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van Kessel R, Ranganathan S, Anderson M, McMillan B, Mossialos E. Exploring potential drivers of patient engagement with their health data through digital platforms: A scoping review. Int J Med Inform 2024; 189:105513. [PMID: 38851132 DOI: 10.1016/j.ijmedinf.2024.105513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 04/11/2024] [Accepted: 06/02/2024] [Indexed: 06/10/2024]
Abstract
BACKGROUND Patient engagement when providing patient access to health data results from an interaction between the available tools and individual capabilities. The recent digital advancements of the healthcare field have altered the manifestation and importance of patient engagement. However, a comprehensive assessment of what factors contribute to patient engagement remain absent. In this review article, we synthesised the most frequently discussed factors that can foster patient engagement with their health data. METHODS A scoping review was conducted in MEDLINE, Embase, and Google Scholar. Relevant data were synthesized within 7 layers using a thematic analysis: (1) social and demographic factors, (2) patient ability factors, (3) patient motivation factors, (4) factors related to healthcare professionals' attitudes and skills, (5) health system factors, (6) technological factors, and (7) policy factors. RESULTS We identified 5801 academic and 200 Gy literature records, and included 292 (4.83%) in this review. Overall, 44 factors that can affect patient engagement with their health data were extracted. We extracted 6 social and demographic factors, 6 patient ability factors, 12 patient motivation factors, 7 factors related to healthcare professionals' attitudes and skills, 4 health system factors, 6 technological factors, and 3 policy factors. CONCLUSIONS Improving patient engagement with their health data enables the development of patient-centered healthcare, though it can also exacerbate existing inequities. While expanding patient access to health data is an important step towards fostering shared decision-making in healthcare and subsequently empowering patients, it is important to ensure that these developments reach all sectors of the community.
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Affiliation(s)
- Robin van Kessel
- LSE Health, Department of Health Policy, London School of Economics and Political Science, London, United Kingdom; Department of International Health, Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands; Digital Public Health Task Force, Association of School of Public Health in the European Region (ASPHER), Brussels, Belgium.
| | | | - Michael Anderson
- LSE Health, Department of Health Policy, London School of Economics and Political Science, London, United Kingdom; Centre for Primary Care and Health Services Research, University of Manchester, Manchester, United Kingdom.
| | - Brian McMillan
- Centre for Primary Care and Health Services Research, University of Manchester, Manchester, United Kingdom.
| | - Elias Mossialos
- LSE Health, Department of Health Policy, London School of Economics and Political Science, London, United Kingdom; Institute of Global Health Innovation, Imperial College London, London, United Kingdom.
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LeFevre A, Welte O, Moopelo K, Tiffin N, Mothoagae G, Ncube N, Gwiji N, Shogole M, Slogrove AL, Moshani N, Boulle A, Goudge J, Griffiths F, Fairlie L, Mehta U, Scott K, Pillay N. Preferences for onward health data use in the electronic age among maternity patients and providers in South Africa: a qualitative study. Sex Reprod Health Matters 2023; 31:2274667. [PMID: 37982758 PMCID: PMC11001361 DOI: 10.1080/26410397.2023.2274667] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2023] Open
Abstract
Despite the expanding digitisation of individual health data, informed consent for the collection and use of health data is seldom explicitly sought in public sector clinics in South Africa. This study aims to identify perceptions of informed consent practices for health data capture, access, and use in Gauteng and the Western Cape provinces of South Africa. Data collection from September to December 2021 included in-depth interviews with healthcare providers (n = 12) and women (n = 62) attending maternity services. Study findings suggest that most patients were not aware that their data were being used for purposes beyond the individualised provision of medical care. Understanding the concept of anonymised use of electronic health data was at times challenging for patients who understood their data in the limited context of paper-based folders and booklets. When asked about preferences for electronic data, patients overwhelmingly were in favour of digitisation. They viewed electronic access to their health data as facilitating rapid and continuous access to health information. Patients were additionally asked about preferences, including delivery of health information, onward health data use, and recontacting. Understanding of these use cases varied and was often challenging to convey to participants who understood their health data in the context of information inputted into their paper folders. Future systems need to be established to collect informed consent for onward health data use. In light of perceived ties to the care received, these systems need to ensure that patient preferences do not impede the content nor quality of care received.
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Affiliation(s)
- Amnesty LeFevre
- Associate Professor, School of Public Health, University of Cape Town, Falmouth Rd, Observatory, Cape Town7925, South Africa
| | - Olivia Welte
- Social Scientist, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa
| | - Kearabetswe Moopelo
- Social Scientist, Sarraounia Public Health Trust, Johannesburg, South Africa
| | - Nicki Tiffin
- Professor, South African Bioinformatics Institute, Life Sciences Building, University of the Western Cape, Bellville
| | - Gaolatlhe Mothoagae
- Associate Researcher, Sarraounia Public Health Trust, Johannesburg, South Africa
| | - Nobukhosi Ncube
- Social Scientist, Sarraounia Public Health Trust, Johannesburg, South Africa
| | - Nasiphi Gwiji
- School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa
| | - Manape Shogole
- Social Scientist, Sarraounia Public Health Trust, Johannesburg, South Africa
| | - Amy L. Slogrove
- Associate Professor, Faculty of Medicine and Health Sciences, Department of Paediatrics & Child Health, Stellenbosch University, Worcester, South Africa
| | - Nomakhawuta Moshani
- Social Scientist, School of Public Health, University of Cape Town, Cape Town, South Africa
| | - Andrew Boulle
- Professor, School of Public Health, University of Cape Town, Cape Town, South Africa
| | - Jane Goudge
- Professor, Centre for Health Policy, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
| | - Frances Griffiths
- Professor, Warwick Medical School, Warwick, UK; Professor, Centre for Health Policy, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
| | - Lee Fairlie
- Director of Maternal and Child Health, Wits RHI, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Ushma Mehta
- Associate Professor, School of Public Health, University of Cape Town, Cape Town, South Africa
| | - Kerry Scott
- Independent research consultant, Toronto, Canada; Associate Faculty, Johns Hopkins School of Public Health, Baltimore, USA
| | - Nirvana Pillay
- Director, Sarraounia Public Health Trust, Johannesburg; Visiting Researcher, School of Sociology, University of the Witwatersrand, Johannesburg, South Africa
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Kassam I, Ilkina D, Kemp J, Roble H, Carter-Langford A, Shen N. Patient Perspectives and Preferences for Consent in the Digital Health Context: State-of-the-art Literature Review. J Med Internet Res 2023; 25:e42507. [PMID: 36763409 PMCID: PMC9960046 DOI: 10.2196/42507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 12/05/2022] [Accepted: 01/19/2023] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND The increasing integration of digital health tools into care may result in a greater flow of personal health information (PHI) between patients and providers. Although privacy legislation governs how entities may collect, use, or share PHI, such legislation has not kept pace with digital health innovations, resulting in a lack of guidance on implementing meaningful consent. Understanding patient perspectives when implementing meaningful consent is critical to ensure that it meets their needs. Consent for research in the context of digital health is limited. OBJECTIVE This state-of-the-art review aimed to understand the current state of research as it relates to patient perspectives on digital health consent. Its objectives were to explore what is known about the patient perspective and experience with digital health consent and provide recommendations on designing and implementing digital health consent based on the findings. METHODS A structured literature search was developed and deployed in 4 electronic databases-MEDLINE, IEEE Xplore, Scopus, and Web of Science-for articles published after January 2010. The initial literature search was conducted in March 2021 and updated in March 2022. Articles were eligible for inclusion if they discussed electronic consent or consent, focused on the patient perspective or preference, and were related to digital health or digital PHI. Data were extracted using an extraction template and analyzed using qualitative content analysis. RESULTS In total, 75 articles were included for analysis. Most studies were published within the last 5 years (58/75, 77%) and conducted in a clinical care context (33/75, 44%) and in the United States (48/75, 64%). Most studies aimed to understand participants' willingness to share PHI (25/75, 33%) and participants' perceived usability and comprehension of an electronic consent notice (25/75, 33%). More than half (40/75, 53%) of the studies did not describe the type of consent model used. The broad open consent model was the most explored (11/75, 15%). Of the 75 studies, 68 (91%) found that participants were willing to provide consent; however, their consent behaviors and preferences were context-dependent. Common patient consent requirements included clear and digestible information detailing who can access PHI, for what purpose their PHI will be used, and how privacy will be ensured. CONCLUSIONS There is growing interest in understanding the patient perspective on digital health consent in the context of providing clinical care. There is evidence suggesting that many patients are willing to consent for various purposes, especially when there is greater transparency on how the PHI is used and oversight mechanisms are in place. Providing this transparency is critical for fostering trust in digital health tools and the innovative uses of data to optimize health and system outcomes.
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Affiliation(s)
- Iman Kassam
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | | | - Jessica Kemp
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Heba Roble
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | | | - Nelson Shen
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
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Soellner M, Koenigstorfer J. Motive perception pathways to the release of personal information to healthcare organizations. BMC Med Inform Decis Mak 2022; 22:240. [PMID: 36100876 PMCID: PMC9468521 DOI: 10.1186/s12911-022-01986-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 09/07/2022] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND The goal of the study is to assess the downstream effects of who requests personal information from individuals for artificial intelligence-(AI) based healthcare research purposes-be it a pharmaceutical company (as an example of a for-profit organization) or a university hospital (as an example of a not-for-profit organization)-as well as their boundary conditions on individuals' likelihood to release personal information about their health. For the latter, the study considers two dimensions: the tendency to self-disclose (which is aimed to be high so that AI applications can reach their full potential) and the tendency to falsify (which is aimed to be low so that AI applications are based on both valid and reliable data). METHODS Across three experimental studies with Amazon Mechanical Turk workers from the U.S. (n = 204, n = 330, and n = 328, respectively), Covid-19 was used as the healthcare research context. RESULTS University hospitals (vs. pharmaceutical companies) score higher on altruism and lower on egoism. Individuals were more willing to disclose data if they perceived that the requesting organization acts based on altruistic motives (i.e., the motives function as gate openers). Individuals were more likely to protect their data by intending to provide false information when they perceived egoistic motives to be the main driver for the organization requesting their data (i.e., the motives function as a privacy protection tool). Two moderators, namely message appeal (Study 2) and message endorser credibility (Study 3) influence the two indirect pathways of the release of personal information. CONCLUSION The findings add to Communication Privacy Management Theory as well as Attribution Theory by suggesting motive-based pathways to the release of correct personal health data. Compared to not-for-profit organizations, for-profit organizations are particularly recommended to match their message appeal with the organizations' purposes (to provide personal benefit) and to use high-credibility endorsers in order to reduce inherent disadvantages in motive perceptions.
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Affiliation(s)
- Michaela Soellner
- Chair of Sport and Health Management, Technical University of Munich, Campus D - Uptown Munich, Georg-Brauchle-Ring 60/62, 80992, Munich, Germany
| | - Joerg Koenigstorfer
- Chair of Sport and Health Management, Technical University of Munich, Campus D - Uptown Munich, Georg-Brauchle-Ring 60/62, 80992, Munich, Germany.
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Kirkham EJ, Crompton CJ, Iveson MH, Beange I, McIntosh AM, Fletcher-Watson S. Co-development of a Best Practice Checklist for Mental Health Data Science: A Delphi Study. Front Psychiatry 2021; 12:643914. [PMID: 34177644 PMCID: PMC8222615 DOI: 10.3389/fpsyt.2021.643914] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Accepted: 05/14/2021] [Indexed: 12/20/2022] Open
Abstract
Background: Mental health research is commonly affected by difficulties in recruiting and retaining participants, resulting in findings which are based on a sub-sample of those actually living with mental illness. Increasing the use of Big Data for mental health research, especially routinely-collected data, could improve this situation. However, steps to facilitate this must be enacted in collaboration with those who would provide the data - people with mental health conditions. Methods: We used the Delphi method to create a best practice checklist for mental health data science. Twenty participants with both expertise in data science and personal experience of mental illness worked together over three phases. In Phase 1, participants rated a list of 63 statements and added any statements or topics that were missing. Statements receiving a mean score of 5 or more (out of 7) were retained. These were then combined with the results of a rapid thematic analysis of participants' comments to produce a 14-item draft checklist, with each item split into two components: best practice now and best practice in the future. In Phase 2, participants indicated whether or not each item should remain in the checklist, and items that scored more than 50% endorsement were retained. In Phase 3 participants rated their satisfaction with the final checklist. Results: The final checklist was made up of 14 "best practice" items, with each item covering best practice now and best practice in the future. At the end of the three phases, 85% of participants were (very) satisfied with the two best practice checklists, with no participants expressing dissatisfaction. Conclusions: Increased stakeholder involvement is essential at every stage of mental health data science. The checklist produced through this work represents the views of people with experience of mental illness, and it is hoped that it will be used to facilitate trustworthy and innovative research which is inclusive of a wider range of individuals.
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Affiliation(s)
- Elizabeth J Kirkham
- Division of Psychiatry, Centre for Clinical Brain Sciences, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, United Kingdom
| | - Catherine J Crompton
- Division of Psychiatry, Centre for Clinical Brain Sciences, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, United Kingdom
| | - Matthew H Iveson
- Division of Psychiatry, Centre for Clinical Brain Sciences, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, United Kingdom
| | - Iona Beange
- Division of Psychiatry, Centre for Clinical Brain Sciences, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, United Kingdom
| | - Andrew M McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, United Kingdom
| | - Sue Fletcher-Watson
- Division of Psychiatry, Centre for Clinical Brain Sciences, Kennedy Tower, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, United Kingdom
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