INTRODUCTION

Satisfaction is an intangible, elusive, multifaceted concept with numerous meanings and applications, which can make it difficult to define.¹ The International Organization for Standardization² defined satisfaction as the extent to which a user’s physical, cognitive, and emotional responses that result from using a system, product, or service meet the user’s needs and expectations. When evaluating satisfaction in system assessments, different indicators are used to measure various aspects of a system, since what constitutes satisfaction to an individual or a group can be influenced by various interconnected factors.³ Some factors used in measuring satisfaction have included user preference for system features and functions.⁴ Other studies have sought feedback on the content, features, outcomes, or interactions with software, as well as an overall experience rating.⁵ Satisfaction has been conceptualized as the usefulness of EHR system templates, efficiency of practice workflow, information services support, number of logon events, and system speed.⁶ In this study, satisfaction is conceptualized based on several indicators, from system usefulness, information usefulness (relevance), information accuracy, and ease of retrieving information to interface quality, consistency of system interface, clarity of screen items (font size), flexibility, speed, and reliability.

The creation of useful systems has always been one of the primary goals of user-centred design and a measure of satisfaction.⁷ System usefulness is the extent to which the functions of a system enable users to complete a set of activities and achieve certain goals in a specific context. Also, information usefulness or quality as an indicator of satisfaction refers to the relevance and quality of the information generated by a system, which is determined by whether the information supplied or generated by an EHR system is fit for use.⁸ Additionally, in the use of software/systems, speed has become increasingly important. Users may be less satisfied and productive with long software/system response times.⁹ User dissatisfaction can lead to application abandonment, especially with discretionary applications like those accessible on the Internet.⁹ System reliability is the probability that a system will work as expected—correctly–over a given period with no repairs required or performed. If the system does not work correctly over a given time, users may be dissatisfied.⁹

According to the International Organisation for Standardisation (ISO) framework for information system success, user satisfaction is important and the success of an information system depends on it,² but Kaipio et al¹⁰ also noted that there is considerable variation in satisfaction levels with Electronic Health Record (EHR) systems between nurses and physicians. Those authors¹⁰ also showed correlations between physicians’ age, gender, practice type, and years of work experience with their satisfaction rates. In this study, we sought to analyze how other characteristics, such as level of education, duration of training, and computer efficacy, affected the satisfaction levels of health professionals who use the Lightwave Health Information Management System (LHIMS; Lightwave eHealthcare Solutions, Ghana) for healthcare delivery.

METHODS

Ethical clearance and approval letters for this study were obtained from the Ghana Health Service Ethics Review Committee (GHS-ERC:011/07/21) and Cape Coast Teaching Hospital-IRB (CCTHERC/EC/2021/095). The informed consent form distributed to all participants covered the study objectives, assured participants of anonymity and confidentiality, and emphasised voluntary participation with the freedom to withdraw at any point without consequence.

Study Design

This research employed a non-interventional descriptive cross-sectional study design to investigate health professionals’ satisfaction with their EHR system in the Central Region of Ghana. The study population was limited to health professionals who practice at facilities using LHMIS EHR for service delivery in the region. This section of health professionals was selected because they have been practicing with this specific EHR for service delivery at their various health facilities, so we could assume a baseline level of requisite knowledge of the EHR to provide valid responses about its usefulness.

Sampling Technique

A stratified probability sampling approach was used to select the health facilities included in this study. This method helped to identify and select homogenous subpopulations with potential respondents who were similar in age, sex, education, work experience, and professional characteristics. The potential study population included 1136 health professionals from 10 health facilities. Each of the 10 health facilities was regarded as a distinct stratum. This strategy allowed for an empirical examination of health professionals’ differences in EHR usage. The sample size was adequate for measuring a single proportion but not for group comparisons or other statistical techniques. The data collection process was meticulously planned in shifts–morning, afternoon, and night–to ensure total representation.

Data Collection

Data was collected via a questionnaire (Appendix 1) administered during an interview with each respondent. Trained research assistants (data collectors) administered the questionnaires through personal interviews with the participants. The questionnaire we developed for this study was modelled on questions used in standardised and validated scales, including the Computer System Usability Questionnaire (CSUQ) created by International Business Machines (IBM) and the IsoMetricsL scale.¹¹ The CSUQ has an overall coefficient alpha of 0.95 and consists of 19 items with a 7-point Likert scale and an option for “Not Available (N/A).”¹¹ The CSUQ has been utilised to evaluate physicians’ satisfaction with a designed EMR system.¹² Ten question items were adapted from the CSUQ, with questions 1, 3, 4, 5, and 6 from the original scale excluded from this study as they were irrelevant. The terms “system” or “computer system” in the questionnaire were replaced with “LHMIS,” the name of the EHR. This study evaluated only one EHR system; thus, the question items were carefully selected and reworded to fit current practices in Ghana. The final questionnaire was divided into two sections: the first section collected data on sociodemographic, professional characteristics, and general computing use; the second section gathered information on user satisfaction with the EHR.

Data Analysis

The 5-point Likert scale included the following categories: strongly disagree (SD), 1 point; disagree (D), 2 points; neutral (N), 3 points; agree (A), 4 points; and strongly agree (SA), 5 points. The weighted mean formula was used to calculate weighted average (WA) scores, which are mathematically written as WA=wx/ w, where w represents the weights and x represents the values. Principal component analysis was used as a dimension reduction technique to obtain a factor score for the dependent variable (efficiency) in the bivariate and multivariate analyses. The result was examined using the orthogonal rotation approach (Varimax) in the IBM Statistical Package for the Social Sciences (Version 24). The study also employed Brooke’s (1986)¹³ System Usability Scale to categorize the dependent variables to make the factor score reflect a natural setting. Respondents with a factor score of less than 30% were classified as low, those with scores above 30% but not more than 70% were defined as moderate, and those with a score of more than 70% were classified as high. This categorization made it possible to run an χ2 test for the bivariate analysis and ordinal logistic regression analysis for the multivariate using the proportion of odds (OR) to interpret the differences in the use of EHR.

RESULTS

Of 1136 potential respondents, 1126 participated in the study, with the response rate of 99.1% attributed to multiple reminders and assistance from trained data collectors. The Kaiser-Meyer-Olkin measure of sampling adequacy was greater than 0.5 for all measured constructs. Bartlett’s sphericity test was significant (p=0.05), and the construct’s eigenvalue was greater than 1, accounting for more than 50% of the variance in every construct with individual item loads greater than 0.4.

Table 1 presents the demographic data of respondents. As shown in Table 2, the majority of respondents expressed satisfaction with several aspects of the EHR system. They rated the system highly for its ability to quickly gather information (3.51), reliability (3.46), ease of retrieving information (3.51), system flexibility (3.62), and accuracy (3.72). Additionally, respondents were satisfied with the EHR’s usefulness and quality (3.72), consistent interface (3.74), quality design (3.70), and speed during task execution (3.71). Respondents also reported being satisfied with the clarity and arrangement of items on the interface; this aspect had the highest mean satisfaction score (3.80).

A chi-square test evaluated how socio-demographic factors influenced satisfaction with the EHR. No statistically significant link was found between gender and satisfaction (χ2 (2, N=1126) = 3.29, P = .192). However, more female respondents (n=221, 32.0%) reported being very satisfied compared to male respondents (n=117, 26.9%). Age did not significantly impact satisfaction (χ2 (4, N=1126) = 5.379, P = .251). Satisfaction levels were consistent across age groups: 20–29 years (26.8%), 30–39 years (28.4%), and 40 years or older (27.8%). Educational qualifications had a significant impact (χ2 (4, N=1126) = 12.77, P = .012). Respondents with diplomas were the most satisfied (n=163, 35.7%), followed by certificate holders (n=38, 29.2%), while degree holders were the least satisfied (25.4%). For work experience, a statistically significant association was observed (χ2 (4, N=1126) = 14.02, P = .007). Respondents with over six years of work experience were the most satisfied (n=86, 36.3%), while those with less than a year of experience were the least satisfied (n=93, 25.4%).

Table 4 demonstrates how professional roles and training influenced satisfaction. For professional roles, a statistically significant relationship emerged (χ2 (4, n=1126) = 13.13, P = .011). Nurses and midwives reported the highest satisfaction (n=242, 33.2%), followed by auxiliary staff (n=41, 29.1%) and prescribers (n=54, 21.3%). No statistically significant link was found between training institutions and satisfaction (χ2 (2, n=1126) = 1.96, P = .375). Still, university-trained respondents reported slightly higher satisfaction (n=153, 30.8%) than those trained in professional institutions (n=185, 29.4%).

Table 5 highlights the effect of EHR training, which had a statistically significant association with satisfaction rates (χ2 (2, n=1126) = 10.38, P = .006). Surprisingly, respondents without training were more satisfied (42.6%) than those who received training (28.5%). Satisfaction was not significantly influenced by training duration (χ2 (6, n=1126) = 6.60, P = .360). However, those trained for 5 or more days were the most satisfied (35.0%), while those trained for 3–4 days were the least satisfied (27.4%). Computer proficiency strongly influenced satisfaction (χ2 (2, n=1126) = 16.93, P < .001). About a third of advanced users were very satisfied (n=291, 32.8%), while fewer beginners were very satisfied (n=47, 19.6%).

We applied ordinal logistic regression models to further explore predictors of satisfaction. In model 1, educational qualification and work experience significantly predicted satisfaction (P<0.05). Age and sex had no predictive value and were excluded. In Model 2, after controlling for education and work experience, the professional role showed significance but was dropped due to multicollinearity. Training before EHR use significantly predicted satisfaction (P<0.05). Model 3 included education, work experience, training status, training duration, and computer efficacy. Key findings included education, where diploma holders had higher odds of satisfaction than degree holders (OR = 1.39, 95% CI = [1.098–1.766]). Respondents with six or more years of experience were significantly more satisfied than those with 1 year or less (OR = 0.568, 95% CI = [0.420–0.768]). Those who received training had lower odds of satisfaction than those who did not (OR = 0.652, 95% CI = [0.454–0.937]). Advanced users were significantly more satisfied than beginners (OR = 0.77, 95% CI = [0.588–1.00]).

DISCUSSION

The digitization of patient information through Electronic Health Records (EHR) has been driven by advancements in information technology aimed at optimizing data management and retrieval processes.¹⁴ The findings of this study indicate that EHR facilitates the quick collection of patient data while offering system flexibility in usage and accuracy. This observation corroborates findings from Menachemi and Collum,¹⁵ which indicated that EHRs can lead to improved clinical outcomes, such as enhanced quality of care and reduced medical errors, as well as organizational benefits like increased efficiency and financial gains. The present study showed that healthcare professionals perceived the EHR system to quickly gather information and be reliable, flexible and accurate, which may contribute to continued adoption and integration into clinical workflows.

Our results indicated that the sex of health professionals did not affect their satisfactory use of the LHIMS. Male and female respondents had similar satisfaction rates with the EHR. However, a previous study by Khairat et al¹⁶ found that sex was a determinant of satisfaction with the use of EHR systems. In their research, that female participants were consistently and substantially more satisfied than male participants with the amount of effort necessary to obtain information and accomplish EHR activities.¹⁶ Female participants also had greater satisfaction with the usability, complexity, and burdensomeness of EHRs.¹⁶ However, that study also found that other factors, such as familiarity with digital systems, frequency of use, and role-specific requirements, played a more substantial role in determining user satisfaction.¹⁶

Our results indicated that training does not necessarily lead to higher satisfaction levels. This counterintuitive finding could suggest that formal training programs do not always address user needs effectively or that self-learned users may have adapted better to the system. Similar studies have reported mixed outcomes regarding the effectiveness of training on EHR satisfaction. For instance, a study by Harris et al¹⁷ found that while training improved initial adoption, it did not necessarily translate into higher long-term satisfaction. Nguyen et al¹⁸ highlighted that training must be tailored to user-specific workflows to have a meaningful impact. These findings suggest that healthcare institutions should prioritize training programs that focus on practical, scenario-based learning rather than simply extending the training duration. Moreover, organizations should consider a blended learning approach that includes self-paced digital resources, peer mentoring, and just-in-time training sessions to enhance learning effectiveness and satisfaction.

Computer efficacy was found to be a highly significant predictor of satisfaction (p = 0.000). This finding aligns with studies that emphasise digital literacy as a key determinant of successful EHR adoption. Research by Alkureishi et al¹⁹ found that healthcare professionals with higher computer literacy experienced fewer usability challenges and reported higher satisfaction with EHR systems. Similarly, a study by Mensah et al²⁰ noted that EHR satisfaction improves when users possess advanced digital skills, enabling them to navigate the system more efficiently and integrate it into their workflow. These findings suggest that targeted digital literacy initiatives should be a core component of EHR training programs to enhance usability and overall user experience. Furthermore, health institutions should conduct regular assessments of users’ digital competencies and provide personalised support to address skill gaps, ensuring that all users, regardless of expertise, can effectively utilize EHR systems.

Our findings also revealed that professional type had no significant effect on health professionals’ satisfactory use of EHR systems. This may be a result of the different information needs that these categories of health professionals require from EHR systems. Kaipio et al¹⁰ found that professional type had no significant effect on health professionals’ satisfaction with the use of EHR. In their research, doctors were more satisfied with the EHR systems’ technical quality and learnability, while nurses were more satisfied with the convenience of use and the ability to collaborate with EHR. Bani-Issa et al²¹ found that physicians were found to be the most satisfied with the use of EHRs, while nurses were more satisfied with the influence on drug administration than any other healthcare professional. Grouped together, the results of their research also suggest that healthcare professionals are typically pleased with EHR systems as a daily element of their clinical practice, as reflected in results from our respondents. Therefore, while professional roles may dictate specific usage patterns, the overall perception of EHR remains positive across different healthcare providers, reinforcing the importance of system adaptability and user-centered design.

One of the strengths of our study is its comprehensive evaluation of various factors affecting EHR satisfaction, including training, digital literacy, and professional role. Our population included a diverse sample of healthcare professionals, providing a well-rounded perspective on EHR adoption. As far as limitations, our study was cross-sectional and did not establish causal effects between variables conclusively. We also did not explore external factors such as technical support availability, system customization, or financial constraints that may influence user satisfaction.

CONCLUSIONS

Our study examined some critical factors influencing EHR satisfaction among healthcare professionals, including training, digital literacy, and professional role. Our findings highlight that training, while necessary, must be tailored to individual user needs rather than simply increasing its duration. Digital literacy also played a pivotal role in ensuring effective EHR use, with advanced users reporting greater satisfaction. Healthcare institutions should prioritise a multi-faceted approach to EHR implementation that includes adaptive training programs, continuous digital literacy development, and workflow-specific support mechanisms. Additionally, the generally positive perception of EHR systems across various professional roles indicates the importance of system adaptability and user-centered design. Future research should explore long-term EHR adoption trends, usability to improve the effectiveness of digital healthcare solutions. Longitudinal research may be needed to assess how satisfaction evolves with continued EHR use.

Data Availability

The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.

Disclosures

The authors have nothing to disclose.

AUTHOR CONTRIBUTIONS

Conceptualization: Emmanuel K. Achampong (Lead), Edward Agyemang (Lead), Kobina Esia-Donkoh (Supporting), Addae Boateng Adu-Gyamfi (Supporting). Supervision: Emmanuel K. Achampong (Lead), Kobina Esia-Donkoh (Lead), Addae Boateng Adu-Gyamfi (Lead). Writing – original draft: Emmanuel K. Achampong (Lead). Writing – review & editing: Emmanuel K. Achampong (Supporting), Edward Agyemang (Supporting), Kobina Esia-Donkoh (Supporting), Addae Boateng Adu-Gyamfi (Supporting). Methodology: Emmanuel K. Achampong (Supporting), Edward Agyemang (Lead), Kobina Esia-Donkoh (Supporting), Addae Boateng Adu-Gyamfi (Supporting). Investigation: Edward Agyemang (Lead). Data curation: Edward Agyemang (Lead).

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

APPENDIX 1. STUDY QUESTIONNAIRE

Section One: Socio-Demographic Characteristics

Section Two: Satisfaction

Please, on a scale of 5; where:
1= “Very Dissatisfied”, 2= “Dissatisfied”, 3 = “Neutral”, 4 = “Satisfied” and 5 = “Very Satisfied; Rate the following statements on your satisfaction with the use of LHIMS for health service delivery at your facility.