Eric Marcon

Validation of statistical methods to compare cancellation rates on the day of surgery.

We investigated the validity of several statistical methods to monitor the cancellation of electively scheduled cases on the day of surgery: &khgr;2 test, Fisher’s exact test, Rao and Scott test, Student’s t-test, Clopper-Pearson confidence intervals, and Chen and Tipping modification of the Clopper-Pearson confidence intervals. Discrete-event computer simulation over many years was used to represent surgical suites with an unchanging cancellation rate. Because the true cancellation rate was fixed, the accuracy of the statistical methods could be determined. Cancellations caused by medical events, rare events, cases lasting longer than scheduled, and full postanesthesia or intensive care unit beds were modeled. We found that applying Student’s two-sample t-test to the transformation of the numbers of cases and canceled cases from each of six 4-wk periods was valid for most conditions. We recommend that clinicians and managers use this method in their quality monitoring reports. The other methods gave inaccurate results. For example, using &khgr;2 or Fisher’s exact test, hospitals may erroneously determine that cancellation rates have increased when they really are unchanged. Conversely, if inappropriate statistical methods are used, administrators may claim success at reducing cancellation rates when, in fact, the problem remains unresolved, affecting patients and clinicians.

Estimating the incidence of prolonged turnover times and delays by time of day.

Background:Prolonged turnover times cause frustration and can thereby reduce professional satisfaction and the workload surgeons bring to a hospital. Methods:The authors analyzed 1 yr of operating room information system data from two academic, tertiary hospitals and Monte-Carlo simulations of a 15–operating room hospital surgical suite. Results:Confidence interval widths for the mean turnover times at the hospitals were negligible when compared with the variation in sample mean turnover times among 31 hospitals. The authors developed a statistical method to estimate the proportion of all turnovers that were prolonged (> 15 min beyond mean) and that occurred during specified hours of the day. Confidence intervals for the proportions corrected for the effect of multiple comparisons. Statistical assumptions were satisfied at the two studied hospitals. The confidence intervals achieved family-wise type I error rates accurate to within 0.5% when applied to between five and nineteen 4-week periods of data. The diurnal pattern in the proportions of all turnovers that were prolonged provided different, more managerially relevant information than the time course throughout the day in the percentage of turnovers at each hour that were prolonged. Conclusions:Benchmarking sample mean turnover times among hospitals, without the use of confidence intervals, can be valid and useful. The authors successfully developed and validated a statistical method to estimate the percentage of turnover times at a surgical suite that are prolonged and occur at specified times of the day. Managers can target their quality improvement efforts on times of the day with the largest percentages of prolonged turnovers.

The operating theatre planning by the follow-up of the risk of no realization

Abstract In the French context of healthcare expenses control, the operating theatre, that represents 9% of hospitals annual budget, presents a stake of major priority. The realization of the operating theatre planning is the fruit of negotiation of different actors of the block such as surgeons, anesthetists, nurses, managerial staff, etc. whose constraints and interests are often different. In this context, a win–win situation for this partnership (all parties involved) requires a good and constructive negotiation. In this paper, we propose an operating theatre planning procedure that aims at mastering the risk of no realization (RNR) of the tentative plan while stabilizing the operating rooms’ utilization time. During the application of this planning, we achieve the follow-up of the RNR and according to its evolution the research of another planning will be proposed in order to reduce the risk level. Finally, we present results obtained by simulations that support the interest for implementing these procedures.

An observational study of surgeons' sequencing of cases and its impact on postanesthesia care unit and holding area staffing requirements at hospitals.

BACKGROUND: Staffing requirements in the operating room (OR) holding area and in the Phase I postanesthesia care unit (PACU) are influenced by the sequencing of each surgeons list of cases in the same OR on the same day. METHODS: Case sequencing was studied using 201 consecutive workdays of data from a 10 OR hospital surgical suite. RESULTS: The surgeons differed significantly among themselves in their sequencing of cases and were also internally nonsystematic, based on case durations. The functional effect of this uncoordinated sequencing was for the surgical suite to behave overall as if there was random sequencing. The resulting PACU staffing requirements were the same as those of the best sequencing method identified in prior simulation studies. Although sequencing “Longest Cases First” performs poorly when all ORs have close to 8 h of cases, at the studied hospital it performed no worse than the other methods. The reason was that some ORs were much busier than others on the same day. The standard deviation among ORs in the hours of cases, including turnovers, was 3.2 h; large relative to the mean workload. Data from 33 other hospitals confirmed that this situation is commonplace. Additional studies showed that case sequencing also had minimal effects on the peak number of patients in the holding area. CONCLUSIONS: The uncoordinated decision-making of multiple surgeons working in different ORs can result in a sufficiently uniform rate of admission of patients into the PACU and holding that the independent sequencing of each surgeons list of cases would not reduce the incidence of delays in admission or staffing requirements.

Determining the number of beds in the postanesthesia care unit: a computer simulation flow approach.

Designing a new operating room (OR) suite is a difficult process owing to the number of caregivers involved and because decision-making managers try to minimize the direct and indirect costs of operating the OR suite. In this study, we devised a computer simulation flow model to calculate, first, the minimum number of beds required in the postanesthesia care unit (PACU). In a second step, we evaluated the relationship between the global performance of the OR suite in terms of OR scheduling and number of staffed PACU beds and porters. We designed a mathematical model of OR scheduling. We then developed a computer simulation flow model of the OR suite. Both models were connected; the first one performed the input flows, and the second simulated the OR suite running. The simulations performed examined the number of beds in the PACU in an ideal situation or in the case of reduction in the number of porters. We then analyzed the variation of number of beds occupied per hour in the PACU when the time spent by patients in the PACU or the number of porters varied. The results highlighted the strong impact of the number of porters on the OR suite performance and particularly on PACU performances.

New Multi-Objective Approach for the Home Care Service Problem Based on Scheduling Algorithms and Variable Neighborhood Descent

Abstract We address a home care service problem, and propose a three-phase metaheuristic based on Variable Neighborhood Decent algorithm and Longest Processing Time algorithm. In the first phase, we resolve the assignment problem using a scheduling algorithm which is the Longest Processing Time algorithm. In the second one, for each nurse, we resolve the routing problem in order to improve the travelled distances using the Variable Neighborhood Decent algorithm. The third phase, is devoted to refine the second phase in terms of maximizing patients satisfaction regarding services rendered using an efficient heuristic that performs replacements of patients not satisfied between nurses if possible while taking into consideration the distances found in the second phase. The numerical results show the efficiency of the proposed three-phase approach.

Improving care efficiency in a radiotherapy center using Lean philosophy: A case study of the proton therapy center of Institut Curie — Orsay

In the field of health care, as in production or services, there is a need for tailor made methodology to help managers improving quality of care as well as efficiency of the organization. Quality Improvement (QI) has become a major preoccupation in the current context where hospitals and health care services need to provide a high level of care and a welcoming environment for patients while reducing costs and maintaining a pleasant work atmosphere for staff. In this paper we present how, with very few adaptation to the local culture, the principles of Lean Thinking combined to the well known DMAIC from Six-Sigma can be applied to improve the efficiency of a French therapy center for cancer treatment. We then discuss how this methodology could be generalized to a larger structure such as a teaching hospital.

Monitoring waiting times (mean tardiness) on the day of elective surgery

Abstract Operating room management decisions on the day before and on the day of surgery are well understood and effective at reducing patient waiting from scheduled start times. We investigated monitoring each surgeons patients’ mean tardiness. Discrete-event simulation shows that mean tardiness can be monitored and accurate confidence intervals obtained using 6 four-week periods of data. As mean tardiness was primarily determined by the scheduled workdays duration, the duration needs to be controlled for in benchmarking. There was no need to control for: 1) average OR time; 2) similarity of OR times among cases; or 3) whether cases can start early.

Management of the care activities in Home Health Care Services: The routing and scheduling of caregivers level

The Home Care Services (HCS) provide continuous and coordinated health cares at the patients home. This paper addresses the problem of routing and scheduling of caregivers of a HCS under precedence and coordination constraints. Indeed, each patient may be visited many caregivers per day. Each visit is provided by a different caregiver. Moreover, visits should not be performed simultaneously and sometimes in a pre-defined order. Two mixed integer programming (MILP) models are proposed, based respectively on TSP (Traveling Salesman Problem) and RCPSP (Resources Constrained Project Scheduling Problem). Numerical results allow, in one side to define the axes of complexity for this problem. In another side, the results allow us to define the context of efficiency of each model.

SIMULATION AND INTEGER PROGRAMMING APPROACH FOR EFFICIENT SHIFT DESIGN

Abstract Operation research approaches and heuristics are often used in the staff organization literature. The main hypothesis considered by shift scheduling approaches is that the workload variability is negligible. Faced to a real organization problem of cleaning staff in a multidisciplinary surgical suite, the lack of exploratory approaches adapted to a context of variable activity has been observed. The purpose of this paper is to implement a hybrid approach combining integer linear programming and a simulation model for assessing performance. Finally, the hybrid approach can save 30% of the cost compared to the solution given by operation research approach alone.