Insights from User Requirements on Electronic Health Record (EHR) System Transition: A Mixed-Method Retrospective Study

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This study aimed to explore strategies to reduce challenges, costs, and time associated with EHR system transitions by analyzing the user requirements that arise during the transition from one EHR system to another at Hospital B, a general hospital with 835 beds. Methods This study analyzed 5,117 unique user requirements collected through interviews with hospital staff. Requirements were categorized by task (clinical care, ancillary services, revenue cycle management, and enterprise resource planning) and reason (ease of use, patient care, hospital-specific processes, and national policies). The study also analyzed the customization rate, which is defined as the proportion of user requirements customized compared with those that were not. Statistical analyses were performed using the Chi-square test. Results There was a statistically significant difference in the customization rate according to task categorization and reasons for user requirements. When user requirements were categorized according to task categorization, the customization rates were lower for clinical care and ancillary services. Conversely, customization rates were higher for revenue cycle management and enterprise resource planning. When categorized by the reasons for user requirements, customization rates were lower for ease of use and patient care. In contrast, the customization rates were higher for hospital-specific processes and national policies. Conclusions It was found that requirements related to administrative tasks and specific causes tended to require higher levels of customization. In contrast, requirements related to patient care and general causes are more likely to reduce the degree of customization through sufficient explanation and consensus. Given the varying customization rates across task categories and the reasons for user requirements, adopting a tailored approach for each category, such as emphasizing thorough explanations for patient care and adapting to unique hospital processes for administrative tasks, can help reduce the costs and time required for EHR system transitions. Trial Registration: Not applicable. Electronic Health Records (EHR) Electronic Medical Records (EMR) Hospital Information System (HIS) EHR transition User Requirement Study Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background The widespread adoption of Electronic Health Record (EHR) systems has revolutionized the way healthcare providers manage patient information. EHRs capture and store comprehensive patient data, including medical history, diagnostic tests, diagnoses, prescriptions, and health management details [ 1 ]. While often used interchangeably, EHRs and Electronic Medical Records (EMRs) serve distinct purposes, with EHRs encompassing a broader range of patient information. In South Korea, the revision of the Medical Service Act enacted on March 31, 2003, enabled the creation and electronic storage of medical records within medical institutions in the form of Electronic Medical Records (EMR), leading to the widespread adoption of EHR systems. According to the "Health and Medical Informatization Survey and Status Report" conducted by the Ministry of Health and Welfare, the adoption rate of EMR systems from 2015 to 2020 consistently remained at 100% in tertiary hospitals, increased from 90.6–96.0% in general hospitals, and rose from 75.9–90.5% in other hospitals [ 2 – 4 ]. Additionally, the same survey reported that the adoption rate of EMR systems in primary care clinics increased from 61.4% in 2015 to 77.0% in 2017 [ 2 , 3 ]. Most hospitals and clinics in South Korea currently use EMR systems, which are considered essential for clinical care. Even for institutions already using an EHR system, transitioning to a new system may be necessary [ 5 ]. This need may arise because of issues such as the cost of maintaining the existing EHR system and problems such as the need for new updates, security concerns, or degraded user experience caused by an outdated system. However, transitioning to a new EHR system poses a significant challenge. These include issues of cost and time, the requirements of employees from various departments and the difficulty for users accustomed to the existing system to adapt to the new one [ 6 – 8 ]. Furthermore, the EHR systems currently used in South Korea lack standardization. Depending on the vendor, and even among different systems from the same vendor, functions, and user interfaces vary significantly, exacerbating the difficulties of EHR system transitions [ 9 ]. The subject of this study, Hospital B, is a general hospital with 835 beds that operates as a municipal general hospital under the management of Hospital S. The existing EHR system at Hospital B was based on Internet Explorer. However, with the discontinuation of Internet Explorer support, security and stability issues emerged. In addition, the aging of EHR systems has led to increased user inconvenience. In response, Hospital B decided to transition to a new EHR system using vendor E. Although studies on the adoption process of EHR systems in hospitals using paper charts exist [ 10 – 18 ], research on the transition from one EHR system to another remains highly limited [ 6 , 7 ]. Given that EHR systems are already widely implemented globally, the transition from existing EHR systems to more advanced systems is expected to increase [ 19 – 21 ]. This study is valuable because it explores the transition from one EHR system to another, an area with limited existing research that is expected to see growing demand. This study focuses on the user requirements arising during the transition from one EHR system to another within the non-standardized EHR market in South Korea. It aims to explore strategies to mitigate the challenges encountered during EHR system transition, as well as the associated time and cost burdens. To analyze user requirements, a literature review was conducted on the factors influencing EHR adoption and transition processes. Most studies have focused on analyzing facilitators and barriers to EHR adoption [ 10 – 13 , 16 , 22 – 24 ], while research specifically addressing user requirements has been limited [ 25 , 26 ]. Moreover, existing studies have often classified factors using arbitrary criteria or by directly adopting the expressions used in user requirement interviews. This mixed-methods retrospective study analyzed user requirements previously collected through interviews with hospital staff and classified user requirements and customization needs based on occupational roles and underlying reasons. Methods EHR Transition Process at Hospital B Before initiating the EHR system transition, Vendor E conducted an analysis of Hospital B’s existing program through interviews, which took the form of unstructured group meetings with Hospital B’s users, including physicians, nurses, and billing staff. These interviews have not been previously published. Subsequently, Vendor E demonstrated the features of their standard program to Hospital B’s users and compared the existing system with their standard program, which is implemented in six of the 47 tertiary hospitals in Korea, to identify similarities and differences in EHR system utilization. Next, Vendor E held unstructured group meetings with Hospital B’s users to gather feedback on the existing EHR system and user requirements for the new system. A team from Vendor E, comprising pharmacists, nurses, and clinical laboratory scientists, anonymized and organized the minutes of these meetings to develop a “gap list.” The interviews were conducted by Vendor E as part of their standard operational procedures for business purposes and were not designed for research purposes. These interviews took the form of unstructured group meetings that had not been previously published. Since these interviews were unstructured, no pre-prepared questionnaire or structured procedure was used. Consequently, the interview content was not documented, making it impossible to provide it as a supplementary file. The researchers were not involved in collecting or processing this information and only had access to the anonymized and organized “gap list.” Therefore, the original interview content itself was not used in the study. Through discussions with hospital administrators and staff, the team categorized the features necessitating customization, those already addressed by the standard program, and those requiring excessive resources for development. Customization efforts focused on features that would be the most beneficial for Hospital B. Analysis of User Requirements from the Gap List The “gap list” compiled by vendor E’s staff included details of all gaps, the departments where the gaps were identified, whether the gaps were merely descriptions of the existing EHR system or actual requirements, and whether the gaps were customized. The Gap List is provided as a supplementary file. The research team obtained the “gap list” from Vendor E and analyzed it by removing duplicates and excluding simple functional descriptions to extract user requirements, which were then explored further. This study was reviewed by the Seoul National University Bundang Hospital Institutional Review Board (SNUBH IRB), which determined that the study did not constitute human subjects research. As a result, the need for consent to participate and ethical approval was deemed unnecessary. This study analyzed 7,794 gaps, excluding 1,891 entries that were simple descriptions of the current system, and identified 5,903 entries that were classified as user requirements. Finally, after removing 786 duplicate entries, a total of 5,117 unique user requirements were analyzed. Classification Criteria for User Requirements In this study, user requirements were classified based on the occupational roles of those raising the requirements, which were further grouped by task categorization. Additionally, to explore the degree of customization required when implementing the same EHR system in other hospitals, the requirements were classified according to their underlying causes into general and hospital-specific factors. Task Categorization The user requirements were categorized into four task categories based on the role of users in their interactions with patients: Clinical care: User requirements raised by physicians and nurses from departments, such as internal medicine and surgery, which are directly involved in patient care. Ancillary services: User requirements raised by physicians and allied health professionals such as clinical pathologists, pharmacists, and radiologic technologists from departments such as diagnostic laboratory medicine and pathology that do not provide direct patient care. Revenue Cycle Management: User requirements raised by administrative staff from medical records and billing departments. Enterprise resource planning: User requirements raised by hospital administrative staff from departments such as human resources, accounting, logistics, and departmental administration. Reasons for User Requirements User requirements were classified into four categories based on the reasons for user requirements: Ease of use: User requirements related to user experience improvements, such as adjustments to screen layouts or automation features, which are commonly required in all hospitals. Patient care: User requirements related to processes universally necessary for patient treatment, including diagnosis, testing, procedures, and surgeries. Hospital-specific process: User requirements related to unique, non-standardized workflows specific to Hospital B. National policy: User requirements associated with national policies implemented by Hospital B as a municipal general hospital, such as care for populations with low socioeconomic status, healthcare networks, and community-based care for discharged patients. User requirements were analyzed based on task categorization and reasons for user requirements, along with the customization status. The customization Status is marked as either customized or not customized. Statistical Analysis of User Requirements The association between task categorization and customization status was analyzed using the chi-square test, and statistical significance was determined at a threshold of p < 0.05. After conducting the chi-square test on the entire dataset, pairwise chi-square tests were performed between each pair of task categories to examine whether the customization rates differed significantly among the groups. In addition, the association between the reasons for user requirements and the customization status was analyzed using the same method. Furthermore, the relationship between task categorization and reasons for user requirements was assessed for statistical significance using a chi-square test. All statistical analyses were performed using Python (version 3.11.8), employing libraries such as Pandas (version 1.5.3) for data manipulation, NumPy (version1.24.0) for numerical computations, and SciPy (version 1.9.3) for statistical testing. Results The distribution of customization status by task categorization and the reasons for user requirements is summarized in Table 1 . Table 1 Total user requirements analysis Ease of use Patient care Hospital-specific processes National policy Sum Clinical care 351 669 427 96 1543 Customized 101 272 183 44 600 Not customized 250 397 244 52 943 Ancillary services 544 1030 325 41 1940 Customized 290 360 198 21 869 Not customized 254 670 127 20 1071 Revenue cycle management 243 406 166 88 903 Customized 148 236 117 62 563 Not customized 95 170 49 26 340 Enterprise resource planning 63 5 655 8 731 Customized 43 3 495 4 545 Not customized 20 2 160 4 186 Sum 1201 2110 1573 233 5117 When user requirements were categorized by task, 30.2% were associated with clinical care, 37.9% with ancillary services, 17.6% with revenue cycle management, and 14.3% with enterprise resource planning (Fig. 1 ). [Figure 1 near here] When categorized by the reasons for user requirements, 23.5% were related to ease of use, 41.2% to patient care, 30.7% to hospital-specific processes, and 4.6% to national policies (Fig. 2 ). [Figure 2 near here] Analysis of Customization Status by Task Categorization A Chi-square test was conducted to examine the relationship between task categorization and customization status. The test results indicated a chi-square statistic of 328.41 with three degrees of freedom and a p-value < 0.001. When the P-value was less than 0.05, task categorization and customization status had a statistically significant relationship. In addition, pairwise chi-square tests were performed for each combination of the four task categorization groups. The results showed a p-value of < 0.05, confirming that the customization status differed significantly across all groups (Table 2 ). Table 2 Chi-square test result for customization status between pairs of groups of task categorization Group 1 Group 2 Chi-squared p-value Degrees of freedom Clinical care Ancillary services 12.06 < 0.001 1 Clinical care Revenue cycle management 124.79 < 0.001 1 Clinical care Enterprise resource planning 251.03 < 0.001 1 Ancillary services Revenue cycle management 75.25 < 0.001 1 Ancillary services Enterprise resource planning 187.57 < 0.001 1 Revenue cycle management Enterprise resource planning 27.02 < 0.001 1 The analysis revealed that customization rates varied according to task categorization: 38.9% for clinical care, 44.8% for ancillary services, 62.3% for revenue cycle management, and 74.6% for enterprise resource planning. Analysis of Customization Status by Reasons for User Requirements A Chi-square test was conducted to analyze the relationship between the reasons for user requirements and customization status. The test results showed a chi-square statistic of 177.11 with three degrees of freedom and a p-value < 0.001. Because the p-value was less than 0.05, it was concluded that there was a statistically significant relationship between the reasons for user requirements and customization status. Pairwise Chi-square tests were also conducted for each combination of the four groups. The results revealed statistically significant differences (p < 0.05) in customization status for all pairs, except for the comparison between hospital-specific processes and national policies (Table 3 ). Table 3 Chi-square test result for customization status between pairs of groups of reasons for user requirements Group 1 Group 2 Chi-squared p-value Degrees of freedom Ease of use Patient care 15.73194913 < 0.001 1 Ease of use Hospital specific processes 59.11143808 < 0.001 1 Ease of use National policy 4.399414135 0.036 1 Patient care Hospital specific processes 171.2203848 < 0.001 1 Patient care National policy 18.53787478 < 0.001 1 Hospital specific processes National policy 3.827972915 0.0504 1 The customization rates were 48.5% for ease of use, 41.3% for patient care, 63.1% for hospital-specific processes, and 56.2% for national policy. Analysis of Reasons for User Requirements by Task Categorization The distribution of customization status by user requirement across each task categorization is summarized in Figs. 3 , 4 , 5 , and 6 . [Figures 3 , 4 , 5 , and 6 near here] A Chi-square test was conducted to examine the relationship between task categorization and reasons for user requirements. The test yielded a chi-square statistic of 1557.69 with nine degrees of freedom and a p-value < 0.001. As the p-value is less than 0.05, it can be interpreted that there is a statistically significant relationship between task categorization and the reasons for user requirements. The distribution of the reasons for user requirements across task categorizations is summarized in Table 4 . Table 4 Proportion of reasons for user requirements by task categorization Clinical care Ancillary services Revenue cycle management Enterprise resource planning Ease of use 22.7% 28.0% 26.9% 8.6% Patient care 43.4% 53.1% 45.0% 0.7% Hospital-specific processes 27.7% 16.8% 18.4% 89.6% National policy 6.2% 2.1% 9.7% 1.1% Sum 100.0% 100.0% 100.0% 100.0% Discussion When the overall user requirements were categorized by task categorization, the clinical care and ancillary service groups had more user requirements than the revenue cycle management and enterprise resource planning groups. This indicates that most requirements originated from parts of the hospital directly involved in patient care and treatment, namely clinical care and ancillary services. Based on the reasons for user requirements categorization, over 40% of the requirements were related to patient care, making it the largest category, whereas requirements related to national policy accounted for only 4.6%. This suggests that although Hospital B participates in unique national policies as a municipal general hospital, the requirements arising from such policies are significantly fewer than those driven by other factors. Additionally, the nature of the requirements varied significantly according to task categorization. For instance, in enterprise resource planning, the requirements related to patient care and ease of use are minimal, whereas the majority are associated with hospital-specific processes. This highlights that the requirement characteristics differ substantially depending on the task categorization. When user requirements were categorized by task, customization rates were lower for clinical care and ancillary services, which are composed of occupations directly related to patient care. Conversely, customization rates were higher for revenue cycle management and enterprise resource planning, which consisted of occupations related to insurance and administrative tasks. When categorized by the reasons for user requirements, the customization rates were lower for general reasons, such as ease of use and patient care. In contrast, customization rates were higher for specific causes such as hospital-specific processes and national policies. The decision to customize a user requirement depended on whether the default functions of vendor E's EHR system aligned with Hospital B’s operational processes. If a corresponding function already existed within vendor E's EHR system, the users, hospital, and vendor E agreed to use that function, thereby excluding it from customization. Conversely, if the EHR system lacked a function that matched Hospital B's existing processes, the requirement was designated for customization. Given that vendor E's EHR system has already incorporated the requirements of many other general hospitals, the degree of customization required indirectly reflects the unique characteristics of Hospital B that differ from those of similarly sized general hospitals. When interpreting the differences in customization rates based on task categorization and reasons for user requirements, requirements related to administrative tasks and those arising from specific causes tended to require higher levels of customization. This is because the processes are relatively rigid and cannot be easily fulfilled using similar functions. By contrast, requirements related to patient care and those stemming from general causes are more likely to align with the systems of other general hospitals. Consequently, it is relatively easier to reduce the degree of customization through sufficient explanation and consensus. This can be attributed to the fact that patient care processes are more standardized than administrative tasks, resulting in fewer differences between hospitals. Despite the collaborative efforts of the hospital, users, and EHR vendors to customize only the necessary features, the total number of user requirements at Hospital B reached 5,117, with 2,577 requirements (50.4%) agreeing upon needing customization. This demonstrates that a substantial amount of customization is required when transitioning to EHR systems in general hospitals. Given the varying customization rates across task categorizations and the reasons for user requirements, it is essential to adopt a specialized approach for each category. For user requirements related to patient care, focusing on thorough explanations and reaching a consensus can help streamline the process. Conversely, regarding the requirements associated with administrative tasks, it is crucial to understand and adapt to a hospital’s unique processes. By tailoring approaches in this manner, it is expected that the costs and time associated with customization during the EHR transition process can be significantly reduced. Additionally, if recurring user requirements are raised by hospitals undergoing EHR system transitions, EHR system developers should go beyond customization and incorporate these requirements into the core functionality of the system. This is particularly important for enhancing the universal features directly related to clinical care or ancillary services. By addressing repetitive customization requests in these areas, it would be possible to reduce trial-and-error and transition costs in future EHR system transitions in other hospitals. User requirements related to administrative tasks may reflect the unique characteristics of a hospital, but they may also stem from inefficiencies in its operational processes. In this context, the process of transitioning to an EHR system holds significance as an opportunity to reassess a hospital's workflow and identify pain points for improvement. The analysis of user requirements can serve as a foundation for EHR vendors to propose a new business model that not only facilitates digital transformation but also offers insights for optimizing hospital processes. This highlights the dual value of EHR transitions: enhancing the digital infrastructure while driving process improvements in hospitals. The methodology adopted by EHR vendors during the system transition is crucial. In the past, vendor E utilized the waterfall approach to transition EHR systems. The waterfall method is a sequential software development process that progresses through the stages of requirements, design, implementation, verification or testing, deployment, and maintenance [ 27 ]. In this approach, the customization of user requirements is identified only during the final phase, deployment, and maintenance, after users begin to use the new EHR system. Moreover, there is no systematic process for excluding user requirements from customization, and customization is performed reactively as new requirements arise. This lack of structure leads to an inefficient and labor-intensive customization process. Subsequently, Vendor E adopted the fit-gap analysis method to improve the customization process. Fit-gap analysis involves identifying and managing the gaps between the current state and user requirements throughout a project [ 28 ]. Using this method, Vendor E systematically collected user requirements through demonstrations and meetings before implementing the EHR system. Customization decisions were made in collaboration with hospital administrators and staff, ensuring a structured approach to customization. Of the 5,117 total requirements, only 2,577 (50.4%) were customized, potentially reducing the time and costs associated with EHR system transition. The amount of user requirements and customization rate of Hospital B’s EHR transition highlights the critical importance of carefully managing user requirements in the EHR transition process, in which a substantial number of requirements arise at various stages. A deliberate and structured approach for handling these requirements is essential for a successful transition. Limitations and future research directions To date, no similar studies have examined the user requirements and customization rates in EHR transitions. Therefore, the conclusions of this study require further research in the same field. This study explored the case of transitioning from one on-premises EHR system to another at Hospital B, a municipal general hospital. Unlike other general hospitals, Hospital B plays a unique role in supporting populations with low socioeconomic status, owing to its municipal nature. User requirements in the national policy category primarily reflect policies aimed at assisting these populations, making them less relevant to other general hospitals. However, as user requirements related to the national policy accounted for only 4.6% of the total, the impact of Hospital B’s municipal status on its differences from other general hospitals appears to be minimal. Therefore, the findings of this study could apply to cases in which general hospitals aim to adopt EHR systems that are already in use at other general hospitals. However, Hospital B is a general hospital, so the conclusions of this study may not be fully applicable to scenarios involving the implementation of EHR systems in non-general hospitals or clinics. In addition, EHR systems can be classified, based on the location of the server, into on-premises EHR systems, where the server is located within the hospital, and cloud-based EHR systems, where the server is located externally. This study focuses on the requirements arising from the transition between two on-premises EHR systems. Therefore, the findings of this study are limited in their applicability to cases involving transitions from paper charts to EHR systems or from legacy EHR systems to cloud-based EHR systems. With the revision of Article 23 of the Medical Service Act on August 6, 2016, in South Korea, allowing patient information to be stored outside medical institutions, cloud-based EHR systems became feasible. Consequently, research is required to address the considerations and challenges associated with the transition from on-premises to cloud-based EHR systems. Given the lack of standardized EHR systems, the differences between hospitals remain a significant issue. Research aimed at analyzing the commonalities and differences among currently used EHR systems could help derive a standardized EHR system, ultimately reducing inter-hospital variability and improving system compatibility [ 9 ]. Conclusions For EHR vendors, it is essential to understand the nature of user requirements and adopt tailored approach for each category, such as emphasizing thorough explanations for patient care and adapting to unique hospital processes for administrative tasks, which can help to reduce the costs and time required for EHR system transitions. For healthcare organizations, hospital administrators can reassess workflow and identify points for improvement by analyzing user requirements from hospital staff. The conclusions of this study are expected to assist EHR system developers in enhancing the efficiency of the implementation of EHR systems. In addition, hospitals using EHR systems may gain valuable insights into the relationship between EHR systems and their operational processes, helping them better align technology with workflow optimization. Abbreviations EHR: Electronic Health Record EMR: Electronic Medical Records HIS: Hospital Information System Declarations Ethics approval and consent to participate : This study adhered to the Declaration of Helsinki and its later amendments. Seoul National University Bundang Hospital Institutional Review Board (SNUBH IRB) determined that the study does not constitute human subjects research. As a result, the need for consent to participate and ethical approval was deemed unnecessary. Consent for publication : Not applicable. Availability of data and materials : The data that support the findings of this study are available from ezCaretech Co., LTD. but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of ezCaretech Co., LTD. Competing interests : The authors declare that they have no competing interests. Funding : Not applicable. Authors' contributions : KHL contributed to the conception of the study, as well as the acquisition, analysis, and interpretation of data, and wrote the original draft. JSH was involved in the conception of the study, interpretation of the data, and revised the manuscript. CH contributed to the conception of the study, analysis, interpretation of the data, and wrote the original draft. HY participated in the conception of the study, created the figures and tables, and wrote the original draft. JK contributed to the conception of the study, interpretation of the data, and wrote the original draft. All authors read and approved the final manuscript. Acknowledgements : We would like to acknowledge Editage (https://www.editage.com/) for English language editing. References Ambinder EP. Electronic health records. J Oncol Pract. 2005;1:57–63. https://doi.org/10.1200/JOP.2005.1.2.57. Park SJ. Survey on the current status of healthcare informatization. National Assembly digital library of Korea; 2015, November. https://dl.nanet.go.kr/SearchDetailView.do?cn=MONO1201621577. Lee GI. Survey on the current status of healthcare informatization. National Assembly digital library of Korea; 2019, November. https://dl.nanet.go.kr/SearchDetailView.do?cn=MONO1201834084. 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Only one quarter of family physicians are very satisfied with their electronic health records platform. J Am Board Fam Med. 2024;37(1):796-8. https://doi.org/10.3122/jabfm.2024.240034R1. Bürkle T, Ammenwerth E, Prokosch HU, Dudeck J. Evaluation of clinical information systems. What can be evaluated and what cannot? J Eval Clin Pract. 2001;7(4):373-85. https://doi.org/10.1046/j.1365-2753.2001.00291.x. Kim YA, Shin SY, Jo EM, Park CH, Hwang MA, Kim KH, et al. Case study: Analysis of end-user requests on electronic medical record and computerized physician order entry system of Seoul National University Hospital in Korea. Stud Health Technol Inform. 2010;160:169–72. Yoo S, Kim S, Lee S, Lee KH, Baek RM, Hwang H. A study of user requests regarding the fully electronic health record system at Seoul National University Bundang Hospital: Challenges for future electronic health record systems. Int J Med Inform. 2013;82:387–97. https://doi.org/10.1016/j.ijmedinf.2012.08.004. Petersen K, Wohlin C, Baca D. The waterfall model in large-scale development. Presented at the 10th International Conference on Product-Focused Software Process Improvement; 2009. https://urn.kb.se/resolve?urn=urn:nbn:se:bth-8073 Spijkman T, Dalpiaz F, Brinkkemper S. Requirements elicitation via fit-gap analysis: A view through the grounded theory lens. In: International Conference on Advanced Information Systems Engineering . Cham: Springer International Publishing; 2021, June. p. 363-80. Additional Declarations No competing interests reported. Supplementary Files GapList.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5949536","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":442048937,"identity":"ebb1b389-c3e7-45b6-a1cf-33d779bbd10b","order_by":0,"name":"Kee-Hyuck Lee","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYDACCQaGA2AGewMDA2PDAVK08BwgQQuUkUCkFv7ZvQ8P/txz2K5/5vNnj3l33GHglz5+Ab8ld44bHOZ5djh5xu0cc2PeM88YJPtyCvBqMZBIYzjMcOBwMsPtHDZp3rbDDAZneBIIajn4A6hF/ubxZ8RrOcBz4LCdwQ0GM6gW9gP4/XID6DCeA+kJhmdyzCTnnjnMI9nDg1cHA/+MNOaPPw5Y28sdP/5M4u2Ow3L8POwP8OuBgsQGKANoBY8BUVrskdhE2jIKRsEoGAUjBgAA2ChMZwXuWugAAAAASUVORK5CYII=","orcid":"","institution":"Seoul National University Bundang Hospital","correspondingAuthor":true,"prefix":"","firstName":"Kee-Hyuck","middleName":"","lastName":"Lee","suffix":""},{"id":442048938,"identity":"47b6b3d5-a008-4a07-bffa-c17400f26fac","order_by":1,"name":"Jong Soo Han","email":"","orcid":"","institution":"Seoul National University Bundang Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jong","middleName":"Soo","lastName":"Han","suffix":""},{"id":442048939,"identity":"8632c82b-46a0-4dc3-8862-ba3b74bb1e36","order_by":2,"name":"Chiung Hwang","email":"","orcid":"","institution":"ezCaretech Co., LTD","correspondingAuthor":false,"prefix":"","firstName":"Chiung","middleName":"","lastName":"Hwang","suffix":""},{"id":442048940,"identity":"7de32726-c894-43e7-9b28-e58dbd5bf623","order_by":3,"name":"Hyeongjun Yun","email":"","orcid":"","institution":"ezCaretech Co., LTD","correspondingAuthor":false,"prefix":"","firstName":"Hyeongjun","middleName":"","lastName":"Yun","suffix":""},{"id":442048941,"identity":"8182112f-fbd0-4223-8d66-50f24006efe1","order_by":4,"name":"Jaesoon Kim","email":"","orcid":"","institution":"ezCaretech Co., LTD","correspondingAuthor":false,"prefix":"","firstName":"Jaesoon","middleName":"","lastName":"Kim","suffix":""}],"badges":[],"createdAt":"2025-02-03 08:38:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5949536/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5949536/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80633255,"identity":"a19c3438-cc4c-490f-9ddc-c1fe1c790b1b","added_by":"auto","created_at":"2025-04-15 11:56:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2238407,"visible":true,"origin":"","legend":"\u003cp\u003eCustomization status of user requirements by task categorization\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5949536/v1/f8619349e0e04b8c079e3c9e.png"},{"id":80633242,"identity":"f7d86433-6c81-44a7-b46f-a469b272cf5b","added_by":"auto","created_at":"2025-04-15 11:56:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2266730,"visible":true,"origin":"","legend":"\u003cp\u003eCustomization status of user requirements by reason for user requirements\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5949536/v1/ae5a635208176bd20085073f.png"},{"id":80631629,"identity":"2cec9dc2-ee9b-4403-b2f2-25ec23f42f16","added_by":"auto","created_at":"2025-04-15 11:48:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2150163,"visible":true,"origin":"","legend":"\u003cp\u003eCustomization status based on reasons for user requirements in clinical care\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-5949536/v1/af003e0e3285ba8ce5862218.png"},{"id":80633247,"identity":"ee7cf00a-cd5a-41cc-8476-2fe297087ef2","added_by":"auto","created_at":"2025-04-15 11:56:49","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2025858,"visible":true,"origin":"","legend":"\u003cp\u003eCustomization status based on reasons for user requirements in ancillary services\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-5949536/v1/e835ffeb9117bd80d5cc3d2c.png"},{"id":80633243,"identity":"0e733aed-0761-413b-a822-2afe3e2f2d71","added_by":"auto","created_at":"2025-04-15 11:56:49","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2179622,"visible":true,"origin":"","legend":"\u003cp\u003eCustomization status based on reasons for user requirements in revenue cycle management\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-5949536/v1/bd041a25f73b7156a9227e3e.png"},{"id":80631633,"identity":"b8e267bd-280e-46aa-be15-257d755553a4","added_by":"auto","created_at":"2025-04-15 11:48:49","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1773437,"visible":true,"origin":"","legend":"\u003cp\u003eCustomization status based on reasons for user requirements in enterprise resource planning\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-5949536/v1/166aef9463087447844fea0f.png"},{"id":87733447,"identity":"fdbd4445-79f9-4bed-b91e-b9208c86c1ff","added_by":"auto","created_at":"2025-07-28 12:02:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8338228,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5949536/v1/83c7bd6e-ac06-4be1-b4a1-30b4903a995f.pdf"},{"id":80633807,"identity":"913ab465-4695-4ba6-aca8-4519e924e75d","added_by":"auto","created_at":"2025-04-15 12:04:49","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":906707,"visible":true,"origin":"","legend":"","description":"","filename":"GapList.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5949536/v1/8e2c21b082548a9832821f69.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Insights from User Requirements on Electronic Health Record (EHR) System Transition: A Mixed-Method Retrospective Study","fulltext":[{"header":"Background","content":"\u003cp\u003eThe widespread adoption of Electronic Health Record (EHR) systems has revolutionized the way healthcare providers manage patient information. EHRs capture and store comprehensive patient data, including medical history, diagnostic tests, diagnoses, prescriptions, and health management details [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. While often used interchangeably, EHRs and Electronic Medical Records (EMRs) serve distinct purposes, with EHRs encompassing a broader range of patient information.\u003c/p\u003e \u003cp\u003eIn South Korea, the revision of the Medical Service Act enacted on March 31, 2003, enabled the creation and electronic storage of medical records within medical institutions in the form of Electronic Medical Records (EMR), leading to the widespread adoption of EHR systems. According to the \"Health and Medical Informatization Survey and Status Report\" conducted by the Ministry of Health and Welfare, the adoption rate of EMR systems from 2015 to 2020 consistently remained at 100% in tertiary hospitals, increased from 90.6\u0026ndash;96.0% in general hospitals, and rose from 75.9\u0026ndash;90.5% in other hospitals [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Additionally, the same survey reported that the adoption rate of EMR systems in primary care clinics increased from 61.4% in 2015 to 77.0% in 2017 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Most hospitals and clinics in South Korea currently use EMR systems, which are considered essential for clinical care.\u003c/p\u003e \u003cp\u003eEven for institutions already using an EHR system, transitioning to a new system may be necessary [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This need may arise because of issues such as the cost of maintaining the existing EHR system and problems such as the need for new updates, security concerns, or degraded user experience caused by an outdated system. However, transitioning to a new EHR system poses a significant challenge. These include issues of cost and time, the requirements of employees from various departments and the difficulty for users accustomed to the existing system to adapt to the new one [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Furthermore, the EHR systems currently used in South Korea lack standardization. Depending on the vendor, and even among different systems from the same vendor, functions, and user interfaces vary significantly, exacerbating the difficulties of EHR system transitions [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe subject of this study, Hospital B, is a general hospital with 835 beds that operates as a municipal general hospital under the management of Hospital S. The existing EHR system at Hospital B was based on Internet Explorer. However, with the discontinuation of Internet Explorer support, security and stability issues emerged. In addition, the aging of EHR systems has led to increased user inconvenience. In response, Hospital B decided to transition to a new EHR system using vendor E.\u003c/p\u003e \u003cp\u003eAlthough studies on the adoption process of EHR systems in hospitals using paper charts exist [\u003cspan additionalcitationids=\"CR11 CR12 CR13 CR14 CR15 CR16 CR17\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], research on the transition from one EHR system to another remains highly limited [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Given that EHR systems are already widely implemented globally, the transition from existing EHR systems to more advanced systems is expected to increase [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This study is valuable because it explores the transition from one EHR system to another, an area with limited existing research that is expected to see growing demand. This study focuses on the user requirements arising during the transition from one EHR system to another within the non-standardized EHR market in South Korea. It aims to explore strategies to mitigate the challenges encountered during EHR system transition, as well as the associated time and cost burdens.\u003c/p\u003e \u003cp\u003eTo analyze user requirements, a literature review was conducted on the factors influencing EHR adoption and transition processes. Most studies have focused on analyzing facilitators and barriers to EHR adoption [\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], while research specifically addressing user requirements has been limited [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Moreover, existing studies have often classified factors using arbitrary criteria or by directly adopting the expressions used in user requirement interviews. This mixed-methods retrospective study analyzed user requirements previously collected through interviews with hospital staff and classified user requirements and customization needs based on occupational roles and underlying reasons.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEHR Transition Process at Hospital B\u003c/h2\u003e \u003cp\u003eBefore initiating the EHR system transition, Vendor E conducted an analysis of Hospital B\u0026rsquo;s existing program through interviews, which took the form of unstructured group meetings with Hospital B\u0026rsquo;s users, including physicians, nurses, and billing staff. These interviews have not been previously published.\u003c/p\u003e \u003cp\u003eSubsequently, Vendor E demonstrated the features of their standard program to Hospital B\u0026rsquo;s users and compared the existing system with their standard program, which is implemented in six of the 47 tertiary hospitals in Korea, to identify similarities and differences in EHR system utilization. Next, Vendor E held unstructured group meetings with Hospital B\u0026rsquo;s users to gather feedback on the existing EHR system and user requirements for the new system. A team from Vendor E, comprising pharmacists, nurses, and clinical laboratory scientists, anonymized and organized the minutes of these meetings to develop a \u0026ldquo;gap list.\u0026rdquo;\u003c/p\u003e \u003cp\u003eThe interviews were conducted by Vendor E as part of their standard operational procedures for business purposes and were not designed for research purposes. These interviews took the form of unstructured group meetings that had not been previously published. Since these interviews were unstructured, no pre-prepared questionnaire or structured procedure was used. Consequently, the interview content was not documented, making it impossible to provide it as a supplementary file. The researchers were not involved in collecting or processing this information and only had access to the anonymized and organized \u0026ldquo;gap list.\u0026rdquo; Therefore, the original interview content itself was not used in the study.\u003c/p\u003e \u003cp\u003eThrough discussions with hospital administrators and staff, the team categorized the features necessitating customization, those already addressed by the standard program, and those requiring excessive resources for development. Customization efforts focused on features that would be the most beneficial for Hospital B.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnalysis of User Requirements from the Gap List\u003c/h3\u003e\n\u003cp\u003eThe \u0026ldquo;gap list\u0026rdquo; compiled by vendor E\u0026rsquo;s staff included details of all gaps, the departments where the gaps were identified, whether the gaps were merely descriptions of the existing EHR system or actual requirements, and whether the gaps were customized. The Gap List is provided as a supplementary file.\u003c/p\u003e \u003cp\u003eThe research team obtained the \u0026ldquo;gap list\u0026rdquo; from Vendor E and analyzed it by removing duplicates and excluding simple functional descriptions to extract user requirements, which were then explored further. This study was reviewed by the Seoul National University Bundang Hospital Institutional Review Board (SNUBH IRB), which determined that the study did not constitute human subjects research. As a result, the need for consent to participate and ethical approval was deemed unnecessary. This study analyzed 7,794 gaps, excluding 1,891 entries that were simple descriptions of the current system, and identified 5,903 entries that were classified as user requirements. Finally, after removing 786 duplicate entries, a total of 5,117 unique user requirements were analyzed.\u003c/p\u003e\n\u003ch3\u003eClassification Criteria for User Requirements\u003c/h3\u003e\n\u003cp\u003eIn this study, user requirements were classified based on the occupational roles of those raising the requirements, which were further grouped by task categorization. Additionally, to explore the degree of customization required when implementing the same EHR system in other hospitals, the requirements were classified according to their underlying causes into general and hospital-specific factors.\u003c/p\u003e\n\u003ch3\u003eTask Categorization\u003c/h3\u003e\n\u003cp\u003eThe user requirements were categorized into four task categories based on the role of users in their interactions with patients:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eClinical care: User requirements raised by physicians and nurses from departments, such as internal medicine and surgery, which are directly involved in patient care.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAncillary services: User requirements raised by physicians and allied health professionals such as clinical pathologists, pharmacists, and radiologic technologists from departments such as diagnostic laboratory medicine and pathology that do not provide direct patient care.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRevenue Cycle Management: User requirements raised by administrative staff from medical records and billing departments.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eEnterprise resource planning: User requirements raised by hospital administrative staff from departments such as human resources, accounting, logistics, and departmental administration.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e\n\u003ch3\u003eReasons for User Requirements\u003c/h3\u003e\n\u003cp\u003eUser requirements were classified into four categories based on the reasons for user requirements:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eEase of use: User requirements related to user experience improvements, such as adjustments to screen layouts or automation features, which are commonly required in all hospitals.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePatient care: User requirements related to processes universally necessary for patient treatment, including diagnosis, testing, procedures, and surgeries.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHospital-specific process: User requirements related to unique, non-standardized workflows specific to Hospital B.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eNational policy: User requirements associated with national policies implemented by Hospital B as a municipal general hospital, such as care for populations with low socioeconomic status, healthcare networks, and community-based care for discharged patients.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eUser requirements were analyzed based on task categorization and reasons for user requirements, along with the customization status. The customization Status is marked as either customized or not customized.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis of User Requirements\u003c/h2\u003e \u003cp\u003eThe association between task categorization and customization status was analyzed using the chi-square test, and statistical significance was determined at a threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. After conducting the chi-square test on the entire dataset, pairwise chi-square tests were performed between each pair of task categories to examine whether the customization rates differed significantly among the groups.\u003c/p\u003e \u003cp\u003eIn addition, the association between the reasons for user requirements and the customization status was analyzed using the same method. Furthermore, the relationship between task categorization and reasons for user requirements was assessed for statistical significance using a chi-square test. All statistical analyses were performed using Python (version 3.11.8), employing libraries such as Pandas (version 1.5.3) for data manipulation, NumPy (version1.24.0) for numerical computations, and SciPy (version 1.9.3) for statistical testing.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe distribution of customization status by task categorization and the reasons for user requirements is summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTotal user requirements analysis\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\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEase of use\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient care\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHospital-specific processes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNational policy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSum\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1543\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCustomized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e600\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot customized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e943\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAncillary services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1940\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCustomized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e869\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot customized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1071\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRevenue cycle management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e903\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCustomized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e563\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot customized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e340\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnterprise resource planning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e731\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCustomized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e545\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot customized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5117\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\u003eWhen user requirements were categorized by task, 30.2% were associated with clinical care, 37.9% with ancillary services, 17.6% with revenue cycle management, and 14.3% with enterprise resource planning (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e[Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e near here]\u003c/p\u003e \u003cp\u003eWhen categorized by the reasons for user requirements, 23.5% were related to ease of use, 41.2% to patient care, 30.7% to hospital-specific processes, and 4.6% to national policies (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e[Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e near here]\u003c/p\u003e\n\u003ch3\u003eAnalysis of Customization Status by Task Categorization\u003c/h3\u003e\n\u003cp\u003eA Chi-square test was conducted to examine the relationship between task categorization and customization status. The test results indicated a chi-square statistic of 328.41 with three degrees of freedom and a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001. When the P-value was less than 0.05, task categorization and customization status had a statistically significant relationship.\u003c/p\u003e \u003cp\u003eIn addition, pairwise chi-square tests were performed for each combination of the four task categorization groups. The results showed a p-value of \u0026lt;\u0026thinsp;0.05, confirming that the customization status differed significantly across all groups (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\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\u003eChi-square test result for customization status between pairs of groups of task categorization\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroup 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChi-squared\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDegrees of freedom\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAncillary services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRevenue cycle management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e124.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnterprise resource planning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e251.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAncillary services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRevenue cycle management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAncillary services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnterprise resource planning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e187.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRevenue cycle management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnterprise resource planning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\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 analysis revealed that customization rates varied according to task categorization: 38.9% for clinical care, 44.8% for ancillary services, 62.3% for revenue cycle management, and 74.6% for enterprise resource planning.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of Customization Status by Reasons for User Requirements\u003c/h2\u003e \u003cp\u003eA Chi-square test was conducted to analyze the relationship between the reasons for user requirements and customization status. The test results showed a chi-square statistic of 177.11 with three degrees of freedom and a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001. Because the p-value was less than 0.05, it was concluded that there was a statistically significant relationship between the reasons for user requirements and customization status.\u003c/p\u003e \u003cp\u003ePairwise Chi-square tests were also conducted for each combination of the four groups. The results revealed statistically significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in customization status for all pairs, except for the comparison between hospital-specific processes and national policies (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\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\u003eChi-square test result for customization status between pairs of groups of reasons for user requirements\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroup 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChi-squared\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDegrees of freedom\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEase of use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePatient care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.73194913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEase of use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital specific processes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59.11143808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEase of use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNational policy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.399414135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital specific processes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e171.2203848\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNational policy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.53787478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital specific processes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNational policy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.827972915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\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 customization rates were 48.5% for ease of use, 41.3% for patient care, 63.1% for hospital-specific processes, and 56.2% for national policy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of Reasons for User Requirements by Task Categorization\u003c/h2\u003e \u003cp\u003eThe distribution of customization status by user requirement across each task categorization is summarized in Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e[Figures \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e near here]\u003c/p\u003e \u003cp\u003eA Chi-square test was conducted to examine the relationship between task categorization and reasons for user requirements. The test yielded a chi-square statistic of 1557.69 with nine degrees of freedom and a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001. As the p-value is less than 0.05, it can be interpreted that there is a statistically significant relationship between task categorization and the reasons for user requirements.\u003c/p\u003e \u003cp\u003eThe distribution of the reasons for user requirements across task categorizations is summarized in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\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\u003eProportion of reasons for user requirements by task categorization\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical care\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAncillary services\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRevenue cycle management\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEnterprise resource planning\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEase of use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital-specific processes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e89.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNational policy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100.0%\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"},{"header":"Discussion","content":"\u003cp\u003eWhen the overall user requirements were categorized by task categorization, the clinical care and ancillary service groups had more user requirements than the revenue cycle management and enterprise resource planning groups. This indicates that most requirements originated from parts of the hospital directly involved in patient care and treatment, namely clinical care and ancillary services.\u003c/p\u003e \u003cp\u003eBased on the reasons for user requirements categorization, over 40% of the requirements were related to patient care, making it the largest category, whereas requirements related to national policy accounted for only 4.6%. This suggests that although Hospital B participates in unique national policies as a municipal general hospital, the requirements arising from such policies are significantly fewer than those driven by other factors.\u003c/p\u003e \u003cp\u003eAdditionally, the nature of the requirements varied significantly according to task categorization. For instance, in enterprise resource planning, the requirements related to patient care and ease of use are minimal, whereas the majority are associated with hospital-specific processes. This highlights that the requirement characteristics differ substantially depending on the task categorization.\u003c/p\u003e \u003cp\u003eWhen user requirements were categorized by task, customization rates were lower for clinical care and ancillary services, which are composed of occupations directly related to patient care. Conversely, customization rates were higher for revenue cycle management and enterprise resource planning, which consisted of occupations related to insurance and administrative tasks.\u003c/p\u003e \u003cp\u003eWhen categorized by the reasons for user requirements, the customization rates were lower for general reasons, such as ease of use and patient care. In contrast, customization rates were higher for specific causes such as hospital-specific processes and national policies.\u003c/p\u003e \u003cp\u003eThe decision to customize a user requirement depended on whether the default functions of vendor E's EHR system aligned with Hospital B\u0026rsquo;s operational processes. If a corresponding function already existed within vendor E's EHR system, the users, hospital, and vendor E agreed to use that function, thereby excluding it from customization. Conversely, if the EHR system lacked a function that matched Hospital B's existing processes, the requirement was designated for customization.\u003c/p\u003e \u003cp\u003eGiven that vendor E's EHR system has already incorporated the requirements of many other general hospitals, the degree of customization required indirectly reflects the unique characteristics of Hospital B that differ from those of similarly sized general hospitals. When interpreting the differences in customization rates based on task categorization and reasons for user requirements, requirements related to administrative tasks and those arising from specific causes tended to require higher levels of customization. This is because the processes are relatively rigid and cannot be easily fulfilled using similar functions.\u003c/p\u003e \u003cp\u003eBy contrast, requirements related to patient care and those stemming from general causes are more likely to align with the systems of other general hospitals. Consequently, it is relatively easier to reduce the degree of customization through sufficient explanation and consensus. This can be attributed to the fact that patient care processes are more standardized than administrative tasks, resulting in fewer differences between hospitals.\u003c/p\u003e \u003cp\u003eDespite the collaborative efforts of the hospital, users, and EHR vendors to customize only the necessary features, the total number of user requirements at Hospital B reached 5,117, with 2,577 requirements (50.4%) agreeing upon needing customization. This demonstrates that a substantial amount of customization is required when transitioning to EHR systems in general hospitals.\u003c/p\u003e \u003cp\u003eGiven the varying customization rates across task categorizations and the reasons for user requirements, it is essential to adopt a specialized approach for each category. For user requirements related to patient care, focusing on thorough explanations and reaching a consensus can help streamline the process. Conversely, regarding the requirements associated with administrative tasks, it is crucial to understand and adapt to a hospital\u0026rsquo;s unique processes. By tailoring approaches in this manner, it is expected that the costs and time associated with customization during the EHR transition process can be significantly reduced.\u003c/p\u003e \u003cp\u003eAdditionally, if recurring user requirements are raised by hospitals undergoing EHR system transitions, EHR system developers should go beyond customization and incorporate these requirements into the core functionality of the system. This is particularly important for enhancing the universal features directly related to clinical care or ancillary services. By addressing repetitive customization requests in these areas, it would be possible to reduce trial-and-error and transition costs in future EHR system transitions in other hospitals.\u003c/p\u003e \u003cp\u003eUser requirements related to administrative tasks may reflect the unique characteristics of a hospital, but they may also stem from inefficiencies in its operational processes. In this context, the process of transitioning to an EHR system holds significance as an opportunity to reassess a hospital's workflow and identify pain points for improvement.\u003c/p\u003e \u003cp\u003eThe analysis of user requirements can serve as a foundation for EHR vendors to propose a new business model that not only facilitates digital transformation but also offers insights for optimizing hospital processes. This highlights the dual value of EHR transitions: enhancing the digital infrastructure while driving process improvements in hospitals.\u003c/p\u003e \u003cp\u003eThe methodology adopted by EHR vendors during the system transition is crucial. In the past, vendor E utilized the waterfall approach to transition EHR systems. The waterfall method is a sequential software development process that progresses through the stages of requirements, design, implementation, verification or testing, deployment, and maintenance [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this approach, the customization of user requirements is identified only during the final phase, deployment, and maintenance, after users begin to use the new EHR system. Moreover, there is no systematic process for excluding user requirements from customization, and customization is performed reactively as new requirements arise. This lack of structure leads to an inefficient and labor-intensive customization process.\u003c/p\u003e \u003cp\u003eSubsequently, Vendor E adopted the fit-gap analysis method to improve the customization process. Fit-gap analysis involves identifying and managing the gaps between the current state and user requirements throughout a project [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUsing this method, Vendor E systematically collected user requirements through demonstrations and meetings before implementing the EHR system. Customization decisions were made in collaboration with hospital administrators and staff, ensuring a structured approach to customization. Of the 5,117 total requirements, only 2,577 (50.4%) were customized, potentially reducing the time and costs associated with EHR system transition.\u003c/p\u003e \u003cp\u003eThe amount of user requirements and customization rate of Hospital B\u0026rsquo;s EHR transition highlights the critical importance of carefully managing user requirements in the EHR transition process, in which a substantial number of requirements arise at various stages. A deliberate and structured approach for handling these requirements is essential for a successful transition.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and future research directions\u003c/h2\u003e \u003cp\u003eTo date, no similar studies have examined the user requirements and customization rates in EHR transitions. Therefore, the conclusions of this study require further research in the same field. This study explored the case of transitioning from one on-premises EHR system to another at Hospital B, a municipal general hospital. Unlike other general hospitals, Hospital B plays a unique role in supporting populations with low socioeconomic status, owing to its municipal nature. User requirements in the national policy category primarily reflect policies aimed at assisting these populations, making them less relevant to other general hospitals. However, as user requirements related to the national policy accounted for only 4.6% of the total, the impact of Hospital B\u0026rsquo;s municipal status on its differences from other general hospitals appears to be minimal. Therefore, the findings of this study could apply to cases in which general hospitals aim to adopt EHR systems that are already in use at other general hospitals.\u003c/p\u003e \u003cp\u003eHowever, Hospital B is a general hospital, so the conclusions of this study may not be fully applicable to scenarios involving the implementation of EHR systems in non-general hospitals or clinics. In addition, EHR systems can be classified, based on the location of the server, into on-premises EHR systems, where the server is located within the hospital, and cloud-based EHR systems, where the server is located externally. This study focuses on the requirements arising from the transition between two on-premises EHR systems. Therefore, the findings of this study are limited in their applicability to cases involving transitions from paper charts to EHR systems or from legacy EHR systems to cloud-based EHR systems.\u003c/p\u003e \u003cp\u003eWith the revision of Article 23 of the Medical Service Act on August 6, 2016, in South Korea, allowing patient information to be stored outside medical institutions, cloud-based EHR systems became feasible. Consequently, research is required to address the considerations and challenges associated with the transition from on-premises to cloud-based EHR systems.\u003c/p\u003e \u003cp\u003eGiven the lack of standardized EHR systems, the differences between hospitals remain a significant issue. Research aimed at analyzing the commonalities and differences among currently used EHR systems could help derive a standardized EHR system, ultimately reducing inter-hospital variability and improving system compatibility [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eFor EHR vendors, it is essential to understand the nature of user requirements and adopt tailored approach for each category, such as emphasizing thorough explanations for patient care and adapting to unique hospital processes for administrative tasks, which can help to reduce the costs and time required for EHR system transitions.\u003c/p\u003e \u003cp\u003eFor healthcare organizations, hospital administrators can reassess workflow and identify points for improvement by analyzing user requirements from hospital staff.\u003c/p\u003e \u003cp\u003eThe conclusions of this study are expected to assist EHR system developers in enhancing the efficiency of the implementation of EHR systems. In addition, hospitals using EHR systems may gain valuable insights into the relationship between EHR systems and their operational processes, helping them better align technology with workflow optimization.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eEHR: Electronic Health Record\u003c/p\u003e\n\u003cp\u003eEMR: Electronic Medical Records\u003c/p\u003e\n\u003cp\u003eHIS: Hospital Information System\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e: This study adhered to the Declaration of Helsinki and its later amendments. Seoul National University Bundang Hospital Institutional Review Board (SNUBH IRB) determined that the study does not constitute human subjects research. As a result, the need for consent to participate and ethical approval was deemed unnecessary.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Not applicable.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e: The data that support the findings of this study are available from ezCaretech Co., LTD. but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of ezCaretech Co., LTD.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e: The authors declare that they have no competing interests.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: Not applicable.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e: KHL contributed to the conception of the study, as well as the acquisition, analysis, and interpretation of data, and wrote the original draft. JSH was involved in the conception of the study, interpretation of the data, and revised the manuscript. CH contributed to the conception of the study, analysis, interpretation of the data, and wrote the original draft. HY participated in the conception of the study, created the figures and tables, and wrote the original draft. JK contributed to the conception of the study, interpretation of the data, and wrote the original draft. All authors read and approved the final manuscript.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e: We would like to acknowledge Editage (https://www.editage.com/) for English language editing.\u003c/p\u003e"},{"header":"References","content":"\u003col start=\"1\" type=\"1\"\u003e\n\u003cli\u003eAmbinder EP. Electronic health records. J Oncol Pract. 2005;1:57\u0026ndash;63. https://doi.org/10.1200/JOP.2005.1.2.57.\u003c/li\u003e\n\u003cli\u003ePark SJ. Survey on the current status of healthcare informatization. National Assembly digital library of Korea; 2015, November. https://dl.nanet.go.kr/SearchDetailView.do?cn=MONO1201621577.\u003c/li\u003e\n\u003cli\u003eLee GI. Survey on the current status of healthcare informatization. National Assembly digital library of Korea; 2019, November. https://dl.nanet.go.kr/SearchDetailView.do?cn=MONO1201834084.\u003c/li\u003e\n\u003cli\u003eLee JH. Survey on the current status of healthcare informatization. Korea Health Information Service; 2021, April. https://www.k-his.or.kr/board.es?mid=a10306040000\u0026amp;bid=0005\u0026amp;act=view\u0026amp;list_no=283\u0026amp;tag=\u0026amp;nPage=1.\u003c/li\u003e\n\u003cli\u003eZandieh SO, Abramson EL, Pfoh ER, Yoon-Flannery K, Edwards A, Kaushal R. Transitioning between ambulatory EHRs: A study of practitioners\u0026apos; perspectives. J Am Med Inform Assoc. 2011;19(2):401-6. https://doi.org/10.1136/amiajnl-2011-000333.\u003c/li\u003e\n\u003cli\u003eBates DW, Ratwani R. Electronic health record transitions-how to make them work. J Gen Intern Med. 2023;38 Suppl 4:946\u0026ndash;8. https://doi.org/10.1007/s11606-023-08329-7.\u003c/li\u003e\n\u003cli\u003ePenrod LE. Electronic health record transition considerations. PM R. 2017;9:S13-8.\u003c/li\u003e\n\u003cli\u003eAhlness EA, Orlander J, Brunner J, Cutrona SL, Kim B, Molloy-Paolillo BK, \u003cem\u003eet al.\u003c/em\u003e \u0026ldquo;Everything\u0026rsquo;s so Role-Specific\u0026rdquo;: VA employee perspectives\u0026rsquo; on electronic health record (EHR) transition implications for roles and responsibilities. J Gen Intern Med. 2023;38 Suppl 4:991-8.\u003c/li\u003e\n\u003cli\u003ePark YT, Han D. Current status of electronic medical record systems in hospitals and clinics in Korea. Healthc Inform Res. 2017;23:189-98.\u003c/li\u003e\n\u003cli\u003eYehualashet DE, Seboka BT, Tesfa GA, Demeke AD, Amede ES. Barriers to the adoption of electronic medical record system in Ethiopia: A systematic review. J Multidiscip Healthc. 2021;14:2597\u0026ndash;603. https://doi.org/10.2147/JMDH.S327539.\u003c/li\u003e\n\u003cli\u003eKruse CS, Kristof C, Jones B, Mitchell E, Martinez A. Barriers to electronic health record adoption: A systematic literature review. J Med Syst. 2016;40(12):252. https://doi.org/10.1007/s10916-016-0628-9.\u003c/li\u003e\n\u003cli\u003eKruse CS, Kothman K, Anerobi K, Abanaka L. Adoption factors of the electronic health record: A systematic review. JMIR Med Inform. 2016;4(2):e19. https://doi.org/10.2196/medinform.5525.\u003c/li\u003e\n\u003cli\u003eHandayani PW, Hidayanto AN, Pinem AA, Hapsari IC, Sandhyaduhita PI, Budi I. Acceptance model of a Hospital Information System. Int J Med Inform. 2017;99:11-28. https://doi.org/10.1016/j.ijmedinf.2016.12.004.\u003c/li\u003e\n\u003cli\u003eSkalkidis Y. Implementation of a hospital information system in a Greek university hospital. Stud Health Technol Inform. 1998;56:62\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eWang BB, Wan TTH, Burke DE, Bazzoli GJ, Lin BYJ. Factors influencing health information system adoption in American hospitals. T. T. Health Care Manage Rev. 2005;30(2):44-51.\u003c/li\u003e\n\u003cli\u003eAhmadi H, Nilashi M, Shahmoradi L, Ibrahim O, Sadoughi F, Alizadeh M, \u003cem\u003eet al.\u003c/em\u003e The moderating effect of hospital size on inter- and intra-organizational factors of Hospital Information System adoption. Technol Forecasting Soc Change. 2018;134:124-49.\u003c/li\u003e\n\u003cli\u003eKazley AS, Ozcan YA. Organizational and environmental determinants of hospital EMR adoption: A national study. J Med Syst. 2007;31(5):375-84.\u003c/li\u003e\n\u003cli\u003eHikmet N, Bhattacherjee A, Menachemi N, Kayhan VO, Brooks RG. The role of organizational factors in the adoption of healthcare information technology in Florida hospitals. Health Care Manag Sci. 2008;11(1):1-9.\u003c/li\u003e\n\u003cli\u003eHenry J, Pylypchuk Y, Searcy T, Patel V. Adoption of electronic health record systems among US non-federal acute care hospitals: 2008\u0026ndash;2015. ONC Data Brief. 2016;(35):1-8.\u003c/li\u003e\n\u003cli\u003eLiang J, Li Y, Zhang Z, Shen D, Xu J, Zheng X, \u003cem\u003eet al.\u003c/em\u003e Adoption of electronic health records (EHRs) in China during the past 10 years: Consecutive survey data analysis and comparison of Sino-American challenges and experiences. J Med Internet Res. 2021;23:e24813.\u003c/li\u003e\n\u003cli\u003eKose I, Rayner J, Birinci S, Ulgu MM, Yilmaz I, Guner S, \u003cem\u003eet al.\u003c/em\u003e Esra Zehir Berrin Gundogdu Mert Ozcan Ceyhan Vardar Behcet Altinli Jale Sungur Hasancebi. BMC Health Serv Res. 2020. Adoption rates of electronic health records in Turkish Hospitals and the relation with hospital sizes; BMC Health Serv Res. 2020;20(1):1-16.\u003c/li\u003e\n\u003cli\u003eYoon D, Chang BC, Kang SW, Bae H, Park RW. Adoption of electronic health records in Korean tertiary teaching and general hospitals. Int J Med Inform. 2012;81(3):196-203. https://doi.org/10.1016/j.ijmedinf.2011.12.002 .\u003c/li\u003e\n\u003cli\u003eHendrix N, Phillips RL, Bazemore AW. Only one quarter of family physicians are very satisfied with their electronic health records platform. J Am Board Fam Med. 2024;37(1):796-8. https://doi.org/10.3122/jabfm.2024.240034R1.\u003c/li\u003e\n\u003cli\u003eB\u0026uuml;rkle T, Ammenwerth E, Prokosch HU, Dudeck J. Evaluation of clinical information systems. What can be evaluated and what cannot? J Eval Clin Pract. 2001;7(4):373-85. https://doi.org/10.1046/j.1365-2753.2001.00291.x. \u003c/li\u003e\n\u003cli\u003eKim YA, Shin SY, Jo EM, Park CH, Hwang MA, Kim KH, \u003cem\u003eet al.\u003c/em\u003e Case study: Analysis of end-user requests on electronic medical record and computerized physician order entry system of Seoul National University Hospital in Korea. Stud Health Technol Inform. 2010;160:169\u0026ndash;72.\u003c/li\u003e\n\u003cli\u003eYoo S, Kim S, Lee S, Lee KH, Baek RM, Hwang H. A study of user requests regarding the fully electronic health record system at Seoul National University Bundang Hospital: Challenges for future electronic health record systems. Int J Med Inform. 2013;82:387\u0026ndash;97. https://doi.org/10.1016/j.ijmedinf.2012.08.004.\u003c/li\u003e\n\u003cli\u003ePetersen K, Wohlin C, Baca D. The waterfall model in large-scale development. Presented at the 10th International Conference on Product-Focused Software Process Improvement; 2009. https://urn.kb.se/resolve?urn=urn:nbn:se:bth-8073\u003c/li\u003e\n\u003cli\u003eSpijkman T, Dalpiaz F, Brinkkemper S. Requirements elicitation via fit-gap analysis: A view through the grounded theory lens. In: \u003cem\u003eInternational Conference on Advanced Information Systems Engineering\u003c/em\u003e. Cham: Springer International Publishing; 2021, June. p. 363-80.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Electronic Health Records (EHR), Electronic Medical Records (EMR), Hospital Information System (HIS), EHR transition, User Requirement Study","lastPublishedDoi":"10.21203/rs.3.rs-5949536/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5949536/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eSince the 2003 revision of the Medical Service Act, the adoption of Electronic Health Record (EHR) systems has steadily increased in South Korea, with most hospitals and clinics implementing these systems by 2020. This study aimed to explore strategies to reduce challenges, costs, and time associated with EHR system transitions by analyzing the user requirements that arise during the transition from one EHR system to another at Hospital B, a general hospital with 835 beds.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study analyzed 5,117 unique user requirements collected through interviews with hospital staff. Requirements were categorized by task (clinical care, ancillary services, revenue cycle management, and enterprise resource planning) and reason (ease of use, patient care, hospital-specific processes, and national policies). The study also analyzed the customization rate, which is defined as the proportion of user requirements customized compared with those that were not. Statistical analyses were performed using the Chi-square test.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThere was a statistically significant difference in the customization rate according to task categorization and reasons for user requirements. When user requirements were categorized according to task categorization, the customization rates were lower for clinical care and ancillary services. Conversely, customization rates were higher for revenue cycle management and enterprise resource planning. When categorized by the reasons for user requirements, customization rates were lower for ease of use and patient care. In contrast, the customization rates were higher for hospital-specific processes and national policies.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIt was found that requirements related to administrative tasks and specific causes tended to require higher levels of customization. In contrast, requirements related to patient care and general causes are more likely to reduce the degree of customization through sufficient explanation and consensus. Given the varying customization rates across task categories and the reasons for user requirements, adopting a tailored approach for each category, such as emphasizing thorough explanations for patient care and adapting to unique hospital processes for administrative tasks, can help reduce the costs and time required for EHR system transitions.\u003c/p\u003e\u003ch2\u003eTrial Registration:\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e","manuscriptTitle":"Insights from User Requirements on Electronic Health Record (EHR) System Transition: A Mixed-Method Retrospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-15 11:48:44","doi":"10.21203/rs.3.rs-5949536/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"04ff14dc-22f5-4dd5-9884-f2d19ef55968","owner":[],"postedDate":"April 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-28T11:53:52+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-15 11:48:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5949536","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5949536","identity":"rs-5949536","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}