How Can Reasoned Transparency Enhance Co-Creation in Health Care and Remedy the Pitfalls of Digitization in Doctor-Patient Relationships?

Document Type : Perspective

Authors

1 Solvay Brussels School of Economics and Management, Université libre de Bruxelles (ULB), Brussels, Belgium

2 Department of Visceral Surgery, Lausanne University Hospital CHUV, Lausanne, Switzerland

Abstract

This article addresses transparency in the current era of digital co-creation between healthcare professionals and patients. The concept of reasoned transparency is presented as a potential tool to guide the development of digital co-creation that is rapidly growing. The aim was to reflect on how doctors can apply transparency in their daily practice, following the shift from paternalistic to more collaborative relationships. On the one hand, our contribution indicates ways to take advantage of the existing digital tools to improve efficiency and increase patient trust, including the latest trend of artificial intelligence. On the other hand, this article identifies pitfalls of digitization and proposes reasoned transparency as remedy for the challenges rose by artificial intelligence. As a result, this perspective article tackles the issue of maintaining trustful and high-quality relationships between doctors and patients, increasingly challenged by the dissemination of online information and the pressures on healthcare professionals’ accountability towards patients and the general public.

Keywords


  1. Levay C, Waks C. Professions and the pursuit of transparency in healthcare: two cases of soft autonomy. Organ Stud. 2009;30(5):509-527. doi:10.1177/0170840609104396
  2. Pronovost PJ, Wu AW, Austin JM. Time for transparent standards in quality reporting by health care organizations. JAMA. 2017;318(8):701-702. doi:10.1001/jama.2017.10124
  3. Goupil B, Balusson F, Naudet F, et al. Association between gifts from pharmaceutical companies to French general practitioners and their drug prescribing patterns in 2016: retrospective study using the French Transparency in Healthcare and National Health Data System databases. BMJ. 2019;367:l6015. doi:10.1136/bmj.l6015
  4. Oettgen P. Transparency in Healthcare. EBSCO Health, DynaMed Plus. https://www.ebsco.com/sites/g/files/nabnos191/files/acquiadam-assets/66751087.pdf.
  5. Frow P, McColl-Kennedy JR, Payne A. Co-creation practices: their role in shaping a health care ecosystem. Ind Mark Manag. 2016;56:24-39. doi:10.1016/j.indmarman.2016.03.007
  6. Lusch RF, Vargo SL, Tanniru M. Service, value networks and learning. J Acad Mark Sci. 2010;38(1):19-31. doi:10.1007/s11747-008-0131-z
  7. Lee D. Effects of key value co-creation elements in the healthcare system: focusing on technology applications. Serv Bus. 2019;13(2):389-417. doi:10.1007/s11628-018-00388-9
  8. Hughes G. The Promise of Conversational AI in Helping Restore the Doctor-Patient Relationship. MedCity News; 2020.
  9. Birdas TJ, Rozycki GF, Dunnington GL, Stevens L, Liali V, Schmidt CM. "Show Me the Data": a recipe for quality improvement success in an academic surgical department. J Am Coll Surg. 2019;228(4):368-373. doi:10.1016/j.jamcollsurg.2018.12.013
  10. Coglianese C. The transparency president? the Obama administration and open government. Governance. 2009;22(4):529-544. doi:10.1111/j.1468-0491.2009.01451.x
  11. Campbell EG. Doctors and drug companies--scrutinizing influential relationships. N Engl J Med. 2007;357(18):1796-1797. doi:10.1056/NEJMp078141
  12. Lehne M, Sass J, Essenwanger A, Schepers J, Thun S. Why digital medicine depends on interoperability. NPJ Digit Med. 2019;2:79. doi:10.1038/s41746-019-0158-1
  13. Fukami T, Uemura M, Nagao Y. Significance of incident reports by medical doctors for organizational transparency and driving forces for patient safety. Patient Saf Surg. 2020;14:13. doi:10.1186/s13037-020-00240-y
  14. Leone D, Schiavone F, Appio FP, Chiao B. How does artificial intelligence enable and enhance value co-creation in industrial markets? an exploratory case study in the healthcare ecosystem. J Bus Res. 2020. doi:10.1016/j.jbusres.2020.11.008
  15. Aminololama-Shakeri S, López JE. The doctor-patient relationship with artificial intelligence. AJR Am J Roentgenol. 2019;212(2):308-310. doi:10.2214/ajr.18.20509
  16. Dowie J, Kaltoft MK. The future of health is self-production and co-creation based on apomediative decision support. Med Sci (Basel). 2018;6(3):66. doi:10.3390/medsci6030066
  17. Kuan R. Adopting AI in health care will be slow and difficult. Harv Bus Rev. 2019 October 18, 2019. https://hbr.org/2019/10/adopting-ai-in-health-care-will-be-slow-and-difficult.  Accessed January 26, 2020.
  18. Jiang F, Jiang Y, Zhi H, et al. Artificial intelligence in healthcare: past, present and future. Stroke Vasc Neurol. 2017;2(4):230-243. doi:10.1136/svn-2017-000101
  19. Spatharou A, Hieronimus S, Jenkins J. Transforming Healthcare with AI: The Impact on the Workforce and Organizations. https://www.mckinsey.com/industries/healthcare-systems-and-services/our-insights/transforming-healthcare-with-ai. Published 2020.
  20. Arora A. Conceptualising artificial intelligence as a digital healthcare innovation: an introductory review. Med Devices (Auckl). 2020;13:223-230. doi:10.2147/mder.s262590
  21. Gunning D, Stefik M, Choi J, Miller T, Stumpf S, Yang GZ. XAI-Explainable artificial intelligence. Sci Robot. 2019;4(37):eaay7120. doi:10.1126/scirobotics.aay7120
  22. Lauritsen SM, Kristensen M, Olsen MV, et al. Explainable artificial intelligence model to predict acute critical illness from electronic health records. Nat Commun. 2020;11(1):3852. doi:10.1038/s41467-020-17431-x
  23. Selbst AD, Powles J. Meaningful information and the right to explanation. Int Data Priv Law. 2017;7(4):233-242. doi:10.1093/idpl/ipx022
  24. Hajjo R. The Ethical Challenges of Applying Machine Learning and Artificial Intelligence in Cancer Care. In: 2018 1st International Conference on Cancer Care Informatics (CCI) ; November 19-21, 2018; Amman, Jordan. doi:10.1109/cancercare.2018.8618186
  25. Carter SM, Rogers W, Win KT, Frazer H, Richards B, Houssami N. The ethical, legal and social implications of using artificial intelligence systems in breast cancer care. Breast. 2020;49:25-32. doi:10.1016/j.breast.2019.10.001
  26. Habli I, Lawton T, Porter Z. Artificial intelligence in health care: accountability and safety. Bull World Health Organ. 2020;98(4):251-256. doi:10.2471/blt.19.237487
  27. Lalmuanawma S, Hussain J, Chhakchhuak L. Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: a review. Chaos Solitons Fractals. 2020;139:110059. doi:10.1016/j.chaos.2020.110059
  28. Balthazar P, Harri P, Prater A, Safdar NM. Protecting your patients' interests in the era of big data, artificial intelligence, and predictive analytics. J Am Coll Radiol. 2018;15(3 Pt B):580-586. doi:10.1016/j.jacr.2017.11.035
  29. Kostkova P, Brewer H, de Lusignan S, et al. Who owns the data? open data for healthcare. Front Public Health. 2016;4:7. doi:10.3389/fpubh.2016.00007
  30. Nagy M, Sisk B. How will artificial intelligence affect patient-clinician relationships? AMA J Ethics. 2020;22(5):E395-400. doi:10.1001/amajethics.2020.395
  31. Nundy S, Montgomery T, Wachter RM. Promoting trust between patients and physicians in the era of artificial intelligence. JAMA. 2019. doi:10.1001/jama.2018.20563