model are illustrated in Table 5. The results of the model s Chi-square test reported a good fitting model. In this case, model chi square has a value of 552.471 and a probability of p < 0.0001. Cox & Snell R- Square indicate that 43.4% of the variation in the service quality (high or low) is explained by the logistic model. In our case, Nagelkerke R-Square is 0.796, indicating a moderately strong relationship of 79.6% between the predictors (all items of SERVPERF and the prediction (high or low overall service quality score). This model indicated that nine items of SERVPERF were a significant predictor of high overall service quality. EXP (B) value indicated that when score of P10 patients feelings of being safe when interacting with the staff is raised by one unit the highest odds ratio is 2.195 times as large. On the other hand, EXP (B) value indicated that when score of P12 being polite is raised by one unit the lowest odds ratio is 1.079 times as large in this study. P1, P5, P6, P7, P10, P11, P13, P14, and P15 items of SERVPERF are significant predictors of high levels of

8 M. Akdere et al. Table 5. Predictors (items of SERVPERF) for high or low service quality. Items of SERVPERF β Std. Error Wald Sig. Tangibles P1. The hospital has up-do-date equipment.558.209 7.170.007* 1.748 P2. The hospital s physical facilities are.405.224 3.262.071 1.500 visually appealing P3. The hospital s employees appear neat.356.196 3.301.069 1.428 Reliability P4. The hospital provides its services at the.187.214.759.384 1.205 time it promises to do so P5. When patients have problems, the.455.226 4.050.044* 1.577 hospital s employees are sympathetic and reassuring P6. The hospital is accurate in its billing.652.184 12.535 <.0001* 1.920 Responsiveness P7. The hospital employees tell patients.553.205 7.254.007* 1.738 exactly when services will be performed P8. Patients receive prompt service from the.367.203 3.276.070 1.443 hospital s employees P9. The hospital s employees are always.317.215 2.182.140 1.373 willing to help patients Assurance PI0. Patients feel safe in their interactions with.786.215 13.332 <.00001* 2.195 the hospital s employees PI1. The hospital s employees are.690.226 9.324.002* 1.995 knowledgeable P12. The hospital s employees are polite.076.208.133.715 1.079 P13. Employees get adequate support from the.492.178 7.655.006* 1.636 hospital to do their jobs well Empathy P14. The hospital s employees give patients.508.191 7.118.008* 1.663 personal attention P15. The hospital has patients best interests at.569.175 10.595.001* 1.767 heart Constant 20.183 2.180 85.700 <.00001*.000 Model Summary 2 Log likelihood: 212.384 Cox & Snell R Square:.434 Nagelkerke R Square:.796 Omnibus Tests of Model Coefficients Model s Chi-square: 552.471 Sig.(p): 0.000 Exp (β) overall service quality. However, P2, P3, P4, P8, P9, and P12 are not a significant predictors of high levels of overall service quality in this hospital. Limitations The generalizability of our findings is limited by the study being conducted with only inpatient care departments in one single public hospital in Turkish health system. Furthermore, the cross-sectional research design used in the study does not allow inference about causality, and common method variance may have inflated intercorrelation among

Total Quality Management 9 the items of interest. Future research is needed to use SERVPERF model to compare patient perceptions of quality of care with private hospitals. Discussion In this study, the highest level of perception of the quality of services delivered by the hospital was the staff being knowledgeable sub-variable of the assurance dimension and the lowest was the hospital having visually attractive physical facilities (interior and exterior buildings, decor, lighting, furniture, etc.) sub-variable of the tangibles dimension. Patients found assurance and responsiveness to be the most important service quality dimensions, while the least important dimension was tangibles. Modernisation of hospital equipment, making the service areas and the healthcare devices more visually attractive, and cleanliness and professional presentability of healthcare professional increases patient perceptions of healthcare quality with regards to the dimension of tangibles. The dimension of assurance can be associated with being knowledgeable and polite to create a significant level of confidence in patients, while the dimension of responsiveness can be associated with staff s ability to inform patients when services will be delivered, deliver these services as soon as possible, and their willingness to help the patients. To increase patient perceptions of the dimensions of assurance and responsiveness in healthcare system, patients need to feel psychologically dependent on the ability of healthcare staff to offer services, demonstrate associated knowledge and experience, effectively inform patients in all aspects of their healthcare and well-being, and provide timely service and care to patients. Our findings indicate the five dimensions of SERVPERF are significantly related to overall service quality as well as the indicators of high service quality. Healthcare organisations cannot afford to ignore the needs and expectations of people they serve. It is important for them to engage in continuous measurement and improvement of their service quality as part of their quality management process. SERVPERF is one of the measures to successfully achieve this goal. Conclusion In this study, service quality and its measurement have been analyzed in a public hospital. Our study is an initial investigation into patients perceived service quality using SERV- PERF model and measurement scale. The results of this study can provide a platform for the government healthcare strategies and policies in enhancing and improving the service quality in hospitals located in underdeveloped areas. This paper sheds light on the quality aspect of the Turkish healthcare system while presenting significant results for better understanding patients perceptions of healthcare service quality in underdeveloped regions in the country. The results could help identify healthcare areas where quality management is much more difficult to implement and practice. The findings also provide new insights to the theoretical framework related to customer satisfaction in the areas of vigilance, competence, advancement in services, and reliability as important components of customer satisfaction. Further, our findings provide directions for hospital managers and policymakers to develop strategies and assess future applications which will support enhancing patient perceptions of service quality, improving patient trust, and increasing quality of care and healthcare outcomes. We argue the notion that, although difficult, service quality in healthcare can be measured and consequently be systematically improved in Turkish healthcare organisations. Our findings are robust against the considered quality dimensions of SERVPERF as all 5 dimensions of the scale impact both

10 M. Akdere et al. low and high levels of service quality. We further conclude that all 5 dimensions of SERV- PERF determine perceptions of service quality in healthcare, with assurance being the highest and empathy being the lowest in the impact of service quality perceptions in our study. Implications There is increasing interest in improving service quality as well as quality of care in hospital clinical practice in order to provide high-quality care and achieve better patient outcomes. The findings of the present study could have several managerial implications for service quality enhancement. The empathy dimension of service quality can be strengthened especially by understanding specific out-patient needs and looking out for the out-patients best interests (Yousapronpaiboon & Johnson, 2013; Zarei, Arab, Froushani, Rashidian, & Ghazi Tabatabaei, 2012). Assurance was the strongest predictor of service quality in this study. Thus, staff in Turkish public hospitals can exercise strong influence over perceived quality by having the knowledge to answer patients questions, and by being courteous and friendly at all times to both out-patients and in-patients. Similarly, hospital staff should make patients aware of their medical conditions, answer their questions, recognise and pay attention to their emotional and social needs, and be available when needed. Disclosure statement No potential conflict of interest was reported by the authors. References Akdere, M., Top, M., & Tekingündüz, S. (2016). An empirical examination of patient perceptions on hospital service quality in Turkey: Implications for evidence-based practice. In T. Bentley (Ed.), Refereed proceedings of the 2016 Australian New Zealand academy of management conference. Brisbane. Ali, M. H., Ali, N. A., & Radam, A. (2010). Validating SERVPERF model in government agencies. The Journal of Human Resource and Adult Learning, 6(1), 84 93. Burch, E., Rogers, H. P., & Underwood, J. (1995). Exploring SERVPERF: An empirical investigation of the importance-performance, service quality relationship in the uniform rental industry. Retrieved from http://sbaer.uca.edu/research/swma/1995/pdf/17.pdf Cronin, J. J., & Taylor, S. A. (1992). Measuring service quality: A reexamination and extension. Journal of Marketing, 56(1), 55 68. Cronin, J. J., & Taylor, S. A. (1994). SERVPERF versus SERVQUAL: Reconciling performancebased and perceptions-minus-expectations measurement of service quality. Journal of Marketing, 58(2), 125 131. Dobrzykowski, D. D., McFadden, K. L., & Vonderembse, M. A. (2016). Examining pathways to safety and financial performance in hospitals: A study of lean in professional service operations. Journal of Operations Management, 42 43(1), 39 51. Drotz, E., & Poksinska, B. (2014). Lean in healthcare from employees perspectives. Journal of Health Organization and Management, 28(2), 177 195. Ghobadian, A., Speller, S., & Jones, M. (1994). Service quality concept and models. International Journal of Quality & Reliability Management, 11(9), 43 66. Gijsenberg, M., Van Heerde, H. J., & Verhoef, P. C. (2015). Losses loom longer than gains: Modeling the impact of service crises on perceived service quality over time. Journal of Marketing Research, 52(5), 642 656. Huang, Y., & Li, S. J. (2010). Understanding quality perception gaps among executives, frontline employees, and patients: The outpatient services in Taiwan hospitals. Quality Management in Health Care, 19(2), 173 184.

Total Quality Management 11 Karl, K., Peluchette, J. V. E., & McIntyre Hall, L. (2016). Employee beliefs regarding the impact of unconventional appearance on customers in Mexico and Turkey. Employee Relations, 38(2), 163 181. Lee, D. (2017). HEALTHQUAL: A multi-item scale for assessing healthcare service quality. Service Business, 11(3), 491 516. Maria Kristina Gustavsson, S. (2014). Improvements in neonatal care: Using experience-based codesign. International Journal of Health Care Quality Assurance, 27(5), 427 438. Ministry of Development (2011). Turkish Ministry of Development. I llerin ve Bölgelerin Sosyo- Ekonomik Gelis misļik Sıralaması Arasţırması. (in Turkish). Retrieved on January 3, 2017 from http://www.kalkinma.gov.tr/lists/yaynlar/attachments/548/sege-2016.pdf. Ministry of Health. (2017). Turkish Ministry of Health. T.C. Sag lık Bakanlıgĭ, Sag lık Iṡtatistikleri Yıllıgĭ. Retrieved on November 14, 2017 from https://mail.google.com/mail/u/0/inbox/ 15fa292377cd950b.45. Oliver, R. L. (1977). Effect of expectation and disconfirmation on postexposure product evaluations: An alternative interpretation. Journal of Applied Psychology, 62(4), 480 486. Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49(1), 41 50. Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12 40. Ponsignon, F., Smart, A., Williams, M., & Hall, J. (2015). Healthcare experience quality: An empirical exploration using content analysis techniques. Journal of Service Management, 26(3), 460 485. Saravanan, R., & Rao, K. S. P. (2007). Measurement of service quality from the customer s perspective An empirical study. Total Quality Management & Business Excellence, 18(4), 435 449. Smith, G., Smith, A., & Clarke, A. (2007). Evaluating service quality in universities: A service department perspective. Quality Assurance in Education, 15(3), 334 351. Solayappan, A., Jayakrishnan, J., & Velmani, S. (2011). Quality measurement for hospital services. IPEDR, 12(2), 246 250. Southard, M. (2016). Implementing challenging policy and systems change: Identifying leadership competencies. Human Service Organizations: Management, Leadership & Governance, 40 (1), 1 5. Topp, S. M., & Chipukuma, J. M. (2016). A qualitative study of the role of workplace and interpersonal trust in shaping service quality and responsiveness in Zambian primary health centres. Health Policy & Planning, 31(2), 192 204. WHO. (2003). What are the best strategies for ensuring quality in hospitals? World Health Organization, WHO Regional Office for Europe s Health Evidence Network. Retrieved from http://www.euro.who.int/document/e82995.pdf Yousapronpaiboon, K., & Johnson, J. W. (2013). Out-patient service quality perceptions in private Thai hospitals. International Journal of Business and Social Science, 4(2), 57 66. Zarei, A., Arab, M., Froushani, A., Rashidian, A., & Ghazi Tabatabaei, S. (2012). Service quality of private hospitals: The Iranian patients perspective. BMC Health Services Research, 12(1), 1 7. Zarei, A., Arab, M., Froushani, A., Rashidian, A., & Tabatabaei, S. (2011). DTP. I llerin ve Bölgelerin Sosyo-Ekonomik Gelis misļik Sıralaması Arasţırması. (in Turkish). Retrieved from http://www. kalkinma.gov.tr/lists/yaynlar/attachments/548/sege-2016.pdf Zarei, A., Arab, M., Froushani, A., Rashidian, A., & Tabatabaei, S. (2016). T.C. Sag lık Bakanlıgĭ, Sag lık Iṡtatistikleri Yıllıgĭ. Retrieved from https://mail.google.com/mail/u/0/#inbox/ 15fa292377cd950b.45