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Takala J, Moser A, Raj R, et al. Variation in severity-adjusted resource use and outcome in intensive care units. Intensive Care Med. 2021;48(1):67-77doi: 10.1007/s00134-021-06546-4.
Takala, J., Moser, A., Raj, R., Pettilä, V., Irincheeva, I., Selander, T., Kiiski, O., Varpula, T., Reinikainen, M., & Jakob, S. M. (2022). Variation in severity-adjusted resource use and outcome in intensive care units. Intensive care medicine, 48(1), 67-77. https://doi.org/10.1007/s00134-021-06546-4
Takala, Jukka, et al. "Variation in severity-adjusted resource use and outcome in intensive care units." Intensive care medicine vol. 48,1 (2022): 67-77. doi: https://doi.org/10.1007/s00134-021-06546-4
Takala J, Moser A, Raj R, Pettilä V, Irincheeva I, Selander T, Kiiski O, Varpula T, Reinikainen M, Jakob SM. Variation in severity-adjusted resource use and outcome in intensive care units. Intensive Care Med. 2022 Jan;48(1):67-77. doi: 10.1007/s00134-021-06546-4. Epub 2021 Oct 18. PMID: 34661693; PMCID: PMC8724095.
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Intensive Care Med. 2022 Jan;48(1):67-77. doi: 10.1007/s00134-021-06546-4. Epub 2021 Oct 18.

Variation in severity-adjusted resource use and outcome in intensive care units.

Intensive care medicine

Jukka Takala, André Moser, Rahul Raj, Ville Pettilä, Irina Irincheeva, Tuomas Selander, Olli Kiiski, Tero Varpula, Matti Reinikainen, Stephan M Jakob

Affiliations

  1. Department of Intensive Care Medicine, Bern University Hospital, University of Bern, Bern, Switzerland. [email protected].
  2. Clinical Trials Unit, University of Bern, Bern, Switzerland.
  3. Department of Neurosurgery, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
  4. Division of Intensive Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
  5. Biostatistics, CSL Behring, Bern, Switzerland.
  6. Science Service Center, Kuopio University Hospital, Kuopio, Finland.
  7. HWE Benchmarking Services, TietoEvry, Helsinki, Finland.
  8. Department of Anesthesiology and Intensive Care, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland.
  9. Department of Intensive Care Medicine, Bern University Hospital, University of Bern, Bern, Switzerland.

PMID: 34661693 PMCID: PMC8724095 DOI: 10.1007/s00134-021-06546-4

Abstract

PURPOSE: Intensive care patients have increased risk of death and their care is expensive. We investigated whether risk-adjusted mortality and resources used to achieve survivors change over time and if their variation is associated with variables related to intensive care unit (ICU) organization and structure.

METHODS: Data of 207,131 patients treated in 2008-2017 in 21 ICUs in Finland, Estonia and Switzerland were extracted from a benchmarking database. Resource use was measured using ICU length of stay, daily Therapeutic Intervention Scoring System Scores (TISS) and purchasing power parity-adjusted direct costs (2015-2017; 17 ICUs). The ratio of observed to severity-adjusted expected resource use (standardized resource use ratio; SRUR) was calculated. The number of expected survivors and the ratio of observed to expected mortality (standardized mortality ratio; SMR) was based on a mortality prediction model covering 2015-2017. Fourteen a priori variables reflecting structure and organization were used as explanatory variables for SRURs in multivariable models.

RESULTS: SMR decreased over time, whereas SRUR remained unchanged, except for decreased TISS-based SRUR. Direct costs of one ICU day, TISS score and ICU admission varied between ICUs 2.5-5-fold. Differences between individual ICUs in both SRUR and SMR were up to > 3-fold, and their evolution was highly variable, without clear association between SRUR and SMR. High patient turnover was consistently associated with low SRUR but not with SMR.

CONCLUSION: The wide and independent variation in both SMR and SRUR suggests that they should be used together to compare the performance of different ICUs or an individual ICU over time.

© 2021. The Author(s).

Keywords: Cost control; Health care benchmarking; Health resources; Hospital mortality; Intensive care unit; Resource allocation

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