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Denecke K, Romero OR, Merolli M, Miron-Shatz T, Gabarron E, Petersen C. How Participatory Health Informatics Catalyzes One Digital Health. Yearb Med Inform 2023; 32:48-54. [PMID: 38147849 PMCID: PMC10751117 DOI: 10.1055/s-0043-1768727] [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: 12/28/2023] Open
Abstract
OBJECTIVE To identify links between Participatory Health Informatics (PHI) and the One Digital Health framework (ODH) and to show how PHI could be used as a catalyst or contributor to ODH. METHODS We have analyzed the addressed topics within the ODH framework in previous IMIA Yearbook contributions from our working group during the last 10 years. We have matched main themes with the ODH's framework three perspectives (individual health and wellbeing, population and society, and ecosystem). RESULTS PHI catalysts ODH individual health and wellbeing perspective by providing a more comprehensive view on human health, attitudes, and relations between human health and animal health. Integration of specific behavior change techniques or gamification strategies in digital solutions are effective to change behaviors which address the P5 paradigm. PHI supports the population and society perspective through the engagement of the various stakeholders in healthcare. At the same time, PHI might increase a risk for health inequities due to technologies inaccessible to all equally and challenges associated with this. PHI is a catalyst for the ecosystem perspective by contributing data into the digital health data ecosystem allowing for analysis of interrelations between the various data which in turn might provide links among all components of the healthcare ecosystem. CONCLUSION Our results suggest that PHI can and will involve topics relating to ODH. As the ODH concept crystalizes and becomes increasingly influential, its themes will permeate and become embedded in PHI even more. We look forward to these developments and co-evolution of the two frameworks.
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Affiliation(s)
| | - Octavio Rivera Romero
- Instituto de Ingeniería Informática (I3US), Universidad de Sevilla, Sevilla, Spain
- Electronic Technology Department, Universidad de Sevilla, Sevilla, Spain
| | - Mark Merolli
- Department of Physiotherapy, School of Health Sciences, the University of Melbourne, Australia
- Centre for Digital Transformation of Health, The University of Melbourne, Australia
| | - Talya Miron-Shatz
- Faculty of Business Administration, Ono Academic College, Israel
- Winton Centre for Risk and Evidence Communication, Cambridge University, England
| | - Elia Gabarron
- Norwegian Centre for E-health Research, University Hospital of North Norway, Tromsø, Norway
- Department of Education, ICT and Learning, Østfold University College, Halden, Norway
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Walsh J, Dwumfour C, Cave J, Griffiths F. Spontaneously generated online patient experience data - how and why is it being used in health research: an umbrella scoping review. BMC Med Res Methodol 2022; 22:139. [PMID: 35562661 PMCID: PMC9106384 DOI: 10.1186/s12874-022-01610-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 04/13/2022] [Indexed: 11/10/2022] Open
Abstract
PURPOSE Social media has led to fundamental changes in the way that people look for and share health related information. There is increasing interest in using this spontaneously generated patient experience data as a data source for health research. The aim was to summarise the state of the art regarding how and why SGOPE data has been used in health research. We determined the sites and platforms used as data sources, the purposes of the studies, the tools and methods being used, and any identified research gaps. METHODS A scoping umbrella review was conducted looking at review papers from 2015 to Jan 2021 that studied the use of SGOPE data for health research. Using keyword searches we identified 1759 papers from which we included 58 relevant studies in our review. RESULTS Data was used from many individual general or health specific platforms, although Twitter was the most widely used data source. The most frequent purposes were surveillance based, tracking infectious disease, adverse event identification and mental health triaging. Despite the developments in machine learning the reviews included lots of small qualitative studies. Most NLP used supervised methods for sentiment analysis and classification. Very early days, methods need development. Methods not being explained. Disciplinary differences - accuracy tweaks vs application. There is little evidence of any work that either compares the results in both methods on the same data set or brings the ideas together. CONCLUSION Tools, methods, and techniques are still at an early stage of development, but strong consensus exists that this data source will become very important to patient centred health research.
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Affiliation(s)
- Julia Walsh
- Warwick Medical School, University of Warwick, Coventry, UK.
| | | | - Jonathan Cave
- Department of Economics, University of Warwick, Coventry, UK
| | - Frances Griffiths
- Warwick Medical School, University of Warwick, Coventry, UK.,Centre for Health Policy, University of the Witwatersrand, Johannesburg, South Africa
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Lakamana S, Yang YC, Al-Garadi MA, Sarker A. Tracking the COVID-19 outbreak in India through Twitter: Opportunities for social media based global pandemic surveillance. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2022; 2022:313-322. [PMID: 35854749 PMCID: PMC9285154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/01/2023]
Abstract
We investigated the utility of Twitter for conducting multi-faceted geolocation-centric pandemic surveillance, using India as an example. We collected over 4 million COVID19-related tweets related to the Indian outbreak between January and July 2021. We geolocated the tweets, applied natural language processing to characterize the tweets (eg., identifying symptoms and emotions), and compared tweet volumes with the numbers of confirmed COVID-19 cases. Tweet numbers closely mirrored the outbreak, with the 7-day average strongly correlated with confirmed COVID-19 cases nationally (Spearman r=0.944; p=0.001), and also at the state level (Spearman r=0.84, p=0.0003). Fatigue, Dyspnea and Cough were the top symptoms detected, while there was a significant increase in the proportion of tweets expressing negative emotions (eg., fear and sadness). The surge in COVID-19 tweets was followed by increased number of posts expressing concern about black fungus and oxygen supply. Our study illustrates the potential of social media for multi-faceted pandemic surveillance.
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Affiliation(s)
- Sahithi Lakamana
- Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322
| | - Yuan-Chi Yang
- Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322
| | - Mohammed Ali Al-Garadi
- Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322
| | - Abeed Sarker
- Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322
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Denecke K, Gabarron E, Grainger R, Konstantinidis ST, Lau A, Rivera-Romero O, Miron-Shatz T, Merolli M. Artificial Intelligence for Participatory Health: Applications, Impact, and Future Implications. Yearb Med Inform 2019; 28:165-173. [PMID: 31022749 PMCID: PMC6697496 DOI: 10.1055/s-0039-1677902] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Objective
: Artificial intelligence (AI) provides people and professionals working in the field of participatory health informatics an opportunity to derive robust insights from a variety of online sources. The objective of this paper is to identify current state of the art and application areas of AI in the context of participatory health.
Methods
: A search was conducted across seven databases (PubMed, Embase, CINAHL, PsychInfo, ACM Digital Library, IEEExplore, and SCOPUS), covering articles published since 2013. Additionally, clinical trials involving AI in participatory health contexts registered at clinicaltrials.gov were collected and analyzed.
Results
: Twenty-two articles and 12 trials were selected for review. The most common application of AI in participatory health was the secondary analysis of social media data: self-reported data including patient experiences with healthcare facilities, reports of adverse drug reactions, safety and efficacy concerns about over-the-counter medications, and other perspectives on medications. Other application areas included determining which online forum threads required moderator assistance, identifying users who were likely to drop out from a forum, extracting terms used in an online forum to learn its vocabulary, highlighting contextual information that is missing from online questions and answers, and paraphrasing technical medical terms for consumers.
Conclusions
: While AI for supporting participatory health is still in its infancy, there are a number of important research priorities that should be considered for the advancement of the field. Further research evaluating the impact of AI in participatory health informatics on the psychosocial wellbeing of individuals would help in facilitating the wider acceptance of AI into the healthcare ecosystem.
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Affiliation(s)
| | - Elia Gabarron
- Norwegian Centre for E-health Research, University Hospital of North Norway, Norway
| | | | | | - Annie Lau
- Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Australia
| | | | - Talya Miron-Shatz
- Ono Academic College, Israel, and Winton Centre for Risk and Evidence Communication, Cambridge University, England
| | - Mark Merolli
- Swinburne University of Technology, and University of Melbourne, Australia
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Bittner JG, Logghe HJ, Kane ED, Goldberg RF, Alseidi A, Aggarwal R, Jacob BP. A Society of Gastrointestinal and Endoscopic Surgeons (SAGES) statement on closed social media (Facebook®) groups for clinical education and consultation: issues of informed consent, patient privacy, and surgeon protection. Surg Endosc 2019; 33:1-7. [PMID: 30421077 DOI: 10.1007/s00464-018-6569-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Accepted: 10/26/2018] [Indexed: 02/06/2023]
Abstract
INTRODUCTION Closed social media groups (CSMG), including closed Facebook® groups, are online communities providing physicians with platforms to collaborate privately via text, images, videos, and live streaming in real time and optimize patient care. CSMG platforms represent a novel paradigm in online learning and education, so it is imperative to ensure that the public and patients trust the physicians using these platforms. Informed consent is an essential aspect of establishing this trust. With the launch of several of its own CSMG, Society of Gastrointestinal and Endoscopic Surgeons (SAGES) sought to define its position on CSMG platforms and provide an informed consent template for educating and protecting patients, surgeons, and institutions. METHODS A review of the literature (2012-2018) discussing the informed consent process for posting clinical scenarios, photography, and/or videography on social media was performed. Pertinent articles and exemplary legal counsel-approved CSMG policies and informed consent forms were reviewed by members of the SAGES Facebook® Task Force. RESULTS Eleven articles and two institutional CSMG policies discussing key components of the informed consent process, including patient transparency and confidentiality, provider-patient partnerships, ethics, and education were included. Using this information and expert opinion, a SAGES-approved statement and informed consent template were formulated. CONCLUSIONS SAGES endorses the professional use of medical and surgical CSMG platforms for education, patient care optimization, and dissemination of clinical information. Despite the growing use of social media as an integral tool for surgical practice and education, issues of informed consent still exist and remain the responsibility of the physician contributor. Responsible, ethical, and compliant use of CSMG platforms is essential. Surgeons and patients embracing CSMG for quality improvement and optimized outcomes should be legally protected. SAGES foresees the use of this type of platform continuing to grow.
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Affiliation(s)
- James G Bittner
- Department of Surgery, St. Francis Hospital and Medical Center, Hartford, CT, USA
| | - Heather J Logghe
- Department of Surgery, Sidney Kimmel Medical College, Thomas Jefferson University Hospitals, Philadelphia, PA, USA
| | - Erica D Kane
- Department of Anesthesia, Perioperative, and Pain Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ross F Goldberg
- Department of Surgery, Maricopa Integrated Health System, Phoenix, AZ, USA
| | - Adnan Alseidi
- Department of Surgery, Virginia Mason Medical Center, Seattle, WA, USA
| | - Rajesh Aggarwal
- Department of Surgery, Sidney Kimmel Medical College, Thomas Jefferson University Hospitals, Philadelphia, PA, USA.,Jefferson Strategic Ventures, Jefferson Health, Philadelphia, PA, USA
| | - Brian P Jacob
- Laparoscopic Surgical Center of New York, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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Karampela M, Ouhbi S, Isomursu M. Personal health data: A systematic mapping study. Int J Med Inform 2018; 118:86-98. [PMID: 30153927 DOI: 10.1016/j.ijmedinf.2018.08.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2018] [Revised: 05/20/2018] [Accepted: 08/02/2018] [Indexed: 01/09/2023]
Abstract
BACKGROUND Personal health data (PHD) research has been intensified over the last years, attracting the attention of scientists from different fields, such as software engineers, computer scientists and medical professionals. The increasing interest of researchers can be attributed to the exponential growth of the available PHD due to the widespread adoption of ubiquitous technology in everyday life, as well as to the potential of the ongoing digital transformation in healthcare. This increasing interest requires that academia has an overview of the published scientific literature to plan future endeavors. OBJECTIVE The main objective of this study is to identify and address research gaps in literature regarding PHD. METHOD This paper conducts a systematic mapping study to summarize the existing PHD approaches in literature and to organize the selected studies according to six classification criteria: publication source, publication year, research types, empirical types, contribution types and research topic. RESULTS In total 79 papers have been included after fulfilling the inclusion criteria and have been classified accordingly. There is an increasing amount of attention that has been paid to PHD since 2014. The majority of papers is published in journals. The two main research types found were solution proposals and evaluation research. The majority of the selected papers were empirically evaluated. The main contribution types were methods and frameworks. Data privacy is the most frequently addressed topic in PHD literature, followed by data sharing. CONCLUSIONS The findings of this systematic mapping study have implications for both researchers who are planning new studies in PHD and for practitioners who are working in connected health and would like to have an overview on the existent studies on PHD research area.
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Affiliation(s)
- Maria Karampela
- IT University of Copenhagen, Copenhagen, Rued Langgaards Vej 7, DK-2300 Copenhagen S, Denmark.
| | - Sofia Ouhbi
- TICLab, FIL, International University of Rabat, Technopolis Rabat-Shore Rocade Rabat-Salé, Rabat, Morocco.
| | - Minna Isomursu
- IT University of Copenhagen, Copenhagen, Rued Langgaards Vej 7, DK-2300 Copenhagen S, Denmark.
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