Cause-and-effect analysis of risk management files to assess patient care in the emergency department

• Published in: Academic emergency medicine 2004-10, Vol.11 (10), p.1035-1041
• Main Authors: White, Andrew A, Wright, Seth W, Blanco, Roberto, Lemonds, Brent, Sisco, Janice, Bledsoe, Sandy, Irwin, Cindy, Isenhour, Jennifer, Pichert, James W
• Format: Article
• Language: English
• Subjects: Causality; Consumer Behavior - statistics & numerical data; Diagnostic Errors - statistics & numerical data; Documentation - statistics & numerical data; Emergency Service, Hospital - standards; Emergency Service, Hospital - statistics & numerical data; Guideline Adherence - statistics & numerical data; Humans; Internship and Residency - statistics & numerical data; Medical Staff, Hospital - organization & administration; Outcome and Process Assessment (Health Care) - methods; Retrospective Studies; Risk Management - methods; Risk Management - statistics & numerical data; Southeastern United States
• ISSN: 1069-6563; 1553-2712
• DOI: 10.1111/j.1553-2712.2004.tb00674.x

Identifying the etiologies of adverse outcomes is an important first step in improving patient safety and reducing malpractice risks. However, relatively little is known about the causes of emergency department-related adverse outcomes. The objective was to describe a method for identification of common causes of adverse outcomes in an emergency department. This methodology potentially can suggest ways to improve care and might provide a model for identification of factors associated with adverse outcomes. This was a retrospective analysis of 74 consecutive files opened by a malpractice insurer between 1995 and 2000. Each risk-management file was analyzed to identify potential causes of adverse outcomes. The main outcomes were rater-assigned codes for alleged problems with care (e.g., failures of communication or problems related to diagnosis). About 50% of cases were related to injuries or abdominal complaints. A contributing cause was found in 92% of cases, and most had more than one contributing cause. The most frequent contributing categories included failure to diagnose (45%), supervision problems (31%), communication problems (30%), patient behavior (24%), administrative problems (20%), and documentation (20%). Specific relating factors within these categories, such as lack of timely resident supervision and failure to follow policies and procedures, were identified. This project documented that an aggregate analysis of risk-management files has the potential to identify shared causes related to real or perceived adverse outcomes. Several potentially correctable systems problems were identified using this methodology. These simple, descriptive management tools may be useful in identifying issues for problem solving and can be easily learned by physicians and managers.