Evaluating the translation of implementation science to clinical artificial intelligence: a bibliometric study of qualitative research

2023 Hogg, Al-Zubaidy, Keane, Hughes, Beyer and Maniatopoulos.Introduction: Whilst a theoretical basis for implementation research is seen as advantageous, there is little clarity over if and how the application of theories, models or frameworks (TMF) impact implementation outcomes. Clinical artificial intelligence (AI) continues to receive multi-stakeholder interest and investment, yet a significant implementation gap remains. This bibliometric study aims to measure and characterize TMF application in qualitative clinical AI research to identify opportunities to improve research practice and its impact on clinical AI implementation. Methods: Qualitative research of stakeholder perspectives on clinical AI published between January 2014 and October 2022 was systematically identified. Eligible studies were characterized by their publication type, clinical and geographical context, type of clinical AI studied, data collection method, participants and application of any TMF. Each TMF applied by eligible studies, its justification and mode of application was characterized. Results: Of 202 eligible studies, 70 (34.7%) applied a TMF. There was an 8-fold increase in the number of publications between 2014 and 2022 but no significant increase in the proportion applying TMFs. Of the 50 TMFs applied, 40 (80%) were only applied once, with the Technology Acceptance Model applied most frequently (n = 9). Seven TMFs were novel contributions embedded within an eligible study. A minority of studies justified TMF application (n = 51,58.6%) and it was uncommon to discuss an alternative TMF or the limitations of the one selected (n = 11,12.6%). The most common way in which a TMF was applied in eligible studies was data analysis (n = 44,50.6%). Implementation guidelines or tools were explicitly referenced by 2 reports (1.0%). Conclusion: TMFs have not been commonly applied in qualitative research of clinical AI. When TMFs have been applied there has been (i) little consensus on TMF selection (ii) limited description of selection rationale and (iii) lack of clarity over how TMFs inform research. We consider this to represent an opportunity to improve implementation science\u27s translation to clinical AI research and clinical AI into practice by promoting the rigor and frequency of TMF application. We recommend that the finite resources of the implementation science community are diverted toward increasing accessibility and engagement with theory informed practices. The considered application of theories, models and frameworks (TMF) are thought to contribute to the impact of implementation science on the translation of innovations into real-world care. The frequency and nature of TMF use are yet to be described within digital health innovations, including the prominent field of clinical AI. A well-known implementation gap, coined as the “AI chasm” continues to limit the impact of clinical AI on real-world care. From this bibliometric study of the frequency and quality of TMF use within qualitative clinical AI research, we found that TMFs are usually not applied, their selection is highly varied between studies and there is not often a convincing rationale for their selection. Promoting the rigor and frequency of TMF use appears to present an opportunity to improve the translation of clinical AI into practice

Evaluating the translation of implementation science to clinical artificial intelligence: a bibliometric study of qualitative research

INTRODUCTION: Whilst a theoretical basis for implementation research is seen as advantageous, there is little clarity over if and how the application of theories, models or frameworks (TMF) impact implementation outcomes. Clinical artificial intelligence (AI) continues to receive multi-stakeholder interest and investment, yet a significant implementation gap remains. This bibliometric study aims to measure and characterize TMF application in qualitative clinical AI research to identify opportunities to improve research practice and its impact on clinical AI implementation. METHODS: Qualitative research of stakeholder perspectives on clinical AI published between January 2014 and October 2022 was systematically identified. Eligible studies were characterized by their publication type, clinical and geographical context, type of clinical AI studied, data collection method, participants and application of any TMF. Each TMF applied by eligible studies, its justification and mode of application was characterized. RESULTS: Of 202 eligible studies, 70 (34.7%) applied a TMF. There was an 8-fold increase in the number of publications between 2014 and 2022 but no significant increase in the proportion applying TMFs. Of the 50 TMFs applied, 40 (80%) were only applied once, with the Technology Acceptance Model applied most frequently (n = 9). Seven TMFs were novel contributions embedded within an eligible study. A minority of studies justified TMF application (n = 51,58.6%) and it was uncommon to discuss an alternative TMF or the limitations of the one selected (n = 11,12.6%). The most common way in which a TMF was applied in eligible studies was data analysis (n = 44,50.6%). Implementation guidelines or tools were explicitly referenced by 2 reports (1.0%). CONCLUSION: TMFs have not been commonly applied in qualitative research of clinical AI. When TMFs have been applied there has been (i) little consensus on TMF selection (ii) limited description of selection rationale and (iii) lack of clarity over how TMFs inform research. We consider this to represent an opportunity to improve implementation science's translation to clinical AI research and clinical AI into practice by promoting the rigor and frequency of TMF application. We recommend that the finite resources of the implementation science community are diverted toward increasing accessibility and engagement with theory informed practices. The considered application of theories, models and frameworks (TMF) are thought to contribute to the impact of implementation science on the translation of innovations into real-world care. The frequency and nature of TMF use are yet to be described within digital health innovations, including the prominent field of clinical AI. A well-known implementation gap, coined as the "AI chasm" continues to limit the impact of clinical AI on real-world care. From this bibliometric study of the frequency and quality of TMF use within qualitative clinical AI research, we found that TMFs are usually not applied, their selection is highly varied between studies and there is not often a convincing rationale for their selection. Promoting the rigor and frequency of TMF use appears to present an opportunity to improve the translation of clinical AI into practice

Про місце антитромботичної терапії у веденні пацієнтів з фібриляцією передсердь

Ішемічні інсульти на фоні ФП часто фатальні, а ті пацієнти що виживають, зазвичай, залишаються з більш вираженою інвалідністю, через наслідки інсульту та більш схильні до повторних інсультів, ніж пацієнти, у яких гостре порушення мозкового кровообігу виникають з інших причин. Як наслідок, ризик смерті від інсульту, обумовлений ФП вдвічі вище, а вартість лікування такого пацієнта зростає в 1,5 рази

Target Product Profile for a Machine Learning–Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study

\ua9 2024 JMIR Publications Inc.. All rights reserved.Background: Diabetic eye screening (DES) represents a significant opportunity for the application of machine learning (ML) technologies, which may improve clinical and service outcomes. However, successful integration of ML into DES requires careful product development, evaluation, and implementation. Target product profiles (TPPs) summarize the requirements necessary for successful implementation so these can guide product development and evaluation. Objective: This study aims to produce a TPP for an ML-automated retinal imaging analysis software (ML-ARIAS) system for use in DES in England. Methods: This work will consist of 3 phases. Phase 1 will establish the characteristics to be addressed in the TPP. A list of candidate characteristics will be generated from the following sources: an overview of systematic reviews of diagnostic test TPPs; a systematic review of digital health TPPs; and the National Institute for Health and Care Excellence’s Evidence Standards Framework for Digital Health Technologies. The list of characteristics will be refined and validated by a study advisory group (SAG) made up of representatives from key stakeholders in DES. This includes people with diabetes; health care professionals; health care managers and leaders; and regulators and policy makers. In phase 2, specifications for these characteristics will be drafted following a series of semistructured interviews with participants from these stakeholder groups. Data collected from these interviews will be analyzed using the shortlist of characteristics as a framework, after which specifications will be drafted to create a draft TPP. Following approval by the SAG, in phase 3, the draft will enter an internet-based Delphi consensus study with participants sought from the groups previously identified, as well as ML-ARIAS developers, to ensure feasibility. Participants will be invited to score characteristic and specification pairs on a scale from “definitely exclude” to “definitely include,” and suggest edits. The document will be iterated between rounds based on participants’ feedback. Feedback on the draft document will be sought from a group of ML-ARIAS developers before its final contents are agreed upon in an in-person consensus meeting. At this meeting, representatives from the stakeholder groups previously identified (minus ML-ARIAS developers, to avoid bias) will be presented with the Delphi results and feedback of the user group and asked to agree on the final contents by vote. Results: Phase 1 was completed in November 2023. Phase 2 is underway and expected to finish in March 2024. Phase 3 is expected to be complete in July 2024. Conclusions: The multistakeholder development of a TPP for an ML-ARIAS for use in DES in England will help developers produce tools that serve the needs of patients, health care providers, and their staff. The TPP development process will also provide methods and a template to produce similar documents in other disease areas

The behavior of osteoblast-like cells on various substrates with functional blocking of integrin-β1 and integrin-β3

This study was designed to examine the influence of integrin subunit-β1 and subunit-β3 on the behavior of primary osteoblast-like cells, cultured on calcium phosphate (CaP)-coated and non coated titanium (Ti). Osteoblast-like cells were incubated with specific monoclonal antibodies against integrin-β1 and integrin-β3 to block the integrin function. Subsequently, cells were seeded on Ti discs, either non coated or provided with a 2 μm carbonated hydroxyapatite coating using Electrostatic Spray Deposition. Results showed that on CaP coatings, cellular attachment was decreased after a pre-treatment with either anti-integrin-β1 or anti-integrin-β3 antibodies. On Ti, cell adhesion was only slightly affected after a pre-treatment with anti-integrin-β3 antibodies. Scanning electron microscopy showed that on both types of substrate, cellular morphology was not changed after a pre-treatment with either antibody. With quantitative PCR, it was shown for both substrates that mRNA expression of integrin-β1 was increased after a pre-treatment with either anti-integrin-β1 or anti-integrin-β3 antibodies. Furthermore, after a pre-treatment with either antibody, mRNA expression of integrin-β3 and ALP was decreased, on both types of substrate. In conclusion, osteoblast-like cells have the ability to compensate to great extent for the blocking strategy as applied here. Still, integrin-β1 and β3 seem to play different roles in attachment, proliferation, and differentiation of osteoblast-like cells, and responses on CaP-coated substrates differ to non coated Ti. Furthermore, the influence on ALP expression suggests involvement of both integrin subunits in signal transduction for cellular differentiation

Opportunities and challenges of a novel cardiac output response to stress (CORS) test to enhance diagnosis of heart failure in primary care: qualitative study.

OBJECTIVE: To explore the role of the novel cardiac output response to stress (CORS), test in the current diagnostic pathway for heart failure and the opportunities and challenges to potential implementation in primary care. DESIGN: Qualitative study using semistructured in-depth interviews which were audio recorded and transcribed verbatim. Data from the interviews were analysed thematically using an inductive approach. SETTING: Newcastle upon Tyne, UK. PARTICIPANTS: Fourteen healthcare professionals (six males, eight females) from primary (general practitioners (GPs), nurses, healthcare assistant, practice managers) and secondary care (consultant cardiologists). RESULTS: Four themes relating to opportunities and challenges surrounding the implementation of the new diagnostic technology were identified. These reflected that the adoption of CORS test would be an advantage to primary care but the test had barriers to implementation which include: establishment of clinical utility, suitability for immobile patients and cost implication to GP practices. CONCLUSION: The development of a simple non-invasive clinical test to accelerate the diagnosis of heart failure in primary care maybe helpful to reduce unnecessary referrals to secondary care. The CORS test has the potential to serve this purpose; however, factors such as cost effectiveness, diagnostic accuracy and seamless implementation in primary care have to be fully explored.This study was funded by the UK Medical Research Council Confidence in Concept Scheme grant to DGJ (grant no. BH161161). SC and NO are supported by the European Horizon 2020 research and innovation programme under grant agreement no 777204. SG is supported by the NIHR MEDTEch In Vitro Diagnostics. DGJ is supported by the UK Research Councils’ Newcastle Centre for Ageing and Vitality (grant no. L016354)

Ectopic bone formation in cell-seeded poly(ethylene oxide)/poly(butylene terephthalate) copolymer scaffolds of varying porosity

Scaffolds from poly(ethylene oxide) and poly(butylene terephthalate), PEOT/PBT, with a PEO molecular weight of 1,000 and a PEOT content of 70 weight% (1000PEOT70PBT30) were prepared by leaching salt particles (425–500 μm). Scaffolds of 73.5, 80.6 and 85.0% porosity were treated with a CO2 gas plasma and seeded with rat bone marrow stromal cells (BMSCs). After in vitro culture for 7 days (d) in an osteogenic medium the scaffolds were subcutaneously implanted for 4 weeks in nude mice. Poly(d, l-lactide) (PDLLA) and biphasic calcium phosphate (BCP) scaffolds were included as references. After 4 weeks (wks) all scaffolds showed ectopic formation of bone and bone marrow. For the scaffolds of different porosities, no significant differences were observed in the relative amounts of bone (7–9%) and bone marrow (6–11%) formed, even though micro computed tomography (μ-CT) data showed considerable differences in accessible pore volume and surface area. 1000PEOT70PBT30 scaffolds with a porosity of 85% could not maintain their original shape in vivo. Surprisingly, 1000PEOT70PBT30 scaffolds with a porosity of 73.5% showed cartilage formation. This cartilage formation is most likely due to poorly accessible pores in the scaffolds, as was observed in histological sections. μ-CT data showed a considerably smaller accessible pore volume (as a fraction of the total volume) than in 1000PEOT70PBT30 scaffolds of 80.6 and 85.0% porosity. BMSC seeded PDLLA (83.5% porosity) and BCP scaffolds (29% porosity) always showed considerably more bone and bone marrow formation (bone marrow formation is approximately 40%) and less fibrous tissue ingrowth than the 1000PEOT70PBT30 scaffolds. The scaffold material itself can be of great influence. In more hydrophobic and rigid scaffolds like the PDLLA or BCP scaffolds, the accessibility of the pore structure is more likely to be preserved under the prevailing physiological conditions than in the case of hydrophilic 1000PEOT70PBT30 scaffolds. Scaffolds prepared from other PEOT/PBT polymer compositions, might prove to be more suited

Microcalcifications in breast cancer: novel insights into the molecular mechanism and functional consequence of mammary mineralisation.

BACKGROUND: Mammographic microcalcifications represent one of the most reliable features of nonpalpable breast cancer yet remain largely unexplored and poorly understood. METHODS: We report a novel model to investigate the in vitro mineralisation potential of a panel of mammary cell lines. Primary mammary tumours were produced by implanting tumourigenic cells into the mammary fat pads of female BALB/c mice. RESULTS: Hydroxyapatite (HA) was deposited only by the tumourigenic cell lines, indicating mineralisation potential may be associated with cell phenotype in this in vitro model. We propose a mechanism for mammary mineralisation, which suggests that the balance between enhancers and inhibitors of physiological mineralisation are disrupted. Inhibition of alkaline phosphatase and phosphate transport prevented mineralisation, demonstrating that mineralisation is an active cell-mediated process. Hydroxyapatite was found to enhance in vitro tumour cell migration, while calcium oxalate had no effect, highlighting potential consequences of calcium deposition. In addition, HA was also deposited in primary mammary tumours produced by implanting the tumourigenic cells into the mammary fat pads of female BALB/c mice. CONCLUSION: This work indicates that formation of mammary HA is a cell-specific regulated process, which creates an osteomimetic niche potentially enhancing breast tumour progression. Our findings point to the cells mineralisation potential and the microenvironment regulating it, as a significant feature of breast tumour development

Materials in particulate form for tissue engineering. 2 Applications in bone

Materials in particulate form have been the subjects of intensive research in view of their use as drug delivery systems. While within this application there are still issues to be addressed, these systems are now being regarded as having a great potential for tissue engineering applications. Bone repair is a very demanding task, due to the specific characteristics of skeletal tissues, and the design of scaffolds for bone tissue engineering presents several difficulties. Materials in particulate form are now seen as a means of achieving higher control over parameters such as porosity, pore size, surface area and the mechanical properties of the scaffold. These materials also have the potential to incorporate biologically active molecules for release and to serve as carriers for cells. It is believed that the combination of these features would create a more efficient approach towards regeneration. This review focuses on the application ofmaterials in particulate formfor bone tissue engineering. A brief overview of bone biology and the healing process is also provided in order to place the application in its broader context. An original compilation of molecules with a documented role in bone tissue biology is listed, as they have the potential to be used in bone tissue engineering strategies. To sum up this review, examples of works addressing the above aspects are presented