| Peer-Reviewed

Satisfaction on Hospital Services in Dhaka Among Heart Disease Patients: A SERVQUAL Modeling Approach

Received: 26 December 2020    Accepted: 7 January 2021    Published: 18 January 2021
Views:       Downloads:
Abstract

Now-a-days, patients’ voice regarding the delivery of health care services is a burning question in the developing countries. It is thought that patients’ perceptions towards health services are mostly ignored in these countries by the health service providers. This study, therefore, seeks the service quality factors which are essential to the patients. A field survey was made in this purpose on the heart disease patients in Dhaka city as this disease is very common in Bangladesh. SERVQUAL modeling approach and principal component analysis were considered to make evaluation over hospital facilities and found, overall, dissatisfaction of the patients. The SERVQUAL model is used to assess patients’ expectations and perceptions regarding service quality in hospitals. Both expectations and perceptions are measured using a 5-point scale to rate their level of agreement or disagreement (1: strongly disagree and 5: strongly agree), on which the higher numbers indicate higher level of expectation or perceptions. Perceptions are based on the actual service they receive in hospitals are based on experiences and information received about hospital stuffs, doctors or overall hospital maintenance system. Service quality scores are obtained from the difference between the expectation and perception scores which range from -4 to +4 (-4: very dissatisfied, +4: very satisfied). The quality score measures the service gap, that is, the degree to which the expectations excels perceptions. Binary logistic regression analysis was used to find out significant covariates for occurring heart disease. Also, a Poisson regression model was performed for detecting potential covariates that affect number of hospital visit (s) per year of the heart disease patients. The study found ultimate dissatisfaction of the patients which brings the thought that a powerful managerial orientation might be launched in the hospitals to ensure quality services.

Published in American Journal of Biomedical and Life Sciences (Volume 9, Issue 1)
DOI 10.11648/j.ajbls.20210901.11
Page(s) 1-9
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Heart Disease, SERVQUAL Modeling, Principal Component Analysis, Binary Logistic Regression, Poisson Regression Model

References
[1] Andaleeb SS. Service quality in public and private hospitals in urban Bangladesh: a comparative study. Health Policy. 2000; 53 (1): 25-37.
[2] Riaz BK, Selim S, Karim MN, Chowdhury KN, Chowdhury SH, Rahman MR. Risk factors of rheumatic heart disease in Bangladesh: a case-control study. Journal of health, population, and nutrition. 2013; 31 (1): 70.
[3] Muhit MA, Rahman MO, Raihan SZ, Asaduzzaman M, Akbar MA, Sharmin N, et al. Cardiovascular disease prevalence and prescription patterns at a tertiary level hospital in Bangladesh. Journal of Applied Pharmaceutical Science. 2012; 2 (3): 8.
[4] Rahman M, Zaman MM, Islam JY, Chowdhury J, Ahsan HN, Rahman R, et al. Prevalence, treatment patterns, and risk factors of hypertension and pre-hypertension among Bangladeshi adults. Journal of human hypertension. 2018; 32 (5): 334-48.
[5] Zaman MM, Choudhury SR, Ahmed J, Khandaker RK, Rouf MA, Malik A. Salt intake in an adult population of Bangladesh. Global heart. 2017; 12 (3): 265.
[6] Chowdhury MZI, Haque MA, Farhana Z, Anik AM, Chowdhury AH, Haque SM, et al. Prevalence of cardiovascular disease among Bangladeshi adult population: a systematic review and meta-analysis of the studies. Vascular health and risk management. 2018; 14: 165.
[7] Zeileis A, Hothorn T. Diagnostic checking in regression relationships. 2002.
[8] Draper NR, Smith H. Applied regression analysis: John Wiley & Sons; 1998.
[9] Fahrmeir L, Kneib T, Lang S, Marx B. Regression models. Regression: Springer; 2013. p. 21-72.
[10] Montgomery DC, Peck EA, Vining GG. Introduction to linear regression analysis: John Wiley & Sons; 2012.
[11] Saber AY, Alam AR, editors. Short term load forecasting using multiple linear regression for big data. 2017 IEEE Symposium Series on Computational Intelligence (SSCI); 2017: IEEE.
[12] Sarkar S, Midi H. Importance of assessing the model adequacy of binary logistic regression. Journal of Applied Sciences. 2010; 10 (6): 479-86.
[13] Myung IJ. Tutorial on maximum likelihood estimation. Journal of mathematical Psychology. 2003; 47 (1): 90-100.
[14] Albert A, Anderson JA. On the existence of maximum likelihood estimates in logistic regression models. Biometrika. 1984; 71 (1): 1-10.
[15] Buttle F. SERVQUAL: review, critique, research agenda. European Journal of marketing. 1996.
[16] Oh H, Parks SC. Customer satisfaction and service quality: a critical review of the literature and research implications for the hospitality industry. Hospitality Research Journal. 1996; 20 (3): 35-64.
[17] Cronin Jr JJ, Taylor SA. Measuring service quality: a reexamination and extension. Journal of marketing. 1992; 56 (3): 55-68.
[18] Carman JM. Consumer perceptions of service quality: an assessment of T. Journal of retailing. 1990; 66 (1): 33.
[19] Andaleeb SS, Basu AK. Technical complexity and consumer knowledge as moderators of service quality evaluation in the automobile service industry. Journal of retailing. 1994; 70 (4): 367-81.
[20] Reidenbach RE, Sandifer-Smallwood B. Exploring perceptions of hospital operations by a modified SERVQUAL approach. Marketing Health Services. 1990; 10 (4): 47.
[21] Wold S, Esbensen K, Geladi P. Principal component analysis. Chemometrics and intelligent laboratory systems. 1987; 2 (1-3): 37-52.
[22] Thomaz CE, Giraldi GA. A new ranking method for principal components analysis and its application to face image analysis. Image and Vision Computing. 2010; 28 (6): 902-13.
[23] Berk R, MacDonald JM. Overdispersion and Poisson regression. Journal of Quantitative Criminology. 2008; 24 (3): 269-84.
[24] Dietz E, Böhning D. On estimation of the Poisson parameter in zero-modified Poisson models. Computational Statistics & Data Analysis. 2000; 34 (4): 441-59.
[25] Parasuraman A, Zeithaml VA, Berry LL. A conceptual model of service quality and its implications for future research. Journal of marketing. 1985; 49 (4): 41-50.
Cite This Article
  • APA Style

    Mohammad Ahsan Uddin, Safiullah. (2021). Satisfaction on Hospital Services in Dhaka Among Heart Disease Patients: A SERVQUAL Modeling Approach. American Journal of Biomedical and Life Sciences, 9(1), 1-9. https://doi.org/10.11648/j.ajbls.20210901.11

    Copy | Download

    ACS Style

    Mohammad Ahsan Uddin; Safiullah. Satisfaction on Hospital Services in Dhaka Among Heart Disease Patients: A SERVQUAL Modeling Approach. Am. J. Biomed. Life Sci. 2021, 9(1), 1-9. doi: 10.11648/j.ajbls.20210901.11

    Copy | Download

    AMA Style

    Mohammad Ahsan Uddin, Safiullah. Satisfaction on Hospital Services in Dhaka Among Heart Disease Patients: A SERVQUAL Modeling Approach. Am J Biomed Life Sci. 2021;9(1):1-9. doi: 10.11648/j.ajbls.20210901.11

    Copy | Download

  • @article{10.11648/j.ajbls.20210901.11,
      author = {Mohammad Ahsan Uddin and Safiullah},
      title = {Satisfaction on Hospital Services in Dhaka Among Heart Disease Patients: A SERVQUAL Modeling Approach},
      journal = {American Journal of Biomedical and Life Sciences},
      volume = {9},
      number = {1},
      pages = {1-9},
      doi = {10.11648/j.ajbls.20210901.11},
      url = {https://doi.org/10.11648/j.ajbls.20210901.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajbls.20210901.11},
      abstract = {Now-a-days, patients’ voice regarding the delivery of health care services is a burning question in the developing countries. It is thought that patients’ perceptions towards health services are mostly ignored in these countries by the health service providers. This study, therefore, seeks the service quality factors which are essential to the patients. A field survey was made in this purpose on the heart disease patients in Dhaka city as this disease is very common in Bangladesh. SERVQUAL modeling approach and principal component analysis were considered to make evaluation over hospital facilities and found, overall, dissatisfaction of the patients. The SERVQUAL model is used to assess patients’ expectations and perceptions regarding service quality in hospitals. Both expectations and perceptions are measured using a 5-point scale to rate their level of agreement or disagreement (1: strongly disagree and 5: strongly agree), on which the higher numbers indicate higher level of expectation or perceptions. Perceptions are based on the actual service they receive in hospitals are based on experiences and information received about hospital stuffs, doctors or overall hospital maintenance system. Service quality scores are obtained from the difference between the expectation and perception scores which range from -4 to +4 (-4: very dissatisfied, +4: very satisfied). The quality score measures the service gap, that is, the degree to which the expectations excels perceptions. Binary logistic regression analysis was used to find out significant covariates for occurring heart disease. Also, a Poisson regression model was performed for detecting potential covariates that affect number of hospital visit (s) per year of the heart disease patients. The study found ultimate dissatisfaction of the patients which brings the thought that a powerful managerial orientation might be launched in the hospitals to ensure quality services.},
     year = {2021}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Satisfaction on Hospital Services in Dhaka Among Heart Disease Patients: A SERVQUAL Modeling Approach
    AU  - Mohammad Ahsan Uddin
    AU  - Safiullah
    Y1  - 2021/01/18
    PY  - 2021
    N1  - https://doi.org/10.11648/j.ajbls.20210901.11
    DO  - 10.11648/j.ajbls.20210901.11
    T2  - American Journal of Biomedical and Life Sciences
    JF  - American Journal of Biomedical and Life Sciences
    JO  - American Journal of Biomedical and Life Sciences
    SP  - 1
    EP  - 9
    PB  - Science Publishing Group
    SN  - 2330-880X
    UR  - https://doi.org/10.11648/j.ajbls.20210901.11
    AB  - Now-a-days, patients’ voice regarding the delivery of health care services is a burning question in the developing countries. It is thought that patients’ perceptions towards health services are mostly ignored in these countries by the health service providers. This study, therefore, seeks the service quality factors which are essential to the patients. A field survey was made in this purpose on the heart disease patients in Dhaka city as this disease is very common in Bangladesh. SERVQUAL modeling approach and principal component analysis were considered to make evaluation over hospital facilities and found, overall, dissatisfaction of the patients. The SERVQUAL model is used to assess patients’ expectations and perceptions regarding service quality in hospitals. Both expectations and perceptions are measured using a 5-point scale to rate their level of agreement or disagreement (1: strongly disagree and 5: strongly agree), on which the higher numbers indicate higher level of expectation or perceptions. Perceptions are based on the actual service they receive in hospitals are based on experiences and information received about hospital stuffs, doctors or overall hospital maintenance system. Service quality scores are obtained from the difference between the expectation and perception scores which range from -4 to +4 (-4: very dissatisfied, +4: very satisfied). The quality score measures the service gap, that is, the degree to which the expectations excels perceptions. Binary logistic regression analysis was used to find out significant covariates for occurring heart disease. Also, a Poisson regression model was performed for detecting potential covariates that affect number of hospital visit (s) per year of the heart disease patients. The study found ultimate dissatisfaction of the patients which brings the thought that a powerful managerial orientation might be launched in the hospitals to ensure quality services.
    VL  - 9
    IS  - 1
    ER  - 

    Copy | Download

Author Information
  • Department of Statistics, University of Dhaka, Dhaka, Bangladesh

  • Abdul Malek Ukil Medical College & Hospital, Noakhali, Bangladesh

  • Sections