A pull-strategy for the appointment scheduling of surgical patients in a hospital-integrated facility.

This paper addresses the daily appointment scheduling (AS) of patients in a hospital-integrated facility where outpatients and inpatients are treated simultaneously and share critical resources. We propose a lean approach based on the pull-strategy "Constant Work in Process" (ConWIP) to develop robust and easy-to-implement AS rules. Our objective is to reduce patients' waiting time and maximise the use rate of resources while considering the global surgical process and stochastic service times. The AS rules based on ConWIP are evaluated using a Discrete-Event-Simulation model. Numerical experiments based on a real-life case study are carried out to assess the proposed appointment rules' performance and compare them to AS rules developed in the literature. The results highlight the robustness of our approach and demonstrate its usefulness in practice.

30 Years of postdisturbance recruitment in a Neotropical forest.

QUESTIONS: Long-term community response to disturbance can follow manifold successional pathways depending on the interplay between various recruitment processes. Analyzing the succession of recruited communities provides a long-term perspective on forest response to disturbance. Specifically, postdisturbance recruitment trajectories assess (a) the successive phases of postdisturbance response and the role of deterministic recruitment processes, and (b) the return to predisturbance state of recruits taxonomic/functional diversity/composition. LOCATION: Amazonian rainforest, Paracou station, French Guiana. METHODS: We analyzed trajectories of recruited tree communities, from twelve forest plots of 6.25 ha each, during 30 years following a disturbance gradient that ranged from 10% to 60% of aboveground biomass removed. We measured recruited community taxonomic composition turnover, compared to whole predisturbance community, and assessed their functional composition by measuring the community weighted means for seven leaf, stem, and life-history functional traits. We also measured recruited community taxonomic richness, taxonomic evenness, and functional diversity and compared them to the diversity values from a random recruitment process. RESULTS: While control plots trajectories resembled random recruitment trajectories, postdisturbance trajectories diverged significantly. This divergence corresponded to an enhanced recruitment of light-demanding species that became dominant above a disturbance intensity threshold. After breakpoints in time, though, recruitment trajectories returned to diversity values and composition similar to those of predisturbance and control plots community. CONCLUSIONS: Following disturbance, recruitment processes specific to undisturbed community were first replaced by the emergence of more restricted, deterministic recruitment processes favoring species with efficient light use and acquisition. Then, a second phase corresponded to a decades-long recovery of recruits predisturbance taxonomic and functional diversity and composition that remained unachieved after 30 years.

Improving Health Care Management Through Persistent Homology of Time-Varying Variability of Emergency Department Patient Flow.

Excessive admissions at the emergency department (ED) is a phenomenon very closely linked to the propagation of viruses. It is a cause of overcrowding for EDs and a public health problem. The aim of this work is to give EDs' leaders more time for decision making during this period. Based on the admissions time series associated with specific clinical diagnoses, we will first perform a detrended fluctuation analysis to obtain the corresponding variability time series. Next, we will embed this time series on a manifold to obtain a point cloud representation and use topological data analysis through persistent homology technic to propose two early real-time indicators. One is the early indicator of abnormal arrivals at the ED whereas the second gives the information on the time index of the maximum number of arrivals. The performance of the detectors is parameter dependent and it can evolve each year. That is why we also propose to solve a biobjective optimization problem to track the variations of this parameter.

Design of shared unit-dose drug distribution network using multi-level particle swarm optimization.

Unit-dose drug distribution systems provide optimal choices in terms of medication security and efficiency for organizing the drug-use process in large hospitals. As small hospitals have to share such automatic systems for economic reasons, the structure of their logistic organization becomes a very sensitive issue. In the research reported here, we develop a generalized multi-level optimization method - multi-level particle swarm optimization (MLPSO) - to design a shared unit-dose drug distribution network. Structurally, the problem studied can be considered as a type of capacitated location-routing problem (CLRP) with new constraints related to specific production planning. This kind of problem implies that a multi-level optimization should be performed in order to minimize logistic operating costs. Our results show that with the proposed algorithm, a more suitable modeling framework, as well as computational time savings and better optimization performance are obtained than that reported in the literature on this subject.

Representation and Characterization of Nonstationary Processes by Dilation Operators and Induced Shape Space Manifolds.

We proposed in this work the introduction of a new vision of stochastic processes through geometry induced by dilation. The dilation matrices of a given process are obtained by a composition of rotation matrices built in with respect to partial correlation coefficients. Particularly interesting is the fact that the obtention of dilation matrices is regardless of the stationarity of the underlying process. When the process is stationary, only one dilation matrix is obtained and it corresponds therefore to Naimark dilation. When the process is nonstationary, a set of dilation matrices is obtained. They correspond to Kolmogorov decomposition. In this work, the nonstationary class of periodically correlated processes was of interest. The underlying periodicity of correlation coefficients is then transmitted to the set of dilation matrices. Because this set lives on the Lie group of rotation matrices, we can see them as points of a closed curve on the Lie group. Geometrical aspects can then be investigated through the shape of the obtained curves, and to give a complete insight into the space of curves, a metric and the derived geodesic equations are provided. The general results are adapted to the more specific case where the base manifold is the Lie group of rotation matrices, and because the metric in the space of curve naturally extends to the space of shapes; this enables a comparison between curves' shapes and allows then the classification of random processes' measures.

The generalized Simpson's entropy is a measure of biodiversity.

Modern measures of diversity satisfy reasonable axioms, are parameterized to produce diversity profiles, can be expressed as an effective number of species to simplify their interpretation, and come with estimators that allow one to apply them to real-world data. We introduce the generalized Simpson's entropy as a measure of diversity and investigate its properties. We show that it has many useful features and can be used as a measure of biodiversity. Moreover, unlike most commonly used diversity indices, it has unbiased estimators, which allow for sound estimation of the diversity of poorly sampled, rich communities.

Early Index for Detection of Pediatric Emergency Department Crowding.

When epidemics occur, such as is the case for bronchiolitis in the Pediatric Emergency Department (ED), the patient flow in the ED incontestably increases and can lead to crowding. We bypassed this difficulty of forecasting patient flow with aggregated weekly or monthly data by tackling the problem from a different point of view. We used daily data to build a multiperiod Serfling-based model. This model is hereinafter assimilated to normal ED flow. We then used the fourth-order moment of distribution of the time series, obtained from the difference between the estimated model and the real data, to provide an early index announcing abnormal ED patient flow. This index is parameter-dependent and we provide criterion to assist in selecting the optimal parameters. A simple program based on this methodology has been developed and has been given to the pediatric physicians for testing. Thanks to this index, the Pediatric ED was able to anticipate crowding almost three weeks before the height of the bronchiolitis epidemic.

Generalization of the partitioning of shannon diversity.

Traditional measures of diversity, namely the number of species as well as Simpson's and Shannon's indices, are particular cases of Tsallis entropy. Entropy decomposition, i.e. decomposing gamma entropy into alpha and beta components, has been previously derived in the literature. We propose a generalization of the additive decomposition of Shannon entropy applied to Tsallis entropy. We obtain a self-contained definition of beta entropy as the information gain brought by the knowledge of each community composition. We propose a correction of the estimation bias allowing to estimate alpha, beta and gamma entropy from the data and eventually convert them into true diversity. We advocate additive decomposition in complement of multiplicative partitioning to allow robust estimation of biodiversity.

Dynamics of aboveground carbon stocks in a selectively logged tropical forest.

The expansion of selective logging in tropical forests may be an important source of global carbon emissions. However, the effects of logging practices on the carbon cycle have never been quantified over long periods of time. We followed the fate of more than 60 000 tropical trees over 23 years to assess changes in aboveground carbon stocks in 48 1.56-ha plots in French Guiana that represent a gradient of timber harvest intensities, with and without intensive timber stand improvement (TSI) treatments to stimulate timber tree growth. Conventional selective logging led to emissions equivalent to more than a third of aboveground carbon stocks in plots without TSI (85 Mg C/ha), while plots with TSI lost more than one-half of aboveground carbon stocks (142 Mg C/ha). Within 20 years of logging, plots without TSI sequestered aboveground carbon equivalent to more than 80% of aboveground carbon lost to logging (-70.7 Mg C/ha), and our simulations predicted an equilibrium aboveground carbon balance within 45 years of logging. In contrast, plots with intensive TSI are predicted to require more than 100 years to sequester aboveground carbon lost to emissions. These results indicate that in some tropical forests aboveground carbon storage can be recovered within half a century after conventional logging at moderate harvest intensities.

Numbers of simultaneous turnovers calculated from anesthesia or operating room information management system data.

BACKGROUND: More personnel are needed to turn over operating rooms (ORs) promptly when there are more simultaneous turnovers. Anesthesia and/or OR information management system data can be analyzed statistically to quantify simultaneous turnovers to evaluate whether to add an additional turnover team. METHODS: Data collected for each case at a six OR facility were room, date of surgery, time of patient entry into the OR, and time of patient exit from the OR. The number of simultaneous turnovers was calculated for each 1 min of 122 4-wk periods. Our end point was the reduction in the daily minutes of simultaneous turnovers exceeding the number of teams caused by the addition of a team. RESULTS: Increasing from two turnover teams to three teams reduced the mean daily minutes of simultaneous turnovers exceeding the numbers of teams by 19 min. The ratio of 19 min to 8 h valued the time of extra personnel as 4.0% of the time of OR staff, surgeons, and anesthesia providers. Validity was suggested by other methods of analyses also suggesting staffing for three simultaneous turnovers. Discrete-event simulation showed that the reduction in daily minutes of turnover times from the addition of a team would likely match or exceed the reduction in the daily minutes of simultaneous turnovers exceeding the numbers of teams. Confidence intervals for daily minutes of turnover times achieved by increasing from two to three teams were calculated using successive 4-wk periods. The distribution was sufficiently close to normal that accurate confidence intervals could be calculated using Student's t distribution (Lilliefors' test P = 0.58). Analysis generally should use 13 4-wk periods as increasing the number of periods from 6 to 13 significantly reduced the coefficient of variation of the averages but not increasing the number of periods from 6 to 9 or from 9 to 13. CONCLUSION: The number of simultaneous turnovers can be calculated for each 1 min over 1 yr. The reduction in the daily minutes of simultaneous turnovers exceeding the number of teams achieved by the addition of a turnover team can be averaged over the year's 13 4-wk periods to provide insight as to the value (or not) of adding an additional team.

Exploring new operational research opportunities within the Home Care context: the chemotherapy at home.

Home Care (HC) services provide complex and coordinated medical and paramedical care to patients at their homes. As health care services move into the home setting, the need for developing innovative approaches that improve the efficiency of home care organizations increases. We first conduct a literature review of investigations dealing with operation planning within the area of home care management. We then address a particular issue dealing with the planning of operations related to chemotherapy at home as it is an emergent problem in the French context. Our interest is focused on issues specific to the anti-cancer drug supply chain. We identify various models that can be developed and analyze one of them.

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 surgeon's 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 non-systematic, 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 surgeon's list of cases would not reduce the incidence of delays in admission or staffing requirements.

Impact of surgical sequencing on post anesthesia care unit staffing.

This paper analyzes the impact of sequencing rules on the phase I post anesthesia care unit (PACU) staffing and over-utilized operating room (OR) time resulting from delays in PACU admission. The sequencing rules are applied to each surgeon's list of cases independently. Discrete event simulation shows the importance of having a sufficient number of PACU nurses. Sequencing rules have a large impact on the maximum number of patients receiving care in the PACU (i.e., peak of activity). Seven sequencing rules are tested, over a wide range of scenarios. The largest effect of sequencing was on the percentage of days with at least one delay in PACU admission. The best rules are those that smooth the flow of patients entering in the PACU (HIHD (Half Increase in OR time and Half Decrease in OR time) and MIX (MIX OR time)). We advise against using the LCF (Longest Cases First) and equivalent sequencing methods. They generate more over-utilized OR time, require more PACU nurses during the workday, and result in more days with at least one delay in PACU admission.

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

UNLABELLED: We investigated the validity of several statistical methods to monitor the cancellation of electively scheduled cases on the day of surgery: chi(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 chi(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. IMPLICATIONS: Operating room cancellation rates can be monitored statistically by considering the number of canceled and performed cases during each 4-week period, performing a transformation of each period's cancellation rate, and then applying Student's t-test. Methods such as the Fisher's exact test and {chi}2 test should be avoided for this application because they can give erroneous results.

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.

Strategies to reduce delays in admission into a postanesthesia care unit from operating rooms.

The authors performed a systematic review of strategies to reduce delays in admission into PACUs from ORs. The purpose of this article was to evaluate for managers how to choose interventions based on effectiveness and practicality. The authors discuss optimization methods that can be used to sequence consecutive cases in the same OR, by the same surgeon, on the same day, based on the objective of reducing delays in PACU admission due to the unavailability of unfilled PACU beds. Although effective, such methods can be impractical because of large organizational change required and limited equipment or personnel availability. When all physical beds are not full, PACU nurse staffing can be adjusted. Statistical methods can be used to ensure that nursing schedules closely match the times that minimize delays in PACU admission. These methods are effective and practical. Explicit criteria can be applied to assist in deciding when to assign other qualified nurses to the PACU, when to ask PACU nurses to work late, and/or when to make a decision on the day before surgery to add more PACU nurses for the next day (if available). The latter would be based on statistical forecasts of the timing of patients' admissions into the PACU. Whether or not all physical beds are full, the risk of delays in PACU admission is relatively insensitive to economically feasible reductions in PACU length of stay. Such interventions should be considered only if statistical analysis, performed by using computer simulation, has established that reducing PACU length of stay will reduce delays in admission at a manager's facility.

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

UNLABELLED: 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. IMPLICATIONS: Designing new operating room (OR) facilities implies many decisions on the number of ORs, postanesthesia care unit (PACU) beds, and on the staff of nurses and porters. To make these decisions, managers can use rules of thumb or recommendations. Our study highlights the interest of using flow simulation to validate these choices. In this case study we determine the number of PACU beds and porter staff and assess the impact of decreasing the number of porters on PACU bed requirements.