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      Managing admission and discharge processes in intensive care units

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          Abstract

          The intensive care unit (ICU) is one of the most crucial and expensive resources in a health care system. While high fixed costs usually lead to tight capacities, shortages have severe consequences. Thus, various challenging issues exist: When should an ICU admit or reject arriving patients in general? Should ICUs always be able to admit critical patients or rather focus on high utilization? On an operational level, both admission control of arriving patients and demand-driven early discharge of currently residing patients are decision variables and should be considered simultaneously. This paper discusses the trade-off between medical and monetary goals when managing intensive care units by modeling the problem as a Markov decision process. Intuitive, myopic rule mimicking decision-making in practice is applied as a benchmark. In a numerical study based on real-world data, we demonstrate that the medical results deteriorate dramatically when focusing on monetary goals only, and vice versa. Using our model, we illustrate the trade-off along an efficiency frontier that accounts for all combinations of medical and monetary goals. Coming from a solution that optimizes monetary costs, a significant reduction of expected mortality can be achieved at little additional monetary cost.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s10729-021-09560-6.

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          Most cited references43

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          Mortality after surgery in Europe: a 7 day cohort study

          Summary Background Clinical outcomes after major surgery are poorly described at the national level. Evidence of heterogeneity between hospitals and health-care systems suggests potential to improve care for patients but this potential remains unconfirmed. The European Surgical Outcomes Study was an international study designed to assess outcomes after non-cardiac surgery in Europe. Methods We did this 7 day cohort study between April 4 and April 11, 2011. We collected data describing consecutive patients aged 16 years and older undergoing inpatient non-cardiac surgery in 498 hospitals across 28 European nations. Patients were followed up for a maximum of 60 days. The primary endpoint was in-hospital mortality. Secondary outcome measures were duration of hospital stay and admission to critical care. We used χ2 and Fisher's exact tests to compare categorical variables and the t test or the Mann-Whitney U test to compare continuous variables. Significance was set at p<0·05. We constructed multilevel logistic regression models to adjust for the differences in mortality rates between countries. Findings We included 46 539 patients, of whom 1855 (4%) died before hospital discharge. 3599 (8%) patients were admitted to critical care after surgery with a median length of stay of 1·2 days (IQR 0·9–3·6). 1358 (73%) patients who died were not admitted to critical care at any stage after surgery. Crude mortality rates varied widely between countries (from 1·2% [95% CI 0·0–3·0] for Iceland to 21·5% [16·9–26·2] for Latvia). After adjustment for confounding variables, important differences remained between countries when compared with the UK, the country with the largest dataset (OR range from 0·44 [95% CI 0·19–1·05; p=0·06] for Finland to 6·92 [2·37–20·27; p=0·0004] for Poland). Interpretation The mortality rate for patients undergoing inpatient non-cardiac surgery was higher than anticipated. Variations in mortality between countries suggest the need for national and international strategies to improve care for this group of patients. Funding European Society of Intensive Care Medicine, European Society of Anaesthesiology.
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            Impact of delayed transfer of critically ill patients from the emergency department to the intensive care unit.

            Numerous factors can cause delays in transfer to an intensive care unit for critically ill emergency department patients. The impact of delays is unknown. We aimed to determine the association between emergency department "boarding" (holding admitted patients in the emergency department pending intensive care unit transfer) and outcomes for critically ill patients. This was a cross-sectional analytical study using the Project IMPACT database (a multicenter U.S. database of intensive care unit patients). Patients admitted from the emergency department to the intensive care unit (2000-2003) were included and divided into two groups: emergency department boarding >or=6 hrs (delayed) vs. emergency department boarding or=6-hr delay in intensive care unit transfer had increased hospital length of stay and higher intensive care unit and hospital mortality. This suggests the need to identify factors associated with delayed transfer as well as specific determinants of adverse outcomes.
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              Evaluation of triage decisions for intensive care admission.

              To assess physician decision-making in triage for intensive care and how judgments impact on patient survival. Prospective, descriptive study. General intensive care unit, university medical center. All patients triaged for admission to a general intensive care unit were studied. Information was collected for the patient's age, diagnoses, surgical status, admission purpose, Acute Physiology and Chronic Health Evaluation (APACHE) II score, and mortality. The number of available beds at the time of triage and reasons for refused admission were obtained. Of 382 patients, 290 were admitted, 92 (24%) were refused admission, and 31 were admitted at a later time. Differences between admission diagnoses were found between patients admitted or not admitted (p < .001). Patients refused admission had higher APACHE II scores (15.6+/-1.5 admitted later and 15.8+/-1.4 never admitted) than did admitted patients (12.1+/-.4; p < .001). The frequency of admitting patients decreased when the intensive care unit was full (p < .001). Multivariate analysis revealed that triage to intensive care correlated with age, a full unit, surgical status, and diagnoses. Hospital mortality was lower in admitted (14%) than in refused patients (36% admitted later and 46% never admitted; p < .01) and in admitted patients with APACHE II scores of 11 to 20 (p = .02). The 28-day survival of patients was greater for admitted patients compared with patients never admitted (p = .01). Physicians triage patients to intensive care based on the number of beds available, the admission diagnosis, severity of disease, age, and operative status. Admitting patients to intensive care is associated with a lower mortality rate, especially in patients with APACHE scores of 11 to 20.
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                Author and article information

                Contributors
                jens.brunner@uni-a.de
                Journal
                Health Care Manag Sci
                Health Care Manag Sci
                Health Care Management Science
                Springer US (New York )
                1386-9620
                1572-9389
                10 June 2021
                10 June 2021
                : 1-20
                Affiliations
                [1 ]GRID grid.6582.9, ISNI 0000 0004 1936 9748, Department of Anesthesiology and Intensive Care Medicine, , School of Medicine, University of Ulm, ; Albert-Einstein-Allee 29, 89081 Ulm, Germany
                [2 ]GRID grid.6190.e, ISNI 0000 0000 8580 3777, Faculty of Management, Economics and Social Sciences, , University of Cologne, ; Albertus-Magnus-Platz, 50923 Cologne, Germany
                [3 ]GRID grid.5718.b, ISNI 0000 0001 2187 5445, Mercator School of Management, , University of Duisburg-Essen, ; Lotharstraße 65, 47057 Duisburg, Germany
                [4 ]GRID grid.7307.3, ISNI 0000 0001 2108 9006, Faculty of Business and Economics, , University of Augsburg, ; Universitätsstraße 16, 86159 Augsburg, Germany
                [5 ]GRID grid.6936.a, ISNI 0000000123222966, Clinics for Anaesthesiology, , Technical University of Munich, Klinikum Rechts der Isar, ; Ismaningerstraße 22, 81675 Munich, Germany
                Author information
                http://orcid.org/0000-0002-2700-4795
                Article
                9560
                10.1007/s10729-021-09560-6
                8189840
                34110549
                1fcd16d9-80de-490e-810a-01d4a6d1df72
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 22 June 2020
                : 3 March 2021
                Funding
                Funded by: Universität Augsburg (3144)
                Categories
                Article

                Medicine
                intensive care unit,admission and discharge decisions,markov decision process,dynamic programming,operations research

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