Nurses’ Work Satisfaction With Electronic Medical Record Use and Associated Facilitators and Barriers in Palestine

Abstract

Background

Electronic Medical Records (EMRs) have become essential tools in modern healthcare, enhancing efficiency, safety, and quality of care. However, multiple factors influence nurses’ satisfaction with EMR use.

Aim

To assess nurses’ work satisfaction with EMR use and identify associated facilitators and barriers among nurses in Palestinian governmental hospitals.

Methods

A cross-sectional quantitative design was employed. A convenience sample of 190 nurses from medical and surgical wards was recruited. Data were collected using a self-administered questionnaire covering demographics, work environment variables, and an adapted version of the Nursing Work Satisfaction Questionnaire (NWSQ). Sample size was determined using G*Power software. Data were analyzed using SPSS.

Results

Among 190 nurses, 51.1% were aged 20–30 years, with nearly equal gender distribution. Most (63.1%) had received EMR training, and 53.2% perceived the system as user-friendly. 52.1% were satisfied with their work using EMRs. Regression analysis demonstrated that ease of system use (β = 0.274, p < .001), EMR training (β = 0.230, p = .020), technical support satisfaction (β = 0.148, p = .012), and age (β = 0.194, p = .045) remained significant predictors of nurses’ work satisfaction after adjustment. The regression model explained 23.4% of the variance in work satisfaction (R² = .234).

Conclusion

Nurses in Palestinian governmental hospitals reported moderate satisfaction with EMR use. Factors such as training, system usability, technical support, and age significantly contributed to satisfaction. Strengthening these areas may enhance the integration and effectiveness of EMRs in nursing practice.

Introduction

Electronic medical record (EMR) is a computerized representation of patient medical history that enables the storing and retrieval of patient information using computers (Dubale et al., 2023). It generally includes critical patient information and treatment guidelines. These technologies, which evolved significantly in the twentieth century, have grown to facilitate system functionality, including access to information and clinical decision support (Alsulaiman et al., 2022). Efficient and accurate documentation is now crucial in the modern healthcare environment, as it forms the basis of nursing workflow and work satisfaction (Moore et al., 2020).

Satisfaction is a positive emotional state of feeling (Kian et al., 2014). There are many factors affecting nurses’ satisfaction, such as education, workload, availability of resources, and fear (Lu et al., 2019; Yasin et al., 2024). Nurses’ dissatisfaction can have a negative impact on nurses’ mental and physical health, intensifying stress and the quality of care provided in the work setting (Yasin et al., 2024).

EMRs improve quality of care as they organize documentation and provide immediate access to information, which can lead to improved workflow and user satisfaction (Abu Raddaha, 2018). EMRs reduce medication administration errors, prevent test duplication, and enhance coordinated care. However, despite these advantages, EMRs come with limitations that require attention (Dubale et al., 2023). EMR systems are often associated with complexity and usability issues, which may result in an increase in the time spent on documentation rather than patient care. Additionally, inadequate technical support and system performance are linked to EMR system users’ inconvenience. This can consistently lead to frustration, dissatisfaction, and burnout, highlighting the need for improved system design and support to enhance the nursing experience with EMRs (Jennings et al., 2022).

Nurses spend more than half of their working hours on EMR data retrieval and data entry (Olivares Bøgeskov & Grimshaw-Aagaard, 2019). Additionally, nurses are resistant to technological innovation primarily because they fear that these systems will disrupt their traditional work patterns (Cheraghi et al., 2023). Implementation of EMR system will most likely result in some form of change that can be the cause for nurses to experience fear, confusion, and fatigue (Hariyati et al., 2020).

In settings such as Palestine, where hospitals face ongoing infrastructural, financial, and staffing constraints (El Jabari et al., 2024; Farajalla et al., 2025), it is especially important to understand how EMRs impact nurses’ professional experiences. This study aims to assess nurses’ work satisfaction with EMR use and identify the associated facilitators and barriers among nurses in Palestinian government hospitals. Guided by the Technology Acceptance Model (TAM), perceived ease of use was operationalized through nurses’ perceptions of EMR ease of navigation, while EMR training and technical support were conceptualized as facilitating conditions that enable effective system use and influence work satisfaction. The main research question guiding this study is, what is the level of nurses’ work satisfaction with EMR use, and what are the associated facilitators and barriers influencing this satisfaction in Palestinian government hospitals?

Review of the Literature

This research is underpinned by the TAM, which states that technology acceptance and user satisfaction are determined by perceived usefulness and perceived ease of use (Davis, 1989). TAM has been extensively used to investigate nurses’ adoption of EMRs, with research in Singapore identifying ease of use and training as significant predictors of satisfaction (Kowitlawakul et al., 2015). This model informs the investigation of factors affecting nurses’ satisfaction with EMRs in Palestinian hospitals.

Several international studies have described varying levels of satisfaction among nurses regarding the use of EMRs, showing a mixed and often contradictory picture. For example, a study in the United States identified system complexity as a significant issue affecting nurses’ satisfaction (Melnick et al., 2021). A global survey reported low satisfaction due to system complexity and inadequate training, particularly in resource-constrained settings (Topaz et al., 2016). 70.9% of Malaysian nurses were moderately satisfied with EMR systems (Ramoo et al., 2022). Similarly, an Indonesian study reported that 53.1% of nurses were satisfied; however, frequent system crashes and inadequate technical support negatively impacted overall work satisfaction (Aris Winata & Hariyati, 2021). In Ethiopia, almost half of the nurses surveyed expressed satisfaction with EMRs.

Prior research has consistently identified demographic and system-related factors as significant predictors of EMR satisfaction. For instance, a cross-sectional studies in Saudi Arabia and Indonesia found that technical support and training have been positively linked to satisfaction (Alsulaiman et al., 2022; Aris Winata & Hariyati, 2021). Furthermore, age, gender, years of experience, and shift work have been shown to affect EMR usage (Dubale et al., 2023). User satisfaction commonly correlates with system-based predictors like ease of navigation and computer availability (Pinevich et al., 2021; Topaz et al., 2016).

In the Middle East, local evidence demonstrates considerable variation. A Saudi Arabia study identified that user satisfaction reported 87.1% of nurses being satisfied with EMRs (Jaber et al., 2021). A study in the United Arab Emirates found that nurses were very happy with EMRs. However, they also said that some nurses did not have enough computer skills (Bani-issa et al., 2016).

In Palestine, the healthcare sector has particular challenges arising from political and financial instability (El Jabari et al., 2024; Farajalla et al., 2025; Najjar et al., 2022). These challenges create a lack of resources, outdated systems of documentation, and staffing shortages, increasing workload and dissatisfaction. To date, no quantitative study has examined nurses’ work satisfaction with EMR use in Palestinian governmental hospitals. The lack of local information, however, reflects a required knowledge gap hindering healthcare professionals and policymakers from implementing evidence-based practices to improve documentation quality. Addressing this gap is vital to support nurse satisfaction and enhance patient care outcomes despite ongoing resource and administrative challenges.

Methods

Design

This study employed a cross-sectional design to assess nurses’ work satisfaction with EMR use and identify facilitators and barriers in Palestine.

Population

The target population was all registered nurses (RNs) who are employed in medical and surgical wards of Palestinian governmental hospitals and are users of EMR systems. The accessible population consisted of RNs employed in the selected government hospitals located in the West Bank. Hospitals were chosen from different areas (Central, northern, and southern West Bank) for better representativeness.

Sample and Sampling

Sample size was determined using General Power Analysis Software (G*Power) 3.1 software because it is appropriate for regression. A priori power analysis was conducted for multiple linear regression (fixed model, R² deviation from zero) for medium effect size (f² = 0.15), significance level of .05, and power of 0.95, as recommended for health sciences research (F. D. Polit & Beck, 2021). Eight potential facilitators and barriers (Predictors) were derived from the work environment and demographic variables. Applying these, the minimum sample size was estimated to be 160 participants. To make room for probable dropouts and statistical errors, the sample was increased to 225. A non-probability convenience sampling method was used due to logistical constraints and has been similarly applied in comparable EMR satisfaction studies in Malaysia and Saudi Arabia (Jaber et al., 2021; Ramoo et al., 2022).

Inclusion and Exclusion Criteria

RNs with more than 4 months of experience with EMR systems were included. Nurses employed on wards with a mix of paper and electronic records were excluded to prevent confusion between dual documentation systems. Non-clinical support personnel, such as administrative and managerial staff, were excluded to target direct nursing experiences with EMRs. The 4-month experience was selected, as 3–6 months is a common period for healthcare professionals to become proficient with EMR systems, facilitating valid satisfaction measurements (Kowitlawakul et al., 2015). Excluding mixed-record wards provided assurance of consistent EMR dependence, as dual systems can obscure satisfaction data due to inconsistent usage patterns (Topaz et al., 2016).

Setting

This study was conducted in the West Bank of Palestine, which has numerous government and nongovernment hospitals. Government hospitals with medical, surgical, or day care departments were included to achieve the study's objectives.

Instrumentation

A structured self-reported questionnaire was used for data collection, aiming to assess nurses’ work satisfaction with EMR use. The questionnaire comprised two main sections: (1) demographic and environmental variables and (2) nurses’ work satisfaction with EMR use, measured through an adapted version of the Nursing Work Satisfaction Questionnaire (NWSQ).

The first section aimed to gather demographic and environmental factors, including age, gender, years of experience, EMR training, work shift, user friendliness, technical support, and computer availability. They were chosen based on empirical evidence from past studies showing their relevance to EMR studies. For example, user-friendliness was one of the greatest EMRs satisfaction drivers in an American study (Pinevich et al., 2021), whereas Saudi studies illustrated the effect of training and technical support on nurses’ competence and self-confidence in using EMR systems (Alsulaiman et al., 2022). Ease of use, technical support, and computer availability were each assessed using a single item, rated on a 5-point Likert scale (1 = Strongly disagree to 5 = Strongly agree).

The second section of the questionnaire used an adapted version of the Nursing Work Satisfaction Questionnaire (NWSQ), which was originally developed by Fairbrother et al. (2010). The instrument assesses work satisfaction in three domains: intrinsic, extrinsic, and relational. In this study, 10 items were selected for their relevance to satisfaction with EMR systems while maintaining congruence with the instrument's psychometric properties. Four of the original six intrinsic satisfaction items were kept because of their relevance to EMR-related work satisfaction. They were “My job gives me a lot of satisfaction,” “My job is very meaningful for me,” “I am enthusiastic about my work,” and “My work gives me the opportunity to show my worth.” Less relevant items were excluded because they were less pertinent to the study's focus. Five items of the extrinsic satisfaction subscale were kept since they pertained to the digital workplace and EMR implementation impacts. The selected items were “I have enough time to deliver good care to patients,” “I have enough opportunity to discuss patient problems with my colleagues,” “I have enough support from colleagues,” “I feel able to learn on the job,” and “I feel isolated from my colleagues at work” (reverse-scored). Only one relational satisfaction item, “I feel that I belong to a team”, was included due to its relevance to EMR-mediated communication and team dynamics.

The 10 items were rated on a 5-point Likert scale (1 = Strongly Disagree, 5 = Strongly Agree). Each item was modified only by adding the phrase “when using the Electronic Medical Records system” to ensure contextual specificity (Table 3). Permission for adaptation was obtained from the original authors. Participants’ average work satisfaction scores were calculated by computing the mean of the scale items (range 1–5). For descriptive purposes only, participants were categorized as ‘Satisfied’ or ‘Not Satisfied’ based on a median split of the average score. Validity of the questionnaire was assessed with the content validity index. This validation was conducted by interviewing three independent, highly experienced research professors and experts in the study field. The questions were modified according to their responses. A Pilot study was conducted among 25 nurses to evaluate clarity, understandability, and feasibility. Their Participants` responses were analyzed for time necessary for completion, response consistency, and item clarity. Feedback from participants was reviewed to identify confusing or ambiguous items. Based on this feedback, minor wording adjustments were made. The completion rate was 100%, and no item was left blank. This was followed by internal consistency testing using Cronbach's alpha (α = .84), indicating high reliability.

Table 3.

Participants’ Responses for Each Work Satisfaction Question (N = 190).

	Strongly disagree	Disagree	Neutral	Agree	Strongly agree
Work satisfaction items	n (%)	n (%)	n (%)	n (%)	n (%)	Mean (SD)
*1. My job gives me a lot of satisfaction when using the EMR system.	8	26	39	81	36	3.58
	(4.2)	(13.7)	(20.5)	(42.6)	(18.9)	(1.07)
*2.My job is very meaningful for me when using the EMR system.	3	23	64	70	30	3.53
	(1.6)	(12.1)	(33.7)	(36.8)	(15.8)	(0.95)
*3.I am enthusiastic about my work when using the EMR system.	4	17	62	74	33	3.60
	(2.1)	(8.9)	(32.6)	(38.9)	(17.4)	(0.94)
*4.My work gives me the opportunity to show my worth when using the EMR system.	8	16	57	82	27	3.54
	(4.2)	(8.4)	(30.0)	(43.2)	(14.2)	(0.97)
**5. I have enough time to deliver good care to patients when using the EMR system.	5	21	46	85	33	3.63
	(2.6)	(11.1)	(24.2)	(44.7)	(17.4)	(0.98)
**6. I have enough opportunity to discuss patient problems with my colleagues when using the EMR system.	5	18	66	67	34	3.56
	(2.6)	(9.5)	(34.7)	(35.3)	(17.9)	(0.97)
**7. I have enough support from colleagues when using the EMR system.	3	20	60	69	38	3.62
	(1.6)	(10.5)	(31.6)	(36.3)	(20.0)	(0.97)
**8. I feel able to learn on the job when using the EMR system.	5	17	60	79	29	3.57
	(2.6)	(8.9)	(31.6)	(41.6)	(15.3)	(0.94)
**9. I feel isolated from my colleagues at work when using the EMR system.	31	71	58	30	0	3.54
	(16.3)	(37.4)	(30.5)	(15.8)	(0.0)	(0.94)
***10. I feel that I belong to a team when using the EMR system.	4	25	64	65	32	3.65
	(2.1)	(13.2)	(33.7)	(34.2)	(16.8)	(2.29)
Total work satisfaction score
(M ± SD)
3.58 ± 0.75

Note. *Intrinsic satisfaction items, **Extrinsic satisfaction items, ***Relational satisfaction item; n = number; % = percentage; M = mean; SD = standard deviation.

Item 9 was negatively worded and reverse coded prior to analysis. Higher scores indicate greater work satisfaction with EMR use.

Pilot study participating nurses were excluded for any potential bias or contamination. The use of neutral language, absence of leading questions, and contextual adaptation reduced social desirability and interpretation bias. Reliability of the adapted work satisfaction scale was assessed using Cronbach's alpha coefficient and was .84. Exploratory or confirmatory factor analysis was not conducted to re-examine the underlying factor structure of the adapted 10-item scale. The adaptation was guided by conceptual alignment with the original intrinsic, extrinsic, and relational domains of the NWSQ and supported by expert content validation and internal consistency reliability testing.

Data Collection

After obtaining ethical approval, meetings were scheduled with the head nurses of each ward in the hospitals to introduce the purpose of the research, request a list of characteristics regarding the participants’ experiences, and obtain access to eligible medical and surgical nurses for inclusion in the study. Data were collected using a paper-based self-administered questionnaire. This approach was selected due to limited access to digital devices in the participating wards and to align with the preference of many nurses for a more familiar and confidential response format. The recruited participants who agreed were asked to sign informed consent and complete the questionnaire; to avoid questionnaire loss, the research team collected the questionnaires at the end of each working day. Data were collected during the month of April in the year 2025. No financial or material incentives were offered for participation, and questionnaires were completed by nurses during their working hours at times that did not interfere with patient care.

The questionnaires were completed in the English language, and each questionnaire was marked to keep track of the count. Based on information provided by ward administrators, the estimated number of eligible nurses working in medical and surgical wards across the participating governmental hospitals was estimated to be 270 at the time of data collection. Of these, 225 nurses were approached, and 190 questionnaires were retrieved and completed, yielding a response rate of 84.4%.

Data Analysis

The data were analyzed using SPSS version 29. To describe the participant's demographics and their work environment factors, descriptive statistics such as frequencies and means were used. Pearson correlation analysis was conducted to assess associations between work satisfaction and study variables. Multiple linear regression analysis was subsequently conducted using the continuous average work satisfaction score as the dependent variable to identify facilitators and barriers to nurses’ satisfaction with EMR use. Multiple linear regression analysis was performed using the standard enter method, with all theoretically relevant demographic and work–environment variables entered simultaneously. Variables were selected a priori based on previous literature and the study framework. Assumptions of linear regression were checked, including normality, linearity, homoscedasticity, and independence of residuals. Multicollinearity was assessed using variance inflation factors (VIF), with all values below the acceptable threshold. Model fit was evaluated using R² and adjusted R². A p-value of less than .05 was considered statistically significant throughout the analysis.

Ethical Consideration

Ethical permission to conduct the study was provided by the Ethical Committee of the College of Nursing, Palestine Polytechnic University (Approval No. EA/2025/48) and the Ministry of Health of Palestine. Written informed consent was provided to all the participants prior to their enrollment in the research. Rapport was built with the participants, and participants were informed that they were voluntarily participating. Confidentiality while gathering data were ensured. Additionally, participants were assured that all personal information will be kept confidential. The research adhered to the ethical standards outlined in the Declaration of Helsinki regarding the rights, protection, and well-being of research participants.

Results

The findings revealed that approximately half of the nurses were between 20 and 30 years (51.6%) with a mean age of 32.6. Gender was nearly equal: male (53.1%) and female (46.9%). Over half of the nurses reported an ABC shift (54.7%). And the majority of participants had more than five years of experience (59.5%). 63.1% of the nurses received training in EMRs (Table 1).

Table 1.

Distribution of Demographic Information Among Participants.

Demographics	Categories	n (%)	Mean (SD)
Age/Years	20–30	98 (51.6)	32.6
	31–40	59 (31)	(7.3)
	41–50	23 (12.1)
	More than 50	10 (5.3)
Years of experience	1–5	77 (40.5)	9.1
	6–10	52 (27.4)	(6.6)
	>10	61 (32.1)
Gender	Male	101 (53.1)
	Female	89 (46.9)
Working Shift	A	50 (26.3)
	BC	36 (19)
	ABC	104 (54.7)
Training on EMR	Yes	120 (63.1)
	No	70 (36.9)

Note. N/n: number; %: percentage; SD: standard deviation.

Our results revealed that a total of 54.2% of participant nurses agreed or strongly agreed that the EMR system was user-friendly, with a mean score of 3.47. Technical support satisfaction was slightly lower, with a total of 44.7% agreeing or strongly agreeing that they received adequate support, yielding a mean score of 3.30, while computer availability showed the lowest satisfaction, with only about 41% agreeing or strongly agreeing that sufficient computers were available for their use (Table 2).

Table 2.

Distribution of Work Environment Factors Among Participants.

	Strongly disagree	Disagree	Neutral	Agree	Strongly agree
Work environmental variables	n (%)	n (%)	n (%)	n (%)	n (%)	Mean (SD)
Ease of use and navigation satisfaction	11	19	57	72	31	3.47)
	(5.8)	(10.0)	(30.0)	(37.9)	(16.3)	(1.04)
Technical support satisfaction	4	39	62	70	15	3.30
	(2.1)	(20.6)	(32.6)	(36.8)	(7.9)	(0.95)
Computer availability satisfaction	6	30	76	65	13	3.25
	(3.2)	(15.8)	(40.0)	(34.2)	(6.8)	(0.91)

Note. N/n: number; %: percentage; SD: standard deviation.

Responses of nurses on the work satisfaction scale were predominantly positive on all dimensions. The overall mean work satisfaction score was 3.58 ± 0.75, indicating a moderate level of satisfaction, with substantial variability among nurses. High levels of the participants indicated intrinsic satisfaction with work during the use of the EMR system. Specifically, 61.5% of them agreed or strongly agreed with the statement: “My job gives me a lot of satisfaction when using the EMR system.” Similarly, 52.6% agreed or strongly agreed on the statement “My job is very meaningful for me when using the EMR system,” and 56.3% showed agreement with enthusiasm when working with EMRs. Notably, the scale “I feel isolated from my colleagues” received more disagreement, with 53.7% (n = 102) stating they disagreed or strongly disagreed, reflecting low perceived isolation. On team dynamics, 51% (n = 97) agreed or strongly agreed with the scale: “I feel that I belong to a team when using the EMR system” (Table 3).

Analysis of the level of work satisfaction revealed that a slight majority 52.1% (n = 99) are satisfied in their work using EMR systems, scoring a mean score above the median (3.6), and 47.9% (n = 91) are unsatisfied in their work using the EMR system, scoring a mean score below the median (3.6), as shown in Table 4.

Table 4.

Level of Work Satisfaction Among Nurses.

Level	n (%)	Mean	Median
Satisfied	99 (52.1)	3.58	3.60
Unsatisfied	91 (47.9)

Note. n = number, % = percentage.

Pearson correlation analysis was conducted to examine associations between work satisfaction and study variables. Work satisfaction was significantly correlated with technical support satisfaction (r = .39, p < .001), user-friendliness (r = .200, p = .006), and computer availability (r = .200, p = .006), indicating that nurses with better technical support and user-friendly systems and infrastructure reported higher satisfaction (Table 5).

Table 5.

Pearson Correlation Between Work Satisfaction and Selected Variables (N = 190).

Variables	Correlation coefficient (r)	p-value
Technical support satisfaction	.39	<.001
User-friendliness	.20	.006
Computer availability	.20	.006
Age	.11	.11
Years of experience	.10	.15

Following the correlation analysis, a multiple linear regression analysis was conducted to identify demographic and work–environmental predictors of nurses’ work satisfaction with EMR use. The overall model was statistically significant and explained 23.4% of the variance in work satisfaction (R² = .234; Adjusted R² = .200). Ease of use of the EMR system emerged as the strongest predictor of work satisfaction (β = 0.274, p < .001), followed by EMR training (β = 0.230, p = .020), technical support satisfaction (β = 0.148, p = .012), and age (β = 0.194, p = .045). Other variables, including gender, years of experience, working shift, and computer availability, did not remain statistically significant after adjustment (Table 6).

Table 6.

Facilitators and Barriers of Work Satisfaction Among Nurses.

		95% confidence interval
Variable	β	Lower bound	Upper bound	p-value
Age	0.194	0.005	0.384	*.045
Gender	−0.062	−0.246	0.121	.504
Years of Experience	−0.081	−0.217	0.054	.238
Working Shift	−0.094	−0.197	0.010	.076
Training on EMR	0.230	0.34	0.426	*.020
Ease of use and navigation	0.274	0.174	0.374	**.000
Technical support	0.148	0.033	0.263	*.012
Computer’s availability	0.067	−0.038	0.172	.212

Note. n = 190; β = standardized regression coefficient; * p < .05; ** p < .01.

Discussion

The discussion is organized around four key findings: the overall level of nurses’ satisfaction with EMR use, the role of training and system usability, the importance of technical support and infrastructure, and the influence of age. A majority of the nurses were aged between 20 and 30 years (51.6%), followed by a close gender balance between male and female, indicating that Palestinian government hospitals have a relatively young and gender-balanced nursing workforce. This demographic pattern is consistent with global trends, where younger nurses, who are often more comfortable with digital tools, are increasingly found in front-line care roles (Moore et al., 2020). A majority of participants indicated working rotating shifts (ABC), reflecting the intense demands and high-paced nature of Palestinian hospitals, where public health systems tend to be resource-limited and faced with staffing issues.

In relation to the work environment, 63.1% of the nurses had undergone EMR training, and 54.2% considered the system easy to use. Satisfaction, however, reduced regarding technical support (44.7%) and computer availability (41%). This aligns with previous research by Hariyati et al. (2020) and Alsulaiman et al. (2022), which emphasizes training and usability as pivotal factors for effective EMR implementation and subsequent user satisfaction. A study in the United States similarly reported that only 40% of nurses were satisfied with technical support for EMR systems, highlighting a global challenge in providing robust IT infrastructure (Topaz et al., 2016). Very low satisfaction on computer availability is especially problematic as such an outcome constrains nurses from using the EMRs immediately, thereby leading to delays and frustration. In Palestine, where hospitals may lack sufficient infrastructure and technological support (Alqaissi et al., 2025; Farajalla, 2025), such limitations can further slow down documentation processes and lead to dissatisfaction among nurses who are striving to deliver timely and accurate patient care. Similar to our study, findings from an Australian study indicated that inadequate hardware availability significantly hindered EMR adoption, with only 38% of nurses reporting sufficient computer access (Jedwab et al., 2021).

This study found a moderate to high work satisfaction among nurses using EMR systems in Palestinian government hospitals with a mean score of 3.57 ± 0.73. This aligns with a Malaysian study where moderate to high levels of satisfaction have been reported among nurses utilizing EMR systems (Ramoo et al., 2022). More than half of the participants agree that EMR systems made their work meaningful and gave them the opportunity to demonstrate their worth. This result is congruent with previous studies hypothesizing that EMRs, by reducing duplicate work and improving access to patient data, have the capability of increasing professional motivation and engagement (Alsulaiman et al., 2022). A 2020 study in Finland further supports this, noting that 62% of nurses felt EMRs enhanced their sense of professional accomplishment by streamlining documentation tasks (Vehko et al., 2019). Moreover, the ability of EMRs to enhance the legibility and organization of documentation contributes to a sense of accomplishment and clarity in clinical tasks (Abu Raddaha, 2018).

In particular, 57.4% agreed that EMRs allowed them to show their worth, and 56.9% had chances to learn on the job. These results are important in the Palestinian context, where human resource shortages and overwork often undermine continuous professional development (Abdullah et al., 2021). The findings are supported by global literature that links positive work cultures and peer work with greater EMR satisfaction levels (Hariyati et al., 2020; Setyowati et al., 2022). The fact that over half disagreed with the statement “I feel isolated from my colleagues” indicates that EMR systems can actually facilitate interprofessional communication, a factor essential in quality care in resource-scarce environments like Palestine (Alsulaiman et al., 2022).

In this study, 52.1% of nurses scored above the median for satisfaction, which is close to Ethiopian and Indonesian levels (53.1%). While this indicates an overall positive trend, 47.9% dissatisfaction indicates ongoing issues such as infrastructure shortage and usability issues that must be addressed to ensure EMR implementation is optimized (Aris Winata & Hariyati, 2021; Rasmi et al., 2020).

Regression analysis revealed that ease of use of the EMR system was the strongest facilitator of work satisfaction (β = 0.274), followed by EMR training (β = 0.230). Technical support (β = 0.148) and age (β = 0.194) were also significant predictors, indicating that both system-related and demographic factors contribute to nurses’ satisfaction with EMR use. This aligns with studies in Ethiopia and Saudi Arabia, in which training emerged as a key enhancer of EMR satisfaction (Alsulaiman et al., 2022; Dubale et al., 2023). Within the Palestinian setting, where training and infrastructural resources are scarce, offering comprehensive EMR training minimizes user frustration, improves efficiency, and increases satisfaction. The Pearson correlation analysis supported the finding of user-friendliness (r = .200, p = .006), consistent with global evidence on EMR usability (Topaz et al., 2016). These findings are strongly supported by an integrative review conducted by Maawati et al. (2025), which synthesized evidence from 19 international studies and identified training, system usability, computer skills, self-efficacy, and technical support as the most consistent facilitators influencing nurses’ acceptance and satisfaction with EMR systems.

Age emerged as a significant predictor of work satisfaction only in the multivariable regression model, while no significant association was observed in the bivariate correlation analysis. This suggests that older nurses reported slightly higher satisfaction with EMR use after adjusting for other demographic and work–environment factors. This finding may reflect accumulated professional experience or different expectations regarding documentation systems. This finding contrasts with a 2019 study in the Netherlands (Kleib & Nagle, 2018), where younger nurses were more satisfied due to greater technological familiarity, suggesting context-specific age-related differences. The lack of correlation for age (p > .05), despite its regression significance, suggests indirect effects through other variables, as older nurses may derive satisfaction from EMR efficiencies (e.g., reduced documentation time) in multivariate models. This is supported by a 2020 study finding that older nurses, despite higher dissatisfaction with EMR time demands, report satisfaction when systems enhance workflow efficiency (Khairat et al., 2020).

Technical support also played a significant role (β = 0.148), which was further supported by correlation analysis (p < .001), again reaffirming that strongly established information technology (IT) support equals smoother workflow and increased work satisfaction. These results resonate with international evidence that stable IT support is one of the leading enablers of EMR adoption success (Aris Winata & Hariyati, 2021; Arruum et al., 2024).

The present findings primarily identify facilitators of work satisfaction based on statistically significant positive associations, while barriers were inferred descriptively from comparatively lower satisfaction levels with technical support and computer availability rather than from direct negative predictors.

Strengths and Limitations

This study is the first to assess nurses’ work satisfaction with EMR use in a Palestinian hospital. It is grounded in a solid research method, including the use of the proper calculation of the sample size based on G*Power for regression and the use of validated instruments (NWSQ) with a highly reliable scale to assess work satisfaction. It also points out significant predictive variables that can be employed to enhance EMR use satisfaction.

However, as with any research, it is not without limitation. Since it is cross-sectional, it cannot make conclusions of cause and effect. The convenience sampling could introduce some bias, and the exclusion of private hospitals restricts generalizability to all healthcare centers. Using questionnaires that nurses completed themselves made it more accessible but perhaps limited the depth of responses and may introduce common method bias. Excluding nurses working in wards with mixed paper and electronic documentation may have limited the representation of nurses experiencing higher documentation complexity. Although the adapted work satisfaction scale demonstrated good internal consistency, factor analytic procedures were not performed to statistically confirm whether the original intrinsic, extrinsic, and relational dimensions were preserved in the adapted EMR-specific context. Categorizing work satisfaction into binary groups based on a median split, although used only for descriptive purposes, may oversimplify the distribution of satisfaction levels and obscure subtle variations in nurses’ experiences. Additionally, the regression analysis did not measure external factors such as workload, organizational culture, or system downtime, which may influence nurses’ satisfaction with EMRs.

Implication for Practice

The findings of this study highlight three actionable priorities for improving nurses’ satisfaction with EMR use in Palestinian government hospitals. First, enhancing structured and ongoing EMR training is essential to strengthen nurses’ competence, confidence, and efficiency when using digital systems. Second, strengthening on-site technical support is critical to ensure timely problem resolution, minimize workflow disruptions, and reduce frustration associated with system failures. Third, improving computer availability within clinical units is necessary to enable consistent and uninterrupted EMR access, particularly in high-workload and resource-limited settings. Addressing these interrelated factors can substantially improve nurses’ work satisfaction, support effective EMR utilization, and ultimately enhance the quality and safety of patient care in Palestinian healthcare institutions.

This study contributes to the TAM by providing empirical evidence from a resource-constrained context that extends its explanatory scope. Consistent with TAM, perceived ease of use emerged as the strongest predictor of nurses’ satisfaction with EMR use. Importantly, the findings suggest that infrastructural elements, such as EMR training, on-site technical support, and computer availability, can be theoretically conceptualized as components of facilitating conditions that enable perceived ease of use and system acceptance, rather than as separate or independent constructs. This refinement supports a contextualized application of TAM in low-resource healthcare settings like Palestine, where infrastructural constraints play a decisive role in shaping technology acceptance and user satisfaction.

Conclusion

This study assessed nurses’ satisfaction with EMR use in Palestinian government hospitals and established predictors of higher satisfaction. Over half of the nurses indicated that they were satisfied with EMRs, and training, ease of use, technical support, and age were identified as key facilitators. These findings suggest that system functionality as well as institutional support influence nurses’ satisfaction. In Palestine, where its hospitals often experience infrastructural deficits and staffing constraints, access to training and technical support is a prerequisite for effective EMR adoption. With the ongoing digitization of the Palestinian healthcare system, these variables can be addressed to optimize EMR adoption, enhance nurse satisfaction, and advance the quality of healthcare provision within resource-scarce settings. Future research should consider exploring additional predictors of EMR-related satisfaction, such as leadership style and organizational support. Moreover, qualitative studies could provide deeper insight into nurses’ perspectives. Finally, longitudinal research would help assess how satisfaction evolves over time and in response to system updates or policy shifts.