Abstract
Patient satisfaction is a key indicator of healthcare service quality and an important component in evaluating health system performance, particularly within referral hospitals in low-resource settings like Tanzania. This interdisciplinary study was conducted at Kilimanjaro Christian Medical Centre (KCMC) Referral Hospital to assess outpatient satisfaction using the SERVQUAL framework. A stratified random sampling technique was employed to ensure proportional representation of patients across various outpatient clinics. Within each clinic stratum, participants were selected using simple random sampling. Outpatients were evaluated across five service quality dimensions: tangibility, reliability, responsiveness, assurance, and empathy. Modified Poisson regression analysis was applied to examine associations between patient satisfaction and selected demographic and service-related variables. The results revealed that effective communication with healthcare providers (RR = 1.246, p = 0.008) and the availability of prescribed medications (RR = 1.093, p = 0.009) were significantly associated with higher satisfaction. Conversely, patients aged 46 years and above reported lower satisfaction levels (RR = 0.903, p = 0.002). Additionally, more than half of the respondents expressed dissatisfaction with the waiting time for services. While overall satisfaction with outpatient services was generally positive, the findings underscore the need for targeted improvements, particularly in reducing waiting times. This study highlights the value of integrating robust statistical modeling and service quality frameworks to generate actionable insights for enhancing patient-centered care in sub-Saharan African referral hospitals.
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Published in
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Clinical Medicine Research (Volume 14, Issue 4)
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DOI
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10.11648/j.cmr.20251404.14
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Page(s)
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127-135 |
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Creative Commons
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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.
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Copyright
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Copyright © The Author(s), 2025. Published by Science Publishing Group
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Keywords
Patient Satisfaction, SERVQUAL Framework, Modified Poisson Regression, Outpatient Services
1. Introduction
Patient satisfaction is a crucial component of quality improvement of hospital services and patient safety in healthcare settings
| [1] | Rahimi M, Quality Assessment Methods of Hospital Services from the Viewpoint of Patients Based on Standard Assessment Models in Iran : A Narrative Rev, 2022, 19(3). https://doi.org/10.5812/modernc-122100 |
[1]
. It is also a critical part of healthcare service quality that needs to be occasionally evaluated and improved
| [2] | Yunis NM, Abdullah MZ, Ramdan NF, Alnuaimi HABS, The Impact of Healthcare Service Quality on Patient Satisfaction at University Health Center, Information Management and Business Review (ISSN 2220-3796), 2024, Vol. 16, No. 3(S), pp. 440-451. |
[2]
, to get patients’ perceptions about healthcare services and their overall satisfaction on services offered at healthcare facilities
Patient satisfaction includes aspects of quality care well-defined in the way health professionals traditionally regard it, for example, good clinical management practices, availability of drugs, waiting time and interaction with providers
| [4] | WHO, Workbook 6: Client Satisfaction Evaluations. Geneva: World Health Organization, 2000. |
[4]
. A healthcare setting striving for excellence must recognize that patient satisfaction directly correlates to the quality of care and organizational success
. In a previous study that was conducted in a tertiary hospital in Shenyang, China, by Xintong et al. [
| [5] | Xintong Z, Ta X, Shuying W, Huq KATME, Huiying G, Michiko M, An evaluation of outpatient satisfaction based on the national standard questionnaire: a satisfaction survey conducted in a tertiary hospital in Shenyang, China. Frontiers in Pub. Health, 2024 12(May), 1-11. https://doi.org/10.3389/fpubh.2024.1348426 |
[5]
, doctor communication and environmental factors were identified as key predictors of outpatients' satisfaction. The waiting time, doctor-patient communication, professional services and accessibility for treatment information were shown to be directly and positively correlated with outpatients’ satisfaction in another study that was carried out in Henan province in China
| [6] | Ren W, Sun L, Tarimo CS, Li, Wu J, The situation and influencing factors of outpatient satisfaction in large hospitals: Evidence from Henan province, China. BMC Health Serv. Res, 2021, 21(1), 1-11. https://doi.org/10.1186/s12913-021-06520-2 |
[6]
.
A cross-sectional study with twelve hospitals using the SERVQUAL Model in China revealed a significant gap in patients' perceived service quality between the hospitals due to demographic and personality factors
| [7] | Shi H, Fan M, Zhang H, Ma S, Wang W, Yan Z, Chen Y, Fan H, Bi R, Perceived health-care quality in China: A comparison of second- And third-tier hospitals. Inter. J. Quality Health Care, 2021, 33(1). https://doi.org/10.1093/intqhc/mzab027 |
[7]
. Moreover, demographic characteristics, expectations, and experiences of the patients were found to be the main determinants of patient satisfaction according to the review study by Kalaja
in Albania.
In the context of Africa, patient demographic characteristics that underlie pregnant women’s expectations of healthcare services were the significant determinants of satisfaction in Kenya, Tanzania, and Malawi.
| [9] | Bergh K, Bishu S, Taddese HB, Identifying the determinants of patient satisfaction in the context of antenatal care in Kenya, Tanzania, and Malawi using service provision assessment data. BMC Health Serv. Res, 2022, 22(1), 1-12. https://doi.org/10.1186/s12913-022-08085-0 |
[9]
. Another study by Eshetie et al.
| [10] | Eshetie G, Feleke A, Genetu M, Patient Satisfaction and Associated Factors among Outpatient Health Service Users at Primary Hospitals of North Gondar, Northwest Ethiopia,. Adv. Public Health, 2020. https://doi.org/10.1155/2020/6102938 |
[10]
at primary hospitals of North Gondar, Northwest Ethiopia found that the availability of drugs within the hospitals, patient waiting time at the registration room, waiting time to see a doctor after registration, and consulting on treatment options were statistically associated with patient satisfaction.
In Ethiopia, a study by Utino et al.
| [11] | Utino L, Birhanu B, Getachew N, Ereso BM, Perceived quality of medical services at the outpatient department of public hospitals in Dawro Zone, Southern Ethiopia. BMC Health Serv. Res, 2023, 23(1). https://doi.org/10.1186/s12913-023-09178-0 |
[11]
reported factors like waiting time, availability of prescribed drugs, information on diagnoses, and privacy level were predictors of client-perceived quality, and in addition, tangibility factors were the predominant common factor for client-perceived service quality. Moreover, a study on patient satisfaction with healthcare service delivery in primary healthcare facilities in an arid and semiarid context in Kenya reported that most of the patients were highly satisfied with the hospital service
| [12] | Opanga Y, Barasa, Sydney J, Mwangangi M, Wangalwa G, Musombi E,..., Ndirangu, M, Patient satisfaction with health care service delivery in primary healthcare facilities in an arid and semi-arid context in Kenya, Preprint 2024, https://doi.org/10.21203/rs.3.rs-5051872/v1 |
[12]
.
According to a study conducted in Sudan by Mohamud et al.
| [13] | Mohamud AI, Shire FA, Hussain KS, Mahmoud AN, Taha LO, Assessing Patient Satisfaction with the Service Quality Provided in Community Pharmacies: Khartoum Locality, Sudan. J. YoungPharmacists, 2021, 13(4), 405-410. https://doi.org/10.5530/jyp.2021.13.98 |
[13]
, patients were satisfied with the pharmacist's communication quality, and they were disappointed with the consultation and the service delivery qualities.
In Tanzania, potential dimensions of quality aspects to be considered when providing quality services in healthcare settings. including patient-centeredness, technical competence, access to services, interpersonal relations, the effectiveness of care, equity, efficiency of care, safety, continuity of care, choice of services, physical infrastructures, and amenities. The Ministry of Health urges the healthcare facilities to improve clients' satisfaction by getting clients' feedback through patients' suggestion boxes, staff suggestion boxes, interviews of patients and workers, periodical QIT/WIT meetings, and questionnaires
| [14] | Ministry of Health and Social Welfare, The Tanzania Quality Improvement Framework in Health Care 2011-2016. MoHS, 2011. |
[14]
.
Despite these guidelines, a study by Kamanda et al.
| [15] | Kamanda S, Majaliwa J, Shehe R, Muro F, Njau, B, Pregnant Women's Level of Satisfaction on Quality of Care in Reproductive and Child Health clinic at Huruma Designated District Hospital in Rombo. East Afr Health Res J, 2020; 4(1): 51-57, https://doi.org/10.24248/eahrj.v4i1.621 |
[15]
reported dissatisfaction of women with the quality of services provided and emphasized the need for improving the quality of services in the reproductive and child health clinic at Huruma Designated District Hospital in Rombo District, Kilimanjaro Region. In another previous study that was conducted at Chanika Hospital-Dar es Salaam, patient-centered experiences with healthcare providers had a significant positive impact on maternal satisfaction
| [16] | Jang S, Lee S, Sohn A, Assessing Maternal Satisfaction : Patient-Centered Care, Hospital Environment, and Information-Seeking in Chanika Hospital in Tanzania. J Pers Med, 2024 Apr 25; 14(5): 455. https://doi.org/10.3390/jpm14050455 |
[16]
. Additionally, a study that was carried out at Mnazi-Mmoja dental clinic in Dar es Salaam revealed high satisfaction of patients based on reception, cleanliness in and around the clinic, waiting time, and effectiveness of local anesthesia services
| [17] | Matofari B, Machibya FM, Mtaya-Mlangwa M, Kikwilu EN, Patients' Satisfaction Toward Dental Health Services Offered at Mnazi-Mmoja Dental Clinic in Dar Es Salaam, Tanzania. Oral Health Dental Sci, 2021; 5(2); 1-5. |
[17]
.
Previous scholars considered the SERVQUAL Model as an appropriate assessment tool for patients' satisfaction with hospital services
| [1] | Rahimi M, Quality Assessment Methods of Hospital Services from the Viewpoint of Patients Based on Standard Assessment Models in Iran : A Narrative Rev, 2022, 19(3). https://doi.org/10.5812/modernc-122100 |
| [7] | Shi H, Fan M, Zhang H, Ma S, Wang W, Yan Z, Chen Y, Fan H, Bi R, Perceived health-care quality in China: A comparison of second- And third-tier hospitals. Inter. J. Quality Health Care, 2021, 33(1). https://doi.org/10.1093/intqhc/mzab027 |
| [18] | Zahra Abbas Ziari EQ, Service Quality Assessment of a Referral Hospital in Semnan with SERVQUAL Model and Related Factors: Patient Views. J. Semnan Univ. Med. Sci, 2024, 26. |
[1, 7, 18]
. SERVQUAL Model is a multidimensional instrument designed to measure service quality by capturing respondents' expectations and perceptions along five dimensions of service quality. These include tangibility (the appearance of physical facilities, equipment, personnel and communication materials); reliability (the ability to perform the promised service dependably and accurately), responsiveness (the willingness to help customers and to provide prompt service), empathy (the provision of caring, individualized attention to customer), and assurance (the knowledge and courtesy of employees and their ability to convey trust and confidence)
| [19] | Parasuraman, A, Berry LL, and Zelthami VA, Refinement and reassessment of the SERVQUAL scale, J. Retailing, 1991, 67(4): 420-450. |
[19]
. The present study employed the SERVQUAL Model with five Likert scale items (very satisfied, satisfied, Neutral, dissatisfied, and very dissatisfied) to identify the key determinants of outpatients' satisfaction with the quality of services provided by the Kilimanjaro Christian Medical Centre.
2. Results
2.1. Demographic Characteristics of the Respondents
A total of 316 outpatients were enrolled to fill out the survey questionnaire, hence a response rate of 82.3%. Demographic characteristics of the respondents in terms of their gender, age, occupation, location, frequency of hospital visits, and payment methods have been summarized in
Table 1.
Table 1. Demographic Characteristics of the Respondents (n=316).
Variable | Frequency (%) |
Gender |
Male | 114 (36.1) |
Female | 202 (63.9) |
Age Group (in years) |
18 - 35 | 181 (57.3) |
36 - 45 | 64 (20.3) |
46 - 60 | 27 (8.5) |
> = 61 | 44 (13.9) |
Occupation |
Business | 49 (15.5) |
Employed | 63 (19.9) |
Farmer | 130 (41.1) |
Retired | 12 (3.8) |
Student | 35 (11.1) |
Unemployed | 27 (8.5) |
Region |
Kilimanjaro | 292 (92.4) |
Arusha | 24 (7.6) |
Number of Visits (Days) |
2 - 3 | 155 (49.1) |
4 - 5 | 62 (19.6) |
6 - 7 | 43 (13.6) |
> = 8 | 56 (17.7) |
Mode of Payment |
Cash | 104 (32.9) |
Insurance | 212 (67.1) |
Source: Field Data, (2024)
2.2. The Influence of Demographic Characteristics on Satisfaction Level
The association between patients’ demographic characteristics and overall satisfaction was examined using modified Poisson regression. Four key demographic variables namely gender, age, occupation, and region (patient location), were assessed for their influence on satisfaction levels. Gender did not exhibit a statistically significant association with patient satisfaction.
Female respondents were slightly more likely to report satisfaction than their male counterparts (RR = 1.016; 95% CI: 0.995-1.038; p = 0.140), but this difference was not statistically significant, suggesting that satisfaction levels are generally consistent across genders in the studied population. Age, however, showed a more pronounced effect. Compared to the youngest age group (18-35 years), those aged 36-45 were marginally less likely to report satisfaction (RR = 0.965; 95% CI: 0.929-1.001; p = 0.058), with the result approaching but not reaching statistical significance.
Notably, respondents aged 46 and above were significantly less likely to report satisfaction (RR = 0.903; 95% CI: 0.846-0.963; p = 0.002), indicating that older patients were about 10% less likely to be satisfied with healthcare services. (
Table 2) This may reflect more complex healthcare needs, higher expectations, or accumulated experiences within the health system that shape perceptions more critically among older adults.
Occupational status was not significantly associated with satisfaction. Both employed individuals (RR = 1.011; 95% CI: 0.985-1.038; p = 0.412) and those engaged in business (RR = 1.010; 95% CI: 0.955-1.067; p = 0.735) had similar satisfaction levels compared to unemployed patients. These findings suggest that income-generating status may not directly affect patient perceptions of care quality in this setting. Lastly, regional differences in satisfaction were explored. Patients from Kilimanjaro were slightly less likely to report satisfaction compared to those from Arusha (RR = 0.885; 95% CI: 0.765-1.023; p = 0.098). Although not statistically significant, this borderline result may indicate possible differences in healthcare delivery or patient expectations between regions of residence, warranting further qualitative or stratified analysis.
In summary, among the demographic variables analyzed, age was the only statistically significant predictor of satisfaction, with older patients (46+) reporting lower satisfaction levels. Gender, occupation, and region were not significantly associated with satisfaction, indicating that these characteristics may play a limited role in shaping perceptions of care quality in this population. These findings imply that other factors, such as patient-provider communication or healthcare outcomes, may play a more pivotal role in explaining satisfaction levels.
2.3. Relationship Between SERVQUAL Dimensions and Patients’ Satisfaction Level
The study examined the association between various SERVQUAL dimensions and overall patient satisfaction using risk ratios (RR) with robust standard errors and 95% confidence intervals (CI). The results highlight several key service quality factors that significantly influence patient satisfaction as shown in
Table 2. Patients who expressed satisfaction with the availability of medication were significantly more likely to report overall satisfaction compared to those who were dissatisfied (RR = 1.093; 95% CI: 1.023-1.168; p = 0.009). This finding underscores the critical role of the reliability dimension of the SERVQUAL model, reflecting the healthcare facility’s ability to provide promised services dependably and accurately. Consistent availability of essential medicines appears to be a fundamental determinant of positive patient experience and satisfaction.
Satisfaction with communication from healthcare providers was strongly and positively associated with overall patient satisfaction (RR = 1.246; 95% CI: 1.059-1.467; p = 0.008). Patients satisfied with communication were approximately 25% more likely to be satisfied overall, emphasizing the importance of the assurance and empathy dimensions. Effective communication likely promotes trust, confidence and a sense of being valued by healthcare providers, thereby enhancing patient perceptions of care quality. Interestingly, satisfaction with primary examinations was negatively associated with overall satisfaction (RR = 0.840; 95% CI: 0.737-0.958; p = 0.009). Patients who reported satisfaction with examinations were 16% less likely to report overall satisfaction. This counterintuitive finding may suggest that while patients appreciate the examination process itself, other related factors such as timeliness, clarity of explanation, or follow-up care may negatively influence their overall evaluation of services. This highlights a potential disconnect within the responsiveness dimension, warranting further qualitative investigation to elucidate underlying issues.
Several other dimensions showed positive associations with overall satisfaction, although these did not reach statistical significance. Satisfaction with infrastructures and hospital environments (tangibles dimension) was associated with a modest increase in overall satisfaction (RR = 1.037; 95% CI: 0.942-1.141; p = 0.461). Similarly, satisfaction with diagnosis services (RR = 1.005; 95% CI: 0.887-1.138; p = 0.937), waiting time for services (responsiveness dimension; RR = 1.013; 95% CI: 0.986-1.041; p = 0.344), ease of obtaining medical information (assurance dimension; RR = 1.181; 95% CI: 0.965-1.444; p = 0.106), and consultation with healthcare providers (empathy and assurance dimensions; RR = 1.072; 95% CI: 0.954-1.206; p = 0.243) were all positively but non-significantly associated with patient satisfaction.
In summary, the findings suggest that among the five SERVQUAL dimensions, reliability (as evidenced by medication availability) and the combined assurance and empathy dimensions (represented by communication from healthcare providers) are significant determinants of patient satisfaction in this healthcare setting. Other aspects of service quality related to tangibles, responsiveness, and empathy showed positive trends but did not achieve statistical significance, indicating areas for potential improvement and further research.
The negative association observed with satisfaction on examinations highlights the complex nature of patient satisfaction and the need to explore the nuanced interplay between different service elements.
Table 2. Modified Poison Regression for Factors Associated with the Outpatients’ Satisfaction (n = 316).
Variable | RR | Robust Standard Error | 95%CI | p- value |
Gender | | | | |
Male (Ref) | 1 | | | |
Female | 1.016 | 0.011 | 0.995 - 1.038 | 0.140 |
Age Group | | | | |
18 - 35 (Ref) | 1 | | | |
36 - 45 | 0.965 | 0.018 | 0.929 - 1.001 | 0.058 |
46 + | 0.903 | 0.030 | 0.846 - 0.963 | 0.002* |
Occupation | | | | |
Unemployed (Ref) | 1 | | | |
Employed | 1.011 | 0.014 | 0.985 - 1.038 | 0.412 |
Business | 1.010 | 0.029 | 0.955 - 1.067 | 0.735 |
Region | | | | |
Arusha (Ref) | 1 | | | |
Kilimanjaro | 0.885 | 0.066 | 0.765 - 1.023 | 0.098 |
Visits | | | | |
2 - 3 (Ref) | 1 | | | |
4 - 5 times | 0.955 | 0.024 | 0.909 - 1.002 | 0.062 |
6 + times | 1.024 | 0.023 | 0.979 - 1.070 | 0.297 |
Payment | | | | |
Cash (Ref) | 1 | | | |
Insurance | 0.977 | 0.019 | 0.940 - 1.015 | 0.227 |
Infrastructures and Hospital Environments | | |
Dissatisfied (Ref) | 1 | | | |
Satisfied | 1.037 | 0.050809 | 0.942- 1.141 | 0.461 |
Availability of Medication | | | | |
Dissatisfied (Ref) | 1 | | | |
Satisfied | 1.093 | 0.037 | 1.023- 1.168 | 0.009* |
Primarily Examinations | | | | |
Dissatisfied (Ref) | 1 | | | |
Satisfied | 0.840 | 0.056 | 0.737 - 0.958 | 0.009* |
Diagnosis Services | | | | |
Dissatisfied (Ref) | 1 | | | |
Satisfied | 1.005 | 0.064 | 0.887 - 1.138 | 0.937 |
Waiting Time for Services | | | | |
Dissatisfied (Ref) | 1 | | | |
Satisfied | 1.013 | 0.013 | 0.986 - 1.041 | 0.344 |
Ease of Obtaining Medical Information | | |
Dissatisfied (Ref) | 1 | | | |
Satisfied | 1.181 | 0.121 | 0.965 - 1.444 | 0.106 |
Communication from Healthcare Providers | | |
Dissatisfied (Ref) | 1 | | | |
Satisfied | 1.246 | 0.104 | 1.059 - 1.467 | 0.008* |
Consultation with Healthcare Providers | | |
Dissatisfied (Ref) | 1 | | | |
Satisfied | 1.072 | 0.064 | 0.954 - 1.206 | 0.243 |
2.4. Patients’ Satisfaction During Last Hospital Visit
The analysis of visit timing and satisfaction as shown in
Table 3 reveals that patients’ recollection of satisfaction from previous visits was notably high, with 97.8% (n = 309) reporting being satisfied, compared to only 2.2% (n = 7) who were dissatisfied. In contrast, satisfaction levels during the most recent visit (i.e., the time of data collection) were slightly lower, with 92.4% (n = 292) reporting satisfaction and 7.6% (n = 24) expressing dissatisfaction. This slight decline suggests that while overall long-term experiences with the facility remain positive, there may have been recent service-related issues that affected satisfaction during the latest visit. These findings underscore the importance of maintaining consistent service quality across time to sustain patient satisfaction.
Table 3. Outpatients' satisfaction with the Hospital services (n=316) during last visit.
Visit Timing | Satisfaction |
Satisfied n (%) | Dissatisfied n (%) |
Recalled satisfaction from previous visits | 309 (97.8) | 7 (2.2) |
Last visit (during data collection) | 292 (92.4) | 24 (7.6) |
3. Materials and Methods
3.1. Study Site
Figure 1. Map of Tanzania showing location of the four referral hospitals.
The study was carried out at the Kilimanjaro Christian Medical Centre (KCMC). The Kilimanjaro Christian Medical Centre is one of the four referral hospitals and one of the four Zonal Consultant hospitals in Tanzania (
Figure 1). It is located in the Kilimanjaro region, in the foothills of the snow-capped Mount Kilimanjaro, 8 kilometers from Moshi town center in Moshi Municipality, Tanzania. The hospital is one of the four Zonal Referral Consultant hospitals in Tanzania, owned by the Evangelical Lutheran Church in Tanzania (ELCT). It serves patients from the northern, eastern, and central zones of Tanzania, including Arusha, Kilimanjaro, Tanga, Singida, and Dodoma, with a has a catchment population of 15,000,000 persons. The hospital is operated jointly by the Ministry of Health of the United Republic of Tanzania and the Good Samaritan Foundation (GSF), an ecumenical non-governmental organization.
3.2. Study Design
This study employed a cross-sectional design to collect primary data from 316 outpatients aged 18 years and above; who had visited the KCMC more than once.
3.3. Dependent and Independent Variables
The dependent variable was the patients' satisfaction with binary categories (satisfied and dissatisfied). The questionnaire was developed in English and then translated into Swahili to enable respondents to understand and get familiar with the study without any language barrier.
The independent variables were the social-demographic characteristics (sex, age, occupation, region, number of visits and mode of payment), tangibility (quality and availability of infrastructures, quality of the surrounding environment and the availability of medication), reliability (preliminary examinations and diagnosis services), responsiveness (waiting for time for services and the ease of obtaining medical information), assurance (communication from the staff and skills and expertise of hospital staff), and empathy (consultation with the health care providers).
3.4. Sampling
A stratified random sampling technique was employed to ensure proportional representation of patients across different outpatient clinics, a method recommended for heterogeneous populations to enhance representativeness and reduce sampling bias
| [20] | Tessema M B, Shiferaw, M H, Tesfaye BW, Application of Stratified Sampling Technique for Survey Research: A Systematic Review. J Soc and Admin Sci, 2022, 9(2), 110-119. https://doi.org/10.1453/jsas.v9i2.24953 (Open Access). |
| [21] | Taherdoost H, Sampling Methods in Research Methodology: How to Choose a Sampling Technique for Research. Inter J Acad Resh in Manag, 2021, 10(2), 50-62. |
[20, 21]
. Each clinic was treated as a stratum, and participants were selected using simple random sampling within each stratum to maintain randomness
.
3.5. Data Collection
Data collection was performed using structured questionnaires administered by trained personnel to ensure consistency and accuracy. Patient satisfaction was measured using the SERVQUAL framework, a validated and widely applied tool to assess service quality across five dimensions: tangibility, reliability, responsiveness, assurance and empathy
| [23] | Al-Hawari M., Ward T, Newby L, The impact of SERVQUAL dimensions on patient satisfaction in hospital outpatient clinics. Inter J Health Care Quality Assurance, 2020, 33(4), 245-260. https://doi.org/10.1108/IJHCQA-01-2020-0005 (Open Access). |
| [24] | Chen H, Lee, SM, Application of SERVQUAL model to assess healthcare service quality: A systematic review. Healthcare, 2021, 9(9), 1104. https://www.mdpi.com/2227-9032/9/9/1104 (Open Access). |
[23, 24]
.
3.6. Data Analysis
Data were entered and analyzed using STATA version 17. Descriptive statistics, including frequencies, percentages, means and standard deviations, were computed to summarize demographic characteristics and satisfaction scores across SERVQUAL dimensions.
For inferential analysis, modified Poisson regression with robust error variance was applied to estimate adjusted relative risks (RR) and 95% confidence intervals (CI) for factors associated with patient satisfaction. This method was selected over logistic regression to provide more interpretable risk estimates for common outcomes and reduce bias
| [25] | Zhou X, Wang Y, Zhang X, Advantages of Modified Poisson Regression in Epidemiological Research. FrontiersinPublicHealth, 2020, 8, 589023. https://www.frontiersin.org/articles/10.3389/fpubh.2020.589023/full (Open Access). |
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[25, 26]
. Variables with a p-value < 0.05 were considered statistically significant.
4. Discussion
The present study investigated the relationship between demographic characteristics and perceived service quality dimensions with overall outpatient satisfaction at a Tanzanian healthcare facility. Among the demographic variables, only age was significantly associated with satisfaction. Patients aged 46 years and above were approximately 10% less likely to report satisfaction (RR = 0.903; 95% CI: 0.846-0.963;
p =.002). This finding suggests that older patients may have more complex healthcare needs or higher expectations that are unmet during service delivery. However, this contrasts with findings from other settings. For instance, a recent systematic review reported that older patients often exhibit higher satisfaction levels in outpatient settings, possibly due to increased tolerance or appreciation for healthcare providers
| [27] | Shih Y-T, Zhan, S, Zhou H, Wan, K H, Pollak KI, Association of age and patient satisfaction scores: A systematic review. BMC Health Serv Res, 2023, 23(1), 91. https://doi.org/10.1186/s12913-023-09123-y |
[27]
. In addition, no significant association was found between gender and satisfaction (RR = 1.016;
p =.140), indicating that both male and female patients had comparable satisfaction experiences. This finding is consistent with research in similar low-resource contexts, which found minimal gender-based differences in patient satisfaction
| [28] | Purba FD, Novianti LE, Nurjannah I, Exploring the gender preferences for healthcare providers and their influence on patient satisfaction. Healthcare, 2023, 13(9), 1063. https://doi.org/10.3390/healthcare13091063 |
[28]
. Furthermore, occupation and region of residence did not significantly influence satisfaction levels.
Although patients from Kilimanjaro showed a slightly reduced likelihood of satisfaction compared to those from Arusha (RR = 0.885;
p =.098), this trend was not statistically significant. This may reflect minor regional differences in expectations or healthcare experiences, as suggested by Batbaatar et al. (2022)
| [29] | Batbaatar E, Dorjdagva J, Luvsannyam A, Savino MM, Amenta P, Determinants of patient satisfaction: A systematic review. BMC Health Serv Res, 2022 22(1), 1056. |
[29]
, who noted such variations in sub-Saharan African contexts. In terms of service quality, the availability of medication and communication from healthcare providers were the strongest predictors of satisfaction (
p <.01). These aspects fall under the reliability and empathy/assurance domains of the SERVQUAL model, reinforcing the idea that consistent service delivery and provider-patient interactions are central to patient satisfaction
| [29] | Batbaatar E, Dorjdagva J, Luvsannyam A, Savino MM, Amenta P, Determinants of patient satisfaction: A systematic review. BMC Health Serv Res, 2022 22(1), 1056. |
[29]
.
Effective communication not only builds trust but also improves patients’ understanding and adherence to treatment, which enhances overall satisfaction. Interestingly, satisfaction with primary examinations was negatively associated with overall satisfaction (RR = 0.840; 95% CI: 0.737-0.958; p =.009). This counterintuitive finding may suggest that while patients appreciate the thoroughness of initial examinations, other facets such as explanation of findings, follow-up care or perceived provider competence may be lacking. Such gaps may affect the perceived responsiveness of care, highlighting the need to not only conduct assessments but also communicate them effectively.
Overall, the findings indicate that service-related factors have a greater influence on patient satisfaction than demographic characteristics, with the exception of older age. Therefore, interventions aimed at enhancing patient satisfaction should prioritize strengthening healthcare providers’ communication skills and ensuring the consistent availability of essential medications. These improvements can benefit a broad range of patients regardless of gender, occupation, or region.
5. Limitations
A notable limitation of this study is that it does not account for certain factors such as income level, length of stay, privacy, distance, and means of transport, which in turn may significantly affect patient satisfaction. Moreover, the findings from this study may underrepresent the actual situation regarding satisfaction with other health facilities because of the differences in resource allocation, patient volume, type of hospital, and patient type. It is also worth noting that this study is limited by its cross-sectional design, which precludes causal interpretations.
6. Conclusions
The findings revealed no statistically significant association between patient satisfaction and socio-demographic characteristics such as gender, occupation, region, frequency of visits, and mode of payment. This suggests that satisfaction levels are not strongly influenced by who the patients are but rather by how services are delivered, suggesting that universal improvements in care quality can yield widespread benefits across diverse patient groups. Therefore, it is recommended that hospital management and policymakers shift their focus toward improving structural and process-related aspects of care, such as reducing waiting times, enhancing provider communication, ensuring cleanliness, and delivering patient-centered services.
Future research should incorporate qualitative approaches to explore patients’ subjective experiences and expectations more deeply and expand the scope to include other dimensions of service quality for a comprehensive understanding of satisfaction drivers. There is also a need to integrate qualitative methods to explore nuanced patient expectations, particularly among older populations, and examine how different SERVQUAL dimensions contribute to satisfaction in both rural and urban settings.
Abbreviations
ELCT | Evangelical Lutheran Church in Tanzania |
GSF | Good Samaritan Foundation |
KCMC | Kilimanjaro Christian Medical Centre |
OPD | Outpatient Department |
QIT | Quality Improvement Team |
SPSS | Statistical Package for the Social Sciences |
WHO | World Health Organization |
WIT | Work Improvement Team |
Author Contributions
Abel Enos Lucas: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Supervision, Writing - original draft
Innocent Titus Kamwamwa: Data curation, Investigation, Methodology, Supervision
James Stanley Kimaro: Data curation, Investigation, Methodology, Supervision
Theresia Bonifasi Mkenda: Conceptualization, Data curation, Investigation, Methodology
Rehema Ahmed Mavura: Data curation, Investigation, Methodology
Johnson Jason Matowo: Investigation, Methodology, Supervision, Writing - review & editing
Funding
This study did not receive any funding.
Data Availability Statement
The data is available from the corresponding author upon reasonable request.
Conflicts of Interest
The authors declare no conflicts of interest.
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Cite This Article
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APA Style
Lucas, A. E., Kamwamwa, I. T., Kimaro, J. S., Mkenda, T. B., Mavura, R. A., et al. (2025). Application of Modified Poisson Regression Analysis in Assessing Patients’ Satisfaction: Insights from SERVQUAL Data at KCMC Referral Hospital, Tanzania. Clinical Medicine Research, 14(4), 127-135. https://doi.org/10.11648/j.cmr.20251404.14
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ACS Style
Lucas, A. E.; Kamwamwa, I. T.; Kimaro, J. S.; Mkenda, T. B.; Mavura, R. A., et al. Application of Modified Poisson Regression Analysis in Assessing Patients’ Satisfaction: Insights from SERVQUAL Data at KCMC Referral Hospital, Tanzania. Clin. Med. Res. 2025, 14(4), 127-135. doi: 10.11648/j.cmr.20251404.14
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AMA Style
Lucas AE, Kamwamwa IT, Kimaro JS, Mkenda TB, Mavura RA, et al. Application of Modified Poisson Regression Analysis in Assessing Patients’ Satisfaction: Insights from SERVQUAL Data at KCMC Referral Hospital, Tanzania. Clin Med Res. 2025;14(4):127-135. doi: 10.11648/j.cmr.20251404.14
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@article{10.11648/j.cmr.20251404.14,
author = {Abel Enos Lucas and Innocent Titus Kamwamwa and James Stanley Kimaro and Theresia Bonifasi Mkenda and Rehema Ahmed Mavura and Johnson Jason Matowo},
title = {Application of Modified Poisson Regression Analysis in Assessing Patients’ Satisfaction: Insights from SERVQUAL Data at KCMC Referral Hospital, Tanzania
},
journal = {Clinical Medicine Research},
volume = {14},
number = {4},
pages = {127-135},
doi = {10.11648/j.cmr.20251404.14},
url = {https://doi.org/10.11648/j.cmr.20251404.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cmr.20251404.14},
abstract = {Patient satisfaction is a key indicator of healthcare service quality and an important component in evaluating health system performance, particularly within referral hospitals in low-resource settings like Tanzania. This interdisciplinary study was conducted at Kilimanjaro Christian Medical Centre (KCMC) Referral Hospital to assess outpatient satisfaction using the SERVQUAL framework. A stratified random sampling technique was employed to ensure proportional representation of patients across various outpatient clinics. Within each clinic stratum, participants were selected using simple random sampling. Outpatients were evaluated across five service quality dimensions: tangibility, reliability, responsiveness, assurance, and empathy. Modified Poisson regression analysis was applied to examine associations between patient satisfaction and selected demographic and service-related variables. The results revealed that effective communication with healthcare providers (RR = 1.246, p = 0.008) and the availability of prescribed medications (RR = 1.093, p = 0.009) were significantly associated with higher satisfaction. Conversely, patients aged 46 years and above reported lower satisfaction levels (RR = 0.903, p = 0.002). Additionally, more than half of the respondents expressed dissatisfaction with the waiting time for services. While overall satisfaction with outpatient services was generally positive, the findings underscore the need for targeted improvements, particularly in reducing waiting times. This study highlights the value of integrating robust statistical modeling and service quality frameworks to generate actionable insights for enhancing patient-centered care in sub-Saharan African referral hospitals.},
year = {2025}
}
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|
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-
TY - JOUR
T1 - Application of Modified Poisson Regression Analysis in Assessing Patients’ Satisfaction: Insights from SERVQUAL Data at KCMC Referral Hospital, Tanzania
AU - Abel Enos Lucas
AU - Innocent Titus Kamwamwa
AU - James Stanley Kimaro
AU - Theresia Bonifasi Mkenda
AU - Rehema Ahmed Mavura
AU - Johnson Jason Matowo
Y1 - 2025/08/08
PY - 2025
N1 - https://doi.org/10.11648/j.cmr.20251404.14
DO - 10.11648/j.cmr.20251404.14
T2 - Clinical Medicine Research
JF - Clinical Medicine Research
JO - Clinical Medicine Research
SP - 127
EP - 135
PB - Science Publishing Group
SN - 2326-9057
UR - https://doi.org/10.11648/j.cmr.20251404.14
AB - Patient satisfaction is a key indicator of healthcare service quality and an important component in evaluating health system performance, particularly within referral hospitals in low-resource settings like Tanzania. This interdisciplinary study was conducted at Kilimanjaro Christian Medical Centre (KCMC) Referral Hospital to assess outpatient satisfaction using the SERVQUAL framework. A stratified random sampling technique was employed to ensure proportional representation of patients across various outpatient clinics. Within each clinic stratum, participants were selected using simple random sampling. Outpatients were evaluated across five service quality dimensions: tangibility, reliability, responsiveness, assurance, and empathy. Modified Poisson regression analysis was applied to examine associations between patient satisfaction and selected demographic and service-related variables. The results revealed that effective communication with healthcare providers (RR = 1.246, p = 0.008) and the availability of prescribed medications (RR = 1.093, p = 0.009) were significantly associated with higher satisfaction. Conversely, patients aged 46 years and above reported lower satisfaction levels (RR = 0.903, p = 0.002). Additionally, more than half of the respondents expressed dissatisfaction with the waiting time for services. While overall satisfaction with outpatient services was generally positive, the findings underscore the need for targeted improvements, particularly in reducing waiting times. This study highlights the value of integrating robust statistical modeling and service quality frameworks to generate actionable insights for enhancing patient-centered care in sub-Saharan African referral hospitals.
VL - 14
IS - 4
ER -
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