Assessing the implementation of a clinical decision support tool in primary care for diabetes prevention: a qualitative interview study using the Consolidated Framework for Implementation Science

Enhancing the follow-up for patients with type 2 diabetes mellitus using a proactive scheduling computer tool: A paired cohort study in primary care

AIM

To assess the impact of an electronic scheduling tool (Planificat) on the management of type 2 diabetes mellitus (T2DM) in primary care settings.

METHODS

This paired cohort study used data from the Catalan primary care electronic health records. The intervention cohort, using Planificat, included all patients aged 15 years or older with T2DM and was matched 1:1 with a control cohort. The study period lasted one year. Mixed general linear models estimated Odds Ratios (OR) and 95 % confidence intervals (95 %CI) for primary outcomes, including T2DM clinical tests (LDL cholesterol, HbA1c), visit frequency, and non-attendance rates.

RESULTS

A total of 51,619 patients (mean age 68.3 years, 42.1 % of female sex) and their paired controls were included. In the primary analysis, significant increases were observed in the Planificat group (N = 18,542) regarding several measures: cholesterol tests performed (83.5 % vs. 75.4 %; OR: 1.65 [95 %CI: 1.57-1.74]), HbA1c tests performed (83.7 % vs. 75.4 %; OR: 1.7 [95 %CI: 1.61-1.79]), and electrocardiograms (65 % vs. 52 %; OR: 1.72 [95 %CI: 1.65-1.8]). Additionally, there was a 36 % increase in patients achieving HbA1c levels < 8 % (OR: 1.36 [95 %CI: 1.3-1.42]). Statistically significant improvements of 30 % and 40 % were also observed in foot and retinopathy screenings, respectively. Face-to-face visits with general practitioners and non-attendance rates remained comparable between cohorts, while face-to-face nurse visits increased by 7 %.

CONCLUSIONS

Planificat significantly improved T2DM management indicators, promoting proactive scheduling and enhancing follow-up in primary care without impacting face-to-face visits. These findings support its integration as a complementary strategy for optimizing chronic disease management.

Barriers and facilitators of the use of clinical informatics resources to facilitate pharmacogenomic implementation in resource-limited settings

Objective

Understand perceived barriers to and facilitators of using clinical informatics applications for pharmacogenomic (PGx) implementation in resource-limited settings.

Materials and Methods

We conducted a qualitative research study using a semi-structured interview guide informed by the Consolidated Framework for Implementation Research (CFIR). Interview questions assessed CFIR contextual determinants related to: electronic health record (EHR) infrastructure; clinical informatics personnel and resources; EHR integration of PGx test results; PGx clinical decision support (CDS) tools; institutional resources; and partner receptivity. Transcripts were coded and analyzed to identify themes.

Results

We interviewed 24 clinical informaticists and executive leaders working in rural or underserved health care settings in Montana (n = 15) and Colorado (n = 9) and identified three major themes: (1) EHR infrastructure limitations, (2) insufficient supporting resources, and (3) unique contextual considerations for resource-limited settings. EHR infrastructure limitations included limited agency related to EHR build and interoperability concerns. Theme 1 highlighted challenges associated with integrating structured data into the EHR and inadequate vendor support. Theme 2 included limited familiarity with PGx across the care team, cost concerns, and allocation of non-financial resources. Theme 3 highlighted perceptions about the clinical utility of PGx within rural and underrepresented populations. Potential facilitators, such as being able to act nimbly, were found to coexist among the reported barriers.

Discussion and Conclusion

Our results provide insight into the clinical informatics infrastructure in resource-limited settings and identify unique considerations for clinical informatics-facilitated PGx implementation. Future efforts in these settings should consider innovative partnerships and strategies to leverage facilitators and minimize barriers associated with integrating PGx CDS applications.

Clinician Perspectives on Decision Support and AI-based Decision Support in a Pediatric ED

BACKGROUND

Clinical decision support (CDS) systems offer the potential to improve pediatric care through enhanced test ordering, prescribing, and standardization of care. Its augmentation with artificial intelligence (AI-CDS) may help address current limitations with CDS implementation regarding alarm fatigue and accuracy of recommendations. We sought to evaluate strengths and perceptions of CDS, with a focus on AI-CDS, through semistructured interviews of clinician partners.

METHODS

We conducted a qualitative study using semistructured interviews of physicians, nurse practitioners, and nurses at a single quaternary-care pediatric emergency department to evaluate clinician perceptions of CDS and AI-CDS. We used reflexive thematic analysis to identify themes and purposive sampling to complete recruitment with the goal of reaching theoretical sufficiency.

RESULTS

We interviewed 20 clinicians. Participants demonstrated a variable understanding of CDS and AI, with some lacking a clear definition. Most recognized the potential benefits of AI-CDS in clinical contexts, such as data summarization and interpretation. Identified themes included the potential of AI-CDS to improve diagnostic accuracy, standardize care, and improve efficiency, while also providing educational benefits to clinicians. Participants raised concerns about the ability of AI-based tools to appreciate nuanced pediatric care, accurately interpret data, and about tensions between AI recommendations and clinician autonomy.

CONCLUSIONS

AI-CDS tools have a promising role in pediatric emergency medicine but require careful integration to address clinicians' concerns about autonomy, nuance recognition, and interpretability. A collaborative approach to development and implementation, informed by clinicians' insights and perspectives, will be pivotal for their successful adoption and efficacy in improving patient care.

Assessing the Utility, Impact, and Adoption Challenges of an Artificial Intelligence-Enabled Prescription Advisory Tool for Type 2 Diabetes Management: Qualitative Study

BACKGROUND

The clinical management of type 2 diabetes mellitus (T2DM) presents a significant challenge due to the constantly evolving clinical practice guidelines and growing array of drug classes available. Evidence suggests that artificial intelligence (AI)-enabled clinical decision support systems (CDSSs) have proven to be effective in assisting clinicians with informed decision-making. Despite the merits of AI-driven CDSSs, a significant research gap exists concerning the early-stage implementation and adoption of AI-enabled CDSSs in T2DM management.

OBJECTIVE

This study aimed to explore the perspectives of clinicians on the use and impact of the AI-enabled Prescription Advisory (APA) tool, developed using a multi-institution diabetes registry and implemented in specialist endocrinology clinics, and the challenges to its adoption and application.

METHODS

We conducted focus group discussions using a semistructured interview guide with purposively selected endocrinologists from a tertiary hospital. The focus group discussions were audio-recorded and transcribed verbatim. Data were thematically analyzed.

RESULTS

A total of 13 clinicians participated in 4 focus group discussions. Our findings suggest that the APA tool offered several useful features to assist clinicians in effectively managing T2DM. Specifically, clinicians viewed the AI-generated medication alterations as a good knowledge resource in supporting the clinician's decision-making on drug modifications at the point of care, particularly for patients with comorbidities. The complication risk prediction was seen as positively impacting patient care by facilitating early doctor-patient communication and initiating prompt clinical responses. However, the interpretability of the risk scores, concerns about overreliance and automation bias, and issues surrounding accountability and liability hindered the adoption of the APA tool in clinical practice.

CONCLUSIONS

Although the APA tool holds great potential as a valuable resource for improving patient care, further efforts are required to address clinicians' concerns and improve the tool's acceptance and applicability in relevant contexts.

Exploring the role of professional identity in the implementation of clinical decision support systems-a narrative review

BACKGROUND

Clinical decision support systems (CDSSs) have the potential to improve quality of care, patient safety, and efficiency because of their ability to perform medical tasks in a more data-driven, evidence-based, and semi-autonomous way. However, CDSSs may also affect the professional identity of health professionals. Some professionals might experience these systems as a threat to their professional identity, as CDSSs could partially substitute clinical competencies, autonomy, or control over the care process. Other professionals may experience an empowerment of the role in the medical system. The purpose of this study is to uncover the role of professional identity in CDSS implementation and to identify core human, technological, and organizational factors that may determine the effect of CDSSs on professional identity.

METHODS

We conducted a systematic literature review and included peer-reviewed empirical studies from two electronic databases (PubMed, Web of Science) that reported on key factors to CDSS implementation and were published between 2010 and 2023. Our explorative, inductive thematic analysis assessed the antecedents of professional identity-related mechanisms from the perspective of different health care professionals (i.e., physicians, residents, nurse practitioners, pharmacists).

RESULTS

One hundred thirty-one qualitative, quantitative, or mixed-method studies from over 60 journals were included in this review. The thematic analysis found three dimensions of professional identity-related mechanisms that influence CDSS implementation success: perceived threat or enhancement of professional control and autonomy, perceived threat or enhancement of professional skills and expertise, and perceived loss or gain of control over patient relationships. At the technological level, the most common issues were the system's ability to fit into existing clinical workflows and organizational structures, and its ability to meet user needs. At the organizational level, time pressure and tension, as well as internal communication and involvement of end users were most frequently reported. At the human level, individual attitudes and emotional responses, as well as familiarity with the system, most often influenced the CDSS implementation. Our results show that professional identity-related mechanisms are driven by these factors and influence CDSS implementation success. The perception of the change of professional identity is influenced by the user's professional status and expertise and is improved over the course of implementation.

CONCLUSION

This review highlights the need for health care managers to evaluate perceived professional identity threats to health care professionals across all implementation phases when introducing a CDSS and to consider their varying manifestations among different health care professionals. Moreover, it highlights the importance of innovation and change management approaches, such as involving health professionals in the design and implementation process to mitigate threat perceptions. We provide future areas of research for the evaluation of the professional identity construct within health care.

Applications of Clinical Decision Support Systems in Diabetes Care: Scoping Review

BACKGROUND

Providing comprehensive and individualized diabetes care remains a significant challenge in the face of the increasing complexity of diabetes management and a lack of specialized endocrinologists to support diabetes care. Clinical decision support systems (CDSSs) are progressively being used to improve diabetes care, while many health care providers lack awareness and knowledge about CDSSs in diabetes care. A comprehensive analysis of the applications of CDSSs in diabetes care is still lacking.

OBJECTIVE

This review aimed to summarize the research landscape, clinical applications, and impact on both patients and physicians of CDSSs in diabetes care.

METHODS

We conducted a scoping review following the Arksey and O'Malley framework. A search was conducted in 7 electronic databases to identify the clinical applications of CDSSs in diabetes care up to June 30, 2022. Additional searches were conducted for conference abstracts from the period of 2021-2022. Two researchers independently performed the screening and data charting processes.

RESULTS

Of 11,569 retrieved studies, 85 (0.7%) were included for analysis. Research interest is growing in this field, with 45 (53%) of the 85 studies published in the past 5 years. Among the 58 (68%) out of 85 studies disclosing the underlying decision-making mechanism, most CDSSs (44/58, 76%) were knowledge based, while the number of non-knowledge-based systems has been increasing in recent years. Among the 81 (95%) out of 85 studies disclosing application scenarios, the majority of CDSSs were used for treatment recommendation (63/81, 78%). Among the 39 (46%) out of 85 studies disclosing physician user types, primary care physicians (20/39, 51%) were the most common, followed by endocrinologists (15/39, 39%) and nonendocrinology specialists (8/39, 21%). CDSSs significantly improved patients' blood glucose, blood pressure, and lipid profiles in 71% (45/63), 67% (12/18), and 38% (8/21) of the studies, respectively, with no increase in the risk of hypoglycemia.

CONCLUSIONS

CDSSs are both effective and safe in improving diabetes care, implying that they could be a potentially reliable assistant in diabetes care, especially for physicians with limited experience and patients with limited access to medical resources.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.37766/inplasy2022.9.0061.

A structural equation model of CFIR inner and outer setting constructs, organization characteristics, and national DPP enrollment

BACKGROUND

The National Diabetes Prevention Program (DPP) has made great strides in increasing accessibility to its year-long, evidence-based lifestyle change program, with around 3000 organizations having delivered the program. This large dissemination effort offers a unique opportunity to identify organization-level factors associated with program implementation and reach (enrollment) across diverse settings. The purpose of this study was to quantitatively examine the relationships among Consolidated Framework for Implementation Research (CFIR) Inner Setting and Outer Setting constructs and the implementation outcome of reach.

METHODS

This study analyzed data from a 2021 cross-sectional online survey with 586 National DPP Staff (lifestyle coaches, master trainers, program coordinators) with information about their organization, implementation outcomes, and responses to quantitative CFIR Inner Setting and Outer Setting construct items. Structural equation modeling was used to test a hypothesized path model with Inner and Outer Setting variables to explore direct and indirect pathways to enrollment.

RESULTS

The CFIR items had good internal consistency and indicated areas of implementation strength and weakness. Eight variables included as part of the CFIR structural characteristics and one organization characteristic variable had significant direct relationships with enrollment. The length of delivery, number of lifestyle coaches, number of full-time staff, large organization size, and organizations delivering in rural, suburban, and/or urban settings all had positive significant direct relationships with enrollment, while academic organizations and organizations with only non-White participants enrolled in their National DPP lifestyle change programs had a negative association with enrollment.

CONCLUSIONS

Participant reach is an important implementation outcome for the National DPP and vital to making population-level decreases in diabetes incidence in the USA. Our findings suggest that to facilitate enrollment, program implementers should focus on organizational structural characteristics such as staffing. Strengths of this study include the use of adapted and newly developed quantitative CFIR measures and structural equation modeling. Health prevention programs can use the methods and findings from this study to further understand and inform the impact of organization factors on implementation outcomes.

Clinician perceptions of a clinical decision support system to reduce cardiovascular risk among prediabetes patients in a predominantly rural healthcare system

Background

The early detection and management of uncontrolled cardiovascular risk factors among prediabetes patients can prevent cardiovascular disease (CVD). Prediabetes increases the risk of CVD, which is a leading cause of death in the United States. CVD clinical decision support (CDS) in primary care settings has the potential to reduce cardiovascular risk in patients with prediabetes while potentially saving clinicians time. The objective of this study is to understand primary care clinician (PCC) perceptions of a CDS system designed to reduce CVD risk in adults with prediabetes.

Methods

We administered pre-CDS implementation (6/30/2016 to 8/25/2016) (n = 183, 61% response rate) and post-CDS implementation (6/12/2019 to 8/7/2019) (n = 131, 44.5% response rate) independent cross-sectional electronic surveys to PCCs at 36 randomized primary care clinics participating in a federally funded study of a CVD risk reduction CDS tool. Surveys assessed PCC demographics, experiences in delivering prediabetes care, perceptions of CDS impact on shared decision making, perception of CDS impact on control of major CVD risk factors, and overall perceptions of the CDS tool when managing cardiovascular risk.

Results

We found few significant differences when comparing pre- and post-implementation responses across CDS intervention and usual care (UC) clinics. A majority of PCCs felt well-prepared to discuss CVD risk factor control with patients both pre- and post-implementation. About 73% of PCCs at CDS intervention clinics agreed that the CDS helped improve risk control, 68% reported the CDS added value to patient clinic visits, and 72% reported they would recommend use of this CDS system to colleagues. However, most PCCs disagreed that the CDS saves time talking about preventing diabetes or CVD, and most PCCs also did not find the clinical domains useful, nor did PCCs believe that the clinical domains were useful in getting patients to take action. Finally, only about 38% reported they were satisfied with the CDS.

Conclusions

These results improve our understanding of CDS user experience and can be used to guide iterative improvement of the CDS. While most PCCs agreed the CDS improves CVD and diabetes risk factor control, they were generally not satisfied with the CDS. Moreover, only 40–50% agreed that specific suggestions on clinical domains helped patients to take action. In spite of this, an overwhelming majority reported they would recommend the CDS to colleagues, pointing for the need to improve upon the current CDS.

Trial registration: NCT02759055 03/05/2016.

Using an Integrated Framework to Investigate the Facilitators and Barriers of Health Information Technology Implementation in Noncommunicable Disease Management: Systematic Review

BACKGROUND

Noncommunicable disease (NCD) management is critical for reducing attributable health burdens. Although health information technology (HIT) is a crucial strategy to improve chronic disease management, many health care systems have failed in implementing HIT. There has been a lack of research on the implementation process of HIT for chronic disease management.

OBJECTIVE

We aimed to identify the barriers and facilitators of HIT implementation, analyze how these factors influence the implementation process, and identify key areas for future action. We will develop a framework for understanding implementation determinants to synthesize available evidence.

METHODS

We conducted a systematic review to understand the barriers and facilitators of the implementation process. We searched MEDLINE, Cochrane, Embase, Scopus, and CINAHL for studies published between database inception and May 5, 2022. Original studies involving HIT-related interventions for NCD management published in peer-reviewed journals were included. Studies that did not discuss relevant outcome measures or did not have direct contact with or observation of stakeholders were excluded. The analysis was conducted in 2 parts. In part 1, we analyzed how the intrinsic attributes of HIT interventions affect the successfulness of implementation by using the intervention domain of the Consolidated Framework for Implementation Research (CFIR). In part 2, we focused on the extrinsic factors of HIT using an integrated framework, which was developed based on the CFIR and the levels of change framework by Ferlie and Shortell.

RESULTS

We identified 51 papers with qualitative, mixed-method, and cross-sectional methodologies. Included studies were heterogeneous regarding disease populations and HIT interventions. In part 1, having a relative advantage over existing health care systems was the most prominent intrinsic facilitator (eg, convenience, improvement in quality of care, and increase in access). Poor usability was the most noted intrinsic barrier of HIT. In part 2, we mapped the various factors of implementation to the integrated framework (the coordinates are shown as level of change-CFIR). The key barriers to the extrinsic factors of HIT included health literacy and lack of digital skills (individual-characteristics of individuals). The key facilitators included physicians' suggestions, cooperation (interpersonal-process), integration into a workflow, and adequate management of data (organizational-inner setting). The importance of health data security was identified. Self-efficacy issues of patients and organizational readiness for implementation were highlighted.

CONCLUSIONS

Internal factors of HIT and external human factors of implementation interplay in HIT implementation for chronic disease management. Strategies for improvement include ensuring HIT has a relative advantage over existing health care; tackling usability issues; and addressing underlying socioeconomic, interpersonal, and organizational conditions. Further research should focus on studying various stakeholders, such as service providers and administrative workforces; various disease populations, such as those with obesity and mental diseases; and various countries, including low- and middle-income countries.