Determinants of healthcare providers’ satisfaction with electronic medical records system (EMRs) in public healthcare facilities in the Ashanti region of Ghana: A multicenter analytical cross-sectional survey

User Satisfaction with LHIMS

This study assessed healthcare providers’ satisfaction with the Lightwave Health Information Management System (LHIMS) in public facilities in the Ashanti Region. Overall satisfaction was moderate, with 57% of the participants reporting satisfaction. This suggests that while LHIMS has gained some acceptance among frontline providers, its full potential has not yet been realised. This finding is comparable to findings from Ethiopia, where 53% of providers in private health facilities expressed satisfaction with their electronic medical records system (5). The similarity of results may be attributed to methodological consistency, as both studies employed the same validated instrument, applied similar scoring approaches, and used median cut-offs to dichotomise satisfaction scores.

Contrastingly, studies from Saudi Arabia, the United States of America, and Canada have reported higher satisfaction levels (38–40). Structural and infrastructural disparities can explain these discrepancies. In high-resource settings, EMR systems are typically supported by multiple workstations per unit, stable internet connectivity, reliable electricity, and dedicated technical support. Such conditions enable providers to fully utilise EMR functionalities, including retrieving laboratory and radiological results, prescribing medications, and issuing treatment orders. In Ghana, however, infrastructural challenges, such as limited workstations, intermittent power supply, prolonged internet downtimes, and occasional service disruptions, undermine these processes and reduce user satisfaction (21).

Furthermore, Rahman et al. (13) and Maraga et al. (41) reported significantly higher satisfaction levels in Saudi Arabia (84%) and Rwanda (91%), respectively. The difference could be attributed to the system’s maturity. In their respective contexts, the EMR had been implemented for nearly a decade in Saudi Arabia and almost 15 years in Rwanda, allowing deficiencies to be corrected, repeated training to be provided, and user-driven upgrades to be introduced. In contrast, LHIMS has been operational for less than five years in the selected facilities, suggesting it is still in a mid-adoption stage. With further optimisation and sustained support, LHIMS could achieve higher levels of satisfaction and long-term sustainability.

Beyond the overall satisfaction, variations were observed across specific domains. Healthcare providers reported higher satisfaction with the quality of information and expressed a stronger preference for electronic records over paper-based documentation. These findings align with evidence from Norway, where EMR systems demonstrated superior information quality over handwritten records (42). The possible explanation could be that EMRs produce more precise, legible, and error-free documentation (43). System-generated outputs are structured and standardised, making them easier to interpret and share. These attributes enhance clinical decision-making and communication among healthcare providers, thereby explaining why they prefer LHIMS to paper-based documentation, which is often illegible and difficult to interpret.

Satisfaction with efficiency was also reported to be high, as providers indicated that LHIMS helped them complete their work faster. This finding is consistent with studies in Ethiopia and Saudi Arabia, where the use of EMRs improved efficiency by simplifying workflows and facilitating quicker access to patient data(6,10). A likely reason is that once information is entered into the system, it can be retrieved and reused instantly, unlike paper documentation that requires repeated entries and manual searching of patients’ folders.

Conversely, satisfaction was lower in domains related to patient safety and quality of care. One key feature of LHIMS is that it allows staff across units to navigate through patient information without restriction. While this design improves access, it also raises concerns about confidentiality, data security, and patient trust. Similar governance challenges have been highlighted in Ghana and other African contexts, where weak data protection frameworks and limited accountability mechanisms undermine user confidence in EMR systems(21,44).

Furthermore, consistent with other studies, field observation revealed users often spent extended periods working on the system, for documentation, retrieving laboratory results, pharmacy instruction etc., which reduces the time available for direct patient care (45). This shift in focus from the bedside to the computer station may have inadvertently contributed to lapses in care delivery and, in some cases, potential medical negligence. These factors therefore explain why satisfaction with LHIMs on quality of care and patients’ safety was relatively lower.

Overall, these findings suggest that while LHIMS improves documentation quality and efficiency, unresolved concerns about data security and bedside engagement continue to limit its overall impact on patient safety and quality of care.

Determinants of Health Providers’ Satisfaction with LHIMS

The study analysed the determinants of healthcare providers’ satisfaction with LHIMS. User background factors were found to influence satisfaction. Access to computers emerged as a significant determinant, with providers who had adequate access reporting higher levels of satisfaction. This finding aligns with research from Ethiopia and Malaysia, where the adequate access to computers such as availability of more workstations and ownership of personal laptops and tablets, enhanced users satisfaction with the implemented EMR systems(10,46). This finding was expected because adequate computer access reduces competition for devices, ensures smooth workflow, and facilitates the timely completion of tasks such as data entry and retrieving laboratory results. Ensuring equitable distribution of computers across facilities is therefore vital to optimising the use and enhance users’ satisfaction with LHIMS in Ghana.

eHealth literacy also emerged as a significant determinant of satisfaction. Providers with higher literacy were more likely to be satisfied with the system. A possible explanation is that greater digital competence enables users to navigate EMRs more efficiently, interpret outputs accurately, and integrate digital information into clinical decision-making, thereby enhancing satisfaction. This finding is consistent with the eHealth Literacy Model and evidence from other scholars, where eHealth literacy was identified as a driver to IS success (31,47,48).

However, contrasting findings have been reported. Dubale et al. observed that eHealth literacy lost its independent association with satisfaction in the multivariable model. This discrepancy may reflect contextual or methodological differences, including variability in digital infrastructure, the scope of training interventions, or differences in how eHealth literacy was measured across studies.

It is equally important to note that not all user-related variables showed predictive value. For instance, LHIMS training did not emerge as a determinant of satisfaction. This evidence is consistent with the findings of Alasmary and Househ et al.(49) and Walle et al. (48), who similarly reported no significant relationship between basic technological training and satisfaction. In contrast, several other empirical studies, as well as established IT adoption frameworks such as the Technology Acceptance Model (TAM), have documented a positive and often strong association between training and satisfaction(5,10,13,50).

A plausible explanation for this apparent inconsistency lies in the training profile of the study population. Nearly all providers surveyed (94%) had already received training, leaving minimal variability for statistical discrimination. In such circumstances, where training coverage approaches universality, a ceiling effect occurs, thereby diminishing the explanatory power of training as a differentiating factor for satisfaction.

Similarly, computer literacy was not a determinant of user satisfaction, despite nearly half of the providers demonstrating good literacy levels. This contrasts with findings from studies conducted in Ethiopia, Saudi Arabia, and Australia, where computer literacy has been strongly associated with EMR satisfaction (5,33,48). A possible explanation is that the measure of literacy used may not have fully captured the operational skills required for effective system use. Field observations revealed that many providers had limited typing skills, which hindered documentation and data entry despite general familiarity with computers. Because these limitations were widespread, they did not translate into measurable differences in satisfaction. Overall, our findings suggest that satisfaction with LHIMS depends less on foundational skills such as basic computer literacy or universal training and more on the combination of enabling resources and advanced digital competencies. This highlights the need for capacity-building initiatives that move beyond basic training to develop advanced digital skills for sustained use of LHIMS.

Besides user background, several system-related constructs also influenced satisfaction. System quality was a significant predictor, as providers who perceived LHIMS to be stable, responsive, and user-friendly reported higher satisfaction. This finding resonates with evidence from Tanzania and Greece(51,52). A possible explanation is that reliable systems inspire user confidence, reduce workflow interruptions, and enable providers to focus on patient care rather than troubleshooting technical issues.

System usability was also a determinant. Providers who considered LHIMS simple, consistent, and easy to navigate were more satisfied, a pattern consistent with studies in Ethiopia (5,10). Usable systems reduce the cognitive burden on providers, shorten the learning curve, and fit more smoothly into clinical routines. Conversely, challenges such as navigating multiple tabs to retrieve patient information increase workload and frustration, diminishing satisfaction. These findings highlight the importance of designing user-friendly interfaces that align with workflow realities.

Information quality similarly played a critical role. Providers who perceived LHIMS outputs as precise, accurate, and valid reported higher satisfaction. This observation is consistent with studies in Ethiopia, Nigeria and Brazil, which have shown a strong relationship between EMR satisfaction and the quality of information produced(5,48,53). The DeLone and McLean IS Success Model also supports this, positing that good information quality is essential to system success(54). One possible explanation is that electronic systems produce structured and legible documentation, unlike handwritten records, which are often illegible and prone to errors. Clearer outputs improve communication among providers, reduce duplication of work, and enhance clinical decision-making, thereby increasing users’ satisfaction.

However, not all system-related factors were significant. Service quality, despite being a central construct of the DeLone and McLean Information Systems Success Model, did not predict satisfaction in this study. Similar findings have been reported in Ethiopia and Rwanda(41,48). By contrast, evidence from higher-resource contexts such as Canada, Saudi Arabia, and Brazil indicated that service quality characterised by responsive technical support was a strong determinant of EMR satisfaction (55–57). This contrast suggests that in resource-limited settings, service quality may not exert the same influence as in higher-resource health systems.

A plausible explanation is that broader infrastructural constraints common in low-resource settings, including unstable electricity, poor internet connectivity, and prolonged downtime, tend to overshadow perceptions of service quality. In Ghana specifically, these systemic challenges were compounded by concerns from health leaders that providers were not adequately consulted during the design and implementation of LHIMS, with their inputs not duly incorporated (21). These contextual issues may therefore reduce the explanatory power of service quality within the D&M model, as structural barriers and limited participatory design weaken its potential impact on user satisfaction.

Overall, system-related attributes, particularly quality, usability, and information outputs, proved central to provider satisfaction with LHIMS. These findings highlight the importance of optimising system performance, ensuring usability, and safeguarding information standards to strengthen user confidence.