A random forest and simulation approach for scheduling operation rooms: Elective surgery cancelation in a Chinese hospital urology department

Abstract

Many hospitals encounter surgery cancelations for various reasons. We present a methodology applying data mining and simulation to optimize operating room (OR) scheduling in a urology department in West China Hospital. To the best of our knowledge, this is 1 of the first efforts to seek an optimal schedule solution based on cancelation risk of elective surgeries as well as OR allocation between elective and nonelective surgeries. First, chi-square test and random forest prediction modeling were used to predict potential elective surgeries with high cancelation risk, and the factors, including surgeon, number of days since admission of patient, first surgery or not, etc., that influence elective surgery cancelation were identified. Second, a simulation technology was designed to compare 7 different scheduling strategies. The results demonstrated that for elective surgery, cancelation rate low surgery first outperformed the others and increased the productivity of the ORs from 72% to 83%, while for nonelective surgery performed in a separate OR, there was no improvement because the supply was greater than necessary at present. However, in total, the selected strategies led to 7% higher productivity.

Factors affecting in‐hospital cost and mortality of patients with stroke: Evidence from a case study in a tertiary hospital in China

“…Generally, patient's age and medical cost present a relationship of smile curve which means that higher or lower the patient's age is, the higher the medical cost is, for the relatively poor immunity of the elderly and children, and their greater difficulty to recover from the disease, prolonging the treatment time and LOS inevitably 14,21 . However, in terms of stroke, results in our study indicate that apart from adolescent group whose age were under 20 years old, with the increasing of age, the hospitalization costs of patients in other age groups decreasing relatively, but the risk of in‐hospital death increasing accordingly.…”

“…In addition to LRs (linear regression and logistic regression) methods, data mining methods 13 have been broadly employed in the literature of health care researches, such as random forest (RF), 14 gradient boosting decision tree (GBDT) 15 and artificial neural network (ANN) 16 . RF and GBDT are advanced rule‐based approaches which ensemble learning methods by developing a large number of decision trees either in parallel or serial fashion 17 .…”

Operating room planning and scheduling for outpatients and inpatients: A review and future research

“…Out of the reviewed papers, about 66% incorporate some sort of variability and the surgery duration uncertainty is most frequently taken into account in both settings. [4, 5, 7, 9, 11, 12, 14, 16, 19, 24, 28, 35, 40, 42, 47, 48, 51, 78, 87, 89, 98, 99, 102, 107, 111, 123, 126-128, 135, 142-144, 152, 156, 159, 164, 166, 171, 172, 181, 186, 187, 189, 191, 193, 199, 200] [ 4, 5, 12, 16, 19, 24, 29, 35, 44, 45, 47, 58, 65, 72, 78, 79, 87, 94, 111, 115, 123, 126-128, 135, 138, 143, 144, 152, 156, 189, 191, 195, 200, 210] Demand 33% (51/30) [2, 13, 15, 21, 22, 25-27, 30, 36, 38, 43, 50, 52, 53, 63, 68, 70, 74, 80, 86, 88, 101, 103, 105, 106, 109, 117-121, 130, 134, 147, 148, 154, 161, 162, 169, 177, 179, 183, 185, 188, 190, 192, 201-203, 212] [ 15,22,33,34,36,38,39,43,50,63,68,70,86,103,109,117,119,120,149,151,161,169,170,177,185,190,192,196,201,202] Duration 54% (79/54) [3, 6, 8, 13, 15, 18, 20, 22, 23, 26, 27, 30, 36, 38, 41, 43, 49, 53, 55, 63, 68, 69, 74, 80, 86, 88, 90, 100, 101, 105, 106, 109, 112-114, 117, 119-122, 124,...…”

Applying Lean Six Sigma to Reduce the Incidence of Unplanned Surgery Cancellation at a Large Comprehensive Tertiary Hospital in China

“…Unplanned surgery cancellation (USC) is a widespread problem for many health care organizations, [16][17][18][19][20] which causes distress and inconvenience to patients, affects health care quality, wastes operating room resource, and leads to low operational inefficiency. Many studies reported that the incidence of USC was higher than 10%, even more than 40% in Low-and middle-income countries.…”