An investigation of the quality of Syrian health insurance services via the SERVQUAL approach: a cross-sectional study

Abstract

Background

The provision of quality healthcare is a global priority, particularly for countries like Syria, which has recently emerged from a devastating war. Many countries, including Syria, have implemented health insurance systems that aimed to reduce government health expenditure and improve access to healthcare services. This study aims to investigate the quality of health insurance services in Syria from the perspective of customers and to identify areas for improvement.

Methods

We conducted a cross-sectional study utilizing the SERVQUAL metric, evaluates service quality across five dimensions: attitude, safety, efficiency, reliability and trustworthiness, and responsiveness. Data were collected through an online questionnaire targeting Syrian residents who have utilized health insurance services.

Results

A total of 284 participants were enrolled in the study, comprising 134 females and 150 males. The findings indicated that the quality of health insurance services in Syria is perceived as average or below average across all SERVQUAL dimensions. Notably, respondents expressed significant concerns regarding the attitude of medical staff, rating it well below average, while safety, reliability and trustworthiness were perceived as average.

Conclusion

Insured patients felt mistreated by healthcare providers compared to those who pay-out-of pocket. This perception is exacerbated by the limited coverage and long waiting times for approval. It is recommended that the Insurance Supervisory Commission, as the regulator of insurance sector, closely monitor the quality of services provided by health insurance companies to ensure that these services are respectful, responsive and readily available. Furthermore, health insurance companies should leverage digital technologies and artificial intelligence to enhance customers experience and improve service quality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12962-025-00691-z.

Background

The provision of efficient and effective healthcare is a global priority, emphasised by the United Nations’ Sustainable Development Goals (SDGs), particularly the third goal, which focuses on insuring good health and well-being. This goal necessitates access to quality health services while minimizing financial burdens for all individuals. However, current tracking of indicators related to financial risk protection and user satisfaction with the health system is lacking [1]. According to World bank statistics, the number of people globally living in poverty or further impoverished at the relative poverty line increased by an average of 31 million per year from 2000 to 2019, reaching 1.3 billion in 2019 [2].

In many countries, financial barriers significantly hinder access to necessary healthcare, leading individuals to forgo care or accept substandard services [2]. Various health insurance schemes have been implemented to address these barriers. The absence or inadequacy of health insurance exposes individuals to catastrophic health consequences, while excessive healthcare spending exacerbates poverty and widens socioeconomic inequalities, particularly regarding access to high-quality healthcare services [3]. Research indicates that patients with lower socioeconomic status experience significantly lower health-related quality of life at the onset of their illnesses and following treatment [4].

Arab countries have adopted various health financing schemes. Historically, most Arab countries implemented universal health coverage, primarily following Beveridge model, which funds health services through taxation and government revenues [5, 6]. However, financial pressures have compelled many, including affluent oil-rich countries like Saudi Arabia, to transition to Bismarck model, where health services are funded through private health insurance companies, with contributions from employers, employees, and sometimes governments [6].

Syria, classified as a low-income country, had a human development index of 0.564 in 2023, significantly lower than the Arab average states of 0.719 [7]. The Syrian healthcare system is complex and has long been severely impacted by ongoing political and economic instability. Wartime conditions have led to a decline in healthcare quality, resulting in fragile health infrastructure and shortages of personnel and resources [8–10]. As of 2023, the system relies heavily on out-of-pocket (OOP) payments, with less than 5% of the population insured [11]. Since 2011, government health expenditures have sharply decreased [12], increasing reliance on OOP payments a common issue in many low- and middle-income countries [13–18]. In fact, OOP payments account for almost 50% of healthcare financing in low-income countries [19]. Countries in the MENA regions generally experience low health expenditures, with Gulf Cooperation Council (GCC) countries showing better health indicators compared to non-GCC countries [20]. According to World Bank statistics from 2022, Syria’s health expenditure per capita is the lowest in the region, at only $34.36, compared to $254.26 in Iraq, $295.14 in Jordan, and $392.28 in Lebanon [21]. This contrast highlights the challenges faced by the Syria healthcare system.

The government’s tax-based health system consists of public hospitals and primary healthcare centres, which are meant to be the first point of contact for healthcare access. However, underfunding these centres, combined with shortages of trained medical staff and an inefficient referral system, forces patients to bypass them and choose either pay out-of-pocket for treatments in private clinics or visit overcrowded public hospitals [22]. Although public hospitals are theoretically accessible, they suffer from regional disparities, long waiting times, and inconsistent service availability, which often deter patients from seeking care [23].

Historically, the landscape of health insurance in Syria has been marked by limited coverage and quality challenges. The introduction of private health insurance in 2006 represented a significant shift; however, its adoption remained modest, with compulsory car insurance dominating the market [24]. Legislative Decree No. 65, enacted in 2009, mandated health insurance through private companies for public sector employees [25]. This led to a remarkable year-on-year growth of 424.68% in health insurance policies in 2010 [26].

Nevertheless, this transition indicated a withdrawal of government for healthcare funding, effectively transferring costs to individuals and outsourcing the service to private sector [27]. The coverage of health insurance policies differs significantly between those offered to private sector employees and those available to public sector employees. For public sector employees, the insurance coverage is centrally negotiated by the government and capped at approximately $75 for out-patient services in 2024. This coverage includes three doctor visits, three prescriptions, three lab tests, three x-rays, each with varying co-insurance contributions. In terms of inpatient coverage, costs range from approximately $500 for private hospital to $1000 for public hospitals, again with varying co-insurance contributions. Notably, these insurance policies do not cover dental treatment or eye-glasses. In contrast, private sector employees typically have more comprehensive coverage, which varies according to the specific rules of their insurance policies. These policies often feature zero co-contributions and generally include dental treatment and one pair of glasses per year [26]

The Syrian health insurance ecosystem consists of various entities, including insurance companies, third party administrators (TPAs), reinsurance companies, intermediaries, medical service providers (such as hospitals, doctors, health centres, and pharmacies), and insurers. TPAs act as intermediaries between the insurers and insurance companies, often representing multiple providers. They maintain a network of medical service providers to manage health insurance services and process claims on behalf of the insurance companies. Additionally, TPAs oversee and regulate medical procedures to insure compliance with insurance policies, scrutinizing all treatments and procedures required by patients.

The Syrian conflict, which began in 2011, has profoundly affected the healthcare system, resulting in a significant decline in government resources and the deterioration of public health facilities [9]. Despite an increase in the number of insured individuals, which reached approximately 908,000 in 2022 [11], this still accounts for less than 5% of the total population [28]. Criticism regarding the coverage and quality of health insurance services has intensified, with many insured patients opting to pay out-of-pocket for treatments due to dissatisfaction with their insurance coverage [9].

The quality of healthcare services in Syria has raised significant concerns, particularly amid the post-conflict situation. Research indicates that the healthcare system suffers from fragmentation, politicization, and workforce shortages, which negatively impact service delivery and patient outcomes [29, 30]. The reliance on OOP payments has created disparities in access to care; wealthier individuals often afford superior services while poorer populations remain vulnerable [30]. This financial strain has led to increased instances of self-medication and unsupervised drug use, further complicating health outcomes [31, 32].

The reported high levels of health coverage in Syria, at 64% in 2021 [11], obscure the poor state and availability of health facilities, staff and medications. While the poor and needy are de jure permitted to receive health services, they are often let down by the quality of care provided [5]. These findings underscore the urgent need to comprehensive reforms to enhance the quality and accessibility of healthcare services in Syria, particularly during the post-conflict recovery phase. The lack of cohesive health policy, coupled with ongoing instability, complicates the implementation of necessary reforms.

A decade after the onset of the war and nearly two decades since the establishment of private health insurance companies, criticism regarding the coverage and quality of health insurance services has intensified. Many well-off patients, despite having health insurance policies, choose to forgo these services and pay for their own treatment [9]. Consequently, numerous insured patients have reverted to out-of-pocket payments for healthcare, including medications and uncovered lab tests [30]. Insurance companies, in turn, have faced significant losses due to the high volume of claims, with a claim rate of 1.4 claim rate in 2023 [11]. This financial strain raises concerns about the sustainability of health insurance in Syria.

The SERVQUAL metric is a widely recognised framework for assessing service quality based on customer perceptions. Originally developed with two dimensions-technical and functional quality-it has evolved into a five-dimensional model that measures the gap between customer expectations and perceptions of service quality [33–35]. SERVQUAL metric has been widely used to evaluate service quality in a variety of sectors, including healthcare, higher education, and banking [36–38]. It has also been used and examined to evaluate the quality of health insurance service in a number of countries [6, 39–41]. This paper aims to utilize the SERVQUAL metric to evaluate the quality of health insurance system in Syria, addressing concerns raised by Seidman [1]. The evaluation will involve conducting factor analysis to illustrate the individual viability of each of the five SERVQUAL dimensions, thereby providing insights that can inform policy reforms and enhance healthcare delivery in the context of Syria’s post-conflict recovery efforts.

This study is novel for two key reasons. First, it measures the quality of health insurance services under post-war conditions, offering valuable insights and lessons for health administrators in liberalized Syria and for other countries emerging from conflict. Second, it provides an evaluation of the existing health system, highlighting its strengths and weaknesses, which may guide future reforms and improvements.

Methods

Study design and settings

The quality of health insurance in Syria was assessed utilizing a five-dimensional SERVQUAL scale. Each dimension included at least three items meeting minimum criteria [42]. Specified dimensions along with their corresponding items as follows: 1. Attitude (3 items; A1, A2, A3), that assesses the demeanour and behaviour of the service staff towards patients, including their professionalism and courtesy. 2. Safety (3 items; S1, S2, S3), that evaluates the perceived safety of the services provided, focusing on whether patients feel secure regarding health risks when utilizing health insurance. 3. Efficiency (4 items; E1, E2, E3, E4), that measures the effectiveness and timeliness of the services, including how well the healthcare system meets patient needs and expectations 4. Reliability and Trustworthiness (4 items; T1, T2, T3, T4), that measures the effectiveness and timeliness of the services, including how well the healthcare system meets patient needs and expectations. 5. Responsiveness (4 items; R1, R2, R3, R4), that looks at how promptly and effectively service providers respond to patient inquiries and needs, including waiting times and the efficiency of communication.

The original SERVQUAL metric includes five dimensions: tangibility, reliability, responsiveness, assurance, and empathy. The model in this study was modified to fit the field of health insurance quality, based on previous modifications in the literature. The “empathy” dimension was replaced by the “attitude” dimension to more accurately reflect the behavioural aspects of the interaction of medical personnel with the insured [43, 44] The dimensions “safety” and “efficiency” were also added to capture patients’ concerns regarding medical risks and speed of completion of insurance transactions, consistent with modifications made to the model in previous studies in the field of healthcare insurance services [45, 46].

Each of these dimensions is critical for understanding the overall quality of health insurance services from the perspective of insured patients. The study utilized a cross-sectional design to gather data through an internet-based questionnaire. Responses were collected from November 2022 to September 2023. The Google platform was used for data collection. To avoid multiple submissions, limit to one response feature was applied and the link to submit another response was not shown. Additionally, participants should log in Google account in order to access the questionnaire.

Participants

The study population encompassed health insurance policy holders who reside in Syria. Due to data protection laws and restrictions imposed by insurance companies, sharing data on customers with third parties are prohibited. Hence, the convenience sampling method was employed as it provides a practical and cost-effective approach under these constraints. Moreover, we could not apply probability-based sampling methods like random or stratified sampling due to this data protection. Hence, convenience sampling is deemed the most feasible option to conduct the study given the circumstances despite concerns on reduced generalizability.

The questionnaire was published online via Facebook and WhatsApp. The study’s purpose, along with its voluntary and confidential nature, was clearly outlined in the questionnaire. All participants provided informed consent to participate in the study. They were instructed to read the questions carefully and respond honestly and objectively regarding their past experiences with their insurance companies. Responses were revised regularly; responses from individuals who do not live in Syria were excluded from the study.

The sample size was calculated using the following equation of large sample population:

Where z is the confidence level and is set to equal 0.90, p stands for the expected prevalence and is set to 50%, and d is the error margin and it equals to 5%. The sample size should be 274 respondents and we reached 284 respondents which exceeded the required sample size.

Questionnaire

The study developed a questionnaire and evaluated the data based on the SERVQUAL from previous research [34]. To create a reliable and valid service quality measurement scale, the study incorporated additional dimensions adopted from [47, 48], which are detailed in Supplementary file 1. Before launching the full survey, the responses from twenty participants were carefully reviewed, and their feedback was implemented accordingly. Adjustments based on this pilot feedback were made to enhance the reliability of the final survey. The questionnaire consists of three sections; the first section gathers demographic information, while the second section includes items corresponding to each dimension. All items in the second section were measured using a 5-point Likert scale, where five indicated “strongly agree” and one indicates “strongly disagree”. In the third section, the respondents were invited to comment on their experience with health insurance services in Syria.

This study was approved by the Faculty of Business Administration Research Ethics Committee (approval no. AIU5525). Informed consent was obtained from the respondents, and they were all given voluntary opportunities to participate in this study. The participants were informed about the purpose of the study and assured that the data collection was completely anonymous.

Statistical analysis

We conducted a pilot study on 50 health insurance policyholders. The language validity of the SERVQUAL scales was assessed, and the scales were prepared for factor analysis. Confirmatory Factor Analysis (CFA) was used to verify the factor structure, and Cronbach’s alpha measured the internal consistency of the factors. A sample t-test was conducted to determine whether the mean scores significantly differed from 3. All the statistical analyses were performed using IBM SPSS 24 for Windows.

Results

A total of 284 participants completed the survey questionnaire. Table 1 illustrates the demographic characteristics of the respondents according to sex, age, monthly income and health insurance coverage. The study sample is almost balanced in terms of gender, with females accounting for 47.2% and males accounting for 52.8% of the sample. The respondents aged 30 to less than 40 years constitute 35.2% of the sample. The participation rates of young (younger than 20 years) and elderly (older than 60 years) individuals are modest at 8.1% and 3.1%, respectively.

Table 1.

Demographic characteristics of participants (gender, age, monthly income, health insurance coverage, and the number of participants

Characteristics		Number of participants	(%)
Gender	Female	134	47.2
	Male	150	52.8
Age-group (years)	Below 20	23	8.1
	20-less than 30	72	25.4
	30-less than 40	100	35.2
	40-less than 50	52	18.3
	50-less than 60	28	9.9
	60 and above	9	3.1
Monthly income (Syrian Pound)	Less than 200,000	46	16.2
	200,000–499,999	86	30.3
	500,000–999,999	64	22.5
	1,000,000–1,999,999	50	17.6
	2,000,000–3,999,999	23	8.1
	4,000,000 and above	15	5.3
Health Insurance Coverage	Currently Uncovered	18	6.3
	25%	29	10.2
	50%	25	8.8
	75%	40	14.1
	100%	157	55.3
	Others	15	5.3

Table 1 also shows that the distribution of health insurance coverage indicates that 55.3% of the respondents have full coverage, whereas only 6.3% are currently uncovered. The two lowest monthly income categories represent the majority of insured respondents, approximately 46.5%. These two categories contain people who are below the poverty line set by the World Bank [50] and indicate that little income is left for healthcare, with the majority of income spent on basic products and services.

Table 2 presents the five constructs of SERVQUAL together with their 18 items. CFA was used to illustrate the individual viability of each item, the factor loadings and the variance explained by each construct.

Table 2.

Exploratory factor analysis and reliability tests of SERVQUAL dimensions

Item		Factor loading					Variance Explained	Eigenvalue	Cronbach’s alpha
		F1	F2	F3	F4	F5
Attitude							59.04%	1.771	0.652
	A1	0.704
	A2	0.861
	A3	0.731
Safety							66.43%	1.994	0.748
	S1		0.814
	S2		0.836
	S3		0.796
Efficiency							55.51%	2.221	0.709
	E1			0.863
	E2			0.842
	E3			0.735
	E4			0.476
Reliability and Trustworthiness							69.74%	2.789	0.854
	T1				0.825
	T2				0.845
	T3				0.866
	T4				0.804
Responsiveness							64.75%	2.59	0.813
	R1					0.572
	R2					0.857
	R3					0.877
	R4					0.871

The factor loadings obtained from PCA are in the range of 0.55 and 0.70, and the eigenvalues for attitude, safety, efficiency, trustworthiness and responsiveness are 2.185, 1.994, 2.221, 2.789, and 2.59, respectively. Given that the factor loadings exceed 0.30 and all eigenvalues are all greater than 1, the proposed indicators are deemed appropriate for the constructs [49].

The percentages of variance explained are as follows: attitude (72.84), safety (66.43), efficiency (55.51), trustworthiness (69.74), and responsiveness (64.75). Trustworthiness was tested on the basis of Cronbach’s alpha values and is illustrated in Table 2. The Cronbach’s alpha value for trustworthiness was the highest at 85.4 percent, and that for attitude was the lowest at 65.2 percent. The results of Cronbach’s alpha for all the factors exceeded the threshold of 60 percent suggested by [50]. These findings suggest that the level of internal consistency for all the examined factors is acceptable.

Table 3 shows the descriptive statistics of the health insurance quality dimensions and the mean scores of the respondents in each dimension. The mean scores of the respondents on Attitude, Responsiveness, Trustworthiness, Safety and Efficiency ranged between 2.507 and 3.144. The results were on lower average limits with scores of Attitude (2.687–2.377), Safety (2.982–3.384), Efficiency (2.799–3.394), Reliability and Trustworthiness (2.859–3.074), and Responsiveness (2.835–3.109). These scores indicate that there were problems with perceived insurance service quality in many dimensions.

Table 3.

Descriptive statistics of health insurance service quality dimensions

Construct				Item	Mean	SD	t-statistics	Sig
Attitude					2.507	0.810	−10.257	< 0.001
				A1	2.687	1.021	−11.331	< 0.001
				A2	2.415	1.123	−6.234	< 0.001
				A3	2.377	1.017	−6.243	< 0.001
Safety					3.144	0.853	2.852	0.005
				S1	3.384	1.065	6.072	0.000
				S2	2.982	1.048	−0.283	0.777
				S3	3.067	1.026	1.099	0.273
Efficiency					3.047	0.696	1.129	0.260
				E1	3.137	0.954	2.425	0.016
				E2	2.856	0.938	−2.593	0.010
				E3	3.394	0.873	7.610	0.000
				E4	2.799	1.039	−3.255	0.001
Reliability and Trustworthiness					3.098	0.763	2.158	0.032
				T1	3.063	0.986	1.084	0.279
				T2	2.859	0.992	−2.393	0.017
				T3	3.074	0.954	1.306	0.192
				T4	2.915	1.060	−1.344	0.180
Responsiveness					2.921	0.795	−1.680	0.094
				R1	3.109	0.932	1.975	0.049
				R2	2.887	1.016	−1.868	0.063
				R3	2.852	1.015	−2.454	0.015
				R4	2.835	1.007	−2.768	0.006

We test whether the mean scores are significantly different from 3 via the independent sample t test. The significance level computed from the t statistics for the attitude dimension indicates that the mean score of the attitude dimension is significantly below the standard value of 3 (p<0.001). The results for Efficiency and Responsiveness indicate that respondents rate those dimensions as mere averages because their t values indicate that they are statistically insignificantly different from 3. The results for the remaining two dimensions, Safety and Reliability and Trustworthiness, indicate that they are slightly above the standard value of 3.

Discussion

The SERVQUAL measure is a widely used tool for understanding expectations and perceptions of service quality, encompassing five main dimensions. SERVQUAL has a number of desirable features [51]. First, it allows service providers to compare their performance against competitors. Second, it enables the comparisons of service quality both at the dimension level and overall. Third, it allows providers to categorize customers based on their scores in each dimension and tailor programs accordingly. The five dimensions of SERVQUAL are:

1. Attitude: This dimension reflects the behaviour and empathy of healthcare providers towards patients. Positive attitudes are essential for patient satisfaction, while negative behaviours can harm patient safety and the reputation of health insurance companies. Numerous studies have integrated attitudes as a key dimension in assessing healthcare service quality and customer satisfaction [43–46, 52–56].

2. Safety: This refers to patients’ perceived safety under health insurance coverage. Concerns arise when healthcare providers exploit the system for profit, leading to unnecessary treatments and compromised patient safety, such as excessive prescribing and unwarranted diagnostic tests, and, in some cases, unnecessary surgical procedures such as caesarean sections [47, 48].

3. Efficiency: This dimension assesses the competencies of medical staff and their ability to deliver quality services. In contexts like Syria, inefficiencies can stem from delayed reimbursements, causing experienced providers to opt out of insurance networks.

4. Reliability and trustworthiness: This encompasses patients’ perceptions of healthcare providers’ competence and integrity [57]. Trust is crucial, especially in systems where profit motives may overshadow patient care. Patients usually view physicians as trustworthy if they believe in their competence and concern for their welfare [58].

5. Responsiveness: This dimension measures how well health insurance providers meet patients’ expectations in a timely manner. Long wait times and inadequate attention can lead to dissatisfaction and dropout from insurance schemes [48].

In this cross-sectional study, the results indicate that the mean score of the Attitude dimension is 2.507, significantly below the standard value of 3. Unsatisfactory elements include medical staff charging patients extra fees when they identify as health insurance holders (A1) and insured patients compared to cash-paying patients (A2). Respondents also believe that insured patients receive lower-quality health services (A3), contradicting evidence from Jordan, where insurance is associated with higher perceived healthcare quality [59]. Overall, insured patients express dissatisfaction with staff attitudes, which do not meet their expectations. This aligns with previous studies indicating unequal treatment, where healthcare providers exhibit more negative attitudes towards insured patients than uninsured ones [60, 61]. One explanation for this may be hyperinflation, which leads providers to feel worse off when treating insured patients due to delayed reimbursements, resulting in mistreatment of insured in favour of cash-paying ones. In Saudi Arabia, however, patients prioritize reliable compensation when assessing health insurance quality [40].

The safety dimension scores the highest, averaging 3.144, statistically above the average value of 3. This high score may be due to respondents feeling safe regarding health risks when holding health insurance certificates (S1) possibly because they are treated in less crowded and more comfortable hospitals [10]. However, respondents are less sure whether health medical staff provide them with safe services. A respondent indicated that some hospitals order unnecessary medications, diagnostic tests, and sometimes operations to earn additional profit at the expense of safety and well-being. Surely, this cannot be recognized by a normal patient but can be easily noticed by medical patients. This can be interpreted as an attempt by health providers to increase the patient bill to compensate for delayed payments. This behaviour may be an attempt by providers to inflate patient bills to compensate for delayed payments, a concern echoed in reports from Syria [30, 32, 62].

The efficiency dimension shows a mean of 3.047, statistically insignificantly different from the average. However, this average masks dissatisfaction with both quality and coverage. Respondents perceive healthcare services as inefficient (E2), with a mean of 2.856, significantly below the average value of 3. Additionally, respondents express dissatisfaction with health coverage provided by insurance companies, particularly regarding the exclusion of transmittable diseases like cholera and COVID-19 (E4). This finding aligns with previous research indicating patient dissatisfaction with insurance companies that avoid covering treatment costs for such diseases [10]

The reliability and trustworthiness dimension has a mean of 3.098, slightly above average, but there is considerable variation in respondents’ views. While respondents believe that healthcare providers are committed to delivering services on time and finding solutions to patients’ problems (T1). However, respondents feel that healthcare providers do not show enough interest to address their complaints and problems (T2). This is possibly due to the disconnection between patients and insurance companies where patients contract with insurance companies but deal with administrators from both TPAs and health providers who are less willing to cooperate. The evidence from Saudi Arabia indicates that patients give considerable importance to solving their problems when assessing the quality of health insurance service [6]. In addition, the respondents were unsure that healthcare providers had given them the best treatment from the first time with peace of mind (T4).

In terms of responsiveness, the results show a mean of 2.921, which is statistically insignificantly different from the average value of 3. Again, there is a variation in respondents’ views with regard to this dimension. On the other hand, respondents believe that they are informed of the exact time of their appointment (R1). On the other hand, they seem unhappy with the waiting time and staying on-hold when contacting TPAs requesting medical appointments or requesting medications and treatment approval (R3, R4). The long waiting time before granting approval, especially in critical cases, jeopardise the service quality and expose patients’ lives to threat and make many patients opt to pay cash for their treatment despite that they are covered by health insurance policies. This result gets along with the evidence obtained from Saudi Arabia where patients give the second priority to fast medical approval when assessing the service quality of health insurance companies [6]. Moreover, they believe that TPAs are not doing their best to quickly provide them with suitable services (R2).

In pre-war Syria, the majority of well-equipped hospitals and specialized medical centres were concentrated in urban areas [29]. These disparities and regional inequalities were exaggerated after the war in 2011 [30]. Hence, even when patients live in rural areas, they have to go to nearby cities to obtain health service. Thus, a discrimination between participants’ geographic location, rural and urban, may not add useful information but rather may introduce confused conclusions. The electronic format of the questionnaire allowed wider national participation and representation, reaching individuals from different regions across Syria.

Conclusions

The health insurance system in Syria is often subject to criticism and proposals for reform. It faces numerous challenges and limitations due to war conditions and consequences; these include a shortage of financial coverage due to job losses or displacement, high OOP payments, destruction of healthcare infrastructure, displacement of healthcare professionals, inadequate funding, inefficient administration and a lack of healthcare service providers.

This study aims to assess the quality of perceived healthcare insurance services in post-conflict Syria. We adopt the SERVQUAL metric, which is based on five dimensions: attitude, safety, efficiency, reliability and trustworthiness, and responsiveness. Identifying the shortcomings of existing health insurance services would contribute to improving the quality of such services and thus the enrolment of health insurance schemes. Moreover, it provides insights and lessons for health administrators in liberalized Syria and for countries that come out of wars

The results of this study uncover Attitude as the main issue that jeopardise health insurance service quality related to war and hyperinflation conditions in Syria which is rarely observed as a concern in health insurance literature in Arab countries. Moreover, this study indicates that health insurance work relatively well in responding to non-urgent cases and incidents but fail to meet patients’ expectation in urgent cases when they are expected to respond quickly and promptly. The need to obtain approval to gain admission to hospitals and to receive every medication let people forgo this service and decide to pay cash despite that they are qualified for the treatment. This increases the OOP payments and jeopardise the life of heart disease and other critical patients.

The findings indicate that health insurance services provided in Syria are either below average or average in four out of five dimensions. This dissatisfaction from the quality of health insurance service documented in Syria is inconsistent with many studies in other countries, from the developing countries [59, 63] and developed world [64]. We argue that the quality of the healthcare system is as good as the funding of the system [65, 66] and war conditions are manifested in the quality of insurance services. Moreover, the low quality of care received by insured patients is due to multifaceted problems, ranging from modest coverage to delays in reimbursing health service providers. Those problems are responsible for the lower levels of satisfaction achieved with the attitude dimension, as insured patients feel discriminated against compared with OOP-paying patients.

Despite the rise in policy premiums, insured patients feel mistreated by healthcare providers compared to those who pay out-of-pocket. This perception is exacerbated by the limited coverage and accessibility of health insurance services, with only a small percentage of the population being insured. It seems that the health insurance system cannot function effectively because the health insurance premium is extremely low, about $30 per person in 2025 for public sector employees, who constitute the majority of health-insured population. Operating a meaningful health insurance system with such limited financing appears almost impossible, as this low premium represents the structural constraint underlying all the observed dissatisfaction.

We recommend that the government increase its contribution to government employees’ health insurance premium to reach $90, ensuring reasonable financial protection for employees. This aligns with World Bank estimates of a reasonable premium necessary for sufficient prepayment and pooling for people in low-income countries [67]. The Insurance Supervisory Commission, as the regulator of insurance sector, should closely monitor the quality of services provided by health insurance companies and impose fines on companies that violate their commitments. Establishing a hotline for patients to report mistreatment by health insurance service providers would improve the image of health insurance and encourage healthcare providers to treat patients with care and dignity. Furthermore, health insurance companies should capitalise on digital technologies and AI to enhance customer experience and service quality. Researchers are encouraged to investigate the most influential determinants of patient satisfaction with health insurance services to help companies retain and increase subscribers.

Finally, while the study produces interesting results regarding the perceived quality of health insurance services, it is admittedly fraught with certain limitations. More specifically, the measurement of quality is based on a subscriber’s experience with the scheme rather than on scientific evaluation. This self-evaluation of healthcare service quality suffers from bias, especially when subscribers are treated with empathy or professionalism, or when they receive services from familiar providers [68]. Moreover, we did not distinguish between residents of rural and urban areas. Furthermore, the use of convenience sampling through electronic distribution may bias our results toward internet-literate and social media users, affecting the generalization of the results beyond the surveyed group. Thus, the results of this study should be interpreted with these limitations in mind. However, the limitations acknowledged in this paper do not undermine the validity of our findings and represent avenues for future research.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Abbreviation

TPA

Third Party Administration

Author contributions

S.M., L.A. and S.A. reviewed the manuscript. L.A. designed the questionnaire. S.M. performed the questionnaire analysis. S.M. implemented the statistical models. L.A., S.A. and S.M. interpreted the results.

Funding

Not applicable.

Data availability

All the raw data used in this study were prepared in Arabic (not English). Data gathered for this study are available in supplementary file 2.

Declarations

Ethics approval and consent to participate

This study was approved by the ethics committee of the Scientific Research Council of Arab International University, and all experimental protocols were approved by the Council; (approval no. AIU5525). All methods were performed in accordance with the relevant guidelines and regulations. Respondents indicated their consent to participate by completing the survey.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.