Insurance-Based Disparities in Stroke Center Access in California: A Network Science Approach

Abstract

Background: Our objectives were to determine whether there is an association between ischemic stroke patient insurance and likelihood of transfer overall and to a stroke center and whether hospital cluster modified the association between insurance and likelihood of stroke center transfer.

Methods: This retrospective network analysis of California data included every nonfederal hospital ischemic stroke admission from 2010 to 2017. Transfers from an emergency department to another hospital were categorized based on whether the patient was discharged from a stroke center (primary or comprehensive). We used logistic regression models to examine the relationship between insurance (private, Medicare, Medicaid, uninsured) and odds of (1) any transfer among patients initially presenting to nonstroke center hospital emergency departments and (2) transfer to a stroke center among transferred patients. We used a network clustering method to identify clusters of hospitals closely connected through transfers. Within each cluster, we quantified the difference between insurance groups with the highest and lowest proportion of transfers discharged from a stroke center.

Results: Of 332 995 total ischemic stroke encounters, 51% were female, 70% were ≥65 years, and 3.5% were transferred from the initial emergency department. Of 52 316 presenting to a nonstroke center, 3466 (7.1%) were transferred. Relative to privately insured patients, there were lower odds of transfer and of transfer to a stroke center among all groups (Medicare odds ratio, 0.24 [95% CI, 0.22-0.26] and 0.59 [95% CI, 0.50-0.71], Medicaid odds ratio, 0.26 [95% CI, 0.23-0.29] and odds ratio, 0.49 [95% CI, 0.38-0.62], uninsured odds ratio, 0.75 [95% CI, 0.63-0.89], and 0.72 [95% CI, 0.6-0.8], respectively). Among the 14 identified hospital clusters, insurance-based disparities in transfer varied and the lowest performing cluster (also the largest; n=2364 transfers) fully explained the insurance-based disparity in odds of stroke center transfer.

Conclusions: Uninsured patients had less stroke center access through transfer than patients with insurance. This difference was largely explained by patterns in 1 particular hospital cluster.

Keywords: United States; hospitals; ischemic stroke; medically uninsured; patients.

Figure 1.. Distribution of Ischemic Stroke Encounters by Transfer Status and Stroke Center Status of Destination Hospital

ED: emergency department; PSC: Primary Stroke Center; CSC: Comprehensive Stroke Center; tPA: intravenous thrombolytic; EVT: endovascular thrombectomy

Figure 2.. Regionalization of Ischemic Stroke Care in California, 2010–2017

The regionalization index (RI; range 0–1) is defined in the Methods as a representation of the degree to which stroke care is regionalized or dependent on transfers for patients to access definitive care. Values approaching 1 indicate high regionalization and higher needs for transfer. The red dashed line indicates the mean RI for each given panel.

Figure 3.. California Stroke Transfer Network 2010–2017, Overall and by Insurance Status

These figures represent the ischemic stroke transfer network in California. Each node represents a hospital; the size of the node is proportional to the hospital’s annual stroke volume (emergency department + inpatient discharges). Each line between hospitals indicates that those two hospitals are connected through patient transfer. Mean driving distance is the mean driving distance for all transfers represented in the network figure. Edge density (range 0–1) is the proportion of potential connections between hospitals that are actually connected through patient transfer. Clustering coefficient (range 0–1) is a property describing the degree to which hospitals tend to cluster together.

Figure 4.. Community-Level Visualization of Stroke Center Access and Transfer Patterns by Insurance Status

Each of the 14 hospital clusters is represented by a column in the figure. The green rows present the percentage of patients discharged from a stroke center within each community, stratified by insurance category. The blue rows present the number of patient encounters transferred from the initial emergency department (ED) of presentation within each community, stratified by insurance status. Community numbers correspond to those in Table 3. PSC: primary stroke center; CSC: comprehensive stroke center.

Figure 5.. Communities of Hospitals Connected through Transfer in California, Characterized by Degree of Insurance-Based Disparity in Stroke Center Access among Transferred Patients

This figure represents the ischemic stroke transfer network for the full study period in California. Each node represents a hospital; the size of the node is proportional to the hospital’s annual stroke volume (emergency department + inpatient discharges). Each line between hospitals indicates that those two hospitals are connected through patient transfer. Communities of hospitals closely connected through patient transfer are depicted as clusters with the same color node and a shape outlining the cluster. The green shading surrounding each cluster indicates the degree of disparity in access to stroke center care (i.e., the insurance disparity). The darkest green community is the lowest performing, with a delta of 49% between privately insured and self-pay transfers.