(075) Crowdsourcing Catatonia: Medical Crowdsourcing in Challenging Clinical Cases

Abstract:

Introduction:

Medicine has a longstanding tradition of collaboration for complex cases, including informal “curbside consultations”, case conferences, and grand rounds to recruit collective wisdom. Information technologies present opportunities to build on this tradition of collaboration, while decreasing barriers (Radcliffe,2019;Sims,2019;Perley,2006). We present the use of an email listserv to crowdsource management recommendations for treatment-refractory catatonia, highlighting this novel method of medical crowdsourcing.

Case Report:

A woman in her 30s with a history of schizophrenia and developmental delay was admitted to hospital with symptoms of catatonia. Evidence-based treatments were trialed, including discontinuation of antipsychotic treatment, initiation of lorazepam up to 20mg daily, and thrice weekly electroconvulsive therapy. Numerous sub-specialty consultations yielded no clinical improvement. Subsequently, input was sought from the Academy of CL Psychiatry’s Neuropsychiatry email listserv to crowdsource recommendations.

Methods/Results:

With consent from the patient’s substitute decision maker, the case was circulated on the listserv to over 800 members. We received 52 responses from clinicians globally, which were qualitatively coded. Of the responses received: 45 related to diagnostic clarification; 28 provided treatment recommendations; 11 recommended further resources; 18 included disclosures of clinical experiences; and 38 offered rationale for suggestions.

These responses highlighted the need to complete further work-up to rule-out underlying neurological or physiological causes, which were pursued and found to be non-contributory. They also highlighted potential treatment with the NMDA receptor antagonist memantine. This was initiated, leading to robust clinical improvement in this case.

Discussion:

Currently, medical crowdsourcing is not a mainstream practice. A review by Radcliffe et al. (2019) identified only four articles describing medical crowdsourcing pertaining directly to patient care (Radcliffe,2019). However, users feel it can help problem-solve at point-of-care and diagnose challenging cases (Sims,2019; Sims,2014).

With respect to this case, we established a subjective hierarchy of responses received. Responses that highlighted academic evidence and those with context/rational (e.g. previous clinical experiences), were considered as more helpful than those without.

Conclusion:

This case highlights the use of medical crowdsourcing via a listserv to help improve clinical care and patient outcomes. Medical crowdsourcing should be considered to enhance clinical care in challenging cases, incorporating the collective knowledge of clinicians worldwide.

References:

Radcliffe K, Lyson HC, Barr-Walker J, Sarkar U. Collective intelligence in medical decision-making: a systematic scoping review. BMC Med Inform Decis Mak. 2019;19(1):158.

Sims MH, Hodges Shaw M, Gilbertson S, Storch J, Halterman MW. Legal and ethical issues surrounding the use of crowdsourcing among healthcare providers. Health Informatics J. 2019 Dec;25(4):1618-1630.

Perley CM. Physician use of the curbside consultation to address information needs: report on a collective case study. J Med Libr Assoc. 2006;94(2):137-144.

Sims, Bigham, J., Kautz, H., & Halterman, M. W. Crowdsourcing medical expertise in near real time. Journal of Hospital Medicine. 2014; 9(7), 451–456.

Presenting Author(s)

Kathleen Sheehan, MD, DPhil, FRCPC

Assistant Professor
University of Toronto
Toronto, Ontario, Canada

Co-Author(s)

Alexander G. Bahadur, MD

Psychiatry Resident
University of Toronto
Toronto, Ontario, Canada
Jason C. Perdue, MD

Psychiatry Resident
University of Toronto
Toronto, Ontario, Canada