The purpose of this article is to explore the key themes and safety considerations connected to the inter-hospital transfer of critically unwell adults. First, the evidence base surrounding the subject is critically explored and clinical guidelines and national policy are discussed. Second, safety considerations are explored that highlight the risks and challenges associated with the inter-hospital transfer of critically unwell people.

BACKGROUND: A key decision facing nonthrombectomy capable (spoke) hospitals is whether to transfer a suspected large vessel occlusion (LVO) patient to a comprehensive stroke center (CSC). In a retrospective cohort study, we investigated the rate of transfers resulting in endovascular thrombectomy (EVT) and associated costs before and after implementation of an artificial intelligence (AI)-based software.
METHODS: All patients with a final diagnosis of acute ischemic stroke presenting across a five-spoke community hospital network in affiliation with a CSC were included. The Viz LVO (Viz.ai, Inc.) software was implemented across the spokes with image sharing and messaging between providers across sites. In a cohort of patients before (pre-AI, December 2018-October 2020) and after (post-AI, October 2020-August 2022) implementation, we compared the EVT rate among ischemic stroke patients transferred out of our health system to the CSC. Secondary outcomes included the EVT rate based on spoke computed tomography angiography (CTA) and estimated transfer costs.
RESULTS: A total of 3113 consecutive eligible patients (mean age 71 years, 50% female) presented to the spoke hospitals with 162 transfers pre-AI and 127 post-AI. The rate of transfers treated with EVT significantly increased (32.1% pre-AI vs. 45.7% post-AI, p = 0.02). There was a sharp increase in CTA use post-AI at the spoke hospitals for all patients and transfers that likely contributed to the increased EVT transfer rate, but prior spoke CTA use alone was not sufficient to account for all improvement in EVT transfer rate (37.2% pre-AI vs. 49.2% post-AI, p = 0.12). In a binary logistic regression model, the odds of an EVT transfer in the intervention period were 1.85 greater as compared to preintervention (adjusted odds ratio 1.85, 95% confidence interval 1.12-3.06). The decrease in non-EVT transfers resulted in an estimated annual benefit of $206,121 in spoke revenue and $119,921 in payor savings (all US dollars).
CONCLUSIONS: The implementation of an automated image interpretation and communication platform was associated with increased CTA use, more transfers treated with EVT, and potential economic benefits.

BACKGROUND: Person-centred care is becoming increasingly recognised as an important element of palliative care. The current review syntheses evidence in relation to transitions in advanced cancer patients with palliative care needs. The review focuses on specific elements which will inform the Pal-Cycles programme, for patients with advanced cancer transitioning from hospital care to community care. Elements of transitional models for cancer patients may include, identification of palliative care needs, compassionate communication with the patient and family members, collaborative effort to establish a multi-dimensional treatment plan, review and evaluation of the treatment plan and identification of the end of life phase.
METHODS: A scoping review of four databases (MEDLINE, EMBASE, CINAHL, PsycINFO) was conducted to identify peer-reviewed studies published from January 2013 to October, 2022. A further hand-search of references to locate additional relevant studies was also undertaken. Inclusion criteria involved cancer patients transitions of care with a minimum of two of components from those listed above. Studies were excluded if they were literature reviews, if transition of care was related to cancer survivors, involved non-cancer patients, had paediatric population, if the transition implied a change of therapy and or a lack of physical transit to a non-hospital place of care. This review was guided by Arksey and O\'Malley\'s framework and narrative synthesis was used.
RESULTS: Out of 5695 records found, 14 records were selected. Transition models identified: increases in palliative care consultations, hospice referrals, reduction in readmission rates and the ability to provide end of life care at home. Transition models highlight emotional and spiritual support for patients and families. No uniform model of transition was apparent, this depends on the healthcare system where it is implemented.
CONCLUSIONS: The findings highlight the importance of collaboration, coordination and communication as central mechanisms for transitional model for patients with advanced cancer. This may require careful planning and will need to be tailored to the contexts of each healthcare system.

A new patient transfer assessment scale for use in inpatient rehabilitation facilities (IRFs) is warranted to assess level of assistance, adaptations needed for success, and movement strategies. This study presents initial psychometric analyses for the Comprehensive Inpatient Transfer Tool (CITT). CITT items were developed through interdisciplinary team discussions. Interrater reliability was assessed between blinded pairs of raters administering the CITT for each subject on the same day. Intrarater reliability was assessed with one rater administering the CITT for each subject twice within the same day. Thirty-six subjects in an IRF completed the CITT four times during their rehabilitation stay; three times at admission and once at discharge. Intraclass correlations (mixed models) were used in reliability and minimal detectable change (MDC) analyses. Spearman correlations of CITT and CITT change scores with their respective Functional Independence Measure (FIM) and Inpatient Rehabilitation Facility - Patient Assessment Instrument (IRF-PAI) transfer scores were performed for concurrent validity. Responsiveness was assessed using paired t-tests on change scores. Interrater and intrarater reliability ranged from 0.90 to 0.98. Correlations between the CITT and FIM/IRF-PAI ranged from 0.6 to 0.8. The MDC for CITT was 7.11 pts. Differences between admission and discharge CITT were significant (P < 0.001). The CITT, developed by an interdisciplinary team, addresses limitations of existing transfer measures utilized in IRFs. The CITT demonstrated excellent inter and intrarater reliability. Concurrent validity demonstrated modest agreement between existing transfer measures and the CITT. The CITT is a reliable, useful scale for evaluating transfer skills in patients admitted to an IRF.

BACKGROUND: The process of transferring patients from small rural primary care facilities to referral facilities impacts the quality of care and effectiveness of the referral healthcare system. The study aimed to develop and evaluate the psychometric properties of a scale measuring requirements for effective rural emergency transfer.
METHODS: An exploratory sequential design was utilized to develop a scale designed to measure requirements for effective emergency transport. Phase one included a qualitative, interview study with 26 nursing transport providers. These transcripts were coded, and items developed for the proposed scale. Phase two included a content validity review by these 16 transport providers of the domains and items developed. Phase three included development and evaluation of psychometric properties of a scale designed to measure requirements for effective emergency transport. This scale was then tested initially with 84 items and later reduced to a final set of 58 items after completion by 302 transport nurses. The final scale demonstrated three factors (technology & tools; knowledge & skills; and organization). Each factor and the total score reported excellent scale reliability.
RESULTS: The initial item pool consisted of 84 items, generated, and synthesized from an extensive literature review and the qualitative descriptive study exploring nurses\' experiences in rural emergency patient transportation. A two-round modified Delphi method with experts generated a scale consisting of 58 items. A cross-sectional study design was used with 302 nurses in rural clinics and health in four rural health districts. A categorical principal components analysis identified three components explaining 63.35% of the total variance. The three factors, technology, tools, personal knowledge and skills, and organization, accounted for 27.32%, 18.15 and 17.88% of the total variance, respectively. The reliability of the three factors, as determined by the Categorical Principal Component Analysis (CATPCA)\'s default calculation of the Cronbach Alpha, was 0.960, 0.946, and 0.956, respectively. The RET Cronbach alpha was 0.980.
CONCLUSIONS: The study offers a three-factor scale to measure the effectiveness of emergency patient transport in rural facilities to better understand and improve care during emergency patient transport.

BACKGROUND: Poor patient progression from the progressive care unit (PCU) beds has been recognized as a bottleneck, limiting the hospital\'s ability to optimize capacity for the sickest patients. Improving nurse management on PCU admission and discharge criteria could avoid PCU bottlenecks.
OBJECTIVE: Our institution lacked a standard process to identify clinically appropriate patients ready for transfer out of the PCU, causing delays in vacating PCU beds.
OBJECTIVE: The aim of this study was to determine if creating a standard process to empower bedside nurses and unit nursing leaders to push readiness information to the provider team improves the appropriateness of PCU stay and transfers patients out of the PCU earlier.
METHODS: The most common causes of delayed transfer out of the PCU were discussed among stakeholders. A process was designed to empower the bedside nurses to partner with a physician leader to send information to the provider team requesting evaluation of the patient\'s readiness to leave the unit. The improvement of meeting the criteria for PCU was evaluated by comparing 60 patients prior to the intervention phase with 139 patients during the intervention.
RESULTS: The primary outcome, percentage of patients meeting PCU criteria, was 53% during the audit phase and 68% during the intervention phase (P = .05). The PCU transfer time was pushed 1 hour earlier in the day.
CONCLUSIONS: The standard process of empowering bedside nurses to partner with physician leaders to push readiness for transferring patients out of the PCU resulted in a significant improvement in the percentage of patients meeting PCU criteria and earlier discharge of appropriate patients.

In a previous study, sepsis was noted as a diagnosis on the home health record only 4% of the time for 165,000 sepsis survivors transitioning from hospital to home health care in America. If sepsis and other conditions are not clearly documented in the transitional care record this can lead to unpreparedness, missed, care, and poor patient outcomes. Our implementation science study discovered a source of this problem regarding the sepsis documentation in 16 hospitals referring to five home care agencies. Together, researchers, hospital, and home care personnel developed and implemented two information technology solutions to address this deficit in seven hospitals. The automated method was more readily adopted and effective in improving information transfer between hospital and home health care.

The use of healthcare information technology (HIT) is vital for storing and exchanging health information during patient transitions, playing a significant role in care coordination for sepsis survivors. The critical role of HIT was evident during the pre-implementation phase of a study to implement an evidence-based protocol supporting the timely transition of sepsis survivors to home health and outpatient care. Through 61 semi-structured interviews involving 91 stakeholders, over half of the 33 identified themes were related to HIT. Notably, electronic health record (EHR) alert systems led to over-capture and alarm fatigue. Efficient information transfer during HHC referral highlighted the need for improved EHR access. The study underscores HIT\'s importance and potential while emphasizing the need for collaborative policy and interface development to promote effective transitions in care.

UNASSIGNED: Interhospital transfer for patients with stroke due to large vessel occlusion for endovascular thrombectomy (EVT) has been associated with treatment delays.
UNASSIGNED: We analyzed data from Optimizing Patient Treatment in Major Ischemic Stroke With EVT, a quality improvement registry to support EVT implementation in Canada. We assessed for unadjusted differences in baseline characteristics, time metrics, and procedural outcomes between patients with large vessel occlusion transferred for EVT and those directly admitted to an EVT-capable center.
UNASSIGNED: Between January 1, 2018, and December 31, 2021, a total of 6803 patients received EVT at 20 participating centers (median age, 73 years; 50% women; and 50% treated with intravenous thrombolysis). Patients transferred for EVT (n=3376) had lower rates of M2 occlusion (22% versus 27%) and higher rates of basilar occlusion (9% versus 5%) compared with those patients presenting directly at an EVT-capable center (n=3373). Door-to-needle times were shorter in patients receiving intravenous thrombolysis before transfer compared with those presenting directly to an EVT center (32 versus 36 minutes). Patients transferred for EVT had shorter door-to-arterial access times (37 versus 87 minutes) but longer last seen normal-to-arterial access times (322 versus 181 minutes) compared with those presenting directly to an EVT-capable center. No differences in arterial access-to-reperfusion times, successful reperfusion rates (85% versus 86%), or adverse periprocedural events were found between the 2 groups. Patients transferred to EVT centers had a similar likelihood for good functional outcome (modified Rankin Scale score, 0-2; 41% versus 43%; risk ratio, 0.95 [95% CI, 0.88-1.01]; adjusted risk ratio, 0.98 [95% CI, 0.91-1.05]) and a higher risk for all-cause mortality at 90 days (29% versus 25%; risk ratio, 1.15 [95% CI, 1.05-1.27]; adjusted risk ratio, 1.14 [95% CI, 1.03-1.28]) compared with patients presenting directly to an EVT center.
UNASSIGNED: Patients transferred for EVT experience significant delays from the time they were last seen normal to the initiation of EVT.

UNASSIGNED: Standard of care for patients with acute ischemic stroke from large vessel occlusion (AIS-LVO) includes prompt evaluation for urgent mechanical thrombectomy (MT) at a comprehensive stroke center (CSC). During the start of the coronavirus 2019 pandemic (COVID-19), there were reports about disruption to emergency department (ED) operations and delays in management of patients with AIS-LVO. In this study we investigate the outcome and operations for patients who were transferred from different EDs to an academic CSC\'s critical care resuscitation unit (CCRU), which specializes in expeditious transfer of time-sensitive disease.
UNASSIGNED: This was a pre-post retrospective study using prospectively collected clinical data from our CSC\'s stroke registry. Adult patients who were transferred from any ED to the CCRU and underwent MT were eligible. We compared time intervals in the pre-pandemic (PP) period between January 2018- February 2020, such as ED in-out and CCRU arrival-angiography, to those during the pandemic (DP) between March 2020-May 31, 2021. We used classification and regression tree (CART) analysis to identify which time intervals, besides clinical factors, were associated with good neurological outcome (90-day modified Rankin scale 0-2).
UNASSIGNED: We analyzed 203 patients: 135 (66.5%) in the PP group and 68 (33.5%) in the DP group. Time from ED triage to computed tomography (difference 7 minutes, 95% confidence interval [CI] -12 to -1, P < 0.01) for the DP group was statistically longer, but ED in-out was similar for both groups. Time from CCRU arrival to angiography (difference 9 minutes, 95% CI 4-13, P < 0.01) for the DP group was shorter. Forty-nine percent of the DP group achieved mRS ≤ 2 vs 32% for the PP group (difference -17%, 95% CI -0.32 to -0.03, P < 0.01). The CART identified initial National Institutes of Health Stroke Scale, age, ED in-and-out time, and CCRU arrival-to-angiography time as important predictors of good outcome.
UNASSIGNED: Overall, the care process in EDs and at this single CSC for patients requiring MT were not heavily affected by the pandemic, as certain time metrics during the pandemic were statistically shorter than pre-pandemic intervals. Time intervals such as ED in-and-out and CCRU arrival-to-angiography were important factors in achieving good neurologic outcomes. Further study is necessary to confirm our observation and improve operational efficiency in the future.