Interhospital transfers of the critically ill: Time spent at referring institutions influences survival

Hanane, Tarik; Wiles, Samuel; Senussi, Mourad H.; Xiao, Han; Hite, R. Duncan; Guzmán, Jorge

doi:10.1016/j.jcrc.2016.12.016

Cited by 9 publications

(9 citation statements)

References 24 publications

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“…This survival benefit can be due to several factors, the primary being those patients experiencing a time-sensitive emergency such as heart attack or stroke that benefit from rapid transfer and intervention at the tertiary care center. Another study identified that length of stay at the referring hospital before transfer is an independent predictor of increased ICU and hospital mortality post-transfer (39). In combination, these findings support the need to identify patients that require transfer and transfer those patients earlier in their healthcare encounter.…”

Section: Discussionmentioning

confidence: 84%

Patient factors associated with survival after critical care interhospital transfer

Reimer,

Dai,

Schiltz

et al. 2024

Front. Disaster Emerg. Med.

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ObjectiveTo identify the factors that predict mortality post-transfer and develop a comprehensive mortality prediction model capable of supporting pre-transfer decision making.Materials and methodsElectronic health record data from the Medical Transport Data Repository of a large health system hospital in Northeast Ohio that consists of a main campus and 11 affiliated medical centers. We retrospectively analyzed patient data from the referring hospital encounter prior to interhospital transfer. All patient data including diagnoses, laboratory results, medication, and medical and social history were analyzed to predict in-hospital mortality post-transfer. We employed a multi-method approach including logistic regression, gradient boosting, and multiple correspondence analysis to identify significant predictors of mortality as well as variables that are clinically useful to inform clinical decision support development. We identified all patients aged 21 and older that underwent critical care transfer in the health system between 2010 and 2017.ResultsWe found that age, laboratory results (albumin, INR, platelets, BUN, leukocyte, hemoglobin, glucose), vital signs (temperature, respirations, pulse, systolic blood pressure, pulse oximetry), and ventilator usage are the most predictive variables of post-interhospital transfer mortality. Using structured data from the EHR we achieved the same performance as APACHE IV within our health system (0.85 vs. 0.85). Lastly, mode of transport alone was not a significant predictor for the general population in any of the outcome models.ConclusionsOur findings provide a foundation for the development of decision support tools to guide transport referrals and identified the need for further inquiry to discern the role of mode of transport to enable future inclusion in decision support approaches. Further inquiry is needed to identify factors that differentiate patients not triaged as time-sensitive transfers but still require helicopter intervention to maintain or improve post-interhospital transfer morbidity and mortality.

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Section: Discussionmentioning

confidence: 84%

Patient factors associated with survival after critical care interhospital transfer

Reimer,

Dai,

Schiltz

et al. 2024

Front. Disaster Emerg. Med.

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“…The 16 articles included in this review were observational in nature, with 14 retrospective analysis that used either administrative databases (15)(16)(17)(18)(19)(20) or electronic health record data (21)(22)(23)(24)(25)(26)(27)(28). One study was prospective in nature and examined the reasons behind patient transfer (29), while another evaluated the efficacy of an intervention on transfer wait times and outcomes (30).…”

Section: Resultsmentioning

confidence: 99%

Interhospital Transfer of Patients With Acute Respiratory Failure in the United States: A Scoping Review

Ludwig,

Slota,

Nunes

et al. 2024

Critical Care Explorations

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OBJECTIVES: Interhospital transfer of patients with acute respiratory failure (ARF) is relevant in the current landscape of critical care delivery. However, current transfer practices for patients with ARF are highly variable, poorly formalized, and lack evidence. We aim to synthesize the existing evidence, identify knowledge gaps, and highlight persisting questions related to interhospital transfer of patients with ARF. DATA SOURCES: Ovid Medline, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Embase, CINAHL Plus, and American Psychological Association. STUDY SELECTION: We included studies that evaluated or described hospital transfers of adult (age > 18) patients with ARF between January 2020 and 2024 conducted in the United States. Using predetermined search terms and strategies, a total of 3369 articles were found across all databases. After deduplication, 1748 abstracts were screened by authors with 45 articles that advanced to full-text review. This yielded 16 studies that fit our inclusion criteria. DATA EXTRACTION: The studies were reviewed in accordance to Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews by three authors. DATA SYNTHESIS: Included studies were mostly retrospective analyses of heterogeneous patients with various etiologies and severity of ARF. Overall, transferred patients were younger, had high severity of illness, and were more likely to have commercial insurance compared with nontransferred cohorts. There is a paucity of data examining why patients get transferred. Studies that retrospectively evaluated outcomes between transferred and nontransferred cohorts found no differences in mortality, although transferred patients have a longer length of stay. There is limited evidence to suggest that patients transferred early in their course have improved outcomes. CONCLUSIONS: Our scoping review highlights the sparse evidence and the urgent need for further research into understanding the complexity behind ARF transfers. Future studies should focus on defining best practices to inform clinical decision-making and improve downstream outcomes.

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“…Our sample consisted of critical care transfers via both ground and air and admitted to all unit types exhibiting an overall mortality of 11.7%, similar to the 8.9% overall mortality reported for all transfers in another interhospital transfers cohort study [ 33 ]. Other studies have reported post-transfer mortality ranging from 16%—32% hospital mortality for transferred patients admitted to intensive care units [ 16 , 34 ].…”

Section: Discussionmentioning

confidence: 99%

High-risk diagnosis combinations in patients undergoing interhospital transfer: a retrospective observational study

2022

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Background There is limited research on individual patient characteristics, alone or in combination, that contribute to the higher levels of mortality in post-transfer patients. The purpose of this work is to identify significant combinations of diagnoses that identify subgroups of post-interhospital transfer patients experiencing the highest levels of mortality. Methods This was a retrospective cross-sectional study using structured electronic health record data from a regional health system between 2010–2017. We employed a machine learning approach, association rules mining using the Apriori algorithm to identify diagnosis combinations. The study population includes all patients aged 21 and older that were transferred within our health system from a community hospital to one of three main receiving hospitals. Results Overall, 8893 patients were included in the analysis. Patients experiencing mortality post-transfer were on average older (70.5 vs 62.6 years) and on average had more diagnoses in 5 of the 6 diagnostic subcategories. Within the diagnostic subcategories, most diagnoses were comorbidities and active medical problems, with hypertension, atrial fibrillation, and acute respiratory failure being the most common. Several combinations of diagnoses identified patients that exceeded 50% post-interhospital transfer mortality. Conclusions Comorbid burden, in combination with active medical problems, were most predictive for those experiencing the highest rates of mortality. Further improving patient level prognostication can facilitate informed decision making between providers and patients to shift the paradigm from transferring all patients to higher level care to only transferring those who will benefit or desire continued care, and reduce futile transfers.

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Interhospital transfers of the critically ill: Time spent at referring institutions influences survival

Cited by 9 publications

References 24 publications

Patient factors associated with survival after critical care interhospital transfer

Patient factors associated with survival after critical care interhospital transfer

Interhospital Transfer of Patients With Acute Respiratory Failure in the United States: A Scoping Review

High-risk diagnosis combinations in patients undergoing interhospital transfer: a retrospective observational study

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