Inter-hospital Transfer Decision-making During the COVID-19 Pandemic: a Qualitative Study

Harlan, Emily A; Mubarak, Eman; Firn, Janice; Goold, Susan Dorr; Shuman, Andrew G.

doi:10.1007/s11606-023-08237-w

Cited by 12 publications

(8 citation statements)

References 37 publications

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“…We combined 2010–2019 all‐payer ED and inpatient hospital discharge data for Florida, obtained from the Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases and State Emergency Department Databases data, with American Hospital Association Annual Survey (2009–2018) hospital characteristic data and median household income data for the patient ZIP code from the Area Health Resource File. We used data prior to the coronavirus disease 2019 (COVID‐19) pandemic due to fundamental difference in ED use and transfers during the acute phase of the pandemic 50–52 …”

Section: Methodsmentioning

confidence: 99%

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Racial and ethnic disparities in emergency department transfers to public hospitals

Hsuan,

Vanness,

Zebrowski

et al. 2024

Health Services Research

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ObjectiveTo examine racial/ethnic differences in emergency department (ED) transfers to public hospitals and factors explaining these differences.Data Sources and Study SettingED and inpatient data from the Healthcare Cost and Utilization Project for Florida (2010–2019); American Hospital Association Annual Survey (2009–2018).Study DesignLogistic regression examined race/ethnicity and payer on the likelihood of transfer to a public hospital among transferred ED patients. The base model was controlled for patient and hospital characteristics and year fixed effects. Models II and III added urbanicity and hospital referral region (HRR), respectively. Model IV used hospital fixed effects, which compares patients within the same hospital. Models V and VI stratified Model IV by payer and condition, respectively. Conditions were classified as emergency care sensitive conditions (ECSCs), where transfer is protocolized, and non‐ECSCs. We reported marginal effects at the means.Data Collection/Extraction MethodsWe examined 1,265,588 adult ED patients transferred from 187 hospitals.Principal FindingsBlack patients were more likely to be transferred to public hospitals compared with White patients in all models except ECSC patients within the same initial hospital (except trauma). Black patients were 0.5–1.3 percentage points (pp) more likely to be transferred to public hospitals than White patients in the same hospital with the same payer. In the base model, Hispanic patients were more likely to be transferred to public hospitals compared with White patients, but this difference reversed after controlling for HRR. Hispanic patients were − 0.6 pp to −1.2 pp less likely to be transferred to public hospitals than White patients in the same hospital with the same payer.ConclusionsLarge population‐level differences in whether ED patients of different races/ethnicities were transferred to public hospitals were largely explained by hospital market and the initial hospital, suggesting that they may play a larger role in explaining differences in transfer to public hospitals, compared with other external factors.

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Section: Methodsmentioning

confidence: 99%

“…We used data prior to the coronavirus disease 2019 (COVID‐19) pandemic due to fundamental difference in ED use and transfers during the acute phase of the pandemic. 50 , 51 , 52 …”

Section: Methodsmentioning

confidence: 99%

Racial and ethnic disparities in emergency department transfers to public hospitals

Hsuan,

Vanness,

Zebrowski

et al. 2024

Health Services Research

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“…Use of call centers to coordinate conversations between providers. [3][4][5]20,21 Explores how call centers are facilitating calls, recording conversation, and documenting information.…”

Section: Tools/technology (Objects Used To Complete Tasks)mentioning

confidence: 99%

“…and require admitting providers to sift through large amounts of T A B L E 1 Applying HFSE via the SEIPS framework to expand IHT study and intervention design. Accepting hospital physicians 4,20,21 Transferring hospital physicians 20 Accepting hospital nurses 5 Transferring hospital nurses 20 Call center nurses (opinions on physician conversations) Determine what new tasks may be needed to educate patients and care partners. Examine impact on workflows.…”

Section: Tools and Technologymentioning

confidence: 99%

Engineering safe care journeys: Reenvisioning interhospital transfers

Yu,

Chopra,

Mueller

et al. 2024

Journal of Hospital Medicine

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The scenario is all too familiar: the admitting medical team flips through a large stack of paper that comes with the new patient transferred from another hospital. Almost all the clinically relevant information is buried or missing. Electronic health records (EHRs) show no prior encounters in the system and no note from the accepting provider. Then, an urgent page appears: "Please see patient; they do not look well. Family is anxious for an update and wants to know the plan." The sense of unease is palpable; no one enjoys being unprepared when meeting a new patient.

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“…Evidence on acute hospital transfers during the pandemic has been limited to local or narrative reports, surveys, specific patient cohorts (eg, those with stroke or ST-elevation myocardial infarction), and non-US studies. 6,[12][13][14][15][16][17] Most US states have not reported their experience with transfers to date, and among the few that have, the ability to transfer patients appeared to vary substantially across individual US state-based transfer coordination enters. 17,18 Furthermore, there were media reports of US hospitals making multiple unsuccessful attempts to move patients to other hospitals.…”

Section: Introductionmentioning

confidence: 99%

Trends in Patient Transfers From Overall and Caseload-Strained US Hospitals During the COVID-19 Pandemic

Sarzynski,

Mancera,

Yek

et al. 2024

JAMA Netw Open

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ImportanceTransferring patients to other hospitals because of inpatient saturation or need for higher levels of care was often challenging during the early waves of the COVID-19 pandemic. Understanding how transfer patterns evolved over time and amid hospital overcrowding could inform future care delivery and load balancing efforts.ObjectiveTo evaluate trends in outgoing transfers at overall and caseload-strained hospitals during the COVID-19 pandemic vs prepandemic times.Design, Setting, and ParticipantsThis retrospective cohort study used data for adult patients at continuously reporting US hospitals in the PINC-AI Healthcare Database. Data analysis was performed from February to July 2023.ExposuresPandemic wave, defined as wave 1 (March 1, 2020, to May 31, 2020), wave 2 (June 1, 2020, to September 30, 2020), wave 3 (October 1, 2020, to June 19, 2021), Delta (June 20, 2021, to December 18, 2021), and Omicron (December 19, 2021, to February 28, 2022).Main Outcomes and MeasuresWeekly trends in cumulative mean daily acute care transfers from all hospitals were assessed by COVID-19 status, hospital urbanicity, and census index (calculated as daily inpatient census divided by nominal bed capacity). At each hospital, the mean difference in transfer counts was calculated using pairwise comparisons of pandemic (vs prepandemic) weeks in the same census index decile and averaged across decile hospitals in each wave. For top decile (ie, high-surge) hospitals, fold changes (and 95% CI) in transfers were adjusted for hospital-level factors and seasonality.ResultsAt 681 hospitals (205 rural [30.1%] and 476 urban [69.9%]; 360 [52.9%] small with &lt;200 beds and 321 [47.1%] large with ≥200 beds), the mean (SD) weekly outgoing transfers per hospital remained lower than the prepandemic mean of 12.1 (10.4) transfers per week for most of the pandemic, ranging from 8.5 (8.3) transfers per week during wave 1 to 11.9 (10.7) transfers per week during the Delta wave. Despite more COVID-19 transfers, overall transfers at study hospitals cumulatively decreased during each high national surge period. At 99 high-surge hospitals, compared with a prepandemic baseline, outgoing acute care transfers decreased in wave 1 (fold change −15.0%; 95% CI, −22.3% to −7.0%; P &lt; .001), returned to baseline during wave 2 (2.2%; 95% CI, −4.3% to 9.2%; P = .52), and displayed a sustained increase in subsequent waves: 19.8% (95% CI, 14.3% to 25.4%; P &lt; .001) in wave 3, 19.2% (95% CI, 13.4% to 25.4%; P &lt; .001) in the Delta wave, and 15.4% (95% CI, 7.8% to 23.5%; P &lt; .001) in the Omicron wave. Observed increases were predominantly limited to small urban hospitals, where transfers peaked (48.0%; 95% CI, 36.3% to 60.8%; P &lt; .001) in wave 3, whereas large urban and small rural hospitals displayed little to no increases in transfers from baseline throughout the pandemic.Conclusions and RelevanceThroughout the COVID-19 pandemic, study hospitals reported paradoxical decreases in overall patient transfers during each high-surge period. Caseload-strained rural (vs urban) hospitals with fewer than 200 beds were unable to proportionally increase transfers. Prevailing vulnerabilities in flexing transfer capabilities for care or capacity reasons warrant urgent attention.

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Inter-hospital Transfer Decision-making During the COVID-19 Pandemic: a Qualitative Study

Cited by 12 publications

References 37 publications

Racial and ethnic disparities in emergency department transfers to public hospitals

Racial and ethnic disparities in emergency department transfers to public hospitals

Engineering safe care journeys: Reenvisioning interhospital transfers

Trends in Patient Transfers From Overall and Caseload-Strained US Hospitals During the COVID-19 Pandemic

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