Insights into healthcare workers' perceptions of electronic medical record system utilization: A cross-sectional study in Mafeteng District, Lesotho

Insights into healthcare workers' perceptions of electronic medical record system utilization: A cross-sectional study in Mafeteng District, Lesotho | 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 Insights into healthcare workers' perceptions of electronic medical record system utilization: A cross-sectional study in Mafeteng District, Lesotho Tebeli E. Sekoai, Astrid C Turner, Janine Mitchell This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5150449/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 May, 2025 Read the published version in BMC Medical Informatics and Decision Making → Version 1 posted 4 You are reading this latest preprint version Abstract Background: Electronic medical record (EMR) systems have significantly transformed the way healthcare data is created, managed and utilized. The advantages offered by the systems over paper-based records include improved legibility and accessibility to up-to-date patient information and provision of support for clinical decision-making. The system’s implementation in Lesotho aimed to enhance patient care, track patients, and generate routine reports for evidence-based programming. It is imperative to understand how healthcare workers (HCWs) perceive the system as frontline end-users; thus, the objective of the study was to explore HCWs’ perceptions of the system, focusing on their perceived usefulness and perceived ease of use and factors influencing acceptance and utilization in Mafeteng district. Methods : A descriptive cross-sectional study design was conducted; 145 healthcare workers from 17 health facilities were invited to participate in the study. A structured questionnaire based on the Technology Acceptance Model was administered for data collection. The analysis included descriptive statistics; the perceived usefulness and perceived ease of use using Stata/BE 18.0 and multiple regression analysis to identify the outcomes of the HCWs’ perceptions. Additional text by participants was extracted to explain quantitative results. Results: There was a 49% response rate (n= 71). The majority of respondents in the study were female (70.42%), and the most common profession was registered nurse midwife (45.07%). A large proportion of the participants reported having good computer skills. 87.32% HCWs found the EMR system useful, with 83.1% agreeing that it improves job performance and saves time. Additionally, 85.91% participants found the system easy to use, with 81.69% able to recover from errors and 85% able to remember how to perform tasks. However, 32.39% experienced unexpected system behaviour. Conclusion: Overall, HCWs showed positive attitudes towards the EMR system, appreciating its usefulness, ease of use and efficiency. Nevertheless, unexpected behavioural issues, such as network issues, unavailability of electricity, and computer skills gaps among the respondents were identified. Addressing these challenges is crucial for successful implementation and adoption of the system, ultimately leading to improved patient care. Acceptance ease-of-use EMR system healthcare workers perceptions technology acceptance model usefulness Figures Figure 1 Background Since February 2015, the US President’s Emergency Plan for AIDS Relief (PEPFAR) has supported Lesotho’s Ministry of Health (MOH) in transforming the country’s Health Management Information System (HMIS) by introducing the District Health Information Software 2 (DHIS2) for data capture, storage, and program queries, which has drastically enhanced the quality of HIV care and treatment data [ 1 ]. However, discrepancies persisted between the program data in DHIS2, and survey data from the Lesotho Population-based HIV Impact Assessment (LePHIA), a household-based national survey conducted between November 2016 and May 2017 to provide a detailed status of the HIV epidemic in the country [ 2 ]. For example, while the LePHIA survey estimated that 235,135 people living with HIV were on antiretroviral therapy (ART) drugs, the DHIS2 reported only 149,951 [ 2 ]. Recognizing the significant gap identified, the Ministry of Health (MOH) took proactive steps to address it by using electronic medical records (EMR). Their approach involved adopting, developing, and deploying an open-source client-level electronic register (eRegister) tailored for HIV, Tuberculosis (TB), and Maternal and Child Health (MCH) services. This strategic shift was based on the recommendations from a thorough assessment conducted in 2017, which highlighted the inadequacies of the hospital-based EMR system previously introduced across 16 public health hospitals in Lesotho's 10 districts back in 2013 [ 1 ]. The evaluation highlighted numerous challenges encountered during the initial implementation of the hospital-based EMR system. These included the Ministry not receiving crucial monthly outpatient department (OPD) reports from the 16 hospitals, discontinuation of EMR implementation in several health facilities, and instances of substandard implementation where EMR systems remained in use but were not optimally utilized [ 6 ]. Building upon lessons learned from this pilot, the eRegister emerged as a promising solution, serving both as a clinical decision-support tool to enhance patient care and as a dynamic monitoring and evaluation instrument aimed at addressing underreporting. Notably, the eRegister's integration with the national DHIS2 facilitated more robust data collection and analysis. Given its demonstrated efficacy, the MOH devised a three-phased implementation plan to systematically roll out the eRegister across relevant healthcare settings [ 6 ]. The MOH implemented the EMR system in 2018, to collect and use high-quality patient-level data, to uniquely distinguish and track patients through the 95-95-95 targets, and to automatically generate facility-level routine and key operational reports in support of data usage and evidence-based programming [ 1 ]. An EMR is a computerized system for keeping track of patient health information that offers ways to gather, store, and display patient data to provide HCWs with accurate and up-to-date information about the patient’s medical records to support patient care and enhance the quality of healthcare [ 3 , 4 , 5 ]. The implementation of EMR benefits healthcare workers (HCWs), patients, and healthcare sector management in different ways. However, HCWs are in the best position to report what encourages or limits its usage as they are the first-hand users of the system [ 7 , 8 ]. The use of EMR improves healthcare quality, productivity and efficiency while also leading to better public health outcomes [ 9 ] and aligning with the Sustainable Development Goal (SDG) 3 of good health and well-being [ 31 ]. The benefits of EMR include enhanced data quality as well as improved and prompt access to records for all healthcare service providers [ 6 , 10 – 12 ]. Moreover, EMR provides patients with easy access to their medical health records which promotes better health outcomes due to improved self-care, informed decision-making, enhanced medical compliance, and stronger trust and communication between patients and HCWs [ 13 – 17 ]. Some of the benefits relate to time management and cost savings due to reduced duplication of tests and sharing of patient records among HCWs [ 18 , 19 ], as well as reduced HCWs, storage facilities, and overall healthcare services such as medical transcriptions and reporting [ 20 , 21 ]. The challenges of EMR implementation include standardized communication between patients and physicians which results in a more formal relationship [ 3 , 4 , 12 ]. The system is believed to significantly change the workflow of HCWs, hence complicating workloads and reducing productivity [ 22 , 23 ]. In addition, the limited adoption and use of EMR systems in developing countries are related to HCWs’ attitudes and awareness levels, lack of proper management, resistance from users, poor commitment from staff and lack of computer skills [ 5 , 24 , 25 ]. A lack of training also contributes to the high rate of EMR rejection by the HCWs as studies postulate that sufficient training related to EMR implementation is associated with improved well-being of HCWs and appears to be extremely crucial [ 3 , 27 ]. There are no studies available related to the views of the frontline end-users of the system since the EMR implementation of the system in Lesotho. It is imperative to understand HCWs’ perceptions of the usage of the system, and their willingness to utilize it, as they influence the effectiveness of its implementation. Therefore, the aim of this study was to examine HCWs’ perceptions of the EMR system in Mafeteng district in Lesotho. Ethical clearance for the study was obtained from the University of Pretoria Faculty of Health Sciences Research Ethics Committee (reference number 492/2023) and the Ministry of Health (MOH) National Research Ethics Committee of Lesotho (ID237-2023). Permission to collect data was obtained from the District Health Management Team of Mafeteng. Participants were duly informed that participation in the study was voluntary. A signed informed consent form was required to proceed. Methods Study design and setting A descriptive cross-sectional study was conducted at 17 government and Christian Health Association of Lesotho (CHAL) healthcare facilities in the Mafeteng district. The health facilities included one district referral hospital and 16 clinics. Study population and sample One hundred forty-five HCWs who were involved in the utilization of the EMR system in Mafeteng district were invited to participate in the study. These HCWs included registered nurse midwives, nurse assistants, HTS counsellors, and data clerks. Purposive non-random sampling was used to select participants from the population. The questionnaire was distributed to the respondents via a link to a web-based questionnaire (Google form) during sites visits, and those who did not utilize the system were excluded from the study. Data collection A structured questionnaire was developed, guided by one from Tubaishat [ 28 ] which determined the factors associated with HCWs’ perceptions of the EMR system. The original questionnaire developed by Davis FD consists of 28 items that assess both PU and PEU and was considered to be valid and reliable. The reliability of PU and PEU were found to be 0.97 and 0.91 respectively, while their validity was reported significant at 0.05, where PU was 100% significant 100% of the time and PEU 95.6%. 28 The questionnaire was pretested with ten respondents from health facilities outside the sites of interest, to ensure reliability, accuracy, and consistency. The questionnaire adopted the Technology Acceptance Model (TAM), a theoretical framework that explains how users come to accept and use a technology, which centres on perceived usefulness (PU) and perceived ease of use (PEU) as the main influencers of individuals’ acceptance and intention to utilize a system [ 29 ]. Perceived usefulness is defined as the extent to which an individual believes that using technology will enhance their job performance while PEU is characterized by the extent to which an individual perceives technology as easy to learn, use, and integrate in their workflow [ 30 ]. The model proposes that these perceptions influence users’ attitude towards usage of technology, hence affecting their intentions to adopt and intention to utilize it. Data analysis Stata/BE 18.0 was used to analyse the data after it was entered into EpiData software. Descriptive statistics was conducted to calculate the frequencies of the demographic characteristics of the sample and the perceived usefulness and perceived ease-of-use of the EMR. Multiple regression analysis was conducted to identify the outcomes of the healthcare workers’ perceptions. Additional text by participants was extracted to explain quantitative results. Results a. Descriptive analysis of participants’ demographic characteristics There was a response rate of 49% (n = 71). Among the professions represented, registered nurse midwives constituted the largest group (45.07%), while nurse assistants made up a smaller proportion (7.04%). Regarding educational qualifications, 12 respondents (16.90%) held the COSC/LGCSE qualification, while majority of the respondents were Bachelor’s degree holders (43.66%). Notably, the majority of participants (50.70%) reported having ‘good computer skills’, implying that they were proficient in common computer applications and tools such as Microsoft Word, Excel and PowerPoint. Table 1 Demographic characteristics of respondents Characteristics N (%) Sex Male 21 (29.58) Female 50 (70.42) Profession Registered nurse midwife 32 (45.07) Nurse assistant 5 (7.04) HTS counsellor 18 (25.35) Data clerk 16 (22.54) Qualification COSC/LGCSE (Equivalent to Matric) 12 (16.90) Diploma 24 (33.80) Bachelor’s Degree 31 (43.66) Honors/Postgraduate Diploma 4 (5.63) Computer skills Poor 4 (5.63) Good 36 (50.70) Very Good 31 (43.66) b. Perceived usefulness According to Table 2 , 52.11% of the HCWs strongly agreed, while 35.21% agreed that the EMR system is useful in their job. The respondents stated that the system makes patients’ record keeping and retrieving of information very easy. One respondent mentioned that the system enables the immediate appointment of patients’ next visit dates and thus minimizes the risk of missed appointments. Approximately 38.03% of the HCWs agreed while 32.39% strongly agreed that their jobs would be difficult without the EMR system, and the majority (83.1%) agreed or strongly agreed that the system improves their job performance. The respondents stated that compiling reports has become easier with the use of the system, hence making their jobs less difficult. They also indicated that the system has made patient monitoring and management easier since access to patients’ records is effortless. A significant number of the HCWs (78.87%) agreed or strongly agreed that the EMR system saves them time and enables them to accomplish more tasks than would otherwise be possible, as postulated by 71.84% of the respondents. A large proportion of the HCWs (84.51%) believe that the system improves the quality of work they do and 76.06% trust that it increases their productivity. They mentioned that reports from the EMR system meet most of the data quality dimensions such as timeliness, and they also have an opportunity to make informed decisions concerning patients’ health needs. However, approximately 9.82% of the HCWs are neutral about the usefulness of the system, as they believe that they have been performing tasks very well without it, and some believe that it has added more workload. Table 2 PU items PU items Rating Scale Strongly Disagree Disagree Neutral Agree Strongly Agree 1. My job would be difficult to perform without EMRs 2,82 7,04 19,72 38,03 32,39 2. Using EMRs improves my job performance 1,41 4,23 11,27 36,62 46,48 3. EMRs save me time and enable me to accomplish tasks more quickly 2,82 5,63 12,68 25,35 53,52 4. Using EMRs allows me to accomplish more work than would otherwise be possible 2,82 4,23 21,13 30,99 40,85 5. Using EMRs enhances my effectiveness on the job 0 7,04 12,68 32,39 47,89 6. Using EMRs improves the quality of work I do 0 4,23 11,27 35,21 49,3 7. Using EMRs increases my productivity 5,63 4,23 14,08 35,21 40,85 8. Overall, I find the EMR system useful in my job 0 2,82 9,86 35,21 52,11 c. Perceived ease of use As shown in Table 3 , a vast majority of the HCWs (59.15% and 26.76%) found the EMR system easy to use. This is supported by the respondents’ opinions that the language of the system is very easy and straightforward, and that they receive supportive supervision from the implementers where they obtain clarity on several issues related to the system. The majority of the HCWs (47.89%) strongly disagreed, while 33.8% disagreed that interacting with the system is often frustrating and requires frequent consultations with the manual. A total of 40.85% of the HCWs strongly disagreed, while 25.35% disagreed that interacting with the system requires a lot of their mental effort. In addition, 85.91% strongly disagreed or disagreed that they find the system cumbersome to use. The respondents mentioned that they received enough training to allow them to navigate the system with ease, without depending on the manual. Table 3 PEU items PEU items Rating Scale Strongly Disagree Disagree Neutral Agree Strongly Agree 1. I often become confused and make frequent errors when I use the EMR system 39,44 45,07 9,86 1,41 4,23 2. Interacting with the EMR system is often frustrating and requires me to consult the manual more often 47,89 33,8 9,86 5,63 2,82 3. Interacting with the EMR system requires a lot of my mental effort 40,85 25,35 18,31 14,08 1,41 4. I find it easy to recover from errors encountered while using the EMR system 4,23 5,63 8,45 32,39 49,3 5. The EMR system often behaves in unexpected ways 5,63 38,03 23,94 26,76 5,63 6. I find it cumbersome (difficult) to use the EMR system 50,7 35,21 4,23 2,82 7,04 7. It is easy for me to remember how to perform tasks using the EMR system 1,41 7,04 5,63 39,44 46,48 8. Overall, I find the EMR system easy to use 5,63 2,82 5,63 26,76 59,15 A notable number of the HCWs (81.69%) agreed or strongly agreed that they find it easy to recover from errors encountered while using the system, while 85.92% find it easy to remember how to perform tasks using the EMR system. This pertains to the fact that the system highlights errors immediately and autocorrects some of the errors. The respondents also pointed out that the system allows editing of information at any point and that errors are usually highlighted by a star, and hence are easy to recognize and recover. The HCWs mentioned that they experience frequent daily network issues, as well as the unavailability of electricity at some of the healthcare facilities, hence 43.66% strongly disagreed or disagreed that the system behaves in unexpected ways. A smaller portion of the HCWs (8.45%), however, do not find the EMR system easy to use, mainly because of their poor computer skills, while others believe that paper-based registers are much easier to use. d. Multiple linear regression Tables 4 and 5 present the results of a multiple linear regression analysis conducted to explore the relationships between demographic characteristics of HCWs and their perceptions of the EMR system. Table 4 Linear regression for PU Model Summary R-squared = 0.3155 Adj R-squared = 0.2740 F-statistic = 7.60 Prob > F = 0.0000 Root MSE = 0.66376 Number of obs = 71 Variable Coefficient Std. Error t-Value p-Value 95% Confidence interval Sex 0.029 0.190 0.15 0.879 -0.350 to 0.408 Profession -0.028 0.073 -0.39 0.701 -0.173 to 0.117 Qualification 0.182 0.105 1.73 0.088 -0.028 to 0.391 Computer skills 0.641 0.167 3.84 0.000 0.308 to 0.975 Constant 1.808 0.699 2.59 0.012 0.413 to 3.203 The F-test (Prob > F = 0.0000) indicates that at least one of the predictor variables in the model has a significant relationship with PU, and approximately 31.55% of the variance in PU is explained by the model. The predictor variables included in the model were sex, profession, qualification, and computer skills. The p-values for sex, profession and qualification were 0.879, 0.701 and 0.088 respectively, suggesting that the variables are not statistically significant at 0.05, and do not have any significant impact on the PU of EMR. In contrast, computer skills demonstrated high significance, (p-value = 0.000), suggesting that better computer skills are associated with a greater PU. Table 5 Linear regression for PEU Model Summary R-squared = 0.2802 Adj R-squared = 0.2366 F-statistic = 6.42 Prob > F = 0.0002 Root MSE = 0.95246 Number of obs = 71 Variable Coefficient Std. Error t-Value p-Value 95% Confidence interval Sex 0.016 0.272 0.06 0.953 -0.527 to 0.560 Profession 0.054 0.104 0.52 0.606 -0.154 to 0.262 Qualification 0.324 0.150 2.16 0.035 0.024 to 0.624 Computer skills 0.672 0.240 2.80 0.007 0.198 to 1.151 Constant 1.060 1.003 1.06 0.294 -0.941 to 3.062 Table 5 reveals that the model is statistically significant (Prob > F = 0.0002, and that at least 28.02% of the variance in PEU is explained by the model. Sex (p-value = 0.953) and profession (p-value = 0.606) did not have any significant impact on the PEU of the EMR system. Qualification and computer skills are on the other hand statistically significant, with p-values of 0.035 and 0.007 respectively, indicating an association with greater PEU of the system. Discussion In general, the majority of the HCWs who participated in this study perceive the EMR system as both useful (87.32%) and easy-to-use (85.91%), which highlights the positive acceptance of the technology. This study revealed that demographic factors such as qualifications and computer literacy have a significant impact on the HCWs’ perceptions of the EMR system. A study by Tubaishat [ 28 ] also revealed that computer skills impact nurses’ PU and PEU of the EMR system. The implementation of EMR is aimed at solving existing inconsistencies within data management and patient care within the healthcare system, and feedback from the respondents revealed that EMR is capable of enhancing patient data management and enabling quick access to patient files [ 7 ]. The study identified several interesting issues regarding the perceptions of the HCWs in the district. The positive reception of the HCWs means that the system's implementation will be sustainable and thus positively impact patient care and management. It is also worth noting a high percentage of HCWs agreed that EMR improves their job performance and enhances the quality of their work. The findings that higher qualifications and better computer skills are associated with greater perceived usefulness and ease of use of the EMR system are particularly interesting, as they highlight specific areas where targeted training and support could increase the adoption rate. The key strengths of the study relate to the fact that the findings are highly relevant to healthcare administrators and policymakers, as they identify the factors that influence the successful implementation and utilization of the EMR system. Adopting the conceptual framework of the TAM, which is a widely known framework for evaluating factors relating to technology adoption improves the credibility of this study. Apart from that, the study targeted the HCWs to examine factors and provide relevant insights into the utilization of the system, as they are the first-hand users of the system. Nonetheless, there are notable limitations exhibited by this study. The researcher was compelled to leave the questionnaires without ensuring complete respondent participation due to execution during working hours, thus contributing to the low response rate (49%). Additionally, budget constraints restricted the study to a single district, thereby limiting the generalizability of its findings to the broader country context. Although TAM is a widely used framework, it primarily focuses on assessing HCWs’ perceptions and attitudes toward the EMR system. It overlooks other critical factors that may influence EMR implementation, such as system quality, organizational culture, and individual social norms. Furthermore, the study identified network connectivity and electricity supply as some of the significant barriers to effective usage of the EMR system in the health facilities, which result in service delivery interruptions. Recommendations Based on the study’s findings related to HCWs’ perceptions and challenges regarding EMR system implementation, we recommend that the MOH take specific actions. Firstly, the MOH is advised to invest in robust infrastructure, reliable network connections and electricity supplies to ensure consistency in the usage of the system. The government is advised to prioritize installation of high-speed internet connections and reliable power sources such as backup solar power systems and generators to alleviate the impact of power outages. These recommended solutions will align with SDG 9, which centres on building resilient infrastructure, promoting inclusive and sustainable industrialization, and fostering innovation [ 31 ]. Secondly, there is a need for enhanced training programs aimed at improving the HCWs’ computer literacy, which are specifically tailored to the usage of the EMR system. Additionally, the ministry can foster continued career development by introducing mentorship programs and peer learning opportunities as computer literacy has been shown to have a remarkable impact on the HCWs’ perceptions of the usage of the system. The implementation of comprehensive training programs on EMR has the potential to enhance the capabilities, skills and knowledge of the HCWs, hence advancing the goal of SDG 4, which focuses on quality education [ 31 ]. In addition, to ensure comprehensive patient data management, interoperability of the EMR system and DHIS2 is critical for seamless exchange and communication of data. Interoperability allows sharing of patient across different healthcare system settings, hence improving productivity and efficiency. The EMR system stores highly confident and sensitive patient information, which must be protected against unauthorised access at all times. Thus, it is crucial to implement robust access control mechanisms to ensure that access is limited to authorized HCWs. It is also imperative to introduce regular feedback mechanisms in the system so that issues are identified and solutions are provided on time. There is also a need for continuous research and evaluations to assess the long-term impact of the system and the HCWs’ satisfaction as well as to monitor implementations of the recommendations, for improved patient care and more effective healthcare data management. Conclusion This study aimed to examine the perceptions of the HCWs towards the utilization of the EMR system, intending to explore their perceived usefulness and ease of use. The findings of the study showed that the majority of the HCWs convey high perceptions of the usefulness and ease of use of the system in Mafeteng district. The benefits of the system have been duly noted, as outlined by the participants, as well as the relationships between the demographic characteristics and the PU and PEU of the EMR system. Abbreviations ART Antiretroviral therapy CHAL Christian Health Association of Lesotho COSC Cambridge Overseas School Certificate (Equivalent to Matric) DHIS2 District Health Information Software 2 EMR Electronic Medical Record eRegister Electronic Register HCWs Healthcare workers HMIS Health Management Information System HTS HIV Testing Services LePHIA Lesotho Population-based HIV Impact Assessment LGCSE Lesotho General Certificate of Secondary School (Equivalent to Matric) MCH Maternal Child Health MOH Ministry of Health OPD Out-patient Department PEPFAR President’s Emergency Plan for AIDS Relief PEU Perceived Ease-of-Use PU Perceived Usefulness SDG Sustainable Development Goal SI Strategic Information TAM Technology Acceptance Model TB Tuberculosis Declarations Ethics approval and consent to participate This study was approved by the University of Pretoria Faculty of Health Sciences Research Ethics Committee (reference number 492/2023). The Ministry of Health (MOH) National Research Ethics Committee of Lesotho (ID237-2023) also approved the study and permission to collect data was obtained from the District Health Management Team of Mafeteng. Participants were duly informed that in the study was voluntary and were asked to sign the informed consent form. Consent for publication Participants were duly informed that the study findings may be published but that measure would be taken to anonymise their role. Competing interests The authors declare that they have no competing interests. Funding Not applicable Author Contribution TES developed the original draft of the manuscript, conducted data collection and analysis, and participated in writing up and shaping the manuscript. ACT and JM provided supervision and constructive feedback during the development and write up of the manuscript. The final manuscript was read and approved by all the authors. Acknowledgement The authors would like to give special thanks to the Ministry of Health in Lesotho for granting access for data collection in the health facilities as well as to the participants who gave off their time for the study. Data Availability The dataset that supports the findings of this study has been deposited in the University of Pretoria research repository with the following DOI for access: https://doi.org/10.25403/UPresearchdata.27078121.v1. References Lesotho Ministry of Health. Standard operating procedure for transition to the eRegister Live DHIS2 reporting. February 2020. Lesotho Population-based HIV Impact. Assessment 2016–2017. https://phia.icap.columbia.edu/wp-content/uploads/2020/02/LePHIA_FinalReport_Web.pdf . Accessed 07 April 2023. Jimma BL, Enyew DB. Barriers to the acceptance of electronic medical records from the perspective of physicians and nurses: A scoping review. Inf Med Unlocked. 2022;31(100991). 10.1016/j.imu.2022.100991 . Boonstra A, Vos J, Rosenberg L. The effect of electronic health records on the medical professional identity of physicians: a systematic literature review. Procedia Comput Sci. 2022;196:272–9. 10.1016/j.procs.2021.12.014 . Oumer A, Muhye A, Dagne I, Ishak N, Ale A, Bekel A. Utilization, determinants and prospects of electronic medical records in Ethiopia. Biomed Res Int. 2021; 2021(2230618); 10.1155/2021/2230618 Government of the Kingdom of Lesotho Ministry of Health. Electronic medical record (EMR) assessment: Final report. 18 October 2017. Nguni PN, Were MC, Babic A. Users’ perception of factors contributing to electronic medical records systems use: a focus group discussion study in healthcare facilities setting in Kenya. BMC Med Inf Dec Mak. 2021;21(362). 10.1186/s12911-021-01737-x . Attafuah PYA, Abor PA, Abbuosi AA, Nketiah-Amponsah E, Tenza IS. Satisfied or not satisfied? Electronic health records system implementation in Ghana: Health leaders’ perspective. BMC Med Inf Dec Mak. 2022;22(249). 10.1186/s12911-022-01998-0 . Lin H-L, Wu D-C, Cheng S-M, Chen C-J, Wang M-C, Cheng C-A. Association between electronic medical records and healthcare quality. Med. 2020;99(e21182):31. 10.1097/MD.0000000000021182 . Adetoyi OE, Raji OA. Electronic health record design for inclusion in sub-Saharan Africa medical record informatics. Sci Afr. 2020;7(00304). 10.1016/j.sciaf.2020.e00304 . Hamade N, Terry A, Malvankar-Mehta M. Interventions to improve the use of EMR in primary health care: a systematic review and meta-analysis. BMJ Health Care Inf. 2019;26(e000023). 10.1136/bmjhci-2019-000023 . Honavar SG. Electronic medical records – The good, the bad and the ugly. Indian J Ophthalmol Case Rep. 2020;68(3):p417–8. 10.4103/ijo.IJO_278_20 . Tapuria A, Porat T, Kalra D, Dsouza G, Xiaohui S, Curcin V. Impact of patient access to their electronic health record: systematic review. Inf Health Soc Care. 2021;46(2):194–206. 10.1080/17538157.2021.1879810 . Janett SR, Yeracaris PP. Electronic medical records in the American health system: challenges and lessons learned. Scie G. 2020;25(4):1293–304. 10.1590/1413-81232020254.28922019 . Wali RM, Alqathtani RM, Alharazi SK, Bukhari SA, Quqandi SM. Patient satisfaction with the implementation of electronic medical records in the Western Region, Saudi Arabia, 2018. BMC Fam Pract. 2020;21(37). 10.1186/s12875-020-1099-0 . Sieck CJ, Pearl N, Bright TJ, Yen P-Y. A qualitative study of physician perspective on adaptation to electronic health records. BMC Med Inf Dec Mak. 2020;20(25). 10.1186/s12911-020-1030-6 . Rahal RM, Mercer J, Kuziemsky C, Yaya S. Factors affecting the mature use of electronic medical records by primary care physicians: a systematic review. BMC Med Inf Dec Mak. 2021;21(67). 10.1186/s12911-021-01434-9 . Jabour AM. The impact of electronic health records on the duration of patients’ visits: Time and motion study. JMIR Med Inf. 2020;8(2):e16502. 10.2196/16502 . Quinn M, Forman J, Harrod M, Winter S, Fowler KE, Krein SL, et al. Electronic health records, communication and data sharing: Challenges and opportunities for improving the diagnostic process. Diagnosis. 2019;6(3):241–8. 10.1515/dx-2018-0036 . Yi M. Major issues in adoption of electronic medical records. Journ Digit Inf Man. 2018;16(4). 10.6025/jdim/2018/16/4/180-191 . Khalifa M. Perceived benefits of implementing and using hospital information systems and electronic medical records. Inf Emp Health Transform. 2017;238:165–8. 10.3233/978-1-61499-781-8-165 . Johnson WG, Gee PM, Kelly LA, Buttler RJ. The effect of electronic medical records on nurses’ job satisfaction: A multi-year analysis. Urban Stud Pub Admin. 2021;4(3). 10.22158/uspa.v4n3p1 . Khairat S, Xi L, Liu S, Shrestha S, Austin C. Understanding the association between electronic health record satisfaction and the well-being of nurses: Survey study. JMIR Nurs. 2020;3(1):e13996. 10.2196/13996 . Berihun B, Atnafu DD, Sitotaw G. Willingness to use electronic medical record (EMR) system in healthcare facilities of Bahir Dar city, Northwest Ethiopia. Biomed Res Int. 2020. 10.1155/2020/3827328 . Or C, Tong E, Tan J, Chan A. Exploring factors affecting voluntary adoption of electronic medical records among physicians and clinical assistants of small or solo private general practice clinics. Journ Med Sys. 2018;42(121). 10.1007/s10916-018-0971-0 . Joukes E, de Keizer NF, de Bruijne MC, Abu-Hanna A, Cornet R. Impact of electronic versus paper-based recording before HER implementation on health care professionals’ perceptions of HER use, data quality and data reuse. Appl Clin Inf. 2019;10(2):199–209. 10.1055/s-0039-1681054 . Heponiemi T, Gluschkoff K, Vehko T, Kaihlanen A, Saranto K, Nissinen S, Nadav J, Kujala S. Electronic health record implementations and insufficient training endanger nurses’ well-being: Cross-sectional survey study. J Med Internet Res. 2021;23(12):e27096. 10.2196/27096 . Tubaishat A. Perceived usefulness and perceived ease of use of electronic health records among nurses: Application of the Technology Acceptance Model. Inf Health Soc Care. 2017;43(4):379–89. 10.1080/17538157.2017.1363761 . Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quart. 1989;13(3):319–40. 10.2307/249008 . Handayani PW, Hidayanto AN, Pinem AA, Hapsari IC, Sandhyaduhita PI, Budi I. Acceptance model of hospital information system. 2017; 99:11–28 10.1016/j.ijmedinf.2016.12.004 United Nations Development Programme. The SDGs in action. https://www.undp.org/sustainable-development-goals . Accessed 26 July 2024. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 12 May, 2025 Read the published version in BMC Medical Informatics and Decision Making → Version 1 posted Editorial decision: Revision requested 30 Sep, 2024 Editor assigned by journal 27 Sep, 2024 Submission checks completed at journal 27 Sep, 2024 First submitted to journal 25 Sep, 2024 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5150449","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":360618295,"identity":"94c058bb-41ec-45c5-b2d0-ff67f5e7fbcc","order_by":0,"name":"Tebeli E. Sekoai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYFACNiA2ACHmhgMfQHx24rQYALUwNhycAeIzE6WFAaKFmQfEJqRFvr0t8cGPgj9y5uyNjYdtfm2T52NmYPzwMQe3FoMzxw4b9hgYGFv2HGw4nNt327CNmYFZcuY2PFok0tskeAwMEjfcSARq6bnNCNTCxsyLR4v8/Odtkn8MDOo33H/YcNiy57Y9QS0MN9iOSQNtSTC4wdhwmOHH7USCWgzOpCUbyxgYG+7sSWw42NtwO7mNmbEZr1/k248ZPnzzR07enP3w4Q8//ty2nd/efPDDR3wOQwGMbWCygVj1IPCHFMWjYBSMglEwUgAAOwVTmwqVlywAAAAASUVORK5CYII=","orcid":"","institution":"University of Pretoria","correspondingAuthor":true,"prefix":"","firstName":"Tebeli","middleName":"E.","lastName":"Sekoai","suffix":""},{"id":360618298,"identity":"65c59fdc-883b-4554-8df3-de5d2d9028a9","order_by":1,"name":"Astrid C Turner","email":"","orcid":"","institution":"University of Pretoria","correspondingAuthor":false,"prefix":"","firstName":"Astrid","middleName":"C","lastName":"Turner","suffix":""},{"id":360618301,"identity":"922d15d0-da23-4877-bfe8-0b334e9a2287","order_by":2,"name":"Janine Mitchell","email":"","orcid":"","institution":"University of Pretoria","correspondingAuthor":false,"prefix":"","firstName":"Janine","middleName":"","lastName":"Mitchell","suffix":""}],"badges":[],"createdAt":"2024-09-25 08:53:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5150449/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5150449/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12911-025-02858-3","type":"published","date":"2025-05-12T15:57:13+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":72281955,"identity":"557a75af-c24e-47bc-82ce-ac02d4e1f527","added_by":"auto","created_at":"2024-12-24 16:34:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":178385,"visible":true,"origin":"","legend":"\u003cp\u003eStages of the eRegister implementation [Created by the researcher]\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5150449/v1/f54fba2ffad0ed49d0e01805.png"},{"id":83067761,"identity":"c96bd544-dc27-4d75-9f99-23339ea6606e","added_by":"auto","created_at":"2025-05-19 16:05:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1015304,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5150449/v1/cf4a177a-1d8d-42c1-9e2b-4209f2d8a8b5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Insights into healthcare workers' perceptions of electronic medical record system utilization: A cross-sectional study in Mafeteng District, Lesotho","fulltext":[{"header":"Background","content":"\u003cp\u003eSince February 2015, the US President\u0026rsquo;s Emergency Plan for AIDS Relief (PEPFAR) has supported Lesotho\u0026rsquo;s Ministry of Health (MOH) in transforming the country\u0026rsquo;s Health Management Information System (HMIS) by introducing the District Health Information Software 2 (DHIS2) for data capture, storage, and program queries, which has drastically enhanced the quality of HIV care and treatment data [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, discrepancies persisted between the program data in DHIS2, and survey data from the Lesotho Population-based HIV Impact Assessment (LePHIA), a household-based national survey conducted between November 2016 and May 2017 to provide a detailed status of the HIV epidemic in the country [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. For example, while the LePHIA survey estimated that 235,135 people living with HIV were on antiretroviral therapy (ART) drugs, the DHIS2 reported only 149,951 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecognizing the significant gap identified, the Ministry of Health (MOH) took proactive steps to address it by using electronic medical records (EMR). Their approach involved adopting, developing, and deploying an open-source client-level electronic register (eRegister) tailored for HIV, Tuberculosis (TB), and Maternal and Child Health (MCH) services. This strategic shift was based on the recommendations from a thorough assessment conducted in 2017, which highlighted the inadequacies of the hospital-based EMR system previously introduced across 16 public health hospitals in Lesotho's 10 districts back in 2013 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe evaluation highlighted numerous challenges encountered during the initial implementation of the hospital-based EMR system. These included the Ministry not receiving crucial monthly outpatient department (OPD) reports from the 16 hospitals, discontinuation of EMR implementation in several health facilities, and instances of substandard implementation where EMR systems remained in use but were not optimally utilized [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e Building upon lessons learned from this pilot, the eRegister emerged as a promising solution, serving both as a clinical decision-support tool to enhance patient care and as a dynamic monitoring and evaluation instrument aimed at addressing underreporting. Notably, the eRegister's integration with the national DHIS2 facilitated more robust data collection and analysis. Given its demonstrated efficacy, the MOH devised a three-phased implementation plan to systematically roll out the eRegister across relevant healthcare settings [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe MOH implemented the EMR system in 2018, to collect and use high-quality patient-level data, to uniquely distinguish and track patients through the 95-95-95 targets, and to automatically generate facility-level routine and key operational reports in support of data usage and evidence-based programming [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. An EMR is a computerized system for keeping track of patient health information that offers ways to gather, store, and display patient data to provide HCWs with accurate and up-to-date information about the patient\u0026rsquo;s medical records to support patient care and enhance the quality of healthcare [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe implementation of EMR benefits healthcare workers (HCWs), patients, and healthcare sector management in different ways. However, HCWs are in the best position to report what encourages or limits its usage as they are the first-hand users of the system [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The use of EMR improves healthcare quality, productivity and efficiency while also leading to better public health outcomes [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and aligning with the Sustainable Development Goal (SDG) 3 of good health and well-being [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The benefits of EMR include enhanced data quality as well as improved and prompt access to records for all healthcare service providers [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMoreover, EMR provides patients with easy access to their medical health records which promotes better health outcomes due to improved self-care, informed decision-making, enhanced medical compliance, and stronger trust and communication between patients and HCWs [\u003cspan additionalcitationids=\"CR14 CR15 CR16\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Some of the benefits relate to time management and cost savings due to reduced duplication of tests and sharing of patient records among HCWs [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], as well as reduced HCWs, storage facilities, and overall healthcare services such as medical transcriptions and reporting [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe challenges of EMR implementation include standardized communication between patients and physicians which results in a more formal relationship [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The system is believed to significantly change the workflow of HCWs, hence complicating workloads and reducing productivity [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In addition, the limited adoption and use of EMR systems in developing countries are related to HCWs\u0026rsquo; attitudes and awareness levels, lack of proper management, resistance from users, poor commitment from staff and lack of computer skills [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. A lack of training also contributes to the high rate of EMR rejection by the HCWs as studies postulate that sufficient training related to EMR implementation is associated with improved well-being of HCWs and appears to be extremely crucial [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are no studies available related to the views of the frontline end-users of the system since the EMR implementation of the system in Lesotho. It is imperative to understand HCWs\u0026rsquo; perceptions of the usage of the system, and their willingness to utilize it, as they influence the effectiveness of its implementation. Therefore, the aim of this study was to examine HCWs\u0026rsquo; perceptions of the EMR system in Mafeteng district in Lesotho.\u003c/p\u003e \u003cp\u003e Ethical clearance for the study was obtained from the University of Pretoria Faculty of Health Sciences Research Ethics Committee (reference number 492/2023) and the Ministry of Health (MOH) National Research Ethics Committee of Lesotho (ID237-2023). Permission to collect data was obtained from the District Health Management Team of Mafeteng. Participants were duly informed that participation in the study was voluntary. A signed informed consent form was required to proceed.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eA descriptive cross-sectional study was conducted at 17 government and Christian Health Association of Lesotho (CHAL) healthcare facilities in the Mafeteng district. The health facilities included one district referral hospital and 16 clinics.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy population and sample\u003c/h3\u003e\n\u003cp\u003eOne hundred forty-five HCWs who were involved in the utilization of the EMR system in Mafeteng district were invited to participate in the study. These HCWs included registered nurse midwives, nurse assistants, HTS counsellors, and data clerks. Purposive non-random sampling was used to select participants from the population.\u003c/p\u003e \u003cp\u003eThe questionnaire was distributed to the respondents via a link to a web-based questionnaire (Google form) during sites visits, and those who did not utilize the system were excluded from the study.\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eA structured questionnaire was developed, guided by one from Tubaishat [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] which determined the factors associated with HCWs\u0026rsquo; perceptions of the EMR system.\u003c/p\u003e \u003cp\u003eThe original questionnaire developed by Davis FD consists of 28 items that assess both PU and PEU and was considered to be valid and reliable. The reliability of PU and PEU were found to be 0.97 and 0.91 respectively, while their validity was reported significant at 0.05, where PU was 100% significant 100% of the time and PEU 95.6%.\u003csup\u003e28\u003c/sup\u003e The questionnaire was pretested with ten respondents from health facilities outside the sites of interest, to ensure reliability, accuracy, and consistency. The questionnaire adopted the Technology Acceptance Model (TAM), a theoretical framework that explains how users come to accept and use a technology, which centres on perceived usefulness (PU) and perceived ease of use (PEU) as the main influencers of individuals\u0026rsquo; acceptance and intention to utilize a system [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Perceived usefulness is defined as the extent to which an individual believes that using technology will enhance their job performance while PEU is characterized by the extent to which an individual perceives technology as easy to learn, use, and integrate in their workflow [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The model proposes that these perceptions influence users\u0026rsquo; attitude towards usage of technology, hence affecting their intentions to adopt and intention to utilize it.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eStata/BE 18.0 was used to analyse the data after it was entered into EpiData software. Descriptive statistics was conducted to calculate the frequencies of the demographic characteristics of the sample and the perceived usefulness and perceived ease-of-use of the EMR. Multiple regression analysis was conducted to identify the outcomes of the healthcare workers\u0026rsquo; perceptions. Additional text by participants was extracted to explain quantitative results.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ea. Descriptive analysis of participants\u0026rsquo; demographic characteristics\u003c/h2\u003e \u003cp\u003eThere was a response rate of 49% (n\u0026thinsp;=\u0026thinsp;71). Among the professions represented, registered nurse midwives constituted the largest group (45.07%), while nurse assistants made up a smaller proportion (7.04%). Regarding educational qualifications, 12 respondents (16.90%) held the COSC/LGCSE qualification, while majority of the respondents were Bachelor\u0026rsquo;s degree holders (43.66%). Notably, the majority of participants (50.70%) reported having \u0026lsquo;good computer skills\u0026rsquo;, implying that they were proficient in common computer applications and tools such as Microsoft Word, Excel and PowerPoint.\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\u003eDemographic characteristics of respondents\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=\"left\" 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\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21 (29.58)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50 (70.42)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eProfession\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRegistered nurse midwife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32 (45.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNurse assistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (7.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHTS counsellor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18 (25.35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eData clerk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (22.54)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eQualification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCOSC/LGCSE (Equivalent to Matric)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (16.90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (33.80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBachelor\u0026rsquo;s Degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31 (43.66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHonors/Postgraduate Diploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (5.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eComputer skills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (5.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36 (50.70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVery Good\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31 (43.66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eb. Perceived usefulness\u003c/h3\u003e\n\u003cp\u003eAccording to Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, 52.11% of the HCWs strongly agreed, while 35.21% agreed that the EMR system is useful in their job. The respondents stated that the system makes patients\u0026rsquo; record keeping and retrieving of information very easy. One respondent mentioned that the system enables the immediate appointment of patients\u0026rsquo; next visit dates and thus minimizes the risk of missed appointments. Approximately 38.03% of the HCWs agreed while 32.39% strongly agreed that their jobs would be difficult without the EMR system, and the majority (83.1%) agreed or strongly agreed that the system improves their job performance. The respondents stated that compiling reports has become easier with the use of the system, hence making their jobs less difficult. They also indicated that the system has made patient monitoring and management easier since access to patients\u0026rsquo; records is effortless.\u003c/p\u003e \u003cp\u003eA significant number of the HCWs (78.87%) agreed or strongly agreed that the EMR system saves them time and enables them to accomplish more tasks than would otherwise be possible, as postulated by 71.84% of the respondents. A large proportion of the HCWs (84.51%) believe that the system improves the quality of work they do and 76.06% trust that it increases their productivity. They mentioned that reports from the EMR system meet most of the data quality dimensions such as timeliness, and they also have an opportunity to make informed decisions concerning patients\u0026rsquo; health needs. However, approximately 9.82% of the HCWs are neutral about the usefulness of the system, as they believe that they have been performing tasks very well without it, and some believe that it has added more workload.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePU items\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePU items\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eRating Scale\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStrongly Disagree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDisagree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNeutral\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAgree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrongly Agree\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. My job would be difficult to perform without EMRs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7,04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19,72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e38,03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e32,39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Using EMRs improves my job performance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11,27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36,62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46,48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. EMRs save me time and enable me to accomplish tasks more quickly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5,63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12,68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25,35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e53,52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. Using EMRs allows me to accomplish more work than would otherwise be possible\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21,13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30,99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40,85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. Using EMRs enhances my effectiveness on the job\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7,04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12,68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32,39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e47,89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6. Using EMRs improves the quality of work I do\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11,27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35,21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e49,3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7. Using EMRs increases my productivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14,08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35,21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40,85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8. Overall, I find the EMR system useful in my job\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9,86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35,21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e52,11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003ec. Perceived ease of use\u003c/h3\u003e\n\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, a vast majority of the HCWs (59.15% and 26.76%) found the EMR system easy to use. This is supported by the respondents\u0026rsquo; opinions that the language of the system is very easy and straightforward, and that they receive supportive supervision from the implementers where they obtain clarity on several issues related to the system. The majority of the HCWs (47.89%) strongly disagreed, while 33.8% disagreed that interacting with the system is often frustrating and requires frequent consultations with the manual. A total of 40.85% of the HCWs strongly disagreed, while 25.35% disagreed that interacting with the system requires a lot of their mental effort. In addition, 85.91% strongly disagreed or disagreed that they find the system cumbersome to use. The respondents mentioned that they received enough training to allow them to navigate the system with ease, without depending on the manual.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePEU items\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePEU items\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eRating Scale\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStrongly Disagree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDisagree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNeutral\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAgree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrongly Agree\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. I often become confused and make frequent errors when I use the EMR system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39,44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45,07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9,86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1,41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4,23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Interacting with the EMR system is often frustrating and requires me to consult the manual more often\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47,89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33,8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9,86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5,63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2,82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. Interacting with the EMR system requires a lot of my mental effort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40,85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25,35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18,31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14,08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1,41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. I find it easy to recover from errors encountered while using the EMR system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5,63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8,45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32,39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e49,3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. The EMR system often behaves in unexpected ways\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38,03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23,94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26,76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5,63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6. I find it cumbersome (difficult) to use the EMR system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50,7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35,21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2,82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7,04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7. It is easy for me to remember how to perform tasks using the EMR system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7,04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5,63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39,44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46,48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8. Overall, I find the EMR system easy to use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5,63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26,76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e59,15\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\u003eA notable number of the HCWs (81.69%) agreed or strongly agreed that they find it easy to recover from errors encountered while using the system, while 85.92% find it easy to remember how to perform tasks using the EMR system. This pertains to the fact that the system highlights errors immediately and autocorrects some of the errors. The respondents also pointed out that the system allows editing of information at any point and that errors are usually highlighted by a star, and hence are easy to recognize and recover. The HCWs mentioned that they experience frequent daily network issues, as well as the unavailability of electricity at some of the healthcare facilities, hence 43.66% strongly disagreed or disagreed that the system behaves in unexpected ways. A smaller portion of the HCWs (8.45%), however, do not find the EMR system easy to use, mainly because of their poor computer skills, while others believe that paper-based registers are much easier to use.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ed. Multiple linear regression\u003c/h2\u003e \u003cp\u003eTables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e present the results of a multiple linear regression analysis conducted to explore the relationships between demographic characteristics of HCWs and their perceptions of the EMR system.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLinear regression for PU\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eModel Summary\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u0026thinsp;=\u0026thinsp;0.3155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdj R-squared\u0026thinsp;=\u0026thinsp;0.2740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF-statistic\u0026thinsp;=\u0026thinsp;7.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProb\u0026thinsp;\u0026gt;\u0026thinsp;F\u0026thinsp;=\u0026thinsp;0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRoot MSE\u0026thinsp;=\u0026thinsp;0.66376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNumber of obs\u0026thinsp;=\u0026thinsp;71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariable\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCoefficient\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eStd. Error\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003et-Value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep-Value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e95% Confidence interval\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.350 to 0.408\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfession\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.173 to 0.117\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQualification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.028 to 0.391\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComputer skills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.308 to 0.975\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.413 to 3.203\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 F-test (Prob\u0026thinsp;\u0026gt;\u0026thinsp;F\u0026thinsp;=\u0026thinsp;0.0000) indicates that at least one of the predictor variables in the model has a significant relationship with PU, and approximately 31.55% of the variance in PU is explained by the model. The predictor variables included in the model were sex, profession, qualification, and computer skills. The p-values for sex, profession and qualification were 0.879, 0.701 and 0.088 respectively, suggesting that the variables are not statistically significant at 0.05, and do not have any significant impact on the PU of EMR. In contrast, computer skills demonstrated high significance, (p-value\u0026thinsp;=\u0026thinsp;0.000), suggesting that better computer skills are associated with a greater PU.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLinear regression for PEU\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eModel Summary\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR-squared\u0026thinsp;=\u0026thinsp;0.2802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdj R-squared\u0026thinsp;=\u0026thinsp;0.2366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF-statistic\u0026thinsp;=\u0026thinsp;6.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProb\u0026thinsp;\u0026gt;\u0026thinsp;F\u0026thinsp;=\u0026thinsp;0.0002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRoot MSE\u0026thinsp;=\u0026thinsp;0.95246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNumber of obs\u0026thinsp;=\u0026thinsp;71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariable\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCoefficient\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eStd. Error\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003et-Value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ep-Value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e95% Confidence interval\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.527 to 0.560\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfession\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.154 to 0.262\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQualification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.024 to 0.624\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComputer skills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.198 to 1.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.941 to 3.062\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e reveals that the model is statistically significant (Prob\u0026thinsp;\u0026gt;\u0026thinsp;F\u0026thinsp;=\u0026thinsp;0.0002, and that at least 28.02% of the variance in PEU is explained by the model. Sex (p-value\u0026thinsp;=\u0026thinsp;0.953) and profession (p-value\u0026thinsp;=\u0026thinsp;0.606) did not have any significant impact on the PEU of the EMR system. Qualification and computer skills are on the other hand statistically significant, with p-values of 0.035 and 0.007 respectively, indicating an association with greater PEU of the system.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn general, the majority of the HCWs who participated in this study perceive the EMR system as both useful (87.32%) and easy-to-use (85.91%), which highlights the positive acceptance of the technology. This study revealed that demographic factors such as qualifications and computer literacy have a significant impact on the HCWs\u0026rsquo; perceptions of the EMR system. A study by Tubaishat [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] also revealed that computer skills impact nurses\u0026rsquo; PU and PEU of the EMR system. The implementation of EMR is aimed at solving existing inconsistencies within data management and patient care within the healthcare system, and feedback from the respondents revealed that EMR is capable of enhancing patient data management and enabling quick access to patient files [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe study identified several interesting issues regarding the perceptions of the HCWs in the district. The positive reception of the HCWs means that the system's implementation will be sustainable and thus positively impact patient care and management. It is also worth noting a high percentage of HCWs agreed that EMR improves their job performance and enhances the quality of their work. The findings that higher qualifications and better computer skills are associated with greater perceived usefulness and ease of use of the EMR system are particularly interesting, as they highlight specific areas where targeted training and support could increase the adoption rate.\u003c/p\u003e \u003cp\u003eThe key strengths of the study relate to the fact that the findings are highly relevant to healthcare administrators and policymakers, as they identify the factors that influence the successful implementation and utilization of the EMR system. Adopting the conceptual framework of the TAM, which is a widely known framework for evaluating factors relating to technology adoption improves the credibility of this study. Apart from that, the study targeted the HCWs to examine factors and provide relevant insights into the utilization of the system, as they are the first-hand users of the system.\u003c/p\u003e \u003cp\u003eNonetheless, there are notable limitations exhibited by this study. The researcher was compelled to leave the questionnaires without ensuring complete respondent participation due to execution during working hours, thus contributing to the low response rate (49%). Additionally, budget constraints restricted the study to a single district, thereby limiting the generalizability of its findings to the broader country context. Although TAM is a widely used framework, it primarily focuses on assessing HCWs\u0026rsquo; perceptions and attitudes toward the EMR system. It overlooks other critical factors that may influence EMR implementation, such as system quality, organizational culture, and individual social norms. Furthermore, the study identified network connectivity and electricity supply as some of the significant barriers to effective usage of the EMR system in the health facilities, which result in service delivery interruptions.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eRecommendations\u003c/h2\u003e \u003cp\u003eBased on the study\u0026rsquo;s findings related to HCWs\u0026rsquo; perceptions and challenges regarding EMR system implementation, we recommend that the MOH take specific actions. Firstly, the MOH is advised to invest in robust infrastructure, reliable network connections and electricity supplies to ensure consistency in the usage of the system. The government is advised to prioritize installation of high-speed internet connections and reliable power sources such as backup solar power systems and generators to alleviate the impact of power outages. These recommended solutions will align with SDG 9, which centres on building resilient infrastructure, promoting inclusive and sustainable industrialization, and fostering innovation [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSecondly, there is a need for enhanced training programs aimed at improving the HCWs\u0026rsquo; computer literacy, which are specifically tailored to the usage of the EMR system. Additionally, the ministry can foster continued career development by introducing mentorship programs and peer learning opportunities as computer literacy has been shown to have a remarkable impact on the HCWs\u0026rsquo; perceptions of the usage of the system. The implementation of comprehensive training programs on EMR has the potential to enhance the capabilities, skills and knowledge of the HCWs, hence advancing the goal of SDG 4, which focuses on quality education [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition, to ensure comprehensive patient data management, interoperability of the EMR system and DHIS2 is critical for seamless exchange and communication of data. Interoperability allows sharing of patient across different healthcare system settings, hence improving productivity and efficiency. The EMR system stores highly confident and sensitive patient information, which must be protected against unauthorised access at all times. Thus, it is crucial to implement robust access control mechanisms to ensure that access is limited to authorized HCWs.\u003c/p\u003e \u003cp\u003eIt is also imperative to introduce regular feedback mechanisms in the system so that issues are identified and solutions are provided on time. There is also a need for continuous research and evaluations to assess the long-term impact of the system and the HCWs\u0026rsquo; satisfaction as well as to monitor implementations of the recommendations, for improved patient care and more effective healthcare data management.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study aimed to examine the perceptions of the HCWs towards the utilization of the EMR system, intending to explore their perceived usefulness and ease of use. The findings of the study showed that the majority of the HCWs convey high perceptions of the usefulness and ease of use of the system in Mafeteng district. The benefits of the system have been duly noted, as outlined by the participants, as well as the relationships between the demographic characteristics and the PU and PEU of the EMR system.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eART Antiretroviral therapy\u003c/p\u003e \u003cp\u003eCHAL Christian Health Association of Lesotho\u003c/p\u003e \u003cp\u003eCOSC Cambridge Overseas School Certificate (Equivalent to Matric)\u003c/p\u003e \u003cp\u003eDHIS2 District Health Information Software 2\u003c/p\u003e \u003cp\u003eEMR Electronic Medical Record\u003c/p\u003e \u003cp\u003eeRegister Electronic Register\u003c/p\u003e \u003cp\u003eHCWs Healthcare workers\u003c/p\u003e \u003cp\u003eHMIS Health Management Information System\u003c/p\u003e \u003cp\u003eHTS HIV Testing Services\u003c/p\u003e \u003cp\u003eLePHIA Lesotho Population-based HIV Impact Assessment\u003c/p\u003e \u003cp\u003eLGCSE Lesotho General Certificate of Secondary School (Equivalent to Matric)\u003c/p\u003e \u003cp\u003eMCH Maternal Child Health\u003c/p\u003e \u003cp\u003eMOH Ministry of Health\u003c/p\u003e \u003cp\u003eOPD Out-patient Department\u003c/p\u003e \u003cp\u003ePEPFAR President\u0026rsquo;s Emergency Plan for AIDS Relief\u003c/p\u003e \u003cp\u003ePEU Perceived Ease-of-Use\u003c/p\u003e \u003cp\u003ePU Perceived Usefulness\u003c/p\u003e \u003cp\u003eSDG Sustainable Development Goal\u003c/p\u003e \u003cp\u003eSI Strategic Information\u003c/p\u003e \u003cp\u003eTAM Technology Acceptance Model\u003c/p\u003e \u003cp\u003eTB Tuberculosis\u003c/p\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e This study was approved by the University of Pretoria Faculty of Health Sciences Research Ethics Committee (reference number 492/2023). The Ministry of Health (MOH) National Research Ethics Committee of Lesotho (ID237-2023) also approved the study and permission to collect data was obtained from the District Health Management Team of Mafeteng. Participants were duly informed that in the study was voluntary and were asked to sign the informed consent form.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eParticipants were duly informed that the study findings may be published but that measure would be taken to anonymise their role.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eTES developed the original draft of the manuscript, conducted data collection and analysis, and participated in writing up and shaping the manuscript. ACT and JM provided supervision and constructive feedback during the development and write up of the manuscript. The final manuscript was read and approved by all the authors.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to give special thanks to the Ministry of Health in Lesotho for granting access for data collection in the health facilities as well as to the participants who gave off their time for the study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe dataset that supports the findings of this study has been deposited in the University of Pretoria research repository with the following DOI for access: https://doi.org/10.25403/UPresearchdata.27078121.v1.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLesotho Ministry of Health. Standard operating procedure for transition to the eRegister Live DHIS2 reporting. February 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLesotho Population-based HIV Impact. Assessment 2016\u0026ndash;2017. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://phia.icap.columbia.edu/wp-content/uploads/2020/02/LePHIA_FinalReport_Web.pdf\u003c/span\u003e\u003cspan address=\"https://phia.icap.columbia.edu/wp-content/uploads/2020/02/LePHIA_FinalReport_Web.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 07 April 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJimma BL, Enyew DB. Barriers to the acceptance of electronic medical records from the perspective of physicians and nurses: A scoping review. Inf Med Unlocked. 2022;31(100991). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.imu.2022.100991\u003c/span\u003e\u003cspan address=\"10.1016/j.imu.2022.100991\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoonstra A, Vos J, Rosenberg L. The effect of electronic health records on the medical professional identity of physicians: a systematic literature review. Procedia Comput Sci. 2022;196:272\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.procs.2021.12.014\u003c/span\u003e\u003cspan address=\"10.1016/j.procs.2021.12.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOumer A, Muhye A, Dagne I, Ishak N, Ale A, Bekel A. Utilization, determinants and prospects of electronic medical records in Ethiopia. Biomed Res Int. 2021; 2021(2230618); \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2021/2230618\u003c/span\u003e\u003cspan address=\"10.1155/2021/2230618\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGovernment of the Kingdom of Lesotho Ministry of Health. Electronic medical record (EMR) assessment: Final report. 18 October 2017.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNguni PN, Were MC, Babic A. Users\u0026rsquo; perception of factors contributing to electronic medical records systems use: a focus group discussion study in healthcare facilities setting in Kenya. BMC Med Inf Dec Mak. 2021;21(362). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12911-021-01737-x\u003c/span\u003e\u003cspan address=\"10.1186/s12911-021-01737-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAttafuah PYA, Abor PA, Abbuosi AA, Nketiah-Amponsah E, Tenza IS. Satisfied or not satisfied? Electronic health records system implementation in Ghana: Health leaders\u0026rsquo; perspective. BMC Med Inf Dec Mak. 2022;22(249). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12911-022-01998-0\u003c/span\u003e\u003cspan address=\"10.1186/s12911-022-01998-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLin H-L, Wu D-C, Cheng S-M, Chen C-J, Wang M-C, Cheng C-A. Association between electronic medical records and healthcare quality. Med. 2020;99(e21182):31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/MD.0000000000021182\u003c/span\u003e\u003cspan address=\"10.1097/MD.0000000000021182\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdetoyi OE, Raji OA. Electronic health record design for inclusion in sub-Saharan Africa medical record informatics. Sci Afr. 2020;7(00304). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.sciaf.2020.e00304\u003c/span\u003e\u003cspan address=\"10.1016/j.sciaf.2020.e00304\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHamade N, Terry A, Malvankar-Mehta M. Interventions to improve the use of EMR in primary health care: a systematic review and meta-analysis. BMJ Health Care Inf. 2019;26(e000023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjhci-2019-000023\u003c/span\u003e\u003cspan address=\"10.1136/bmjhci-2019-000023\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHonavar SG. Electronic medical records \u0026ndash; The good, the bad and the ugly. Indian J Ophthalmol Case Rep. 2020;68(3):p417\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/ijo.IJO_278_20\u003c/span\u003e\u003cspan address=\"10.4103/ijo.IJO_278_20\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTapuria A, Porat T, Kalra D, Dsouza G, Xiaohui S, Curcin V. Impact of patient access to their electronic health record: systematic review. Inf Health Soc Care. 2021;46(2):194\u0026ndash;206. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/17538157.2021.1879810\u003c/span\u003e\u003cspan address=\"10.1080/17538157.2021.1879810\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJanett SR, Yeracaris PP. Electronic medical records in the American health system: challenges and lessons learned. Scie G. 2020;25(4):1293\u0026ndash;304. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1590/1413-81232020254.28922019\u003c/span\u003e\u003cspan address=\"10.1590/1413-81232020254.28922019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWali RM, Alqathtani RM, Alharazi SK, Bukhari SA, Quqandi SM. Patient satisfaction with the implementation of electronic medical records in the Western Region, Saudi Arabia, 2018. BMC Fam Pract. 2020;21(37). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12875-020-1099-0\u003c/span\u003e\u003cspan address=\"10.1186/s12875-020-1099-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSieck CJ, Pearl N, Bright TJ, Yen P-Y. A qualitative study of physician perspective on adaptation to electronic health records. BMC Med Inf Dec Mak. 2020;20(25). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12911-020-1030-6\u003c/span\u003e\u003cspan address=\"10.1186/s12911-020-1030-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRahal RM, Mercer J, Kuziemsky C, Yaya S. Factors affecting the mature use of electronic medical records by primary care physicians: a systematic review. BMC Med Inf Dec Mak. 2021;21(67). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12911-021-01434-9\u003c/span\u003e\u003cspan address=\"10.1186/s12911-021-01434-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJabour AM. The impact of electronic health records on the duration of patients\u0026rsquo; visits: Time and motion study. JMIR Med Inf. 2020;8(2):e16502. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/16502\u003c/span\u003e\u003cspan address=\"10.2196/16502\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQuinn M, Forman J, Harrod M, Winter S, Fowler KE, Krein SL, et al. Electronic health records, communication and data sharing: Challenges and opportunities for improving the diagnostic process. Diagnosis. 2019;6(3):241\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1515/dx-2018-0036\u003c/span\u003e\u003cspan address=\"10.1515/dx-2018-0036\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYi M. Major issues in adoption of electronic medical records. Journ Digit Inf Man. 2018;16(4). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.6025/jdim/2018/16/4/180-191\u003c/span\u003e\u003cspan address=\"10.6025/jdim/2018/16/4/180-191\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhalifa M. Perceived benefits of implementing and using hospital information systems and electronic medical records. Inf Emp Health Transform. 2017;238:165\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3233/978-1-61499-781-8-165\u003c/span\u003e\u003cspan address=\"10.3233/978-1-61499-781-8-165\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohnson WG, Gee PM, Kelly LA, Buttler RJ. The effect of electronic medical records on nurses\u0026rsquo; job satisfaction: A multi-year analysis. Urban Stud Pub Admin. 2021;4(3). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.22158/uspa.v4n3p1\u003c/span\u003e\u003cspan address=\"10.22158/uspa.v4n3p1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhairat S, Xi L, Liu S, Shrestha S, Austin C. Understanding the association between electronic health record satisfaction and the well-being of nurses: Survey study. JMIR Nurs. 2020;3(1):e13996. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/13996\u003c/span\u003e\u003cspan address=\"10.2196/13996\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerihun B, Atnafu DD, Sitotaw G. Willingness to use electronic medical record (EMR) system in healthcare facilities of Bahir Dar city, Northwest Ethiopia. Biomed Res Int. 2020. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2020/3827328\u003c/span\u003e\u003cspan address=\"10.1155/2020/3827328\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOr C, Tong E, Tan J, Chan A. Exploring factors affecting voluntary adoption of electronic medical records among physicians and clinical assistants of small or solo private general practice clinics. Journ Med Sys. 2018;42(121). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10916-018-0971-0\u003c/span\u003e\u003cspan address=\"10.1007/s10916-018-0971-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoukes E, de Keizer NF, de Bruijne MC, Abu-Hanna A, Cornet R. Impact of electronic versus paper-based recording before HER implementation on health care professionals\u0026rsquo; perceptions of HER use, data quality and data reuse. Appl Clin Inf. 2019;10(2):199\u0026ndash;209. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1055/s-0039-1681054\u003c/span\u003e\u003cspan address=\"10.1055/s-0039-1681054\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeponiemi T, Gluschkoff K, Vehko T, Kaihlanen A, Saranto K, Nissinen S, Nadav J, Kujala S. Electronic health record implementations and insufficient training endanger nurses\u0026rsquo; well-being: Cross-sectional survey study. J Med Internet Res. 2021;23(12):e27096. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/27096\u003c/span\u003e\u003cspan address=\"10.2196/27096\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTubaishat A. Perceived usefulness and perceived ease of use of electronic health records among nurses: Application of the Technology Acceptance Model. Inf Health Soc Care. 2017;43(4):379\u0026ndash;89. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/17538157.2017.1363761\u003c/span\u003e\u003cspan address=\"10.1080/17538157.2017.1363761\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quart. 1989;13(3):319\u0026ndash;40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2307/249008\u003c/span\u003e\u003cspan address=\"10.2307/249008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHandayani PW, Hidayanto AN, Pinem AA, Hapsari IC, Sandhyaduhita PI, Budi I. Acceptance model of hospital information system. 2017; 99:11\u0026ndash;28 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ijmedinf.2016.12.004\u003c/span\u003e\u003cspan address=\"10.1016/j.ijmedinf.2016.12.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUnited Nations Development Programme. The SDGs in action. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.undp.org/sustainable-development-goals\u003c/span\u003e\u003cspan address=\"https://www.undp.org/sustainable-development-goals\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 26 July 2024.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-informatics-and-decision-making","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"midm","sideBox":"Learn more about [BMC Medical Informatics and Decision Making](http://bmcmedinformdecismak.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/midm/default.aspx","title":"BMC Medical Informatics and Decision Making","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Acceptance, ease-of-use, EMR system, healthcare workers, perceptions, technology acceptance model, usefulness","lastPublishedDoi":"10.21203/rs.3.rs-5150449/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5150449/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Electronic medical record (EMR) systems have significantly transformed the way healthcare data is created, managed and utilized. The advantages offered by the systems over paper-based records include improved legibility and accessibility to up-to-date patient information and provision of support for clinical decision-making. The system’s implementation in Lesotho aimed to enhance patient care, track patients, and generate routine reports for evidence-based programming. It is imperative to understand how healthcare workers (HCWs) perceive the system as frontline end-users; thus, the objective of the study was to explore HCWs’ perceptions of the system, focusing on their perceived usefulness and perceived ease of use and factors influencing acceptance and utilization in Mafeteng district.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: A descriptive cross-sectional study design was conducted; 145 healthcare workers from 17 health facilities were invited to participate in the study. A structured questionnaire based on the Technology Acceptance Model was administered for data collection. The analysis included descriptive statistics; the perceived usefulness and perceived ease of use using Stata/BE 18.0 and multiple regression analysis to identify the outcomes of the HCWs’ perceptions. Additional text by participants was extracted to explain quantitative results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e There was a 49% response rate (n= 71). The majority of respondents in the study were female (70.42%), and the most common profession was registered nurse midwife (45.07%). A large proportion of the participants reported having good computer skills. 87.32% HCWs found the EMR system useful, with 83.1% agreeing that it improves job performance and saves time. Additionally, 85.91% participants found the system easy to use, with 81.69% able to recover from errors and 85% able to remember how to perform tasks. However, 32.39% experienced unexpected system behaviour.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eOverall, HCWs showed positive attitudes towards the EMR system, appreciating its usefulness, ease of use and efficiency. Nevertheless, unexpected behavioural issues, such as network issues, unavailability of electricity, and computer skills gaps among the respondents were identified. Addressing these challenges is crucial for successful implementation and adoption of the system, ultimately leading to improved patient care.\u003c/p\u003e","manuscriptTitle":"Insights into healthcare workers' perceptions of electronic medical record system utilization: A cross-sectional study in Mafeteng District, Lesotho","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-24 16:26:33","doi":"10.21203/rs.3.rs-5150449/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-30T11:47:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-27T13:29:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-27T13:27:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Informatics and Decision Making","date":"2024-09-25T08:39:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-informatics-and-decision-making","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"midm","sideBox":"Learn more about [BMC Medical Informatics and Decision Making](http://bmcmedinformdecismak.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/midm/default.aspx","title":"BMC Medical Informatics and Decision Making","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e9311bee-a0cc-4f73-a232-0b6d0b408002","owner":[],"postedDate":"December 24th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-19T15:59:41+00:00","versionOfRecord":{"articleIdentity":"rs-5150449","link":"https://doi.org/10.1186/s12911-025-02858-3","journal":{"identity":"bmc-medical-informatics-and-decision-making","isVorOnly":false,"title":"BMC Medical Informatics and Decision Making"},"publishedOn":"2025-05-12 15:57:13","publishedOnDateReadable":"May 12th, 2025"},"versionCreatedAt":"2024-12-24 16:26:33","video":"","vorDoi":"10.1186/s12911-025-02858-3","vorDoiUrl":"https://doi.org/10.1186/s12911-025-02858-3","workflowStages":[]},"version":"v1","identity":"rs-5150449","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5150449","identity":"rs-5150449","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}