Management of operating room is essential in a hospital as it affects the budget, time, reputation, and patient satisfaction.
FREMONT, CA: Optimizing management of multiple hospital operation rooms (OR) is very complex. It has been seen that delays in OR procedures due to mix-ups and lapses in scheduling and resource availability account for countless surgical delays and a significant number of postsurgical complications. The situation gets complicated because patients can differ so much; even standard procedures can need substantial variations in the time required for the process.
There has been a breakthrough known as the CORNET artificial intelligent (AI) system. This offers an innovative and cost-effective hardware/software OR awareness solution that can detect the step of a given procedure the OR staff is at, determine if steps are out of order, identify procedural delays, irregularities and unused OR time, recognize missed steps, and assist in root cause identification, analyses, and assessment.
Optimal OR scheduling methods predict specific lengths of surgeries on the basis of procedure being performed and do not take into account the differentiation in medical teams’ performance. The reality is that each specific OR method needs to form a complex and multi-skilled team led by a surgeon in a particular block of time; mostly for differing amounts of time for the same procedure.
Another unfortunate reality is that surgical procedures need to be either delayed or cancelled too often because of the previous procedures which have taken more time than expected or if they did not begin on time in the first place. Furthermore, surgical teams can lead to conflicts of space and time that had been reserved for other scheduled procedures.
A team of researchers have developed an agent-based mathematical solution that reintroduces the human factor into the equation. The OR/AI system considers multiple factors from several levels of the hospital organization. It automatically informs what becomes, in essence, smarter OR units. It does that unobtrusively, without getting in the way of the functioning of surgical teams. The model is capable of providing better-informed recommendations for improving OR management in real-time, and timely alerts when the decisions to adjust and adapt has to be taken in order to improve scheduling or minimize delays.