Cause and effect analysis of closed claims in obstetrics and gynecology.
BACKGROUND
Identifying the etiologies of real or perceived adverse clinical events and undesired outcomes is an important step in improving patient safety and reducing malpractice risks. Systematic analysis of obstetrics and gynecology-related risk management files allows a more complete examination of ways that human and systems factors may contribute to adverse events.


OBJECTIVE
To learn the medical complaints of patients who experienced apparent adverse events, the general causes of those adverse events, and the significant specific causal factors involved in obstetrics and gynecology-related risk management cases.


METHODS
This was a retrospective analysis of 90 consecutive obstetrics and gynecology-related internal review files opened by a medical center's risk managers between 1995 and 2001. Each file was analyzed to identify factors that may have contributed to or caused unanticipated adverse events. The main outcome was the pattern of contributing factors when they were aggregated into categories.


RESULTS
Fifty percent of cases were associated with inpatient obstetrics. Factors that may have contributed to adverse events were identified in 78% of cases, and most had more than one contributing factor. Thirty-one percent of adverse events were associated with apparent communication problems. Clinical performance issues were identified in 31% of cases, diagnostic issues in 18% of cases, and patient behavior contributed to 14% of adverse events.


CONCLUSIONS
Diagnostic, therapeutic, and communication issues were the most common factors identified. Although the generalizability of these data are unknown, all obstetrics and gynecology departments face multiple challenges in assuring consistent quality care. Analysis of claims files may help identify opportunities for improvement.
White
Andrew A
AA
Vanderbilt University School of Medicine, Nashville, USA.
Pichert
James W
JW
Bledsoe
Sandra H
SH
Irwin
Cindy
C
Entman
Stephen S
SS
D015331:Cohort Studies; D003675:Defensive Medicine / Q000379:methods; D005260:Female; D006176:Gynecology / Q000592:standards* / Q000706:statistics & numerical data; D006785:Hospitals, University / Q000706:statistics & numerical data; D006801:Humans; D007049:Iatrogenic Disease / Q000453:epidemiology*; D008318:Malpractice / Q000706:statistics & numerical data; D008485:Medical Audit; D019300:Medical Errors / Q000145:classification / Q000706:statistics & numerical data*; D009774:Obstetrics / Q000592:standards* / Q000706:statistics & numerical data; D010817:Physician-Patient Relations; D011247:Pregnancy; D012189:Retrospective Studies; D012308:Risk Management; D013597:Systems Analysis; D013714:Tennessee / Q000453:epidemiology