How Implementation Context Shapes Clinician Acceptance and Engagement with Guideline-Based Clinical Decision Support Systems in Primary Care: A Qualitative Study

Abstract

Background

Guideline-based clinical decision support (CDS) tools have become central to promoting evidence-based, high-quality primary care. Despite widespread implementation, clinician adoption and sustained use remain inconsistent. Existing research has typically examined technological usability or organizational implementation factors separately, providing limited understanding of how these influences interact in real-world primary care settings. This study examined how organizational implementation context and clinician technology acceptance jointly shape adoption and sustained use of guideline-based CDS tools in US primary care using an integrated Consolidated Framework for Implementation Research (CFIR) and Technology Acceptance Model (TAM) perspective.

Methods

A qualitative study using reflexive thematic analysis was conducted with 13 US primary care clinicians, including physicians, nurse practitioners, physician assistants, and pharmacists with prescribing authority. Participants were purposively recruited from diverse ambulatory settings. Semi-structured interviews explored experiences with CDS usability, workflow integration, organizational support, trust, cognitive burden, and implementation processes. Data were analyzed iteratively using Braun and Clarke’s reflexive thematic analysis, informed by CFIR and TAM.

Results

Six interrelated themes emerged. Clinician acceptance and sustained use of CDS were shaped by (1) workflow integration, (2) organizational legitimacy and leadership support, (3) preservation of clinical judgment, particularly with emerging AI-enabled CDS, (4) social reinforcement and team-based implementation, (5) cognitive and resource constraints, and (6) clinician role, experience, and digital comfort. Across themes, acceptance was driven less by technological capability than by the interaction of workflow design, organizational context, implementation climate, trust, and clinician perceptions.

Conclusion

Guideline-based CDS implementation is fundamentally a sociotechnical process requiring alignment between technology, workflow, organizational context, and clinician acceptance. Integrating CFIR and TAM provides a comprehensive framework for understanding these interactions. The findings informed the TRUST framework, which offers practical implementation guidance emphasizing tailored workflow integration, reinforced organizational legitimacy, usability, social reinforcement, and transparent, trustworthy AI-supported CDS to support sustainable implementation in primary care.

Introduction

The rapid expansion of medical knowledge, increasing clinical complexity, and growing cognitive demands on clinicians have intensified the need for tools that support timely, evidence-based decision-making in healthcare.¹ Medical knowledge is estimated to double approximately every 60 days, while translation of evidence into routine practice may take many years.^2–4 These challenges are especially pronounced in primary care, where clinicians manage multimorbidity, preventive care, chronic disease, medication reconciliation, payer requirements, and broad diagnostic responsibilities within limited visit durations.^5–7 The resulting cognitive burden contributes to workflow strain, diagnostic uncertainty, and preventable harm in ambulatory care settings.^6,8–11 In this context, technologies that synthesize evidence and deliver patient-specific, evidence-based recommendations at the point of care are increasingly viewed as important supports for the delivery of safe, high-quality, and value-based care.¹²

Guideline-Based Clinical Decision Support in Primary Care

Clinical decision support systems, including guideline-based clinical decision support (CDS) tools embedded within electronic health records (EHRs), are important mechanisms for translating evidence into clinical practice.¹³ CDS tools can provide alerts, reminders, diagnostic support, treatment recommendations, risk-stratification tools, and evidence-based pathways to improve clinical decision-making and reduce unwarranted variation in care.¹⁴ Rather than replacing clinician judgment, CDS is intended to augment clinical reasoning and support evidence-informed care during real-time patient encounters.^15,16 Prior research has shown that CDS tools can improve adherence to clinical guidelines, medication safety, preventive care delivery, practice consistency, and clinical efficiency.^10,17,18

The importance of guideline-based CDS has grown alongside broader healthcare initiatives emphasizing evidence-based, value-driven care.¹⁹ Policy initiatives such as the Medicare Access and CHIP Reauthorization Act (MACRA) and the Quality Payment Program (QPP) have emphasized interoperability, quality reporting, and integration of evidence-based CDS within clinical workflows.^20,21 CDS tools have therefore been promoted not only as technologies for improving clinical decision-making, but also as mechanisms for strengthening prescribing safety, reducing unwarranted variation in care, supporting preventive care delivery, and streamlining increasingly complex clinical and administrative workflows.²²

Persistent Underutilization of Guideline-Based CDS

Despite substantial investment in health information technology, adoption and sustained use of guideline-based CDS remain inconsistent, particularly in primary care.^22–24 Although EHR adoption now exceeds 90% among US hospitals and physician practices, effective integration and routine use of CDS remain limited.²⁵ High alert-override rates, inconsistent engagement with CDS recommendations, and clinician bypassing of decision support interventions continue to be widely reported.²⁶ Medication-related CDS alerts, for example, have reported override rates ranging from approximately 49% to 96%, with some high-priority drug interaction alerts overridden more than 90% of the time.²⁷

Evidence suggests that clinician engagement improves when CDS tools are embedded within clinical workflows, reducing cognitive burden, and minimizing unnecessary clicks or disruptions.²⁸ Conversely, workflow disruption, alert fatigue, excessive navigation, poor usability, inconsistent training, limited leadership support, and weak integration into clinical routines are associated with reduced engagement and long-term abandonment.²⁹ These findings suggest that CDS availability alone does not ensure meaningful use. Rather, successful implementation depends on how CDS tools are experienced within the realities of frontline clinical work.³⁰

These challenges have become increasingly important as healthcare systems adopt AI-enabled and algorithm-driven CDS technologies.³¹ AI-supported CDS offers opportunities to improve efficiency, predictive analytics, personalization, and clinical decision-making, but it also raises concerns about explainability, transparency, trust, workflow fit, clinician autonomy, and governance.^32–34 Increasingly, clinicians are evaluating not only whether CDS technologies function technically, but also whether they are trustworthy, clinically relevant, cognitively supportive, and appropriately integrated into patient care.

Individual, Organizational, and Workflow Factors Shaping CDS Engagement

Prior research has identified barriers and facilitators to CDS implementation at individual, technological, organizational, and policy levels.²³ Clinicians are more likely to engage with CDS tools when they perceive them as clinically useful, trustworthy, efficient, and supportive of diagnostic accuracy and patient safety.^23,35,36 Trust in recommendations, confidence in the evidence base, familiarity with digital technologies, and perceptions of usability all influence clinician engagement.^23,35,36 Conversely, poorly designed interfaces, excessive alerts, cumbersome navigation, workflow interruptions, and increased cognitive burden contribute to frustration, alert fatigue, and reduced use.^23,35,36

However, CDS engagement is not determined solely by individual attitudes or technology characteristics.³⁷ Organizational and workflow conditions strongly influence whether CDS tools are experienced as useful, legitimate, burdensome, or clinically relevant in everyday practice.^37,38 Tools that require separate logins, operate outside routine EHR workflows, disrupt patient encounters, or increase the documentation burden are often underused even when they are technically sophisticated or evidence based.³⁷ Similarly, organizational culture, leadership endorsement, implementation climate, staffing support, protected training time, governance structures, and information technology resources shape the feasibility and sustainability of CDS implementation.^37,38 Practices that invest in workflow redesign, clinician feedback, local customization, and implementation planning report greater usability, clinician satisfaction, and sustained engagement with CDS tools.^13,37,39

These factors are highly interdependent.^23,30 Technically sophisticated CDS tools may still fail if clinicians perceive them as disruptive, poorly integrated, or unsupported by the organization. Likewise, well-designed implementation efforts may fall short if clinicians experience CDS as cognitively burdensome or clinically irrelevant.^13,30 Understanding these sociotechnical interactions is particularly important in primary care settings characterized by high patient volumes, competing priorities, interdisciplinary care delivery, reimbursement pressures, and resource constraints.^40,41

Limitations of Existing Research and Frameworks

Several theoretical and implementation science frameworks have been used to examine CDS adoption and implementation.²² Technology acceptance frameworks, including the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), focus on perceived usefulness, perceived ease of use, attitudes toward technology, and behavioral intention to use health information technologies.⁴² These frameworks provide valuable insight into clinicians’ cognitive and behavioral responses to CDS.⁴² However, they give comparatively less attention to how organizational structures, implementation climate, workflow realities, governance processes, leadership engagement, and broader contextual conditions shape those perceptions in practice.^42,43

Implementation science frameworks, including the Consolidated Framework for Implementation Research (CFIR), Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM), and Non-adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS), emphasize organizational context, workflow processes, leadership support, implementation climate, and system-level determinants of implementation success.^44–46 These frameworks provide important insight into implementation context but offer less explanation of how clinicians develop trust, perceptions of usability, and sustained engagement with CDS during patient care.^44–46 Similarly, classification frameworks such as the Human, Organization, and Technology-fit (HOT-Fit) framework, categorize barriers across human, organizational, and technological domains but provide less explanatory insight into how these factors interact dynamically to shape real-world adoption outcomes.^23,41

Much of the CDS implementation literature also derives from inpatient, specialty, or hospital-based settings that differ substantially from primary care in workflow structure, staffing models, patient continuity, resource availability, reimbursement pressures, and longitudinal care demands.^34,47 In addition, many studies examine technological, organizational, or behavioral factors in isolation, limiting understanding of how implementation context shapes clinician technology acceptance and sustained engagement in routine primary care.¹³ As healthcare organizations continue expanding digital, AI-supported, and guideline-driven CDS technologies, a more integrated understanding of these interacting influences is needed.⁴⁸

Rationale for Integrating CFIR and TAM

Guideline-based CDS implementation in primary care is a complex sociotechnical process shaped by interactions among technology design, workflow integration, organizational culture, clinician cognition, leadership support, and implementation strategy.^13,22 Understanding these interactions requires frameworks that examine both implementation conditions and clinician technology acceptance processes.^13,22

CFIR and TAM offer complementary perspectives for examining clinician acceptance and sustained engagement with CDS.^49–55 CFIR supports systematic examination of multilevel contextual determinants, including intervention characteristics, organizational culture, leadership engagement, implementation climate, external policies, and implementation processes.^53,54 TAM complements this perspective by examining perceived usefulness, perceived ease of use, attitudes toward technology, and behavioral intention to use.⁵⁵

Integrating CFIR and TAM enables examination of how implementation climate shape clinicians’ perceptions of CDS usefulness, usability, trustworthiness, workflow compatibility, cognitive burden, and clinical relevance.^49–55 From this perspective, technology acceptance is not only an individual cognitive process but also a socially and organizationally mediated experience shaped by workflow realities, organizational legitimacy, implementation climate, and social reinforcement. This integrated sociotechnical lens provides a more comprehensive understanding of why CDS tools are accepted, resisted, sustained, or abandoned in real-world primary care settings.

Study Purpose and Objectives

This qualitative study examined how implementation context and clinicians’ technology acceptance processes jointly shape clinicians’ acceptance of and sustained engagement with guideline-based CDS tools in US primary care settings through an integrated CFIR-TAM lens. The study addresses an important gap in CDS implementation research by examining how workflow design, leadership endorsement, implementation climate, governance structures, cognitive burden, and organizational trust collectively shape clinician perceptions and experiences of CDS in primary care. It also contributes contemporary insights into clinician perceptions of AI-supported CDS, including concerns regarding explainability, transparency, workflow fit, and preservation of clinical autonomy. By including physicians, nurse practitioners, physician assistants, and pharmacists with prescribing authority, the study reflects the increasingly interdisciplinary nature of primary care delivery and CDS implementation.

This study had four primary objectives:

1. Examine primary care providers’ attitudes, perceptions, and experiences related to guideline-based clinical decision support tools.

2. Assess individual, workflow-related, organizational, and technological factors associated with clinician acceptance, engagement, and sustained use of guideline-based CDS in primary care settings.

3. Explore how organizational culture, workflow design, leadership engagement, implementation climate, and related contextual conditions shape clinicians’ use of evidence-based CDS.

4. Develop implementation-focused insights and strategies that may support effective, scalable, and sustainable integration of guideline-based CDS tools in primary care practice.

Conceptual Framework

Understanding clinician acceptance, engagement, and sustained use of guideline-based CDS systems in primary care requires conceptual approaches that examine both organizational implementation conditions and clinician technology acceptance processes.^49–55 Because CDS implementation occurs within complex organizational and clinical environments, adoption cannot be understood solely as a technological or individual behavioral phenomenon.^49,52–55 This study, therefore, integrates the Consolidated Framework for Implementation Research (CFIR) and the Technology Acceptance Model (TAM) to provide a complementary sociotechnical lens for examining how implementation conditions shape clinicians’ perceptions, experiences, and sustained engagement with guideline-based CDS in primary care. Figure 1 illustrates the study’s conceptual framework.

Figure 1.

Integrated CFIR–TAM Conceptual Framework for Understanding Clinician Acceptance and Sustained Engagement with Guideline-Based Clinical Decision Support in Primary Care. This integrated CFIR–TAM framework illustrates how organizational, workflow, and implementation conditions influence clinicians’ perceptions of guideline-based clinical decision support (CDS) systems in primary care. These contextual influences affect technology acceptance processes that, in turn, shape clinician acceptance, sustained engagement, and integration of CDS into routine clinical practice.

Understanding CDS Adoption as a Sociotechnical Process

Implementation of guideline-based CDS represents a complex sociotechnical process in which technology design, workflow integration, organizational culture, leadership, clinician cognition, and implementation strategy interact to influence adoption and sustained use.^31,40,43,52 Clinicians’ engagement depends on how CDS tools fit within patient care workflows and organizational implementation environments, rather than on technological functionality alone. Accordingly, this study integrates CFIR and TAM to examine how implementation context shapes clinician acceptance and sustained engagement with guideline-based CDS.

CFIR and Organizational Implementation Context

CFIR is a widely used implementation science framework for examining contextual determinants of implementation success across healthcare settings.^49,53,54 CFIR conceptualizes implementation as being influenced by five interacting domains: intervention characteristics, outer setting, inner setting, characteristics of individuals, and implementation processes.^53,54 Together, these domains provide a structured approach for understanding how organizational, environmental, workflow-related, and individual factors shape implementation outcomes.

Within primary care, these domains influence how CDS tools are introduced, integrated into workflows, and sustained over time. Intervention characteristics such as usability, adaptability, complexity, and evidence strength may influence clinicians’ willingness to engage with CDS recommendations. Outer-setting influences, including payer requirements, quality metrics, professional guidelines, patient care demands, and policy pressures, may shape organizational priorities surrounding CDS implementation. The inner setting encompasses organizational culture, workflow structures, implementation climate, communication patterns, leadership engagement, staffing support, and available resources that influence whether CDS is experienced as supportive or burdensome during routine care. Characteristics of individuals, including clinicians’ knowledge, beliefs, prior technology experience, and attitudes toward evidence-based care, together with implementation processes such as planning, stakeholder engagement, training, execution, and ongoing evaluation, further influence successful implementation.^53,54

CFIR therefore provides an important framework for understanding how organizational context and implementation processes shape clinicians’ experiences with CDS beyond technological functionality alone.^49,53,54

TAM and Clinician Technology Acceptance

TAM complements CFIR by explaining the cognitive and behavioral mechanisms underlying clinicians’ acceptance and use of healthcare technologies.^55–58 TAM proposes that technology adoption is primarily influenced by perceived usefulness and perceived ease of use, which in turn shape attitudes toward technology and behavioral intention to use it.⁵⁵

Within guideline-based CDS, perceived usefulness reflects clinicians’ beliefs that CDS improves clinical decision-making, supports evidence-based care, reduces cognitive burden, enhances workflow efficiency, and improves patient safety.^56–58 Perceived ease of use reflects the extent to which CDS is viewed as intuitive, efficient, minimally disruptive, and compatible with routine clinical workflows. Together, these perceptions shape clinicians’ willingness to engage with CDS recommendations and sustain their use over time.

Although TAM focuses primarily on individual cognition, clinicians’ perceptions of usefulness, usability, trustworthiness, and workflow compatibility are themselves influenced by organizational context, leadership support, implementation climate, workflow realities, and social reinforcement.^56–58 Technology acceptance in healthcare therefore extends beyond an individual cognitive process and is shaped by the broader organizational and practice environments in which clinicians deliver care.^56–58

Integrating CFIR and TAM

Integrating CFIR and TAM provides a more comprehensive framework for understanding guideline-based CDS adoption than either framework alone.^49–55 Rather than viewing technology acceptance solely as an individual cognitive process, this integrated perspective recognizes that clinician acceptance is shaped by organizational context, workflow conditions, leadership support, governance, and implementation climate.

Implementation conditions influence whether CDS tools are perceived as trustworthy, clinically relevant, cognitively supportive, and compatible with routine clinical practice.^53–55 Workflow integration shapes perceptions of ease of use, whereas leadership support, governance, and implementation climate influence trust, legitimacy, and sustained engagement. Conversely, workflow disruption, alert fatigue, inadequate training, and poor integration into clinical routines may undermine perceived usefulness and contribute to resistance or abandonment despite strong technological capability.

By examining the mechanisms through which implementation context shapes clinician technology acceptance and sustained engagement, the integrated CFIR–TAM framework provides the theoretical foundation for this study and for identifying implementation strategies that support effective, scalable, and sustainable CDS integration in primary care.^54–56

Methods

Building on the integrated CFIR-TAM framework described above, this study employed a qualitative design to examine how implementation context shapes clinicians’ experiences with guideline-based CDS use and sustained engagement in primary care practice. The methods were designed to capture both organizational implementation conditions and clinician technology acceptance experiences across diverse ambulatory care environments.

Study Design

This qualitative study examined how organizational implementation context and clinician technology acceptance jointly shape the adoption and sustained use of guideline-based CDS tools in US primary care settings. Guided by the integrated CFIR-TAM framework, the study used reflexive thematic analysis to explore clinicians’ experiences with CDS implementation, including workflow integration, organizational culture, leadership engagement, implementation climate, and cognitive burden.

Reflexive thematic analysis was selected because it supports in-depth exploration of participants’ experiences while allowing both inductive identification of emergent themes and theory-informed interpretation using CFIR and TAM constructs. Reporting followed the Consolidated Criteria for Reporting Qualitative Research (COREQ) to enhance transparency, reflexivity, and methodological rigor.⁵⁹ The completed COREQ checklist is provided in Appendix 1.

Study Setting, Participants, and Recruitment

Participants were recruited from ambulatory primary care practices across the United States to capture diverse experiences with guideline-based CDS implementation across organizational and workflow contexts. The study received approval from the University of New Haven Institutional Review Board (Protocol #2025-063).

Eligible participants were US-based physicians (MD/DO), nurse practitioners (NP), physician assistants (PA), and pharmacists (PharmD) with prescribing authority who had current or prior experience using guideline-based CDS tools in ambulatory primary care. Medical trainees, including medical students and residents, and clinicians without prior experience using guideline-based CDS tools were excluded.

Purposive sampling was used to recruit clinicians meeting predefined eligibility criteria through professional networks, LinkedIn, clinic newsletters, and snowball sampling. Recruitment continued until sufficient conceptual depth and thematic richness were achieved and additional interviews yielded no conceptually meaningful new insights relevant to the study objectives and conceptual framework. Thirteen clinicians participated, providing variation across professional roles, organizational settings, and workflow environments to support examination of multilevel influences on CDS adoption and sustained use.

Research Team and Reflexivity

Interviews were conducted by the lead researcher (PM), a female doctoral researcher with training in qualitative methods, implementation science, and healthcare systems research, under the supervision of senior researchers. Participants had no prior professional relationship with the interviewer and were informed of the study’s purpose and the interviewer’s role in doctoral research.

Reflexivity was maintained throughout data collection and analysis to promote awareness of researcher assumptions and their potential influence on interpretation. Coding decisions, thematic development, and conceptual interpretation were discussed iteratively between the lead researcher (P.M.) and the senior researcher (PR), who has extensive experience in qualitative health systems and implementation research. Consistent with Braun and Clarke’s reflexive thematic analysis approach, themes evolved collaboratively throughout analysis. Additional discussions with co-authors (S.L.S. and A.T.) informed later-stage interpretation and refinement of the manuscript. Reflexive field notes and analytic memos documented emerging interpretations, contextual observations, and conceptual insights throughout the study.

Data Collection

Semi-structured individual interviews were conducted via Zoom between September and October 2025. Interviews lasted approximately 60–90 minutes, were audio-recorded with participant consent, and followed an interview guide informed by CFIR, TAM, and prior CDS implementation literature. Questions explored clinicians’ experiences with CDS usability, workflow integration, organizational support, implementation processes, trust, and sustained engagement. The interview guide is provided in Appendix 2.

The interview guide was pilot-tested before formal data collection. Follow-up prompts and adaptive questioning were used to explore emerging concepts in greater depth. Zoom-generated transcripts were reviewed for accuracy, de-identified prior to analysis, and assigned pseudonyms to protect participant confidentiality.

Data Analysis

Data were analyzed using Braun and Clarke’s reflexive thematic analysis approach.⁶⁰ Interview transcripts were imported into MAXQDA qualitative analysis software to support data management and coding. Analysis was iterative, beginning with repeated reading of transcripts and familiarization with the data, followed by inductive coding of participants’ experiences and deductive coding informed by sensitizing concepts derived from CFIR and TAM.

Consistent with Braun and Clarke’s six-phase approach, analysis involved familiarization with the data, generation of initial codes, development of candidate themes, iterative review and refinement of themes, conceptual definition of themes, and construction of the final analytic narrative.⁶⁰ Throughout the analysis, CFIR informed interpretation of organizational implementation context, including workflow integration, implementation climate, leadership engagement, governance, organizational culture, and implementation processes, while TAM informed interpretation of clinicians’ perceptions of usefulness, ease of use, trust, usability, and technology acceptance.^49–55

Codes were iteratively refined into broader conceptual themes through constant comparison across transcripts and continuous movement between data, coding, and interpretation. Themes were reviewed to ensure conceptual coherence, distinction, and alignment with the study objectives and integrated CFIR-TAM framework. Attention was given to understanding how implementation conditions influenced clinicians’ perceptions of workflow compatibility, usability, cognitive burden, trust, and sustained CDS engagement. Illustrative examples demonstrating progression from participant quotations to codes, subthemes, and final themes are presented in Appendix 3, while mapping of the final themes to CFIR domains and TAM constructs is provided in Appendix 4.

Trustworthiness and Rigor

Several strategies enhanced methodological rigor and trustworthiness. Maximum variation sampling captured diverse organizational settings and clinician perspectives. Reflexive memoing, iterative coding refinement, and ongoing analytic discussions promoted transparency and interpretive rigor throughout the analytic process. An audit trail documenting coding decisions, thematic development, and conceptual refinement was maintained throughout the study. Interpretive discussions between the lead and senior researchers supported analytic depth and consistency between participant narratives, thematic findings, and the integrated CFIR-TAM framework. Transcripts were reviewed for completeness, and participant clarification was obtained when necessary. Although transcripts and final themes were not formally returned to participants for member checking, clarification was sought through follow-up communication when appropriate.

Ethical Considerations

All participants provided informed consent before participation, including consent for the publication of anonymized responses and direct quotations. Participants did not receive compensation or other incentives for participation. Participation was voluntary, and participants could withdraw at any time. Interview transcripts were de-identified following transcription, and all study data were stored on password-protected systems accessible only to the research team.

Results

This section presents findings from interviews with 13 primary care clinicians regarding their experiences with implementing guideline-based CDS in ambulatory practice. Findings are organized into participant characteristics followed by six interrelated themes describing how workflow integration, organizational context, clinician perceptions, cognitive burden, and social influences shaped CDS adoption and sustained engagement. Collectively, the findings characterize CDS implementation as a sociotechnical process extending beyond technological functionality alone.

Participant Characteristics

Thirteen primary care clinicians participated in the study, representing physicians (MD/DO), nurse practitioners (NPs), physician assistants (PAs), and pharmacists (PharmDs) with prescribing authority. Participants practiced in diverse ambulatory primary care settings across the United States, including independent practices, group practices, and health system-affiliated clinics. The sample reflected variation in clinical experience, organizational settings, workflow structures, and prior exposure to guideline-based CDS tools, supporting exploration of the multilevel factors influencing clinician acceptance, engagement, and sustained CDS use. Participant demographic and practice characteristics are summarized in Table 1.

Table 1.

Participant Demographic and Practice Characteristics (N = 13)

Characteristic	n	%
Provider Type
Physicians (MD)	6	46.2
Physicians (DO)	1	7.7
Nurse Practitioners	3	23.1
Physician Assistants	1	7.7
Pharmacists (PharmD) with Prescribing Authority	2	15.4
Total	13	100
Gender
Female	9	69.2
Male	4	30.8
Total	13	100
Age
<40 years	4	30.8
40–60 years	9	69.2
Total	13	100
Practice Size
1–5 providers	8	61.5
6–10 providers	5	38.5
Total	13	100
Geographic Region
Western/Midwestern United States	8	61.5
Eastern United States	5	38.5
Total	13	100

Overview of Key Thematic Findings

Analysis of the interview data generated six interrelated thematic findings describing how implementation context shaped clinicians’ experiences with guideline-based CDS in primary care. Consistent with the integrated CFIR-TAM framework, clinician acceptance and sustained engagement reflected not only technological functionality but also workflow integration, organizational legitimacy, leadership support, cognitive burden, social reinforcement, and clinical context.

The six thematic findings were: (1) workflow integration shaped perceived usability and cognitive burden; (2) organizational legitimacy and leadership support shaped trust in CDS; (3) CDS acceptance increased when systems supported rather than disrupted clinical judgment; (4) social reinforcement and team-based implementation influenced sustained engagement; (5) cognitive and resource constraints limited sustained CDS engagement; and (6) clinician role, experience, and digital comfort influenced patterns of CDS use. Table 2 summarizes the relationship among these themes, their underlying subthemes, and their interpretations.

Table 2.

Key Thematic Findings, Underlying Themes and Subthemes, and Central Interpretive Meaning

Key Thematic Finding	Underlying Themes and Subthemes	Central Meaning
Workflow integration shaped perceived usability and cognitive burden	Workflow Compatibility: seamless integration; right-time prompts; usability and design features; role-based task allocation. Cognitive Burden and Alert Fatigue: low-value alerts; signal-to-noise issues; multi-step CDS interactions; time and resource pressures.	Clinicians were more likely to accept and sustain engagement with CDS when tools integrated naturally into clinical workflows, appeared at meaningful decision points, minimized unnecessary clicks, and reduced rather than amplified cognitive burden.
Organizational legitimacy and leadership support shaped trust in CDS	Trust and Organizational Alignment: local context alignment; transparency of evidence and update processes; governance and review mechanisms; leadership endorsement.	Trust in CDS was shaped not only by technological functionality, but also by organizational legitimacy, visible leadership support, transparent governance processes, and alignment with local clinical priorities and workflows.
CDS acceptance increased when systems supported rather than disrupted clinical judgment	Expectations for AI-Enabled CDS: personalized recommendations; automation to reduce burden; predictive support; transparency and explainability. Also linked to Trust and Organizational Alignment.	Clinicians were receptive to CDS and AI-enabled CDS when systems augmented clinical reasoning, supported personalization, preserved professional autonomy, and remained transparent, explainable, and clinically accountable
Social reinforcement and team-based implementation influenced sustained engagement	Social Influence: clinical champions; peer-based reinforcement and informal training; team-based reinforcement; culture of evidence-based practice. Also linked to Workflow Compatibility: role-based task allocation.	Sustained CDS engagement was reinforced through clinical champions, peer modeling, collaborative workflows, and organizational cultures supportive of evidence-based practice and continuous improvement.
Cognitive and resource constraints limited sustained CDS engagement	Cognitive Burden and Alert Fatigue: time and resource pressures; low-value alerts; multi-step CDS interactions. Also linked to Workflow Compatibility: workflow interruption and poor integration.	Time pressure, staffing limitations, administrative burden, and competing clinical demands constrained clinicians’ ability to engage consistently with CDS tools, even when potential clinical value was recognized.
Clinician role, experience, and digital comfort influenced patterns of CDS use	Role and Experience Differences: experience-based variation; digital literacy differences; role-based perceived value.	CDS engagement varied across professional roles, years of experience, digital familiarity, and perceived relevance to clinicians’ responsibilities within team-based primary care environments.

Workflow Integration Shaped Perceived Usability and Cognitive Burden

Clinicians described workflow integration as a central determinant of CDS acceptance and long-term engagement. CDS tools were viewed positively when they fit naturally into clinical routines, minimized disruption, reduced unnecessary clicks, and supported real-time decision-making. In contrast, tools perceived as fragmented, poorly timed, cognitively burdensome, or disconnected from workflow realities were often bypassed regardless of their technical sophistication or evidence base.

Participants emphasized that CDS usability was inseparable from workflow design. Tools embedded directly within existing EHR workflows were viewed as more acceptable than systems requiring separate navigation, duplicate data entry, or additional platforms. One clinician explained:

I mean, it would be number one for them to be within the workflow. In an ideal world, you want your tool to be integrated into your EHR. (MD, Participant 12)

Similarly, another participant stated:

Integration is gonna be very helpful; if you have a separate platform to go to, it’s very hard to get away from your screen. (MD, Participant 2)

Several clinicians also emphasized simplicity, rapid interpretability, and minimal cognitive effort during patient encounters. One nurse practitioner described the importance of streamlined interfaces:

Something very precise and to the point, like less scrolling, single clicks, a red, green, or yellow signal… usability is a big, big, big component. (NP, Participant 7)

Workflow misalignment increased cognitive burden and reduced willingness to engage with CDS recommendations. Excessive clicks, redundant tasks, irrelevant alerts, and interruptions during patient conversations were especially problematic in high-volume primary care environments. One participant described the burden associated with poorly integrated alerts:

They get very frustrated with alert fatigue, especially with our EHR, which is not the most user-friendly. There is already a lot of clicking, a lot of alerts. (PharmD, Participant 8)

Participants also emphasized timing and contextual relevance. Alerts delivered at clinically meaningful moments were perceived as supportive, whereas poorly timed prompts contributed to frustration and disengagement. Several clinicians noted that CDS systems often failed to account for patient complexity, longitudinal care realities, and contextual clinical nuance in primary care.

Overall, workflow compatibility was described not simply as a usability preference, but as a prerequisite for meaningful CDS adoption and sustained engagement. Even highly evidence-based tools were unlikely to be used consistently when they disrupted clinical workflow, increased mental workload, or failed to align with frontline patient-care realities. Additional illustrative quotations are presented in Table 3, and related barriers, facilitators, and implementation implications are summarized in Table 4.

Table 3.

Illustrative Quotations Supporting Key Thematic Findings

Key Thematic Finding	Illustrative Quotations	Participant	Implementation Insight
Workflow Integration Shaped Perceived Usability and Cognitive Burden	“I mean, it would be number one for them to be within the workflow. In an ideal world, you want your tool to be integrated into your EHR.”	Participant 12 (MD)	Clinicians consistently emphasized that CDS usability depended on seamless workflow integration, minimal navigation burden, and rapid access to actionable recommendations within existing EHR environments.
	“Integration is gonna be very helpful; if you have a separate platform to go to, it’s very hard to get away from your screen.”	Participant 2 (MD)
	“Something very precise and to the point, like less scrolling, single clicks, a red, green, or yellow signal. Usability is a big, big, big component.”	Participant 7 (NP)
Cognitive and Resource Constraints Limited Sustained CDS Engagement	“They get very frustrated with alert fatigue, especially with our EHR, which is not the most user-friendly. There is already a lot of clicking, a lot of alerts.”	Participant 8 (PharmD)	Alert overload, time pressure, fragmented workflows, and limited organizational resources contributed to cognitive burden and constrained sustained CDS engagement in primary care settings.
	“Time is just very important to everybody. I think it does affect it if it’s not embedded or at least made more accessible.”	Participant 9 (PharmD)
	“But there simply are not the resources—finances, personnel, time—for it in independent primary care practices.”	Participant 3 (PA)
Organizational Legitimacy and Leadership Support Shaped Trust in CDS	“You need to have leadership buy-in. You need to have a showcase in the staff meetings. These are the tools that we have available, this is how you use them, and this is the data that shows that it works and it’s worth your time.”	Participant 12 (MD)	Leadership endorsement, governance processes, and visible organizational oversight strengthened clinicians’ trust in CDS recommendations and implementation efforts.
	“You have to have your leadership and your organizational support to implement it. The first step will always be first to talk to the leadership.”	Participant 8 (PharmD)
	“We definitely conduct chart reviews, and we review the new upgrades that come from the EHR. We are not blindly trusting.”	Participant 2 (MD)
CDS Acceptance Increased When Systems Supported Rather Than Disrupted Clinical Judgment	“My vision, especially as AI gets more robust, is that we’re gonna have an AI clinical co-pilot that’s working alongside the doctor searching the chart simultaneously to look for trends or gaps or things that need to be tested.”	Participant 13 (MD)	Clinicians viewed AI-enabled CDS positively when systems augmented clinical reasoning and reduced burden, but expressed concern regarding overly rigid implementations that could undermine professional judgment.
	“I’ve seen people just use guidelines to do patient care, which is not what we want. We still need to use our brains and clinical judgment.”	Participant 5 (MD)
	“So, something that would be amazing is to have a program that could capture what I’m talking to the patient in real time, giving me an option for breast cancer for a 40-year-old.”	Participant 6 (NP)
Social Reinforcement and Team-Based Implementation Influenced Sustained Engagement	“Without that clinical champion, and clinical leadership supporting it and saying, this is why you’re getting this new tool, it makes it challenging.”	Participant 11 (MD)	Clinical champions, peer reinforcement, and team-based workflow participation strengthened clinician receptivity and facilitated normalization of CDS use within practice settings.
	“Adoption was much higher when they were hearing from their own specialist, who had been using the tool and was satisfied with it.”	Participant 2 (MD)
	“The other thing that can help out, too, is not limiting it to the clinicians. You could also have your nurse or MA use the tool when they’re prepping their chart.”	Participant 12 (MD)
Clinician Role, Experience, and Digital Comfort Influenced Patterns of CDS Use	“I feel like someone that’s new will definitely use it. People in the middle, I would say, maybe, maybe would use it.”	Participant 4 (NP)	Clinicians perceived CDS engagement patterns as varying according to professional role, level of experience, digital comfort, and expectations regarding technology-enabled workflow support.
	“Some people are more comfortable with technology than others.”	Participant 11 (MD)

Table 4.

Integrated Interpretation of Key Barriers, Facilitators, and Implementation Implications for Guideline-Based CDS Adoption in Primary Care

Key Thematic Finding	Key Barriers Identified	Key Facilitators Identified	Relative Analytic Emphasis	Illustrative CFIR Domains	Illustrative TAM Constructs	Implementation Implications
Workflow Integration Shaped Perceived Usability and Cognitive Burden	Poor EHR integration; excessive clicks; workflow interruption; fragmented platforms; poorly timed alerts; documentation burden	Seamless EHR integration; workflow-aligned prompts; minimal-click design; right-time recommendations; role-based task support	Widely emphasized across participants and practice settings	Intervention Characteristics; Inner Setting; Implementation Process	Perceived Ease of Use; Perceived Usefulness	CDS tools should be embedded directly into routine clinical workflows with minimal disruption to patient encounters and cognitive processes.
Organizational Legitimacy and Leadership Support Shaped Trust in CDS	Outdated recommendations; clinically irrelevant alerts; lack of transparency; weak governance oversight; poor contextual alignment	Leadership endorsement; transparent evidence updates; governance and review processes; local customization; visible organizational support	Frequently emphasized as central to sustained engagement	Inner Setting; Process; Intervention Characteristics	Perceived Usefulness; Behavioral Intention to Use	Sustained CDS engagement requires visible organizational endorsement, transparent updating mechanisms, and governance structures that reinforce clinical legitimacy and trust.
CDS Acceptance Increased When Systems Supported Rather Than Disrupted Clinical Judgment	Perceived threats to autonomy; overly generic recommendations; lack of contextual nuance; explainability concerns; concerns regarding over-automation and inappropriate AI-generated recommendations	CDS framed as a supportive “co-pilot”; clinician oversight; patient-specific recommendations; explainable and transparent AI-supported functionality; automation that reduced information burden	Strongly emphasized across discussions of clinical autonomy, AI-supported CDS, and contextual decision-making	Characteristics of Individuals; Intervention Characteristics; Inner Setting	Perceived Usefulness; Attitude Toward Use	CDS systems, including emerging AI-enabled tools, should augment rather than override clinician reasoning and should preserve transparency, explainability, contextual relevance, and clinician oversight.
Social Reinforcement and Team-Based Implementation Influenced Sustained Engagement	Lack of clinical champions; insufficient peer support; weak implementation culture; inadequate training support	Clinical champions; peer-based reinforcement and informal training; interdisciplinary reinforcement; culture of evidence-based practice	Frequently discussed as important for implementation sustainability	Inner Setting; Process	Attitude Toward Use; Behavioral Intention to Use	Team-based implementation strategies and peer-supported learning environments may strengthen long-term CDS engagement and normalization within primary care settings.
Cognitive and Resource Constraints Limited Sustained CDS Engagement	Low-value alerts; signal-to-noise problems; excessive notifications; competing demands; time pressure; staffing and resource limitations	Streamlined interfaces; higher-value alerts; reduction of unnecessary prompts; automation that reduced cognitive workload	Widely discussed, particularly in high-volume primary care environments	Inner Setting; Intervention Characteristics	Perceived Ease of Use	CDS implementation strategies should prioritize reduction of unnecessary cognitive burden, improve relevance-to-alert ratios, and account for staffing and time constraints within frontline practice settings.
Clinician Role, Experience, and Digital Comfort Influenced Patterns of CDS Use	Established practice habits; variability in digital literacy; skepticism among experienced clinicians	Engagement among newer clinicians; role-based delegation; advanced practice provider involvement; team-based workflow participation	Moderately emphasized but conceptually important	Characteristics of Individuals	Perceived Ease of Use; Behavioral Intention to Use	CDS implementation strategies should account for role-specific workflow needs, varying levels of digital comfort, and differentiated training approaches across interdisciplinary primary care teams.

Organizational Legitimacy and Leadership Support Shaped Trust in CDS

Trust emerged as a central determinant of clinician engagement with CDS technologies. Rather than viewing trust as solely an individual attitude toward technology, clinicians described it as being shaped by organizational legitimacy, governance structures, leadership endorsement, implementation climate, and confidence in the processes that guide CDS development and oversight. Participants emphasized that visible leadership support increased their willingness to engage with CDS recommendations by reinforcing their clinical relevance and alignment with organizational quality improvement priorities. One participant explained:

You need to have leadership buy-in. You need to have a showcase in the staff meetings. These are the tools that we have available, this is how you use them, and this is the data that shows that it works and it’s worth your time. (MD, Participant 12)

Similarly, another participant emphasized that organizational support was foundational for successful implementation

You have to have your leadership and your organizational support to implement it. The first step will always be first to talk to the leadership. (PharmD, Participant 8)

Trust was also closely linked to evidence quality, transparency, and governance. Clinicians expressed greater confidence in CDS when recommendations were regularly updated, evidence sources were transparent, and formal oversight processes incorporated clinician feedback. One clinician described the importance of ongoing review

We definitely conduct chart reviews, and we review the new upgrades that come from the EHR. We are not blindly trusting. (MD, Participant 2)

Conversely, trust eroded when CDS recommendations appeared outdated, clinically inappropriate, overly generic, or disconnected from patient context. One participant recalled:

They turned on the alerts for men and women. We had to tell them no, it’s not for men, it’s only for women. (DO, Participant 10)

Overall, clinicians linked trust to organizational alignment. CDS systems that reflected local workflows, institutional priorities, and clinical realities were viewed as more legitimate and clinically useful, whereas poorly contextualized alerts or externally imposed implementation efforts often generated skepticism despite clinicians’ general support for evidence-based care.

CDS Acceptance Increased When Systems Supported, Not Disrupted, Clinical Judgment

Clinicians generally viewed CDS favorably when it functioned as a supportive clinical aid rather than a mechanism that constrained autonomy or replaced professional judgment. Participants consistently emphasized that CDS was most acceptable when it augmented clinical reasoning, reduced information burden, and supported decision-making without undermining clinician expertise or contextual judgment.

This perspective was especially evident in discussions of emerging AI-enabled CDS technologies. Participants viewed AI-supported CDS not simply as a technological innovation but as a means of managing increasing clinical complexity, information overload, and documentation burden. Several envisioned AI functioning as a “clinical co-pilot” that could synthesize patient information, identify care gaps, and support real-time clinical decision-making. One participant explained:

I think that as AI gets more robust, we’re gonna have an AI clinical co-pilot that’s working alongside the doctor.

The same participant further elaborated:

My vision, especially as AI gets more robust, is that we’re gonna have an AI clinical co-pilot that’s working alongside the doctor, searching the chart simultaneously to look for trends or gaps or things that need to be tested. (MD, Participant 13)

Participants also anticipated benefits from AI-supported automation, predictive analytics, patient-specific recommendations, and documentation support that could reduce cognitive burden and enhance personalized care. However, enthusiasm remained contingent on transparency, explainability, clinician oversight, and preservation of professional judgment. As one clinician noted:

AI is not going anywhere; it’s important that we learn how to safely use it. (MD, Participant 13)

Resistance therefore reflected concerns about preserving clinician autonomy rather than opposition to AI itself. Participants expressed reluctance when CDS recommendations appeared to oversimplify patient complexity or substitute for clinical reasoning. One physician cautioned:

I’ve seen people just use guidelines to do patient care, which is not what we want. We still need to use our brains and clinical judgment. (MD, Participant 5)

Overall, clinicians were more likely to embrace CDS technologies that reinforced rather than replaced professional expertise and contextual clinical decision-making.

Social Reinforcement and Team-Based Implementation Influenced Sustained Engagement

Participants consistently described CDS adoption as a socially mediated process shaped by peer influence, team dynamics, clinical champions, and implementation culture. Sustained engagement was reinforced through interpersonal relationships, shared workflows, and visible support from respected colleagues. Clinical champions were viewed as particularly important in normalizing CDS use by modeling implementation and reinforcing its legitimacy. One participant stated:

Without that clinical champion, and clinical leadership supporting it and saying, this is why you’re getting this new tool, it makes it challenging. (MD, Participant 11)

Peer-to-peer learning and informal “micro-training” also supported CDS engagement. Participants frequently described informal demonstrations and colleague recommendations as more influential than formal training alone. One clinician noted:

Adoption was much higher when they were hearing from their own specialist, who had been using the tool and was satisfied with it. (MD, Participant 2)

Team-based workflows further strengthened sustained use. Several participants emphasized that distributing CDS-related responsibilities across nurses, medical assistants, pharmacists, and other team members made implementation more manageable. One participant explained:

The other thing that can help out, too, is not limiting it to the clinicians. You could also have your nurse or MA use the tool when they’re prepping their chart. (MD, Participant 12)

Participants also highlighted implementation culture as an important determinant of sustained engagement. Practices characterized by collaborative workflow redesign, continuous improvement, and support for evidence-based practice appeared more receptive to CDS integration than environments resistant to workflow change. Overall, sustained CDS engagement was shaped not only by individual clinician perceptions but also by broader social and organizational processes embedded within team-based care.

Cognitive and Resource Constraints Limited Sustained CDS Engagement

Participants consistently emphasized that time pressure, staffing shortages, competing priorities, and administrative burden constrained their ability to engage meaningfully with CDS technologies. These structural and cognitive demands influenced whether CDS implementation was perceived as feasible in routine primary care practice.

Clinicians described primary care as a cognitively saturated environment characterized by heavy workloads, brief visits, documentation demands, and competing organizational expectations. In this context, even minor workflow disruptions became meaningful barriers to sustained CDS engagement. One participant explained:

Time is just very important to everybody… I think it does affect it if it’s not embedded or at least made more accessible. (PharmD, Participant 9)

Another clinician stated:

As primary care providers, we get 15 to 20 minutes per patient, and they come with three to four problems. (MD, Participant 2)

Participants frequently associated alert fatigue with broader cognitive overload and workflow disruption, describing excessive or poorly targeted alerts as mentally exhausting and counterproductive during busy patient encounters.

Resource constraints extended beyond time alone. Participants also cited inadequate staffing, limited implementation infrastructure, financial constraints, and insufficient protected training time as barriers to sustained CDS use. One clinician summarized these challenges directly:

But there simply are not the resources — finances, personnel, time — for it in independent primary care practices. (PA, Participant 3)

Overall, clinicians did not reject CDS technologies themselves; rather, they described structural and organizational constraints that limited their capacity to engage with CDS consistently within already overextended primary care environments.

Clinician Role, Experience, and Digital Comfort Influenced Patterns of CDS Use

Clinicians’ experiences with CDS varied according to professional role, years of experience, prior exposure to digital technologies, and comfort with EHR-based workflows. Participants consistently described differences in CDS adoption across provider groups and practice settings.

Early-career clinicians and advanced practice providers were often viewed as more receptive to CDS and more comfortable integrating digital tools into routine practice. Several participants suggested that newer clinicians regarded CDS as a natural extension of contemporary evidence-based care and digital healthcare. One participant explained:

I feel like someone that’s new will definitely use it. People in the middle, I would say, maybe, maybe would use it. (NP, Participant 4)

Another clinician remarked:

If you’re young, then you’re probably using a lot of tools. (MD, Participant 11)

Participants also described growing expectations for real-time technological support within clinical workflows. One nurse practitioner explained:

So, something that would be amazing is to have a program that could capture what I’m talking to the patient in real time… (NP, Participant 6)

In contrast, more experienced clinicians were often described as more selective in their use of CDS and more likely to rely on established clinical routines and experiential judgment. Participants suggested that previous experience with poorly designed systems sometimes contributed to skepticism toward newer implementation efforts.

Digital literacy and prior exposure to health information technologies also influenced CDS engagement. Clinicians with greater familiarity navigating EHRs and digital workflows generally perceived CDS as more useful and manageable, whereas limited digital experience or insufficient training contributed to variability in adoption across practices.

Overall, CDS adoption was not experienced uniformly across clinicians or practice settings. Instead, sustained engagement reflected interactions among professional role, clinical experience, digital comfort, implementation support, and organizational context. Integrated barriers, facilitators, and implementation implications are summarized in Table 4, while Table 5 aligns the study objectives, key thematic findings, and CFIR–TAM constructs supporting the study’s integrated sociotechnical interpretation.

Table 5.

Alignment of Study Objectives, Key Thematic Findings, and CFIR–TAM Constructs

Study Objective	Key Thematic Findings	Dominant CFIR Constructs	Dominant TAM Constructs	Key Interpretive Insights
Examine primary care providers’ attitudes, perceptions, and experiences related to guideline-based clinical decision support tools	Workflow Integration Shaped Perceived Usability and Cognitive Burden; CDS Acceptance Increased When Systems Supported Rather Than Disrupted Clinical Judgment	Intervention Characteristics; Inner Setting	Perceived Ease of Use; Perceived Usefulness	Clinicians’ perceptions of CDS were shaped not only by technical functionality, but also by how seamlessly CDS tools aligned with real-world workflow demands and supported clinical reasoning during patient care encounters.
Assess the individual, workflow-related, organizational, and technological factors associated with clinician acceptance, engagement, and sustained use of guideline-based CDS in primary care settings	Cognitive and Resource Constraints Limited Sustained CDS Engagement; Clinician Role, Experience, and Digital Comfort Influenced Patterns of CDS Use	Inner Setting; Characteristics of Individuals	Perceived Ease of Use; Behavioral Intention to Use	Barriers to clinician acceptance, engagement, and sustained use emerged when CDS systems increased cognitive burden, disrupted workflow efficiency, or failed to account for variation in clinicians’ experience, digital comfort, and practice realities.
Explore how organizational culture, workflow design, leadership engagement, implementation climate, and related contextual conditions shape clinicians’ use of evidence-based CDS	Organizational Legitimacy and Leadership Support Shaped Trust in CDS; Social Reinforcement and Team-Based Implementation Influenced Sustained Engagement	Inner Setting; Process	Perceived Usefulness; Behavioral Intention to Use	Organizational endorsement, peer reinforcement, governance structures, and implementation climate shaped clinicians’ trust in CDS systems and willingness to engage with CDS recommendations over time.
Develop implementation-focused insights and strategies that may support effective, scalable, and sustainable integration of guideline-based CDS tools in primary care practice	All six key thematic findings contributed collectively to implementation-oriented insights regarding workflow integration, trust, leadership support, team-based implementation, usability optimization, and responsible AI integration	Process; Inner Setting; Intervention Characteristics	Perceived Usefulness; Perceived Ease of Use; Behavioral Intention to Use	Sustainable CDS implementation requires organizationally aligned, workflow-compatible, cognitively supportive, and clinically trustworthy systems reinforced through leadership engagement, governance structures, team-based implementation, and responsive integration strategies.

Discussion

This study examined how implementation context and clinician technology acceptance jointly shaped the adoption and sustained use of guideline-based CDS tools in US primary care. The findings demonstrate that clinician acceptance of CDS is fundamentally a sociotechnical process, influenced not only by technological functionality but also by workflow integration, organizational legitimacy, cognitive burden, trust, social reinforcement, and preservation of clinician judgment. As summarized in Table 5, the integrated CFIR–TAM framework provides a comprehensive explanation of how these interacting organizational, workflow, and behavioral factors shape sustained CDS engagement in real-world primary care settings.

Interpretation of Findings

The findings demonstrate that clinician acceptance and sustained engagement with guideline-based CDS in primary care are fundamentally shaped by interactions between implementation context and technology acceptance rather than by technological functionality alone. Consistent with the integrated CFIR–TAM framework, workflow conditions, organizational legitimacy, cognitive burden, trust, and social reinforcement, collectively influenced how CDS technologies were perceived, adopted, and sustained in routine practice. Together, these findings position CDS implementation as a dynamic sociotechnical process occurring within complex primary care environments rather than as a purely technological or individual behavioral phenomenon.

A primary finding was that workflow integration and cognitive burden were central determinants of CDS acceptance and sustained engagement. Consistent with prior CDS implementation research, clinicians viewed seamless EHR integration, minimal workflow disruption, clinically relevant decision support, and efficient interface design as essential to sustained use.^{22,23,29,31,40} However, the present study extends existing literature by demonstrating that workflow compatibility influences clinicians’ perceptions of usefulness and ease of use, thereby linking implementation context directly to technology acceptance. Even evidence-based CDS tools were unlikely to be adopted when they disrupted clinical workflows or increased cognitive workload within already time-constrained primary care environments.

A second key insight is that trust emerged as an organizationally mediated construct rather than simply an individual attitude toward technology. Leadership endorsement, governance structures, transparent evidence review, clinical champions, peer learning, and supportive implementation cultures collectively reinforced clinicians’ confidence in CDS recommendations and sustained engagement. These findings extend implementation science literature by demonstrating that organizational legitimacy and social reinforcement shape technology acceptance alongside traditional implementation determinants.^{24,31,44,49,53,54,57} Importantly, trust was grounded not only in technological performance but also in organizational accountability, implementation climate, and confidence that CDS recommendations reflected transparent, evidence-based governance.

The findings also contribute to ongoing discussions regarding AI-enabled CDS implementation in primary care.^7,36,42 Participants viewed AI-supported CDS as valuable for reducing information burden, improving personalization, identifying care gaps, and supporting clinical decision-making. However, acceptance remained contingent upon transparency, explainability, governance, and preservation of clinician autonomy. Rather than resisting AI itself, clinicians emphasized that AI-supported CDS should complement—not replace—professional judgment and contextual clinical reasoning.^32,33,40,61 These findings suggest that successful implementation of AI-enabled CDS will depend as much on trustworthy governance and workflow integration as on technological sophistication.

Collectively, these findings advance the CDS implementation literature by demonstrating that clinician acceptance is best understood as a dynamic sociotechnical process in which workflow integration, organizational legitimacy, cognitive burden, trust, social reinforcement, and clinician judgment interact to shape sustained engagement over time. By integrating CFIR and TAM, this study moves beyond static descriptions of barriers and facilitators to provide a more comprehensive explanation of how implementation context and technology acceptance jointly influence real-world CDS adoption in primary care settings.^{22,31,40,41,45,49,55}

Implications for Practice

The findings suggest that successful implementation of guideline-based CDS systems in primary care requires more than technical deployment alone.^22,31,40 Consistent with Objective 4, the findings support an implementation-oriented perspective in which workflow integration, organizational legitimacy, cognitive support, team-based implementation, and transparent governance collectively shape sustained CDS engagement. Building on these findings, we propose the TRUST framework as a practical guide for implementing scalable and sustainable CDS systems in primary care.

T: Tailored Workflow Integration. CDS should integrate seamlessly into routine EHR workflows, minimize unnecessary clicks, and deliver recommendations at clinically meaningful decision points. Implementation efforts should prioritize workflow compatibility that reflects the realities of time-constrained, interdisciplinary primary care practice.^{23,29,31,40,41,48}

R: Reinforced Organizational Legitimacy. Leadership endorsement, transparent governance, clinician involvement, and continuous feedback strengthen trust in CDS and reinforce its legitimacy within everyday clinical practice.^{24,32,33,44,53,54}

U: Usability and Cognitive Burden Reduction. CDS should emphasize intuitive interfaces, clinically relevant alerts, and human-centered design that minimizes cognitive overload and alert fatigue while supporting efficient decision-making.^{23,29,35,39,40,58}

S: Social Reinforcement and Team-Based Implementation. Clinical champions, peer learning, interdisciplinary collaboration, and shared responsibility for CDS use can promote normalization and sustained engagement across care teams.^{44,49,53,54,57}

T: Transparent and Trustworthy AI-Supported CDS. As AI-enabled CDS becomes more common, implementation should emphasize explainability, transparent governance, clinician oversight, and preservation of professional judgment alongside technological performance.^32,33,42,61

Collectively, the TRUST framework emphasizes that sustainable CDS implementation depends not only on technological capability but also on workflow alignment, organizational culture, cognitive support, interdisciplinary teamwork, and clinician trust.^22,31,40,45

Implications for Health System Leadership

The findings suggest that health system leaders should view CDS implementation as an organizational change initiative rather than simply a technology acquisition. Sustainable implementation requires investment in workflow redesign, protected training time, implementation resources, governance oversight, interdisciplinary implementation teams, and mechanisms for continuous clinician feedback.^24,44,53,54 As organizations increasingly adopt AI-enabled CDS, leadership should also prioritize transparent governance, clinician engagement, and ongoing evaluation to maintain trust, accountability, and long-term adoption.^32,33,42,61 A detailed presentation of the TRUST framework and its corresponding implementation considerations is provided in Appendix 5.

Implications for Policy

The findings suggest that policies promoting guideline-based CDS implementation should extend beyond technology adoption to address the organizational and workforce conditions that influence sustained use. Participants consistently identified productivity pressures, reimbursement demands, administrative burden, and time-constrained workflows as barriers to meaningful CDS engagement, underscoring the need for policies that better align implementation expectations with frontline clinical realities.^{23,31,35,40,48,58}

As healthcare systems increasingly adopt digital and AI-enabled CDS, policy efforts should also emphasize implementation infrastructure, transparent governance, clinician oversight, organizational readiness, and responsible AI use alongside technological innovation.^32,33,42,61 Policies supporting workflow redesign, usability standards, protected implementation resources, and accountable AI governance may strengthen sustainable CDS integration across primary care settings.^32,40,58

Implications for Future Research

Future research should examine how clinician acceptance of CDS evolves across implementation phases and organizational contexts, with particular attention to changes in trust, workflow integration, usability, and organizational legitimacy over time. Additional studies are also needed to evaluate the implementation of AI-enabled CDS in primary care, including the roles of explainability, governance, clinician oversight, and workflow integration in shaping sustained adoption.^32,33,36,61

Comparative studies across healthcare systems and practice settings, together with mixed-methods and quantitative investigations building on the integrated CFIR–TAM framework, could further clarify how implementation context influences perceived usefulness, cognitive burden, trust, and long-term CDS engagement.^41,45,49,53

Limitations and Strengths

This study has some limitations. The sample was modest and limited to US primary care clinicians, which may affect transferability to other settings. The findings were based on self-reported experiences rather than objective measures of CDS use, and the cross-sectional qualitative design could not capture changes in clinician perceptions over time. In addition, variation across organizations, clinical workflows, and EHR platforms may limit the applicability of the findings to all CDS implementation contexts. Because interviews were conducted remotely through Zoom, the researchers may also have had fewer opportunities to observe certain nonverbal and contextual cues than would have been possible during in-person interviews. Although the integrated CFIR–TAM framework provided a useful interpretive lens, the relationships identified warrant further examination in larger and more diverse populations.

Despite these limitations, the study has several strengths. Remote interviewing reduced geographic and transportation barriers and enabled participation by clinicians from diverse ambulatory primary care settings across the United States. By integrating CFIR and TAM, the study provides a comprehensive sociotechnical perspective on CDS implementation that incorporates both organizational implementation context and clinician technology acceptance. The interdisciplinary sample of physicians, nurse practitioners, physician assistants, and pharmacists with prescribing authority captured diverse perspectives across primary care settings, while reflexive thematic analysis enabled an in-depth examination of workflow, organizational, and cognitive influences on CDS engagement. Finally, the proposed TRUST framework translates these findings into practical implementation guidance for supporting sustainable CDS integration in primary care.

Conclusion

Successful implementation of guideline-based CDS in primary care depends on far more than technological capability alone. This study demonstrates that workflow integration, organizational legitimacy, trust, cognitive burden, social reinforcement, and preservation of clinician judgment collectively shape clinician acceptance and sustained engagement with CDS. By integrating CFIR and TAM, the study advances a sociotechnical understanding of CDS implementation that recognizes the dynamic interaction between organizational context and clinician technology acceptance.

The proposed TRUST framework translates these findings into practical implementation guidance, emphasizing workflow alignment, organizational support, usability, team-based implementation, and transparent governance. As healthcare systems continue to expand guideline-based and AI-enabled CDS, implementation strategies that prioritize these organizational and human factors may be better positioned to achieve sustainable adoption and meaningful integration into primary care practice.

Funding Statement

No specific external funding was received for the conduct of this study.

Abbreviations

AI, Artificial Intelligence; APP, Advanced Practice Provider; CDS, Clinical Decision Support; CFIR, Consolidated Framework for Implementation Research; EHR, Electronic Health Record; NP, Nurse Practitioner; PA, Physician Assistant; PharmD, Doctor of Pharmacy; TAM, Technology Acceptance Model; TRUST: Tailored Workflow Integration, Reinforced Organizational Legitimacy, Usability and Cognitive Burden Reduction, Social Reinforcement and Team-Based Implementation, Transparent and Trustworthy AI-Supported CDS.

Data Sharing Statement

The datasets generated and analyzed during the current study are not publicly available because they contain information that could potentially compromise participant confidentiality. Deidentified study materials may be available from the corresponding author upon reasonable request and subject to institutional review board requirements and participant consent provisions.

Ethical Considerations

This study was approved by the University of New Haven Institutional Review Board (Protocol #2025-063). All participants provided informed consent prior to participation, including consent for the publication of anonymized responses and direct quotations. Participation was voluntary, and participants could withdraw from the study at any time. Interview transcripts were de-identified prior to analysis, and all study data were stored on secure password-protected systems accessible only to the research team.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors declare no conflicts of interest.