Hospital mortality prediction for intermediate care patients: Assessing the generalizability of the Intermediate Care Unit Severity Score (IMCUSS)

Hager, David N.; Tanykonda, Varshitha; Noorain, Zeba; Sahetya, Sarina K.; Simpson, Carol; Lucena, Juan Felipe

doi:10.1016/j.jcrc.2018.05.009

Cited by 15 publications

(11 citation statements)

References 35 publications

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“…As previously reported, between July and December 2012, there were 765 IMCU admissions representing 628 unique patients. 8 Patient characteristics are summarized in Table 1. Approximately half of all patients were admitted directly from the ED (n = 319), with the medical floor being the second most common source (n = 213).…”

Section: Resultsmentioning

confidence: 99%

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Performance of Critical Care Outcome Prediction Models in an Intermediate Care Unit

Brusca

Simpson

Sahetya

et al. 2019

J Intensive Care Med

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Background: Intermediate care units (IMCUs) are heterogeneous in design and operation, which makes comparative effectiveness studies challenging. A generalizable outcome prediction model could improve such comparisons. However, little is known about the performance of critical care outcome prediction models in the intermediate care setting. The purpose of this study is to evaluate the performance of the Acute Physiology and Chronic Health Evaluation version II (APACHE II), Simplified Acute Physiology Score version II (SAPS II) and version 3 (SAPS 3), and Mortality Probability Model version III (MPM0III) in patients admitted to a well-characterized IMCU. Materials and Methods: In the IMCU of an academic medical center (July to December 2012), the discrimination and calibration of each outcome prediction model were evaluated using the area under the receiver–operating characteristic and Hosmer-Lemeshow goodness-of-fit test, respectively. Standardized mortality ratios (SMRs) were also calculated. Results: The cohort included data from 628 unique IMCU admissions with an inpatient mortality rate of 8.3%. All models exhibited good discrimination, but only the SAPS II and MPM0III were well calibrated. While the APACHE II and SAPS 3 both markedly overestimated mortality, the SMR for the SAPS II and MPM0III were 0.91 and 0.91, respectively. Conclusions: The SAPS II and MPM0III exhibited good discrimination and calibration, with slight overestimation of mortality. Each model should be further evaluated in multicenter studies of patients in the intermediate care setting.

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Section: Resultsmentioning

confidence: 99%

“…Finally, we have previously assessed the performance of the ImCUSS, the only outcome prediction model to date developed and validated for use in the IMCU. 7,8 This model has only 9 data elements that are dichotomous and assessed at the time of IMCU admission. Like the MPM 0 III, this low burden of data collection is appealing.…”

Section: Discussionmentioning

confidence: 99%

Performance of Critical Care Outcome Prediction Models in an Intermediate Care Unit

Brusca

Simpson

Sahetya

et al. 2019

J Intensive Care Med

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“…For reference, review of our historical data show that 50% of IMCU admissions arrive via the emergency department and 30% via medical wards. 31 Of these, 65% are transferred to, or return to, the medical ward following IMCU admission with median IMCU and hospital lengths of stay of 3 and 10 days, respectively. In short, residents directing the care of patients across both settings are likely to develop a higher degree of competence in managing the dynamic disease processes commonly encountered by practicing internists.…”

Section: Discussionmentioning

confidence: 99%

Models of Intermediate Care Organization and Staffing at an Academic Medical Center: Considerations of an Inpatient Planning Committee

Hager

Dezube

Disney

et al. 2022

J Intensive Care Med

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Rationale: Geographic co-localization of patients and provider teams (geography) may improve care efficiency and quality. Patients requiring intermediate care present a unique challenge to the geographic model. Objective: Identify the best organizational and staffing model for intermediate care at our academic medical center. Methods: A modified nominal group technique was employed to assess the benefits and limitations of an existing model of intermediate care, identify and review potential alternative models, and choose a new model. Results: In addition to the institution's current model, the benefits and limitations of six alternative organizational and staffing models were characterized. The anticipated impact of each model on nurse: provider communication, maintenance of nursing competencies, nurse satisfaction, efficient utilization of technical and human resources, triage of patients to the unit, care continuity, and the impact on trainee education are described. After considering these features, stakeholders ranked a closed provider staffing model on a unit dedicated to intermediate care highest of the six alternative models. Important outcomes to monitor following transition to a closed staffing model included patient outcomes, nursing job satisfaction and retention, provider and trainee experience, unexpected patient transfers to higher or lower levels of care, and administrative costs. Conclusions: After considering six alternative staffing models for intermediate care, stakeholders ranked a closed provider staffing model highest. Further qualitative and quantitative comparisons to determine optimal models of intermediate care are needed.

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“…Our results outline the daily hospital cycle of LSC limited patients’ admission to the IMCU. Few data are available to date on this topic [5–7], although, IMCU currently represents a significant part of acute care resources in Europe and Northern America [2, 15, 16–19].…”

Section: Discussionmentioning

confidence: 99%

“…In our hospital, we believe that IMCUs have an important role in the management of patients who have been placed on limitations of care and withholding or withdrawal of life-supporting care (LSC). However, little is known about the prevalence of such patients in the IMCU settings [5–7]. We, therefore, sought to characterize the prevalence of patients with LSC in our IMCU population, as well as the severity of illness, comorbidities, transitions to the withdrawal of support, and in-hospital mortality.…”

Section: Introductionmentioning

confidence: 99%

Patients with limitation or withdrawal of life supporting care admitted in a medico-surgical intermediate care unit: Prevalence, description and outcome over a six-month period

et al. 2019

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PurposeThere have been few studies on the limitation of Life Supporting Care (LSC) and Withdrawal of LSC in Intermediate Care Units (IMCUs). We report the prevalence of LSC limited patients in a medico-surgical IMCU over a six-month period, examining the description, outcomes, and patterns of LSC Limitations and Withdrawal of LSC.MethodsSingle center, retrospective observational study in an IMCU of a 500-bed general hospital.ResultsOur study of 404 patients, reported 79 (19.5%, 95%CI: [16.0–23.7]%) being admitted with LSC limitations in the IMCU. This group of LSC limited patients presented with higher chronic and acute severity scores. The most common admission diagnosis of LSC limited patients was acute respiratory failure (51%). Non-invasive ventilation (NIV) was frequently used within this population (39%). Hospital mortality for LSC limited patients was high (53%) and associated with age (OR = 1.07, 95%CI: [1.01–1.13)]), SOFA score (OR 1.29, 95%CI: [1.01–1.64]), and hypoxemic respiratory failure (OR 7.2, 95%CI: [1.27–40.9]). Withdrawal of LSC occurred in 19.5% of cases, often accompanied with terminal sedation with or without NIV removal (43.8%).ConclusionsPatients with limitation of LSC are frequently admitted into IMCU. Hospital mortality rate was high and associated with age, acute organ failures, and hypoxemic respiratory failure. Life support withdrawal includes palliative sedation with or without NIV discontinuation.

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Hospital mortality prediction for intermediate care patients: Assessing the generalizability of the Intermediate Care Unit Severity Score (IMCUSS)

Abstract: The IMCUSS exhibited acceptable discrimination, poor calibration, and underestimated mortality. Other centers should assess the performance of the IMCUSS before adopting its use.

Cited by 15 publications

References 35 publications

Performance of Critical Care Outcome Prediction Models in an Intermediate Care Unit

Performance of Critical Care Outcome Prediction Models in an Intermediate Care Unit

Models of Intermediate Care Organization and Staffing at an Academic Medical Center: Considerations of an Inpatient Planning Committee

Patients with limitation or withdrawal of life supporting care admitted in a medico-surgical intermediate care unit: Prevalence, description and outcome over a six-month period

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