Event-based knowledge elicitation of operating room management decision-making using scenarios adapted from information systems data

被引:13
作者
Dexter, Franklin [1 ]
Wachtel, Ruth E. [1 ]
Epstein, Richard H. [2 ]
机构
[1] Univ Iowa, Dept Anesthesia, Iowa City, IA 52242 USA
[2] Thomas Jefferson Univ, Jefferson Med Coll, Dept Anesthesiol, Philadelphia, PA 19107 USA
来源
BMC MEDICAL INFORMATICS AND DECISION MAKING | 2011年 / 11卷
关键词
SCHEDULED START TIMES; CASE DURATIONS; ANESTHESIA GROUP; ELICITING KNOWLEDGE; PREDICTION BOUNDS; EARLIER PROBLEMS; TURNOVER TIMES; LABOR COSTS; EFFICIENCY; EXAMPLES;
D O I
10.1186/1472-6947-11-2
中图分类号
R-058 [];
学科分类号
摘要
Background: No systematic process has previously been described for a needs assessment that identifies the operating room (OR) management decisions made by the anesthesiologists and nurse managers at a facility that do not maximize the efficiency of use of OR time. We evaluated whether event-based knowledge elicitation can be used practically for rapid assessment of OR management decision-making at facilities, whether scenarios can be adapted automatically from information systems data, and the usefulness of the approach. Methods: A process of event-based knowledge elicitation was developed to assess OR management decision-making that may reduce the efficiency of use of OR time. Hypothetical scenarios addressing every OR management decision influencing OR efficiency were created from published examples. Scenarios are adapted, so that cues about conditions are accurate and appropriate for each facility (e. g., if OR 1 is used as an example in a scenario, the listed procedure is a type of procedure performed at the facility in OR 1). Adaptation is performed automatically using the facility's OR information system or anesthesia information management system (AIMS) data for most scenarios (43 of 45). Performing the needs assessment takes approximately 1 hour of local managers' time while they decide if their decisions are consistent with the described scenarios. A table of contents of the indexed scenarios is created automatically, providing a simple version of problem solving using case-based reasoning. For example, a new OR manager wanting to know the best way to decide whether to move a case can look in the chapter on "Moving Cases on the Day of Surgery" to find a scenario that describes the situation being encountered. Results: Scenarios have been adapted and used at 22 hospitals. Few changes in decisions were needed to increase the efficiency of use of OR time. The few changes were heterogeneous among hospitals, showing the usefulness of individualized assessments. Conclusions: Our technical advance is the development and use of automated event-based knowledge elicitation to identify suboptimal OR management decisions that decrease the efficiency of use of OR time. The adapted scenarios can be used in future decision-making.
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页数:13
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