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Mattison G, Canfell OJ, Smith D, Forrester D, Reid D, Töyräs J, Dobbins C. "An excellent servant but a terrible master": Understanding the value of wearables for self-management in people with cystic fibrosis and their healthcare providers - A qualitative study. Int J Med Inform 2024; 189:105532. [PMID: 38925023 DOI: 10.1016/j.ijmedinf.2024.105532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 06/18/2024] [Accepted: 06/24/2024] [Indexed: 06/28/2024]
Abstract
BACKGROUND Wearables hold potential to improve chronic disease self-management in conditions like cystic fibrosis (CF) through remote monitoring, early detection of illness and motivation. Little is known about the acceptability and sustainability of integrating wearables into routine care from the perspectives of people with CF (pwCF) and their treating clinicians. METHODS A cross-sectional qualitative study involving semi-structured interviews with adult pwCF and focus groups comprising members of a CF multidisciplinary team (MDT) were conducted at a specialist CF centre in Australia. A phenomenological orientation underpinned the study. Inductive thematic analysis was performed using the Framework method. The study adhered to the Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist. RESULTS Nine pwCF and eight members of a CF MDT, representing six clinical disciplines, participated in the study. Eight themes were inductively generated from the data, of which four were identified from each group. PwCF valued wearables for providing real-time data to motivate healthy behaviours and support shared goal-setting with healthcare providers. Wearables did not influence adherence to CF-specific self-management practices and had some hardware limitations. Members of the CF MDT recognised potential benefits of remote monitoring and shared goal-setting, but advised caution regarding data accuracy, generating patient anxiety in certain personality traits, and lack of evidence supporting use in CF self-management. CONCLUSIONS Perspectives on integrating wearables into CF care were cautiously optimistic, with emerging risks related to patient anxiety and lack of evidence moderating acceptance.
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Affiliation(s)
- Graeme Mattison
- Queensland Digital Health Centre, The University of Queensland, Brisbane, Australia; The Prince Charles Hospital, Metro North Hospitals and Health Service, Brisbane, Australia; Digital Health Cooperative Research Centre, Sydney Knowledge Hub, The University of Sydney, Sydney, Australia.
| | - Oliver J Canfell
- Queensland Digital Health Centre, The University of Queensland, Brisbane, Australia; Digital Health Cooperative Research Centre, Sydney Knowledge Hub, The University of Sydney, Sydney, Australia; UQ Business School, Faculty of Business, Economics and Law, The University of Queensland, Brisbane, Australia; Department of Nutritional Sciences, Faculty of Life Sciences and Medicine, King's College, London SE1 9NH, UK
| | - Daniel Smith
- The Prince Charles Hospital, Metro North Hospitals and Health Service, Brisbane, Australia; Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Doug Forrester
- The Prince Charles Hospital, Metro North Hospitals and Health Service, Brisbane, Australia; Faculty of Health Sciences, Curtin University, Perth, Australia
| | - David Reid
- The Prince Charles Hospital, Metro North Hospitals and Health Service, Brisbane, Australia; Faculty of Medicine, The University of Queensland, Brisbane, Australia; QIMR Berghofer Institute of Medical Research, Brisbane, Australia
| | - Juha Töyräs
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Australia; Department of Technical Physics, University of Eastern Finland, Kuopio, Finland; Science Service Center, Kuopio University Hospital, Kuopio, Finland
| | - Chelsea Dobbins
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Australia
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Nagappan A, Krasniansky A, Knowles M. Patterns of Ownership and Usage of Wearable Devices in the United States, 2020-2022: Survey Study. J Med Internet Res 2024; 26:e56504. [PMID: 39058548 PMCID: PMC11316147 DOI: 10.2196/56504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 03/31/2024] [Accepted: 06/25/2024] [Indexed: 07/28/2024] Open
Abstract
BACKGROUND Although wearable technology has become increasingly common, comprehensive studies examining its ownership across different sociodemographic groups are limited. OBJECTIVE The aims of this study were to (1) measure wearable device ownership by sociodemographic characteristics in a cohort of US consumers and (2) investigate how these devices are acquired and used for health-related purposes. METHODS Data from the Rock Health Digital Health Consumer Adoption Survey collected from 2020 to 2022 with 23,974 US participants were analyzed. The sample was US Census-matched for demographics, including age, race/ethnicity, gender, and income. The relationship between sociodemographic factors and wearable ownership was explored using descriptive analysis and multivariate logistic regression. RESULTS Of the 23,974 respondents, 10,679 (44.5%) owned wearables. Ownership was higher among younger individuals, those with higher incomes and education levels, and respondents living in urban areas. Compared to those aged 18-24 years, respondents 65 years and older had significantly lower odds of wearable ownership (odds ratio [OR] 0.18, 95% CI 0.16-0.21). Higher annual income (≥US $200,000; OR 2.27, 95% CI 2.01-2.57) and advanced degrees (OR 2.23, 95% CI 2.01-2.48) were strong predictors of ownership. Living in rural areas reduced ownership odds (OR 0.65, 95% CI 0.60-0.72). There was a notable difference in ownership based on gender and health insurance status. Women had slightly higher ownership odds than men (OR 1.10, 95% CI 1.04-1.17). Private insurance increased ownership odds (OR 1.28, 95% CI 1.17-1.40), whereas being uninsured (OR 0.41, 95% CI 0.36-0.47) or on Medicaid (OR 0.75, 95% CI 0.68-0.82) decreased the odds of ownership. Interestingly, minority groups such as non-Hispanic Black (OR 1.14, 95% CI 1.03-1.25) and Hispanic/Latine (OR 1.20, 95% CI 1.10-1.31) respondents showed slightly higher ownership odds than other racial/ethnic groups. CONCLUSIONS Our findings suggest that despite overall growth in wearable ownership, sociodemographic divides persist. The data indicate a need for equitable access strategies as wearables become integral to clinical and public health domains.
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Affiliation(s)
- Ashwini Nagappan
- Department of Health Policy and Management, University of California, Los Angeles, Los Angeles, CA, United States
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Bulaj G, Coleman M, Johansen B, Kraft S, Lam W, Phillips K, Rohaj A. Redesigning Pharmacy to Improve Public Health Outcomes: Expanding Retail Spaces for Digital Therapeutics to Replace Consumer Products That Increase Mortality and Morbidity Risks. PHARMACY 2024; 12:107. [PMID: 39051391 PMCID: PMC11270305 DOI: 10.3390/pharmacy12040107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Revised: 06/26/2024] [Accepted: 07/09/2024] [Indexed: 07/27/2024] Open
Abstract
United States healthcare outcomes, including avoidable mortality rates, are among the worst of high-income countries despite the highest healthcare spending per capita. While community pharmacies contribute to chronic disease management and preventive medicine, they also offer consumer products that increase mortality risks and the prevalence of cardiovascular diseases, diabetes, cancer, and depression. To resolve these contradictions, our perspective article describes opportunities for major pharmacy chains (e.g., CVS Pharmacy and Walgreens) to introduce digital health aisles dedicated to prescription and over-the-counter digital therapeutics (DTx), together with mobile apps and wearables that support disease self-management, wellness, and well-being. We provide an evidence-based rationale for digital health aisles to replace spaces devoted to sugar-sweetened beverages and other unhealthy commodities (alcohol, tobacco) that may increase risks for premature death. We discuss how digital health aisles can serve as marketing and patient education resources, informing customers about commercially available DTx and other technologies that support healthy lifestyles. Since pharmacy practice requires symbiotic balancing between profit margins and patient-centered, value-based care, replacing health-harming products with health-promoting technologies could positively impact prevention of chronic diseases, as well as the physical and mental health of patients and caregivers who visit neighborhood pharmacies in order to pick up medicines.
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Affiliation(s)
- Grzegorz Bulaj
- Department of Medicinal Chemistry, College of Pharmacy, University of Utah, Salt Lake City, UT 84112, USA
| | - Melissa Coleman
- College of Pharmacy, University of Utah, Salt Lake City, UT 84112, USA
| | - Blake Johansen
- College of Pharmacy, University of Utah, Salt Lake City, UT 84112, USA
| | - Sarah Kraft
- Independent Researcher, Salt Lake City, UT 84112, USA
| | - Wayne Lam
- College of Pharmacy, University of Utah, Salt Lake City, UT 84112, USA
| | - Katie Phillips
- College of Pharmacy, University of Utah, Salt Lake City, UT 84112, USA
| | - Aarushi Rohaj
- Department of Medicinal Chemistry, College of Pharmacy, University of Utah, Salt Lake City, UT 84112, USA
- The Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, UT 84112, USA
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Vitali D, Olugbade T, Eccleston C, Keogh E, Bianchi-Berthouze N, de C Williams AC. Sensing behavior change in chronic pain: a scoping review of sensor technology for use in daily life. Pain 2024; 165:1348-1360. [PMID: 38258888 DOI: 10.1097/j.pain.0000000000003134] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 09/26/2023] [Indexed: 01/24/2024]
Abstract
ABSTRACT Technology offers possibilities for quantification of behaviors and physiological changes of relevance to chronic pain, using wearable sensors and devices suitable for data collection in daily life contexts. We conducted a scoping review of wearable and passive sensor technologies that sample data of psychological interest in chronic pain, including in social situations. Sixty articles met our criteria from the 2783 citations retrieved from searching. Three-quarters of recruited people were with chronic pain, mostly musculoskeletal, and the remainder with acute or episodic pain; those with chronic pain had a mean age of 43 (few studies sampled adolescents or children) and 60% were women. Thirty-seven studies were performed in laboratory or clinical settings and the remainder in daily life settings. Most used only 1 type of technology, with 76 sensor types overall. The commonest was accelerometry (mainly used in daily life contexts), followed by motion capture (mainly in laboratory settings), with a smaller number collecting autonomic activity, vocal signals, or brain activity. Subjective self-report provided "ground truth" for pain, mood, and other variables, but often at a different timescale from the automatically collected data, and many studies reported weak relationships between technological data and relevant psychological constructs, for instance, between fear of movement and muscle activity. There was relatively little discussion of practical issues: frequency of sampling, missing data for human or technological reasons, and the users' experience, particularly when users did not receive data in any form. We conclude the review with some suggestions for content and process of future studies in this field.
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Affiliation(s)
- Diego Vitali
- Research Department of Clinical, Educational & Health Psychology, University College London, London, United Kingdom
| | - Temitayo Olugbade
- School of Engineering and Informatics, University of Sussex, Brighton, United Kingdom
- Interaction Centre, University College London, London, United Kingdom
| | - Christoper Eccleston
- Centre for Pain Research, The University of Bath, Bath, United Kingdom
- Department of Experimental, Clinical and Health Psychology, Ghent University, Ghent, Belgium
- Department of Psychology, The University of Helsinki, Helsinki, Finland
| | - Edmund Keogh
- Centre for Pain Research, The University of Bath, Bath, United Kingdom
| | | | - Amanda C de C Williams
- Research Department of Clinical, Educational & Health Psychology, University College London, London, United Kingdom
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Janssen A, Donnelly C, Shaw T. A Taxonomy for Health Information Systems. J Med Internet Res 2024; 26:e47682. [PMID: 38820575 PMCID: PMC11179026 DOI: 10.2196/47682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 10/05/2023] [Accepted: 01/31/2024] [Indexed: 06/02/2024] Open
Abstract
The health sector is highly digitized, which is enabling the collection of vast quantities of electronic data about health and well-being. These data are collected by a diverse array of information and communication technologies, including systems used by health care organizations, consumer and community sources such as information collected on the web, and passively collected data from technologies such as wearables and devices. Understanding the breadth of IT that collect these data and how it can be actioned is a challenge for the significant portion of the digital health workforce that interact with health data as part of their duties but are not for informatics experts. This viewpoint aims to present a taxonomy categorizing common information and communication technologies that collect electronic data. An initial classification of key information systems collecting electronic health data was undertaken via a rapid review of the literature. Subsequently, a purposeful search of the scholarly and gray literature was undertaken to extract key information about the systems within each category to generate definitions of the systems and describe the strengths and limitations of these systems.
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Affiliation(s)
- Anna Janssen
- Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Candice Donnelly
- Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Tim Shaw
- Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
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Polus M, Keikhosrokiani P, Korhonen O, Behutiye W, Isomursu M. Impact of Digital Interventions on the Treatment Burden of Patients With Chronic Conditions: Protocol for a Systematic Review. JMIR Res Protoc 2024; 13:e54833. [PMID: 38652531 PMCID: PMC11077406 DOI: 10.2196/54833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 02/20/2024] [Accepted: 03/13/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND There is great potential for delivering cost-effective, quality health care for patients with chronic conditions through digital interventions. Managing chronic conditions often includes a substantial workload required for adhering to the treatment regimen and negative consequences on the patient's function and well-being. This treatment burden affects adherence to treatment and disease outcomes. Digital interventions can potentially exacerbate the burden but also alleviate it. OBJECTIVE The objective of this review is to identify, summarize, and synthesize the evidence of how digital interventions impact the treatment burden of people with chronic conditions. METHODS The search, selection, and data synthesis processes were designed according to the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) 2015. A systematic search was conducted on October 16, 2023, from databases PubMed, Scopus, Web of Science, ACM, PubMed Central, and CINAHL. RESULTS Preliminary searches have been conducted, and screening has been started. The review is expected to be completed in October 2024. CONCLUSIONS As the number of patients with chronic conditions is increasing, it is essential to design new digital interventions for managing chronic conditions in a way that supports patients with their treatment burden. To the best of our knowledge, the proposed systematic review will be the first review that investigates the impact of digital interventions on the treatment burden of patients. The results of this review will contribute to the field of health informatics regarding knowledge of the treatment burden associated with digital interventions and practical implications for developing better digital health care for patients with chronic conditions. TRIAL REGISTRATION PROSPERO CRD42023477605; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=477605. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/54833.
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Affiliation(s)
- Manria Polus
- Faculty of Information Technology and Electrical Engineering, University of Oulu, Oulu, Finland
- Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Pantea Keikhosrokiani
- Faculty of Information Technology and Electrical Engineering, University of Oulu, Oulu, Finland
- Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Olli Korhonen
- Faculty of Information Technology and Electrical Engineering, University of Oulu, Oulu, Finland
| | - Woubshet Behutiye
- Faculty of Information Technology and Electrical Engineering, University of Oulu, Oulu, Finland
| | - Minna Isomursu
- Faculty of Information Technology and Electrical Engineering, University of Oulu, Oulu, Finland
- Faculty of Medicine, University of Oulu, Oulu, Finland
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7
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Hindelang M, Wecker H, Biedermann T, Zink A. Continuously monitoring the human machine? - A cross-sectional study to assess the acceptance of wearables in Germany. Health Informatics J 2024; 30:14604582241260607. [PMID: 38900846 DOI: 10.1177/14604582241260607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/22/2024]
Abstract
Background: Wearables have the potential to transform healthcare by enabling early detection and monitoring of chronic diseases. This study aimed to assess wearables' acceptance, usage, and reasons for non-use. Methods: Anonymous questionnaires were used to collect data in Germany on wearable ownership, usage behaviour, acceptance of health monitoring, and willingness to share data. Results: Out of 643 respondents, 550 participants provided wearable acceptance data. The average age was 36.6 years, with 51.3% female and 39.6% residing in rural areas. Overall, 33.8% reported wearing a wearable, primarily smartwatches or fitness wristbands. Men (63.3%) and women (57.8%) expressed willingness to wear a sensor for health monitoring, and 61.5% were open to sharing data with healthcare providers. Concerns included data security, privacy, and perceived lack of need. Conclusion: The study highlights the acceptance and potential of wearables, particularly for health monitoring and data sharing with healthcare providers. Addressing data security and privacy concerns could enhance the adoption of innovative wearables, such as implants, for early detection and monitoring of chronic diseases.
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Affiliation(s)
- Michael Hindelang
- TUM School of Medicine and Health, Department of Dermatology and Allergy, Technical University of Munich, Munich, Germany; Pettenkofer School of Public Health, Munich, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology - IBE, LMU Munich, Munich, Germany
| | - Hannah Wecker
- TUM School of Medicine and Health, Department of Dermatology and Allergy, Technical University of Munich, Munich, Germany
| | - Tilo Biedermann
- TUM School of Medicine and Health, Department of Dermatology and Allergy, Technical University of Munich, Munich, Germany
| | - Alexander Zink
- TUM School of Medicine and Health, Department of Dermatology and Allergy, Technical University of Munich, Munich, Germany; Division of Dermatology and Venereology, Department of Medicine Solna, Karolinska Institute, Stockholm, Sweden
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Cha E, Lee S. Identifying Main Themes in Diabetes Management Interviews Using Natural Language Processing-Based Text Mining. Comput Inform Nurs 2024:00024665-990000000-00174. [PMID: 38453535 DOI: 10.1097/cin.0000000000001114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2024]
Abstract
This study aimed to identify the main themes from exit interviews of adult patients with type 2 diabetes after completion of a diabetes education program. Eighteen participants with type 2 diabetes completed an exit interview regarding their program experience and satisfaction. Semistructured interview questions were used, and the interviews were auto-recorded. The interview transcripts were preprocessed and analyzed using four natural language processing-based text-mining techniques. The top 30 words from the term frequency and term frequency-inverse document frequency each were derived. In the N-gram analysis, the connection strength of "diabetes" and "education" was the highest, and the simultaneous connectivity of word chains ranged from a maximum of seven words to a minimum of two words. Based on the CONvergence of iteration CORrelation (CONCOR) analysis, three clusters were generated, and each cluster was named as follows: participation in a diabetes education program to control blood glucose, exercise, and use of digital devices. This study using text mining proposes a new and useful approach to visualize data to develop patient-centered diabetes education.
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Affiliation(s)
- EunSeok Cha
- Author Affiliations: College of Nursing, Chungnam National University, Daejeon, Republic of Korea (Dr Cha); Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, USA (Dr Cha); and College of Nursing, Chonnam National University, Gwangju, Republic of Korea (Dr Lee)
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Messinis S, Temenos N, Protonotarios NE, Rallis I, Kalogeras D, Doulamis N. Enhancing Internet of Medical Things security with artificial intelligence: A comprehensive review. Comput Biol Med 2024; 170:108036. [PMID: 38295478 DOI: 10.1016/j.compbiomed.2024.108036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 01/08/2024] [Accepted: 01/26/2024] [Indexed: 02/02/2024]
Abstract
Over the past five years, interest in the literature regarding the security of the Internet of Medical Things (IoMT) has increased. Due to the enhanced interconnectedness of IoMT devices, their susceptibility to cyber-attacks has proportionally escalated. Motivated by the promising potential of AI-related technologies to improve certain cybersecurity measures, we present a comprehensive review of this emerging field. In this review, we attempt to bridge the corresponding literature gap regarding modern cybersecurity technologies that deploy AI techniques to improve their performance and compensate for security and privacy vulnerabilities. In this direction, we have systematically gathered and classified the extensive research on this topic. Our findings highlight the fact that the integration of machine learning (ML) and deep learning (DL) techniques improves both the performance of cybersecurity measures and their speed, reliability, and effectiveness. This may be proven to be useful for improving the security and privacy of IoMT devices. Furthermore, by considering the numerous advantages of AI technologies as opposed to their core cybersecurity counterparts, including blockchain, anomaly detection, homomorphic encryption, differential privacy, federated learning, and so on, we provide a structured overview of the current scientific trends. We conclude with considerations for future research, emphasizing the promising potential of AI-driven cybersecurity in the IoMT landscape, especially in patient data protection and in data-driven healthcare.
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Affiliation(s)
- Sotirios Messinis
- Institute of Communication and Computer Systems (ICCS), National Technical University of Athens, Athens, 15780, Greece.
| | - Nikos Temenos
- School of Rural, Surveying and Geoinformatics Engineering, National Technical University of Athens, Athens, 15780, Greece.
| | | | - Ioannis Rallis
- School of Rural, Surveying and Geoinformatics Engineering, National Technical University of Athens, Athens, 15780, Greece.
| | - Dimitrios Kalogeras
- Institute of Communication and Computer Systems (ICCS), National Technical University of Athens, Athens, 15780, Greece.
| | - Nikolaos Doulamis
- School of Rural, Surveying and Geoinformatics Engineering, National Technical University of Athens, Athens, 15780, Greece.
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He T, Cui W, Feng Y, Li X, Yu G. Digital health integration for noncommunicable diseases: Comprehensive process mapping for full-life-cycle management. J Evid Based Med 2024; 17:26-36. [PMID: 38361398 DOI: 10.1111/jebm.12583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 01/05/2024] [Indexed: 02/17/2024]
Abstract
AIM To create a systematic digital health process mapping framework for full-life-cycle noncommunicable disease management grounded in key stakeholder engagement. METHODS A triphasic, qualitative methodology was employed to construct a process mapping framework for digital noncommunicable disease management in Shanghai, China. The first phase involved desk research to examine current guidance and practices. In the second phase, pivotal stakeholders participated in focus group discussions to identify prevalent digital touchpoints across lifetime noncommunicable disease management. In the final phase, the Delphi technique was used to refine the framework based on expert insights and obtain consensus. RESULTS We identified 60 digital touchpoints across five essential stages of full-life-cycle noncommunicable disease management. Most experts acknowledged the rationality and feasibility of these touchpoints. CONCLUSIONS This study led to the creation of a comprehensive digital health process mapping framework that encompasses the entire life cycle of noncommunicable disease management. The insights gained emphasize the importance of a systemic strategic, person-centered approach over a fragmented, purely technocentric approach. We recommend that healthcare professionals use this framework as a linchpin for efficient disease management and seamless technology incorporation in clinical practice.
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Affiliation(s)
- Tianrui He
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenbin Cui
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Children's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuxuan Feng
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xingyi Li
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guangjun Yu
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Children's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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LaMarca A, Tse I, Keysor J. Rehabilitation Technologies for Chronic Conditions: Will We Sink or Swim? Healthcare (Basel) 2023; 11:2751. [PMID: 37893825 PMCID: PMC10606667 DOI: 10.3390/healthcare11202751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 10/08/2023] [Accepted: 10/11/2023] [Indexed: 10/29/2023] Open
Abstract
INTRODUCTION Chronic conditions such as stroke, Parkinson's disease, spinal cord injury, multiple sclerosis, vestibular disorders, chronic pain, arthritis, diabetes, chronic obstructive pulmonary disease (COPD), and heart disease are leading causes of disability among middle-aged and older adults. While evidence-based treatment can optimize clinical outcomes, few people with chronic conditions engage in the recommended levels of exercise for clinical improvement and successful management of their condition. Rehabilitation technologies that can augment therapeutic care-i.e., exoskeletons, virtual/augmented reality, and remote monitoring-offer the opportunity to bring evidence-based rehabilitation into homes. Successful integration of rehabilitation techniques at home could help recovery and access and foster long term self-management. However, widespread uptake of technology in rehabilitation is still limited, leaving many technologies developed but not adopted. METHODS In this narrative review, clinical need, efficacy, and obstacles and suggestions for implementation are discussed. The use of three technologies is reviewed in the management of the most prevalent chronic diseases that utilize rehabilitation services, including common neurological, musculoskeletal, metabolic, pulmonary, and cardiac conditions. The technologies are (i) exoskeletons, (ii) virtual and augmented reality, and (iii) remote monitoring. RESULTS Effectiveness evidence backing the use of technology in rehabilitation is growing but remains limited by high heterogeneity, lack of long-term outcomes, and lack of adoption outcomes. CONCLUSION While rehabilitation technologies bring opportunities to bridge the gap between clinics and homes, there are many challenges with adoption. Hybrid effectiveness and implementation trials are a possible path to successful technology development and adoption.
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Affiliation(s)
- Amber LaMarca
- Rehabilitation Sciences, MGH Institute of Health Professions, Boston, MA 02129, USA;
| | - Ivy Tse
- Doctor of Physical Therapy Program, MGH Institute of Health Professions, Boston, MA 02129, USA
| | - Julie Keysor
- School of Health Care Leadership, MGH Institute of Health Professions, Boston, MA 02129, USA
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Roos LG, Slavich GM. Wearable technologies for health research: Opportunities, limitations, and practical and conceptual considerations. Brain Behav Immun 2023; 113:444-452. [PMID: 37557962 PMCID: PMC11233111 DOI: 10.1016/j.bbi.2023.08.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 07/31/2023] [Accepted: 08/06/2023] [Indexed: 08/11/2023] Open
Abstract
One of the most notable limitations of laboratory-based health research is its inability to continuously monitor health-relevant physiological processes as individuals go about their daily lives. As a result, we have generated large amounts of data with unknown generalizability to real-world situations and also created a schism between where data are collected (i.e., in the lab) and where we need to intervene to prevent disease (i.e., in the field). Devices using noninvasive wearable technology are changing all of this, however, with their ability to provide high-frequency assessments of peoples' ever-changing physiological states in daily life in a manner that is relatively noninvasive, affordable, and scalable. Here, we discuss critical points that every researcher should keep in mind when using these wearables in research, spanning device and metric decisions, hardware and software selection, and data quality and sampling rate issues, using research on stress and health as an example throughout. We also address usability and participant acceptability issues, and how wearable "digital biomarker" and behavioral data can be integrated to enhance basic science and intervention studies. Finally, we summarize 10 key questions that should be addressed to make every wearable study as strong as possible. Collectively, keeping these points in mind can improve our ability to study the psychobiology of human health, and to intervene, precisely where it matters most: in peoples' daily lives.
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Affiliation(s)
- Lydia G Roos
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA.
| | - George M Slavich
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
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Charpignon ML, Byers J, Cabral S, Celi LA, Fernandes C, Gallifant J, Lough ME, Mlombwa D, Moukheiber L, Ong BA, Panitchote A, William W, Wong AKI, Nazer L. Critical Bias in Critical Care Devices. Crit Care Clin 2023; 39:795-813. [PMID: 37704341 DOI: 10.1016/j.ccc.2023.02.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
Abstract
Critical care data contain information about the most physiologically fragile patients in the hospital, who require a significant level of monitoring. However, medical devices used for patient monitoring suffer from measurement biases that have been largely underreported. This article explores sources of bias in commonly used clinical devices, including pulse oximeters, thermometers, and sphygmomanometers. Further, it provides a framework for mitigating these biases and key principles to achieve more equitable health care delivery.
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Affiliation(s)
- Marie-Laure Charpignon
- Institute for Data, Systems, and Society (IDSS), E18-407A, 50 Ames Street, Cambridge, MA 02142, USA.
| | - Joseph Byers
- Respiratory Therapy, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215, USA
| | - Stephanie Cabral
- Department of Medicine, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215, USA
| | - Leo Anthony Celi
- Laboratory for Computational Physiology, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA; Division of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Chrystinne Fernandes
- Laboratory for Computational Physiology, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Jack Gallifant
- Imperial College London NHS Trust, St Thomas' Hospital, Westminster Bridge Road, London SE1 7EH, UK
| | - Mary E Lough
- Stanford Health Care, Stanford University, 300 Pasteur Drive, Stanford, CA 94305, USA
| | - Donald Mlombwa
- Zomba Central Hospital, 8th Avenue, Zomba, Malawi; Kamuzu College of Health Sciences, Blantyre, Malawi; St. Luke's College of Health Sciences, Chilema-Zomba, Malawi
| | - Lama Moukheiber
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 77 Massachusetts Avenue, E25-330, Cambridge, MA 02139, USA
| | - Bradley Ashley Ong
- College of Medicine, University of the Philippines Manila, Calderon hall, UP College of Medicine, 547 Pedro Gil Street, Ermita Manila, Philippines
| | - Anupol Panitchote
- Faculty of Medicine, Khon Kaen University, 123 Mittraparp Highway, Muang District, Khon Kaen 40002, Thailand
| | - Wasswa William
- Mbarara University of Science and Technology, P.O. Box 1410, Mbarara, Uganda
| | - An-Kwok Ian Wong
- Duke University Medical Center, 2424 Erwin Road, Suite 1102, Hock Plaza Box 2721, Durham, NC 27710, USA
| | - Lama Nazer
- King Hussein Cancer Center, Queen Rania Street 202, Amman, Jordan
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14
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Dhingra LS, Shen M, Mangla A, Khera R. Cardiovascular Care Innovation through Data-Driven Discoveries in the Electronic Health Record. Am J Cardiol 2023; 203:136-148. [PMID: 37499593 PMCID: PMC10865722 DOI: 10.1016/j.amjcard.2023.06.104] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 05/24/2023] [Accepted: 06/29/2023] [Indexed: 07/29/2023]
Abstract
The electronic health record (EHR) represents a rich source of patient information, increasingly being leveraged for cardiovascular research. Although its primary use remains the seamless delivery of health care, the various longitudinally aggregated structured and unstructured data elements for each patient within the EHR can define the computational phenotypes of disease and care signatures and their association with outcomes. Although structured data elements, such as demographic characteristics, laboratory measurements, problem lists, and medications, are easily extracted, unstructured data are underused. The latter include free text in clinical narratives, documentation of procedures, and reports of imaging and pathology. Rapid scaling up of data storage and rapid innovation in natural language processing and computer vision can power insights from unstructured data streams. However, despite an array of opportunities for research using the EHR, specific expertise is necessary to adequately address confidentiality, accuracy, completeness, and heterogeneity challenges in EHR-based research. These often require methodological innovation and best practices to design and conduct successful research studies. Our review discusses these challenges and their proposed solutions. In addition, we highlight the ongoing innovations in federated learning in the EHR through a greater focus on common data models and discuss ongoing work that defines such an approach to large-scale, multicenter, federated studies. Such parallel improvements in technology and research methods enable innovative care and optimization of patient outcomes.
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Affiliation(s)
| | - Miles Shen
- Section of Cardiovascular Medicine, Department of Internal Medicine; Department of Internal Medicine
| | - Anjali Mangla
- Section of Cardiovascular Medicine, Department of Internal Medicine; Department of Neuroscience, Yale School of Medicine, New Haven, Connecticut
| | - Rohan Khera
- Section of Cardiovascular Medicine, Department of Internal Medicine; Center for Outcomes Research and Evaluation (CORE), Yale New Haven Hospital, New Haven, Connecticut; Section of Health Informatics, Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut.; Section of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, Connecticut.
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15
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Kaplan DM, Greenleaf M, Lam WA. Wear With Care: A Call for Empirical Investigations of Adverse Outcomes of Consumer Health Wearables. MAYO CLINIC PROCEEDINGS. DIGITAL HEALTH 2023; 1:413-418. [PMID: 38143554 PMCID: PMC10745206 DOI: 10.1016/j.mcpdig.2023.06.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/26/2023]
Affiliation(s)
- Deanna M Kaplan
- Center for the Advancement of Diagnostics for a Just Society (ADJUST Center) (D.M.K., M.G., W.A.L.), and Department of Spiritual Health, Woodruff Health Sciences Center (D.M.K.), Emory University, Atlanta, GA; Department of Family and Preventive Medicine (D.M.K), and Aflac Cancer and Blood Disorders Center of Children's Healthcare of Atlanta and Department of Pediatrics (W.A.L.), Emory University School of Medicine, Atlanta, GA; Emory University School of Medicine, Atlanta, GA (M.G.); and Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA (W.A.L.)
| | - Morgan Greenleaf
- Center for the Advancement of Diagnostics for a Just Society (ADJUST Center) (D.M.K., M.G., W.A.L.), and Department of Spiritual Health, Woodruff Health Sciences Center (D.M.K.), Emory University, Atlanta, GA; Department of Family and Preventive Medicine (D.M.K), and Aflac Cancer and Blood Disorders Center of Children's Healthcare of Atlanta and Department of Pediatrics (W.A.L.), Emory University School of Medicine, Atlanta, GA; Emory University School of Medicine, Atlanta, GA (M.G.); and Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA (W.A.L.)
| | - Wilbur A Lam
- Center for the Advancement of Diagnostics for a Just Society (ADJUST Center) (D.M.K., M.G., W.A.L.), and Department of Spiritual Health, Woodruff Health Sciences Center (D.M.K.), Emory University, Atlanta, GA; Department of Family and Preventive Medicine (D.M.K), and Aflac Cancer and Blood Disorders Center of Children's Healthcare of Atlanta and Department of Pediatrics (W.A.L.), Emory University School of Medicine, Atlanta, GA; Emory University School of Medicine, Atlanta, GA (M.G.); and Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA (W.A.L.)
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16
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Ye X, Sun M, Yu S, Yang J, Liu Z, Lv H, Wu B, He J, Wang X, Huang L. Smartwatch-Based Maximum Oxygen Consumption Measurement for Predicting Acute Mountain Sickness: Diagnostic Accuracy Evaluation Study. JMIR Mhealth Uhealth 2023; 11:e43340. [PMID: 37410528 PMCID: PMC10360014 DOI: 10.2196/43340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 12/11/2022] [Accepted: 06/09/2023] [Indexed: 07/07/2023] Open
Abstract
BACKGROUND Cardiorespiratory fitness plays an important role in coping with hypoxic stress at high altitudes. However, the association of cardiorespiratory fitness with the development of acute mountain sickness (AMS) has not yet been evaluated. Wearable technology devices provide a feasible assessment of cardiorespiratory fitness, which is quantifiable as maximum oxygen consumption (VO2max) and may contribute to AMS prediction. OBJECTIVE We aimed to determine the validity of VO2max estimated by the smartwatch test (SWT), which can be self-administered, in order to overcome the limitations of clinical VO2max measurements. We also aimed to evaluate the performance of a VO2max-SWT-based model in predicting susceptibility to AMS. METHODS Both SWT and cardiopulmonary exercise test (CPET) were performed for VO2max measurements in 46 healthy participants at low altitude (300 m) and in 41 of them at high altitude (3900 m). The characteristics of the red blood cells and hemoglobin levels in all the participants were analyzed by routine blood examination before the exercise tests. The Bland-Altman method was used for bias and precision assessment. Multivariate logistic regression was performed to analyze the correlation between AMS and the candidate variables. A receiver operating characteristic curve was used to evaluate the efficacy of VO2max in predicting AMS. RESULTS VO2max decreased after acute high altitude exposure, as measured by CPET (25.20 [SD 6.46] vs 30.17 [SD 5.01] at low altitude; P<.001) and SWT (26.17 [SD 6.71] vs 31.28 [SD 5.17] at low altitude; P<.001). Both at low and high altitudes, VO2max was slightly overestimated by SWT but had considerable accuracy as the mean absolute percentage error (<7%) and mean absolute error (<2 mL·kg-1·min-1), with a relatively small bias compared with VO2max-CPET. Twenty of the 46 participants developed AMS at 3900 m, and their VO2max was significantly lower than that of those without AMS (CPET: 27.80 [SD 4.55] vs 32.00 [SD 4.64], respectively; P=.004; SWT: 28.00 [IQR 25.25-32.00] vs 32.00 [IQR 30.00-37.00], respectively; P=.001). VO2max-CPET, VO2max-SWT, and red blood cell distribution width-coefficient of variation (RDW-CV) were found to be independent predictors of AMS. To increase the prediction accuracy, we used combination models. The combination of VO2max-SWT and RDW-CV showed the largest area under the curve for all parameters and models, which increased the area under the curve from 0.785 for VO2max-SWT alone to 0.839. CONCLUSIONS Our study demonstrates that the smartwatch device can be a feasible approach for estimating VO2max. In both low and high altitudes, VO2max-SWT showed a systematic bias toward a calibration point, slightly overestimating the proper VO2max when investigated in healthy participants. The SWT-based VO2max at low altitude is an effective indicator of AMS and helps to better identify susceptible individuals following acute high-altitude exposure, particularly by combining the RDW-CV at low altitude. TRIAL REGISTRATION Chinese Clinical Trial Registry ChiCTR2200059900; https://www.chictr.org.cn/showproj.html?proj=170253.
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Affiliation(s)
- Xiaowei Ye
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Mengjia Sun
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Shiyong Yu
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jie Yang
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Zhen Liu
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Hailin Lv
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Boji Wu
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jingyu He
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Xuhong Wang
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Lan Huang
- Institute of Cardiovascular Diseases of People's Liberation Army, The Second Affiliated Hospital, Army Medical University (Third Military Medical University), Chongqing, China
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17
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Mattison G, Canfell OJ, Forrester D, Dobbins C, Smith D, Reid D, Sullivan C. A step in the right direction: the potential role of smartwatches in supporting chronic disease prevention in health care. Med J Aust 2023; 218:384-388. [PMID: 37182214 DOI: 10.5694/mja2.51920] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 02/14/2023] [Accepted: 02/20/2023] [Indexed: 05/16/2023]
Affiliation(s)
- Graeme Mattison
- Queensland Digital Health Centre, University of Queensland, Brisbane, QLD
- Digital Health Cooperative Research Centre, Sydney, NSW
| | - Oliver J Canfell
- Queensland Digital Health Centre, University of Queensland, Brisbane, QLD
- Digital Health Cooperative Research Centre, Sydney, NSW
| | - Doug Forrester
- The Prince Charles Hospital, Brisbane, QLD
- Curtin University, Perth, WA
| | | | - Daniel Smith
- The Prince Charles Hospital, Brisbane, QLD
- University of Queensland, Brisbane, QLD
| | - David Reid
- The Prince Charles Hospital, Brisbane, QLD
- QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - Clair Sullivan
- Queensland Digital Health Centre, University of Queensland, Brisbane, QLD
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18
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Abstract
Wearable devices, such as smartwatches and activity trackers, are commonly used by patients in their everyday lives to manage their health and well-being. These devices collect and analyze long-term continuous data on measures of behavioral or physiologic function, which may provide clinicians with a more comprehensive view of a patients' health compared with the traditional sporadic measures captured by office visits and hospitalizations. Wearable devices have a wide range of potential clinical applications ranging from arrhythmia screening of high-risk individuals to remote management of chronic conditions such as heart failure or peripheral artery disease. As the use of wearable devices continues to grow, we must adopt a multifaceted approach with collaboration among all key stakeholders to effectively and safely integrate these technologies into routine clinical practice. In this Review, we summarize the features of wearable devices and associated machine learning techniques. We describe key research studies that illustrate the role of wearable devices in the screening and management of cardiovascular conditions and identify directions for future research. Last, we highlight the challenges that are currently hindering the widespread use of wearable devices in cardiovascular medicine and provide short- and long-term solutions to promote increased use of wearable devices in clinical care.
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Affiliation(s)
- Andrew Hughes
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | | | - Hiral Master
- Vanderbilt Institute of Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN
| | - Jessilyn Dunn
- Department of Biomedical Engineering, Duke University, Durham, NC
- Department of Biostatistics & Bioinformatics, Duke University, Durham, NC
| | - Evan Brittain
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN
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19
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Chen F, Pongpirul K. Rethink nutritional management in chronic kidney disease care. FRONTIERS IN NEPHROLOGY 2023; 3:1108842. [PMID: 37675377 PMCID: PMC10479564 DOI: 10.3389/fneph.2023.1108842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Accepted: 01/02/2023] [Indexed: 09/08/2023]
Affiliation(s)
- Fangyue Chen
- Department of Preventive and Social Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Thailand Public Health Research Fellowship, Health Education England, Leeds, United Kingdom
- School of Public Health, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Krit Pongpirul
- Department of Preventive and Social Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Clinical Research Center, Bumrungrad International Hospital, Bangkok, Thailand
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20
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Canfell OJ, Davidson K, Sullivan C, Eakin EE, Burton-Jones A. PREVIDE: A Qualitative Study to Develop a Decision-Making Framework (PREVention decIDE) for Noncommunicable Disease Prevention in Healthcare Organisations. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:15285. [PMID: 36430005 PMCID: PMC9690592 DOI: 10.3390/ijerph192215285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 10/27/2022] [Accepted: 11/09/2022] [Indexed: 06/16/2023]
Abstract
Noncommunicable diseases (NCDs), including obesity, remain a significant global public health challenge. Prevention and public health innovation are needed to effectively address NCDs; however, understanding of how healthcare organisations make prevention decisions is immature. This study aimed to (1) explore how healthcare organisations make decisions for NCD prevention in Queensland, Australia (2) develop a contemporary decision-making framework to guide NCD prevention in healthcare organisations. Cross-sectional and qualitative design, comprising individual semi-structured interviews. Participants (n = 14) were recruited from two organisations: the state public health care system (CareQ) and health promotion/disease prevention agency (PrevQ). Participants held executive, director/manager or project/clinical lead roles. Data were analysed in two phases (1) automated content analysis using machine learning (Leximancer v4.5) (2) researcher-led interpretation of the text analytics. Final themes were consolidated into a proposed decision-making framework (PREVIDE, PREvention decIDE) for NCD prevention in healthcare organisations. Decision-making was driven by four themes: Data, Evidence, Ethics and Health, i.e., data, its quality and the story it tells; traditional and non-traditional sources of evidence; ethical grounding in fairness and equity; and long-term value generated across multiple determinants of health. The strength of evidence was directly proportional to confidence in the ethics of a decision. PREVIDE can be adapted by public health practitioners and policymakers to guide real-world policy, practice and investment decisions for obesity prevention and with further validation, other NCDs and priority settings (e.g., healthcare).
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Affiliation(s)
- Oliver J. Canfell
- UQ Business School, Faculty of Business, Economics and Law, The University of Queensland, St. Lucia, QLD 4072, Australia
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, St. Lucia, QLD 4072, Australia
- Queensland Digital Health Centre, Faculty of Medicine, The University of Queensland, Herston, QLD 4006, Australia
- Digital Health Cooperative Research Centre, Australian Government, Sydney, NSW 2000, Australia
| | - Kamila Davidson
- UQ Business School, Faculty of Business, Economics and Law, The University of Queensland, St. Lucia, QLD 4072, Australia
| | - Clair Sullivan
- Centre for Health Services Research, Faculty of Medicine, The University of Queensland, St. Lucia, QLD 4072, Australia
- Queensland Digital Health Centre, Faculty of Medicine, The University of Queensland, Herston, QLD 4006, Australia
- Metro North Hospital and Health Service, Department of Health, Queensland Government, Herston, QLD 4072, Australia
| | - Elizabeth E. Eakin
- School of Public Health, Faculty of Medicine, The University of Queensland, Herston, QLD 4072, Australia
| | - Andrew Burton-Jones
- UQ Business School, Faculty of Business, Economics and Law, The University of Queensland, St. Lucia, QLD 4072, Australia
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21
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Tam W, Alajlani M, Abd-alrazaq A. An Exploration of Wearable Device Features Used in UK Hospital Parkinson Disease Care: Scoping Review (Preprint).. [DOI: 10.2196/preprints.42950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
BACKGROUND
The prevalence of Parkinson disease (PD) is becoming an increasing concern owing to the aging population in the United Kingdom. Wearable devices have the potential to improve the clinical care of patients with PD while reducing health care costs. Consequently, exploring the features of these wearable devices is important to identify the limitations and further areas of investigation of how wearable devices are currently used in clinical care in the United Kingdom.
OBJECTIVE
In this scoping review, we aimed to explore the features of wearable devices used for PD in hospitals in the United Kingdom.
METHODS
A scoping review of the current research was undertaken and reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The literature search was undertaken on June 6, 2022, and publications were obtained from MEDLINE or PubMed, Embase, and the Cochrane Library. Eligible publications were initially screened by their titles and abstracts. Publications that passed the initial screening underwent a full review. The study characteristics were extracted from the final publications, and the evidence was synthesized using a narrative approach. Any queries were reviewed by the first and second authors.
RESULTS
Of the 4543 publications identified, 39 (0.86%) publications underwent a full review, and 20 (0.44%) publications were included in the scoping review. Most studies (11/20, 55%) were conducted at the Newcastle upon Tyne Hospitals NHS Foundation Trust, with sample sizes ranging from 10 to 418. Most study participants were male individuals with a mean age ranging from 57.7 to 78.0 years. The AX3 was the most popular device brand used, and it was commercially manufactured by Axivity. Common wearable device types included body-worn sensors, inertial measurement units, and smartwatches that used accelerometers and gyroscopes to measure the clinical features of PD. Most wearable device primary measures involved the measured gait, bradykinesia, and dyskinesia. The most common wearable device placements were the lumbar region, head, and wrist. Furthermore, 65% (13/20) of the studies used artificial intelligence or machine learning to support PD data analysis.
CONCLUSIONS
This study demonstrated that wearable devices could help provide a more detailed analysis of PD symptoms during the assessment phase and personalize treatment. Using machine learning, wearable devices could differentiate PD from other neurodegenerative diseases. The identified evidence gaps include the lack of analysis of wearable device cybersecurity and data management. The lack of cost-effectiveness analysis and large-scale participation in studies resulted in uncertainty regarding the feasibility of the widespread use of wearable devices. The uncertainty around the identified research gaps was further exacerbated by the lack of medical regulation of wearable devices for PD, particularly in the United Kingdom where regulations were changing due to the political landscape.
CLINICALTRIAL
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