An exact approach for tactical planning and patient selection for elective surgeries

Anjomshoa, Hamideh; Dumitrescu, Irina; Lustig, Irvin J.; Smith, Olivia J.

doi:10.1016/j.ejor.2018.01.048

Cited by 16 publications

(5 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is subject to a set of mathematical constraints that portray the conditions under which the decisions have to be made. These models can then be solved by using standard software (e.g., CPLEX solver [12,87]) or by developing exact solution methods (e.g., branch-and-price [121,138]).…”

Section: Research Methodology Classificationmentioning

confidence: 99%

“…Big data analytics are normally used for analysis on large-scale datasets called 'big data' and for functions of classification, association, clustering, as well as optimization [140]. Papers of OR planning and scheduling use BDA for different purposes, including grouping similar surgeries [12,160], predicting the duration of key activities (e.g., surgery durations [79,141], PACU LOSs [69]), and predicting the PMs of interest (e.g., the probability of surgical cancellations [119] and the bed occupancy in the ICU [158]).…”

Section: Research Methodology Classificationmentioning

confidence: 99%

See 1 more Smart Citation

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

Wang

Demeulemeester

Vansteenkiste

et al. 2021

Operations Research for Health Care

View full text Add to dashboard Cite

Section: Research Methodology Classificationmentioning

confidence: 99%

Section: Research Methodology Classificationmentioning

confidence: 99%

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

Wang

Demeulemeester

Vansteenkiste

et al. 2021

Operations Research for Health Care

View full text Add to dashboard Cite

“…Fügener et al published a tutorial with an example from a surgical suite [20]. Some contemporary studies treat each patient as having a length of stay equal to the mean for their procedure category (i.e., assuming perfect predictive ability) [21][22][23][24][25]. Others use discrete empirical probability distributions, statistically analogous to the Wilcoxon-Mann-Whitney approach [20,[26][27][28][29].…”

Section: Discussionmentioning

confidence: 99%

Proportions of Surgical Patients Discharged Home the Same or the Next Day Are Sufficient Data to Assess Cases’ Contributions to Hospital Occupancy

Dexter¹,

Epstein²,

Shi³

2021

Cureus

View full text Add to dashboard Cite

Introduction When the hospital census is high, perioperative medical directors or operating room (OR) managers may need to consider postponing some surgical cases scheduled to be performed within the next three workdays. This scenario has arisen at hospitals in regions with large increases in admissions due to coronavirus disease 2019 (COVID-19). We compare summary measures for hospital length of stay (LOS) to guide the OR manager having to decide which cases may need to be postponed to ensure a sufficient reserve of available inpatient beds. Methods We studied the 1,201,815 ambulatory and 649,962 inpatient elective cases with a major therapeutic procedure performed during 2018 at all 412 non-federal hospitals in Florida. The data were sorted by the hospital, and then by procedure category. Statistical comparisons of LOS were made pairwise among all procedure categories with at least 100 cases at (the) each hospital, using the chi-square test (LOS ≤ 1 day versus LOS > 1 day), Student's t-test with unequal variances, and the Wilcoxon-Mann-Whitney test. The comparisons among the three tests then were repeated having sorted the data by procedure category and making statistical comparisons among all hospitals with at least 100 cases for the procedure category. Results Whether using a criterion for statistical significance of P < 0.05 or P < 0.01, and whether compared with Student's t-test with unequal variances or Wilcoxon-Mann-Whitney test, the chi-square test had greater odds (i.e., greater statistical power) to detect differences in LOS (all four with P < 0.0001 and all 95% lower confidence limits for odds ratios ≥ 3.00). The findings were consistent when the data, first sorted by procedure category and then by probability distributions of LOS, were compared between hospitals (all P < 0.0001 and the 95% lower confidence limits for odds ratio ≥ 3.72). Conclusions For purposes of comparing procedure categories pairwise at the same hospital, there was no loss of information by summarizing the probability distributions using single numbers, the percentages of cases among patients staying longer than overnight. This finding substantially simplifies the mathematics for constructing dashboards or summaries of OR information system data to help the perioperative OR manager or medical director decide which cases may need to be postponed, when the hospital census is high, to provide a sufficient reserve of inpatient hospital beds.

show abstract

“…Surgery types are often sets of surgeries that are similar in economic and resource usage perspective. This is the case in, e.g., Bovim et al (2020); Anjomshoa et al (2018); Kumar et al (2018); Dellaert and Jeunet (2017); Visintin et al (2016); Cappanera et al (2014); Banditori et al (2013);van Oostrum et al (2008). Once again, decisions on how much operating room time to assign to each specialty are not usually considered or do not take into account issues such as equity or waiting list length.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Although building a four-week cycle MSS which repeats along the year, Anjomshoa et al (2018) starts from a base MSS and only allows a maximum number of differences between this base MSS and the proposed plan. Moreover, every six months slightly changes to the base plan are allowed.…”

Section: Literature Reviewmentioning

confidence: 99%

Flexible master surgery scheduling: combining optimization and simulation in a rolling horizon approach

et al. 2021

View full text Add to dashboard Cite

Operating room managers are facing increasingly complex challenges, namely in complying with waiting time targets before surgery. This paper proposes a framework that combines optimization and simulation to generate dynamic master surgery schedules for a long planning horizon, in which the schedules are optimized by an integer programming model and the demand levels are modelled using the simulation model. The developed approach allows the resulting operating room plan to balance waiting lists as it assigns more time to the specialties with higher demand in terms of time needed to perform all the surgeries in the corresponding waiting lists. The analysis of the results obtained for the proposed flexible rolling horizon approach were proven robust, and were compared to static and flexible long-term approaches, the former not allowing flexibility and the latter using a deterministic update of the demand. Considering throughput, tardiness and waiting time, the flexible rolling horizon approach showed the best results, while the static one had the worst results.

show abstract

An exact approach for tactical planning and patient selection for elective surgeries

Cited by 16 publications

References 23 publications

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

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

Proportions of Surgical Patients Discharged Home the Same or the Next Day Are Sufficient Data to Assess Cases’ Contributions to Hospital Occupancy

Flexible master surgery scheduling: combining optimization and simulation in a rolling horizon approach

Contact Info

Product

Resources

About