Barriers and Facilitators for Implementation of a Computerized Clinical Decision Support System in Lung Cancer Multidisciplinary Team Meetings-A Qualitative Assessment

Facilitators and Barriers to Lung Cancer Screening during Long COVID: A Global Systematic Review and Meta-Study Synthesis of Qualitative Research

Background: Participation in targeted screening reduces lung cancer mortality by 30-60%, but screening is not universally available. Therefore, the study aimed to synthesize the evidence and identify facilitators and barriers to lung cancer screening participation globally. Methods: Two reviewers screened primary studies using qualitative methods published up to February 2023. We used two-phase synthesis consistent with a meta-study methodology to create an interpretation of lung cancer screening decisions grounded in primary studies, carried out a thematic analysis of group themes as specific facilitators and barriers, systematically compared investigations for similarities and differences, and performed meta-synthesis to generate an expanded theory of lung cancer screening participation. We used the Social Ecological Model to organize and interpret the themes: individual, interpersonal, social/cultural, and organizational/structural levels. Results: Fifty-two articles met the final inclusion criteria. Themes identified as facilitating lung cancer screening included prioritizing patient education, quality of communication, and quality of provider-initiated encounter/coordination of care (individual patient and provider level), quality of the patient-provider relationship (interpersonal group), perception of a life's value and purpose (cultural status), quality of tools designed, and care coordination (and organizational level). Themes coded as barriers included low awareness, fear of cancer diagnosis, low perceived benefit, high perceived risk of low-dose computerized tomography, concern about cancer itself, practical obstacle, futility, stigma, lack of family support, COVID-19 fear, disruptions in cancer care due to COVID-19, inadequate knowledge of care providers, shared decision, and inadequate time (individual level), patient misunderstanding, poor rapport, provider recommendation, lack of established relationship, and confusing decision aid tools (interpersonal group), distrust in the service, fatalistic beliefs, and perception of aging (cultural level), and lack of institutional policy, lack of care coordinators, inadequate infrastructure, absence of insurance coverage, and costs (and organizational status). Conclusions: This study identified critical barriers, facilitators, and implications to lung cancer screening participation. Therefore, we employed strategies for a new digital medicine (artificial intelligence) screening method to balance the cost-benefit, "workdays" lost in case of disease, and family hardship, which is essential to improve lung cancer screening uptake.

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.

Physicians' Perspectives on AI in Clinical Decision Support Systems: Interview Study of the CURATE.AI Personalized Dose Optimization Platform

BACKGROUND

Physicians play a key role in integrating new clinical technology into care practices through user feedback and growth propositions to developers of the technology. As physicians are stakeholders involved through the technology iteration process, understanding their roles as users can provide nuanced insights into the workings of these technologies that are being explored. Therefore, understanding physicians' perceptions can be critical toward clinical validation, implementation, and downstream adoption. Given the increasing prevalence of clinical decision support systems (CDSSs), there remains a need to gain an in-depth understanding of physicians' perceptions and expectations toward their downstream implementation. This paper explores physicians' perceptions of integrating CURATE.AI, a novel artificial intelligence (AI)-based and clinical stage personalized dosing CDSSs, into clinical practice.

OBJECTIVE

This study aims to understand physicians' perspectives of integrating CURATE.AI for clinical work and to gather insights on considerations of the implementation of AI-based CDSS tools.

METHODS

A total of 12 participants completed semistructured interviews examining their knowledge, experience, attitudes, risks, and future course of the personalized combination therapy dosing platform, CURATE.AI. Interviews were audio recorded, transcribed verbatim, and coded manually. The data were thematically analyzed.

RESULTS

Overall, 3 broad themes and 9 subthemes were identified through thematic analysis. The themes covered considerations that physicians perceived as significant across various stages of new technology development, including trial, clinical implementation, and mass adoption.

CONCLUSIONS

The study laid out the various ways physicians interpreted an AI-based personalized dosing CDSS, CURATE.AI, for their clinical practice. The research pointed out that physicians' expectations during the different stages of technology exploration can be nuanced and layered with expectations of implementation that are relevant for technology developers and researchers.

Leveraging web-based prediction calculators to set patient expectations for elective spine surgery: a qualitative study to inform implementation

BACKGROUND

Prediction calculators can help set outcomes expectations following orthopaedic surgery, however effective implementation strategies for these tools are unknown. This study evaluated provider and patient perspectives on clinical implementation of web-based prediction calculators developed using national prospective spine surgery registry data from the Quality Outcomes Database.

METHODS

We conducted semi-structured interviews in two health systems, Vanderbilt University Medical Center (VUMC) and Duke University Health System (DUHS) of orthopedic and neurosurgery health care providers (VUMC: n = 19; DUHS: n = 6), health care administrators (VUMC: n = 9; DUHS: n = 9), and patients undergoing elective spine surgery (VUMC: n = 16). Qualitative template analysis was used to analyze interview data, with a focus on end-user perspectives regarding clinical implementation of web-based prediction tools.

RESULTS

Health care providers, administrators and patients overwhelmingly supported the use of the calculators to help set realistic expectations for surgical outcomes. Some clinicians had questions about the validity and applicability of the calculators in their patient population. A consensus was that the calculators needed seamless integration into clinical workflows, but there was little agreement on best methods for selecting which patients to complete the calculators, timing, and mode of completion. Many interviewees expressed concerns that calculator results could influence payers, or expose risk of liability. Few patients expressed concerns over additional survey burden if they understood that the information would directly inform their care.

CONCLUSIONS

Interviewees had a largely positive opinion of the calculators, believing they could aid in discussions about expectations for pain and functional recovery after spine surgery. No single implementation strategy is likely to be successful, and strategies vary, even within the same healthcare system. Patients should be well-informed of how responses will be used to deliver better care, and concerns over how the calculators could impact payment and liability should be addressed prior to use. Future research is necessary to determine whether use of calculators improves management and outcomes for people seeking a surgical consult for spine pain.

Pros and cons of streamlining and use of computerised clinical decision support systems to future-proof oncological multidisciplinary team meetings

Introduction

Nowadays nearly every patient with cancer is discussed in a multidisciplinary team meeting (MDTM) to determine an optimal treatment plan. The growth in the number of patients to be discussed is unsustainable. Streamlining and use of computerised clinical decision support systems (CCDSSs) are two major ways to restructure MDTMs. Streamlining is the process of selecting the patients who need to be discussed and in which type of MDTM. Using CCDSSs, patient data is automatically loaded into the minutes and a guideline-based treatment proposal is generated. We aimed to identify the pros and cons of streamlining and CCDSSs.

Methods

Semi-structured interviews were conducted with Dutch MDTM participants. With purposive sampling we maximised variation in participants' characteristics. Interview data were thematically analysed.

Results

Thirty-five interviews were analysed. All interviewees agreed on the need to change the current MDTM workflow. Streamlining suggestions were thematised based on standard and complex cases and the location of the MDTM (i.e. local, regional or nationwide). Interviewees suggested easing the pressure on MDTMs by discussing standard cases briefly, not at all, or outside the MDTM with only two to three specialists. Complex cases should be discussed in tumour-type-specific regional MDTMs and highly complex cases by regional/nationwide expert teams. Categorizing patients as standard or complex was found to be the greatest challenge of streamlining. CCDSSs were recognised as promising, although none of the interviewees had made use of them. The assumed advantage was their capacity to generate protocolised treatment proposals based on automatically uploaded patient data, to unify treatment proposals and to facilitate research. However, they were thought to limit the freedom to deviate from the treatment advice.

Conclusion

To make oncological MDTMs sustainable, methods of streamlining should be developed and introduced. Physicians still have doubts about the value of CCDSSs.

Barriers and facilitators for implementation of a digital referral algorithm for inflammatory arthritis - a qualitative assessment in patients and caregivers

Purpose

Difficulty to recognize inflammatory rheumatic diseases (IRD) in a primary care setting leads to late referral to secondary care. An evidence-based digital referral algorithm can support early referral, yet implementation in daily practice only succeeds with support of end users. We aim to understand the context of implementing a digital referral algorithm and explore the potential barriers and facilitators to implementation.

Methods

This qualitative study comprised focus groups and an online survey. Focus groups were performed with patients from outpatient rheumatology clinics. Surveys were sent out to general practitioners and rheumatologists distributed over The Netherlands. The presented digital referral algorithm originates from the JOINT referral study. Thematic analysis was used with inductive and deductive approaches.

Results

In total 26 patients participated distributed over three focus groups, and 215 caregivers (104 rheumatologists, 111 general practitioners) filled out the survey. Both patients and caregivers endorse the need for early referral, and recognize the perceived benefit of the digital algorithm. Potential barriers include the complexity of currently included questions, and the outcome lacking information on what to do with no risk of IRD. In order for implementation to be successful, the inclusivity, accessibility, content and outcome of the algorithm are considered important themes.

Conclusion

Successful implementation of a digital referral algorithm needs a systematic multi-facetted approach, considering the barriers and facilitators for implementation as discussed. Since the majority of identified barriers and facilitators was overlapping between all stakeholders, findings from this study can reliably inform further decision strategies for successful implementation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-022-01858-w.

Meteorological factors' effects on COVID-19 show seasonality and spatiality in Brazil

The meteorological conditions may affect COVID-19 transmission. However, the roles of seasonality and macro-climate are still contentious due to the limited time series for early-stage studies. We studied meteorological factors' effects on COVID-19 transmission in Brazil from February 25 to November 15, 2020. We aimed to explore whether this impact showed seasonal characteristics and spatial variations related to the macro-climate. We applied two-way fixed-effect models to identify the effects of meteorological factors on COVID-19 transmission and used spatial analysis to explore their spatial-temporal characteristics with a relatively long-time span. The results showed that cold, dry and windless conditions aggravated COVID-19 transmission. The daily average temperature, humidity, and wind speed negatively affected the daily new cases. Humidity and temperature played a dominant role in this process. For the time series, the influences of meteorological conditions on COVID-19 had a periodic fluctuation of 3-4 months (in line with the seasons in Brazil). The turning points of this fluctuation occurred at the turn of seasons. Spatially, the negative effects of temperature and humidity on COVID-19 transmission clustered in the northeastern and central parts of Brazil. This is consistent with the range of arid climate types. Overall, the seasonality and similar climate types should be considered to estimate the spatial-temporal COVID-19 patterns. Winter is a critical time to be alert for COVID-19, especially in the northern part of Brazil.

Trustworthy AI: Closing the gap between development and integration of AI systems in ophthalmic practice

An increasing number of artificial intelligence (AI) systems are being proposed in ophthalmology, motivated by the variety and amount of clinical and imaging data, as well as their potential benefits at the different stages of patient care. Despite achieving close or even superior performance to that of experts, there is a critical gap between development and integration of AI systems in ophthalmic practice. This work focuses on the importance of trustworthy AI to close that gap. We identify the main aspects or challenges that need to be considered along the AI design pipeline so as to generate systems that meet the requirements to be deemed trustworthy, including those concerning accuracy, resiliency, reliability, safety, and accountability. We elaborate on mechanisms and considerations to address those aspects or challenges, and define the roles and responsibilities of the different stakeholders involved in AI for ophthalmic care, i.e., AI developers, reading centers, healthcare providers, healthcare institutions, ophthalmological societies and working groups or committees, patients, regulatory bodies, and payers. Generating trustworthy AI is not a responsibility of a sole stakeholder. There is an impending necessity for a collaborative approach where the different stakeholders are represented along the AI design pipeline, from the definition of the intended use to post-market surveillance after regulatory approval. This work contributes to establish such multi-stakeholder interaction and the main action points to be taken so that the potential benefits of AI reach real-world ophthalmic settings.

Virtual Multidisciplinary Tumor Boards: A Narrative Review Focused on Lung Cancer

To date, the virtual multidisciplinary tumor boards (vMTBs) are increasingly used to achieve high-quality treatment recommendations across health-care regions, which expands and develops the local MTB team to a regional or national expert network. This review describes the process of lung cancer-specific MTBs and the transition process from face-to-face tumor boards to virtual ones. The review also focuses on the project organization's description, advantages, and disadvantages. Semi-structured interviews identified five major themes for MTBs: current practice, attitudes, enablers, barriers, and benefits for the MTB. MTB teams exhibited positive responses to modeled data feedback. Virtualization reduces time spent for travel, allowing easier and timely patient discussions. This process requires a secure web platform to assure the respect of patients' privacy and presents the same unanswered problems. The implementation of vMTB also permits the implementation of networks especially in areas with geographical barriers facilitating interaction between large referral cancer centers and tertiary or community hospitals as well as easier access to clinical trial opportunities. Studies aimed to improve preparations, structure, and conduct of MTBs, research methods to monitor their performance, teamwork, and outcomes are also outlined in this article. Analysis of literature shows that MTB participants discuss 5-8 cases per meeting and that the use of a vMTB for lung cancer and in particular stage III NSCLC and complex stage IV cases is widely accepted by most health professionals. Despite still-existing gaps, overall vMTB represents a unique opportunity to optimize patient management in a patient-centered approach.

Big Data-Enabled Solutions Framework to Overcoming the Barriers to Circular Economy Initiatives in Healthcare Sector

Ever-changing conditions and emerging new challenges affect the ability of the healthcare sector to survive with the current system, and to maintain its processes effectively. In the healthcare sector, the conservation of the natural resources is being obstructed by insufficient infrastructure for managing residual waste resulting from single-use medical materials, increased energy use, and its environmental burden. In this context, circularity and sustainability concepts have become essential in healthcare to meliorate the sector’s negative impacts on the environment. The main aim of this study is to identify the barriers related to circular economy (CE) in the healthcare sector, apply big data analytics in healthcare, and provide solutions to these barriers. The contribution of this research is the detailed examination of the current healthcare literature about CE adaptation, and a proposal for a big data-enabled solutions framework to barriers to circularity, using fuzzy best-worst Method (BWM) and fuzzy VIKOR. Based on the findings, managerial, policy, and theoretical implementations are recommended to support sustainable development initiatives in the healthcare sector.

The cancer multidisciplinary team meeting: in need of change? History, challenges and future perspectives

Two decades since their inception, multidisciplinary teams (MDTs) are widely regarded as the 'gold standard' of cancer care delivery. Benefits of MDT working include improved patient outcomes, adherence to guidelines, and even economic benefits. Benefits to MDT members have also been demonstrated. An increasing body of evidence supports the use of MDTs and provides guidance on best practise. The system of MDTs in cancer care has come under increasing pressure of late, due to the increasing incidence of cancer, the popularity of MDT working, and financial pressures. This pressure has resulted in recommendations by national bodies to implement streamlining to reduce workload and improve efficiency. In the present review we examine the historical evidence for MDT working, and the scientific developments that dictate best practise. We also explore how streamlining can be safely and effectively undertaken. Finally, we discuss the future of MDT working including the integration of artificial intelligence and decision support systems and propose a new model for improving patient centredness.

Development and validation of the ADVANCER framework for naturopathic education and practice: A delphi study

BACKGROUND

There has been little attempt to date to narrow the education-practice gap in naturopathic medicine. A framework that brings naturopathic medicine education and practice closer together could help codify the knowledge of naturopathic medicine by providing simultaneous guidance on curriculum development and clinical decision-making in the discipline.

OBJECTIVE

To develop, refine and validate the Advancing Naturopathic Education and Practice (ADVANCER) framework.

METHODS

Published literature and pertinent government, professional association and institutional websites were scoped to identify key constructs for the ADVANCER framework. The constructs were grouped into ten domains, with each domain defined and translated into teaching and clinical practice outcomes. A two-round e-Delphi method, comprising international experts in naturopathic medicine education, was used to refine and validate the framework definitions and outcomes.

RESULTS

Sixteen academics, from five different countries, participated in the Delphi study. In round one, nine of the ten domains of the ADVANCER framework were rated as either very important or extremely important by 81.2% of participants. Only 68.8% of participants rated the tenth domain as either very important or extremely important. Participant feedback on each domain were pooled and reviewed, and where suggested changes were recommended by more than one participant, respective definitions and outcomes of each domain were amended. In round two, at least 90% of participants rated each domain of the amended ADVANCER framework as either very important or extremely important, meaning consensus to retain these domains, definitions and outcomes had been reached.

CONCLUSIONS

The study findings indicate that the ADVANCER framework is conceptually sound and potentially applicable to diverse institutions and countries. An important next step of this research is to establish whether implementation of the ADVANCER framework within naturopathic medicine education and practice is feasible, effective and sustainable.

The Impact of Multidisciplinary Team Meetings on Patient Management in Oncologic Thoracic Surgery: A Single-Center Experience

BACKGROUND

the aim of this paper is to quantify multidisciplinary team meeting (MDT) impact on the decisional clinical pathway of thoracic cancer patients, assessing the modification rate of the initial out-patient evaluation.

METHODS

the impact of MDT was classified as follows: confirmation: same conclusions as out-patient hypothesis; modification: change of out-patient hypothesis; implementation: definition of a clear clinical track/conclusion for patients that did not receive any clinical hypothesis; further exams required: the findings that emerged in the MDT meeting require further exams.

RESULTS

one thousand consecutive patients evaluated at MDT meetings were enrolled. Clinical settings of patients were: early stage lung cancer (17.4%); locally advanced lung cancer (27.4%); stage IV lung cancer (9.8%); mesothelioma (1%); metastases to the lung from other primary tumors (4%); histologically proven or suspected recurrence from previous lung cancer (15%); solitary pulmonary nodule (19.2%); mediastinal tumors (3.4%); other settings (2.8%).

CONCLUSIONS

MDT meetings impact patient management in oncologic thoracic surgery by modifying the out-patient clinical hypothesis in 10.6% of cases; the clinical settings with the highest decisional modification rates are "solitary pulmonary nodule" and "proven or suspected recurrence" with modification rates of 14.6% and 13.3%, respectively.