Both Bias and Lack of Knowledge Influence Organizational Focus on First Case of the Day Starts


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Abstract

BACKGROUND:The economic costs of reducing first case delays are often high, because efforts need to be applied to multiple operating rooms (ORs) simultaneously. Nevertheless, delays in starting first cases of the day are a common topic in OR committee meetings.METHODS:We added three scientific questions to a 24 question online, anonymous survey performed before the implementation of a new OR information system. The 57 respondents cared sufficiently about OR management at the United States teaching hospital to complete all questions.RESULTS:The survey revealed reasons why personnel may focus on the small reductions in nonoperative time achievable by reducing tardiness in first cases of the day. (A) Respondents lacked knowledge about principles in reducing over-utilized OR time to increase OR efficiency, based on their answering the relevant question correctly at a rate no different from guessing at random. Those results differed from prior findings of responses at a rate worse than random, resulting from a bias on the day of surgery of making decisions that increase clinical work per unit time. (B) Most respondents falsely believed that a 10 min delay at the start of the day causes subsequent cases to start at least 10 min late (P < 0.0001 versus random chance). (C) Most respondents did not know that cases often take less time than scheduled (P = 0.008 versus chance). No one who demonstrated knowledge (C) about cases sometimes taking less time than scheduled applied that information to their response to (B) regarding cases starting late (P = 0.0002).CONCLUSIONS:Knowledge of OR efficiency was low among the respondents working in ORs. Nevertheless, the apparent absence of bias shows that education may influence behavior. In contrast, presence of bias on matters of tardiness of start times shows that education may be of no benefit. As the latter results match findings of previous studies of scheduling decisions, interventions to reduce patient and surgeon waiting from start times may depend principally on the application of automation to guide decision-making.

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