{"title":"协调","authors":"H. Vrijhoef","doi":"10.1177/20534345231182882","DOIUrl":null,"url":null,"abstract":"Artificial Intelligence (AI) systems have been increasingly used in health care with the potential that such systems may help develop and augment the capacity of humans in diagnostics, therapeutics, and management of patient care and health care systems. It is claimed that AI systems have the capability to transform health care by, for example, improving risk prediction, augmenting patient– care provider relationships, and optimizing operations and resource allocation. Moreover, it is indicated that AI will be helping the complete journey of patients in terms of prehospital alert and in-hospital stay, and eventually, creating a pathway for post-hospital care. In a rapid review covering the evidence base for promising AI application scenarios for nursing care, Seibert et al. found that from a sample of 292 included studies, most (29.8%) describe AI applications in hospital settings. Further, they report that ‘care coordination and communication are frequent topics, which among others, include AI approaches classifying information in nursing documentation, supporting decision-making, and yielding information for coordination and continuity of care’. However, only a few publications went beyond proof-of-concept studies and few studies have assessed the effects of AI on clinical and organizational outcomes. In a perspective piece, London writes that the ability of AI systems to overcome fragmented, uncoordinated, and unwarranted medical practices is frustrated by the degree to which the ecosystems in which AI systems are being developed suffer from these same shortcomings. Moreover, he argues that the current state of AI has the potential to simply add another dimension to unnecessary variation in clinical care. To get a better grip on the value of AI for improving patient care, London points to applying a framework for indicating the level of maturity of AI systems and the level of evidence supporting specific claims to clinical utility. Further, he makes a point for implementation science to play a greater role in structuring and evaluating proposals to implement AI systems in healthcare settings. To stimulate research in this field and to clarify whether, how and when AI lives up to its promise regarding care coordination, the International Journal of Care Coordination will launch a special issue inviting authors to submit relevant work. Please visit the journal’s website for details about the special issue on CoordinAtIon scheduled for early 2024. In the current issue of the International Journal of Care Coordination, Kokorelias et al. present the findings of a scoping review regarding the implementation characteristics of dementia-specific navigation programs to help the integration of care across various settings. Based on 22 studies, mostly from the United States, key factors to the successful implementation of navigation programs for persons living with dementia were identified. With these factors fitting the constructs of the Consolidated Framework for Implementation Research (CFIR), a theoretical foundation to guide the implementation of dementia-specific navigation was provided. By exploring the experiences of older adults with complex care needs who have received services from a Canadian hospital-to-home transition patient navigation program, Kokorelias et al. were able to share important lessons. One important insight from this qualitative study is that patient navigators are well-positioned to improve the quality of care delivered to community-dwelling older adults and that they may address gaps in the coordination of care across multiple healthcare settings. Kallio et al. explored how future professionals in the field of service provision to children with special needs are being prepared for interprofessional collaboration in the Finnish context. From 24 curricula at eight universities, 38 courses focused on interprofessional collaboration. Considering the need for interprofessional collaboration, Kallio et al. found it contradictory that most of these courses were provided exclusively to a certain study programme without interaction with other disciplines. Important recommendations follow from their analysis that may hold relevance for studies in Finland and elsewhere. The final paper in this issue of the International Journal of Care Coordination is a focus article by Hynes and Thomas who propose a new integrated theoretical model of healthcare and care coordination. They argue that whereas care models have evolved to measure aspects of care coordination, current theoretical models remained unchanged. Their proposed model is expected to serve as Editorial","PeriodicalId":43751,"journal":{"name":"International Journal of Care Coordination","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CoordinAtIon\",\"authors\":\"H. 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Further, they report that ‘care coordination and communication are frequent topics, which among others, include AI approaches classifying information in nursing documentation, supporting decision-making, and yielding information for coordination and continuity of care’. However, only a few publications went beyond proof-of-concept studies and few studies have assessed the effects of AI on clinical and organizational outcomes. In a perspective piece, London writes that the ability of AI systems to overcome fragmented, uncoordinated, and unwarranted medical practices is frustrated by the degree to which the ecosystems in which AI systems are being developed suffer from these same shortcomings. Moreover, he argues that the current state of AI has the potential to simply add another dimension to unnecessary variation in clinical care. To get a better grip on the value of AI for improving patient care, London points to applying a framework for indicating the level of maturity of AI systems and the level of evidence supporting specific claims to clinical utility. Further, he makes a point for implementation science to play a greater role in structuring and evaluating proposals to implement AI systems in healthcare settings. To stimulate research in this field and to clarify whether, how and when AI lives up to its promise regarding care coordination, the International Journal of Care Coordination will launch a special issue inviting authors to submit relevant work. Please visit the journal’s website for details about the special issue on CoordinAtIon scheduled for early 2024. In the current issue of the International Journal of Care Coordination, Kokorelias et al. present the findings of a scoping review regarding the implementation characteristics of dementia-specific navigation programs to help the integration of care across various settings. Based on 22 studies, mostly from the United States, key factors to the successful implementation of navigation programs for persons living with dementia were identified. With these factors fitting the constructs of the Consolidated Framework for Implementation Research (CFIR), a theoretical foundation to guide the implementation of dementia-specific navigation was provided. By exploring the experiences of older adults with complex care needs who have received services from a Canadian hospital-to-home transition patient navigation program, Kokorelias et al. were able to share important lessons. One important insight from this qualitative study is that patient navigators are well-positioned to improve the quality of care delivered to community-dwelling older adults and that they may address gaps in the coordination of care across multiple healthcare settings. Kallio et al. explored how future professionals in the field of service provision to children with special needs are being prepared for interprofessional collaboration in the Finnish context. From 24 curricula at eight universities, 38 courses focused on interprofessional collaboration. Considering the need for interprofessional collaboration, Kallio et al. found it contradictory that most of these courses were provided exclusively to a certain study programme without interaction with other disciplines. Important recommendations follow from their analysis that may hold relevance for studies in Finland and elsewhere. The final paper in this issue of the International Journal of Care Coordination is a focus article by Hynes and Thomas who propose a new integrated theoretical model of healthcare and care coordination. They argue that whereas care models have evolved to measure aspects of care coordination, current theoretical models remained unchanged. 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Artificial Intelligence (AI) systems have been increasingly used in health care with the potential that such systems may help develop and augment the capacity of humans in diagnostics, therapeutics, and management of patient care and health care systems. It is claimed that AI systems have the capability to transform health care by, for example, improving risk prediction, augmenting patient– care provider relationships, and optimizing operations and resource allocation. Moreover, it is indicated that AI will be helping the complete journey of patients in terms of prehospital alert and in-hospital stay, and eventually, creating a pathway for post-hospital care. In a rapid review covering the evidence base for promising AI application scenarios for nursing care, Seibert et al. found that from a sample of 292 included studies, most (29.8%) describe AI applications in hospital settings. Further, they report that ‘care coordination and communication are frequent topics, which among others, include AI approaches classifying information in nursing documentation, supporting decision-making, and yielding information for coordination and continuity of care’. However, only a few publications went beyond proof-of-concept studies and few studies have assessed the effects of AI on clinical and organizational outcomes. In a perspective piece, London writes that the ability of AI systems to overcome fragmented, uncoordinated, and unwarranted medical practices is frustrated by the degree to which the ecosystems in which AI systems are being developed suffer from these same shortcomings. Moreover, he argues that the current state of AI has the potential to simply add another dimension to unnecessary variation in clinical care. To get a better grip on the value of AI for improving patient care, London points to applying a framework for indicating the level of maturity of AI systems and the level of evidence supporting specific claims to clinical utility. Further, he makes a point for implementation science to play a greater role in structuring and evaluating proposals to implement AI systems in healthcare settings. To stimulate research in this field and to clarify whether, how and when AI lives up to its promise regarding care coordination, the International Journal of Care Coordination will launch a special issue inviting authors to submit relevant work. Please visit the journal’s website for details about the special issue on CoordinAtIon scheduled for early 2024. In the current issue of the International Journal of Care Coordination, Kokorelias et al. present the findings of a scoping review regarding the implementation characteristics of dementia-specific navigation programs to help the integration of care across various settings. Based on 22 studies, mostly from the United States, key factors to the successful implementation of navigation programs for persons living with dementia were identified. With these factors fitting the constructs of the Consolidated Framework for Implementation Research (CFIR), a theoretical foundation to guide the implementation of dementia-specific navigation was provided. By exploring the experiences of older adults with complex care needs who have received services from a Canadian hospital-to-home transition patient navigation program, Kokorelias et al. were able to share important lessons. One important insight from this qualitative study is that patient navigators are well-positioned to improve the quality of care delivered to community-dwelling older adults and that they may address gaps in the coordination of care across multiple healthcare settings. Kallio et al. explored how future professionals in the field of service provision to children with special needs are being prepared for interprofessional collaboration in the Finnish context. From 24 curricula at eight universities, 38 courses focused on interprofessional collaboration. Considering the need for interprofessional collaboration, Kallio et al. found it contradictory that most of these courses were provided exclusively to a certain study programme without interaction with other disciplines. Important recommendations follow from their analysis that may hold relevance for studies in Finland and elsewhere. The final paper in this issue of the International Journal of Care Coordination is a focus article by Hynes and Thomas who propose a new integrated theoretical model of healthcare and care coordination. They argue that whereas care models have evolved to measure aspects of care coordination, current theoretical models remained unchanged. Their proposed model is expected to serve as Editorial
期刊介绍:
The International Journal of Care Coordination (formerly published as the International Journal of Care Pathways) provides an international forum for the latest scientific research in care coordination. The Journal publishes peer-reviewed original articles which describe basic research to a multidisciplinary field as well as other broader approaches and strategies hypothesized to improve care coordination. The Journal offers insightful overviews and reflections on innovation, underlying issues, and thought provoking opinion pieces in related fields. Articles from multidisciplinary fields are welcomed from leading health care academics and policy-makers. Published articles types include original research, reviews, guidelines papers, book reviews, and news items.