Potential medical adverse events associated with death: a forensic pathology perspective.
OBJECTIVE
To determine the incidence of potential medical adverse events among patients undergoing forensic autopsy, and to present the characteristics of potential medical adverse events.


METHODS
Retrospective review of consecutive autopsy records.


METHODS
Department of Forensic Medicine, the Jikei University School of Medicine, Tokyo, Japan.


METHODS
A total of 3355 forensic autopsy cases between 1983 and 2006.


METHODS
Incidence of potential medical adverse events identified in decedents undergoing forensic autopsy, classified by actual occurrence as 'confirmed', 'equivocal' and 'negative' cases; proportion of potential diagnostic, performance and system errors among potential medical adverse events.


RESULTS
Of 291 autopsies (8.7%) with potential medical adverse events, 66 cases (22.7%) were confirmed, 42 cases (14.4%) were negative and 183 cases (62.9%) were equivocal. Confirmed cases consisted of potential diagnostic errors in 49 cases (74.2%) and performance errors in 17 cases (25.8%). Equivocal cases included 99 cases associated with potential diagnostic errors (54.1%) and 60 cases associated with potential system errors (32.8%). In 38 of the confirmed cases (57.5%), serious exacerbation of patient condition occurred outside the medical facility.


CONCLUSIONS
Potential medical adverse events are not uncommon in decedents undergoing forensic autopsy. They are particularly associated with potential diagnostic errors. Forensic autopsy may provide information that could be used to improve care and reduce deaths due to potential medical adverse events.
Sakai
Kentaro
K
Department of Forensic Medicine, The Jikei University School of Medicine, 3-25-8, Nishi-Shimbashi, Minato-ku, Tokyo 105-8461, Japan. kentaro.sakai@jikei.ac.jp
Takatsu
Akihiro
A
Shigeta
Akio
A
Fukui
Kenji
K
Maebashi
Kyoko
K
Abe
Shuntaro
S
Iwadate
Kimiharu
K
D000367:Age Factors; D001344:Autopsy; D005260:Female; D049429:Forensic Pathology; D006801:Humans; D008297:Male; D019300:Medical Errors / Q000145:classification* / Q000706:statistics & numerical data*; D008875:Middle Aged; D012189:Retrospective Studies; D012737:Sex Factors