OBJECTIVE: The objective of this study is to identify variables associated with clinical outcomes after urologic transfers before and during the COVID pandemic.
METHODS: After IRB approval, a retrospective chart review was performed on adult patients transferred to our institution from 01/01/2018 to 12/31/2019 (\"pre-COVID\") and from 01/02/2020 to 12/31/2022 (\"COVID\"). We identified demographics, origin hospitals, ICD-10 pre- and post-transfer diagnoses, distance of transfer, and post-transfer CPT codes.
RESULTS: During the study period, our adult urology service accepted 160 transfers with a mean patient age of 71 years. A total of 49/160 (30%) of subjects made up the \"pre-COVID\" cohort and 111/160 (70%) made up the \"COVID\" cohort. There were 11/111 (10%) transfers of >100 miles in the COVID period but 0/49 in the pre-COVID period (p = 0.02). Patients from the COVID period waited on average 1.2 days longer for a procedure after transfer compared to pre-COVID period (p = 0.03). The time until a patient\'s surgical procedure after transfer was a significant predictor of length of stay > 5 days (OR 1.91, CI 1.43 - 2.58, p < 0.01). Different diagnosis upon re-evaluation after transfer was associated with a decreased rate of subsequent readmission (OR 0.30, CI 0.09-0.97, p = 0.05).
CONCLUSIONS: Long-distance transfer, even >100 miles (which we termed \"mega-transfers\"), was a new pandemic-related phenomenon at our institution. Delays in definitive care and changes in diagnoses after transfer were associated with readmission and length of stay. Our findings illustrate the importance of inter-institutional communication, diagnostic accuracy, and post discharge planning when managing transfer patients.

BACKGROUND: Patients with head and neck cancers (HNC) experience many transitions in care (TiC), occurring when patients are transferred between healthcare providers and/or settings. TiC can compromise patient safety, decrease patient satisfaction, and increase healthcare costs. The evidence around TiC among patients with HNC is sparse. The objective of this study was to improve our understanding of TiC among patients with HNC to identify ways to improve care.
METHODS: This multimethod study consisted of two phases: Phase I (retrospective population-based cohort study) characterized the number and type of TiC that patients with HNC experienced using deterministically linked, population-based administrative health data in Alberta, Canada (January 1, 2012, to September 1, 2020), and Phase II (qualitative descriptive study) used semi-structured interviews to explore the lived experiences of patients with HNC and their healthcare providers during TiC.
RESULTS: There were 3,752 patients with HNC; most were male (70.8%) with a mean age at diagnosis of 63.3 years (SD 13.1). Patients underwent an average of 1.6 (SD 0.7) treatments, commonly transitioning from surgery to radiotherapy (21.2%). Many patients with HNC were admitted to the hospital during the study period, averaging 3.3 (SD 3.0) hospital admissions and 7.8 (SD 12.6) emergency department visits per patient over the study period. Visits to healthcare providers were also frequent, with the highest number of physician visits being to general practitioners (average = 70.51 per patient). Analysis of sixteen semi-structured interviews (ten patients with HNC and six healthcare providers) revealed three themes: (1) Navigating the healthcare system including challenges with the complexity of HNC care amongst healthcare system pressures, (2) Relational head and neck cancer care which encompasses patient expectations and relationships, and (3) System and individual impact of transitions in care.
CONCLUSIONS: This study identified challenges faced by both patients with HNC and their healthcare providers amidst the frequent TiC within cancer care, which was perceived to have an impact on quality of care. These findings provide crucial insights that can inform and guide future research or the development of health interventions aiming to improve the quality of TiC within this patient population.

OBJECTIVE: To explore and describe the everyday practices (Work-As-Done) that hinder and facilitate patient care transitions from the intensive care unit (ICU) to the ward.
METHODS: Multiple qualitative case studies in the ICU and various specialized wards of three Dutch hospitals. Adult patients planned to be transferred were purposively sampled on a variety of characteristics along with their relative (if present), and the ICU and ward nurses who were involved in the transition process. Data were collected by using multiple sources (i.e., observations, semi-structured interviews and a qualitative survey) and then systematically analyzed using the thematic analysis approach until saturation was reached.
RESULTS: Twenty-six cases were studied. For each case, the actual transfer was observed. Sixteen patients, five relatives and 36 nurses were interviewed. Two patients completed the survey. Fifteen themes emerged from the data, showing that the quality of transitions is influenced by the extent to which nurses anticipate to patient-specific needs (e.g., providing timely and adequate information, orientation, mental support and aftercare) and to the needs of the counterpart to continue care (e.g., by preparing handovers) besides following standard procedures. Data also show that procedures sometimes interfere with what works best in practice (e.g., communication via a liaison service instead of direct communication between ICU and ward nurses).
CONCLUSIONS: Subtle, non-technical nursing skills play an important role in comforting patients and in the coordination of care when patients are transferred from the ICU to the ward.
CONCLUSIONS: These Work-As-Done findings and their underlying narratives, that are often overlooked when focusing on quality improvement, can be used as material to reflect on own practice and raise awareness for its impact on patients. They may stimulate healthcare staff in crafting interventions for optimizing the transition process.

UNASSIGNED: Stroke treatment is exquisitely time sensitive. The door-in-door-out (DIDO) time, defined as the total time spent in the emergency department (ED) at a transferring hospital, is an important quality metric for the care of acute stroke. However, little is known about the contributions of specific process steps to delays and disparities in DIDO time.
UNASSIGNED: To quantify process steps and their association with DIDO times at transferring hospitals among patients with acute ischemic stroke (AIS).
UNASSIGNED: This retrospective cohort study analyzed patients in the American Heart Association Get With the Guidelines-Stroke registry with AIS presenting between January 1, 2019, to December 31, 2021, and transferred from the presenting hospital ED to another acute care hospital for evaluation of thrombolytics, endovascular therapy, or postthrombolytic care. Data were analyzed from July 8 to October 13, 2023.
UNASSIGNED: Intervals of ED care of ischemic stroke: door-to-imaging and imaging-to-door times.
UNASSIGNED: The primary outcome was DIDO time. Multivariate generalized estimating equations regression models were performed to compare contributions of interval process times to explain variation in DIDO time, controlling for patient- and hospital-level characteristics.
UNASSIGNED: Among 28 887 patients (50.5% male; mean [SD] age, 68.3 [14.8] years; 5.5% Hispanic, 14.7% non-Hispanic Black, and 73.2% non-Hispanic White), mean (SD) DIDO time was 171.4 (149.5) minutes, mean (SD) door-to-imaging time was 18.3 (34.1) minutes, and mean (SD) imaging-to-door time was 153.1 (141.5) minutes. In the model adjusting for door-to-imaging time, the following were associated with longer DIDO time: age 80 years or older (compared with 18-59 years; 5.97 [95% CI, 1.02-10.92] minutes), female sex (5.21 [95% CI, 1.55-8.87] minutes), and non-Hispanic Black race (compared with non-Hispanic White 10.09 [95% CI, 4.21-15.96] minutes). In the model including imaging-to-door time as a covariate, disparities in DIDO by age and female sex became nonsignificant, and the disparity by Black race was attenuated (2.32 [95% CI, 1.09-3.56] minutes).
UNASSIGNED: In this national cohort study of interhospital transfer of patients with AIS, delays in DIDO time by Black race, older age (≥80 years), and female sex were largely explained by the imaging-to-door period, suggesting that future systems interventions should target this interval to reduce these disparities. While existing guidelines and care resources heavily focus on reducing door-to-imaging times, further attention is warranted to reduce imaging-to-door times in the management of patients with AIS who require interhospital transfer.

OBJECTIVE: Endovascular reperfusion therapy (EVT) for acute ischemic stroke (AIS) with large vessel occlusion (LVO) has resulted in increased patient transfers to comprehensive stroke centers (CSCs). Clinical outcomes including the financial impact of these transfers from geographically dispersed population are lacking. Hence, we studied outcomes and cost-effectiveness of stroke transfers from remote areas.
METHODS: We used a 3-year cohort of AIS patients transferred from geographically dispersed counties (<100 mi., 101-200 mi., and >200 mi.). A 3-month modified Rankin scale (mRS) score of 0-2 defined a favorable clinical outcome. Cost-effectiveness is studied by calculating the incremental cost effectiveness ratio, using hospital costs reimbursed data and utility-weighted (UW)-mRS.
RESULTS: Among 172 patients transferred for EVT, patients transferred from nearby counties were more likely to undergo intervention compared to other counties (56.9 % vs. 36.7 % vs. 49.2 % p = .11). Irrespective of proximity (in mi.) to CSC [21.5 (14-56.3)] vs. 185 (137-185) vs. 349 (325-355)], there was a similar delay (in min.) to arrival from all locations [321.5 (244-490), 366 (298-432), and 460 (385-554.5) respectively], but no statistically significant differences in favorable outcomes (18.0 %, 34.1 %, and 22.2 %, respectively, p = .41). Patients undergoing EVT had higher hospital costs reimbursed compared to non-EVT patients [$37,303 (25,745-40,658) vs. $14,008 (8,640-21,273) respectively, p < .001] and no statistically significant difference in UW-mRS [0.32 (0.06-0.56) vs. 0.06 (0-0.56), p = .30].
CONCLUSIONS: Our study identifies a need for targeted interventions to improve community awareness and optimize systems of care to improve outcomes and cost-effectiveness of EVT.

BACKGROUND: The incongruity between the regional supply and demand of healthcare services is a persistent challenge both globally and in China. Patient mobility plays a pivotal role in addressing this issue. This study aims to delineate the cross-provincial inpatient mobility network (CIMN) in China and identify the underlying factors influencing this CIMN.
METHODS: We established China\'s CIMN by applying a spatial transfer matrix, utilizing the flow information from 5,994,624 cross-provincial inpatients in 2019, and identified the primary demand and supply provinces for healthcare services. Subsequently, we employed GeoDetector to analyze the impact of 10 influencing factors-including medical resources, medical quality, and medical expenses-on the spatial patterns of CIMN.
RESULTS: Beijing, Shanghai, Zhejiang, and Jiangsu provinces are the preferred medical destinations for cross-provincial inpatients, while Anhui, Henan, Hebei, and Jiangsu provinces are the main sources for cross-provincial inpatients. Patient flow between provinces decreases with distance. The spatial distribution of medical resources, medical quality, and medical expenses account for 87%, 73%, and 56% of the formation of CIMN, respectively. Additionally, interactions between these factors enhance explanatory power, suggesting that considering their interactions can more effectively optimize medical resources and services.
CONCLUSIONS: The analysis of CIMN reveals the supply and demand patterns of healthcare services, providing insights into the inequality characteristics of healthcare access. Furthermore, understanding the driving factors and their interactions offers essential evidence for optimizing healthcare services.

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OBJECTIVE: To describe the clinical trajectories of patients discharged directly from a critical unit to a postacute care facility.
METHODS: This was a retrospective cohort study of patients who were transferred from an intensive care unit or intermediate care unit to a postacute care facility between July 2017 and April 2023. Functional status was measured by the Functional Independence Measure score.
RESULTS: A total of 847 patients were included in the study, and the mean age was 71 years. A total of 692 (82%) patients were admitted for rehabilitation, while 155 (18%) were admitted for palliative care. The mean length of stay in the postacute care facility was 36 days; 389 (45.9%) patients were discharged home, 173 (20.4%) were transferred to an acute hospital, and 285 (33.6%) died during hospitalization, of whom 263 (92%) had a do-not-resuscitate order. Of the patients admitted for rehabilitation purposes, 61 (9.4%) had a worsened functional status, 179 (27.6%) had no change in functional status, and 469 (63%) had an improved functional status during hospitalization. Moreover, 234 (33.8%) patients modified their care goals to palliative care, most of whom were in the group that did not improve functional status. Patients whose functional status improved during hospitalization were younger, had fewer comorbidities, had fewer previous hospitalizations, had lower rates of enteral feeding and tracheostomy, had higher Functional Independence Measure scores at admission to the postacute care facility and were more likely to be discharged home with less complex health care assistance.
CONCLUSIONS: Postacute care facilities may play a role in the care of patients after discharge from intensive care units, both for those receiving rehabilitation and palliative care, especially for those with more severe illnesses who may not be discharged directly home.

BACKGROUND: To analyze the knowledge, abilities, and emotional state of cystic fibrosis patients during a specific follow-up period and compare this with the recall they had of the transition (planned and gradual shift from the pediatric unit) / transfer (direct change skipping the steps recommended by the guidelines) to a specialized cystic fibrosis adult unit.
METHODS: Prospective cross-sectional study with cystic fibrosis adult patients under follow-up in a specialist consultation. Group 1 were patients who transitioned and Group 2 were transferred patients. The following information was collected: sociodemographic variables, degree of knowledge, skills, and emotional state using a survey designed for this purpose (as part of the internal consistency validation process). Participants also completed the emotional subscale of Cystic Fibrosis Questionnaire-Revised. Inter-group comparisons were made for the transition/transfer, at the follow-up, and during the evolution.
RESULTS: Thirty-five patients were analyzed; 65.8% male; mean age 31.9 years (SD =10.1). At the transition, Group 1 (n=19; 54.3%) had greater knowledge about their medication and reduced ability to manage appointments and making decisions in comparison to Group 2 at transfer. At follow-up, Group 1 made a better report on their emotional state and significantly improved their ability to manage appointments, communication, and decision-making.
CONCLUSIONS: Patients who were moved to an adult cystic fibrosis unit through transition were more knowledgeable about their medications. However, those who were transferred managed their appointments and decision-making better, but felt sadder.

Background: National Personal Health Records (PHRs) have been proposed to improve the transfer of medication-related information during transition of care. Objective: To evaluate the concordance between the medications captured in the Australian national PHR, My Health Record (MyHR), and the pharmacist obtained best possible medication history (BPMH) for patients upon hospital admission. Method: This prospective observational study used a convenience sample of hospital patients. For newly admitted patients, the investigating pharmacist obtained a BPMH and then compared it to the medication list captured in MyHR. Upon comparison, the medications were categorised into either complete match, partial match or mismatch. Medications with a complete or partial match were grouped together. Medications with deviations were then assessed for risk based on their potential consequence, and reported descriptively. A multivariable logistic regression was conducted to assess the factors associated with a drug being mismatched. Results: A total of 82 patients were recruited, with a cumulative total of 1,207 medications documented. Of the 1,207 medications, 714 (59.2%) medications were documented as a complete/partial match. The remaining 493 (40.8%) medications were mismatched. Of the 493 mismatched medications, 442 (89.7%) were deemed low-risk deviations and 51 (10.3%) were deemed high-risk. A medication was more likely to be mismatched, rather than completely/partially matched, if it was a regular non-prescription medication, or \"when-required\" prescription medication, or \"when required\" non-prescription medication, or if it was administered parenterally. Conclusion: National PHRs may be a secondary source to either confirm a patient\'s medication history or be used as a starting point for a BPMH.