Postoperative Overtriage to an Intensive Care Unit Is Associated With Low Value of Care

Loftus, Tyler J.; Ruppert, Matthew M.; Ozrazgat‐Baslanti, Tezcan; Balch, Jeremy A.; Shickel, Benjamin; Hu, Die; Efron, Philip A.; Tighe, Patrick J.; Hogan, William R.; Rashidi, Parisa; Upchurch, Gilbert R.

doi:10.1097/sla.0000000000005460

Cited by 11 publications

(12 citation statements)

References 40 publications

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“…In the postoperative period, low-acuity patients who were over triaged to ICUs had similar outcomes compared with risk-matched ward patients showed higher costs and lower value of care [21].…”

Section: Low-value Care In the Perioperative Periodmentioning

confidence: 94%

Can we nudge to reduce the perioperative low value care? Decision making factors influencing safe practice implementation

Paz-Martin,

Arnal-Velasco

2023

Current Opinion in Anaesthesiology

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Purpose of the review Highlight sources of low-value care (LVC) during the perioperative period help understanding the decision making behind its persistence, the barriers for change, and the potential implementation strategies to reduce it. Recent findings The behavioural economics science spread of use through aligned strategies or nudge units offer an opportunity to improve success in the LVC reduction. Summary LVC, such as unneeded surgeries, or preanaesthesia tests for low-risk surgeries in low-risk patients, is a relevant source of waste and preventable harm, most especially in the perioperative period. Despite the international focus on it, initial efforts to reduce it in the last decade have not clearly shown a sustainable improvement. Understanding the shared decision-making process and the barriers to be expected when tackling LVC is the first step to build the change. Applying a structured strategy based on the behavioural science principles may be the path to increasing high value care in an effective an efficient way. It is time to foster nudge units at different healthcare system levels.

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Section: Low-value Care In the Perioperative Periodmentioning

confidence: 94%

Can we nudge to reduce the perioperative low value care? Decision making factors influencing safe practice implementation

Paz-Martin,

Arnal-Velasco

2023

Current Opinion in Anaesthesiology

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“…As the model also measures intra-operative variables, it will update risk measures to aid in post-operative triage decisions. We have shown how over-and under-triage may harm patients or result in lower value of care using our risk prediction algorithms (Loftus et al 2021(Loftus et al , 2022b. Pilot usability testing is currently on-going at our institution to develop a decision support tool.…”

Section: Future Directionsmentioning

confidence: 99%

Building an automated, machine learning-enabled platform for predicting post-operative complications

Balch

Ruppert²,

Shickel³

et al. 2023

Physiol. Meas.

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In 2019, the University of Florida College of Medicine launched the MySurgeryRisk algorithm to predict eight major post-operative complications using automatically extracted data from the electronic health record. This project was developed in parallel with our Intelligent Critical Care Center and represents a culmination of efforts to build an efficient and accurate model for data processing and predictive analytics. This paper discusses how our model was constructed and improved upon. We highlight the consolidation of the database, processing of fixed and time-series physiologic measurements, development and training of predictive models, and expansion of those models into different aspects of patient assessment and treatment. We end by discussing future directions of the model.

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“…Postoperative undertriage of high-acuity patients to hospital wards is associated with increased mortality and morbidity; overtriage of low-acuity patients to ICUs is associated with low value of care (outcomes/costs). 2 – 4 …”

Section: Introductionmentioning

confidence: 99%

Association of Sociodemographic Factors With Overtriage, Undertriage, and Value of Care After Major Surgery

Loftus,

Ruppert,

Shickel

et al. 2024

Annals of Surgery Open

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Objective: To determine whether certain patients are vulnerable to errant triage decisions immediately after major surgery and whether there are unique sociodemographic phenotypes within overtriaged and undertriaged cohorts. Background: In a fair system, overtriage of low-acuity patients to intensive care units (ICUs) and undertriage of high-acuity patients to general wards would affect all sociodemographic subgroups equally. Methods: This multicenter, longitudinal cohort study of hospital admissions immediately after major surgery compared hospital mortality and value of care (risk-adjusted mortality/total costs) across 4 cohorts: overtriage (N = 660), risk-matched overtriage controls admitted to general wards (N = 3077), undertriage (N = 2335), and risk-matched undertriage controls admitted to ICUs (N = 4774). K-means clustering identified sociodemographic phenotypes within overtriage and undertriage cohorts. Results: Compared with controls, overtriaged admissions had a predominance of male patients (56.2% vs 43.1%, P < 0.001) and commercial insurance (6.4% vs 2.5%, P < 0.001); undertriaged admissions had a predominance of Black patients (28.4% vs 24.4%, P < 0.001) and greater socioeconomic deprivation. Overtriage was associated with increased total direct costs [$16.2K ($11.4K–$23.5K) vs $14.1K ($9.1K–$20.7K), P < 0.001] and low value of care; undertriage was associated with increased hospital mortality (1.5% vs 0.7%, P = 0.002) and hospice care (2.2% vs 0.6%, P < 0.001) and low value of care. Unique sociodemographic phenotypes within both overtriage and undertriage cohorts had similar outcomes and value of care, suggesting that triage decisions, rather than patient characteristics, drive outcomes and value of care. Conclusions: Postoperative triage decisions should ensure equality across sociodemographic groups by anchoring triage decisions to objective patient acuity assessments, circumventing cognitive shortcuts and mitigating bias.

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Postoperative Overtriage to an Intensive Care Unit Is Associated With Low Value of Care

Cited by 11 publications

References 40 publications

Can we nudge to reduce the perioperative low value care? Decision making factors influencing safe practice implementation

Can we nudge to reduce the perioperative low value care? Decision making factors influencing safe practice implementation

Building an automated, machine learning-enabled platform for predicting post-operative complications

Association of Sociodemographic Factors With Overtriage, Undertriage, and Value of Care After Major Surgery

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