Abstract 10
Category: Clinical Science
At the end of the session, participants will be able to:
- Appreciate factors to consider in the laboratory management of autopsy in neuropathology
- Appreciate useful data parameters to collect and organize for laboratory management purposes
COI Disclosure:
None to disclose.
Presenter
Hao Li is a clinical fellow in Neuropathology at the Schulich School of Medicine and Dentistry, Western University (London ON). He completed his residency in Diagnostic and Molecular Pathology (previously Anatomical Pathology) at the same institution. Prior to Pathology, he also received 3 years of postgraduate medical training in Neurosurgery.
He has a clinical interest in the integration of Anatomical Pathology and Neuropathology. His academic and research interests include medical education, laboratory management and leadership, and healthcare system advocacy.
Hao Li1,2, Qi Zhang1,2
1Pathology and Laboratory Medicine, London Health Sciences Centre, London, ON, Canada
2Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
Target Audience:
Pathologists, Residents, Medical Students
CanMEDS:
Medical Expert (the integrating role), Communicator, Collaborator, Leader, Health Advocate, Scholar, Professional
An internal audit of neuropathology consultation for autopsies at the London Health Sciences Centre – a quality improvement project
Abstract
Background and Objective: In autopsy, neuropathological workups tend to be relatively extensive, requiring more tissue sampling, ancillary testing, and examination time compared to other body systems. As London Health Sciences Centre (LHSC) is a high-volume autopsy institution, in this quality improvement project we present the utility of a centralized neuropathology medical (hospital) / biobank autopsy database as an internal audit for laboratory management purposes.
Methodology: The database is a simple digital spreadsheet recording retrospectively, on all LHSC medical and biobank neuropathological autopsy consultations from 2005 to 2023, the following parameters: Case type (routine medical vs. biobank), in-house vs. externally-referred, reason for neuropathology consultation, specimens examined (eg. brain, spinal cord, muscle), age at death, dates of autopsy / brain cut / sign-out, involvement of trainees, and final diagnosis.
Results: Once established, the database is easy to utilize, and multiple laboratory management statistics can be mined using basic spreadsheet functions. These include volume trends of case types over time, proportions of different reasons for consultation, and turn-around-time as a function of other parameters such as diagnosis, deceased age, trainee involvement, among others.
Conclusions: The practical applications of an institutional neuropathology autopsy database for internal audit and laboratory management are many, including guidance on resource management based on consultation patterns, technical expertise based on specimen types, analysis of factors influencing turn-around-time, and guiding curriculum design in neuropathology education. Future directions include extending such strategy to forensic/medical-legal autopsies, which would also be useful in analyzing contributions of neuropathological consultations in addressing the forensic question.