Implementing Evidence-Based Practice in Community Clinics: A Process Evaluation of Barriers, Adaptation, and Workflow Integration in the United States

Implementing Evidence-Based Practice in Community Clinics: A Process Evaluation of Barriers, Adaptation, and Workflow Integration in the United States | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Implementing Evidence-Based Practice in Community Clinics: A Process Evaluation of Barriers, Adaptation, and Workflow Integration in the United States CHINEDU Onyekwelu-Udoka This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8768667/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Evidence-based practices (EBPs) are problem solving-approach practices in the clinical setting that incorporates the best available research evidence which could include the best practice or expertise while looking out for the patient's values and preferences. They are mandated in the US community clinics based on federal policy and Medicaid contracting requirements. Although these mandates were created to level the playing field for both standardized quality care and implementation within routine care workflows, however, this has not been the case. Existing studies infer that EBP implementation failure is driven by the misalignment amongst organizational, technological and workflow not the clinician acceptance of usage. Objectives This study used the process evaluation techniques to assess the Implementation of Evidence-based Practice in Community Clinic in the United States community clinics with the aim of identifying major barriers, adaptation patterns, and workflow integration dynamics. Methods A process evaluation was conducted on twenty-eight (28) literature using an analytic approach informed by implementation science. The EBP investigated was a standardized clinical screening tool needed to be regulated during routine care encounters with patients and documented in the structured electronic health record (EHR) system to meet the Medicaid quality reporting requirements. Data sources were empirical studies from peer-reviewed papers that contained federal and state policy documents, EHR documentation specifications, workflow artefacts, and implementation guidance relevant to community clinic operations. Data analysis was done through structured thematic synthesis and mapping workflow with the end goal of establishing implementation frameworks and how they can be translated into real-world experience. Findings: Implementation barriers were mostly impeded by the lack of flexibility in the EHR system, the burden that comes from documentation, time pressure constraints and audit-driven compliance. Clinicians never resisted the use of EBPs, rather they engaged in informal adaptations such as shifting tasks, developing a workaround within the workflow, alteration of task sequencing, and documented later to make sure patient routine care continues. This resulted in partial fidelity, hidden compliance, and divergence between reported and enacted practice. Conclusions This evaluation reveals that the implementation outcomes in community clinics are controlled mostly by the compatibility of workflow and the context of the clinical environment as opposed to the clinician's attitude towards EBPs. Hence, it is important to design EBPs and implementation approach that can work in the real-world clinical workflows to attain sustainability in the community clinic setting. MSC Code: 00A06 Scientific community and society/Business and industry Health sciences/Health care Health sciences/Medical research Clinical Social Work Evidence-Based Practice Implementation Science Health Services Research US Community Clinics Electronic Health Records Systems Figures Figure 1 Background gap Evidence-based practices (EBPs) are referred to as the bedrock of clinical practices and they are vital for the functional and improvement of patient care. Evidence-based practices (EBPs) are problem solving-approach practices in the clinical setting that incorporates the best available research evidence which could include the best practice or expertise while looking out for the patient's values and preferences. EBP is broadly recognized as being foundational and fundamental to the improvement of health outcomes, standard and consistent care delivery, and bridging the gap between research and practice in the clinics or medical setting in communities across the United States (Alsadaan & Ramadan, 2025; Beňová et al., 2023). Over the years, EBPs have been observed with the potential to mitigate disparities, enhance management of severe illnesses and support preventive interventions (Beňová et al., 2023). However, regardless of the potential of EBPs and its widespread policy support, translating it into a routine practice present a continuous challenge: interventions falter when it is administered in the community primary care settings usually due to the complexity that exists in the real-world where there are structural restrictions, interruptions of workflows, and limitations of technology (Mathieson et al., 2018; Jaramillo et al., 2023; Durojaiye et al., 2024; Olakotan et al., 2025). The implication of this is that it creates a barrier for complete adoption. For instance, the nature by which every medical center or clinic runs, they are often too busy to restructure or reorganise the current setting to adopt the EBPs. When services are rearranged or spread thin across several locations, time and attention of personnel are pulled in multiple directions creating a lack of focus on implementation of the proposed practices (Mathieson, et al., 2018). More so, factors such as frequent changes in leadership, inadequate training for personnel and introduction to newer technologies or tech support (e.g., Electronic Health Records, etc.) --cause too many disruptions such as numerous alerts, workflow redundancy, and increment in paperwork– makes adoption even more difficult (McCurdie et al., 2017; Pinevich et al., 2021). As a result, clinicians are bound to spend more time doing documentation than providing care. These challenges show up in several kinds of conditions and services reflecting a broader systemic problem that affect the clinical practice (Durojaiye et al., 2024). According to Zhang et al., (2025), implementation science focuses on the fact that research evidence must go beyond existence to real practice and usage in clinics. Guidelines do automatically translate into practice --routine care, rather evidence has to go through the everyday clinical channel such as workflows, schedules, tech support and different clinical roles. Hence, the need for adoption and adaptation of the EBPs to fit into community primary health care settings. Several existing studies have documented numerous hindrances that complicates the usage of EBPs in everyday routine care such as improper alignment on EHRs, documentation process that requires proper audit, limitation in staffing capacity and lack of time to administer care to patients (Olakotan et al., 2025; Pinevich et al., 2021; Mörike et al., 2024). Although quite a number of theses research work have focused on the identification of barriers they, however, fail or rarely examine the active response of clinicians to these practices. Comparatively, there's little to no empirical information to how clinicians navigate routines, adapt to informal workarounds or integrate multiple clinical workflows. Hence, translating policy directives and organizational expectations into daily care routine is insufficiently understood (von Thiele Schwarz et al., 2019; Wooldridge et al., 2017). Existing research has highlighted that there are tensions between adjusting the EBP protocols and practices into real-world clinical scenarios which often leads clinicians to modify procedures to ensure a patient-centered care (Owczarzak et al., 2016; Lennox et al., 2018). However, less research has shown the adaptation of these practices in the real-world especially in under-resourced community care centers leaving significant gaps in operationalization, barriers and workflow integration (Jaramillo et al., 2023; Damschroder et al., 2022). Therefore, to guide the development of EBPs in a way that brings balance and practical applicability to implementation science and health services research without diminishing the quality of care, this gap must be addressed. This study responds to these gaps by conducting a multi-process evaluation of EBPs in community clinics in the United States examining the structural, organizational and workflow barriers alongside formal and informal adaptations with the aim of generating evidence-based recommendations for an implementation design that is responsive. Theoretical and Conceptual Framework Process Evaluation as an Explanatory Lens This study utilizes an implementation science approach guided by a process evaluation framework to explore the operationalization and enactment of EBPs within the community clinic settings in the United States. In situations where only outcomes from interventions are measured, this framework examines the incorporation of EBPs in clinical work routines, organizational highlights, structural workflows, possible barriers and practice adaptations occurrence (Moore et al., 2015; Damschroder et al., 2022). The implementation of EBPs comes with different forms of complexities, hence, they have to be shaped, interpreted and enacted to fit the existing original workflows, technologies and clinical practices already in existence (Cunningham & Card, 2014; Wiltsey Stirman et al., 2019). Although process evaluation mostly documents how interventions match the implementation, however, they have been criticized for overlooking the dynamic nature of how organizational routine reshapes the enactment of interventions (Moore et al., 2015; Howard-Grenville et al., 2016). In numerous applied health services studies, process evaluation is rather portrayed as descriptive adjunct to outcome reporting than making them out to be mechanisms that critically analyze how workflow design and institutional logic affect implementation success or failure (Damschroder et al., 2022; Nilsen, 2020). This study intentionally positions process evaluation as an explanatory lens as opposed to a supplementary assessment tool. By foregrounding workflow integration, it moves beyond identifying determinants to examining how those determinants are operationalized within the temporal, technological, and professional constraints of community clinics. Moreover, implementation science has shown that adoption is not a one-time thing or something that should be forced on clinicians but an evolving process and negotiations that fits into local and ground-level clinical reality (Lobb & Colditz, 2013; Miller et al., 2020). Hence, this framework ensures that stages are treated as recursive and interdependent processes evolving through feedback loops and professional adaptation. Integration of Determinant Frameworks: Conceptual Use of CFIR This framework builds upon determinant-focused implementation research, particularly the Consolidated Framework for Implementation Research (CFIR) highlighting organizational factors such as the compatibility of workflow, readiness to change and climate implementation, and how they influence the adoption of the EBPs. This study employs CIFR as less of an analytical and more as a conceptual guide to help with understanding the structural and functional workflows of an organization and how it influences processes of implementation without the formal application of the framework (Damschroder et al., 2022). CFIR is the best tool for a comprehensive overview but not an “how-to” guide because its broad nature makes it difficult to explain the specific, dynamic causes of implementation success or failure without pairing it with other theories that focus on the process of change (Nilsen, 2020; Reardon et al., 2025). The CFIR domains were juxtaposed with observable workflow enactments rather than abstract readiness scores. This analytical approach takes the attention from static organisational characteristics to dynamic interactions between structural conditions and clinician behaviour. More so, determinant frameworks alone may undermine the role of technology in influencing implementation trajectories (May et al., 2016; McCurdie et al., 2017). For instance, electronic heath records (EHR) are not neural infrastructures; they actively configure task sequencing, documentation priorities, and cognitive workload (Pinevich et al., 2021). By integrating system-level approach, this framework recognises that technological artefacts participate in the implementation process by redistributing attention, structuring decision pathways, and constraining temporal flexibility. In this sense, workflow friction is not merely a human resource issue but an emergent property of system design. Sociotechnical and Workflow Perspectives Clinical settings emerge from interactions among clinicians, technologies, tasks, and organisational rules. Hence, this framework integrates sociotechnical and workflow perspectives (Carayon et al., 2020; McCurdie et al., 2017). Research has shown that EBPs are usually known to require more documentation, screening, and frequent coordination which could impede strict time-appointments, rigid EHRs and increase cognitive demands causing workflow friction (Pinevich et al., 2021; Olakotan et al., 2025). Fidelity, Adaptation, and Professional Agency This framework adopts unconventional insights on fidelity and adaptation by paying more attention to the clinicians on the frontline who naturally modify their EBPs to fit the needs of patients, constraints on employment and the local norms. Moreover, there has been a continuous and persistent debate between fidelity and adaptation in implementation science, mostly seen as a trade-off between internal validity and contextual fit (Wiltsey Stirman et al., 2019; Chambers et al., 2013). However, recent research opined that the term fidelity needs to be redefined as a core component as opposed to a rigid procedural adherence (von Thiele Schwarz et al., 2019). Also, if a strict fidelity is place in community clinic setting where there are high patient complexity and scarcity of resource it can undermine sustainability and disregard feasibility of workflow. As stated by (Chambers et al., 2013 and May et al., 2016), this study approaches adaptation as a pragmatic expression of professional expertise within structural constraints. Multi-Level Implementation Dynamics Implementation can only be understood across interconnected events rather than a single phase with each event influencing the interpretation and enactment of EBPs in routine practice. These interrelated stages are carefully illustrated in Table 1 alongside their corresponding methodological empirical examples with the process visually documented in Fig. 1 . Previous studies have shown that past policy and payer mandates have positioned EBPs as obligations that drive compliance, in turn, influencing organizational priorities, allocation of resources, and structural accountability within the medical settings. However, at the highest level, the expectations that surround the adoption of EBP are shaped by these mandates –Medicaid contracts, standardized quality reporting and regulatory guidance inclusive (Crable et al., 2020; Durojaiye et al., 2024). Policy and payer mandates encourages EBP adoption by improving organizational accountability system in ways that allow measurable outputs over holistic or relational processes of care (Crable et al., 2022; Hu et al., 2025). Constant auditing of Medicaid contracts and strict regulatory monitoring system gives room for performative logics shifting EBPs from clinically-oriented practice to compliance-oriented documentation (Posch & Speckbacher, 2017; Durojaiye et al., 2024). This distinction is analytically important to explain why implementation behaviour may reflect regulatory visibility rather than therapeutic optimization. Contextually, adherence to documentation practices is what becomes routinized and not intervention itself. More so, in a compliance-driven environments escalates vertical accountability and reduces horizontal accountability among clinicians (Nilsen et al., 2020; May et al., 2016). This revaluation of accountability makes certain that EBPs are prioritized during time-constrained encounters regulating professional autonomy. The forms this translation takes are mostly benchmarks performances, expectation on documentation, processing training of clinicians and specific protocols for clinics. Organisational Translation and Leadership Mediation On the other hand, the approach from a leadership perspective influenced by availability of resources, perceived regulatory risks, and auditing pressure, all affects the prioritization and positioning of EBPs within the community primary care on a daily basis (Mathieson et al., 2018; Damschroder et al., 2022). When the expectation of EBP has been incorporated into the daily routine, implementation gears into the workflow state. This implies that requirements will be embedded into the EHR systems, responsibilities allocated across clinical roles and designated tasks as clinicians encounter more patients. Studies have shown that from a human perspective challenges often arise when EBPs are not effectively incorporated creating some form of misalignment within the clinical care routine especially if corresponding adjustments were not made elsewhere. These misalignments often create friction in workflow and informal workflows causing clinicians to juggle more work than expected (McCurdie et al., 2017; Pinevich et al., 2021). Workflow Integration and Structural Misalignment Workflow misalignment is a kind of socio-organizational strain that builds up when the intervention requirements place more demand on the existing capacity than an organization can handle (Carayon et al., 2020; Zheng et al., 2020). This framework views this tension as indicators of a structural misalignment (in policy design and clinical operations) rather than standalone constraints. For instance, adding a screening protocol without appropriate staff rotation and time balancing can snowball into cognitive load (Pinevich et al., 2021). In the long run, these micro-level frictions accumulate causing clinicians to become indifferent towards EBPs. Significantly, such misalignments highlight the limits of linear implementation models that assume proportional resource adaptation following policy change (Damschroder et al., 2022; Nilsen, 2015). Practically, successful implementation of EBPs often depends on frontline clinicians compensating for delayed or partial resource augmentation. Clinicians sometimes use informal coordination, labour redistribution and temporarily deferring task to accommodate both planned resources and actual availability. Drawing from past research especially in the area of safety-net and community settings, interventions supported by EHRs and the efforts to improve quality in care has often caused different types of disruptions ranging from existing workflow interruptions, less capacity placing a heavy demand beyond what's available to conflict in clinician's personal judgement. Since EBPs are mostly carried out by the frontline clinicians constantly facing tight schedules, juggling multiple work calls, and various levels of care complexity there's expected to be an emergence of friction in the framework (Zheng et al., 2020; Olakotan et al., 2025). In the emergence of these challenges, clinicians mostly respond by adjusting the EBPs usage in practice. For instance, instead of taking on multiple tasks all at once, they redistribute it to other competent clinicians or take it on another time. Order of activities are changed to suit the current situations, documentation or filing of reports become limited and electronic prompts are bypassed. Structural and Behavioural Adaptations This framework provides a clear distinction between structural and behavioural adaptations. Structural adaptations refer to organisational-level modifications like role reallocation or configuration changes of EHR systems (Chambers et al., 2013). Conversely, behavioural adaptations refer to the clinical-level modification which involves moment-to-moment adjustments in sequencing, emphasis, or documentation practice. Understanding the difference between these two is analytically important as it determines how each adaptation is absolved, either institutionally or left to individual discretion (Lennox et al., 2018). More so, formalization of behavioural adaptations ensures that everyone has access to the best practices and reduces the chances of anyone left behind across all sites. Besides, under constrained conditions, informal workarounds can serve as the stabilising element that preserves core therapeutic elements (McCurdie et al., 2017; May et al., 2020). Yet, normalizing workaround raises the question about hidden labour and professional burden. Allowing EBPs to rely on compensatory effort put its sustainability at the mercy of the resilience of clinicians rather than system design. Hence, this framework treats workarounds as indicative markers that require organization reflection rather than endpoints. Eventually, this feedback can create revisions to protocols, strengthen current approaches, prompt normalization of informal workarounds which could lead to more sustained and suitable patterns of modified EBPs (Chambers et al., 2013; Lennox et al., 2018). Since other approaches have taken a linear approach towards a perfect fidelity for EBPs, this framework enables a more dynamic and systematic approach that explores barriers to implementation and creates adaptive responses to challenges faced when integrating EBPs into everyday care. Methods This study employed the process evaluation design model to investigate the working system of the EBPs and its implementation in United States community clinic settings focusing on barrier identification, adaptations and workflow integration challenges. Process evaluation is applicable for examining real-world context with complexity giving room for close analysis of how implementation activities are done and how they might evolve in the near future (Moore et al., 2015; Damschroder et al., 2022). This evaluation did not consider the effectiveness of clinical practice or outcomes of patients; however, it focused on the protocols by which EBP was implemented, following how requirements at organizational level were interpreted, translated into clinical workflows and adapted into routine care. This focus is closely related to the study of policy-driven EBPs in resource-limited healthcare settings (Cunningham & Card, 2014; Lennox et al., 2018). The study used no qualitative data such as interview, surveys and observation methods, but adopted multiple sites, document-based design, and relied on existing organizational policy and system records. The evidence-based practice (EBP) used in the evaluation is a mandated clinical approach embedded within the daily routine care in the US community clinics alongside the required quality reporting for Medicaid. This practice must be done or overseen by a clinician using the standardized screening tool during patient consultation and records must be done in a structured environment within the EHRs, depending on the workflow of the clinic. A successful implementation of the screening is classed by the adherence to policy guidance, consistency in administration, EHR documentation accuracy, and correct data generation suitable for audit and reporting. EBPs of this magnitude are mostly documented for implementation research as the comprise clinical, administrative and technological domains which is good for literature and show the technicality and additional workflow it demands if it needs to be integrated into daily routine care (Zheng et al., 2020; Olakotan et al., 2025) The evaluation was constructed by drawing on studies on US community clinics —federal-based health centers and community-based clinics inclusive— all operating within the reimbursement arrangement of Medicaid. Data collection sources were intentionally chosen to show implementation practices in relation to expectations on policy-level, organisational decision-making and execution of workflow by the frontline clinicians. Based on established guidelines for process evaluation, this study relied mostly on multiple data sources to aid the triangulation and improve the interpretation of the implementation practice (Moore et al., 2015). These materials comprise of the policy and payer documents —contracts provision by Medicaid, local protocols, quality reports, implementation manuals, clinic-level organisational artefacts, training resources, diagrams of workflows, logic specifications alert, reporting system configurations, dashboard qualities and compliance feedback summaries— including EHRs related documents. Table 1 outlines these data sources, the actors involved, the major touchpoints workflows, and their contributions to the analytic framework. Implementation science informed the thematic approach used in the data analysis with the aim of identifying patterns that are recurrent in relation to implementation barriers, adaptive practice and workflow integration. All data sources were iteratively analyzed by tracing how the EBP requirements were interpreted at the policy level and equally translated into organizational protocols and routine care. Instead of using a deductive approach in a determinant framework, the analysis was guided by sensitizing concepts from implementation science literature that has been established. These consisted of the readiness of the organization, climate implementation, how the EBP requirements aligns with the existing workflows, sociotechnical interactions involving EHRs and a trade-off between fidelity and adaptation. These concepts align with the CFIR domains in terms of inner setting and process implementations; however, they were employed as conceptual guides and not a formal coding structure to avoid exaggerating the methodological claims (Damschroder et al., 2022). More so, a rather analytical approach was placed on identifying where enacted workflows diverged, types of adaptations could maintain feasibility and the feedback approach can shape the progressive implementation. Findings were integrated from different research literature to highlight shared implementation dynamics rather than a generic comparative analysis. To coherently strengthen this study analytically, the conceptual model was developed to illustrate how the EBP will progress from an extrinsic policy mandate to the frontline execution with possible future adaptations. The model was sourced directly from already established and grounded implementation and workflow literature (Chambers et al., 2013; McCurdie et al., 2017). It lays out how the policy and payer mandates are implemented by clinic leaders and translated into the workflow of the organization, EHR configurations and enacted into routine care, paying a close attention to the friction that emerges from implementation in order to process feedback as it influences ongoing delivery. A presentation of the model is shown in Fig. 1 and is mentioned in the Findings section to establish the empirical observations within a larger implementation process. Quite a number of strategies were employed to improve analytical credibility and rigour. Using multiple literature supports the triangulation process across policy, organizational and workflow levels with analytical claims grounded in documented artefacts and established empirical literature rather than web reports or self-reported perceptions. Interpretations were intentionally restricted to reasonably supported data available. This approach aligns with the process evaluation method (Moore et al., 2015; Clement et al., 2018). This study relied mostly on existing documents and system artefacts. No human participation was involved, neither was any identifiable patient information collected. Hence, an approval from an institutional board was not needed. All materials used were handled with confidential standards. Findings Barriers Having reviewed several policy documents, organizational materials, and EHR-related artefacts, several implementation barriers have been identified across organizational, structural and clinical-workflow levels. Across this level, these barriers largely reflect the misalignment between the requirement of EBP externally and its practicality in the real-world when delivering care in community clinic settings. At the structural level, a key restriction shaping implementation are audit requirements and Medicaid-linked reporting. Policy and payer mandates emphasize on completeness of documentation, standardization, reportability of data with less attention to how screening activities could be integrated into existing workflows. More so, the EHR configuration materials also reinforced this result by embedding screening tools as mandatory fields or automated alerts with little flexibility to accommodate visit complexity, staffing variability, or competing clinical priorities. Prior research has shown consistency with this study that rigid digital systems cause friction when EBPs were integrated into existing systems without accompanying workflow redesign (Zheng et al., 2020; Olakotan et al., 2025). Across the artefacts examined, the challenges faced were not because of a singular operational glitch but a series of patterned events of systemic design that was prioritize. This mismatch indicates that the attention of the organization is geared towards measurability rather than what is sustainable in practice (Powell et al., 2021; Williams et al., 2024). Significantly, the EHR’s logic specifications forces clinicians to follow a non-flexible and hard-stopped mandatory field that focus more on data collection instead of their ability to manage patient care normally. This finding shows that technological rigidity doesn’t just create technical limitations but affects structural reinforcement. At the organizational level, the gaps between formal workflows as intended and how screening should be done in clinical practice was revealed from assessing clinic protocols and materials used for training. Although official documentation showed screening processes were linear and standardized, other materials such as audit clarification showed that there are ongoing uncertainties around task ownership and effective timing. This pattern indicates that a broader scope of implementation will reveal unclear responsibility and competing demands within the organisation which can compromise readiness (Weiner et al., 2017; Jaramillo et al., 2023). Furthermore, workflow artefacts and documentation of EHR showed that clinicians at the forefront of the job are expected to complete even more documentation tasks with their tight schedule. Common recurring issues stated by clinicians were: burden of documentation, high alert frequency, task sequencing conflicts, especially in areas where screening requires registration, triage and clinical assessment activities. These findings corroborate the issue of cognitive load and pressure on clinicians when dealing care for outpatients (Pinevich et al., 2021; McCurdie et al., 2017). Adaptations Clinics have responded to the implementation barriers by trying to make formal and informal adaptations to make EBP workable by balancing its fidelity and flexibility requirements with daily routine care. The formal adaptations require changes in workflows, allocation of tasks, and time documentation (to avoid time-constraints situations) which reflects iterative adjustments with the aim of maintaining flow of patient care as opposed to a rigid system (von Thiele Schwarz et al., 2019; Chambers et al., 2013). Technology in healthcare is often designed with formal adaptations to force compliance with data rules, which unfortunately strips doctors of their ability to prioritize patient needs (Chambers et al., 2013). However, clinics fight back against this rigidity by strategically moving these mandatory tasks to other staff members, effectively recalibrating internal systems to maintain operational continuity. Conversely, informal adaptations are like unofficial micro-level compensatory practices clinicians use to manage cognitive load under temporal constraints. Some of these practices include delaying documentation, selective alert engagement and task bundling (McCurdie et al., 2017). Although these adaptations help preserve workflow, it also results in inconsistent medical records (Mörike et al., 2024; Zheng et al., 2020). Importantly, these findings reinforce that adaptations are not fatal, they reflect a rather pragmatic approach of solving the problem at hand. Hence, this indicates that adaptation is normal and it is a necessary feature for real-world implementation of EBP enabling clinics to maintain routine care while navigating these constraints (Owczarzak et al., 2016; Lennox et al., 2018). Workflow integration Analyzing the workflow documents and system materials it is evident that the community clinic settings struggle to integrate the EBP with ease into everyday routine care. As shown in Fig. 1 , when patients come to visit for care, clinicians find it difficult to juggle attending to the patients and attend to EHR-generated tasks. More so, it seems like the EBP activities—EHR logic, task allocation, and staff training— were adding more responsibilities to the already available work instead of streamlining other tasks —this has increased interruptions and created more conflict in the order in which the work needs to be completed. Additionally, the workflow challenges were augmented by the feedback mechanism that seemed to prioritize audit results over learning the major workflow design. Audit reports, benchmarks, metrics and performance dashboards are more focused on documentation processes rather than the actual work, hence, this limited workflow structure affecting the implementation practicality. Some research has shown that unintentionally prioritizing a performance measurement system can breed inefficient practice as compliance has overridden usability (Lennox et al., 2018; Wooldridge et al., 2017). Discussion Reframing Implementation Beyond Clinician Compliance These findings have suggested that implementation outcomes have been influenced more by the system design than the willingness of clinicians or EBP acceptance. Barriers were caused by policy requirements, organizational procedures and digital systems that have no interconnection with everyday routine care workflow creating misalignment. These results show that EBPs need to be designed with the intention of workflow fit, flexible EHR configurations, and feedback systems that promote learning rather than focus on compliance alone. Also, any implementation effort that overlooks constraints created by structure and technology while focusing on only staff training and motivation will most likely not support long-term integration. These implications support the claims that implementation science needs to go farther from fidelity-centric models and adapt towards workflow integration approaches that can work in the real-world of community clinic care (Powell et al., 2021; Lewis et al., 2018). This study argues that implementation science focuses excessively on the attitude of clinical professional. This is more like a distraction. In reality, the system-level design forces clinician to act a certain way whether they are motivated or not. This is known as “determinative influence” and it implies that the structural configuration of a digital infrastructure predetermines how care will occur. For instance, if a system is designed for auditing or billing, the clinician is not an independent decision-maker rather a user in an automated process (Carayon et al., 2015; McCurdie et al., 2017). Researchers have argued that implementation success shouldn’t be about individual grit or motivation alone but an emergent of interactions between organizational systems and professional practice. By empirically illustrating how EHR configurations and audit mechanisms shape workflow density, the study shifts explanatory attention from behavioural compliance to infrastructural alignment. Policy Mandates and the Compliance—Care Tension The findings show a major traceability trap that highlights a structural tension. Medicaid-linked EBPs mandates conflates documentation of a task with implementation success. The implication of this is that it turns EHR into a repeatability tool instead of a healing tool; success is no longer measured by patient recovery but by performance dashboards (Williams et al., 2020; Durojaiye et al., 2024). This compliance-care tension creates broader implications for policy design. Instead of making transformative care improvements, these mandates pile on more work for clinicians. This suggests that policy designers are possibly “clinically illiterate” as they create rules without understanding the temporal and staffing realities. More so, by ignoring workflow frameworks, system compliance is reached but operational sustainability is compromised. This simply implies that today can produce a perfect audit report but the next day can bring a clinic full of burn-out staff and a broken healthcare system (Lennox et al., 2018). Future policy reforms may therefore benefit from embedding workflow simulation or pilot integration assessments prior to widespread mandate enforcement. Adaptation as Organisational Intelligence One of the key contributions of this study is the empirical differentiation between structural and behavioural adaptations. Informal workarounds by clinicians shouldn’t be seen as fidelity erosion, in fact it is a form of intelligent behavioural adaptation (Wiltsey Stirman et al., 2019). However, this is a trap of individual resilience. Relying on informal workarounds for clinics to stay afloat means they’re gambling on the clinician’s stamina. If the system only works when medical professionals are willing to multitask and work through their rest time, then, it is no longer a strategy but a systemic exploitation (Chambers et al., 2013). However, the sustainability of adaptation depends on its institutional absorption. Where behavioural adjustments remain informal and unacknowledged, implementation stability becomes contingent on individual resilience. Over the course of time, this may exacerbate professional strain and variability across sites. Consequently, implementation strategies should incorporate structured mechanisms for capturing and formalising effective frontline adaptations, thereby converting experiential adjustments into organisational learning (von Thiele Schwarz et al., 2019). Implications for Implementation Science Theory Theoretically, this study indicates that the CFIR is good for pointing out a list of problems, however, it is a static model. Mixing policies, tech and workflow could be unpredictable and chaotic creating invisible reactions. This is like using the map to predict traffic movement; you can see the road but you can’t see movement (Damschroder et al., 2022; Nilsen, 2020). The best way to understand how a new program works is to check how it fits into the daily flow of work and systems surrounding it. This relational orientation highlights that successful implementation is not just an event, but a result of the interactions between people, tools, and their environment. Such an approach is particularly relevant in community clinic settings characterised by constrained resources and dense regulatory oversight. Limitations and Reflexive Considerations There are several limitations in this study that needs to be carefully considered. The first thing to note is that the study relied heavily on document-based and artefactual analysis without direct observational or interview data. Although this approach lessens retrospective bias and strengthen structural inference, it restricts insights into experiential workflow enactment in real-time. The implication of this is that informal practices will most likely be underrepresented due to lack of formal documentation (Lennox et al., 2018). Furthermore, despite the inclusion of numerous clinic sites, the analysis is exclusive to mostly the U.S. Medicaid reimbursement context implying that these findings might not be directly transferable to other healthcare system outside the US or private healthcare system. Hence, contextual specificity should guide interpretation as opposed to universal extrapolation. Additionally, in terms of clinical effectiveness, the absence of patient outcome data affects conclusions. This study deliberately focused on implementation processes only; however, future research integrating workflow analysis with outcome evaluation would provide a more comprehensive understanding of policy-driven EBP sustainability. Overall, while feedback and documentation of workflow provide indirect insight into adaptation, observational validation could possibly improve casual inference in future studies. More so, artefactual data reflect formalised organisational intent but may fail to capture the nuance of workarounds. Concluding Reflections Conclusively, this discussion pinpoints that successful EBP implementation in community clinics is more a function of systemic coherence and less a question of clinician willingness. When policy mandates, digital infrastructures, and workflow design operate in alignment, it stabilizes implementation. When misaligned, adaptation emerges as a work burden. Recognising this dynamic reframes implementation from a compliance problem to a systems engineering challenge. Consequently, advancing implementation science in policy-driven environments requires integrating governance analysis, sociotechnical design, and workflow modelling into future research agendas. Only through such integrative approaches can EBPs transition from mandated requirements to sustainably embedded components of everyday care. Declarations Ethical Approval This study did not involve human participants, patient data, or identifiable personal information. The research was based exclusively on publicly available literature and secondary documentary sources; therefore, formal ethical approval was not required. Informed Consent Informed consent was not applicable, as the study did not involve human subjects or the collection of primary data. Data Availability This study adopted the process evaluation design and critical interpretive synthesis drawing exclusively on publicly available peer-reviewed literature, published implementation frameworks, and secondary documentary sources. No primary human participant data, patient-level datasets, or confidential institutional records were collected or analysed. To support transparency and reproducibility of the analytic process, the following materials have been made available as Supplementary Files: A structured list of document categories reviewed; The coding framework and analytic logic structure used for thematic synthesis; A framework mapping matrix linking identified artefacts to relevant implementation science constructs (including CFIR domains and sustainability constructs); An analytic decision trail documenting theme development and refinement. All cited literature is publicly accessible through their respective publishers. No proprietary datasets were used; because this study did not generate or analyse raw quantitative datasets, there are no numerical datasets or statistical scripts to deposit. The supplementary materials provided contain all documentation necessary for editors and referees to scrutinise the methodological approach and analytic decisions underlying the findings. Supplementary materials are available alongside this manuscript submission. Author Contribution O.U.C.F. conceived the study, conducted the research, wrote the manuscript, and prepared all figures. The author reviewed and approved the final version of the manuscript. References Alsadaan, N. and Ramadan, O.M.E. (2025) Barriers and facilitators in implementing evidence-based practice: a parallel cross-sectional mixed methods study among nursing administrators. BMC Nursing , 24 (1), 403. https://doi.org/10.1186/s12912-025-03059-z Andersen, B.L. and Dorfman, C.S. (2016) Evidence-based psychosocial treatment in the community: considerations for dissemination and implementation. Psycho-Oncology , 25 (5), 482–490. https://doi.org/10.1002/pon.3864 Beňová, L., Semaan, A., Portela, A., Bonet, M., van den Akker, T., Pembe, A.B. and Duclos, D. (2023) Facilitators and barriers of implementation of routine postnatal care guidelines for women: a systematic scoping review using critical interpretive synthesis. Journal of Global Health , 13 , 04176. https://doi.org/10.7189/jogh.13.04176 Calderon, M.A., Casale, T.B., Nelson, H.S. et al. (2023) Extrapolating evidence-based medicine of allergen immunotherapy into clinical practice in the United States. Journal of Allergy and Clinical Immunology: In Practice , 11 (4), 1100–1115. https://doi.org/10.1016/j.jaip.2022.10.033 Carayon, P., Wooldridge, A., Hoonakker, P., Hundt, A.S. and Kelly, M.M. (2020) SEIPS 3.0: human-centered design of the patient journey for patient safety. Applied Ergonomics , 84 , 103033. https://doi.org/10.1016/j.apergo.2019.103033 Chambers, D.A., Glasgow, R.E. and Stange, K.C. (2013) The dynamic sustainability framework: addressing the paradox of sustainment amid ongoing change. 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(2022) Improving implementation of evidence-based therapies for heart failure. Clinical Cardiology , 45 (S1), S52–S59. https://doi.org/10.1002/clc.23816 Dias, E.M., Padilla, J.R., Cuccaro, P.M. et al. (2024) Barriers to and facilitators of implementing colorectal cancer screening evidence-based interventions in federally qualified health centers. BMC Health Services Research , 24 , 797. https://doi.org/10.1186/s12913-024-11163-0 Durojaiye, C., Prausnitz, S., Schneider, J.L. et al. (2024) Barriers and facilitators to high-volume evidence-based innovation and implementation in a large community-based learning health system. BMC Health Services Research , 24 , 1446. https://doi.org/10.1186/s12913-024-11803-5 Ebrahimi, H., Megally, S., Plotkin, E. et al. (2024) Barriers to clinical trial implementation among community care centers. JAMA Network Open , 7 (4), e248739. https://doi.org/10.1001/jamanetworkopen.2024.8739 Haynes, A.B., Weiser, T.G., Berry, W.R. et al. (2009) A surgical safety checklist to reduce morbidity and mortality in a global population. New England Journal of Medicine , 360 (5), 491–499. Howard-Grenville, J., Rerup, C., Langley, A. and Tsoukas, H. (2016) Organizational routines: how they are created, maintained, and changed. Hu, S., Liu, S., Li, X., Zhao, J., Chen, J., Chen, W. and Hu, J. (2025) Organizational evidence-based practice culture, implementation leadership, and nurses: a bidirectional mediation model. International Nursing Review , 72 (2), e13054. https://doi.org/10.1111/inr.13054 Jaramillo, E.T., Willging, C.E., Saldana, L., Self-Brown, S., Weeks, E.A. and Whitaker, D.J. (2023) Barriers and facilitators to implementing evidence-based interventions in the context of a randomized clinical trial in the United States. BMC Health Services Research , 23 , 88. https://doi.org/10.1186/s12913-023-09079-2 Kilbourne, A.M., Neumann, M.S., Waxmonsky, J. et al. (2012) Public-academic partnerships: evidence-based implementation. Psychiatric Services , 63 (3), 205–207. https://doi.org/10.1176/appi.ps.201200032 Lennox, L., Maher, L. and Reed, J. (2018) Navigating the sustainability landscape: a systematic review. Implementation Science , 13 , 27. https://doi.org/10.1186/s13012-017-0707-4 Lewis, C.C., Klasnja, P., Powell, B.J. et al. (2018) From classification to causality: advancing understanding of mechanisms of change in implementation science. Frontiers in Public Health , 6 , 136. https://doi.org/10.3389/fpubh.2018.00136 Lobb, R. and Colditz, G.A. (2013) Implementation science and its application to population health. Annual Review of Public Health , 34 , 235–251. https://doi.org/10.1146/annurev-publhealth-031912-114444 May, C.R., Johnson, M. and Finch, T. (2016) Implementation, context and complexity. Implementation Science , 11 (1), 141. https://doi.org/10.1186/s13012-016-0506-3 May, C., Finch, T. and Rapley, T. (2020) Normalization process theory. In: Handbook on Implementation Science . Edward Elgar Publishing, pp. 144–167. McCurdie, T., Sanderson, P., Aitken, L.M. and Liu, D. (2017) Two sides to every story: examining interruptions in healthcare. Applied Ergonomics , 58 , 102–109. https://doi.org/10.1016/j.apergo.2016.05.003 Miller, C.J., Wiltsey-Stirman, S. and Baumann, A.A. (2020) Iterative Decision-making for Evaluation of Adaptations (IDEA): a decision tree for balancing adaptation, fidelity, and intervention impact. Journal of Community Psychology , 48 (4), 1163–1177. https://doi.org/10.1002/jcop.22279 Moore, G.F., Audrey, S., Barker, M., Bond, L., Bonell, C., Hardeman, W. et al. (2015) Process evaluation of complex interventions: Medical Research Council guidance. BMJ , 350 , h1258. https://doi.org/10.1136/bmj.h1258 Mörike, F., Spiehl, H.L. and Feufel, M.A. (2024) Workarounds in the shadow system: an ethnographic study. Human Factors , 66 (3), 636–646. https://doi.org/10.1177/00187208231200000 Nilsen, P. (2015) Making sense of implementation theories, models, and frameworks. Implementation Science , 10 , 53. https://doi.org/10.1186/s13012-015-0242-0 Olakotan, O., Samuriwo, R., Ismaila, H. and Atiku, S. (2025) Usability challenges in electronic health records: a scoping review. Journal of Evaluation in Clinical Practice , 31 (4), e70189. https://doi.org/10.1111/jep.70189 Owczarzak, J., Broaddus, M. and Pinkerton, S. (2016) Fidelity and adaptation in evidence-based HIV prevention. Health Education Research , 31 (2), 283–294. https://doi.org/10.1093/her/cyw012 Pinevich, Y., Clark, K.J., Harrison, A.M., Pickering, B.W. and Herasevich, V. (2021) Interaction time with electronic health records: a systematic review. Applied Clinical Informatics , 12 (4), 788–799. https://doi.org/10.1055/s-0041-1733909 Posch, A. and Speckbacher, G. (2017) The role of middle management in the implementation of sustainability strategies. Available at SSRN: 2902552. Powell, B.J., Fernandez, M.E., Williams, N.J. et al. (2019) Enhancing the impact of implementation strategies in healthcare. Frontiers in Public Health , 7 , 3. https://doi.org/10.3389/fpubh.2019.00003 Powell, B.J., Mettert, K.D., Dorsey, C.N., Weiner, B.J., Stanick, C.F., Lengnick-Hall, R., Ehrhart, M.G., Aarons, G.A., Barwick, M.A., Damschroder, L.J. and Lewis, C.C. (2021) Measures of organizational culture, organizational climate, and implementation climate in behavioral health: a systematic review. Implementation Research and Practice , 2 , 26334895211018862. https://doi.org/10.1177/26334895211018862 Pronovost, P., Needham, D., Berenholtz, S. et al. (2006) An intervention to decrease catheter-related bloodstream infections in the ICU. New England Journal of Medicine , 355 (26), 2725–2732. Reardon, C.M., Damschroder, L.J., Ashcraft, L.E., Kerins, C., Bachrach, R.L., Nevedal, A.L., Domlyn, A.M., Dodge, J., Chinman, M. and Rogal, S. (2025) The Consolidated Framework for Implementation Research (CFIR) User Guide: a five-step guide for conducting implementation research using the framework. Implementation Science , 20 (1), 39. https://doi.org/10.1186/s13012-025-01450-7 Schriger, S.H., Knowles, M., Daglieri, T., Kangovi, S. and Beidas, R.S. (2024) Barriers and facilitators to implementing an evidence-based community health worker model. JAMA Health Forum , 5 (3), e240034. https://doi.org/10.1001/jamahealthforum.2024.0034 von Thiele Schwarz, U., Aarons, G.A. and Hasson, H. (2019) Reconciling fidelity and adaptation in evidence-based practice implementation. BMC Health Services Research , 19 , 868. https://doi.org/10.1186/s12913-019-4668-y Williams, N.J., Ehrhart, M.G., Aarons, G.A., Esp, S., Sklar, M., Carandang, K., Vega, N.R., Brookman-Frazee, L. and Marcus, S.C. (2024) Improving measurement-based care implementation in youth mental health through organizational leadership and climate: a mechanistic analysis within a randomized trial. Implementation Science , 19 (1), 29. https://doi.org/10.1186/s13012-024-01356-w World Health Organization (2017) Evidence of hand hygiene as the building block for infection prevention and control . Geneva: WHO Press. Zheng, K., Ratwani, R.M. and Adler-Milstein, J. (2020) Studying workflow and workarounds in EHR-supported work. Annals of Internal Medicine , 172 (11 Suppl), S116–S122. https://doi.org/10.7326/M19-0871 Table Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.png Table 1. Conceptual Framework Components and Supporting Literature SupplementaryMaterial1DocumentClassificationandAnalyticMappingFramework.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8768667","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":610834556,"identity":"6735e39d-8d40-4bba-ace4-fbeef2e8099d","order_by":0,"name":"CHINEDU Onyekwelu-Udoka","email":"data:image/png;base64,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","orcid":"","institution":"Morgan State University","correspondingAuthor":true,"prefix":"","firstName":"CHINEDU","middleName":"","lastName":"Onyekwelu-Udoka","suffix":""}],"badges":[],"createdAt":"2026-02-02 20:09:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8768667/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8768667/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105476654,"identity":"f602b83b-9256-409f-a617-89add880cbf8","added_by":"auto","created_at":"2026-03-26 12:59:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":86513,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual Process Model of EBP Implementation in Community Clinics\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8768667/v1/627dc9a1697a364fc88e7e76.png"},{"id":106960947,"identity":"7e291e7d-532b-47fd-a30f-451cbb5a2a1a","added_by":"auto","created_at":"2026-04-15 09:23:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":860576,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8768667/v1/73b0cc33-d7d1-4ffc-aa51-6b55a3ce2144.pdf"},{"id":105476655,"identity":"75794a58-66bf-4480-98de-417801925cca","added_by":"auto","created_at":"2026-03-26 12:59:18","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":688980,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Conceptual Framework Components and Supporting Literature\u003c/p\u003e","description":"","filename":"Table1.png","url":"https://assets-eu.researchsquare.com/files/rs-8768667/v1/f29ca8f5455b6d36c280fc1d.png"},{"id":105476656,"identity":"734f4fba-6f94-4375-8e50-55f84bf7ffc3","added_by":"auto","created_at":"2026-03-26 12:59:18","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":117880,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial1DocumentClassificationandAnalyticMappingFramework.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8768667/v1/454859f874c4871376fa9b6b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Implementing Evidence-Based Practice in Community Clinics: A Process Evaluation of Barriers, Adaptation, and Workflow Integration in the United States","fulltext":[{"header":"Background gap","content":"\u003cp\u003eEvidence-based practices (EBPs) are referred to as the bedrock of clinical practices and they are vital for the functional and improvement of patient care. Evidence-based practices (EBPs) are problem solving-approach practices in the clinical setting that incorporates the best available research evidence which could include the best practice or expertise while looking out for the patient's values and preferences. EBP is broadly recognized as being foundational and fundamental to the improvement of health outcomes, standard and consistent care delivery, and bridging the gap between research and practice in the clinics or medical setting in communities across the United States (Alsadaan \u0026amp; Ramadan, 2025; Beňov\u0026aacute; et al., 2023). Over the years, EBPs have been observed with the potential to mitigate disparities, enhance management of severe illnesses and support preventive interventions (Beňov\u0026aacute; et al., 2023). However, regardless of the potential of EBPs and its widespread policy support, translating it into a routine practice present a continuous challenge: interventions falter when it is administered in the community primary care settings usually due to the complexity that exists in the real-world where there are structural restrictions, interruptions of workflows, and limitations of technology (Mathieson et al., 2018; Jaramillo et al., 2023; Durojaiye et al., 2024; Olakotan et al., 2025). The implication of this is that it creates a barrier for complete adoption. For instance, the nature by which every medical center or clinic runs, they are often too busy to restructure or reorganise the current setting to adopt the EBPs. When services are rearranged or spread thin across several locations, time and attention of personnel are pulled in multiple directions creating a lack of focus on implementation of the proposed practices (Mathieson, et al., 2018). More so, factors such as frequent changes in leadership, inadequate training for personnel and introduction to newer technologies or tech support (e.g., Electronic Health Records, etc.) --cause too many disruptions such as numerous alerts, workflow redundancy, and increment in paperwork\u0026ndash; makes adoption even more difficult (McCurdie et al., 2017; Pinevich et al., 2021). As a result, clinicians are bound to spend more time doing documentation than providing care. These challenges show up in several kinds of conditions and services reflecting a broader systemic problem that affect the clinical practice (Durojaiye et al., 2024).\u003c/p\u003e \u003cp\u003eAccording to Zhang et al., (2025), implementation science focuses on the fact that research evidence must go beyond existence to real practice and usage in clinics. Guidelines do automatically translate into practice --routine care, rather evidence has to go through the everyday clinical channel such as workflows, schedules, tech support and different clinical roles. Hence, the need for adoption and adaptation of the EBPs to fit into community primary health care settings. Several existing studies have documented numerous hindrances that complicates the usage of EBPs in everyday routine care such as improper alignment on EHRs, documentation process that requires proper audit, limitation in staffing capacity and lack of time to administer care to patients (Olakotan et al., 2025; Pinevich et al., 2021; M\u0026ouml;rike et al., 2024). Although quite a number of theses research work have focused on the identification of barriers they, however, fail or rarely examine the active response of clinicians to these practices. Comparatively, there's little to no empirical information to how clinicians navigate routines, adapt to informal workarounds or integrate multiple clinical workflows. Hence, translating policy directives and organizational expectations into daily care routine is insufficiently understood (von Thiele Schwarz et al., 2019; Wooldridge et al., 2017).\u003c/p\u003e \u003cp\u003eExisting research has highlighted that there are tensions between adjusting the EBP protocols and practices into real-world clinical scenarios which often leads clinicians to modify procedures to ensure a patient-centered care (Owczarzak et al., 2016; Lennox et al., 2018). However, less research has shown the adaptation of these practices in the real-world especially in under-resourced community care centers leaving significant gaps in operationalization, barriers and workflow integration (Jaramillo et al., 2023; Damschroder et al., 2022). Therefore, to guide the development of EBPs in a way that brings balance and practical applicability to implementation science and health services research without diminishing the quality of care, this gap must be addressed. This study responds to these gaps by conducting a multi-process evaluation of EBPs in community clinics in the United States examining the structural, organizational and workflow barriers alongside formal and informal adaptations with the aim of generating evidence-based recommendations for an implementation design that is responsive.\u003c/p\u003e"},{"header":"Theoretical and Conceptual Framework","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eProcess Evaluation as an Explanatory Lens\u003c/h2\u003e \u003cp\u003eThis study utilizes an implementation science approach guided by a process evaluation framework to explore the operationalization and enactment of EBPs within the community clinic settings in the United States. In situations where only outcomes from interventions are measured, this framework examines the incorporation of EBPs in clinical work routines, organizational highlights, structural workflows, possible barriers and practice adaptations occurrence (Moore et al., 2015; Damschroder et al., 2022). The implementation of EBPs comes with different forms of complexities, hence, they have to be shaped, interpreted and enacted to fit the existing original workflows, technologies and clinical practices already in existence (Cunningham \u0026amp; Card, 2014; Wiltsey Stirman et al., 2019). Although process evaluation mostly documents how interventions match the implementation, however, they have been criticized for overlooking the dynamic nature of how organizational routine reshapes the enactment of interventions (Moore et al., 2015; Howard-Grenville et al., 2016). In numerous applied health services studies, process evaluation is rather portrayed as descriptive adjunct to outcome reporting than making them out to be mechanisms that critically analyze how workflow design and institutional logic affect implementation success or failure (Damschroder et al., 2022; Nilsen, 2020). This study intentionally positions process evaluation as an explanatory lens as opposed to a supplementary assessment tool. By foregrounding workflow integration, it moves beyond identifying determinants to examining how those determinants are operationalized within the temporal, technological, and professional constraints of community clinics. Moreover, implementation science has shown that adoption is not a one-time thing or something that should be forced on clinicians but an evolving process and negotiations that fits into local and ground-level clinical reality (Lobb \u0026amp; Colditz, 2013; Miller et al., 2020). Hence, this framework ensures that stages are treated as recursive and interdependent processes evolving through feedback loops and professional adaptation.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIntegration of Determinant Frameworks: Conceptual Use of CFIR\u003c/h3\u003e\n\u003cp\u003eThis framework builds upon determinant-focused implementation research, particularly the Consolidated Framework for Implementation Research (CFIR) highlighting organizational factors such as the compatibility of workflow, readiness to change and climate implementation, and how they influence the adoption of the EBPs. This study employs CIFR as less of an analytical and more as a conceptual guide to help with understanding the structural and functional workflows of an organization and how it influences processes of implementation without the formal application of the framework (Damschroder et al., 2022). CFIR is the best tool for a comprehensive overview but not an \u0026ldquo;how-to\u0026rdquo; guide because its broad nature makes it difficult to explain the specific, dynamic causes of implementation success or failure without pairing it with other theories that focus on the process of change (Nilsen, 2020; Reardon et al., 2025). The CFIR domains were juxtaposed with observable workflow enactments rather than abstract readiness scores. This analytical approach takes the attention from static organisational characteristics to dynamic interactions between structural conditions and clinician behaviour. More so, determinant frameworks alone may undermine the role of technology in influencing implementation trajectories (May et al., 2016; McCurdie et al., 2017). For instance, electronic heath records (EHR) are not neural infrastructures; they actively configure task sequencing, documentation priorities, and cognitive workload (Pinevich et al., 2021). By integrating system-level approach, this framework recognises that technological artefacts participate in the implementation process by redistributing attention, structuring decision pathways, and constraining temporal flexibility. In this sense, workflow friction is not merely a human resource issue but an emergent property of system design.\u003c/p\u003e\n\u003ch3\u003eSociotechnical and Workflow Perspectives\u003c/h3\u003e\n\u003cp\u003eClinical settings emerge from interactions among clinicians, technologies, tasks, and organisational rules. Hence, this framework integrates sociotechnical and workflow perspectives (Carayon et al., 2020; McCurdie et al., 2017). Research has shown that EBPs are usually known to require more documentation, screening, and frequent coordination which could impede strict time-appointments, rigid EHRs and increase cognitive demands causing workflow friction (Pinevich et al., 2021; Olakotan et al., 2025).\u003c/p\u003e\n\u003ch3\u003eFidelity, Adaptation, and Professional Agency\u003c/h3\u003e\n\u003cp\u003eThis framework adopts unconventional insights on fidelity and adaptation by paying more attention to the clinicians on the frontline who naturally modify their EBPs to fit the needs of patients, constraints on employment and the local norms. Moreover, there has been a continuous and persistent debate between fidelity and adaptation in implementation science, mostly seen as a trade-off between internal validity and contextual fit (Wiltsey Stirman et al., 2019; Chambers et al., 2013). However, recent research opined that the term fidelity needs to be redefined as a core component as opposed to a rigid procedural adherence (von Thiele Schwarz et al., 2019). Also, if a strict fidelity is place in community clinic setting where there are high patient complexity and scarcity of resource it can undermine sustainability and disregard feasibility of workflow. As stated by (Chambers et al., 2013 and May et al., 2016), this study approaches adaptation as a pragmatic expression of professional expertise within structural constraints.\u003c/p\u003e\n\u003ch3\u003eMulti-Level Implementation Dynamics\u003c/h3\u003e\n\u003cp\u003eImplementation can only be understood across interconnected events rather than a single phase with each event influencing the interpretation and enactment of EBPs in routine practice. These interrelated stages are carefully illustrated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e alongside their corresponding methodological empirical examples with the process visually documented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Previous studies have shown that past policy and payer mandates have positioned EBPs as obligations that drive compliance, in turn, influencing organizational priorities, allocation of resources, and structural accountability within the medical settings. However, at the highest level, the expectations that surround the adoption of EBP are shaped by these mandates \u0026ndash;Medicaid contracts, standardized quality reporting and regulatory guidance inclusive (Crable et al., 2020; Durojaiye et al., 2024). Policy and payer mandates encourages EBP adoption by improving organizational accountability system in ways that allow measurable outputs over holistic or relational processes of care (Crable et al., 2022; Hu et al., 2025). Constant auditing of Medicaid contracts and strict regulatory monitoring system gives room for performative logics shifting EBPs from clinically-oriented practice to compliance-oriented documentation (Posch \u0026amp; Speckbacher, 2017; Durojaiye et al., 2024). This distinction is analytically important to explain why implementation behaviour may reflect regulatory visibility rather than therapeutic optimization. Contextually, adherence to documentation practices is what becomes routinized and not intervention itself. More so, in a compliance-driven environments escalates vertical accountability and reduces horizontal accountability among clinicians (Nilsen et al., 2020; May et al., 2016). This revaluation of accountability makes certain that EBPs are prioritized during time-constrained encounters regulating professional autonomy. The forms this translation takes are mostly benchmarks performances, expectation on documentation, processing training of clinicians and specific protocols for clinics.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eOrganisational Translation and Leadership Mediation\u003c/h2\u003e \u003cp\u003eOn the other hand, the approach from a leadership perspective influenced by availability of resources, perceived regulatory risks, and auditing pressure, all affects the prioritization and positioning of EBPs within the community primary care on a daily basis (Mathieson et al., 2018; Damschroder et al., 2022). When the expectation of EBP has been incorporated into the daily routine, implementation gears into the workflow state. This implies that requirements will be embedded into the EHR systems, responsibilities allocated across clinical roles and designated tasks as clinicians encounter more patients. Studies have shown that from a human perspective challenges often arise when EBPs are not effectively incorporated creating some form of misalignment within the clinical care routine especially if corresponding adjustments were not made elsewhere. These misalignments often create friction in workflow and informal workflows causing clinicians to juggle more work than expected (McCurdie et al., 2017; Pinevich et al., 2021).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eWorkflow Integration and Structural Misalignment\u003c/h3\u003e\n\u003cp\u003eWorkflow misalignment is a kind of socio-organizational strain that builds up when the intervention requirements place more demand on the existing capacity than an organization can handle (Carayon et al., 2020; Zheng et al., 2020). This framework views this tension as indicators of a structural misalignment (in policy design and clinical operations) rather than standalone constraints. For instance, adding a screening protocol without appropriate staff rotation and time balancing can snowball into cognitive load (Pinevich et al., 2021). In the long run, these micro-level frictions accumulate causing clinicians to become indifferent towards EBPs. Significantly, such misalignments highlight the limits of linear implementation models that assume proportional resource adaptation following policy change (Damschroder et al., 2022; Nilsen, 2015). Practically, successful implementation of EBPs often depends on frontline clinicians compensating for delayed or partial resource augmentation. Clinicians sometimes use informal coordination, labour redistribution and temporarily deferring task to accommodate both planned resources and actual availability.\u003c/p\u003e \u003cp\u003eDrawing from past research especially in the area of safety-net and community settings, interventions supported by EHRs and the efforts to improve quality in care has often caused different types of disruptions ranging from existing workflow interruptions, less capacity placing a heavy demand beyond what's available to conflict in clinician's personal judgement. Since EBPs are mostly carried out by the frontline clinicians constantly facing tight schedules, juggling multiple work calls, and various levels of care complexity there's expected to be an emergence of friction in the framework (Zheng et al., 2020; Olakotan et al., 2025). In the emergence of these challenges, clinicians mostly respond by adjusting the EBPs usage in practice. For instance, instead of taking on multiple tasks all at once, they redistribute it to other competent clinicians or take it on another time. Order of activities are changed to suit the current situations, documentation or filing of reports become limited and electronic prompts are bypassed.\u003c/p\u003e\n\u003ch3\u003eStructural and Behavioural Adaptations\u003c/h3\u003e\n\u003cp\u003eThis framework provides a clear distinction between structural and behavioural adaptations. Structural adaptations refer to organisational-level modifications like role reallocation or configuration changes of EHR systems (Chambers et al., 2013). Conversely, behavioural adaptations refer to the clinical-level modification which involves moment-to-moment adjustments in sequencing, emphasis, or documentation practice. Understanding the difference between these two is analytically important as it determines how each adaptation is absolved, either institutionally or left to individual discretion (Lennox et al., 2018). More so, formalization of behavioural adaptations ensures that everyone has access to the best practices and reduces the chances of anyone left behind across all sites. Besides, under constrained conditions, informal workarounds can serve as the stabilising element that preserves core therapeutic elements (McCurdie et al., 2017; May et al., 2020). Yet, normalizing workaround raises the question about hidden labour and professional burden. Allowing EBPs to rely on compensatory effort put its sustainability at the mercy of the resilience of clinicians rather than system design. Hence, this framework treats workarounds as indicative markers that require organization reflection rather than endpoints. Eventually, this feedback can create revisions to protocols, strengthen current approaches, prompt normalization of informal workarounds which could lead to more sustained and suitable patterns of modified EBPs (Chambers et al., 2013; Lennox et al., 2018). Since other approaches have taken a linear approach towards a perfect fidelity for EBPs, this framework enables a more dynamic and systematic approach that explores barriers to implementation and creates adaptive responses to challenges faced when integrating EBPs into everyday care.\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eThis study employed the process evaluation design model to investigate the working system of the EBPs and its implementation in United States community clinic settings focusing on barrier identification, adaptations and workflow integration challenges. Process evaluation is applicable for examining real-world context with complexity giving room for close analysis of how implementation activities are done and how they might evolve in the near future (Moore et al., 2015; Damschroder et al., 2022). This evaluation did not consider the effectiveness of clinical practice or outcomes of patients; however, it focused on the protocols by which EBP was implemented, following how requirements at organizational level were interpreted, translated into clinical workflows and adapted into routine care. This focus is closely related to the study of policy-driven EBPs in resource-limited healthcare settings (Cunningham \u0026amp; Card, 2014; Lennox et al., 2018). The study used no qualitative data such as interview, surveys and observation methods, but adopted multiple sites, document-based design, and relied on existing organizational policy and system records. The evidence-based practice (EBP) used in the evaluation is a mandated clinical approach embedded within the daily routine care in the US community clinics alongside the required quality reporting for Medicaid. This practice must be done or overseen by a clinician using the standardized screening tool during patient consultation and records must be done in a structured environment within the EHRs, depending on the workflow of the clinic. A successful implementation of the screening is classed by the adherence to policy guidance, consistency in administration, EHR documentation accuracy, and correct data generation suitable for audit and reporting. EBPs of this magnitude are mostly documented for implementation research as the comprise clinical, administrative and technological domains which is good for literature and show the technicality and additional workflow it demands if it needs to be integrated into daily routine care (Zheng et al., 2020; Olakotan et al., 2025)\u003c/p\u003e\u003cp\u003eThe evaluation was constructed by drawing on studies on US community clinics —federal-based health centers and community-based clinics inclusive— all operating within the reimbursement arrangement of Medicaid. Data collection sources were intentionally chosen to show implementation practices in relation to expectations on policy-level, organisational decision-making and execution of workflow by the frontline clinicians. Based on established guidelines for process evaluation, this study relied mostly on multiple data sources to aid the triangulation and improve the interpretation of the implementation practice (Moore et al., 2015). These materials comprise of the policy and payer documents —contracts provision by Medicaid, local protocols, quality reports, implementation manuals, clinic-level organisational artefacts, training resources, diagrams of workflows, logic specifications alert, reporting system configurations, dashboard qualities and compliance feedback summaries— including EHRs related documents. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e outlines these data sources, the actors involved, the major touchpoints workflows, and their contributions to the analytic framework.\u003c/p\u003e\u003cp\u003eImplementation science informed the thematic approach used in the data analysis with the aim of identifying patterns that are recurrent in relation to implementation barriers, adaptive practice and workflow integration. All data sources were iteratively analyzed by tracing how the EBP requirements were interpreted at the policy level and equally translated into organizational protocols and routine care. Instead of using a deductive approach in a determinant framework, the analysis was guided by sensitizing concepts from implementation science literature that has been established. These consisted of the readiness of the organization, climate implementation, how the EBP requirements aligns with the existing workflows, sociotechnical interactions involving EHRs and a trade-off between fidelity and adaptation. These concepts align with the CFIR domains in terms of inner setting and process implementations; however, they were employed as conceptual guides and not a formal coding structure to avoid exaggerating the methodological claims (Damschroder et al., 2022). More so, a rather analytical approach was placed on identifying where enacted workflows diverged, types of adaptations could maintain feasibility and the feedback approach can shape the progressive implementation. Findings were integrated from different research literature to highlight shared implementation dynamics rather than a generic comparative analysis.\u003c/p\u003e\u003cp\u003eTo coherently strengthen this study analytically, the conceptual model was developed to illustrate how the EBP will progress from an extrinsic policy mandate to the frontline execution with possible future adaptations. The model was sourced directly from already established and grounded implementation and workflow literature (Chambers et al., 2013; McCurdie et al., 2017). It lays out how the policy and payer mandates are implemented by clinic leaders and translated into the workflow of the organization, EHR configurations and enacted into routine care, paying a close attention to the friction that emerges from implementation in order to process feedback as it influences ongoing delivery. A presentation of the model is shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and is mentioned in the Findings section to establish the empirical observations within a larger implementation process. Quite a number of strategies were employed to improve analytical credibility and rigour. Using multiple literature supports the triangulation process across policy, organizational and workflow levels with analytical claims grounded in documented artefacts and established empirical literature rather than web reports or self-reported perceptions. Interpretations were intentionally restricted to reasonably supported data available. This approach aligns with the process evaluation method (Moore et al., 2015; Clement et al., 2018). This study relied mostly on existing documents and system artefacts. No human participation was involved, neither was any identifiable patient information collected. Hence, an approval from an institutional board was not needed. All materials used were handled with confidential standards.\u003c/p\u003e"},{"header":"Findings","content":"\u003ch2\u003eBarriers\u003c/h2\u003e\u003cp\u003eHaving reviewed several policy documents, organizational materials, and EHR-related artefacts, several implementation barriers have been identified across organizational, structural and clinical-workflow levels. Across this level, these barriers largely reflect the misalignment between the requirement of EBP externally and its practicality in the real-world when delivering care in community clinic settings. At the structural level, a key restriction shaping implementation are audit requirements and Medicaid-linked reporting. Policy and payer mandates emphasize on completeness of documentation, standardization, reportability of data with less attention to how screening activities could be integrated into existing workflows. More so, the EHR configuration materials also reinforced this result by embedding screening tools as mandatory fields or automated alerts with little flexibility to accommodate visit complexity, staffing variability, or competing clinical priorities. Prior research has shown consistency with this study that rigid digital systems cause friction when EBPs were integrated into existing systems without accompanying workflow redesign (Zheng et al., 2020; Olakotan et al., 2025). Across the artefacts examined, the challenges faced were not because of a singular operational glitch but a series of patterned events of systemic design that was prioritize. This mismatch indicates that the attention of the organization is geared towards measurability rather than what is sustainable in practice (Powell et al., 2021; Williams et al., 2024). Significantly, the EHR’s logic specifications forces clinicians to follow a non-flexible and hard-stopped mandatory field that focus more on data collection instead of their ability to manage patient care normally. This finding shows that technological rigidity doesn’t just create technical limitations but affects structural reinforcement.\u003c/p\u003e\u003cp\u003eAt the organizational level, the gaps between formal workflows as intended and how screening should be done in clinical practice was revealed from assessing clinic protocols and materials used for training. Although official documentation showed screening processes were linear and standardized, other materials such as audit clarification showed that there are ongoing uncertainties around task ownership and effective timing. This pattern indicates that a broader scope of implementation will reveal unclear responsibility and competing demands within the organisation which can compromise readiness (Weiner et al., 2017; Jaramillo et al., 2023). Furthermore, workflow artefacts and documentation of EHR showed that clinicians at the forefront of the job are expected to complete even more documentation tasks with their tight schedule. Common recurring issues stated by clinicians were: burden of documentation, high alert frequency, task sequencing conflicts, especially in areas where screening requires registration, triage and clinical assessment activities. These findings corroborate the issue of cognitive load and pressure on clinicians when dealing care for outpatients (Pinevich et al., 2021; McCurdie et al., 2017).\u003c/p\u003e\u003ch2\u003eAdaptations\u003c/h2\u003e\u003cp\u003eClinics have responded to the implementation barriers by trying to make formal and informal adaptations to make EBP workable by balancing its fidelity and flexibility requirements with daily routine care. The formal adaptations require changes in workflows, allocation of tasks, and time documentation (to avoid time-constraints situations) which reflects iterative adjustments with the aim of maintaining flow of patient care as opposed to a rigid system (von Thiele Schwarz et al., 2019; Chambers et al., 2013). Technology in healthcare is often designed with formal adaptations to force compliance with data rules, which unfortunately strips doctors of their ability to prioritize patient needs (Chambers et al., 2013). However, clinics fight back against this rigidity by strategically moving these mandatory tasks to other staff members, effectively recalibrating internal systems to maintain operational continuity. Conversely, informal adaptations are like unofficial micro-level compensatory practices clinicians use to manage cognitive load under temporal constraints. Some of these practices include delaying documentation, selective alert engagement and task bundling (McCurdie et al., 2017). Although these adaptations help preserve workflow, it also results in inconsistent medical records (Mörike et al., 2024; Zheng et al., 2020). Importantly, these findings reinforce that adaptations are not fatal, they reflect a rather pragmatic approach of solving the problem at hand. Hence, this indicates that adaptation is normal and it is a necessary feature for real-world implementation of EBP enabling clinics to maintain routine care while navigating these constraints (Owczarzak et al., 2016; Lennox et al., 2018).\u003c/p\u003e\u003ch2\u003eWorkflow integration\u003c/h2\u003e\u003cp\u003eAnalyzing the workflow documents and system materials it is evident that the community clinic settings struggle to integrate the EBP with ease into everyday routine care. As shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, when patients come to visit for care, clinicians find it difficult to juggle attending to the patients and attend to EHR-generated tasks. More so, it seems like the EBP activities—EHR logic, task allocation, and staff training— were adding more responsibilities to the already available work instead of streamlining other tasks —this has increased interruptions and created more conflict in the order in which the work needs to be completed. Additionally, the workflow challenges were augmented by the feedback mechanism that seemed to prioritize audit results over learning the major workflow design. Audit reports, benchmarks, metrics and performance dashboards are more focused on documentation processes rather than the actual work, hence, this limited workflow structure affecting the implementation practicality. Some research has shown that unintentionally prioritizing a performance measurement system can breed inefficient practice as compliance has overridden usability (Lennox et al., 2018; Wooldridge et al., 2017).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eReframing Implementation Beyond Clinician Compliance\u003c/h2\u003e \u003cp\u003eThese findings have suggested that implementation outcomes have been influenced more by the system design than the willingness of clinicians or EBP acceptance. Barriers were caused by policy requirements, organizational procedures and digital systems that have no interconnection with everyday routine care workflow creating misalignment. These results show that EBPs need to be designed with the intention of workflow fit, flexible EHR configurations, and feedback systems that promote learning rather than focus on compliance alone. Also, any implementation effort that overlooks constraints created by structure and technology while focusing on only staff training and motivation will most likely not support long-term integration. These implications support the claims that implementation science needs to go farther from fidelity-centric models and adapt towards workflow integration approaches that can work in the real-world of community clinic care (Powell et al., 2021; Lewis et al., 2018).\u003c/p\u003e \u003cp\u003eThis study argues that implementation science focuses excessively on the attitude of clinical professional. This is more like a distraction. In reality, the system-level design forces clinician to act a certain way whether they are motivated or not. This is known as \u0026ldquo;determinative influence\u0026rdquo; and it implies that the structural configuration of a digital infrastructure predetermines how care will occur. For instance, if a system is designed for auditing or billing, the clinician is not an independent decision-maker rather a user in an automated process (Carayon et al., 2015; McCurdie et al., 2017). Researchers have argued that implementation success shouldn\u0026rsquo;t be about individual grit or motivation alone but an emergent of interactions between organizational systems and professional practice. By empirically illustrating how EHR configurations and audit mechanisms shape workflow density, the study shifts explanatory attention from behavioural compliance to infrastructural alignment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003ePolicy Mandates and the Compliance\u0026mdash;Care Tension\u003c/h2\u003e \u003cp\u003eThe findings show a major traceability trap that highlights a structural tension. Medicaid-linked EBPs mandates conflates documentation of a task with implementation success. The implication of this is that it turns EHR into a repeatability tool instead of a healing tool; success is no longer measured by patient recovery but by performance dashboards (Williams et al., 2020; Durojaiye et al., 2024). This compliance-care tension creates broader implications for policy design. Instead of making transformative care improvements, these mandates pile on more work for clinicians. This suggests that policy designers are possibly \u0026ldquo;clinically illiterate\u0026rdquo; as they create rules without understanding the temporal and staffing realities. More so, by ignoring workflow frameworks, system compliance is reached but operational sustainability is compromised. This simply implies that today can produce a perfect audit report but the next day can bring a clinic full of burn-out staff and a broken healthcare system (Lennox et al., 2018). Future policy reforms may therefore benefit from embedding workflow simulation or pilot integration assessments prior to widespread mandate enforcement.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eAdaptation as Organisational Intelligence\u003c/h2\u003e \u003cp\u003eOne of the key contributions of this study is the empirical differentiation between structural and behavioural adaptations. Informal workarounds by clinicians shouldn\u0026rsquo;t be seen as fidelity erosion, in fact it is a form of intelligent behavioural adaptation (Wiltsey Stirman et al., 2019). However, this is a trap of individual resilience. Relying on informal workarounds for clinics to stay afloat means they\u0026rsquo;re gambling on the clinician\u0026rsquo;s stamina. If the system only works when medical professionals are willing to multitask and work through their rest time, then, it is no longer a strategy but a systemic exploitation (Chambers et al., 2013). However, the sustainability of adaptation depends on its institutional absorption. Where behavioural adjustments remain informal and unacknowledged, implementation stability becomes contingent on individual resilience. Over the course of time, this may exacerbate professional strain and variability across sites. Consequently, implementation strategies should incorporate structured mechanisms for capturing and formalising effective frontline adaptations, thereby converting experiential adjustments into organisational learning (von Thiele Schwarz et al., 2019).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eImplications for Implementation Science Theory\u003c/h2\u003e \u003cp\u003eTheoretically, this study indicates that the CFIR is good for pointing out a list of problems, however, it is a static model. Mixing policies, tech and workflow could be unpredictable and chaotic creating invisible reactions. This is like using the map to predict traffic movement; you can see the road but you can\u0026rsquo;t see movement (Damschroder et al., 2022; Nilsen, 2020). The best way to understand how a new program works is to check how it fits into the daily flow of work and systems surrounding it. This relational orientation highlights that successful implementation is not just an event, but a result of the interactions between people, tools, and their environment. Such an approach is particularly relevant in community clinic settings characterised by constrained resources and dense regulatory oversight.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and Reflexive Considerations\u003c/h2\u003e \u003cp\u003eThere are several limitations in this study that needs to be carefully considered. The first thing to note is that the study relied heavily on document-based and artefactual analysis without direct observational or interview data. Although this approach lessens retrospective bias and strengthen structural inference, it restricts insights into experiential workflow enactment in real-time. The implication of this is that informal practices will most likely be underrepresented due to lack of formal documentation (Lennox et al., 2018). Furthermore, despite the inclusion of numerous clinic sites, the analysis is exclusive to mostly the U.S. Medicaid reimbursement context implying that these findings might not be directly transferable to other healthcare system outside the US or private healthcare system. Hence, contextual specificity should guide interpretation as opposed to universal extrapolation. Additionally, in terms of clinical effectiveness, the absence of patient outcome data affects conclusions. This study deliberately focused on implementation processes only; however, future research integrating workflow analysis with outcome evaluation would provide a more comprehensive understanding of policy-driven EBP sustainability. Overall, while feedback and documentation of workflow provide indirect insight into adaptation, observational validation could possibly improve casual inference in future studies. More so, artefactual data reflect formalised organisational intent but may fail to capture the nuance of workarounds.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eConcluding Reflections\u003c/h2\u003e \u003cp\u003eConclusively, this discussion pinpoints that successful EBP implementation in community clinics is more a function of systemic coherence and less a question of clinician willingness. When policy mandates, digital infrastructures, and workflow design operate in alignment, it stabilizes implementation. When misaligned, adaptation emerges as a work burden. Recognising this dynamic reframes implementation from a compliance problem to a systems engineering challenge. Consequently, advancing implementation science in policy-driven environments requires integrating governance analysis, sociotechnical design, and workflow modelling into future research agendas. Only through such integrative approaches can EBPs transition from mandated requirements to sustainably embedded components of everyday care.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not involve human participants, patient data, or identifiable personal information. The research was based exclusively on publicly available literature and secondary documentary sources; therefore, formal ethical approval was not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was not applicable, as the study did not involve human subjects or the collection of primary data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study adopted the process evaluation design and critical interpretive synthesis drawing exclusively on publicly available peer-reviewed literature, published implementation frameworks, and secondary documentary sources. No primary human participant data, patient-level datasets, or confidential institutional records were collected or analysed.\u003c/p\u003e\n\u003cp\u003eTo support transparency and reproducibility of the analytic process, the following materials have been made available as Supplementary Files:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eA structured list of document categories reviewed;\u003c/li\u003e\n \u003cli\u003eThe coding framework and analytic logic structure used for thematic synthesis;\u003c/li\u003e\n \u003cli\u003eA framework mapping matrix linking identified artefacts to relevant implementation science constructs (including CFIR domains and sustainability constructs);\u003c/li\u003e\n \u003cli\u003eAn analytic decision trail documenting theme development and refinement.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAll cited literature is publicly accessible through their respective publishers. No proprietary datasets were used; because this study did not generate or analyse raw quantitative datasets, there are no numerical datasets or statistical scripts to deposit. The supplementary materials provided contain all documentation necessary for editors and referees to scrutinise the methodological approach and analytic decisions underlying the findings. Supplementary materials are available alongside this manuscript submission.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eO.U.C.F. conceived the study, conducted the research, wrote the manuscript, and prepared all figures. The author reviewed and approved the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlsadaan, N. and Ramadan, O.M.E. 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(2020) Studying workflow and workarounds in EHR-supported work. \u003cem\u003eAnnals of Internal Medicine\u003c/em\u003e, \u003cstrong\u003e172\u003c/strong\u003e(11 Suppl), S116\u0026ndash;S122. https://doi.org/10.7326/M19-0871\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\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":"Clinical Social Work, Evidence-Based Practice, Implementation Science, Health Services Research, US Community Clinics, Electronic Health Records Systems","lastPublishedDoi":"10.21203/rs.3.rs-8768667/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8768667/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEvidence-based practices (EBPs) are problem solving-approach practices in the clinical setting that incorporates the best available research evidence which could include the best practice or expertise while looking out for the patient's values and preferences. They are mandated in the US community clinics based on federal policy and Medicaid contracting requirements. Although these mandates were created to level the playing field for both standardized quality care and implementation within routine care workflows, however, this has not been the case. Existing studies infer that EBP implementation failure is driven by the misalignment amongst organizational, technological and workflow not the clinician acceptance of usage.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study used the process evaluation techniques to assess the Implementation of Evidence-based Practice in Community Clinic in the United States community clinics with the aim of identifying major barriers, adaptation patterns, and workflow integration dynamics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA process evaluation was conducted on twenty-eight (28) literature using an analytic approach informed by implementation science. The EBP investigated was a standardized clinical screening tool needed to be regulated during routine care encounters with patients and documented in the structured electronic health record (EHR) system to meet the Medicaid quality reporting requirements. Data sources were empirical studies from peer-reviewed papers that contained federal and state policy documents, EHR documentation specifications, workflow artefacts, and implementation guidance relevant to community clinic operations. Data analysis was done through structured thematic synthesis and mapping workflow with the end goal of establishing implementation frameworks and how they can be translated into real-world experience.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFindings:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eImplementation barriers were mostly impeded by the lack of flexibility in the EHR system, the burden that comes from documentation, time pressure constraints and audit-driven compliance. Clinicians never resisted the use of EBPs, rather they engaged in informal adaptations such as shifting tasks, developing a workaround within the workflow, alteration of task sequencing, and documented later to make sure patient routine care continues. This resulted in partial fidelity, hidden compliance, and divergence between reported and enacted practice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis evaluation reveals that the implementation outcomes in community clinics are controlled mostly by the compatibility of workflow and the context of the clinical environment as opposed to the clinician's attitude towards EBPs. Hence, it is important to design EBPs and implementation approach that can work in the real-world clinical workflows to attain sustainability in the community clinic setting.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMSC Code: 00A06\u003c/strong\u003e\u003c/p\u003e","manuscriptTitle":"Implementing Evidence-Based Practice in Community Clinics: A Process Evaluation of Barriers, Adaptation, and Workflow Integration in the United States","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-26 12:58:52","doi":"10.21203/rs.3.rs-8768667/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":"9368f232-3ed1-446d-8fcc-d0d3153affd9","owner":[],"postedDate":"March 26th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":64993597,"name":"Scientific community and society/Business and industry"},{"id":64993598,"name":"Health sciences/Health care"},{"id":64993599,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-04-14T13:57:18+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-26 12:58:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8768667","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8768667","identity":"rs-8768667","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}