|Title||Modeling the Impact of Interhospital Transfer Network Design on Stroke Outcomes in a Large City.|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Parikh NS, Chatterjee A, Díaz I, Pandya A, Merkler AE, Gialdini G, Kummer BR, Mir SA, Lerario MP, Fink ME, Navi BB, Kamel H|
|Date Published||2018 Feb|
BACKGROUND AND PURPOSE: We sought to model the effects of interhospital transfer network design on endovascular therapy eligibility and clinical outcomes of stroke because of large-vessel occlusion for the residents of a large city.
METHODS: We modeled 3 transfer network designs for New York City. In model A, patients were transferred from spoke hospitals to the closest hub hospitals with endovascular capabilities irrespective of hospital affiliation. In model B, which was considered the base case, patients were transferred to the closest affiliated hub hospitals. In model C, patients were transferred to the closest affiliated hospitals, and transfer times were adjusted to reflect full implementation of streamlined transfer protocols. Using Monte Carlo methods, we simulated the distributions of endovascular therapy eligibility and good functional outcomes (modified Rankin Scale score, 0-2) in these models.
RESULTS: In our models, 200 patients (interquartile range [IQR], 168-227) with a stroke amenable to endovascular therapy present to New York City spoke hospitals each year. Transferring patients to the closest hub hospital irrespective of affiliation (model A) resulted in 4 (IQR, 1-9) additional patients being eligible for endovascular therapy and an additional 1 (IQR, 0-2) patient achieving functional independence. Transferring patients only to affiliated hospitals while simulating full implementation of streamlined transfer protocols (model C) resulted in 17 (IQR, 3-41) additional patients being eligible for endovascular therapy and 3 (IQR, 1-8) additional patients achieving functional independence.
CONCLUSIONS: Optimizing acute stroke transfer networks resulted in clinically small changes in population-level stroke outcomes in a dense, urban area.
|PubMed Central ID||PMC5780257|
|Grant List||K23 NS082367 / NS / NINDS NIH HHS / United States |
K23 NS091395 / NS / NINDS NIH HHS / United States
R01 NS097443 / NS / NINDS NIH HHS / United States
T32 NS007153 / NS / NINDS NIH HHS / United States