Stochastic master surgery scheduling

Bovim, Thomas Reiten; Christiansen, Marielle; Gullhav, Anders N.; Range, Troels Martin; Hellemo, Lars

doi:10.1016/j.ejor.2020.02.001

Cited by 49 publications

(42 citation statements)

References 24 publications

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“…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

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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.

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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

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“…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%

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

et al. 2021

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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.

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“…Kvantitative modeller vil vaere nyttige verktøy for å finne en balanse mellom fast og fleksibel kapasitet Vi har brukt en optimerings-og simuleringsmodell som vi har utviklet i felleskap mellom NTNU, SINTEF og Avdeling for ortopedi ved St. Olavs hospital (6). Målet har vaert å finne en god avveining mellom fleksibel og fast kapasitet og deretter teste betydningen av fleksibilitet for planlegging av operasjoner.…”

Section: Simulering Dokumenterer Potensialunclassified

“…Men helsevesenets verden er uforutsigbar, noe som stiller krav til rask omstilling og replanlegging av ressursbruken. Datasimuleringer indikerer imidlertid at fleksibel planlegging -en prosess som legger til rette for at endringer kan skje på kort varsel -kan hjelpe norske sykehus med å håndtere en uforutsigbar hverdag og bli mer effektive (1) .…”

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Fleksibel planlegging i sykehus er effektivt

Bovim¹,

Hellemo²,

Gullhav³

et al. 2020

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Thomas Reiten Bovim er fysioterapeut og Master of Science ved SINTEF Industri og ph.d.-kandidat ved Institutt for industriell økonomi og teknologiledelse, NTNU. Kronikken bygger på hans mastergrad fra Institutt for industriell økonomi og teknologiledelse, NTNU. Forfatteren har fylt ut ICMJE-skjemaet og oppgir ingen interessekonflikter. LARS HELLEMO Lars Hellemo er ph.d. og forsker ved SINTEF Industri. Forfatteren har fylt ut ICMJE-skjemaet og oppgir ingen interessekonflikter. ANDERS NORDBY GULLHAV Anders Nordby Gullhav er ph.d. og førsteamanuensis ved Institutt for industriell økonomi og teknologiledelse, NTNU, og forsker ved Regionalt senter for helsetjenesteuvikling, St. Olavs hospital. Forfatteren har fylt ut ICMJE-skjemaet og oppgir ingen interessekonflikter. VIGLEIK JESSEN Vigleik Jessen er spesialist i generell kirurgi og ortopedisk kirurgi og klinikksjef ved Klinikk for ortopedi, revmatologi og hudsykdommer, St. Olavs hospital. Forfatteren har fylt ut ICMJE-skjemaet og oppgir ingen interessekonflikter. TRUDE MITTET Trude Mittet er sykepleier, MBA og avdelingssjef ved Ortopedisk operasjonsavdeling, Klinikk for ortopedi, revmatologi og hudsykdommer, St. Olavs hospital. Hun har også videreutdanning i operasjonssykepleie ved Høgskolen i Sør-Trøndelag. Forfatteren har fylt ut ICMJE-skjemaet og oppgir ingen interessekonflikter.

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Stochastic master surgery scheduling

Cited by 49 publications

References 24 publications

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

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

Fleksibel planlegging i sykehus er effektivt

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