The Development of Electronic Health and Artificial Intelligence in Surgery after the SARS-CoV-2 Pandemic—A Scoping Review

Background: SARS-CoV-2 has significantly transformed the healthcare environment, and it has triggered the development of electronic health and artificial intelligence mechanisms, for instance. In this overview, we concentrated on enhancing the two concepts in surgery after the pandemic, and we examined the factors on a global scale. Objective: The primary goal of this scoping review is to elaborate on how surgeons have used eHealth and AI before; during; and after the current global pandemic. More specifically, this review focuses on the empowerment of the concepts of electronic health and artificial intelligence after the pandemic; which mainly depend on the efforts of countries to advance the notions of surgery. Design: The use of an online search engine was the most applied method. The publication years of all the studies included in the study ranged from 2013 to 2021. Out of the reviewed studies; forty-four qualified for inclusion in the review. Discussion: We evaluated the prevalence of the concepts in different continents such as the United States; Europe; Asia; the Middle East; and Africa. Our research reveals that the success of eHealth and artificial intelligence adoption primarily depends on the efforts of countries to advance the notions in surgery. Conclusions: The study’s primary limitation is insufficient information on eHealth and artificial intelligence concepts; particularly in developing nations. Future research should focus on establishing methods of handling eHealth and AI challenges around confidentiality and data security.

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Health Inequalities in Children and Adolescents: A Scoping Review of the Mediating and Moderating Effects of Family Characteristics

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18157739 ◽

2021 ◽

Vol 18 (15) ◽

pp. 7739

Author(s):

Miriam Blume ◽

Petra Rattay ◽

Stephanie Hoffmann ◽

Jacob Spallek ◽

Lydia Sander ◽

...

Keyword(s):

Mental Health ◽

Children And Adolescents ◽

Health Inequalities ◽

Scoping Review ◽

The United States ◽

Family Characteristics ◽

Future Research ◽

Childhood And Adolescence ◽

Moderating Effects ◽

Scoping Reviews

This scoping review systematically mapped evidence of the mediating and moderating effects of family characteristics on health inequalities in school-aged children and adolescents (6–18 years) in countries with developed economies in Europe and North America. We conducted a systematic scoping review following the PRISMA extension for Scoping Reviews recommendations. We searched the PubMed, PsycINFO and Scopus databases. Two reviewers independently screened titles, abstracts and full texts. Evidence was synthesized narratively. Of the 12,403 records initially identified, 50 articles were included in the synthesis. The included studies were conducted in the United States (n = 27), Europe (n = 18), Canada (n = 3), or in multiple countries combined (n = 2). We found that mental health was the most frequently assessed health outcome. The included studies reported that different family characteristics mediated or moderated health inequalities. Parental mental health, parenting practices, and parent-child-relationships were most frequently examined, and were found to be important mediating or moderating factors. In addition, family conflict and distress were relevant family characteristics. Future research should integrate additional health outcomes besides mental health, and attempt to integrate the complexity of families. The family characteristics identified in this review represent potential starting points for reducing health inequalities in childhood and adolescence.

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Research and application of artificial intelligence based on electronic health record data from patients with cancer: a systematic review (Preprint)

10.2196/preprints.33799 ◽

2021 ◽

Author(s):

Xinyu Yang ◽

Dongmei Mu ◽

Hao Peng ◽

Hua Li ◽

Ying Wang ◽

...

Keyword(s):

Artificial Intelligence ◽

Electronic Health Records ◽

Ensemble Methods ◽

Future Research ◽

Electronic Health Record Data ◽

Health Records ◽

Patients With Cancer ◽

Cancer Management ◽

Treatment And Prevention ◽

Electronic Health

BACKGROUND With the accumulation of electronic health records data and the development of artificial intelligence, patients with cancer urgently need new evidence of more personalized clinical and demographic characteristics and more sophisticated treatment and prevention strategies. However, no research has systematically analyzed the application and significance of electronic health records and artificial intelligence in cancer care. OBJECTIVE In this study, we reviewed the literature on the application of AI based on EHR data from patients with cancer, hoping to provide reference for subsequent researchers, and help accelerate the application of EHR data and AI technology in the field of cancer, so as to help patients get more scientific and accurate treatment. METHODS Three databases were systematically searched to retrieve potentially relevant articles published from January 2009 to October 2020. A combination of terms related to "electronic health records", "artificial intelligence" and "cancer" was used to search for these publications. RESULTS Of the 1034 articles considered, 148 met the inclusion criteria. The review has shown that ensemble methods and deep learning were on the rise. It presented the representative literatures on the subfield of cancer diagnosis, treatment and care. In addition, the vast majority of studies in this area were based on private institutional databases, resulting in poor portability of the proposed methodology process. CONCLUSIONS The use of new methods and electronic health records data sharing and fusion were recommended for future research. With the help of specialists, artificial intelligence and the mining of massive electronic medical records could provide great opportunities for improving cancer management.

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Complexity In The Context of Palliative Care: A Scoping Review

10.21203/rs.3.rs-969011/v1 ◽

2021 ◽

Author(s):

Hironori Ohinata ◽

Maho Aoyama ◽

Mitsunori Miyashita

Keyword(s):

Palliative Care ◽

Scoping Review ◽

Healthcare Providers ◽

The United States ◽

Patient Specific ◽

Future Research ◽

Care Needs ◽

Living Situation ◽

Research Activities ◽

Specific Factors

Abstract Background: Understanding the factors of complexity of patients in palliative care is very important for healthcare providers in addressing the care needs of their patients. However, the healthcare providers’ perception of the factors of complexity in palliative care lacks a common understanding. This study aimed to determine the scope of research activities and specific factors of complexity in the context of palliative care.Methods: A scoping literature review was performed, following the methods described by the Joanna Briggs Institute. We conducted an electronic literature search in MEDLINE (Ovid), PsycINFO, Web of Science Core Collection, and CINAHL, examining literature from May 1972 to 2020.Results: We identified 32 peer-reviewed articles published in English before 2020. The target literature mainly originated in Europe and the United States. The research methods included quantitative studies (n=13), qualitative studies (n=12), case studies (n=3), and reviews (n=4). We reviewed 32 studies and summarized the factors of complexity into three levels: the patient’s level, the healthcare setting level, and the socio-cultural landscape level. We identified factors affecting patient-specific complexity, including sex, race, age, living situation, family burden, resources, treatment, decision-making, communication, prognosis, disease, and comorbidity/complexity. Other factors identified as contributing to patient complexity were the interaction of physical, psychological, social, and spiritual categories, as well as the healthcare providers’ confidence and skills, and the socio-cultural components.Conclusions: This scoping review shows specific factors of complexity and future challenges in the context of palliative care. Future research should include the factors of complexity identified in this review and conduct longitudinal studies on the interactions among them. In addition, it is necessary to examine specific complexity factors in patients from various social and ethnic backgrounds.

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Towards a Stakeholder-Oriented Blockchain-Based Architecture for Electronic Health Records: Design Science Research Study

Journal of Medical Internet Research ◽

10.2196/13585 ◽

2019 ◽

Vol 21 (10) ◽

pp. e13585 ◽

Cited By ~ 14

Author(s):

Jan Heinrich Beinke ◽

Christian Fitte ◽

Frank Teuteberg

Keyword(s):

Electronic Health Records ◽

Data Security ◽

Design Science ◽

Science Research ◽

Design Science Research ◽

Future Research ◽

Health Records ◽

Blockchain Technology ◽

Recommendations For Action ◽

Electronic Health

Background Data security issues still constitute the main reason for the sluggish dissemination of electronic health records (EHRs). Given that blockchain technology offers the possibility to verify transactions through a decentralized network, it may serve as a solution to secure health-related data. Therefore, we have identified stakeholder-specific requirements and propose a blockchain-based architecture for EHRs, while referring to the already existing scientific discussions on the potential of blockchain for use in EHRs. Objective This study aimed to introduce blockchain technology for EHRs, based on identifying stakeholders and systematically eliciting their requirements, and to discuss the key benefits (KBs) and key challenges (KCs) of blockchain technology in the context of EHRs. Methods The blockchain-based architecture was developed in the framework of the design science research paradigm. The requirements were identified using a structured literature review and interviews with nine health care experts. Subsequently, the proposed architecture was evaluated using 4 workshops with 15 participants. Results We identified three major EHR stakeholder groups and 34 respective requirements. On this basis, we developed a five-layer architecture. The subsequent evaluation of the artifact was followed by the discussion of 12 KBs and 12 KCs of a blockchain-based architecture for EHRs. To address the KCs, we derived five recommendations for action for science and practice. Conclusions Our findings indicate that blockchain technology offers considerable potential to advance EHRs. Improvements to currently available EHR solutions are expected, for instance, in the areas of data security, traceability, and automation by smart contracts. Future research could examine the patient’s acceptance of blockchain-based EHRs and cost-benefit analyses.

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Towards a Stakeholder-Oriented Blockchain-Based Architecture for Electronic Health Records: Design Science Research Study (Preprint)

10.2196/preprints.13585 ◽

2019 ◽

Author(s):

Jan Heinrich Beinke ◽

Christian Fitte ◽

Frank Teuteberg

Keyword(s):

Electronic Health Records ◽

Data Security ◽

Design Science ◽

Science Research ◽

Design Science Research ◽

Future Research ◽

Health Records ◽

Blockchain Technology ◽

Recommendations For Action ◽

Electronic Health

BACKGROUND Data security issues still constitute the main reason for the sluggish dissemination of electronic health records (EHRs). Given that blockchain technology offers the possibility to verify transactions through a decentralized network, it may serve as a solution to secure health-related data. Therefore, we have identified stakeholder-specific requirements and propose a blockchain-based architecture for EHRs, while referring to the already existing scientific discussions on the potential of blockchain for use in EHRs. OBJECTIVE This study aimed to introduce blockchain technology for EHRs, based on identifying stakeholders and systematically eliciting their requirements, and to discuss the key benefits (KBs) and key challenges (KCs) of blockchain technology in the context of EHRs. METHODS The blockchain-based architecture was developed in the framework of the design science research paradigm. The requirements were identified using a structured literature review and interviews with nine health care experts. Subsequently, the proposed architecture was evaluated using 4 workshops with 15 participants. RESULTS We identified three major EHR stakeholder groups and 34 respective requirements. On this basis, we developed a five-layer architecture. The subsequent evaluation of the artifact was followed by the discussion of 12 KBs and 12 KCs of a blockchain-based architecture for EHRs. To address the KCs, we derived five recommendations for action for science and practice. CONCLUSIONS Our findings indicate that blockchain technology offers considerable potential to advance EHRs. Improvements to currently available EHR solutions are expected, for instance, in the areas of data security, traceability, and automation by smart contracts. Future research could examine the patient’s acceptance of blockchain-based EHRs and cost-benefit analyses.

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Accelerating the Appropriate Adoption of Artificial Intelligence in Health Care: Protocol for a Multistepped Approach

JMIR Research Protocols ◽

10.2196/30940 ◽

2021 ◽

Vol 10 (10) ◽

pp. e30940

Author(s):

David Wiljer ◽

Mohammad Salhia ◽

Elham Dolatabadi ◽

Azra Dhalla ◽

Caitlin Gillan ◽

...

Keyword(s):

Artificial Intelligence ◽

Health Care ◽

Health Care Providers ◽

Scoping Review ◽

The United States ◽

Data Driven ◽

Data Sets ◽

Health Providers ◽

Care Providers ◽

Environmental Scan

Background Significant investments and advances in health care technologies and practices have created a need for digital and data-literate health care providers. Artificial intelligence (AI) algorithms transform the analysis, diagnosis, and treatment of medical conditions. Complex and massive data sets are informing significant health care decisions and clinical practices. The ability to read, manage, and interpret large data sets to provide data-driven care and to protect patient privacy are increasingly critical skills for today’s health care providers. Objective The aim of this study is to accelerate the appropriate adoption of data-driven and AI-enhanced care by focusing on the mindsets, skillsets, and toolsets of point-of-care health providers and their leaders in the health system. Methods To accelerate the adoption of AI and the need for organizational change at a national level, our multistepped approach includes creating awareness and capacity building, learning through innovation and adoption, developing appropriate and strategic partnerships, and building effective knowledge exchange initiatives. Education interventions designed to adapt knowledge to the local context and address any challenges to knowledge use include engagement activities to increase awareness, educational curricula for health care providers and leaders, and the development of a coaching and practice-based innovation hub. Framed by the Knowledge-to-Action framework, we are currently in the knowledge creation stage to inform the curricula for each deliverable. An environmental scan and scoping review were conducted to understand the current state of AI education programs as reported in the academic literature. Results The environmental scan identified 24 AI-accredited programs specific to health providers, of which 11 were from the United States, 6 from Canada, 4 from the United Kingdom, and 3 from Asian countries. The most common curriculum topics across the environmental scan and scoping review included AI fundamentals, applications of AI, applied machine learning in health care, ethics, data science, and challenges to and opportunities for using AI. Conclusions Technologies are advancing more rapidly than organizations, and professionals can adopt and adapt to them. To help shape AI practices, health care providers must have the skills and abilities to initiate change and shape the future of their discipline and practices for advancing high-quality care within the digital ecosystem. International Registered Report Identifier (IRRID) PRR1-10.2196/30940

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Explainable artificial intelligence models using real-world electronic health record data: a systematic scoping review

Journal of the American Medical Informatics Association ◽

10.1093/jamia/ocaa053 ◽

2020 ◽

Vol 27 (7) ◽

pp. 1173-1185 ◽

Cited By ~ 2

Author(s):

Seyedeh Neelufar Payrovnaziri ◽

Zhaoyi Chen ◽

Pablo Rengifo-Moreno ◽

Tim Miller ◽

Jiang Bian ◽

...

Keyword(s):

Artificial Intelligence ◽

Electronic Health Record ◽

Scoping Review ◽

Real World ◽

Research Trend ◽

Health Record ◽

Electronic Health Record Data ◽

Explainable Artificial Intelligence ◽

Record Data ◽

Electronic Health

Abstract Objective To conduct a systematic scoping review of explainable artificial intelligence (XAI) models that use real-world electronic health record data, categorize these techniques according to different biomedical applications, identify gaps of current studies, and suggest future research directions. Materials and Methods We searched MEDLINE, IEEE Xplore, and the Association for Computing Machinery (ACM) Digital Library to identify relevant papers published between January 1, 2009 and May 1, 2019. We summarized these studies based on the year of publication, prediction tasks, machine learning algorithm, dataset(s) used to build the models, the scope, category, and evaluation of the XAI methods. We further assessed the reproducibility of the studies in terms of the availability of data and code and discussed open issues and challenges. Results Forty-two articles were included in this review. We reported the research trend and most-studied diseases. We grouped XAI methods into 5 categories: knowledge distillation and rule extraction (N = 13), intrinsically interpretable models (N = 9), data dimensionality reduction (N = 8), attention mechanism (N = 7), and feature interaction and importance (N = 5). Discussion XAI evaluation is an open issue that requires a deeper focus in the case of medical applications. We also discuss the importance of reproducibility of research work in this field, as well as the challenges and opportunities of XAI from 2 medical professionals’ point of view. Conclusion Based on our review, we found that XAI evaluation in medicine has not been adequately and formally practiced. Reproducibility remains a critical concern. Ample opportunities exist to advance XAI research in medicine.

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Scoping Review of Nursing Case Management in the United States

Clinical Nursing Research ◽

10.1177/1054773817717861 ◽

2017 ◽

Vol 27 (8) ◽

pp. 1002-1016 ◽

Cited By ~ 7

Author(s):

Jee Young Joo ◽

Diane L. Huber

Keyword(s):

United States ◽

Case Management ◽

Scoping Review ◽

The United States ◽

Case Managers ◽

Future Research ◽

Theoretical Frameworks ◽

Process Measures ◽

Definition Of ◽

Role Confusion

The purpose of this study is to identify issues of case management (CM) interventions in the United States in recent studies and to identify implications for future research into CM. This study was guided by the following framework for a scoping review. Multiple electronic databases were searched to identify studies published between 2007 and 2016 in the United States and related to nursing CM. Five weaknesses were identified: no clear and consistent definition of CM, lack of theoretical frameworks, lack of standard guidelines in CM practice, lack of precise CM dosage and of process measures, and limited reports of explicit role of nurse case managers and role confusion by nurses. Three strengths were also identified. More rigorous and continuous efforts to develop theoretical frameworks and evaluation tools, as well as clear definitions and precise role descriptions, are required for future research and practice into CM.

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The Water Footprint of the United States

Water ◽

10.3390/w12113286 ◽

2020 ◽

Vol 12 (11) ◽

pp. 3286

Author(s):

Megan Konar ◽

Landon Marston

Keyword(s):

United States ◽

Water Footprint ◽

Virtual Water ◽

The United States ◽

Global Scale ◽

Future Research ◽

Special Issue ◽

Water Flows ◽

Global Water

This paper commemorates the influence of Arjen Y. Hoekstra on water footprint research of the United States. It is part of the Special Issue “In Memory of Prof. Arjen Y. Hoekstra”. Arjen Y. Hoekstra both inspired and enabled a community of scholars to work on understanding the water footprint of the United States. He did this by comprehensively establishing the terminology and methodology that serves as the foundation for water footprint research. His work on the water footprint of humanity at the global scale highlighted the key role of a few nations in the global water footprint of production, consumption, and virtual water trade. This research inspired water scholars to focus on the United States by highlighting its key role amongst world nations. Importantly, he enabled the research of many others by making water footprint estimates freely available. We review the state of the literature on water footprints of the United States, including its water footprint of production, consumption, and virtual water flows. Additionally, we highlight metrics that have been developed to assess the vulnerability, resiliency, sustainability, and equity of sub-national water footprints and domestic virtual water flows. We highlight opportunities for future research.

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Left-Behind Women in the Context of International Migration: A Scoping Review

Journal of Transcultural Nursing ◽

10.1177/1043659620935962 ◽

2020 ◽

Vol 31 (6) ◽

pp. 606-616

Author(s):

Higinio Fernández-Sánchez ◽

Jordana Salma ◽

Patricia Marisol Márquez-Vargas ◽

Bukola Salami

Keyword(s):

Scoping Review ◽

Social Economic ◽

Transnational Migration ◽

Well Being ◽

The United States ◽

Descriptive Statistics ◽

Future Research ◽

Left Behind ◽

Cultural Conditions ◽

Conventional Content Analysis

Introduction: Despite the research on left-behind children, less is known about left-behind women across transnational spaces. The purpose of this scoping review was to assess the extent, range, and nature of the existing body of literature on left-behind women whose partners have migrated across borders. Method: This scoping review was guided by the five-step approach of Arksey and O’Malley. Fifty-four articles that focused on left-behind women across transnational spaces were included. Data were synthesized using descriptive statistics and conventional content analysis. Results: Left-behind women were primarily from Mexico ( n = 13) and the migrants’ place of destination was primarily the United States ( n = 14). We identified two major themes: (a) women’s social, economic and cultural conditions and (b) women’s well-being. Discussion: We identified significant knowledge gaps regarding left-behind women in the context of transnational migration. Implications for future research and practice are discussed.

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