2021
DOI: 10.1111/poms.13455
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Differentiating Interhospital Transfer Types: Varied Impacts and Diverging Coordination Strategies

Abstract: I nterhospital transfer (IHT) is common in care delivery. As a form of care transition, IHT faces coordination challenges and can negatively affect care outcomes. Understanding the underlying reasons and the associated operational challenges of different IHT types can help hospital managers design mitigation mechanisms to improve the IHT care outcomes. We conceptually and empirically differentiate between clinical and non-clinical transfers based on their unique characteristics and compare their respective imp… Show more

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Cited by 5 publications
(7 citation statements)
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“…In the main analysis, we follow existing studies (see, e.g., Batt et al., 2019; Fan et al., 2021; Huang et al., 2021; Oh et al., 2018) by using propensity score matching to identify from the control and treatment groups a sample of counties that have similar baseline features and pretreatment outcomes. A potential concern is that individual counties have different pretreatment outcomes.…”
Section: Results and Robustness Checksmentioning
confidence: 99%
See 1 more Smart Citation
“…In the main analysis, we follow existing studies (see, e.g., Batt et al., 2019; Fan et al., 2021; Huang et al., 2021; Oh et al., 2018) by using propensity score matching to identify from the control and treatment groups a sample of counties that have similar baseline features and pretreatment outcomes. A potential concern is that individual counties have different pretreatment outcomes.…”
Section: Results and Robustness Checksmentioning
confidence: 99%
“…We follow existing studies (see, e.g., Batt et al., 2019; Fan et al., 2021; Huang et al., 2021; Oh et al., 2018) by using the propensity score matching method to address the curse of dimensionality. To describe this matching method, we denote by Featurei$Feature_i$ and NewCasesi$NewCases_i$ baseline features and pretreatment outcomes of county i$i$, and StayAtHomeOrdersi$StayAtHomeOrders_i$ a dummy that indicates whether county i$i$ implemented the stay‐at‐home order during our study period.…”
Section: Econometric Modelmentioning
confidence: 99%
“…Others have reported large increases in LOS after intrahospital transfers, [11], [57] highlighting the importance of avoiding transfers where possible. Similarly, while the outcomes of patients following an inter-hospital transfer have been studied, [58], [59] the impact of a transfer to a hospital within a single trust has been unexplored. Our finding that such transfers are associated with a decrease in mortality suggests that localisation of specialist and general hospitals within a trust is a successful model of care, in the context of a large urban hospital trust.…”
Section: Triangulation and Interpretation In Light Of Other Evidencementioning
confidence: 99%
“…Interhospital transfers of patients involve the complex and rapid coordination of clinical processes at two different hospitals. Most commonly, transfers occur because a patient's needs fall outside the scope of a hospital's level of care, requiring specialty surgical, subspecialty medical, or intensive care services 1 . Less commonly, patient preference or capacity constraints dictate the decision to transfer 2 .…”
mentioning
confidence: 99%
“…Most commonly, transfers occur because a patient's needs fall outside the scope of a hospital's level of care, requiring specialty surgical, subspecialty medical, or intensive care services. 1 Less commonly, patient preference or capacity constraints dictate the decision to transfer. 2 Both formal (transfer of medical imaging) and informal (phone calls between providers) coordinating mechanisms facilitate moving a patient from one hospital to another.…”
mentioning
confidence: 99%