1
|
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.
Collapse
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.
| |
Collapse
|
2
|
Dashtkoohi M, Poursalehian M, Azadmanjir Z, Vaeidi M, Mohammadzadeh M, Sharif-Alhoseini M, Naghdi K, Moniri Asl M, Harrop J, Rahimi-Movaghar V. Data Consistency of Two National Registries in Iran: A Preliminary Assessment to Health Information Exchange. ARCHIVES OF IRANIAN MEDICINE 2024; 27:357-363. [PMID: 39072383 PMCID: PMC11316184 DOI: 10.34172/aim.30023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Accepted: 06/09/2024] [Indexed: 07/30/2024]
Abstract
BACKGROUND The National Spinal Cord Injury Registry of Iran (NSCIR-IR) and the National Trauma Registry of Iran (NTRI) were established to meet the data needs for research and assessing trauma status in Iran. These registries have a group of patients shared by both registries, and it is expected that some identical data will be collected about them. A general question arises whether the spinal cord injury registry can receive part of the common data from the trauma registry and not collect them independently. METHODS We examined variables captured in both registries based on structure and concept, identified the overlapping period during which both systems recorded data in the same centers and extracted relevant data from both registries. Further, we evaluated the data for any discrepancies in amount or nature and pinpointed the underlying reasons for any inconsistencies. RESULTS Out of all the variables in the NSCIR-IR database, 18.6% of variables were similar to the NTRI in terms of concept and structure. Although four hospitals participated in both registries, only two (Sina and Beheshti Hospitals) had common cases. Patient names, prehospital intubation, ambulance arrival time, ICU length of stay, and admission time were consistent across both registries with no differences. Other common data variables had significant discrepancies. CONCLUSION This study highlights the potential for health information exchange (HIE) between NSCIR-IR and NTRI and serves as a starting point for stakeholders and policymakers to understand the differences between the two registries and work toward the successful adoption of HIE.
Collapse
Affiliation(s)
- Mohammad Dashtkoohi
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
- Students’ Scientific Research Center (SSRC), Tehran University of Medical Sciences, Tehran, Iran
- Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Poursalehian
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
- Students’ Scientific Research Center (SSRC), Tehran University of Medical Sciences, Tehran, Iran
| | - Zahra Azadmanjir
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
- Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
| | - Masoomeh Vaeidi
- Trauma Research Center, Kashan University of Medical Sciences, Kashan, Iran
| | | | - Mahdi Sharif-Alhoseini
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Khatereh Naghdi
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Marzieh Moniri Asl
- Health Information Technology Department, Urmia University of Medical Sciences, Urmia, Iran
| | - James Harrop
- Department of Neurological Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA
| | - Vafa Rahimi-Movaghar
- Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
- Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| |
Collapse
|
3
|
Cascini F, Pantovic A, Al-Ajlouni YA, Puleo V, De Maio L, Ricciardi W. Health data sharing attitudes towards primary and secondary use of data: a systematic review. EClinicalMedicine 2024; 71:102551. [PMID: 38533128 PMCID: PMC10963197 DOI: 10.1016/j.eclinm.2024.102551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 02/29/2024] [Accepted: 03/01/2024] [Indexed: 03/28/2024] Open
Abstract
Background To receive the best care, people share their health data (HD) with their health practitioners (known as sharing HD for primary purposes). However, during the past two decades, sharing for other (i.e., secondary) purposes has become of great importance in numerous fields, including public health, personalized medicine, research, and development. We aimed to conduct the first comprehensive overview of all studies that investigated people's HD sharing attitudes-along with associated barriers/motivators and significant influencing factors-for all data types and across both primary and secondary uses. Methods We searched PubMed, MEDLINE, PsycINFO, Web of Science, EMBASE, and CINAHL for relevant studies published in English between database inception and February 28, 2023, using a predefined set of keywords. Studies were included, regardless of their design, if they reported outcomes related to attitudes towards sharing HD. We extracted key data from the included studies, including the type of HD involved and findings related to: HD sharing attitudes (either in general or depending on type of data/user); barriers/motivators/benefits/concerns of the study participants; and sociodemographic and other variables that could impact HD sharing behaviour. The qualitative synthesis was conducted by dividing the studies according to the data type (resulting in five subgroups) as well as the purpose the data sharing was focused on (primary, secondary or both). The Newcastle-Ottawa Scale (NOS) was used to assess the quality of non-randomised studies. This work was registered with PROSPERO, CRD42023413822. Findings Of 2109 studies identified through our search, 116 were included in the qualitative synthesis, yielding a total of 228,501 participants and various types of HD represented: person-generated HD (n = 17 studies and 10,771 participants), personal HD in general (n = 69 studies and 117,054 participants), Biobank data (n = 7 studies and 27,073 participants), genomic data (n = 13 studies and 54,716 participants), and miscellaneous data (n = 10 studies and 18,887 participants). The majority of studies had a moderate level of quality (83 [71.6%] of 116 studies), but varying levels of quality were observed across the included studies. Overall, studies suggest that sharing intentions for primary purposes were observed to be high regardless of data type, and it was higher than sharing intentions for secondary purposes. Sharing for secondary purposes yielded variable findings, where both the highest and the lowest intention rates were observed in the case of studies that explored sharing biobank data (98% and 10%, respectively). Several influencing factors on sharing intentions were identified, such as the type of data recipient, data, consent. Further, concerns related to data sharing that were found to be mutual for all data types included privacy, security, and data access/control, while the perceived benefits included those related to improvements in healthcare. Findings regarding attitudes towards sharing varied significantly across sociodemographic factors and depended on data type and type of use. In most cases, these findings were derived from single studies and therefore warrant confirmations from additional studies. Interpretation Sharing health data is a complex issue that is influenced by various factors (the type of health data, the intended use, the data recipient, among others) and these insights could be used to overcome barriers, address people's concerns, and focus on spreading awareness about the data sharing process and benefits. Funding None.
Collapse
Affiliation(s)
- Fidelia Cascini
- Department of Life Sciences and Public Health, Section of Hygiene and Public Health, Università Cattolica del Sacro Cuore, L. go Francesco Vito 1, Rome, 00168, Italy
- Directorate General for the Digitisation of the Health Information System and Statistics, Ministry of Health, Italy
| | - Ana Pantovic
- Faculty of Biology, University of Belgrade, Belgrade, Serbia
| | | | - Valeria Puleo
- Department of Life Sciences and Public Health, Section of Hygiene and Public Health, Università Cattolica del Sacro Cuore, L. go Francesco Vito 1, Rome, 00168, Italy
| | - Lucia De Maio
- Department of Life Sciences and Public Health, Section of Hygiene and Public Health, Università Cattolica del Sacro Cuore, L. go Francesco Vito 1, Rome, 00168, Italy
| | - Walter Ricciardi
- Department of Life Sciences and Public Health, Section of Hygiene and Public Health, Università Cattolica del Sacro Cuore, L. go Francesco Vito 1, Rome, 00168, Italy
| |
Collapse
|
4
|
Soni H, Morrison H, Vasilev D, Ong T, Wilczewski H, Allen C, Hughes-Halbert C, Ritchie JB, Narma A, Schiffman JD, Ivanova J, Bunnell BE, Welch BM. User experience of a family health history chatbot: A quantitative analysis. Health Informatics J 2024; 30:14604582241262251. [PMID: 38865081 PMCID: PMC11391477 DOI: 10.1177/14604582241262251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2024]
Abstract
OBJECTIVE Family health history (FHx) is an important tool in assessing one's risk towards specific health conditions. However, user experience of FHx collection tools is rarely studied. ItRunsInMyFamily.com (ItRuns) was developed to assess FHx and hereditary cancer risk. This study reports a quantitative user experience analysis of ItRuns. METHODS We conducted a public health campaign in November 2019 to promote FHx collection using ItRuns. We used software telemetry to quantify abandonment and time spent on ItRuns to identify user behaviors and potential areas of improvement. RESULTS Of 11,065 users who started the ItRuns assessment, 4305 (38.91%) reached the final step to receive recommendations about hereditary cancer risk. Highest abandonment rates were during Introduction (32.82%), Invite Friends (29.03%), and Family Cancer History (12.03%) subflows. Median time to complete the assessment was 636 s. Users spent the highest median time on Proband Cancer History (124.00 s) and Family Cancer History (119.00 s) subflows. Search list questions took the longest to complete (median 19.50 s), followed by free text email input (15.00 s). CONCLUSION Knowledge of objective user behaviors at a large scale and factors impacting optimal user experience will help enhance the ItRuns workflow and improve future FHx collection.
Collapse
Affiliation(s)
- Hiral Soni
- Doxy.me Research, Doxy.me Inc., Rochester, NY, USA
| | | | | | - Triton Ong
- Doxy.me Research, Doxy.me Inc., Rochester, NY, USA
| | | | - Caitlin Allen
- Biomedical Informatics Center, Public Health and Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Chanita Hughes-Halbert
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Jordon B Ritchie
- Biomedical Informatics Center, Public Health and Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Alexa Narma
- Doxy.me Research, Doxy.me Inc., Rochester, NY, USA
| | | | | | - Brian E Bunnell
- Doxy.me Research, Doxy.me Inc., Rochester, NY, USA
- Innovation in Mental Health Lab., Department of Psychiatry and Behavioral Neurosciences, University of South Florida, Tampa, FL, USA
| | - Brandon M Welch
- Doxy.me Research, Doxy.me Inc., Rochester, NY, USA
- Biomedical Informatics Center, Public Health and Sciences, Medical University of South Carolina, Charleston, SC, USA
| |
Collapse
|
5
|
Baines R, Stevens S, Austin D, Anil K, Bradwell H, Cooper L, Maramba ID, Chatterjee A, Leigh S. Patient and Public Willingness to Share Personal Health Data for Third-Party or Secondary Uses: Systematic Review. J Med Internet Res 2024; 26:e50421. [PMID: 38441944 PMCID: PMC10951832 DOI: 10.2196/50421] [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: 06/30/2023] [Revised: 12/01/2023] [Accepted: 12/18/2023] [Indexed: 03/07/2024] Open
Abstract
BACKGROUND International advances in information communication, eHealth, and other digital health technologies have led to significant expansions in the collection and analysis of personal health data. However, following a series of high-profile data sharing scandals and the emergence of COVID-19, critical exploration of public willingness to share personal health data remains limited, particularly for third-party or secondary uses. OBJECTIVE This systematic review aims to explore factors that affect public willingness to share personal health data for third-party or secondary uses. METHODS A systematic search of 6 databases (MEDLINE, Embase, PsycINFO, CINAHL, Scopus, and SocINDEX) was conducted with review findings analyzed using inductive-thematic analysis and synthesized using a narrative approach. RESULTS Of the 13,949 papers identified, 135 were included. Factors most commonly identified as a barrier to data sharing from a public perspective included data privacy, security, and management concerns. Other factors found to influence willingness to share personal health data included the type of data being collected (ie, perceived sensitivity); the type of user requesting their data to be shared, including their perceived motivation, profit prioritization, and ability to directly impact patient care; trust in the data user, as well as in associated processes, often established through individual choice and control over what data are shared with whom, when, and for how long, supported by appropriate models of dynamic consent; the presence of a feedback loop; and clearly articulated benefits or issue relevance including valued incentivization and compensation at both an individual and collective or societal level. CONCLUSIONS There is general, yet conditional public support for sharing personal health data for third-party or secondary use. Clarity, transparency, and individual control over who has access to what data, when, and for how long are widely regarded as essential prerequisites for public data sharing support. Individual levels of control and choice need to operate within the auspices of assured data privacy and security processes, underpinned by dynamic and responsive models of consent that prioritize individual or collective benefits over and above commercial gain. Failure to understand, design, and refine data sharing approaches in response to changeable patient preferences will only jeopardize the tangible benefits of data sharing practices being fully realized.
Collapse
Affiliation(s)
- Rebecca Baines
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
| | - Sebastian Stevens
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
- Prometheus Health Technologies Ltd, Newquay, United Kingdom
| | - Daniela Austin
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
| | | | - Hannah Bradwell
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
| | - Leonie Cooper
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
| | | | - Arunangsu Chatterjee
- Centre for Health Technology, University of Plymouth, Plymouth, United Kingdom
- School of Medicine, University of Leeds, Leeds, United Kingdom
| | - Simon Leigh
- Prometheus Health Technologies Ltd, Newquay, United Kingdom
- Warwick Medical School, University of Warwick, Conventry, United Kingdom
| |
Collapse
|
6
|
Watson E, Fletcher-Watson S, Kirkham EJ. Views on sharing mental health data for research purposes: qualitative analysis of interviews with people with mental illness. BMC Med Ethics 2023; 24:99. [PMID: 37964278 PMCID: PMC10648337 DOI: 10.1186/s12910-023-00961-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 09/24/2023] [Indexed: 11/16/2023] Open
Abstract
BACKGROUND Improving the ways in which routinely-collected mental health data are shared could facilitate substantial advances in research and treatment. However, this process should only be undertaken in partnership with those who provide such data. Despite relatively widespread investigation of public perspectives on health data sharing more generally, there is a lack of research on the views of people with mental illness. METHODS Twelve people with lived experience of mental illness took part in semi-structured interviews via online video software. Participants had experience of a broad range of mental health conditions including anxiety, depression, schizophrenia, eating disorders and addiction. Interview questions sought to establish how participants felt about the use of routinely-collected health data for research purposes, covering different types of health data, what health data should be used for, and any concerns around its use. RESULTS Thematic analysis identified four overarching themes: benefits of sharing mental health data, concerns about sharing mental health data, safeguards, and data types. Participants were clear that health data sharing should facilitate improved scientific knowledge and better treatments for mental illness. There were concerns that data misuse could become another way in which individuals and society discriminate against people with mental illness, for example through insurance premiums or employment decisions. Despite this there was a generally positive attitude to sharing mental health data as long as appropriate safeguards were in place. CONCLUSIONS There was notable strength of feeling across participants that more should be done to reduce the suffering caused by mental illness, and that this could be partly facilitated by well-managed sharing of health data. The mental health research community could build on this generally positive attitude to mental health data sharing by following rigorous best practice tailored to the specific concerns of people with mental illness.
Collapse
Affiliation(s)
- Emily Watson
- University of Edinburgh Medical School, Edinburgh, UK
| | | | - Elizabeth Joy Kirkham
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
- Clinical Psychology, School of Health in Social Science, University of Edinburgh, Edinburgh, UK.
- Medical School, Teviot Place, Edinburgh, EH8 9AG, UK.
| |
Collapse
|
7
|
Eluru M, Mendoza DH, Wong A, Jafari M, Todd M, Bayless P, Chern D, Eldredge C, Fonseca R, Franco-Fuquen P, Garcia-Robledo JE, Gifford BG, Hans R, Moreno-Cortes EF, Perumbeti A, Vargas-Cely FS, Zhao L, Grando MA. Physicians' Perspectives on HL7 Information Policy Sensitive Value Set: A Validation Study through Health Concept Categorization. Healthcare (Basel) 2023; 11:2845. [PMID: 37957990 PMCID: PMC10647660 DOI: 10.3390/healthcare11212845] [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: 07/07/2023] [Revised: 10/18/2023] [Accepted: 10/21/2023] [Indexed: 11/15/2023] Open
Abstract
The Health Level 7 (HL7) organization introduced the Information Sensitivity Policy Value Set with 45 sensitive data categories to facilitate the implementation of granular electronic consent technology. The goal is to allow patients to have control over the sharing of their sensitive medical records. This study represents the first attempt to explore physicians' viewpoints on these categories. Twelve physicians participated in a survey, leading to revisions in 21 HL7 categories. They later classified 600 clinical data items through a second survey using the updated categories. Participants' perspectives were documented, and data analysis included descriptive measures and heat maps. In the first survey, six participants suggested adding 19 new categories (e.g., personality disorder), and modifying 25 category definitions. Two new categories and sixteen revised category definitions were incorporated to support more patient-friendly content and inclusive language. Fifteen new category recommendations were addressed through a revision of category definitions (e.g., personality disorder described as a behavioral health condition). In the second survey, data categorizations led to recommendations for more categories from ten participants. Future revisions of the HL7 categories should incorporate physicians' viewpoints, validate the categories using patient data or/and include patients' perspectives, and develop patient-centric category specifications.
Collapse
Affiliation(s)
- Maheswari Eluru
- College of Health Solutions, Arizona State University, Phoenix, AZ 85054, USA (D.H.M.)
| | - Daniel Hector Mendoza
- College of Health Solutions, Arizona State University, Phoenix, AZ 85054, USA (D.H.M.)
| | - Audrey Wong
- College of Health Solutions, Arizona State University, Phoenix, AZ 85054, USA (D.H.M.)
| | - Mohammad Jafari
- College of Health Solutions, Arizona State University, Phoenix, AZ 85054, USA (D.H.M.)
- Health Level Seven International, Ann Arbor, MI 48104, USA
| | - Michael Todd
- Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, AZ 85004, USA;
| | | | | | - Christina Eldredge
- Morsani College of Medicine, University of South Florida, Tampa, FL 33602, USA
| | | | | | | | | | - Rhea Hans
- Mayo Clinic, Phoenix, AZ 85054, USA; (R.F.); (F.S.V.-C.)
| | | | - Ajay Perumbeti
- College of Medicine, University of Arizona, Phoenix, AZ 85004, USA
- Banner Health Systems, Phoenix, AZ 85006, USA
| | | | - Lin Zhao
- HonorHealth, Phoenix, AZ 85020, USA
| | - Maria Adela Grando
- College of Health Solutions, Arizona State University, Phoenix, AZ 85054, USA (D.H.M.)
| |
Collapse
|
8
|
Esmaeilzadeh P, Mirzaei T. Role of Incentives in the Use of Blockchain-Based Platforms for Sharing Sensitive Health Data: Experimental Study. J Med Internet Res 2023; 25:e41805. [PMID: 37594783 PMCID: PMC10474518 DOI: 10.2196/41805] [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: 08/15/2022] [Revised: 02/02/2023] [Accepted: 07/17/2023] [Indexed: 08/19/2023] Open
Abstract
BACKGROUND Blockchain is an emerging technology that enables secure and decentralized approaches to reduce technical risks and governance challenges associated with sharing data. Although blockchain-based solutions have been suggested for sharing health information, it is still unclear whether a suitable incentive mechanism (intrinsic or extrinsic) can be identified to encourage individuals to share their sensitive data for research purposes. OBJECTIVE This study aimed to investigate how important extrinsic incentives are and what type of incentive is the best option in blockchain-based platforms designed for sharing sensitive health information. METHODS In this study, we conducted 3 experiments with 493 individuals to investigate the role of extrinsic incentives (ie, cryptocurrency, money, and recognition) in data sharing with research organizations. RESULTS The findings highlight that offering different incentives is insufficient to encourage individuals to use blockchain technology or to change their perceptions about the technology's premise for sharing sensitive health data. The results demonstrate that individuals still attribute serious risks to blockchain-based platforms. Privacy and security concerns, trust issues, lack of knowledge about the technology, lack of public acceptance, and lack of regulations are reported as top risks. In terms of attracting people to use blockchain-based platforms for data sharing in health care, we show that the effects of extrinsic motivations (cryptoincentives, money, and status) are significantly overshadowed by inhibitors to technology use. CONCLUSIONS We suggest that before emphasizing the use of various types of extrinsic incentives, the users must be educated about the capabilities and benefits offered by this technology. Thus, an essential first step for shifting from an institution-based data exchange to a patient-centric data exchange (using blockchain) is addressing technology inhibitors to promote patient-driven data access control. This study shows that extrinsic incentives alone are inadequate to change users' perceptions, increase their trust, or encourage them to use technology for sharing health data.
Collapse
Affiliation(s)
- Pouyan Esmaeilzadeh
- Department of Information Systems and Business Analytics, Florida International University, Miami, FL, United States
| | - Tala Mirzaei
- Department of Information Systems and Business Analytics, Florida International University, Miami, FL, United States
| |
Collapse
|
9
|
Benevento M, Mandarelli G, Carravetta F, Ferorelli D, Caterino C, Nicolì S, Massari A, Solarino B. Measuring the willingness to share personal health information: a systematic review. Front Public Health 2023; 11:1213615. [PMID: 37546309 PMCID: PMC10397406 DOI: 10.3389/fpubh.2023.1213615] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 07/05/2023] [Indexed: 08/08/2023] Open
Abstract
Background In the age of digitalization and big data, personal health information is a key resource for health care and clinical research. This study aimed to analyze the determinants and describe the measurement of the willingness to disclose personal health information. Methods The study conducted a systematic review of articles assessing willingness to share personal health information as a primary or secondary outcome. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis protocol. English and Italian peer-reviewed research articles were included with no restrictions for publication years. Findings were narratively synthesized. Results The search strategy found 1,087 papers, 89 of which passed the screening for title and abstract and the full-text assessment. Conclusion No validated measurement tool has been developed for willingness to share personal health information. The reviewed papers measured it through surveys, interviews, and questionnaires, which were mutually incomparable. The secondary use of data was the most important determinant of willingness to share, whereas clinical and socioeconomic variables had a slight effect. The main concern discouraging data sharing was privacy, although good data anonymization and the high perceived benefits of sharing may overcome this issue.
Collapse
Affiliation(s)
- Marcello Benevento
- Department of Interdisciplinary Medicine, University of Bari, Bari, Italy
| | | | | | - Davide Ferorelli
- Department of Interdisciplinary Medicine, University of Bari, Bari, Italy
| | - Cristina Caterino
- Department of Interdisciplinary Medicine, University of Bari, Bari, Italy
| | - Simona Nicolì
- Department of Interdisciplinary Medicine, University of Bari, Bari, Italy
| | - Antonella Massari
- Department of Economics, Management and Business Law, University of Bari, Bari, Italy
| | - Biagio Solarino
- Department of Interdisciplinary Medicine, University of Bari, Bari, Italy
| |
Collapse
|
10
|
Banerjee I, Syed K, Potturu A, Pragada VS, Sharma RS, Murcko A, Chern D, Todd M, Aking P, Al-Yaqoobi A, Bayless P, Belmonte W, Cuadra T, Dockins T, Eldredge C, El-Kareh R, Gale G, Gentile E, Kalpas E, Morris M, Mueller L, Piekut D, Ross MK, Sarris J, Singh G, Tharani S, Wallace M, Grando MA. Physicians differ in their perceptions of sensitive medical records: Survey and interview study. Health Informatics J 2023; 29:14604582231193519. [PMID: 37544770 DOI: 10.1177/14604582231193519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Physician categorizations of electronic health record (EHR) data (e.g., depression) into sensitive data categories (e.g., Mental Health) and their perspectives on the adequacy of the categories to classify medical record data were assessed. One thousand data items from patient EHR were classified by 20 physicians (10 psychiatrists paired with ten non-psychiatrist physicians) into data categories via a survey. Cluster-adjusted chi square tests and mixed models were used for analysis. 10 items were selected per each physician pair (100 items in total) for discussion during 20 follow-up interviews. Interviews were thematically analyzed. Survey item categorization yielded 500 (50.0%) agreements, 175 (17.5%) disagreements, 325 (32.5%) partial agreements. Categorization disagreements were associated with physician specialty and implied patient history. Non-psychiatrists selected significantly (p = .016) more data categories than psychiatrists when classifying data items. The endorsement of Mental Health and Substance Use categories were significantly (p = .001) related for both provider types. During thematic analysis, Encounter Diagnosis (100%), Problems (95%), Health Concerns (90%), and Medications (85%) were discussed the most when deciding the sensitivity of medical information. Most (90.0%) interview participants suggested adding additional data categories. Study findings may guide the evolution of digital patient-controlled granular data sharing technology and processes.
Collapse
Affiliation(s)
| | - Kazi Syed
- Arizona State University, Scottsdale, AZ, US
| | | | | | | | | | | | | | - Padma Aking
- Trinity Integrated Medicine, Phoenix, AZ, US
| | | | | | | | - Teresa Cuadra
- New York City Zen Center for Contemplative Care, New York, NY, US
| | | | | | | | | | | | - Edward Kalpas
- Arizona State University, Scottsdale, AZ, US
- HonorHealth, Scottsdale, AZ, US
| | - Meghan Morris
- Arizona State University, Scottsdale, AZ, US
- HonorHealth, Scottsdale, AZ, US
| | - Laurel Mueller
- Arizona Osteopathic Medical Association, Phoenix, AZ, US
| | | | | | | | | | | | | | | |
Collapse
|
11
|
Reeves J, Treharne GJ, Ratima M, Theodore R, Edwards W, Poulton R. A one-size-fits-all approach to data-sharing will not suffice in lifecourse research: a grounded theory study of data-sharing from the perspective of participants in a 50-year-old lifecourse study about health and development. BMC Med Res Methodol 2023; 23:118. [PMID: 37194009 DOI: 10.1186/s12874-023-01940-6] [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: 06/29/2022] [Accepted: 05/05/2023] [Indexed: 05/18/2023] Open
Abstract
BACKGROUND Data-sharing is increasingly encouraged or required by funders and journals. Data-sharing is more complicated for lifecourse studies that rely upon ongoing participation, but little is known about perspectives on data-sharing among participants of such studies. The aim of this qualitative study was to explore perspectives on data-sharing of participants in a birth cohort study. METHODS Semi-structured interviews were conducted with 25 members of the Dunedin Multidisciplinary Health and Development Study when aged between 45 and 48 years. Interviews were led by the Director of the Dunedin Study and involved questions about different scenarios for data-sharing. The sample consisted of nine Dunedin Study members who are Māori (the Indigenous peoples of Aotearoa/New Zealand) and 16 who are non-Māori. RESULTS Principles of grounded theory were applied to develop a model of participant perspectives on data-sharing. The model consists of three factors that inform a core premise that a one-size-fits-all approach to data-sharing will not suffice in lifecourse research. Participants suggested that data-sharing decisions should depend on the cohort and might need to be declined if any one Dunedin Study member was opposed (factor 1). Participants also expressed a proven sense of trust in the researchers and raised concerns about loss of control once data have been shared (factor 2). Participants described a sense of balancing opportunities for public good against inappropriate uses of data, highlighting variability in perceived sensitivity of data, and thus a need to take this into account if sharing data (factor 3). CONCLUSIONS Communal considerations within cohorts, loss of control over shared data, and concerns about inappropriate uses of shared data need to be addressed through detailed informed consent before data-sharing occurs for lifecourse studies, particularly where this has not been established from the start of the study. Data-sharing may have implications for the retention of participants in these studies and thus may impact on the value of long-term sources of knowledge about health and development. Researchers, ethics committees, journal editors, research funders, and government policymakers need to consider participants' views when balancing the proposed benefits of data-sharing against the potential risks and concerns of participants in lifecourse research.
Collapse
Affiliation(s)
- Jane Reeves
- Department of Psychology, University of Otago, PO Box 56, Dunedin, Aotearoa, 9054, New Zealand
| | - Gareth J Treharne
- Department of Psychology, University of Otago, PO Box 56, Dunedin, Aotearoa, 9054, New Zealand.
| | - Mihi Ratima
- Te Pou Tiringa, New Plymouth, Aotearoa, New Zealand
| | - Reremoana Theodore
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, PO Box 56, Dunedin, Aotearoa, 9054, New Zealand
| | - Will Edwards
- Taumata Associates, New Plymouth, Aotearoa, New Zealand
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, PO Box 56, Dunedin, Aotearoa, 9054, New Zealand
| |
Collapse
|
12
|
Allen C. User experience of a family health history chatbot: A quantitative analysis. RESEARCH SQUARE 2023:rs.3.rs-2886804. [PMID: 37205400 PMCID: PMC10187455 DOI: 10.21203/rs.3.rs-2886804/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Objective Family health history (FHx) is an important tool in assessing one's risk towards specific health conditions. However, user experience of FHx collection tools is rarely studied. ItRunsInMyFamily.com (ItRuns) was developed to assess FHx and hereditary cancer risk. This study reports a quantitative user experience analysis of ItRuns. Methods We conducted a public health campaign in November 2019 to promote FHx collection using ItRuns. We used software telemetry to quantify abandonment and time spent on ItRuns to identify user behaviors and potential areas of improvement. Results Of 11065 users who started the ItRuns assessment, 4305 (38.91%) reached the final step to receive recommendations about hereditary cancer risk. Highest abandonment rates were during Introduction (32.82%), Invite Friends (29.03%), and Family Cancer History (12.03%) subflows. Median time to complete the assessment was 636 seconds. Users spent the highest median time on Proband Cancer History (124.00 seconds) and Family Cancer History (119.00 seconds) subflows. Search list questions took the longest to complete (median 19.50 seconds), followed by free text email input (15.00 seconds). Conclusion Knowledge of objective user behaviors at a large scale and factors impacting optimal user experience will help enhance the ItRuns workflow and improve future FHx collection.
Collapse
|
13
|
Cumyn A, Ménard JF, Barton A, Dault R, Lévesque F, Ethier JF. Patients' and Members of the Public's Wishes Regarding Transparency in the Context of Secondary Use of Health Data: Scoping Review. J Med Internet Res 2023; 25:e45002. [PMID: 37052967 PMCID: PMC10141314 DOI: 10.2196/45002] [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: 12/12/2022] [Revised: 02/09/2023] [Accepted: 03/03/2023] [Indexed: 03/06/2023] Open
Abstract
BACKGROUND Secondary use of health data has reached unequaled potential to improve health systems governance, knowledge, and clinical care. Transparency regarding this secondary use is frequently cited as necessary to address deficits in trust and conditional support and to increase patient awareness. OBJECTIVE We aimed to review the current published literature to identify different stakeholders' perspectives and recommendations on what information patients and members of the public want to learn about the secondary use of health data for research purposes and how and in which situations. METHODS Using PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we conducted a scoping review using Medline, CINAHL, PsycINFO, Scopus, Cochrane Library, and PubMed databases to locate a broad range of studies published in English or French until November 2022. We included articles reporting a stakeholder's perspective or recommendations of what information patients and members of the public want to learn about the secondary use of health data for research purposes and how or in which situations. Data were collected and analyzed with an iterative thematic approach using NVivo. RESULTS Overall, 178 articles were included in this scoping review. The type of information can be divided into generic and specific content. Generic content includes information on governance and regulatory frameworks, technical aspects, and scientific aims. Specific content includes updates on the use of one's data, return of results from individual tests, information on global results, information on data sharing, and how to access one's data. Recommendations on how to communicate the information focused on frequency, use of various supports, formats, and wording. Methods for communication generally favored broad approaches such as nationwide publicity campaigns, mainstream and social media for generic content, and mixed approaches for specific content including websites, patient portals, and face-to-face encounters. Content should be tailored to the individual as much as possible with regard to length, avoidance of technical terms, cultural competence, and level of detail. Finally, the review outlined 4 major situations where communication was deemed necessary: before a new use of data, when new test results became available, when global research results were released, and in the advent of a breach in confidentiality. CONCLUSIONS This review highlights how different types of information and approaches to communication efforts may serve as the basis for achieving greater transparency. Governing bodies could use the results: to elaborate or evaluate strategies to educate on the potential benefits; to provide some knowledge and control over data use as a form of reciprocity; and as a condition to engage citizens and build and maintain trust. Future work is needed to assess which strategies achieve the greatest outreach while striking a balance between meeting information needs and use of resources.
Collapse
Affiliation(s)
- Annabelle Cumyn
- Département de médecine, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Jean-Frédéric Ménard
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
- Faculté de droit, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Adrien Barton
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
- Institut de recherche en informatique de Toulouse, Toulouse, France
| | - Roxanne Dault
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Frédérique Lévesque
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Jean-François Ethier
- Département de médecine, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
- Groupe de recherche interdisciplinaire en informatique de la santé, Faculté des sciences/Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
| |
Collapse
|
14
|
Hillebrand K, Hornuf L, Müller B, Vrankar D. The social dilemma of big data: Donating personal data to promote social welfare. INFORMATION AND ORGANIZATION 2023. [DOI: 10.1016/j.infoandorg.2023.100452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
|
15
|
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.
Collapse
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
| |
Collapse
|
16
|
Li G, Togo R, Ogawa T, Haseyama M. Compressed gastric image generation based on soft-label dataset distillation for medical data sharing. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 227:107189. [PMID: 36323177 DOI: 10.1016/j.cmpb.2022.107189] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 07/07/2022] [Accepted: 10/17/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND AND OBJECTIVE Sharing of medical data is required to enable the cross-agency flow of healthcare information and construct high-accuracy computer-aided diagnosis systems. However, the large sizes of medical datasets, the massive amount of memory of saved deep convolutional neural network (DCNN) models, and patients' privacy protection are problems that can lead to inefficient medical data sharing. Therefore, this study proposes a novel soft-label dataset distillation method for medical data sharing. METHODS The proposed method distills valid information of medical image data and generates several compressed images with different data distributions for anonymous medical data sharing. Furthermore, our method can extract essential weights of DCNN models to reduce the memory required to save trained models for efficient medical data sharing. RESULTS The proposed method can compress tens of thousands of images into several soft-label images and reduce the size of a trained model to a few hundredths of its original size. The compressed images obtained after distillation have been visually anonymized; therefore, they do not contain the private information of the patients. Furthermore, we can realize high-detection performance with a small number of compressed images. CONCLUSIONS The experimental results show that the proposed method can improve the efficiency and security of medical data sharing.
Collapse
Affiliation(s)
- Guang Li
- Graduate School of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-Ku, Sapporo, 060-0814, Japan.
| | - Ren Togo
- Faculty of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-Ku, Sapporo, 060-0814, Japan.
| | - Takahiro Ogawa
- Faculty of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-Ku, Sapporo, 060-0814, Japan.
| | - Miki Haseyama
- Faculty of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-Ku, Sapporo, 060-0814, Japan.
| |
Collapse
|
17
|
Karway G, Ivanova J, Kaing T, Todd M, Chern D, Murcko A, Syed K, Garcia M, Franczak M, Whitfield MJ, Grando MA. My data choices: Pilot evaluation of patient-controlled medical record sharing technology. Health Informatics J 2022; 28:14604582221143893. [DOI: 10.1177/14604582221143893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Patients desire greater control over sharing their digital health data. Consent2Share (C2S) is an open-source consent tool offered by SAMHA and the VA to support granular data sharing (GDS) options that align with patient preferences and data privacy regulations. The need to validate this tool exists. We pilot tested C2S with 199 English and Spanish-speaking patients with behavioral health conditions (BHCs) and patient guardians. Data were analyzed using mixed methodology. All participants desired granular control over the sharing of their health data. Most participants (87%) were highly interested in using a tool that offered granular options for executing data sharing decisions, with over half (55%) indicated that being able to specify the data type, data recipient, and data use purpose made them more willing to share their medical records. Majority (83%) indicated that the supported data type sharing categories satisfied their data-sharing privacy preferences. Majority (87%) also reported that knowing the purpose of data use made them more comfortable in sharing. Some participants (28%) accessed the education materials provided on data type sharing options. Patients want granular choices when sharing medical records. Consent2Share and its supported data type sharing categories are adequate to capture patients’ data sharing preferences. Further development is needed before deployment in clinical environments.
Collapse
|
18
|
Corman A, Canaway R, Culnane C, Teague V. Public comprehension of privacy protections applied to health data shared for research: an Australian cross-sectional study. Int J Med Inform 2022; 167:104859. [DOI: 10.1016/j.ijmedinf.2022.104859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 08/10/2022] [Accepted: 08/22/2022] [Indexed: 10/31/2022]
|
19
|
Ivanova J, Tang T, Idouraine N, Murcko A, Whitfield MJ, Dye C, Chern D, Grando A. Behavioral Health Professionals' Perceptions on Patient-Controlled Granular Information Sharing (Part 2): Focus Group Study. JMIR Ment Health 2022; 9:e18792. [PMID: 35442213 PMCID: PMC9069296 DOI: 10.2196/18792] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2020] [Revised: 11/30/2020] [Accepted: 09/28/2021] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Patient-directed selection and sharing of health information "granules" is known as granular information sharing. In a previous study, patients with behavioral health conditions categorized their own health information into sensitive categories (eg, mental health) and chose the health professionals (eg, pharmacists) who should have access to those records. Little is known about behavioral health professionals' perspectives of patient-controlled granular information sharing (PC-GIS). OBJECTIVE This study aimed to assess behavioral health professionals' (1) understanding of and opinions about PC-GIS; (2) accuracy in assessing redacted medical information; (3) reactions to patient rationale for health data categorization, assignment of sensitivity, and sharing choices; and (4) recommendations to improve PC-GIS. METHODS Four 2-hour focus groups and pre- and postsurveys were conducted at 2 facilities. During the focus groups, outcomes from a previous study on patients' choices for medical record sharing were discussed. Thematic analysis was applied to focus group transcripts to address study objectives. RESULTS A total of 28 health professionals were recruited. Over half (14/25, 56%) were unaware or provided incorrect definitions of granular information sharing. After PC-GIS was explained, all professionals demonstrated understanding of the terminology and process. Most (26/32 codes, 81%) recognized that key medical data had been redacted from the study case. A majority (41/62 codes, 66%) found the patient rationale for categorization and data sharing choices to be unclear. Finally, education and other approaches to inform and engage patients in granular information sharing were recommended. CONCLUSIONS This study provides detailed insights from behavioral health professionals on granular information sharing. Outcomes will inform the development, deployment, and evaluation of an electronic consent tool for granular health data sharing.
Collapse
Affiliation(s)
- Julia Ivanova
- School of Human Evolution and Social Change, Arizona State University, Tempe, AZ, United States
| | - Tianyu Tang
- College of Medicine, University of Arizona, Tucson, AZ, United States
| | - Nassim Idouraine
- College of Health Solutions, Biomedical Informatics, Arizona State University, Scottsdale, AZ, United States
| | - Anita Murcko
- College of Health Solutions, Biomedical Informatics, Arizona State University, Scottsdale, AZ, United States
| | | | - Christy Dye
- Partners in Recovery, Phoenix, AZ, United States
| | - Darwyn Chern
- Partners in Recovery, Phoenix, AZ, United States
| | - Adela Grando
- College of Health Solutions, Biomedical Informatics, Arizona State University, Scottsdale, AZ, United States
| |
Collapse
|
20
|
Ivanova J, Tang T, Idouraine N, Murcko A, Whitfield MJ, Dye C, Chern D, Grando A. Behavioral Health Professionals' Perceptions on Patient-Controlled Granular Information Sharing (Part 1): Focus Group Study. JMIR Ment Health 2022; 9:e21208. [PMID: 35442199 PMCID: PMC9069278 DOI: 10.2196/21208] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 10/17/2020] [Accepted: 09/28/2021] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Patient-controlled granular information sharing (PC-GIS) allows a patient to select specific health information "granules," such as diagnoses and medications; choose with whom the information is shared; and decide how the information can be used. Previous studies suggest that health professionals have mixed or concerned opinions about the process and impact of PC-GIS for care and research. Further understanding of behavioral health professionals' views on PC-GIS are needed for successful implementation and use of this technology. OBJECTIVE The aim of this study was to evaluate changes in health professionals' opinions on PC-GIS before and after a demonstrative case study. METHODS Four focus groups were conducted at two integrated health care facilities: one serious mental illness facility and one general behavioral health facility. A total of 28 participants were given access to outcomes of a previous study where patients had control over medical record sharing. Participants were surveyed before and after focus groups on their views about PC-GIS. Thematic analysis of focus group output was paired with descriptive statistics and exploratory factor analysis of surveys. RESULTS Behavioral health professionals showed a significant opinion shift toward concern after the focus group intervention, specifically on the topics of patient understanding (P=.001), authorized electronic health record access (P=.03), patient-professional relationship (P=.006), patient control acceptance (P<.001), and patient rights (P=.02). Qualitative methodology supported these results. The themes of professional considerations (2234/4025, 55.5% of codes) and necessity of health information (260/766, 33.9%) identified key aspects of PC-GIS concerns. CONCLUSIONS Behavioral health professionals agreed that a trusting patient-professional relationship is integral to the optimal implementation of PC-GIS, but were concerned about the potential negative impacts of PC-GIS on patient safety and quality of care.
Collapse
Affiliation(s)
- Julia Ivanova
- School of Human Evolution and Social Change, Arizona State University, Tempe, AZ, United States
| | - Tianyu Tang
- College of Medicine, University of Arizona, Tucson, AZ, United States
| | - Nassim Idouraine
- College of Health Solutions, Biomedical Informatics, Arizona State University, Scottsdale, AZ, United States
| | - Anita Murcko
- College of Health Solutions, Biomedical Informatics, Arizona State University, Scottsdale, AZ, United States
| | | | - Christy Dye
- Partners in Recovery, Phoenix, AZ, United States
| | - Darwyn Chern
- Partners in Recovery, Phoenix, AZ, United States
| | - Adela Grando
- College of Health Solutions, Biomedical Informatics, Arizona State University, Scottsdale, AZ, United States
| |
Collapse
|
21
|
Kirkham EJ, Lawrie SM, Crompton CJ, Iveson MH, Jenkins ND, Goerdten J, Beange I, Chan SWY, McIntosh A, Fletcher-Watson S. Experience of clinical services shapes attitudes to mental health data sharing: findings from a UK-wide survey. BMC Public Health 2022; 22:357. [PMID: 35183146 PMCID: PMC8858475 DOI: 10.1186/s12889-022-12694-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 02/02/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Routinely-collected mental health data could deliver novel insights for mental health research. However, patients' willingness to share their mental health data remains largely unknown. We investigated factors influencing likelihood of sharing these data for research purposes amongst people with and without experience of mental illness. METHODS We collected responses from a diverse sample of UK National Health Service (NHS) users (n = 2187) of which about half (n = 1087) had lifetime experience of mental illness. Ordinal logistic regression was used to examine the influence of demographic factors, clinical service experience, and primary mental illness on willingness to share mental health data, contrasted against physical health data. RESULTS There was a high level of willingness to share mental (89.7%) and physical (92.8%) health data for research purposes. Higher levels of satisfaction with the NHS were associated with greater willingness to share mental health data. Furthermore, people with personal experience of mental illness were more willing than those without to share mental health data, once the variable of NHS satisfaction had been controlled for. Of the mental illnesses recorded, people with depression, obsessive-compulsive disorder (OCD), personality disorder or bipolar disorder were significantly more likely to share their mental health data than people without mental illness. CONCLUSIONS These findings suggest that positive experiences of health services and personal experience of mental illness are associated with greater willingness to share mental health data. NHS satisfaction is a potentially modifiable factor that could foster public support for increased use of NHS mental health data in research.
Collapse
Affiliation(s)
- E J Kirkham
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, EH10 5HF, UK.
| | - S M Lawrie
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, EH10 5HF, UK
| | - C J Crompton
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, EH10 5HF, UK
| | - M H Iveson
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, EH10 5HF, UK
| | - N D Jenkins
- Edinburgh Dementia Prevention & Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - J Goerdten
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, EH10 5HF, UK
- Department of Epidemiological Methods and Etiological Research, Leibniz Institute for Prevention Research and Epidemiology-BIPS, Bremen, Germany
| | - I Beange
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, EH10 5HF, UK
| | - S W Y Chan
- Department of Clinical Psychology, School of Health in Social Science, University of Edinburgh, Edinburgh, UK
- School of Psychology & Clinical Language Sciences, University of Reading, Reading, UK
| | - A McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, EH10 5HF, UK
| | - S Fletcher-Watson
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Kennedy Tower, Royal Edinburgh Hospital, Morningside Park, Edinburgh, EH10 5HF, UK
| |
Collapse
|
22
|
Evaluating the Balance Between Privacy and Access in Digital Information Sharing. Crit Care Med 2021; 50:e109-e116. [PMID: 34637416 PMCID: PMC8797001 DOI: 10.1097/ccm.0000000000005234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Supplemental Digital Content is available in the text. Access to personal health records in an ICU by persons involved in the patient’s care (referred to broadly as “family members” below) has the potential to increase engagement and reduce the negative psychologic sequelae of such hospitalizations. Currently, little is known about patient preferences for information sharing with a designated family member in the ICU. We sought to understand the information-sharing preferences of former ICU patients and their family members and to identify predictors of information-sharing preferences.
Collapse
|
23
|
Soni H, Ivanova J, Grando A, Murcko A, Chern D, Dye C, Whitfield MJ. A pilot comparison of medical records sensitivity perspectives of patients with behavioral health conditions and healthcare providers. Health Informatics J 2021; 27:14604582211009925. [PMID: 33878989 DOI: 10.1177/14604582211009925] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
This pilot study compares medical record data sensitivity (e.g., depression is sensitive) and categorization perspective (e.g., depression categorized as mental health information) of patients with behavioral health conditions and healthcare providers using a mixed-methods approach employing patient's own EHR. Perspectives of 25 English- and Spanish-speaking patients were compared with providers. Data categorization comparisons resulted in 66.3% agreements, 14.5% partial agreements, and 19.3% disagreements. Sensitivity comparisons obtained 54.5% agreement, 11.9% partial agreement, and 33.6% disagreements. Patients and providers disagreed in classification of genetic data, mental health, drug abuse, and physical health information. Factors influencing patients' sensitivity determination were sensitive category comprehension, own experience, stigma towards category labels (e.g., drug abuse), and perception of information applicability (e.g., alcohol dependency). Knowledge of patients' sensitivity perceptions and reconciliation with providers could expedite the development of granular and personalized consent technology.
Collapse
|
24
|
Grando A, Sottara D, Singh R, Murcko A, Soni H, Tang T, Idouraine N, Todd M, Mote M, Chern D, Dye C, Whitfield MJ. Pilot evaluation of sensitive data segmentation technology for privacy. Int J Med Inform 2020; 138:104121. [PMID: 32278288 DOI: 10.1016/j.ijmedinf.2020.104121] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2019] [Revised: 03/12/2020] [Accepted: 03/13/2020] [Indexed: 11/17/2022]
Abstract
BACKGROUND Consent2Share (C2S) is an open source software created by the Office of the National Coordinator Data Segmentation for Privacy initiative to support electronic health record (EHR) granular segmentation. To date, there are no published formal evaluations of Consent2Share. METHOD Structured data (e.g. medications) codified using standard clinical terminologies (e.g. RxNorm) was extracted from the EHR of 36 patients with behavioral health conditions from study sites. EHRs were available through a health information exchange and two sites. The EHR data was already classified into data types (e.g. procedures and services). Both Consent2Share and health providers classified EHR data based on value sets (e.g. mental health) and sensitivity (e.g. not sensitive. Descriptive statistics and Chi-square analysis were used to compare differences between data categorizations. RESULTS From the resulting 1,080 medical records items, 584 were distinct. Significant differences were found between sensitivity classifications by Consent2Share and providers (χ2 (2, N = 584) = 114.74, p = <0.0001). Sensitivity comparisons led to 56.0 % of agreements, 31.2 % disagreements, and 12.8 % partial agreements. Most (97.8 %) disagreements resulted from information classified as not sensitive by Consent2Share, but sensitive by provider (e.g. behavioral health prevention education service). In terms of data types, most disagreements (57.1 %) focused on procedures and services information (e.g. ligation of fallopian tube). When considering value sets, most disagreements focused on genetic data (100.0 %), followed by sexual and reproductive health (88.9 %). CONCLUSIONS There is a need to further validate Consent2Share before broad use in health care settings. The outcomes from this pilot study will help guide improvements in segmentation logic of tools like Consent2Share and may set the stage for a new generation of personalized consent engines.
Collapse
Affiliation(s)
- Adela Grando
- Biomedical Informatics, College of Health Solutions, Arizona State University, Scottsdale, AZ, United States.
| | | | - Ripudaman Singh
- School of Computing, Informatics and Decision Systems Engineering, Tempe, AZ, United States
| | - Anita Murcko
- Biomedical Informatics, College of Health Solutions, Arizona State University, Scottsdale, AZ, United States
| | - Hiral Soni
- Biomedical Informatics, College of Health Solutions, Arizona State University, Scottsdale, AZ, United States
| | - Tianyu Tang
- University of Arizona, College of Medicine, Tucson, AZ, United States
| | - Nassim Idouraine
- Biomedical Informatics, College of Health Solutions, Arizona State University, Scottsdale, AZ, United States
| | - Michael Todd
- College of Nursing and Health Innovation, Arizona State University, Phoenix, United States
| | - Mike Mote
- Health Current, Phoenix, AZ, United States
| | - Darwyn Chern
- Partners in Recovery, Phoenix, AZ, United States
| | - Christy Dye
- Partners in Recovery, Phoenix, AZ, United States
| | | |
Collapse
|