Electronic Medical Records (EMRs) have become a central component of contemporary health-system digitalization because their effective implementation can improve information continuity, clinical coordination, documentation quality, and patient safety. Healthcare organizations increasingly depend on digital records to support communication across professional groups and to ensure that clinical information is available at the point of care (Elkefi et al., 2023). Evidence from different healthcare settings nevertheless shows that the availability of technology alone does not guarantee effective use, as implementation depends on the readiness and capability of the workforce expected to interact with the system. Digital competence has therefore become an important determinant of whether healthcare professionals can use EMRs accurately, efficiently, and consistently in routine practice. Recent evidence underscores that digital readiness and capability remain critical prerequisites for successful digital health implementation, particularly when healthcare workers must adapt rapidly to evolving technological environments (Borges do Nascimento et al., 2023; Alotaibi et al., 2025). An umbrella review of systematic reviews similarly found that digital technologies influence healthcare workers’ competencies, clinical practice, performance, and workplace processes, reinforcing the importance of workforce capability during digital transformation.

The Indonesian healthcare context makes this issue particularly important because hospitals are increasingly required to implement EMRs under regulatory pressure rather than through a gradual and entirely voluntary process of technological adoption. Hospitals consequently face the simultaneous challenges of meeting institutional requirements, maintaining clinical services, developing adequate digital infrastructure, and preparing healthcare workers with different professional backgrounds and levels of technological experience. Recent national evidence demonstrates substantial heterogeneity in EMR readiness and digital maturity across Indonesian hospitals, including differences in infrastructure, human capital, interoperability, governance, and competence (Amiruddin et al., 2026). Rapid implementation can create an implicit assumption that staff members already possess the competencies required to operate newly introduced systems. Such an assumption may obscure differences in age, professional role, work experience, exposure to computers, and organizational support that influence actual system use, with Indonesian evidence demonstrating significant variations in informatics competence according to age, education, professional position, and work experience (Hariyati et al., 2024). A hospital may therefore appear institutionally ready for EMR implementation while important gaps remain at the individual-user level.

Existing research on EMR adoption has predominantly examined organizational and behavioral readiness through frameworks addressing infrastructure, leadership, organizational resources, perceived usefulness, facilitating conditions, and technology–organization fit. Approaches such as the Doctor’s Office Quality–Information Technology framework, Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), and Human–Organization–Technology fit (HOT-fit) model have contributed substantially to understanding why healthcare organizations and professionals accept or resist health-information technologies. Contemporary EHR research confirms the relevance of UTAUT constructs such as performance expectancy, facilitating conditions, and organizational support for sustained system use. At the same time, TAM-based studies continue to demonstrate relationships among perceived usefulness, ease of use, trust, actual EHR use, and professional performance (Alsyouf et al., 2024; Al-Momani et al., 2024). These perspectives are valuable because both organizational capacity and individual perceptions of technology influence EMR implementation. Their application may nonetheless provide an incomplete explanation when the basic digital competence required to perform EMR-related tasks has not been established first.

Digital competence is a related but conceptually distinct dimension of EMR implementation, as acceptance of a technology does not necessarily demonstrate the capability to use it effectively. Research specifically examining digital competencies among healthcare professionals remains less developed than the broader literature on technology acceptance and organizational readiness. Available reviews indicate considerable variation in how digital competence is conceptualized and measured across healthcare settings, with no universally accepted instrument for assessing the construct in clinical populations (Longhini et al., 2022; Mainz et al., 2024). Recent systematic evidence further identifies education, professional experience, digital infrastructure, technological competence, and age as determinants of healthcare professionals’ digital health literacy, emphasizing that competence cannot be inferred simply from exposure to technology (Özatkan & Tekin, 2026). This measurement heterogeneity complicates comparisons across studies and makes it difficult to determine whether implementation difficulties reflect limited technological acceptance, inadequate organizational conditions, insufficient digital skills, or an interaction among these factors. Assessing acceptance without establishing baseline competence may therefore misattribute problems to the technology or organization when part of the difficulty originates from users’ capabilities.

A further research gap concerns the limited integration of quantitative assessments of digital competence with qualitative evidence describing how healthcare workers actually experience EMR implementation in everyday clinical and administrative practice. Cross-sectional surveys can identify which groups demonstrate comparatively lower competence or perceive weaker organizational support, yet numerical patterns alone cannot adequately explain how those disparities are produced, negotiated, or compensated for during routine work (Molloy-Paolillo et al., 2023; Mensah et al., 2024). Qualitative inquiry can reveal implementation processes that remain invisible in questionnaire data, including informal workarounds, interprofessional redistribution of tasks, training deficiencies, infrastructure-related disruptions, and differences in professional motivation (Robertson et al., 2024). Integrating these forms of evidence is therefore necessary to move beyond identifying competence gaps to understanding the organizational and experiential mechanisms that underlie them. Mixed-methods EHR research has specifically shown that quantitative usage indicators and qualitative accounts can yield different pictures of implementation, making integration valuable for explaining actual user experience.

The novelty of this study lies in examining digital competence and lived EMR experience sequentially while treating established technology-adoption frameworks as sensitizing perspectives rather than if recorded technology use necessarily reflects genuine individual acceptance or capability. The explanatory sequential design allows quantitative patterns in digital competence and perceived organizational support to guide subsequent phenomenological exploration across clinical, support, and management/IT stakeholder groups. This approach is particularly relevant in a setting where implementation has progressed under substantial regulatory pressure and where formal indicators of system use may not fully represent how documentation is performed in practice (Molloy-Paolillo et al., 2023; Robertson et al., 2024). Evidence that healthcare professionals develop workarounds in response to system limitations, situational constraints, and routine work requirements further supports the need to distinguish recorded system use from the processes through which that use is achieved (Tazkarji et al., 2024). The study consequently provides an opportunity to identify discrepancies between apparent EMR compliance and the everyday processes by which healthcare workers achieve it.

This study aimed to assess healthcare workers' digital competence and their perceived organizational support for EMR use, and to explain the quantitative patterns by exploring participants lived experiences of implementation. Attention was given to demographic and professional groups with comparatively lower competence, as well as to the organizational, technical, and interpersonal conditions that shape their use of EMRs. The study is urgent because hospitals undergoing rapid digital transformation require evidence that distinguishes formal implementation from effective and sustainable use. Contemporary implementation research shows that successful digital-health adoption depends on the alignment of workforce characteristics, workflow demands, training, technical support, organizational arrangements, and implementation context (Barnes et al., 2022; Weik et al., 2024). Evidence from real-world digital record implementation also emphasizes the importance of interoperability, provider training, and sustained organizational support for maintaining adoption beyond initial deployment (Davis et al., 2024). A clearer understanding of how competence, organizational support, infrastructure, professional roles, and workplace adaptations interact may help hospitals design more targeted training, improve implementation governance, and ensure that EMR compliance reflects meaningful digital capability rather than administrative completion alone.

The integration of the quantitative and qualitative findings indicates that EMR adoption at Hospital Y cannot be understood solely through individual digital competence or organizational readiness. Evidence from other health systems similarly indicates that EMR implementation reflects the interaction of workforce readiness, organizational capacity, and implementation conditions rather than a single technological or individual determinant (Yilma et al., 2023; Provenzano et al., 2024). Most healthcare workers demonstrated high digital competence, with 85.5% classified in the high category, yet substantial variation remained across age groups, professional categories, and levels of perceived organizational support. The qualitative findings provided an explanatory layer by showing that EMR use occurred within a context of reactive implementation, uneven training, infrastructure instability, hybrid paper–digital workflows, and informal redistribution of documentation responsibilities, challenges also reported in private hospital settings undergoing digital transition (Afriyie et al., 2026). These findings suggest that apparently successful EMR adoption may coexist with operational vulnerabilities that are not captured by competence scores or routine system-use indicators. The identification of proxy compliance is particularly important because it demonstrates that documented EMR activity may not always represent direct use by the account holder. The combined findings therefore support a broader interpretation of EMR implementation as an interaction between individual capability, organizational support, technical reliability, professional roles, regulatory pressure, and informal workplace adaptation.

The high overall level of digital competence observed in this study is consistent with the demographic profile of a workforce concentrated in productive age groups and characterized predominantly by intermediate computer experience. Previous research has similarly shown that younger healthcare professionals and those with greater exposure to computers tend to demonstrate stronger readiness for digital health technologies (Gelchu et al., 2025; Jarva et al., 2024). The present findings extend this evidence by showing that digital competence may be relatively strong even when implementation processes remain organizationally imperfect. Infrastructure-related support was generally rated positively, particularly computer availability and IT responsiveness, which is broadly consistent with earlier DOQ-IT assessments describing hospitals in Surabaya as highly prepared for digital implementation. Educational support remained comparatively weak, particularly regarding accessible user guidance and the clarity of EMR training. Evidence from a recent scoping review indicates that effective EHR training should account for computer literacy, role-specific needs, documentation expectations, opportunities for practice, and access to implementation support (Nguyen et al., 2024). The qualitative findings help explain this discrepancy by showing that training was introduced reactively and often followed system rollout rather than preceding it. Digital readiness should therefore not be interpreted as evidence that healthcare workers no longer require systematic training, particularly when system changes involve new responsibilities, documentation standards, and medicolegal accountability.

The age-related gradient in digital competence highlights the continuing importance of workforce heterogeneity in EMR implementation. High digital competence declined from 100.0% among workers younger than 25 years to 63.2% among those older than 45 years, consistent with evidence of age-related variation in healthcare professionals' engagement with digital solutions and competence development (Jarva et al., 2024; Erfani et al., 2025). The qualitative findings complicate a straightforward interpretation of this relationship because some senior clinicians appeared to maintain satisfactory EMR documentation through assistance from other healthcare workers. Proxy compliance may therefore conceal part of the competence gap by allowing an account to appear active and compliant even when another person has entered documentation. This distinction is methodologically important because self-reported competence, account-based usage statistics, and actual independent system use may represent different constructs. EHR audit-log research supports this distinction, as audit data can provide time-sequenced behavioral measures of how individual clinicians interact with electronic systems, rather than relying solely on self-reported use (Kannampallil & Adler-Milstein, 2023). A clinician may appear to be an effective EMR user according to system records, yet rely substantially on nurses or midwives to perform documentation tasks. Future assessments of digital competence may therefore need to distinguish between perceived capability, independently demonstrated capability, and recorded account activity to avoid overestimating individual adoption.

Professional differences in digital competence should also be interpreted within the structure of the EMR workflow rather than solely as individual skill deficits. Other health workers demonstrated a markedly lower proportion of high competence at 50.0%, compared with 96.2% among nurses and 92.9% among physicians. The qualitative findings indicate that support personnel frequently occupied downstream positions in the documentation process, making their work dependent on the completeness and timeliness of information entered by clinicians. Research on EHR documentation demonstrates that mismatches between electronic documentation structures and clinical workflows can lead to redundant tasks, increased workload, and workflow inefficiencies (Lindsay & Lytle, 2022; van Offenbeek et al., 2024). Network interruptions or delayed physician documentation could result in incomplete records, workflow disruptions, and interpersonal tension in units that were not responsible for the original problem. This finding is consistent with broader HOT-fit evaluations in Indonesian hospitals in which the Technology dimension has often emerged as a relatively weak component of implementation. Global evidence also indicates that infrastructure reliability remains a persistent barrier well into an EMR system's life (Finnegan & Mountford, 2025). Professional disparities in EMR performance may therefore reflect workflow position and technological dependency as much as individual competence.

The reactive nature of EMR implementation represents another important explanation for the gap between measured competence and lived experience. Participants described a rollout process strongly shaped by regulatory pressure, with modules introduced incrementally and training often focused on software functions rather than on the rationale, accountability, and workflow implications of electronic documentation. Evidence from EHR implementation research emphasizes that training effectiveness depends on personalization, appropriate pacing, opportunities to practice, clear documentation expectations, and continued implementation support (Nguyen et al., 2024). The absence of readily available written SOPs at workstations further suggests that implementation support had not kept pace with technological deployment. Staff responded by producing informal solutions, including printed WhatsApp instructions, parallel Excel records, and interpersonal assistance. Comparable research shows that EHR workarounds commonly emerge when formal system design does not adequately fit clinical work practices and that such accommodations may subsequently reinforce existing sociotechnical misfits (Van Offenbeek et al., 2024; Nguyen et al., 2026). These practices demonstrate organizational adaptability, yet they also indicate that formal implementation structures were insufficient to support consistent use. Informal workarounds may sustain service delivery in the short term while simultaneously normalizing practices that weaken standardization, traceability, and accountability. EMR training should therefore address not only how to operate system functions but also why specific documentation procedures matter for patient safety, continuity of care, legal responsibility, and institutional governance.

The findings also have theoretical implications for the application of TAM, UTAUT, HOT-fit, and DOI to mandatory health-information technologies. Systematic evidence confirms that TAM and UTAUT remain useful frameworks for explaining healthcare professionals’ acceptance of digital technologies, particularly through constructs related to perceived usefulness, ease of use, facilitating conditions, and behavioral intention (Rouidi et al., 2022; Tetik et al., 2024). These frameworks remained useful for interpreting perceived usefulness, facilitating conditions, organizational fit, social influences, and patterns of adoption, yet two findings extend beyond their conventional assumptions. Regulatory pressure was a central driver of implementation, meaning adoption was not primarily initiated by voluntary acceptance or gradual diffusion but by an externally imposed compliance requirement. Indonesian evidence has similarly shown that government regulation can operate as a predominant environmental determinant of health-information technology adoption, demonstrating that institutional pressure may shape adoption independently of individual willingness (Harahap et al., 2022). Proxy compliance poses an additional theoretical problem because TAM and UTAUT generally assume that the individual recorded as using the technology is the same individual whose acceptance and behavioral intention are being represented. EMR documentation performed by another healthcare worker disrupts this assumed correspondence between user identity, technology acceptance, and recorded behavior. The same issue affects HOT-fit interpretations because apparently successful alignment between organizational objectives and system-use indicators may partly reflect informal accommodation rather than genuine alignment between users, organizational processes, and technology. Future technology-adoption research may therefore benefit from distinguishing authentic use from delegated or proxy use, particularly in regulated clinical environments where documentation is linked to professional accountability.

The practical implications of these findings extend beyond increasing access to computers or delivering additional software demonstrations. Training programs should explain the clinical, organizational, and legal rationale for EMR documentation before emphasizing technical functions, with differentiated support directed toward older workers and professional groups demonstrating lower competence. Recent evidence supports role-specific EHR training and emphasizes the importance of tailoring competence development to users' digital skills, learning needs, and organizational context (Nguyen et al., 2024; Jarva et al., 2024). Written SOPs and accessible user guides should accompany each EMR module from the start of implementation, rather than being developed only after operational problems emerge. Infrastructure investment should prioritize areas with recurring connectivity problems because failures in a single unit can cause downstream disruptions across multiple professional groups. Routine monitoring should also verify the identity of the person entering clinical information, rather than relying exclusively on account-level completion indicators. Audit logs offer a particularly relevant mechanism because they capture time-sequenced user activity and can provide behavioral measures of clinical system use at scale (Kannampallil & Adler-Milstein, 2023). Proxy compliance deserves particular attention because documentation under another clinician's credentials may create implications for medicolegal accountability, auditability, information security, and BPJS claims. Organizational leaders should treat such practices as governance issues requiring transparent assessment rather than as informal solutions to workload or competence constraints.

Several limitations should be considered when interpreting these findings. The study was conducted in a single type-C private hospital, which limits transferability to hospitals with different ownership structures, workforce characteristics, information systems, or implementation maturity. Digital competence was measured through self-report and may therefore be affected by social-desirability bias or inaccurate self-assessment; contemporary reviews also demonstrate considerable heterogeneity in how healthcare professionals’ digital competence is conceptualized and assessed (Longhini et al., 2024). The quantitative subgroup analyses were descriptive and exploratory, preventing causal interpretation of relationships involving age, profession, tenure, or organizational support. The qualitative phase did not include personnel from delivery rooms or operating theatres because their EMR modules were still under separate development, leaving some high-intensity clinical environments underrepresented. Both phases also captured a particular period within an ongoing implementation process, meaning that staff experiences and organizational practices may change as the system matures. Future research should examine proxy compliance directly through triangulation with duty rosters, access logs, timestamps, or other system-level audit data. Audit-log methodologies can objectively characterize clinician–EHR interactions and have been proposed as a valuable source for understanding workflow, collaboration, and actual system-use behaviors (Kannampallil & Adler-Milstein, 2023; Huilgol et al., 2022). Longitudinal research should also determine whether competence gaps, hybrid documentation, and informal delegation persist after full implementation.

This study demonstrates that successful EMR implementation depends not only on healthcare workers’ digital competence but also on organizational support, infrastructure reliability, professional roles, and the conditions under which technology adoption occurs. Although most participants showed high digital competence, persistent gaps among older staff, non-clinical health workers, and those experiencing lower organizational support were compounded by reactive training, unstable infrastructure, prolonged hybrid workflows, and informal redistribution of documentation tasks. The identification of proxy compliance, in which EMR entries are completed by individuals other than the registered account holders, highlights a critical discrepancy between recorded system use and authentic technology adoption, with important implications for accountability, information governance, and medicolegal practice. Hospitals implementing EMR should prioritize targeted competency development, timely SOPs, reliable infrastructure, and routine auditing of actual system use to ensure that regulatory compliance reflects genuine, safe, and sustainable digital transformation.

The authors thank the Director and management of Hospital Y for institutional permission and support, and all participating healthcare workers for their time and candor across both study phases.

The authors declare no conflict of interest, financial or non-financial, in relation to this manuscript.