Influence of Hospital Characteristics on Hospital Transfer Destinations for Patients With Stroke

Effect of the Implementation of the French Hospital Regionalization Policy on Patient Mobility

A new law was voted in France in 2016 to increase cooperation between public sector hospitals. Hospitals were encouraged to work under the leadership of local referral centers and to share their support functions (e.g., information systems) with newly created hospital groups, called "Regional Hospital Groups." The law made it compulsory for each public sector hospital to become affiliated with one of 136 newly created hospital groups. The policy's aim was to ensure that all patients were sent to the hospital best qualified to treat their unique condition, among the hospitals available at the regional level. Therefore, we aimed to assess whether this regionalization policy was associated with changes in observed patterns of patient mobility between hospitals. This nationwide observational study followed an interrupted time series design. For each stay occurring from 2014 to 2019, we ascertained whether or not the stay was followed by mobility toward another hospital within 90 days, and whether or not the receiving hospital was part of the same Regional Hospital Group as the sender hospital. The proportion of mobility directed toward the same regional hospital group increased from 22.9% in 2014 (95% CI 22.7-23.1) to 24.6% in 2019 (95% CI 24.4-24.8). However, the absence of discontinuity during the policy change year was consistent with the hypothesis of a preexisting trend toward regionalization. Therefore, the policy did not achieve major changes in patterns of mobility between hospitals. Other objectives of the reform, including long-term consequences on the healthcare offer, remain to be assessed.

Changing Health Care Markets Have the Potential to Undermine Stroke Systems of Care

This Viewpoint discusses the importance of prioritizing quality of care for patients with stroke in a changing health care environment.

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

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.

Prehospital Stroke Care Part 1: Emergency Medical Services and the Stroke Systems of Care

Acute stroke care begins before hospital arrival, and several prehospital factors are critical in influencing overall patient care and poststroke outcomes. This topical review provides an overview of the state of the science on prehospital components of stroke systems of care and how emergency medical services systems may interact in the system to support acute stroke care. Topics include layperson recognition of stroke, prehospital transport strategies, networked stroke care, systems for data integration and real-time feedback, and inequities that exist within and among systems.