Electronic medical record system user satisfaction and its implications for individual work performance: The case of a university teaching hospital in Rwanda

Electronic medical record system user satisfaction and its implications for individual work performance: The case of a university teaching hospital in Rwanda | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Electronic medical record system user satisfaction and its implications for individual work performance: The case of a university teaching hospital in Rwanda Evode Uwamungu, Alpha Arsene Marara, Emmanuel Munyaneza, Joel Pinney This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4206008/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Information system user satisfaction has been extensively documented as a key component and a surrogate of success and a determinant of individual and organizational performance. However, most related studies have focused on measuring user satisfaction and its impact through mathematical models, which might not exhaustively capture the issues affecting user satisfaction and performance. This study was conducted at the “Centre Hospitalier Universtaire de Kigali”, one of the two tertiary public and university teaching hospitals in Rwanda. This hospital has been implementing OpenClinic as an electronic medical record system since 2007, and few studies have focused on its evaluation. In addition, no study has focused on understanding the implications of user satisfaction for individuals’ work performance in this hospital. This study was cross-sectional mixed research using an explanatory embedded design. The data were collected from a convenient sample of OpenClinic users through questionnaires, which included closed- and open-ended questions, to capture both quantitative and qualitative data. The OpenClinic user satisfaction was high (91%), as was the proportion of users who perceived it as having a positive impact on their work performance (94%). The relationship between user satisfaction and perceived impact was statistically significant, and satisfied users were 20 times more likely to perceive that the impact was positive than unsatisfied users. Important concerns were expressed by users, and the main concerns were the poor functionality of the system due to unstable internet, the limited capacity for use and the scarcity of computers. Therefore, the implementation of the Electronic Medical Record system at the hospital has been successful, and user satisfaction has led to a perceived positive impact; however, further improvements are needed for optimal success. The inclusion of a qualitative component in future studies is recommended for a better understanding of IS success. Medical Informatics Electronic Medical Record System Open Clinic Management Information System User satisfaction Individual work performance Figures Figure 1 Figure 2 Figure 3 I. Introduction 1.1. Background Many developing countries suffer from a lack of or poor use of healthcare Management Information Systems (MIS) [1]. The purpose of MIS in healthcare settings is to improve efficiency and service delivery to patients to achieve positive outcomes, including saving lives [2]. However, achieving that purpose is not straightforward because many systems fail [3] [4] [5]. The successful implementation of information systems (ISs) requires recurrent and rigorous evaluations that inform the decision making and actions of organizations [6]. Many researchers have identified information system (IS) user satisfaction as a key component of information systems’ success in achieving organizational goals [6]. In Rwanda, the “Centre Hospitalier de Kigali (CHUK)”, one of the two first-level public university teaching hospitals in the country, is a tertiary hospital providing healthcare services to thousands of people annually, including those who are self-referred and those who are transferred from different hospitals across the country. This hospital has been among the few pioneers in Rwanda for implementing Openclinic as a healthcare MIS since 2007 [1]. This system is currently used by more than 800 healthcare providers, including physicians, nurses, allied health professionals, and finance department staff. Nevertheless, only one study has focused on its evaluation [7]. In addition, no study has focused on understanding the implications of user satisfaction for individual work performance to determine the extent of success or failure or to inform hospital leaders of necessary improvements that would eventually lead to increased outcomes of patient care. Therefore, this study intends to fill this gap by assessing user experience in terms of satisfaction with using OpenClinic and evaluating its impact on work performance. The results of the study can inform hospitals on the interventions needed to ensure successful adoption of MISs and improve the services provided to patients. 1.2. Study context and relevance Information system (IS) user satisfaction has been documented as a key indicator of IS success, and extensive quantitative studies have been conducted in many countries to understand the factors associated with this satisfaction. However, such studies have rarely been conducted in Rwanda, especially in healthcare settings. In addition, few qualitative studies have been conducted to deepen the understanding of the lessons learned and issues associated with user satisfaction. In particular, no assessment has been conducted on the user experience of OpenClinic at the CHUK for the past 7 years to inform its leadership on necessary improvements for increased patient benefit. This study closes the explained gaps in the following way. First, it adds to the literature on issues affecting IS user satisfaction and work performance. Second, it enables hospital leaders to determine the level of satisfaction as a key component of successful implementation of their healthcare system. Third, for staff who are dissatisfied or for whom the system negatively affects their work performance, leaders are informed of the reasons for dissatisfaction, which might help in planning remedial. 1.2. Research objectives, hypotheses and questions The aim of this study was to assess the level of user satisfaction with an electronic medical records system (OpenClinic) provided by healthcare service providers at the CHUK and its implications for their work performance. The specific objectives are as follows: To determine user satisfaction with OpenClinic in the hospital setting; To identify drivers and key issues that affect user satisfaction; To evaluate the perceived impact of OpenClinic on the work performance of the users; To provide recommendations on improvements needed for increased satisfaction and performance. Therefore, this study focuses on the following research hypothesis and questions. Research Hypothesis OpenClinic user satisfaction has a positive relationship with individual work performance. Research Questions What is the level of OpenClinic user satisfaction by healthcare providers in the CHUK? What are the triggers and key issues that affect user satisfaction? How does user satisfaction affect individual work performance? What improvements need to be made to ensure successful implementation of the system and its impact on work performance? II. Literature Review Currently, information systems constitute an essential component of organizational management for improving efficiency and performance. However, many systems fail to achieve the expectations of their users, which negatively impacts individual and organizational performance [3] [4] [5]. Therefore, the need for research on the successful operationalization of information systems emerged from these challenges and still continues to be an important subject of inquiry [6]. Thus, the evaluation of an IS being operationalized is a worthwhile undertaking to ensure its success and benefits [7]. One of the key aspects of IS success is the perceived satisfaction of its users [6]. 2.1. IS user satisfaction as a measure of IS success The IS user satisfaction reflects the degree to which a user feels that an IS meets his needs and expectations [8]. IS user satisfaction has been considered an important element or even a surrogate of an information system’s success, especially when the use of MIS is mandatory for work [9] [7]. This assertion stems from the fact that users interact with an IS and know its functionality strengths and weaknesses, thus playing the role of evaluators [6] [10]. In addition to these intuitive findings, extensive studies have been conducted that have shown a correlation between user satisfaction and IS success [10]. Therefore, as measuring IS success is difficult, satisfaction is usually used as a proxy for IS success [11] [12]. 2.2. Factors affecting user satisfaction A variety of models have been developed to understand the factors that affect user satisfaction with an IS. Among these, the most widely used are the DeLone and McLean (D&M) original and revised multidimensional and interdependent construct models [13] [7] [14]. According to the updated D&M model, user satisfaction has been theorized to be associated with system quality, information quality and service quality [14] [15]. The model stipulates that the quality dimension of an IS has a positive effect on its use or intention to use and on its user satisfaction, which in turn brings about IS benefits, as shown in Fig. 1 below [14]. According to the D&M model, system quality reflects the aspects of usability, availability, reliability, adaptability and response time; information quality relates to interface content issues, including personalization, completeness, relevance, ease of understanding and security; service quality is concerned with support provided to users, whether coming from internally or externally to the organization; use measures the aspects of navigation, retrieval of information and execution of operations; user satisfaction captures users’ opinions through their experience while interacting with the system; and finally, net benefits direct them to impacts, whether they are positives or negatives [14] [15]. The model suggests that the results of IS quality are iteratively interrelated [14]. In fact, system use must precede user satisfaction, but a good experience of use (user satisfaction) can also lead to the intention to use the system [7] [14] [15]. On the other hand, system use and user satisfaction result in net benefits, but these net benefits also result in intention to use and user satisfaction [14]. A variety of empirical studies have been conducted to validate the D&M IS model. Most of these studies used a quantitative design and revealed significant relationships between the quality of IS and user satisfaction as well as a positive relationship between user satisfaction and IS benefits [16] [17] [18] [19] [20] [21] [22]. The D&M IS model was criticized for its difficulties in application due to the different contexts of IS research, modeling processes with causal explanations resulting in confusing meanings, and limited coverage of dependent variables, as there are many other possible categories of measures varying from user to user [23] [14] [15] [10] [24] [25]. Thus, a variety of other IS success models have been proposed, and others have surged, including the technology acceptance model, human-organizational-technology and fit model, technology-organization-environment model, and innovation dissemination theory [13] [7] [26]. 2.3. Other main models of IS success a. Technology acceptance model (TAM) According to this model, IS success is characterized by the extent of user acceptance measured through actual use, while the underlying factors of that acceptance are perceived usefulness and perceived ease of use [27] [28]. The mode defines perceived usefulness as the extent to which users believe the information system is important for helping them complete their job requirements, while perceived ease of use is defined as the extent to which users believe the system is used without effort [27]. The model recognizes that these two factors are influenced by external factors, which can include social, cultural and political factors [27] [29]. As illustrated in Fig. 2 below, the model stipulates that perceived usefulness and ease of use influence attitudes toward the use of technology and that those attitudes influence intention to use the technology, whereas that intention leads to the actual use of technology [27]. Many studies have been conducted to validate the TAM, highlighting the significance of the relationship between perceived usefulness and perceived ease of use on technology acceptance [28] [29]. However, there have also been a high number of studies in which the findings did not fit the TAM model [30]. b. The human-organizational-technology (HOT) fit model The HOT fit model assumes that the effectiveness of an IS depends on the alignment of human factors, organizational structures and technology, with the purpose of understanding IS success through complex interactions between people, organizations and technology [31]. Human attributes reflect individual characteristics and interactions, such as knowledge, skills, capabilities, motivation, position, tasks, collaboration, communication, competition and supervision; organizational structures encompass internal and external organizational management environments and traits, such as organizational size, culture, policies and strategy, practices and government regulations; and technology relates to IS characteristics and requirements, such as software, hardware, network tools, professional skills, systems quality, information quality, service quality and social presence [31]. Numerous studies have been conducted with hypothetical assumptions based on the fact that when an information system is well aligned with individual attributes, organizational management practices, as well as the technological equipment and tools in place, lead to higher user satisfaction, increased productivity, and improved system performance [32] [33]. Thus, the underlying technology adoption factors highlighted in these studies include (i) training, perception, roles, skills, clarity of system purpose and user involvement as human attributes; (ii) leadership and support, process, participation or user involvement, internal communication and inter-organizational systems as organizational factors; and (iii) ease of use, system usefulness, system flexibility, time efficiency, information accessibility and relevancy as technological factors [32] [33]. However, the literature emphasizes the necessity for constant realignment of HOT components [31]. In fact, the alignment has to be dynamically adapted due to constant technological changes and evolving needs of the organization [31]. The literature also highlights the nuances and complex interactions between HOT components and recommends further research to explore those interactions as well as their implications for emerging technologies and workplace dynamics [31] [34]. c. The Technology-Organization-Environment (TOE) model The TOE model focuses on technological, organizational and environmental factors for modeling technology adoption and innovation within organizations [35]. Technological factors capture the key characteristics of the technology under consideration, including the complexity of the technology and its compatibility with existing systems [36] [37]. Technological factors cover the internal characteristics and capabilities of an organization, such as the organization's absorptive capacity, leadership and innovation culture [36]. The environmental factors include the elements that are external to the organization but crucial in shaping technology adoption in an organization, such as industry regulations, pressure from competitors and market trends [36]. Studies have shown the relevance of the TOE model, highlighting specific elements that influence technology adoption, such as connectivity, IT capabilities and management support [36] [37]. d. Innovation dissemination theory (IDT) The IDT theory explains the success of an information system in terms of gradual technology adoption. According to this theory, the extent of technology adoption passes through a diffusion process and communicates over time through members of an organization [38]. In the context of an IS, an innovation is defined as a technology that is perceived as new by its users, even if it has long been on the market, and it is manifested through their knowledge, persuasion and decisions [38]. Thus, the key point of the IDT model is to achieve convergence in understanding and adopting technology through a framework of information sharing where change agents and opinion leaders can significantly influence desired practices [38] [39]. This state of adoption depends on five main factors: perceived attributes of innovation, type of innovation decision, communication channels, nature of the social system, and extent of promotion agents’ efforts [39]. 2.4. User satisfaction and individual performance The measurement of net benefits in terms of individual or organizational impact, as a result of system quality, use and user satisfaction, has been advocated. For instance, D&M has advocated for this measurement, cautioning researchers not only to limit their investigations on use and user satisfaction as measures of IS success but also to extend them toward the benefits realized in terms of performance [14]. Therefore, measuring the impact of user satisfaction on individual work performance is essential and adds value to the literature on IS success. The impact of IS on individual performance is defined as the extent to which the individual perceives the level of productivity due to the use of IS [40]. While many studies have shown that IS use has a positive impact through increased quantities and quality of productivity, other studies have indicated that it has a negative or neutral impact on individuals’ performance and social life [8] [40] [18] [41]. 2.5. Critical analysis and conclusion The D&M and subsequent models intended to associate IS qualities with user satisfaction or technology adoption in terms of causal relationships between dependent and independent variables. However, the intuitive nature of the relationship is internal rather than external. When a user appreciates positively or expresses difficulties with an aspect of an IS quality or use, such as ease of use or usefulness of the information generated by an IS, this is a means of expressing his satisfaction or dissatisfaction with the IS use or usefulness. Therefore, this study will focus on understanding the reasons for, issues and challenges related to a certain level of satisfaction rather than understanding it in terms of correlation and causality. Most of the studies conducted have been quantitative and have explored the relationship between user satisfaction and IS quality through a number of dependent and independent variables [15]. However, understanding the challenges and issues associated with user satisfaction might not be limited to parametric models and predefined variables [14] [24]. In addition, there is divergence in how IS quality variables are measured, and critics of their reliability exist [8]. This implies that studies must give the flow to users to express their concerns as measures of IS qualities. Thus, this study will integrate a qualitative component that will further the understanding of the issues of healthcare providers while using the system. Therefore, the D&M model and other models that subsequently emerged were adapted to the conceptual framework of this study, as shown in Fig. 3 . D&M recommended that researchers select a small number of measurements while using their model [14] [15]. However, many of the quantitative studies conducted generally use long questionnaires, and many questions have similarities, which can lead to confusion in distinguishing variables [13] [14] [15] [19] [20] [42]. This study used a concise questionnaire with a single question addressing user satisfaction and another one addressing the perceived impact of user satisfaction on work performance. In this study, the aspects of IS qualities and other issues characterizing user satisfaction and how they affect individual work performance were obtained through qualitative questions. This enables discerning user judgments, avoiding a blurt in expressing their experience and allowing the flow of the expression for the qualitative component of the questionnaire. 2.6. Summary and gaps in the literature The D&M model has been essential for explaining IS success through user satisfaction and quality characteristics. Following the criticisms of the D&M model, further studies have been conducted through a variety of other models and elaborate other factors that affect IS success, including perceived ease of use and usefulness of IS, trustworthiness, top management support, design of user requirements, training, computer literacy, organizational structure and management style [26] [27] [28] [29] [30]. Despite a multitude of those models, no one is claiming to exhaustively explain all the elements of an IS success. However, qualitative studies can effectively capture a wide range of IS characteristics underlying the status of IS success, taking into account the specificity of organizations, but this approach has yet to be explored. Thus, this study uses a mixed research approach to take advantage of the benefits of both quantitative and qualitative approaches for analyzing the extent of an IS success as well as the underlying issues in the context of a specific hospital. III. Methodology 3.1. Study design This study used a cross-sectional mixed research method with an explanatory embedded design to obtain a deep understanding of key issues affecting OpenClinic user satisfaction and individual performance. Quantitative studies have been useful and extensively used in studies exploring information systems success but have been criticized for their underlying assumptions [43]. However, qualitative studies are lacking, yet they have been advocated for due to their strengths in identifying virtues in their natural state with little or no assumptions [43]. The combination of qualitative and quantitative approaches is necessary for studying information systems success. Some of the key benefits of that combination are as follows: the value of combining qualitative and quantitative methods is superior to using one of them; it enables accounting for context-specific nature and practices in organizations rather than relying on standard context-independent variables and assumptions; it takes into account the natural process experienced by users while evaluating information systems; it can capture the multidimensional relationships between an IS and user perceptions rather than unidirectional assumptions; and it enriches the knowledge by bringing in diversification in system research [44] [43]. As a consequence, this study opted to integrate the two approaches to take advantage of each of them. The purpose of the quantitative component was to measure the level of OpenClinic user satisfaction, the level of its perceived impact on individual work performance, and the relationship between user satisfaction and perceived work performance [45] [46]. On the other hand, the qualitative component was aimed at providing more explanations of issues affecting user satisfaction and its impact on individual work performance [43]. 3.2. Sample selection The sampling frame of this study was the list of staff who use OpenClining at the CHUK. A convenient sample was used for this study, which was spread across service departments of the hospital and covered the main categories of healthcare professionals administered by the hospital, including physicians, nurses, allied health professionals and administration staff. This sampling approach has proven to be effective in exploring information system success [47]. 3.3. Data collector and collection procedure The data were collected personally by the principal investigator. Prior to data collection, an appointment was requested during the departmental staff meetings, and the data were collected during those meetings with the flexibility to submit the questionnaire after the meeting. During the data collection, the investigator provided the questionnaire and explained the study to the participants, ensuring that they understood its importance and agreed to participate voluntarily. Thereafter, the participants who agreed to participate in the study signed a hard copy of the concert form and responded to the self-registered questionnaire. 3.4. Data collection, entry and analysis tools A self-registered questionnaire was used to collect data from the participants (Ref. Appendix 2 and Appendix 3). This questionnaire was designed specifically for this study based on the research questions. The first section of the questionnaire consisted of closed questions inspired by the Likert measurement framework and was focused on collecting quantitative data [49]. The second section of the questionnaire consisted of open-ended questions and was focused on qualitative data. The electronic Epi-Info data entry platform was used for the data entry of quantitative data, while MS-Excel was used for the transcription of qualitative data. The quantitative data were analyzed using “R” software, whereas the qualitative data were analyzed using “NVivo 12” software. 3.5. Data analysis techniques The quantitative data were analyzed using descriptive statistics and statistical tests, including the chi-square test, Fisher’s exact test and the Wald test. The descriptive statistics provide the proportions of user satisfaction and the perceived impact of the system. The chi-square test provides the significance of the relationship between user satisfaction and the perceived impact of the system. Fisher’s exact test was used for reconfirming chi-square findings due to the presence of low absolute numbers of dissatisfied users and for determining the magnitude of the relationship. In addition, the Wald test was used to determine the magnitude and significance of the relationship between user satisfaction and the perceived impact of the system and to evaluate the consistency of the previous results. The analysis of user satisfaction and perceived impact through demographic variables was not performed due to the presence of empty or very low numbers of dissatisfied cross-tabulated cells. The qualitative data were analyzed using content analysis. The participants’ expressions were grouped and coded into themes and subthemes during the process of analysis using NVivo12. When the expressions did not match or elaborate upon the related theme, clarifications were sought from the participants. IV. Demographic Findings 4.1. Sample distribution by major categories of participants The sample frame obtained from the Human Resources Office of the CHUK consisted of 832 OpenClinic users, including 529 nurses, 80 physicians, 157 allied health professionals and 66 administrative staff. The data collection was conducted during August and September 2023, targeting the representativeness of users from all four professional categories and all departments of the hospital. The self-registered responses were obtained from 217 participants who were subdivided as follows (ref. Table 1 ): Table 1 Distribution of users and sample by major categories of health professions Categories of staff # All users Sample Nurses 529 133 Physicians 80 41 AHPs 157 25 Administrative staff 66 18 Total 832 217 4.2. Sample distribution by age categories of participants The majority of the sample participants were aged between 30 and 39 years (46%), followed by 35% aged 40 and 49 years. Sample distribution by age categories Age category Number Percentage 20 - 29 years 20 9% 30 - 39 years 99 46% 40 - 49 years 77 35% 50 - 59 years 18 8% 60+ years 1 0% Missing 2 1% Total 217 100% 4.2. Sample distribution by age, years of job experience and years of experience using OpenClinic Most of the sample participants had many years of job experience, including 78% who had more than 5 years of experience. On the other hand, the majority had between 1 and 45 years of experience using OpenClinic (41%). The proportions of participants with age ranges of use experience between “6 to 10 years” and “11 to 15 years” were also high, representing 29% and 23%, respectively. Sample distribution by years of professional experience and years of experience using OpenClinic Category of years Job experience Experience with OpenClinic 20 years 16% 0% Total 100% 100% V. Analysis and Results 5.1. Overall user satisfaction Most users (91%) were satisfied with the electronic medical records system (OpenClinic) during their service delivery, including 28% who indicated their satisfaction as “very satisfied” and 63% as “satisfied”. Nine percent (9%) were not satisfied, including 5% who were neutral (neither satisfied nor dissatisfied), 2% who were dissatisfied and 2% who were very dissatisfied. Number and percentage of respondents per their level of satisfaction according to the Likert scale Likert scale satisfaction level Number Percentage Very satisfied 61 28% Satisfied 136 63% Neutral 11 5% Dissatisfied 4 2% Very dissatisfied 5 2% Total 217 100% 5.2. Sources of satisfaction : A high proportion of respondents (95%) expressed at least one cause of satisfaction. The sources of satisfaction expressed and percentages of respondents who expressed that satisfaction are the following: The importance of its functionalities (83%) was as follows: respondents were satisfied with the system functionalities, which helped them store, archive, access and retrieve patient data easily, bill care services provided to patients, generate codes for patient files useful for their classification, quickly access diagnostic results, including laboratory and imagery results; ensure security and long-lasting data; and provide reliable and accurate information. Facilitation and simplification of the work (32%): The system facilitated and simplified the work, including communicating and sharing information, which has become easier; reducing movements between departments and accessing the archive, which is looking for patient information and diagnostic results; reducing written work; and easing workload by reducing the amount of time that one spends performing operations such as billing calculations and facilitating requests for supplies. Time management (22%): The system allowed users to manage their time efficiently by saving their time while looking for information and caring for patients. Ease of use (14%): Participants described the system as user friendly or not complicated and not requiring special skills. Service digitalization (13%): This satisfaction occurred because healthcare services were digitalized and service procedures were shifted from traditional paperwork toward a modern paperless work environment. Some of the users also see the system as an opportunity to familiarize themselves and to increase their skills with the use of technology. Quick performance (11%): The system was described as having a high speed in performance and not taking much time to respond to user requests. Data protection and confidentiality (5%): These users were confident that records are safely kept and archived electronically within the system that is protected by usernames and passwords and that those records cannot be changed. 5.3. Sources of dissatisfaction Despite the high percentage of users who expressed their satisfaction, a high percentage (98%) also expressed one or more issues resulting in their dissatisfaction. The main issues for dissatisfaction and the percentage of respondents who addressed those issues are as follows: Poor functionality or dysfunctionality due to an unstable network or electricity (57%) Limited capacity for use due to lack or insufficient training (44%) Insufficient computers (22%) Impossibility or difficulty editing and correcting errors (17%) time-consuming system, adding more workload to their already usual high workload (17%) Partial digitalization, which results in double work, using both paper files and the system (16%) Patient information was collected when all users could access patients’ confidential data (9%). Incomplete or incorrect diagnosis service coding (8%) Missing information in the system (7%) Frequent password expiration (6%) Inability to generate a performance report (6%) Errors in records (4%) Challenging management of patients’ identification with patients having 2 or more identifications and patients’ addresses section not well ordered (3%) The system allowing changing information to be entered by others (2%) Lack of extension to and interoperability with the systems at district hospitals (2%) Ineffective use where some staff do not comply with standard use procedures and leave incomplete data (2%) Loss or mismatch of data (2%) No access to some information (2%) The use of desktops fixed at the designated place and care givers are obliged to make frequent movements to access the system (2%). For example, the system may refuse to output supplies already available in stock or refuse other operations, which would simplify the work (1%). Inability to work with multiple files at a time on the computer (1%) There was a lack of search options, for example, when performing investigative procedures or during the validation of laboratory results (1%). Sometimes the system crushes (1%). Over reliance on automation, which raises skeptics (1%) Scattered and unintegrated registers that cause multiple entries of similar information into the same patient, especially in the laboratory department (1%). Health risks such as eye problems due to longer exposure to computers (1%) Not respecting guide in attributing credentials (1%), and There was poor communication between clinicians and cashiers (1%). 5.4. Perceived impact of OpenClinic on work performance a. Overall perceived impact : Most users (94%) perceived the system to have a positive impact on their work performance, including 25% who rated the impact as “very positive” and 69% as “just positive”. Six percent (6%) were not satisfied, including 4% who were neutral (seeing the impact as neither positive nor negative), 1% who considered its impact to be negative and 1% who considered it to be very negative. Number and percentage of respondents per level of perceived impact according to the Likert scale Likert scale satisfaction level Number % Strongly positive 53 24% Positive 150 69% Neutral 8 4% Negative 3 1% Strongly negative 3 1% Total 217 100% b. Perceived positive impact : The improved efficiency and effectiveness of service delivery were seen as a positive impact induced by the use of the system. Specifically, the main benefits expressed by the users and the percentages of respondents who expressed that benefit were that the system: Enhance quick service performance and delivery (22%); Helps in providing good (quality) services, especially reducing patient waiting time (9%) improving the quantity of work performed by serving more clients (7%); improving income generation through the increased number of clients served and revenue recovery (4%); improving efficiency in the use of resources such as minimizing paper files and archive space, abolishing printings of patients’ results, better control of healthcare supplies’ requests and use and human resources management though evaluation of clients served (2%) Helps to ensure continuity of care based on the history of the patient who is kept for a long time and easily accessible (2%). c. Perceived negative impact : The negative side of the impact was expressed to a limited extent (18% of the respondents) as delays in service delivery, mainly due to the interruption of work caused by the loss of internet connections, limited capacity for use, insufficient equipment and high workload. 5.5. User satisfaction and individual work performance To analyze the relationship between “user satisfaction” and “perceived work performance”, the original variables were transformed as follows: For user satisfaction, those who scored “very satisfied” or “satisfied” were assumed to be both “satisfied”, while those who scored “neutral”, “dissatisfied” or “very dissatisfied” were assumed to be “not satisfied”. For the impact on work performance, the “very positive and positive” scores were rescored as “positive”, while the “neutral, negative and very negative” scores were rescored as “not positive”. Thus, the results of this transformation provided the contingent table presented below with the numbers of respondents per new category of user satisfaction and perceived work performance. Number of respondents per user satisfaction and perceived work performance User satisfaction Impact on individual work performance Positive Not positive Total Satisfied 191 6 197 Not satisfied 12 8 20 Total 203 14 217 The chi-square test, Fisher’s exact test and Wald test were performed to analyze the significance and strength of the association between user satisfaction and perceived work performance (ref. Appendix 1). Both chi-square and Fisher tests confirmed the significance of the association, with p values less than 0.001, whereas the Fisher and Wald tests indicated a high strength of association through odds ratio values. Fisher’s test odds ratio was 20.5 (CI: 5.3 85.1), while the Wald test odds ratio was 21.2 (CI: 6.3, 71.1). Thus, the respondents who were satisfied were 20 times more likely to have a positive perception of the EMR (OpenClinic) on their work performance than were those who were not satisfied. 5.5. Recommended improvements for reviews and actions Based on the sources of dissatisfaction and expressed needs of the system users, the following are the recommendations for consideration by hospital leaders to improve their satisfaction and increase their productivity: Provide sufficient and continuous training on OpenClinic to increase knowledge and skills on the use of the system; Ensuring strong, stable and permanent internet connections; Increase the number of computers until users can have timely access without any waiting time; Fully digitalize healthcare services and eliminate the double workload of using both computer- and paper-based files during the process of patient care; Ensure a complete and correct coding of services based on the standard coding procedure; Assess the possibility of enabling the system to work offline or through an intranet and avoid disruption of care once the internet and electricity are lost; Integrate functionality to enable editing or deleting errors within a reasonable time; Integrate functionalities for ensuring patient data protection and confidentiality by tightening access to the relevant content by authorized users; Review the system and ensure constant recovery of data once the internet or electricity are lost or once the system crushes; The system can include performance reporting functionality so that users can obtain summary reports, including performance reports of the work completed, retrieval of information registered during a given period of time, and consolidated and detailed bills. Integrate other necessary process functionalities, such as providing additional search options, especially while reviewing ordered investigational procedures; increasing the number of words in space where text is necessary; adding images for some diagnostic methods, such as histopathology; completing the list of all necessary elements required for result validation, including the date, time and person who performed validation; and improving the calculation of the turnaround time of the samples; Integrate advanced functionalities such as associating diagnostic device results with patient IDs to enter data into the system immediately through those devices, which prevents or reduces errors such as interchanging results; inputting electronic signatures and stamps into the system; introducing payment systems such as the VISA and MasterCard; and including SMS functionalities that inform patients when laboratory or radiological results are available by sending them a message; Review the management procedures of passwords and avoid frequent password expiration or devise a strategy for helping staff manage their periodically changing passwords; Merge and integrate scattered registers such as consultation and radio image results, and avoid multiple entries of similar patients’ data into different registers; Individualize services delivered in the system in such a way that only users who have put the data in the system and authorizers such as heads of departments and system administrators can make changes to the information entered. The system should trace changes by indicating the person who made those changes, and the changes should be time stamped. Upgrading the system to mobile devices so that patient records can immediately be entered into the system during the time of patient care provision; Review the patient data accessibility policy with the aim of enabling remote access, particularly for insufficient specialist doctors who can be contacted beyond their working hours; Ensuring constant availability of the information needed by healthcare providers; Increase the number of staff members to ease the high workload of users; Increase the number of support staff and ensure regular and timely support for the users; Segregate the responsibilities by assigning dedicated users to the system and avoiding the combination of entering data and providing patient care; and Dialogs were developed with the government to extend the use of OpenClinic to all district hospitals, and interoperability was promoted to improve the continuity of informed patient care. VI. Results and Discussion Overall, the implementation of the Open Clinic for Healthcare Provision in the CHUK has been successful. In fact, this study revealed that a high proportion of employed individuals (91%) were satisfied with the use of OpenClinic. According to D&M and many other models, this is an indication of information system success [9] [7] [10]. In addition, these findings serve as an evaluation feedback to the hospital leadership being on track in implementing the EMR. On the other hand, in general and especially in developing counties, the literature shows that many systems fail [1] [3] [4] [5]. Thus, the operationalization of OpenClinic in the CHUK can serve as a lesson to interested parties for successful implementation of IS in healthcare settings. The level of satisfaction identified though Likert scale scores of success is not sufficient for characterizing user satisfaction and success [48]. In fact, although 91% of the participants were ranked as very or just satisfied according to a 5-point Likert scale in this study, even more employees (98%) expressed dissatisfaction through qualitative open-ended questions. Therefore, an IS user who provides an overall score of good satisfaction can still have specific concerns, such as dissatisfaction, which should be addressed to optimize success in IS implementation. The key drivers of OpenClinic success in the CHUK can arguably reflect the main causes of user satisfaction stipulated by D&M and other IS success models, but self-expressed appraisals are more specific and clearer for understanding success in the context of the hospital. Thus, the reliability of system functionalities, ease of use, quick performance, role in patient data protection and confidentiality, shift from paper-based to digital systems, appreciation for time management and facilitation, as well as simplification of employees’ work, can reflect the system, information and service qualities as well as its usefulness, acceptability and trustworthiness. However, self-expressed appraisals identified by employees are more self-explanatory because of the reasons behind their user satisfaction and IS benefits. Although the identified triggers of satisfaction might implicitly match with suggested models of IS success, especially the D&M model, they are also mitigated by self-expressed dissatisfactions equally identifiable with those models. Thus, factors such as poor functionality or dysfunctionality due to unstable networks or electricity, limited capacity for use due to lack or insufficient training, insufficient computers, inflexibility due to difficulties in correcting errors, incomplete digitalization, a high workload, patient info exposure, inconsistent diagnosis coding and many other issues addressed by users can equally be negatively related to the key components of IS success models through user satisfaction, including system quality, information quality, service quality and usefulness, acceptability and trustworthiness. This finding suggested that user satisfaction should be evaluated holistically, discerning both positive and negative aspects of satisfaction. The perceived impact of OpenClinic was expressed by users in terms of efficiency and effectiveness in terms of work performance, which is the purpose of an information system [2]. The positive aspects of this impact were specifically explained as a higher speed of service, improved service quality, an increased number (volume) of beneficiaries who received healthcare services, increased revenue recovery, efficient management and use of resources and continuity of patient care. The negative side of the impact was expressed to a limited extent as delays in service delivery mainly due to the interruption of work caused by the loss of Internet connections, limited capacity for use, insufficient equipment and high workload. Thus, the success of OpenClinic has been achieved beyond satisfaction but would be more improved if the causes of expressed delays in service delivery were addressed. The interrelationship between the components of IS success stipulated in the D&M model was even observed through the interchangeable responses of participants between user satisfaction components and perceived impact. For instance, according to the D&M model, user satisfaction results in net benefits, but these net benefits also result in user satisfaction [14]. Through this analogy, some of the participants expressed interchangeably the reasons for their satisfaction as the impact that the system has on their work, such as being satisfied by increased speed or efficiency of services, while others expressed the perceived impact as sources of their satisfaction, such as the appraisal of its functionalities and its role in their work performance. Some of the dissatisfaction addressed by users might not have been real challenges but would have been due to limited capacity for knowledge and use. For instance, according to the system administrators at CHUK, some issues, such as the inability to work simultaneously with multiple files and missing information in the system, could be due to the limited capacity of users. In addition, addressing some of the functionalities according to the wishes of the users might cause other challenges that are difficult to address. This is, for example, the case for frequent password expiration, difficulties in editing and correcting errors and limited access to some information that, if addressed differently, would increase data security and confidentiality. Furthermore, some challenges are beyond the feasibility of hospital operation, such as interoperability with district hospital systems, which would require establishment of the system in those hospitals; however, other challenges are difficult to address due to financial constraints and management capacity, such as finding sufficient computers for every user. The results of this study highlighted the positive relationship between user satisfaction and individual work performance. Consequently, satisfied users were much more likely to have a positive perception of the system on their work performance than unsatisfied users were. This finding adds to the many existing studies on IS user satisfaction and individual performance [16] [17] [18] [19] [20] [21]. This study adds to a few existing studies that have used mixed methods research designs, and this approach has enabled a deeper understanding of the relationship between these two factors by identifying key aspects of user satisfaction as well as acquired benefits through their opinions. VII. Conclusion This study reviewed the extent of success in the implementation of electronic medical records (EMRs) at the “Centre Hospitalier Universitaire de Kigali (CHUK)”. The implementation was found to be successful due to a high level of overall user satisfaction (91%) and the high proportion of users who felt it to be beneficial (94%) through its perceived positive impact. However, the users also addressed important points of concern, such as dissatisfaction, which need to be reviewed and appropriately addressed by hospital leaders for further improvements in service delivery and increased patient outcomes. This study also provides insights relevant to the wide audience interested in healthcare information systems management by taking advantage of using both quantitative and qualitative approaches for analyzing IS success and issues in the context of healthcare facilities, thus adding to a few existing studies of this kind. VIII. Limitations and Recommendations for Further Studies The findings from this study suggest the need for using mixed research methods for evaluating information systems’ success. In fact, it is necessary to quantify overall satisfaction and benefits, as well as to understand the challenges and issues addressed by users. The key aspect in favor of mixed research is the fact that a high level of user satisfaction and perceived benefits does not preclude the existence of many challenges and issues experienced by users, which constitute dissatisfaction and hindrance to their performance. Therefore, the inclusion of a qualitative component in evaluating information systems’ success would lead to a holistic review of both the positive and negative aspects of user satisfaction and IS benefits. This study used a convenient sample of healthcare providers, which is prone to selection bias and limits the generalizability of the results. This sampling method was used due to the difficulty of accessing participants who had a busy schedule and worked different shifts during the day. To mitigate selection bias, the sample was enlarged to include 217 participants selected from different departmental services at the hospital. This study assessed the impact of OpenClinic usage on the work performance of healthcare providers. However, the assessment was limited to identifying what healthcare providers believe to be positive or negative impacts of the system on their work performance and not strictly assessing the impact of the system, which limits the reliability of the results. Although this study highlighted important aspects of dissatisfaction and improvements needed, it did not intend to objectively evaluate system dysfunctionalities. Thus, the findings elaborate on the sources of dissatisfaction and the actions that might be taken for improvements based on user opinions, and some of the suggestions might not be relevant or easily applicable. Therefore, it is recommended that hospitals conduct a deep review of the sources of dissatisfaction expressed, as well as recommended improvements, analyze the feasibility of suggested improvements and take appropriate measures to ensure the optimal operationalization of their electronic medical records system. IX. Declarations 9.1. Ethics approval and consent to participate Ethical approval was obtained from Wrexham University and from the Research Committee of the CHUK. The essential component of this study that needed special attention during the data collection was voluntary participation. This was explained to the participants, and the data collectors signed a consent form prior to responding to the data collection questionnaire. Another key element that needed attention was ensuring that the study did not interrupt participants’ access to the services. The participants were asked to test this aspect with caution and were provided with a flexible schedule for completing and submitting the questionnaire. Participants’ data protection and confidentiality are also aspects that were paid attention to by deidentification of their data: before stating the data collection, participants were briefed on the confidentiality of their data. Personal identifiable data such as names were not collected from participants through the questionnaire, and the participants were assigned new identification codes. 9.2. Consent for publication Not applicable 9.3. Availability of data and materials The datasets used and analyzed during the current study are available from the main author and may be provided upon reasonable request. 9.4. Competing interests The authors declare that they have no competing interests. 9.5. Funding There was no funding associated with this study. 9.6. Authors' contributions The main author conceptualized and initiated the study. 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Damanabi, "Factors Influencing User Satisfaction with Information Systems: A Systematic Review," Galen Medical Journal, 2020. Additional Declarations The authors declare no competing interests. Supplementary Files Appendix1.ResultsofChisquareFisherandWaldteststhroughRstudio.jpg Appendix2.QuantitativeQuestionnaire.png Appendix3.QualitativeQuestionnaire.png Appendix4.InstitutionalReviewBoardApprovalfromtheCHUK.png Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4206008","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":286588278,"identity":"df681020-b38a-4853-ba58-9d2d403e665a","order_by":0,"name":"Evode 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a university teaching hospital in Rwanda\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"I. Introduction","content":"\u003cp\u003e \u003cem\u003e1.1. Background\u003c/em\u003e \u003c/p\u003e \u003cp\u003eMany developing countries suffer from a lack of or poor use of healthcare Management Information Systems (MIS) [1]. The purpose of MIS in healthcare settings is to improve efficiency and service delivery to patients to achieve positive outcomes, including saving lives [2]. However, achieving that purpose is not straightforward because many systems fail [3] [4] [5]. The successful implementation of information systems (ISs) requires recurrent and rigorous evaluations that inform the decision making and actions of organizations [6]. Many researchers have identified information system (IS) user satisfaction as a key component of information systems\u0026rsquo; success in achieving organizational goals [6].\u003c/p\u003e \u003cp\u003eIn Rwanda, the \u0026ldquo;Centre Hospitalier de Kigali (CHUK)\u0026rdquo;, one of the two first-level public university teaching hospitals in the country, is a tertiary hospital providing healthcare services to thousands of people annually, including those who are self-referred and those who are transferred from different hospitals across the country. This hospital has been among the few pioneers in Rwanda for implementing Openclinic as a healthcare MIS since 2007 [1]. This system is currently used by more than 800 healthcare providers, including physicians, nurses, allied health professionals, and finance department staff.\u003c/p\u003e \u003cp\u003eNevertheless, only one study has focused on its evaluation [7]. In addition, no study has focused on understanding the implications of user satisfaction for individual work performance to determine the extent of success or failure or to inform hospital leaders of necessary improvements that would eventually lead to increased outcomes of patient care. Therefore, this study intends to fill this gap by assessing user experience in terms of satisfaction with using OpenClinic and evaluating its impact on work performance. The results of the study can inform hospitals on the interventions needed to ensure successful adoption of MISs and improve the services provided to patients.\u003c/p\u003e \u003cp\u003e \u003cem\u003e1.2. Study context and relevance\u003c/em\u003e \u003c/p\u003e \u003cp\u003eInformation system (IS) user satisfaction has been documented as a key indicator of IS success, and extensive quantitative studies have been conducted in many countries to understand the factors associated with this satisfaction. However, such studies have rarely been conducted in Rwanda, especially in healthcare settings. In addition, few qualitative studies have been conducted to deepen the understanding of the lessons learned and issues associated with user satisfaction. In particular, no assessment has been conducted on the user experience of OpenClinic at the CHUK for the past 7 years to inform its leadership on necessary improvements for increased patient benefit.\u003c/p\u003e \u003cp\u003eThis study closes the explained gaps in the following way. First, it adds to the literature on issues affecting IS user satisfaction and work performance. Second, it enables hospital leaders to determine the level of satisfaction as a key component of successful implementation of their healthcare system. Third, for staff who are dissatisfied or for whom the system negatively affects their work performance, leaders are informed of the reasons for dissatisfaction, which might help in planning remedial.\u003c/p\u003e \u003cp\u003e \u003cem\u003e1.2. Research objectives, hypotheses and questions\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe aim of this study was to assess the level of user satisfaction with an electronic medical records system (OpenClinic) provided by healthcare service providers at the CHUK and its implications for their work performance.\u003c/p\u003e \u003cp\u003eThe specific objectives are as follows:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eTo determine user satisfaction with OpenClinic in the hospital setting;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTo identify drivers and key issues that affect user satisfaction;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTo evaluate the perceived impact of OpenClinic on the work performance of the users;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTo provide recommendations on improvements needed for increased satisfaction and performance.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eTherefore, this study focuses on the following research hypothesis and questions.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eResearch Hypothesis\u003c/em\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eOpenClinic user satisfaction has a positive relationship with individual work performance.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eResearch Questions\u003c/em\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eWhat is the level of OpenClinic user satisfaction by healthcare providers in the CHUK?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eWhat are the triggers and key issues that affect user satisfaction?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHow does user satisfaction affect individual work performance?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eWhat improvements need to be made to ensure successful implementation of the system and its impact on work performance?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e"},{"header":"II. Literature Review","content":"\u003cp\u003eCurrently, information systems constitute an essential component of organizational management for improving efficiency and performance. However, many systems fail to achieve the expectations of their users, which negatively impacts individual and organizational performance [3] [4] [5]. Therefore, the need for research on the successful operationalization of information systems emerged from these challenges and still continues to be an important subject of inquiry [6]. Thus, the evaluation of an IS being operationalized is a worthwhile undertaking to ensure its success and benefits [7]. One of the key aspects of IS success is the perceived satisfaction of its users [6].\u003c/p\u003e \u003cp\u003e \u003cem\u003e2.1. IS user satisfaction as a measure of IS success\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe IS user satisfaction reflects the degree to which a user feels that an IS meets his needs and expectations [8]. IS user satisfaction has been considered an important element or even a surrogate of an information system\u0026rsquo;s success, especially when the use of MIS is mandatory for work [9] [7]. This assertion stems from the fact that users interact with an IS and know its functionality strengths and weaknesses, thus playing the role of evaluators [6] [10]. In addition to these intuitive findings, extensive studies have been conducted that have shown a correlation between user satisfaction and IS success [10]. Therefore, as measuring IS success is difficult, satisfaction is usually used as a proxy for IS success [11] [12].\u003c/p\u003e \u003cp\u003e \u003cem\u003e2.2. Factors affecting user satisfaction\u003c/em\u003e \u003c/p\u003e \u003cp\u003eA variety of models have been developed to understand the factors that affect user satisfaction with an IS. Among these, the most widely used are the DeLone and McLean (D\u0026amp;M) original and revised multidimensional and interdependent construct models [13] [7] [14]. According to the updated D\u0026amp;M model, user satisfaction has been theorized to be associated with system quality, information quality and service quality [14] [15]. The model stipulates that the quality dimension of an IS has a positive effect on its use or intention to use and on its user satisfaction, which in turn brings about IS benefits, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e below [14].\u003c/p\u003e\u003cp\u003eAccording to the D\u0026amp;M model, system quality reflects the aspects of usability, availability, reliability, adaptability and response time; information quality relates to interface content issues, including personalization, completeness, relevance, ease of understanding and security; service quality is concerned with support provided to users, whether coming from internally or externally to the organization; use measures the aspects of navigation, retrieval of information and execution of operations; user satisfaction captures users\u0026rsquo; opinions through their experience while interacting with the system; and finally, net benefits direct them to impacts, whether they are positives or negatives [14] [15].\u003c/p\u003e \u003cp\u003eThe model suggests that the results of IS quality are iteratively interrelated [14]. In fact, system use must precede user satisfaction, but a good experience of use (user satisfaction) can also lead to the intention to use the system [7] [14] [15]. On the other hand, system use and user satisfaction result in net benefits, but these net benefits also result in intention to use and user satisfaction [14]. A variety of empirical studies have been conducted to validate the D\u0026amp;M IS model. Most of these studies used a quantitative design and revealed significant relationships between the quality of IS and user satisfaction as well as a positive relationship between user satisfaction and IS benefits [16] [17] [18] [19] [20] [21] [22].\u003c/p\u003e \u003cp\u003eThe D\u0026amp;M IS model was criticized for its difficulties in application due to the different contexts of IS research, modeling processes with causal explanations resulting in confusing meanings, and limited coverage of dependent variables, as there are many other possible categories of measures varying from user to user [23] [14] [15] [10] [24] [25]. Thus, a variety of other IS success models have been proposed, and others have surged, including the technology acceptance model, human-organizational-technology and fit model, technology-organization-environment model, and innovation dissemination theory [13] [7] [26].\u003c/p\u003e \u003cp\u003e \u003cem\u003e2.3. Other main models of IS success\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003ea. Technology acceptance model (TAM)\u003c/em\u003e \u003c/p\u003e \u003cp\u003eAccording to this model, IS success is characterized by the extent of user acceptance measured through actual use, while the underlying factors of that acceptance are perceived usefulness and perceived ease of use [27] [28]. The mode defines perceived usefulness as the extent to which users believe the information system is important for helping them complete their job requirements, while perceived ease of use is defined as the extent to which users believe the system is used without effort [27]. The model recognizes that these two factors are influenced by external factors, which can include social, cultural and political factors [27] [29]. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below, the model stipulates that perceived usefulness and ease of use influence attitudes toward the use of technology and that those attitudes influence intention to use the technology, whereas that intention leads to the actual use of technology [27].\u003c/p\u003e\u003cp\u003eMany studies have been conducted to validate the TAM, highlighting the significance of the relationship between perceived usefulness and perceived ease of use on technology acceptance [28] [29]. However, there have also been a high number of studies in which the findings did not fit the TAM model [30].\u003c/p\u003e \u003cp\u003e \u003cem\u003eb. The human-organizational-technology (HOT) fit model\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe HOT fit model assumes that the effectiveness of an IS depends on the alignment of human factors, organizational structures and technology, with the purpose of understanding IS success through complex interactions between people, organizations and technology [31]. Human attributes reflect individual characteristics and interactions, such as knowledge, skills, capabilities, motivation, position, tasks, collaboration, communication, competition and supervision; organizational structures encompass internal and external organizational management environments and traits, such as organizational size, culture, policies and strategy, practices and government regulations; and technology relates to IS characteristics and requirements, such as software, hardware, network tools, professional skills, systems quality, information quality, service quality and social presence [31].\u003c/p\u003e \u003cp\u003eNumerous studies have been conducted with hypothetical assumptions based on the fact that when an information system is well aligned with individual attributes, organizational management practices, as well as the technological equipment and tools in place, lead to higher user satisfaction, increased productivity, and improved system performance [32] [33]. Thus, the underlying technology adoption factors highlighted in these studies include (i) training, perception, roles, skills, clarity of system purpose and user involvement as human attributes; (ii) leadership and support, process, participation or user involvement, internal communication and inter-organizational systems as organizational factors; and (iii) ease of use, system usefulness, system flexibility, time efficiency, information accessibility and relevancy as technological factors [32] [33].\u003c/p\u003e \u003cp\u003eHowever, the literature emphasizes the necessity for constant realignment of HOT components [31]. In fact, the alignment has to be dynamically adapted due to constant technological changes and evolving needs of the organization [31]. The literature also highlights the nuances and complex interactions between HOT components and recommends further research to explore those interactions as well as their implications for emerging technologies and workplace dynamics [31] [34].\u003c/p\u003e \u003cp\u003e \u003cem\u003ec. The Technology-Organization-Environment (TOE) model\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe TOE model focuses on technological, organizational and environmental factors for modeling technology adoption and innovation within organizations [35]. Technological factors capture the key characteristics of the technology under consideration, including the complexity of the technology and its compatibility with existing systems [36] [37]. Technological factors cover the internal characteristics and capabilities of an organization, such as the organization's absorptive capacity, leadership and innovation culture [36]. The environmental factors include the elements that are external to the organization but crucial in shaping technology adoption in an organization, such as industry regulations, pressure from competitors and market trends [36]. Studies have shown the relevance of the TOE model, highlighting specific elements that influence technology adoption, such as connectivity, IT capabilities and management support [36] [37].\u003c/p\u003e \u003cp\u003ed. \u003cem\u003eInnovation dissemination theory (IDT)\u003c/em\u003e\u003c/p\u003e \u003cp\u003eThe IDT theory explains the success of an information system in terms of gradual technology adoption. According to this theory, the extent of technology adoption passes through a diffusion process and communicates over time through members of an organization [38]. In the context of an IS, an innovation is defined as a technology that is perceived as new by its users, even if it has long been on the market, and it is manifested through their knowledge, persuasion and decisions [38]. Thus, the key point of the IDT model is to achieve convergence in understanding and adopting technology through a framework of information sharing where change agents and opinion leaders can significantly influence desired practices [38] [39]. This state of adoption depends on five main factors: perceived attributes of innovation, type of innovation decision, communication channels, nature of the social system, and extent of promotion agents\u0026rsquo; efforts [39].\u003c/p\u003e \u003cp\u003e \u003cem\u003e2.4. User satisfaction and individual performance\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe measurement of net benefits in terms of individual or organizational impact, as a result of system quality, use and user satisfaction, has been advocated. For instance, D\u0026amp;M has advocated for this measurement, cautioning researchers not only to limit their investigations on use and user satisfaction as measures of IS success but also to extend them toward the benefits realized in terms of performance [14]. Therefore, measuring the impact of user satisfaction on individual work performance is essential and adds value to the literature on IS success.\u003c/p\u003e \u003cp\u003eThe impact of IS on individual performance is defined as the extent to which the individual perceives the level of productivity due to the use of IS [40]. While many studies have shown that IS use has a positive impact through increased quantities and quality of productivity, other studies have indicated that it has a negative or neutral impact on individuals\u0026rsquo; performance and social life [8] [40] [18] [41].\u003c/p\u003e \u003cp\u003e \u003cem\u003e2.5. Critical analysis and conclusion\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe D\u0026amp;M and subsequent models intended to associate IS qualities with user satisfaction or technology adoption in terms of causal relationships between dependent and independent variables. However, the intuitive nature of the relationship is internal rather than external. When a user appreciates positively or expresses difficulties with an aspect of an IS quality or use, such as ease of use or usefulness of the information generated by an IS, this is a means of expressing his satisfaction or dissatisfaction with the IS use or usefulness. Therefore, this study will focus on understanding the reasons for, issues and challenges related to a certain level of satisfaction rather than understanding it in terms of correlation and causality.\u003c/p\u003e \u003cp\u003eMost of the studies conducted have been quantitative and have explored the relationship between user satisfaction and IS quality through a number of dependent and independent variables [15]. However, understanding the challenges and issues associated with user satisfaction might not be limited to parametric models and predefined variables [14] [24]. In addition, there is divergence in how IS quality variables are measured, and critics of their reliability exist [8]. This implies that studies must give the flow to users to express their concerns as measures of IS qualities. Thus, this study will integrate a qualitative component that will further the understanding of the issues of healthcare providers while using the system. Therefore, the D\u0026amp;M model and other models that subsequently emerged were adapted to the conceptual framework of this study, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eD\u0026amp;M recommended that researchers select a small number of measurements while using their model [14] [15]. However, many of the quantitative studies conducted generally use long questionnaires, and many questions have similarities, which can lead to confusion in distinguishing variables [13] [14] [15] [19] [20] [42]. This study used a concise questionnaire with a single question addressing user satisfaction and another one addressing the perceived impact of user satisfaction on work performance. In this study, the aspects of IS qualities and other issues characterizing user satisfaction and how they affect individual work performance were obtained through qualitative questions. This enables discerning user judgments, avoiding a blurt in expressing their experience and allowing the flow of the expression for the qualitative component of the questionnaire.\u003c/p\u003e \u003cp\u003e \u003cem\u003e2.6. Summary and gaps in the literature\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe D\u0026amp;M model has been essential for explaining IS success through user satisfaction and quality characteristics. Following the criticisms of the D\u0026amp;M model, further studies have been conducted through a variety of other models and elaborate other factors that affect IS success, including perceived ease of use and usefulness of IS, trustworthiness, top management support, design of user requirements, training, computer literacy, organizational structure and management style [26] [27] [28] [29] [30]. Despite a multitude of those models, no one is claiming to exhaustively explain all the elements of an IS success. However, qualitative studies can effectively capture a wide range of IS characteristics underlying the status of IS success, taking into account the specificity of organizations, but this approach has yet to be explored. Thus, this study uses a mixed research approach to take advantage of the benefits of both quantitative and qualitative approaches for analyzing the extent of an IS success as well as the underlying issues in the context of a specific hospital.\u003c/p\u003e"},{"header":"III. Methodology","content":"\u003cp\u003e \u003cem\u003e3.1. Study design\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThis study used a cross-sectional mixed research method with an explanatory embedded design to obtain a deep understanding of key issues affecting OpenClinic user satisfaction and individual performance. Quantitative studies have been useful and extensively used in studies exploring information systems success but have been criticized for their underlying assumptions [43]. However, qualitative studies are lacking, yet they have been advocated for due to their strengths in identifying virtues in their natural state with little or no assumptions [43].\u003c/p\u003e \u003cp\u003eThe combination of qualitative and quantitative approaches is necessary for studying information systems success. Some of the key benefits of that combination are as follows: the value of combining qualitative and quantitative methods is superior to using one of them; it enables accounting for context-specific nature and practices in organizations rather than relying on standard context-independent variables and assumptions; it takes into account the natural process experienced by users while evaluating information systems; it can capture the multidimensional relationships between an IS and user perceptions rather than unidirectional assumptions; and it enriches the knowledge by bringing in diversification in system research [44] [43].\u003c/p\u003e \u003cp\u003eAs a consequence, this study opted to integrate the two approaches to take advantage of each of them. The purpose of the quantitative component was to measure the level of OpenClinic user satisfaction, the level of its perceived impact on individual work performance, and the relationship between user satisfaction and perceived work performance [45] [46]. On the other hand, the qualitative component was aimed at providing more explanations of issues affecting user satisfaction and its impact on individual work performance [43].\u003c/p\u003e \u003cp\u003e \u003cem\u003e3.2. Sample selection\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe sampling frame of this study was the list of staff who use OpenClining at the CHUK. A convenient sample was used for this study, which was spread across service departments of the hospital and covered the main categories of healthcare professionals administered by the hospital, including physicians, nurses, allied health professionals and administration staff. This sampling approach has proven to be effective in exploring information system success [47].\u003c/p\u003e \u003cp\u003e \u003cem\u003e3.3. Data collector and collection procedure\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe data were collected personally by the principal investigator. Prior to data collection, an appointment was requested during the departmental staff meetings, and the data were collected during those meetings with the flexibility to submit the questionnaire after the meeting. During the data collection, the investigator provided the questionnaire and explained the study to the participants, ensuring that they understood its importance and agreed to participate voluntarily. Thereafter, the participants who agreed to participate in the study signed a hard copy of the concert form and responded to the self-registered questionnaire.\u003c/p\u003e \u003cp\u003e \u003cem\u003e3.4. Data collection, entry and analysis tools\u003c/em\u003e \u003c/p\u003e \u003cp\u003eA self-registered questionnaire was used to collect data from the participants (Ref. Appendix 2 and Appendix 3). This questionnaire was designed specifically for this study based on the research questions. The first section of the questionnaire consisted of closed questions inspired by the Likert measurement framework and was focused on collecting quantitative data [49]. The second section of the questionnaire consisted of open-ended questions and was focused on qualitative data.\u003c/p\u003e \u003cp\u003eThe electronic Epi-Info data entry platform was used for the data entry of quantitative data, while MS-Excel was used for the transcription of qualitative data. The quantitative data were analyzed using \u0026ldquo;R\u0026rdquo; software, whereas the qualitative data were analyzed using \u0026ldquo;NVivo 12\u0026rdquo; software.\u003c/p\u003e \u003cp\u003e \u003cem\u003e3.5. Data analysis techniques\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe quantitative data were analyzed using descriptive statistics and statistical tests, including the chi-square test, Fisher\u0026rsquo;s exact test and the Wald test. The descriptive statistics provide the proportions of user satisfaction and the perceived impact of the system. The chi-square test provides the significance of the relationship between user satisfaction and the perceived impact of the system. Fisher\u0026rsquo;s exact test was used for reconfirming chi-square findings due to the presence of low absolute numbers of dissatisfied users and for determining the magnitude of the relationship. In addition, the Wald test was used to determine the magnitude and significance of the relationship between user satisfaction and the perceived impact of the system and to evaluate the consistency of the previous results. The analysis of user satisfaction and perceived impact through demographic variables was not performed due to the presence of empty or very low numbers of dissatisfied cross-tabulated cells.\u003c/p\u003e \u003cp\u003eThe qualitative data were analyzed using content analysis. The participants\u0026rsquo; expressions were grouped and coded into themes and subthemes during the process of analysis using NVivo12. When the expressions did not match or elaborate upon the related theme, clarifications were sought from the participants.\u003c/p\u003e"},{"header":"IV. Demographic Findings","content":"\u003cp\u003e \u003cem\u003e4.1. Sample distribution by major categories of participants\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe sample frame obtained from the Human Resources Office of the CHUK consisted of 832 OpenClinic users, including 529 nurses, 80 physicians, 157 allied health professionals and 66 administrative staff. The data collection was conducted during August and September 2023, targeting the representativeness of users from all four professional categories and all departments of the hospital. The self-registered responses were obtained from 217 participants who were subdivided as follows (ref. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e):\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of users and sample by major categories of health professions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategories of staff\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e# All users\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNurses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysicians\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAHPs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdministrative staff\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e832\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e217\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e4.2. Sample distribution by age categories of participants\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe majority of the sample participants were aged between 30 and 39 years (46%), followed by 35% aged 40 and 49 years.\u003c/p\u003e \u003cp\u003eSample distribution by age categories\u003c/p\u003e \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"292\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.71232876712329%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91780821917808%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.36986301369863%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercentage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.71232876712329%\" valign=\"bottom\"\u003e\n \u003cp\u003e20 - 29 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91780821917808%\" valign=\"bottom\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.36986301369863%\" valign=\"bottom\"\u003e\n \u003cp\u003e9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.71232876712329%\" valign=\"bottom\"\u003e\n \u003cp\u003e30 - 39 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91780821917808%\" valign=\"bottom\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.36986301369863%\" valign=\"bottom\"\u003e\n \u003cp\u003e46%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.71232876712329%\" valign=\"bottom\"\u003e\n \u003cp\u003e40 - 49 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91780821917808%\" valign=\"bottom\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.36986301369863%\" valign=\"bottom\"\u003e\n \u003cp\u003e35%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.71232876712329%\" valign=\"bottom\"\u003e\n \u003cp\u003e50 - 59 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91780821917808%\" valign=\"bottom\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.36986301369863%\" valign=\"bottom\"\u003e\n \u003cp\u003e8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.71232876712329%\" valign=\"bottom\"\u003e\n \u003cp\u003e60+ years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91780821917808%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.36986301369863%\" valign=\"bottom\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.71232876712329%\" valign=\"bottom\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91780821917808%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.36986301369863%\" valign=\"bottom\"\u003e\n \u003cp\u003e1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.71232876712329%\" valign=\"bottom\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.91780821917808%\" valign=\"bottom\"\u003e\n \u003cp\u003e217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.36986301369863%\" valign=\"bottom\"\u003e\n \u003cp\u003e100%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u003c/br\u003e \u003cp\u003e \u003cem\u003e4.2. Sample distribution by age, years of job experience and years of experience using OpenClinic\u003c/em\u003e \u003c/p\u003e \u003cp\u003eMost of the sample participants had many years of job experience, including 78% who had more than 5 years of experience. On the other hand, the majority had between 1 and 45 years of experience using OpenClinic (41%). The proportions of participants with age ranges of use experience between \u0026ldquo;6 to 10 years\u0026rdquo; and \u0026ldquo;11 to 15 years\u0026rdquo; were also high, representing 29% and 23%, respectively.\u003c/p\u003e \u003cp\u003eSample distribution by years of professional experience and years of experience using OpenClinic\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory of years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJob experience\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExperience with OpenClinic\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1 year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 to 5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6 to 10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11 to 15 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16 to 20 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;20 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e100%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"V. Analysis and Results","content":"\u003cp\u003e \u003cem\u003e5.1. Overall user satisfaction\u003c/em\u003e \u003c/p\u003e \u003cp\u003eMost users (91%) were satisfied with the electronic medical records system (OpenClinic) during their service delivery, including 28% who indicated their satisfaction as \u0026ldquo;very satisfied\u0026rdquo; and 63% as \u0026ldquo;satisfied\u0026rdquo;. Nine percent (9%) were not satisfied, including 5% who were neutral (neither satisfied nor dissatisfied), 2% who were dissatisfied and 2% who were very dissatisfied.\u003c/p\u003e \u003cp\u003eNumber and percentage of respondents per their level of satisfaction according to the Likert scale\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLikert scale satisfaction level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery satisfied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatisfied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDissatisfied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery dissatisfied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e217\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e5.2. Sources of satisfaction\u003c/em\u003e:\u003c/p\u003e \u003cp\u003eA high proportion of respondents (95%) expressed at least one cause of satisfaction. The sources of satisfaction expressed and percentages of respondents who expressed that satisfaction are the following:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eThe importance of its functionalities (83%) was as follows: respondents were satisfied with the system functionalities, which helped them store, archive, access and retrieve patient data easily, bill care services provided to patients, generate codes for patient files useful for their classification, quickly access diagnostic results, including laboratory and imagery results; ensure security and long-lasting data; and provide reliable and accurate information.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFacilitation and simplification of the work (32%): The system facilitated and simplified the work, including communicating and sharing information, which has become easier; reducing movements between departments and accessing the archive, which is looking for patient information and diagnostic results; reducing written work; and easing workload by reducing the amount of time that one spends performing operations such as billing calculations and facilitating requests for supplies.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTime management (22%): The system allowed users to manage their time efficiently by saving their time while looking for information and caring for patients.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEase of use (14%): Participants described the system as user friendly or not complicated and not requiring special skills.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eService digitalization (13%): This satisfaction occurred because healthcare services were digitalized and service procedures were shifted from traditional paperwork toward a modern paperless work environment. Some of the users also see the system as an opportunity to familiarize themselves and to increase their skills with the use of technology.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eQuick performance (11%): The system was described as having a high speed in performance and not taking much time to respond to user requests.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eData protection and confidentiality (5%): These users were confident that records are safely kept and archived electronically within the system that is protected by usernames and passwords and that those records cannot be changed.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e5.3. Sources of dissatisfaction\u003c/em\u003e \u003c/p\u003e \u003cp\u003eDespite the high percentage of users who expressed their satisfaction, a high percentage (98%) also expressed one or more issues resulting in their dissatisfaction. The main issues for dissatisfaction and the percentage of respondents who addressed those issues are as follows:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePoor functionality or dysfunctionality due to an unstable network or electricity (57%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eLimited capacity for use due to lack or insufficient training (44%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInsufficient computers (22%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eImpossibility or difficulty editing and correcting errors (17%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003etime-consuming system, adding more workload to their already usual high workload (17%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePartial digitalization, which results in double work, using both paper files and the system (16%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePatient information was collected when all users could access patients\u0026rsquo; confidential data (9%).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIncomplete or incorrect diagnosis service coding (8%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eMissing information in the system (7%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFrequent password expiration (6%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInability to generate a performance report (6%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eErrors in records (4%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eChallenging management of patients\u0026rsquo; identification with patients having 2 or more identifications and patients\u0026rsquo; addresses section not well ordered (3%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe system allowing changing information to be entered by others (2%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eLack of extension to and interoperability with the systems at district hospitals (2%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIneffective use where some staff do not comply with standard use procedures and leave incomplete data (2%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eLoss or mismatch of data (2%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eNo access to some information (2%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe use of desktops fixed at the designated place and care givers are obliged to make frequent movements to access the system (2%).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFor example, the system may refuse to output supplies already available in stock or refuse other operations, which would simplify the work (1%).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInability to work with multiple files at a time on the computer (1%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThere was a lack of search options, for example, when performing investigative procedures or during the validation of laboratory results (1%).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSometimes the system crushes (1%).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eOver reliance on automation, which raises skeptics (1%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eScattered and unintegrated registers that cause multiple entries of similar information into the same patient, especially in the laboratory department (1%).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHealth risks such as eye problems due to longer exposure to computers (1%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eNot respecting guide in attributing credentials (1%), and\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThere was poor communication between clinicians and cashiers (1%).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003e5.4. Perceived impact of OpenClinic on work performance\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003ea. Overall perceived impact\u003c/em\u003e: Most users (94%) perceived the system to have a positive impact on their work performance, including 25% who rated the impact as \u0026ldquo;very positive\u0026rdquo; and 69% as \u0026ldquo;just positive\u0026rdquo;. Six percent (6%) were not satisfied, including 4% who were neutral (seeing the impact as neither positive nor negative), 1% who considered its impact to be negative and 1% who considered it to be very negative.\u003c/p\u003e \u003cp\u003eNumber and percentage of respondents per level of perceived impact according to the Likert scale\u003c/p\u003e \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"324\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"57.098765432098766%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eLikert scale satisfaction level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.382716049382715%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"57.098765432098766%\" valign=\"bottom\"\u003e\n \u003cp\u003eStrongly positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.382716049382715%\" valign=\"bottom\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"bottom\"\u003e\n \u003cp\u003e24%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"57.098765432098766%\" valign=\"bottom\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.382716049382715%\" valign=\"bottom\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"bottom\"\u003e\n \u003cp\u003e69%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"57.098765432098766%\" valign=\"bottom\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.382716049382715%\" valign=\"bottom\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"bottom\"\u003e\n \u003cp\u003e4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"57.098765432098766%\" valign=\"bottom\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.382716049382715%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"bottom\"\u003e\n \u003cp\u003e1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"57.098765432098766%\" valign=\"bottom\"\u003e\n \u003cp\u003eStrongly negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.382716049382715%\" valign=\"bottom\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"bottom\"\u003e\n \u003cp\u003e1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"57.098765432098766%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.382716049382715%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e217\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.51851851851852%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e100%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u003cp\u003e \u003cem\u003eb. Perceived positive impact\u003c/em\u003e: The improved efficiency and effectiveness of service delivery were seen as a positive impact induced by the use of the system. Specifically, the main benefits expressed by the users and the percentages of respondents who expressed that benefit were that the system:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eEnhance quick service performance and delivery (22%);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHelps in providing good (quality) services, especially reducing patient waiting time (9%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eimproving the quantity of work performed by serving more clients (7%);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eimproving income generation through the increased number of clients served and revenue recovery (4%);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eimproving efficiency in the use of resources such as minimizing paper files and archive space, abolishing printings of patients\u0026rsquo; results, better control of healthcare supplies\u0026rsquo; requests and use and human resources management though evaluation of clients served (2%)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eHelps to ensure continuity of care based on the history of the patient who is kept for a long time and easily accessible (2%).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003ec. Perceived negative impact\u003c/em\u003e: The negative side of the impact was expressed to a limited extent (18% of the respondents) as delays in service delivery, mainly due to the interruption of work caused by the loss of internet connections, limited capacity for use, insufficient equipment and high workload.\u003c/p\u003e\u003cp\u003e \u003cem\u003e5.5. User satisfaction and individual work performance\u003c/em\u003e \u003c/p\u003e \u003cp\u003eTo analyze the relationship between \u0026ldquo;user satisfaction\u0026rdquo; and \u0026ldquo;perceived work performance\u0026rdquo;, the original variables were transformed as follows:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eFor user satisfaction, those who scored \u0026ldquo;very satisfied\u0026rdquo; or \u0026ldquo;satisfied\u0026rdquo; were assumed to be both \u0026ldquo;satisfied\u0026rdquo;, while those who scored \u0026ldquo;neutral\u0026rdquo;, \u0026ldquo;dissatisfied\u0026rdquo; or \u0026ldquo;very dissatisfied\u0026rdquo; were assumed to be \u0026ldquo;not satisfied\u0026rdquo;.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFor the impact on work performance, the \u0026ldquo;very positive and positive\u0026rdquo; scores were rescored as \u0026ldquo;positive\u0026rdquo;, while the \u0026ldquo;neutral, negative and very negative\u0026rdquo; scores were rescored as \u0026ldquo;not positive\u0026rdquo;.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThus, the results of this transformation provided the contingent table presented below with the numbers of respondents per new category of user satisfaction and perceived work performance.\u003c/p\u003e \u003cp\u003eNumber of respondents per user satisfaction and perceived work performance\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabe\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUser satisfaction\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eImpact on individual work performance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eNot positive\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatisfied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e197\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot satisfied\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe chi-square test, Fisher\u0026rsquo;s exact test and Wald test were performed to analyze the significance and strength of the association between user satisfaction and perceived work performance (ref. Appendix 1). Both chi-square and Fisher tests confirmed the significance of the association, with p values less than 0.001, whereas the Fisher and Wald tests indicated a high strength of association through odds ratio values.\u003c/p\u003e \u003cp\u003eFisher\u0026rsquo;s test odds ratio was 20.5 (CI: 5.3 85.1), while the Wald test odds ratio was 21.2 (CI: 6.3, 71.1). Thus, the respondents who were satisfied were 20 times more likely to have a positive perception of the EMR (OpenClinic) on their work performance than were those who were not satisfied.\u003c/p\u003e \u003cp\u003e \u003cem\u003e5.5. Recommended improvements for reviews and actions\u003c/em\u003e \u003c/p\u003e \u003cp\u003eBased on the sources of dissatisfaction and expressed needs of the system users, the following are the recommendations for consideration by hospital leaders to improve their satisfaction and increase their productivity:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eProvide sufficient and continuous training on OpenClinic to increase knowledge and skills on the use of the system;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEnsuring strong, stable and permanent internet connections;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIncrease the number of computers until users can have timely access without any waiting time;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eFully digitalize healthcare services and eliminate the double workload of using both computer- and paper-based files during the process of patient care;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEnsure a complete and correct coding of services based on the standard coding procedure;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAssess the possibility of enabling the system to work offline or through an intranet and avoid disruption of care once the internet and electricity are lost;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIntegrate functionality to enable editing or deleting errors within a reasonable time;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIntegrate functionalities for ensuring patient data protection and confidentiality by tightening access to the relevant content by authorized users;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eReview the system and ensure constant recovery of data once the internet or electricity are lost or once the system crushes;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe system can include performance reporting functionality so that users can obtain summary reports, including performance reports of the work completed, retrieval of information registered during a given period of time, and consolidated and detailed bills.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIntegrate other necessary process functionalities, such as providing additional search options, especially while reviewing ordered investigational procedures; increasing the number of words in space where text is necessary; adding images for some diagnostic methods, such as histopathology; completing the list of all necessary elements required for result validation, including the date, time and person who performed validation; and improving the calculation of the turnaround time of the samples;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIntegrate advanced functionalities such as associating diagnostic device results with patient IDs to enter data into the system immediately through those devices, which prevents or reduces errors such as interchanging results; inputting electronic signatures and stamps into the system; introducing payment systems such as the VISA and MasterCard; and including SMS functionalities that inform patients when laboratory or radiological results are available by sending them a message;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eReview the management procedures of passwords and avoid frequent password expiration or devise a strategy for helping staff manage their periodically changing passwords;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eMerge and integrate scattered registers such as consultation and radio image results, and avoid multiple entries of similar patients\u0026rsquo; data into different registers;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIndividualize services delivered in the system in such a way that only users who have put the data in the system and authorizers such as heads of departments and system administrators can make changes to the information entered. The system should trace changes by indicating the person who made those changes, and the changes should be time stamped.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eUpgrading the system to mobile devices so that patient records can immediately be entered into the system during the time of patient care provision;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eReview the patient data accessibility policy with the aim of enabling remote access, particularly for insufficient specialist doctors who can be contacted beyond their working hours;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEnsuring constant availability of the information needed by healthcare providers;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIncrease the number of staff members to ease the high workload of users;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIncrease the number of support staff and ensure regular and timely support for the users;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSegregate the responsibilities by assigning dedicated users to the system and avoiding the combination of entering data and providing patient care; and\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDialogs were developed with the government to extend the use of OpenClinic to all district hospitals, and interoperability was promoted to improve the continuity of informed patient care.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e"},{"header":"VI. Results and Discussion","content":"\u003cp\u003eOverall, the implementation of the Open Clinic for Healthcare Provision in the CHUK has been successful. In fact, this study revealed that a high proportion of employed individuals (91%) were satisfied with the use of OpenClinic. According to D\u0026amp;M and many other models, this is an indication of information system success [9] [7] [10]. In addition, these findings serve as an evaluation feedback to the hospital leadership being on track in implementing the EMR. On the other hand, in general and especially in developing counties, the literature shows that many systems fail [1] [3] [4] [5]. Thus, the operationalization of OpenClinic in the CHUK can serve as a lesson to interested parties for successful implementation of IS in healthcare settings.\u003c/p\u003e \u003cp\u003eThe level of satisfaction identified though Likert scale scores of success is not sufficient for characterizing user satisfaction and success [48]. In fact, although 91% of the participants were ranked as very or just satisfied according to a 5-point Likert scale in this study, even more employees (98%) expressed dissatisfaction through qualitative open-ended questions. Therefore, an IS user who provides an overall score of good satisfaction can still have specific concerns, such as dissatisfaction, which should be addressed to optimize success in IS implementation.\u003c/p\u003e \u003cp\u003eThe key drivers of OpenClinic success in the CHUK can arguably reflect the main causes of user satisfaction stipulated by D\u0026amp;M and other IS success models, but self-expressed appraisals are more specific and clearer for understanding success in the context of the hospital. Thus, the reliability of system functionalities, ease of use, quick performance, role in patient data protection and confidentiality, shift from paper-based to digital systems, appreciation for time management and facilitation, as well as simplification of employees\u0026rsquo; work, can reflect the system, information and service qualities as well as its usefulness, acceptability and trustworthiness. However, self-expressed appraisals identified by employees are more self-explanatory because of the reasons behind their user satisfaction and IS benefits.\u003c/p\u003e \u003cp\u003eAlthough the identified triggers of satisfaction might implicitly match with suggested models of IS success, especially the D\u0026amp;M model, they are also mitigated by self-expressed dissatisfactions equally identifiable with those models. Thus, factors such as poor functionality or dysfunctionality due to unstable networks or electricity, limited capacity for use due to lack or insufficient training, insufficient computers, inflexibility due to difficulties in correcting errors, incomplete digitalization, a high workload, patient info exposure, inconsistent diagnosis coding and many other issues addressed by users can equally be negatively related to the key components of IS success models through user satisfaction, including system quality, information quality, service quality and usefulness, acceptability and trustworthiness. This finding suggested that user satisfaction should be evaluated holistically, discerning both positive and negative aspects of satisfaction.\u003c/p\u003e \u003cp\u003eThe perceived impact of OpenClinic was expressed by users in terms of efficiency and effectiveness in terms of work performance, which is the purpose of an information system [2]. The positive aspects of this impact were specifically explained as a higher speed of service, improved service quality, an increased number (volume) of beneficiaries who received healthcare services, increased revenue recovery, efficient management and use of resources and continuity of patient care. The negative side of the impact was expressed to a limited extent as delays in service delivery mainly due to the interruption of work caused by the loss of Internet connections, limited capacity for use, insufficient equipment and high workload. Thus, the success of OpenClinic has been achieved beyond satisfaction but would be more improved if the causes of expressed delays in service delivery were addressed.\u003c/p\u003e \u003cp\u003eThe interrelationship between the components of IS success stipulated in the D\u0026amp;M model was even observed through the interchangeable responses of participants between user satisfaction components and perceived impact. For instance, according to the D\u0026amp;M model, user satisfaction results in net benefits, but these net benefits also result in user satisfaction [14]. Through this analogy, some of the participants expressed interchangeably the reasons for their satisfaction as the impact that the system has on their work, such as being satisfied by increased speed or efficiency of services, while others expressed the perceived impact as sources of their satisfaction, such as the appraisal of its functionalities and its role in their work performance.\u003c/p\u003e \u003cp\u003eSome of the dissatisfaction addressed by users might not have been real challenges but would have been due to limited capacity for knowledge and use. For instance, according to the system administrators at CHUK, some issues, such as the inability to work simultaneously with multiple files and missing information in the system, could be due to the limited capacity of users. In addition, addressing some of the functionalities according to the wishes of the users might cause other challenges that are difficult to address. This is, for example, the case for frequent password expiration, difficulties in editing and correcting errors and limited access to some information that, if addressed differently, would increase data security and confidentiality. Furthermore, some challenges are beyond the feasibility of hospital operation, such as interoperability with district hospital systems, which would require establishment of the system in those hospitals; however, other challenges are difficult to address due to financial constraints and management capacity, such as finding sufficient computers for every user.\u003c/p\u003e \u003cp\u003eThe results of this study highlighted the positive relationship between user satisfaction and individual work performance. Consequently, satisfied users were much more likely to have a positive perception of the system on their work performance than unsatisfied users were. This finding adds to the many existing studies on IS user satisfaction and individual performance [16] [17] [18] [19] [20] [21]. This study adds to a few existing studies that have used mixed methods research designs, and this approach has enabled a deeper understanding of the relationship between these two factors by identifying key aspects of user satisfaction as well as acquired benefits through their opinions.\u003c/p\u003e"},{"header":"VII. Conclusion","content":"\u003cp\u003e This study reviewed the extent of success in the implementation of electronic medical records (EMRs) at the \u0026ldquo;Centre Hospitalier Universitaire de Kigali (CHUK)\u0026rdquo;. The implementation was found to be successful due to a high level of overall user satisfaction (91%) and the high proportion of users who felt it to be beneficial (94%) through its perceived positive impact. However, the users also addressed important points of concern, such as dissatisfaction, which need to be reviewed and appropriately addressed by hospital leaders for further improvements in service delivery and increased patient outcomes. This study also provides insights relevant to the wide audience interested in healthcare information systems management by taking advantage of using both quantitative and qualitative approaches for analyzing IS success and issues in the context of healthcare facilities, thus adding to a few existing studies of this kind.\u003c/p\u003e"},{"header":"VIII. Limitations and Recommendations for Further Studies","content":"\u003cp\u003eThe findings from this study suggest the need for using mixed research methods for evaluating information systems\u0026rsquo; success. In fact, it is necessary to quantify overall satisfaction and benefits, as well as to understand the challenges and issues addressed by users. The key aspect in favor of mixed research is the fact that a high level of user satisfaction and perceived benefits does not preclude the existence of many challenges and issues experienced by users, which constitute dissatisfaction and hindrance to their performance. Therefore, the inclusion of a qualitative component in evaluating information systems\u0026rsquo; success would lead to a holistic review of both the positive and negative aspects of user satisfaction and IS benefits.\u003c/p\u003e \u003cp\u003eThis study used a convenient sample of healthcare providers, which is prone to selection bias and limits the generalizability of the results. This sampling method was used due to the difficulty of accessing participants who had a busy schedule and worked different shifts during the day. To mitigate selection bias, the sample was enlarged to include 217 participants selected from different departmental services at the hospital.\u003c/p\u003e \u003cp\u003eThis study assessed the impact of OpenClinic usage on the work performance of healthcare providers. However, the assessment was limited to identifying what healthcare providers believe to be positive or negative impacts of the system on their work performance and not strictly assessing the impact of the system, which limits the reliability of the results.\u003c/p\u003e \u003cp\u003eAlthough this study highlighted important aspects of dissatisfaction and improvements needed, it did not intend to objectively evaluate system dysfunctionalities. Thus, the findings elaborate on the sources of dissatisfaction and the actions that might be taken for improvements based on user opinions, and some of the suggestions might not be relevant or easily applicable. Therefore, it is recommended that hospitals conduct a deep review of the sources of dissatisfaction expressed, as well as recommended improvements, analyze the feasibility of suggested improvements and take appropriate measures to ensure the optimal operationalization of their electronic medical records system.\u003c/p\u003e"},{"header":"IX. Declarations","content":"\u003cp\u003e\u003cem\u003e9.1. Ethics approval and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from Wrexham University and from the Research Committee of the CHUK. The essential component of this study that needed special attention during the data collection was voluntary participation. This was explained to the participants, and the data collectors signed a consent form prior to responding to the data collection questionnaire. Another key element that needed attention was ensuring that the study did not interrupt participants\u0026rsquo; access to the services. The participants were asked to test this aspect with caution and were provided with a flexible schedule for completing and submitting the questionnaire.\u003c/p\u003e\n\u003cp\u003eParticipants\u0026rsquo; data protection and confidentiality are also aspects that were paid attention to by deidentification of their data: before stating the data collection, participants were briefed on the confidentiality of their data. Personal identifiable data such as names were not collected from participants through the questionnaire, and the participants were assigned new identification codes.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e9.2. Consent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e9.3. Availability of data and materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the main author and may be provided upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e9.4. Competing interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e9.5. Funding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThere was no funding associated with this study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e9.6. Authors\u0026apos; contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe main author conceptualized and initiated the study. Other authors discussed and advised the main author on the approaches and methodology. The authors reviewed and revised the manuscript and provided comments. The authors also guided and facilitated the approval of the main author. A.M. and E.M. facilitated the reach of the participants by the main author.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e9.7. Acknowledgments\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eG. Karara, F. Verbeke and M. Nyssen, \u0026quot;Hospital Information Management Using Open Source Software: Results of the MIDA Project in 3 Hospitals in Rwanda,\u0026quot; in 8th Health Informatics in Africa Conference (HELINA 2013), Eldoret, 2013.\u003c/li\u003e\n\u003cli\u003eA. Winter, E. Ammenwerth, R. Haux, M. Marschollek, B. Steiner and F. Jahn, Health Information Systems: Technological and Management Perspectives, Springer Nature: Health Informatics, 2023.\u003c/li\u003e\n\u003cli\u003eR. Heeks, \u0026quot;Information Systems and Developing Countries: Failure, Success, and Local Improvisations,\u0026quot; The Information Society, vol. 18, pp. 101-112, 2002.\u003c/li\u003e\n\u003cli\u003eR. 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Degoulet, \u0026quot;Determinants of User Satisfaction with a Clinical Information System,\u0026quot; AMIA Annu Symp Proc., pp. 614-618, 2006.\u003c/li\u003e\n\u003cli\u003eL. R. Kalankesh, Z. Nasiry, R. A. Fein and S. Damanabi, \u0026quot;Factors Influencing User Satisfaction with Information Systems: A Systematic Review,\u0026quot; Galen Medical Journal, 2020.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Electronic Medical Record System, Open Clinic, Management Information System, User satisfaction, Individual work performance","lastPublishedDoi":"10.21203/rs.3.rs-4206008/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4206008/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eInformation system user satisfaction has been extensively documented as a key component and a surrogate of success and a determinant of individual and organizational performance. However, most related studies have focused on measuring user satisfaction and its impact through mathematical models, which might not exhaustively capture the issues affecting user satisfaction and performance. This study was conducted at the \u0026ldquo;Centre Hospitalier Universtaire de Kigali\u0026rdquo;, one of the two tertiary public and university teaching hospitals in Rwanda. This hospital has been implementing OpenClinic as an electronic medical record system since 2007, and few studies have focused on its evaluation. In addition, no study has focused on understanding the implications of user satisfaction for individuals\u0026rsquo; work performance in this hospital. This study was cross-sectional mixed research using an explanatory embedded design. The data were collected from a convenient sample of OpenClinic users through questionnaires, which included closed- and open-ended questions, to capture both quantitative and qualitative data. The OpenClinic user satisfaction was high (91%), as was the proportion of users who perceived it as having a positive impact on their work performance (94%). The relationship between user satisfaction and perceived impact was statistically significant, and satisfied users were 20 times more likely to perceive that the impact was positive than unsatisfied users. Important concerns were expressed by users, and the main concerns were the poor functionality of the system due to unstable internet, the limited capacity for use and the scarcity of computers. Therefore, the implementation of the Electronic Medical Record system at the hospital has been successful, and user satisfaction has led to a perceived positive impact; however, further improvements are needed for optimal success. The inclusion of a qualitative component in future studies is recommended for a better understanding of IS success.\u003c/p\u003e","manuscriptTitle":"Electronic medical record system user satisfaction and its implications for individual work performance: The case of a university teaching hospital in Rwanda","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-03 18:32:56","doi":"10.21203/rs.3.rs-4206008/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bd578cab-6ac3-428e-8574-f44ee1c3762a","owner":[],"postedDate":"April 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":30164975,"name":"Medical Informatics"}],"tags":[],"updatedAt":"2024-04-03T18:32:56+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-03 18:32:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4206008","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4206008","identity":"rs-4206008","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}