Interhospital transfers among Medicare beneficiaries admitted for acute myocardial infarction at nonrevascularization hospitals

Network analysis of stroke systems of care in Korea

Background

The landscape of stroke care has shifted from stand-alone hospitals to cooperative networks among hospitals. Despite the importance of these networks, limited information exists on their characteristics and functional attributes.

Methods

We extracted patient-level data on acute stroke care and hospital connectivity by integrating national stroke audit data with reimbursement claims data. We then used this information to transform interhospital transfers into a network framework, where hospitals were designated as nodes and transfers as edges. Using the Louvain algorithm, we grouped densely connected hospitals into distinct stroke care communities. The quality and characteristics in given stroke communities were analysed, and their distinct types were derived using network parameters. The clinical implications of this network model were also explored.

Results

Over 6 months, 19 113 patients with acute ischaemic stroke initially presented to 1009 hospitals, with 3114 (16.3%) transferred to 246 stroke care hospitals. These connected hospitals formed 93 communities, with a median of 9 hospitals treating a median of 201 patients. Derived communities demonstrated a modularity of 0.904 , indicating a strong community structure, highly centralised around one or two hubs. Three distinct types of structures were identified: single-hub (n=60), double-hub (n=22) and hubless systems (n=11). The endovascular treatment rate was highest in double-hub systems, followed by single-hub systems, and was almost zero in hubless systems. The hubless communities were characterised by lower patient volumes, fewer hospitals, no hub hospital and no stroke unit.

Conclusions

This network analysis could quantify the national stroke care system and point out areas where the organisation and functionality of acute stroke care could be improved.

Multi-Institution Survey of Accepting Physicians' Perception of Appropriate Reasons for Interhospital Transfer: A Mixed-Methods Evaluation

OBJECTIVES

There is a lack of evidence-based guidelines to direct best practices in interhospital transfers (IHTs). We aimed to identify frontline physicians' current and ideal reasons for accepting IHT patients to inform future IHT research and guidelines.

METHODS

We conducted a cross-sectional survey of hospitalist physicians across 11 geographically diverse hospitals. The survey asked respondents how frequently they currently consider and should consider various factors when triaging IHT requests. Responses were dichotomized into "highly considered" and "less considered" factors. Frequencies of the "highly considered" factors (current and ideal) were analyzed. Write-in responses were coded into themes within a priori domains in a qualitative analysis.

RESULTS

Of the 666 hospitalists surveyed, 238 (36%) responded. Respondents most frequently identified the need for specialty procedural and nonprocedural care and bed capacity as factors that should be considered when triaging IHT patients in current and ideal practice, whereas the least frequently considered factors were COVID-related care, insurance/financial considerations, and patient/family preference. More experienced respondents considered patient/family preference more frequently in current and ideal practice compared with less experienced respondents (33% versus 11% [ P = 0.0001] and 26% versus 9% [ P = 0.01], respectively). Qualitative analysis identified several themes in the domains of Criteria for Acceptance, Threshold for Acceptance, and Indications for Physician-to-Physician Communication.

CONCLUSIONS

This geographically diverse sample of hospitalist physicians responsible for accepting IHT patients showed general agreement between primary factors that are currently and that should be considered for IHT acceptance, with greatest weight placed on patients' need for specialty care.

Racial and ethnic disparities in emergency department transfers to public hospitals

OBJECTIVE

To examine racial/ethnic differences in emergency department (ED) transfers to public hospitals and factors explaining these differences.

DATA SOURCES AND STUDY SETTING

ED and inpatient data from the Healthcare Cost and Utilization Project for Florida (2010-2019); American Hospital Association Annual Survey (2009-2018).

STUDY DESIGN

Logistic regression examined race/ethnicity and payer on the likelihood of transfer to a public hospital among transferred ED patients. The base model was controlled for patient and hospital characteristics and year fixed effects. Models II and III added urbanicity and hospital referral region (HRR), respectively. Model IV used hospital fixed effects, which compares patients within the same hospital. Models V and VI stratified Model IV by payer and condition, respectively. Conditions were classified as emergency care sensitive conditions (ECSCs), where transfer is protocolized, and non-ECSCs. We reported marginal effects at the means.

DATA COLLECTION/EXTRACTION METHODS

We examined 1,265,588 adult ED patients transferred from 187 hospitals.

PRINCIPAL FINDINGS

Black patients were more likely to be transferred to public hospitals compared with White patients in all models except ECSC patients within the same initial hospital (except trauma). Black patients were 0.5-1.3 percentage points (pp) more likely to be transferred to public hospitals than White patients in the same hospital with the same payer. In the base model, Hispanic patients were more likely to be transferred to public hospitals compared with White patients, but this difference reversed after controlling for HRR. Hispanic patients were - 0.6 pp to -1.2 pp less likely to be transferred to public hospitals than White patients in the same hospital with the same payer.

CONCLUSIONS

Large population-level differences in whether ED patients of different races/ethnicities were transferred to public hospitals were largely explained by hospital market and the initial hospital, suggesting that they may play a larger role in explaining differences in transfer to public hospitals, compared with other external factors.

Investigating racial and ethnic disparities in interhospital transfer within an academic integrated healthcare system: A matched cohort study

The presence of racial and ethnic disparities in interhospital transfer (IHT) within integrated healthcare systems has not been fully explored. We matched Black and Latinx patients admitted to community hospitals in our integrated healthcare system between June 2015 and December 2019 to White patients by origin hospital, age, time of year, and disease severity. We performed conditional logistic regression models to determine if race or ethnicity was associated with IHT in one of the tertiary academic medical centers in the system, adjusting for covariates. The sample contained 107,895 admissions (82.6% White, 7.8% Black, and 9.6% Latinx). Transfer rates were 2.2% versus 2.2% after the Black/White match and 1.8% versus 1.8% after the Latinx/White match. After adjusting for covariates, there was no association between race or ethnicity and IHT (Black vs. White odds ratio [OR]: 0.87, 95% confidence interval [CI]: 0.72-1.07; Latinx vs. White OR: 1.05, 95% CI: 0.79-1.40). This may be due to reduced barriers to transfer with an integrated healthcare system.

Initial treatment of uninsured patients with ST-elevation myocardial infarction by facility percutaneous coronary intervention capabilities

BACKGROUND

Timely reperfusion is necessary to reduce morbidity and mortality in patients with ST-elevation myocardial infarction (STEMI). Initial care by facilities with percutaneous coronary intervention (PCI) capabilities reduces time to reperfusion. We sought to examine whether insurance status was associated with initial care at emergency departments (EDs) with PCI capabilities among adult patients with STEMI.

METHODS

We conducted a retrospective cross-sectional study using Department of Healthcare Access and Information, a nonpublic statewide database reporting ED visits and hospitalizations in California. We included adults initially arriving at EDs with STEMI by diagnostic code (International Classification of Diseases Ninth Revision or 10th Revision) from 2011 to 2019. Multivariable logistic regression modeling included initial care by PCI capable facility as the primary outcome and insurance status (none vs. any) as the primary exposure. Covariates included patient, facility, and temporal factors and we conducted multiple robustness checks.

RESULTS

We analyzed 135,358 eligible visits with STEMI included. In our multivariable model, the odds of uninsured patients being initially treated at a PCI-capable facility were significantly lower than those of insured patients (adjusted odds ratio 0.62, 95% CI 0.54-0.72, p < 0.001) and was unchanged in sensitivity analyses.

CONCLUSIONS

Uninsured patients with STEMI had significantly lower odds of first receiving care at facilities with PCI capabilities. Our results suggest potential disparities in accessing high-quality and time-sensitive treatment for uninsured patients with STEMI.

Advancing health information during interhospital transfer: An interrupted time series

INTRODUCTION

Although the transfer of patients between acute care hospitals (interhospital transfer, IHT) is common, health information exchange (HIE) during IHT remains inadequate, with fragmented communication and unreliable access to clinical information. This study aims to design, implement, and rigorously evaluate the implementation of a HIE platform to improve data access during IHT.

METHODS AND ANALYSIS

Study subjects include patients aged >18 transferred to the medical, cardiology, oncology, or intensive care unit (ICU) services at an 800-bed quaternary care hospital; and healthcare workers involved in their care. The first aim of this study is to optimize clinician workflow, data visualization, and interoperability through user-centered design sessions for HIE platform development. The second aim is to evaluate the impact of the intervention on clinician-reported medical errors among 500 pre- and 500 postintervention IHT patients using interrupted time series methodology, adjusting for confounding variables and temporal trends. The third aim is to evaluate intervention fidelity, use and perceived usability of the platform, and barriers and facilitators of implementation from interprofessional stakeholder input, using mixed-methods evaluation. The fourth aim is to consolidate key findings to create a toolkit for spread and sustainability.

ETHICS AND DISSEMINATION

We will track patient safety endpoints and clinician workflow burdens and ensure the protection of patient data throughout the study. We will disseminate our findings via the creation of a toolkit for spread and sustainability, partnering with our funder (AHRQ) for dissemination, and communicating our results via abstracts and publications.

Pediatric Patient Insurance Status and Regionalization of Admissions

BACKGROUND

Pediatric hospital care is becoming increasingly regionalized, and previous data have suggested that insurance may be associated with transfer. The aims of the study are to describe regionalization of pediatric care and density of the interhospital transfer network and to determine whether these varied by insurance status.

METHODS

Using the New York State ED Database and State Inpatient Database from 2016, we identified all pediatric patients and calculated regionalization indices (RI) and network density, overall and stratified by insurance. Regionalization indices are based on the likelihood of a patient completing care at the initial hospital. Network density is the proportion of actual transfers compared with the number of potential hospital transfer connections. Both were calculated using the standard State ED Database/State Inpatient Database transfer definition and in a sensitivity analysis, excluding the disposition code requirement.

RESULTS

We identified 1,595,566 pediatric visits (emergency department [ED] or inpatient) in New York in 2016; 7548 (0.5%) were transferred and 7374 transferred visits had eligible insurance status (Medicaid, private, uninsured). Of the transfers, 24% were from ED to ED with discharge, 28% from ED to ED with admission, 31% from ED to inpatient, 16% from inpatient to inpatient, and 1.2% from inpatient to ED. The overall RI was 0.25 (95% confidence interval [95% CI], 0.20-0.31). The overall weighted RI was 0.09 (95% CI, 0.06-0.12) and was 0.09 (95% CI, 0.06-0.13) for Medicaid-insured patients, 0.08 (95% CI, 0.05-0.11) for privately insured patients, and 0.08 (95% CI, 0.05-0.11) for patients without insurance. The overall network density was 0.018 (95% CI, 0.017-0.020). Network density was higher, and transfer rates were lower, for patients with Medicaid insurance as compared with private insurance.

CONCLUSIONS

We found significant regionalization of pediatric emergency care. Although there was not material variation by insurance in regionalization, there was variation in network density and transfer rates. Additional work is needed to understand factors affecting transfer decisions and how these patterns might vary by state.

Implementation of a standardised accept note to improve communication during inter-hospital transfer: a prospective cohort study

IMPORTANCE

The transfer of patients between hospitals (interhospital transfer, IHT), exposes patients to communication errors and gaps in information exchange.

OBJECTIVE

To design and implement a standardised accept note to improve communication during medical service transfers, and evaluate its impact on patient outcomes.

DESIGN

Prospective interventional cohort study.

SETTING

A 792-bed tertiary care hospital.

PARTICIPANTS

All patient transfers from any acute care hospital to the general medicine, cardiology, oncology and intensive care unit (ICU) services between August 2020 and June 2022.

INTERVENTIONS

A standardised accept note template was developed over a 9-month period with key stakeholder input and embedded in the electronic health record, completed by nurses within the hospital's Access Centre.

MAIN OUTCOMES AND MEASURES

Primary outcome was clinician-reported medical errors collected via surveys of admitting clinicians within 72 hours after IHT patient admission. Secondary outcomes included clinician-reported failures in communication; presence and 'timeliness' of accept note documentation; patient length of stay (LOS) after transfer; rapid response or ICU transfer within 24 hours and in-hospital mortality. All outcomes were analysed postintervention versus preintervention, adjusting for patient demographics, diagnosis, comorbidity, illness severity, admitting service, time of year, hospital COVID census and census of admitting service and admitting team on date of admission.

RESULTS

Of the 1004 and 654 IHT patients during preintervention and postintervention periods, surveys were collected on 735 (73.2%) and 462 (70.6%), respectively. Baseline characteristics were similar among patients in each time period and between survey responders and non-responders. Adjusted analyses demonstrated a 27% reduction in clinician-reported medical error rates postimplementation versus preimplementation (11.5 vs 15.8, adjusted OR (aOR) 0.73, 95% CI 0.53 to 0.99). Secondary outcomes demonstrated lower adjusted odds of clinician-reported failures in communication (aOR 0.88; 0.78 to 0.98) and rapid response/ICU transfer (aOR 0.57; 0.34 to 0.97), and improved presence (aOR 2.30; 1.75 to 3.02) and timeliness (-21.4 hours vs -8.7 hours, p<0.001) of accept note documentation. There were no significant differences in LOS or mortality.

CONCLUSIONS AND RELEVANCE

Among 1658 medical patient transfers, implementing a standardised accept note was associated with improved presence and timeliness of accept note documentation, clinician-reported medical errors, failures in communication and clinical decline following transfer, suggesting that improving communication during IHT can improve patient outcomes.

A Conceptual Framework for Optimizing the Equity of Hospital-Based Emergency Care: The Structure of Hospital Transfer Networks

Policy Points Current pay-for-performance and other payment policies ignore hospital transfers for emergency conditions, which may exacerbate disparities. No conceptual framework currently exists that offers a patient-centered, population-based perspective for the structure of hospital transfer networks. The hospital transfer network equity-quality framework highlights the external and internal factors that determine the structure of hospital transfer networks, including structural inequity and racism.

CONTEXT

Emergency care includes two key components: initial stabilization and transfer to a higher level of care. Significant work has focused on ensuring that local facilities can stabilize patients. However, less is understood about transfers for definitive care. To better understand how transfer network structure impacts population health and equity in emergency care, we proposea conceptual framework, the hospital transfer network equity-quality model (NET-EQUITY). NET-EQUITY can help optimize population outcomes, decrease disparities, and enhance planning by supporting a framework for understanding emergency department transfers.

METHODS

To develop the NET-EQUITY framework, we synthesized work on health systems and quality of health care (Donabedian, the Institute of Medicine, Ferlie, and Shortell) and the research framework of the National Institute on Minority Health and Health Disparities with legal and empirical research.

FINDINGS

The central thesis of our framework is that the structure of hospital transfer networks influences patient outcomes, as defined by the Institute of Medicine, which includes equity. The structure of hospital transfer networks is shaped by internal and external factors. The four main external factors are the regulatory, economic environment, provider, and sociocultural and physical/built environment. These environments all implicate issues of equity that are important to understand to foster an equitable population-based system of emergency care. The framework highlights external and internal factors that determine the structure of hospital transfer networks, including structural racism and inequity.

CONCLUSIONS

The NET-EQUITY framework provides a patient-centered, equity-focused framework for understanding the health of populations and how the structure of hospital transfer networks can influence the quality of care that patients receive.

Association of Physician Coordination With Interfacility Transfer Acceptance Timeliness

Objectives

Interfacility transfer for time-sensitive emergencies involves rapid and complex care transitions between facilities. We sought to validate relational coordination, a 7-dimension measure of coordination in which a higher score reflects higher-quality coordination, to examine how the quality of coordination affects timeliness in an emergency care setting.

Study Design

Retrospective observational cohort design.

Methods

We used a novel method to examine how the quality of coordination between physicians at the time of transfer affects timeliness of physician acceptance. We recorded physician-to-physician conversations from the transfer of patients with ST-segment elevation myocardial infarction (STEMI), a time-sensitive emergency requiring immediate intervention to prevent morbidity and mortality.

Results

We identified 81 patients experiencing STEMI who were transferred between August 1, 2016, and March 31, 2018. Descriptive statistics, interrater reliability (Spearman correlation coefficients), and generalized linear models were used to examine the association between relational coordination and the physician time-to-acceptance duration. Median (IQR) relational coordination score was 445 (403-493) of a maximum of 700, and median (IQR) time to acceptance was 90.4 (60.2-140.8) seconds. Agreement between abstractors was high (ρ = 0.76). There was a significant, negative relationship between relational coordination and time to acceptance (ρ = -0.38; P < .001). Every 40-point increase in relational coordination was associated with a 25% reduction in time to acceptance.

Conclusions

Relational coordination not only demonstrated high interrater reliability, but we also found that higher-quality coordination was associated with faster physician acceptance during time-sensitive transfers. Use of such measures may provide a mechanism to improve the quality of care and outcomes for patients with STEMI who experience interfacility transfers.

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

BACKGROUND

Patients with stroke are frequently transferred between hospitals. This may have implications on the quality of care received by patients; however, it is not well understood how the characteristics of sending and receiving hospitals affect the likelihood of a transfer event. Our objective was to identify hospital characteristics associated with sending and receiving patients with stroke.

METHODS

Using a comprehensive statewide administrative dataset, including all 78 Massachusetts hospitals, we identified all transfers of patients with ischemic stroke between October 2007 and September 2015 for this observational study. Hospital variables included reputation (US News and World Report ranking), capability (stroke center status, annual stroke volume, and trauma center designation), and institutional affiliation. We included network variables to control for the structure of hospital-to-hospital transfers. We used relational event modeling to account for complex temporal and relational dependencies associated with transfers. This method decomposes a series of patient transfers into a sequence of decisions characterized by transfer initiations and destinations, modeling them using a discrete-choice framework.

RESULTS

Among 73 114 ischemic stroke admissions there were 7189 (9.8%) transfers during the study period. After accounting for travel time between hospitals and structural network characteristics, factors associated with increased likelihood of being a receiving hospital (in descending order of relative effect size) included shared hospital affiliation (5.8× higher), teaching hospital status (4.2× higher), stroke center status (4.3× and 3.8× higher when of the same or higher status), and hospitals of the same or higher reputational ranking (1.5× higher).

CONCLUSIONS

After accounting for distance and structural network characteristics, in descending order of importance, shared hospital affiliation, hospital capabilities, and hospital reputation were important factor in determining transfer destination of patients with stroke. This study provides a starting point for future research exploring how relational coordination between hospitals may ensure optimized allocation of patients with stroke for maximal patient benefit.

Patient and Physician Experience with Interhospital Transfer: A Qualitative Study

OBJECTIVES

Although existing data suggest marked variability in interhospital transfer (IHT), little is known about specific factors that may impact the quality and safety of this care transition. We aimed to explore transferred patients' and involved physicians' experience with IHT to better understand the components of the transfer continuum and identify potential targets for improvement.

METHODS

We performed a qualitative study using individual interviews of adult patients recently transferred to cardiology, general medicine, and oncology services at a tertiary care academic medical center, as well as their transferring physician, accepting attending physician, and accepting/admitting resident physician. We conducted a thematic analysis, using an inductive approach and an a priori framework from pre-established domains.

RESULTS

Participants included 10 hospitalized adults (6 cardiology, 2 general medicine, and 2 oncology), 9 accepting attending physicians, 12 accepting and/or admitting resident physicians, and 5 transferring physicians (N = 36). Emergent themes demonstrated that participants held a shared understanding of the reason for transfer (most commonly access to more specialized care), and relayed a general dissatisfaction regarding the timing and lack of advanced notification of transfer. We also found distinct differences in IHT experience by stakeholder group: physician participants relayed discontent with intrahospital chains of communication and interhospital information exchange, and patient participants focused more readily on the physical aspects of IHT.

CONCLUSIONS

This study offers insight into IHT from the perspective of those most affected by this process, thereby identifying potential targets in addressing the quality and safety of this transition.

Assessment of Hospital Characteristics and Interhospital Transfer Patterns of Adults With Emergency General Surgery Conditions

IMPORTANCE

Although patients with emergency general surgery (EGS) conditions frequently undergo interhospital transfers, the transfer patterns and associated factors are not well understood.

OBJECTIVE

To examine whether patients with EGS conditions are consistently directed to hospitals with more resources and better outcomes.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study performed a network analysis of interhospital transfers among adults with EGS conditions from January 1 to December 31, 2016. The analysis used all-payer claims data from the 2016 Healthcare Cost and Utilization Project state inpatient and emergency department databases in 8 states. A total of 728 hospitals involving 85 415 transfers of 80 307 patients were included. Patients were eligible for inclusion if they were 18 years or older and had an acute care hospital encounter with a diagnosis of an EGS condition as defined by the American Association for the Surgery of Trauma. Data were analyzed from January 1, 2020, to June 17, 2021.

EXPOSURES

Hospital-level measures of size (total bed capacity), resources (intensive care unit [ICU] bed capacity, teaching status, trauma center designation, and presence of trauma and/or surgical critical care fellowships), EGS volume (annual EGS encounters), and EGS outcomes (risk-adjusted failure to rescue and in-hospital mortality).

MAIN OUTCOMES AND MEASURES

The main outcome was hospital-level centrality ratio, defined as the normalized number of incoming transfers divided by the number of outgoing transfers. A higher centrality ratio indicated more incoming transfers per outgoing transfer. Multivariable regression analysis was used to test the hypothesis that a higher hospital centrality ratio would be associated with more resources, higher volume, and better outcomes.

RESULTS

Among 80 307 total patients, the median age was 63 years (interquartile range [IQR], 50-75 years); 52.1% of patients were male and 78.8% were White. The median number of outgoing and incoming transfers per hospital were 106 (IQR, 61-157) and 36 (IQR, 8-137), respectively. A higher log-transformed centrality ratio was associated with more resources, such as higher ICU capacity (eg, >25 beds vs 0-10 beds: β = 1.67 [95% CI, 1.16-2.17]; P < .001), and higher EGS volume (eg, quartile 4 [highest] vs quartile 1 [lowest]: β = 0.78 [95% CI, 0-1.57]; P = .01). However, a higher log-transformed centrality ratio was not associated with better outcomes, such as lower in-hospital mortality (eg, quartile 4 [highest] vs quartile 1 [lowest]: β = 0.30 [95% CI, -0.09 to 0.68]; P = .83) and lower failure to rescue (eg, quartile 4 [highest] vs quartile 1 [lowest]: β = -0.50 [95% CI, -1.13 to 0.12]; P = .27).

CONCLUSIONS AND RELEVANCE

In this study, EGS transfers were directed to high-volume hospitals with more resources but were not necessarily directed to hospitals with better clinical outcomes. Optimizing transfer destination in the interhospital transfer network has the potential to improve EGS outcomes.

Defining Best Practices for Interhospital Transfers

INTRODUCTION

Interhospital transfers (IHT) are important yet high-risk transitions in care. Variable IHT processes and a lack of clarity around best practice may contribute to risk. To define the best practice principles for IHTs and identify improvement opportunities in the transfer process to our hospital's Cardiology services.

METHODS

Through literature review, interviews with experts and key stakeholders, a survey of health care professionals at our institution, and a failure modes effect analysis, we identified themes in IHT best practices and improvement opportunities.

RESULTS

We identified six critical elements of IHT: (1) initiation of transfer request; (2) the management of transfer request and information exchange; (3) updates between transfer acceptance and patient transport; (4) transport; (5) patient admission and information availability; and (6) measurement, evaluation, and feedback. Improvement opportunities were found in all elements.

CONCLUSIONS

The standardization of these six critical elements may improve the safety of IHTs.

The Prevalence and Emergency Department Utilization of Patients Who Underwent Single and Double Inter-hospital Transfers in the Emergency Department: a Nationwide Population-based Study in Korea, 2016-2018

BACKGROUND

Inter-hospital transfer (IHT) for emergency department (ED) admission is a burden to high-level EDs. This study aimed to evaluate the prevalence and ED utilization patterns of patients who underwent single and double IHTs at high-level EDs in South Korea.

METHODS

This nationwide cross-sectional study analyzed data from the National Emergency Department Information System for the period of 2016-2018. All the patients who underwent IHT at Level I and II emergency centers during this time period were included. The patients were categorized into the single-transfer and double-transfer groups. The clinical characteristics and ED utilization patterns were compared between the two groups.

RESULTS

We found that 2.1% of the patients in the ED (n = 265,046) underwent IHTs; 18.1% of the pediatric patients (n = 3,556), and 24.2% of the adult patients (n = 59,498) underwent double transfers. Both pediatric (median, 141.0 vs. 208.0 minutes, P < 0.001) and adult (median, 189.0 vs. 308.0 minutes, P < 0.001) patients in the double-transfer group had longer duration of stay in the EDs. Patient's request was the reason for transfer in 41.9% of all IHTs (111,076 of 265,046). Unavailability of medical resources was the reason for transfer in 30.0% of the double transfers (18,920 of 64,054).

CONCLUSION

The incidence of double-transfer of patients is increasing. The main reasons for double transfers were patient's request and unavailability of medical resources at the first-transfer hospitals. Emergency physicians and policymakers should focus on lowering the number of preventable double transfers.

The association of Medicaid expansion and racial/ethnic inequities in access, treatment, and outcomes for patients with acute myocardial infarction

Introduction

After having an acute myocardial infarction (AMI), racial and ethnic minorities have less access to care, decreased rates of invasive treatments such as percutaneous coronary intervention (PCI), and worse outcomes compared with white patients. The objective of this study was to determine whether the Affordable Care Act’s expansion of Medicaid eligibility was associated with changes in racial disparities in access, treatments, and outcomes after AMI.

Methods

Quasi-experimental, difference-in-differences-in-differences analysis of non-Hispanic white and minority patients with acute myocardial infarction in California and Florida from 2010–2015, using linear regression models to estimate the difference-in-differences. This population-based sample included all Medicaid and uninsured patients ages 18–64 hospitalized with acute myocardial infarction in California, which expanded Medicaid through the Affordable Care Act beginning as early as July 2011 in certain counties, and Florida, which did not expand Medicaid. The main outcomes included rates of admission to hospitals capable of performing PCI, rates of transfer for patients who first presented to hospitals that did not perform PCI, rates of PCI during hospitalization and rates of early (within 48 hours of admission) PCI, rates of readmission to the hospital within 30 days, and rates of in-hospital mortality.

Results

A total of 55,991 hospital admissions met inclusion criteria, 32,540 of which were in California and 23,451 were in Florida. Among patients with AMI who initially presented to a non-PCI hospital, the likelihood of being transferred increased by 12 percentage points (95% CI 2 to 21) for minority patients relative to white patients after the Medicaid expansion. The likelihood of undergoing PCI increased by 3 percentage points (95% CI 0 to 5) for minority patients relative to white patients after the Medicaid expansion. We did not find an association between the Medicaid expansion and racial disparities in overall likelihood of admission to a PCI hospital, hospital readmissions, or in-hospital mortality.

Conclusions

The Medicaid expansion was associated with a decrease in racial disparities in transfers and rates of PCI after AMI. We did not find an association between the Medicaid expansion and admission to a PCI hospital, readmissions, and in-hospital mortality. Additional factors outside of insurance coverage likely continue to contribute to disparities in outcomes after AMI. These findings are crucial for policy makers seeking to reduce racial disparities in access, treatment and outcomes in AMI.

Optimizing Safety for Surgical Patients Undergoing Interhospital Transfer

Interhospital transfers play a key role in ensuring that patients receive necessary care. However, patients who are transferred between hospitals are a vulnerable population, and outcomes of transferred patients are suboptimal. Despite the critical nature of interhospital transfers, only limited effort has been dedicated to standardization and improvement of the transfer process. Studying and adapting quality improvement efforts directed at other transitions of care, particularly those that cross between different facilities and care teams "such as the transition from hospital to home or extended care facilities" may improve the care of surgical patients transferred between acute care institutions.

Identifying Racial/Ethnic Disparities in Interhospital Transfer: an Observational Study

BACKGROUND

Interhospital transfer (IHT) is often performed to provide patients with specialized care. Racial/ethnic disparities in IHT have been suggested but are not well-characterized.

OBJECTIVE

To evaluate the association between race/ethnicity and IHT.

DESIGN

Cross-sectional analysis of 2016 National Inpatient Sample data.

PATIENTS

Patients aged ≥ 18 years old with common medical diagnoses at transfer, including acute myocardial infarction, congestive heart failure, arrhythmia, stroke, sepsis, pneumonia, and gastrointestinal bleed.

MAIN MEASURES

We performed a series of logistic regression models to estimate adjusted odds of transfer by race/ethnicity controlling for patient demographics, clinical variables, and hospital characteristics and to identify potential mediators. In secondary analyses, we estimated adjusted odds of transfer among patients at community hospitals (those more likely to transfer patients) and performed subgroup analyses by region and primary medical diagnosis.

KEY RESULTS

Of 5,774,175 weighted hospital admissions, 199,015 (4.5%) underwent IHT, including 4.7% of White patients, compared with 3.9% of Black patients and 3.8% of Hispanic patients. Black (OR 0.83, 95% CI 0.78-0.89) and Hispanic (OR 0.81, 95% CI 0.75-0.87) patients had lower crude odds of transfer compared with White patients, but this became non-significant after adjusting for hospital-level characteristics. In secondary analyses among patients hospitalized at community hospitals, Hispanic patients had lower adjusted odds of transfer (aOR 0.89, 95% CI 0.79-0.98). Disparities in IHT by race/ethnicity varied by region and medical diagnosis.

CONCLUSIONS

Black and Hispanic patients had lower odds of IHT, largely explained by a higher likelihood of being hospitalized at urban teaching hospitals. Racial/ethnic disparities in transfer were demonstrated at community hospitals, in certain geographic regions and among patients with specific diseases.

Dealing with the Sick Rural Surgery Patient in Need of Transfer

Care for rural and urban surgical patients is increasingly more complex due to advancing knowledge and technology. Interhospital transfers occur in approximately 10% of index encounters at rural hospitals secondary to mismatch of patient needs and local resources. Due to the recent expansion of air transport to rural areas, distance and geography are less of a barrier. The interhospital transfer process is understudied and far from standardized. Interhospital transfer status is associated with increase in mortality, complications, length of stay, and costs. The cost, price to patients, and safety of air ambulance transports cannot be ignored.

Rural Interfacility Emergency Department Transfers: Framework and Qualitative Analysis

Introduction

Interfacility transfers from rural emergency departments (EDs) are an important means of access to timely and specialized care.

Methods

Our goal was to identify and explore facilitators and barriers in transfer processes and their implications for emergency rural care and access. Semi-structured interviews with ED staff at five rural and two urban Veterans Health Administration (VHA) hospitals were recorded, transcribed, coded, and analyzed using an iterative inductive-deductive approach to identify themes and construct a conceptual framework.

Results

From 81 interviews with clinical and administrative staff between March–June 2018, four themes in the interfacility transfer process emerged: 1) patient factors; 2) system resources; and 3) processes and communication for transfers, which culminate in 4) the location decision. Current and anticipated resource limitations were highly influential in transfer processes, which were described as burdensome and diverting resources from clinical care for emergency patients. Location decision was highly influenced by complexity of the transfer process, while perceived quality at the receiving location or patient preferences were not reported in interviews as being primary drivers of location decision. Transfers were described as burdensome for patients and their families. Finally, patients with mental health conditions epitomized challenges of emergency transfers.

Conclusion

Interfacility transfers from rural EDs are multifaceted, resource-driven processes that require complex coordination. Anticipated resource needs and the transfer process itself are important determinants in the location decision, while quality of care or patient preferences were not reported as key determinants by interviewees. These findings identify potential benefits from tracking transfer boarding as an operational measure, directed feedback regarding outcomes of transferred patients, and simplified transfer processes.

Association between Hospital volume of cardiopulmonary resuscitation for in-hospital cardiac arrest and survival to Hospital discharge

BACKGROUND

Prior studies have shown that hospital case volume is not associated with survival in patients with out-of-hospital cardiac arrest (OHCA). However, how case volume impact on survival for in-hospital cardiac arrest (IHCA) is unknown.

METHODS

We queried the National Inpatient Sample (NIS) in the U.S. 2005-2011 to identify cases in which in-hospital CPR was performed for IHCA. Restricted cubic spine was used to evaluate the association between hospital annual CPR volume and survival to hospital discharge.

RESULTS

Across more than 1000 hospitals in NIS, we identified 125,082 cases (mean age 67, 45% female) of IHCA for which CPR was performed over the study period. Median [Q1, Q3] case volume was 60 [34, 99]. Compared to those in the 1 st quartile of case volume, hospitals in the 4th quartile tends to have younger patients (mean = 66 vs 68 yrs), higher comorbidities (median Elixhauser score = 4 vs 3), and in low income areas (37 vs 30%). Overall, 23% of the patients survived to hospital discharge. There was a non-linear association between CPR volume and survival: a non-significant trend towards better survival was observed with increasing annual CPR volume that reached a plateau at 51-55 cases per year, after which survival began to drop and became significantly lower after 75 cases per year (p for non-linearity<0.001). Compared to those in first quartile of case volume, hospitals in 4^th quartile had higher length of stay (median = 8 vs 10 days, respectively) and higher rate of non-routine home discharge (64% vs 67%) among those who survived.

CONCLUSION

Unlike OHCA, low CPR volume is an indicator of good performing hospitals and increasing CPR case volume does not translate to improve survival for IHCA.

Hospital Factors Associated With Interhospital Transfer Destination for Stroke in the Northeast United States

Background

We aimed to determine if there is an association between hospital quality and the likelihood of a given hospital being a preferred transfer destination for stroke patients.

Methods and Results

Data from Medicare claims identified acute ischemic stroke transferred between 394 northeast US hospitals from 2007 to 2011. Hospitals were categorized as transferring (n=136), retaining (n=241), or receiving (n=17) hospitals based on the proportion of acute ischemic stroke encounters transferred or received. We identified all 6409 potential dyads of sending and receiving hospitals, and categorized dyads as connected if ≥5 patients were transferred between the hospitals annually (n=82). We used logistic regression to identify hospital characteristics associated with establishing a connected dyad, exploring the effect of adjusting for different quality measures and outcomes. We also adjusted for driving distance between hospitals, receiving hospital stroke volume, and the number of hospitals in the receiving hospital referral region. The odds of establishing a transfer connection increased when rate of alteplase administration increased at the receiving hospital or decreased at the sending hospital, however this finding did not hold after applying a potential strategy to adjust for clustering. Receiving hospital performance on 90‐day home time was not associated with likelihood of transfer connection.

Conclusions

Among northeast US hospitals, we found that differences in hospital quality, specifically higher levels of alteplase administration, may be associated with increased likelihood of being a transfer destination. Further research is needed to better understand acute ischemic stroke transfer patterns to optimize stroke transfer systems.

Inter-hospital transfer and patient outcomes: a retrospective cohort study

BACKGROUND

Inter-hospital transfer (IHT, the transfer of patients between hospitals) occurs regularly and exposes patients to risks of discontinuity of care, though outcomes of transferred patients remains largely understudied.

OBJECTIVE

To evaluate the association between IHT and healthcare utilisation and clinical outcomes.

DESIGN

Retrospective cohort.

SETTING

CMS 2013 100 % Master Beneficiary Summary and Inpatient claims files merged with 2013 American Hospital Association data.

PARTICIPANTS

Beneficiaries≥age 65 enrolled in Medicare A and B, with an acute care hospitalisation claim in 2013 and 1 of 15 top disease categories.

MAIN OUTCOME MEASURES

Cost of hospitalisation, length of stay (LOS) (of entire hospitalisation), discharge home, 3 -day and 30- day mortality, in transferred vs non-transferred patients.

RESULTS

The final cohort consisted of 53 420 transferred patients and 53 420 propensity-score matched non-transferred patients. Across all 15 disease categories, IHT was associated with significantly higher costs, longer LOS and lower odds of discharge home. Additionally, IHT was associated with lower propensity-matched odds of 3-day and/or 30- day mortality for some disease categories (acute myocardial infarction, stroke, sepsis, respiratory disease) and higher propensity-matched odds of mortality for other disease categories (oesophageal/gastrointestinal disease, renal failure, congestive heart failure, pneumonia, renal failure, chronic obstructivepulmonary disease, hip fracture/dislocation, urinary tract infection and metabolic disease).

CONCLUSIONS

In this nationally representative study of Medicare beneficiaries, IHT was associated with higher costs, longer LOS and lower odds of discharge home, but was differentially associated with odds of early death and 30 -day mortality depending on patients' disease category. These findings demonstrate heterogeneity among transferred patients depending on the diagnosis, presenting a nuanced assessment of this complex care transition.

A Network Approach to Stroke Systems of Care

The landscape of stroke systems of care is evolving as patients are increasingly transferred between hospitals for access to higher levels of care. This is driven by time-sensitive disability-reducing interventions such as mechanical thrombectomy. However, coordination and triage of patients for such treatment remain a challenge worldwide, particularly given complex eligibility criteria and varying time windows for treatment. Network analysis is an approach that may be applied to this problem. Hospital networks interlinked by patients moved from facility to facility can be studied using network modeling that respects the interdependent nature of the system. This allows understanding of the central hubs, the change of network structure over time, and the diffusion of innovations. This topical review introduces the basic principles of network science and provides an overview on the applications and potential interventions in stroke systems of care.

Sepsis as the primary admitting diagnosis of transferred patients who died within 48 hours of arrival at a Central Texas hospital

Interhospital transfers are independently associated with inpatient mortality, and transferred patients have worse outcomes. The aim of this study was to retrospectively assess the 48-hour mortality rate in interhospital transfer cohorts of all transfers to a Central Texas teaching hospital and to identify a primary admitting diagnosis for potential intervention. A total of 15,435 patients with 19,161 transfers over the course of the study were retrospectively reviewed and placed in 18 different categories based upon the primary admitting diagnosis. There were about 5000 transfer patients yearly with ∼1.4% deaths within 48 hours of arrival. The three leading categories for transferred patients were cardiovascular, neurologic, and psychiatric. In this group, 268 of 19,161 transfers died within 48 hours of arrival. Despite being the 10th leading category for transfer, sepsis was the leading primary admitting diagnosis of patients who died within 48 hours of arrival, accounting for nearly 22% of those patients. Given the significant association found between sepsis and 48-hour mortality after transfer, we devised a novel interhospital transfer checklist based upon the Surviving Sepsis guidelines in an attempt to decrease mortality associated with these transfers.

Technological innovation for prehospital stroke triage: ripe for disruption

Background

With the benefit of mechanical thrombectomy firmly established, the focus has shifted to improved delivery of care. Reducing time from symptom onset to reperfusion is a primary goal. Technology promises tremendous opportunities in the prehospital space to achieve this goal.

Methods

This review explores existing, fledgling, and potential future technologies for application in the prehospital space.

Results

The opportunity for technology to improve stroke care resides in the detection, evaluation, triage, and transport of patients to an appropriate healthcare facility. Most prehospital technology remains in the early stages of design and implementation.

Conclusion

The major challenges to tackle for future improvement in prehospital stroke care are that of public awareness, emergency medical service detection, and triage, and improved systems of stroke care. Thoughtfully applied technology will transform all these areas.

Physician Perspectives on Interhospital Transfers

OBJECTIVE

The transfer of patients between acute care hospitals (interhospital transfer [IHT]) is a common but nonstandardized process leading to variable quality and safety. The goal of this study was to survey accepting physicians regarding problems encountered in the transfer process.

METHODS

A cross-sectional survey of residents and inpatient attendings from internal medicine, neurology, and surgery services at a large tertiary care referral hospital was undertaken to identify problematic aspects of the IHT process as perceived by accepting frontline providers. The frequency that specific scenarios were encountered in caring for transferred patients and whether these processes impacted patient safety were determined using 5- and 3-point Likert scales, respectively. The frequency of responses to each question were measured using proportions.

RESULTS

Approximately 51% of the 284 physicians surveyed responded. Pertinent findings included the following: physician subject surveys found that transferred patients sometimes, frequently, or always arrived without requiring specialized care in 56% of responses, arrived with unrealistic expectations of care in 77.2% of responses, arrived more than 24 hours after accepted for transfer in 80.1% of responses, and arrived without necessary transfer records in 86.9% of responses. Most respondents felt that lack of availability of transfer records and the time of day of arrival frequently posed a risk to transferred patients (57.2% and 53.1%, respectively). Response variation was noted between resident and attending physician respondents.

CONCLUSIONS

Expectations of care, delays and timing of transfer, and information exchange at time of transfer were identified as all too common problems in IHT, which creates a risk for patient safety. These areas are important targets for investigation and the development of interventions to improve patient safety.

Hospitals Strengthened Relationships With Close Partners After Joining Accountable Care Organizations

The strategies that hospitals participating in Medicare Accountable Care Organizations (ACOs) use to achieve quality and cost containment goals are poorly understood. One possibility is that participating hospitals could try to influence where their patients receive care. To test this hypothesis, we examined whether a hospital's participation in a Medicare ACO was associated with changes in its patterns of patient sharing with other hospitals. Between 2010 and 2014, patient sharing across hospitals increased 23.3%. After controlling for hospital and regional factors, patient sharing increased 4.4% more at ACO hospitals than non-ACO hospitals (p = .001 for difference). This increase occurred disproportionately among hospitals with which ACO hospitals already shared a high proportion of their patients prior to participation, and among hospitals in ACOs characterized as physician-hospital collaborations. The increased sharing of patients among closely affiliated hospitals may serve to achieve ACO quality and cost containment goals through increased interorganizational coordination.

Ischemic Stroke Transfer Patterns in the Northeast United States

BACKGROUND

Little is known about how hospitals are connected in the transfer of ischemic stroke (IS) patients. We aimed to describe differences in characteristics of transferred versus nontransferred patients and between transferring and receiving hospitals in the Northeastern United States, and to describe changes over time.

METHODS

We used Medicare claims data, and a subset linked with the Get with the Guidelines-Stroke registry from 2007 to 2011. Receiving hospitals were those with annual IS volume greater than or equal to 120 and greater than or equal to 15% received as transfers, and transferring hospitals were nonaccepting hospitals that transferred greater than or equal to 15% of their total (ED plus inpatient) IS patient discharges. A transferring-to-receiving hospital connection was identified if greater than or equal to 5 patients per year were shared. ArcGIS 10.3.1 was used for network visualization.

RESULTS

Among 177,270 admissions to 402 Northeast hospitals, 6906 (3.9%) patients were transferred. Transferred patients were younger with more severe strokes (78 versus 81 years, P < .001; National Institutes of Health Stroke Severity 7 versus 5, P < .001), and were as likely to receive tissue plasminogen activator as nontransferred (P = .29). From 2007 to 2011, there were more patients transferred (960 [3%] to 1777 [6%], P < .001), and more transferring hospitals (46 [12%] to 91 [24%], P < .001), and receiving hospitals (6 [2%] to 16 [4%], P < .001). Most transferring hospitals were exclusively connected to a single receiving hospital.

CONCLUSIONS

From 2007 to 2011, hospitals in the United States Northeast became more connected in the care of IS patients, with increasing patient transfers and hospital connections. Yet most hospitals remained unconnected. Further characterization of this transfer network will be important for understanding and improving regional stroke systems of care.

Interhospital Transfer and Receipt of Specialty Procedures

The practice of transferring patients between acute care hospitals is variable and largely nonstandardized. Although often-cited reasons for transfer include providing patients access to specialty services only available at the receiving institution, little is known about whether and when patients receive such specialty care during the transfer continuum. We performed a retrospective analysis using 2013 100% Master Beneficiary Summary and Inpatient claims files from Centers for Medicare and Medicaid Services. Beneficiaries were included if they were aged =65 years, continuously enrolled in Medicare A and B, with an acute care hospitalization claim, and transferred to another acute care hospital with a primary diagnosis of acute myocardial infarction, gastrointestinal bleed, renal failure, or hip fracture/dislocation. Associated specialty procedure codes (International Classification of Diseases, Ninth Revision, Clinical Modification) were identified for each diagnosis. We performed descriptive analyses to compare receipt of specialty procedural services between transferring and receiving hospitals, stratified by diagnosis. Across the 19,613 included beneficiaries, receipt of associated specialty procedures was more common at the receiving than the transferring hospital, with the exception of patients with a diagnosis of gastrointestinal bleed. Depending on primary diagnosis, between 32.4% and 89.1% of patients did not receive any associated specialty procedure at the receiving hospital. Our results demonstrate variable receipt of specialty procedural care across the transfer continuum, implying the likelihood of alternate drivers of interhospital transfer other than solely receipt of specialty procedural care.

Applications of network analysis to routinely collected health care data: a systematic review

Objective

To survey network analyses of datasets collected in the course of routine operations in health care settings and identify driving questions, methods, needs, and potential for future research.

Materials and Methods

A search strategy was designed to find studies that applied network analysis to routinely collected health care datasets and was adapted to 3 bibliographic databases. The results were grouped according to a thematic analysis of their settings, objectives, data, and methods. Each group received a methodological synthesis.

Results

The search found 189 distinct studies reported before August 2016. We manually partitioned the sample into 4 groups, which investigated institutional exchange, physician collaboration, clinical co-occurrence, and workplace interaction networks. Several robust and ongoing research programs were discerned within (and sometimes across) the groups. Little interaction was observed between these programs, despite conceptual and methodological similarities.

Discussion

We use the literature sample to inform a discussion of good practice at this methodological interface, including the concordance of motivations, study design, data, and tools and the validation and standardization of techniques. We then highlight instances of positive feedback between methodological development and knowledge domains and assess the overall cohesion of the sample.

Modeling the Impact of Interhospital Transfer Network Design on Stroke Outcomes in a Large City

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.

Rates, Predictors and Variability of Interhospital Transfers: A National Evaluation

IMPORTANCE

Interhospital transfer (IHT) remains a largely unstudied process of care.

OBJECTIVE

To determine the nationwide frequency of, patient and hospital-level predictors of, and hospital variability in IHT.

DESIGN

Cross-sectional study.

SETTING

Centers for Medicare and Medicaid 2013 100% Master Beneficiary Summary and Inpatient claims files merged with 2013 American Hospital Association data.

PATIENTS

Beneficiaries ≥65 years and older enrolled in Medicare A and B, with an acute care hospitalization claim in 2013.

EXPOSURES

Patient and hospital characteristics of transferred and nontransferred patients.

MEASUREMENTS

Frequency of interhospital transfers (IHT); adjusted odds of transfer of each patient and each hospital characteristic; and variability in hospital transfer rates.

RESULTS

Of 6.6 million eligible beneficiaries with an acute care hospitalization, 101,507 (1.5%) underwent IHT. Selected characteristics associated with greater adjusted odds of transfer included: patient age 74-85 years (odds ratio [OR], 2.38 compared with 65-74 years; 95% confidence intervals [CI], 2.33-2.43); nonblack race (OR, 1.17; 95% CI, 1.13-1.20); higher comorbidity (OR, 1.37; 95% CI, 1.36-1.37); lower diagnosis-related group-weight (OR, 2.02; 95% CI, 1.95-2.09); fewer recent hospitalizations (OR, 1.87; 95% CI, 1.79-1.95); and hospitalization in the Northeast (OR, 1.40; 95% CI, 1.27-1.55). Higher case mix index of the hospital was associated with a lower adjusted odds of transfer (OR, 0.36; 95% CI, 0.30-0.45). Variability in hospital transfer rates remained significant after adjustment for patient and hospital characteristics (variance 0.28, P = 0.01).

CONCLUSIONS

In this nationally representative evaluation, we found that a sizable number of patients undergo IHT. We identified both expected and unexpected patient and hospital-level predictors of IHT, as well as unexplained variability in hospital transfer rates, suggesting lack of standardization of this complex care transition. Our study highlights further investigative avenues to help guide best practices in IHT. Journal of Hospital Medicine 2017;12:435-442.

Hospital-Level Changes in Adult ICU Bed Supply in the United States

OBJECTIVES

Although the number of intensive care beds in the United States is increasing, little is known about the hospitals responsible for this growth. We sought to better characterize national growth in intensive care beds by identifying hospital-level factors associated with increasing numbers of intensive care beds over time.

DESIGN

We performed a repeated-measures time series analysis of hospital-level intensive care bed supply using data from Centers for Medicare and Medicaid Services.

SETTING

All United States acute care hospitals with adult intensive care beds over the years 1996-2011.

PATIENTS

None.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We described the number of beds, teaching status, ownership, intensive care occupancy, and urbanicity for each hospital in each year of the study. We then examined the relationship between increasing intensive care beds and these characteristics, controlling for other factors. The study included 4,457 hospitals and 55,865 hospital-years. Overall, the majority of intensive care bed growth occurred in teaching hospitals (net, +13,471 beds; 72.1% of total growth), hospitals with 250 or more beds (net, +18,327 beds; 91.8% of total growth), and hospitals in the highest quartile of occupancy (net, +10,157 beds; 54.0% of total growth). In a longitudinal multivariable model, larger hospital size, teaching status, and high intensive care occupancy were associated with subsequent-year growth. Furthermore, the effects of hospital size and teaching status were modified by occupancy: the greatest odds of increasing ICU beds were in hospitals with 500 or more beds in the highest quartile of occupancy (adjusted odds ratio, 18.9; 95% CI, 14.0-25.5; p < 0.01) and large teaching hospitals in the highest quartile of occupancy (adjusted odds ratio, 7.3; 95% CI, 5.3-9.9; p < 0.01).

CONCLUSIONS

Increasingly, intensive care bed expansion in the United States is occurring in larger hospitals and teaching centers, particularly following a year with high ICU occupancy.

Differences in Hospital Risk-standardized Mortality Rates for Acute Myocardial Infarction When Assessed Using Transferred and Nontransferred Patients

BACKGROUND

One in 5 patients with acute myocardial infarction (AMI) are transferred between hospitals. However, current hospital performance measures based on AMI mortality exclude these patients from the evaluation of referral hospitals.

OBJECTIVE

To determine the relationship between risk-standardized mortality for transferred and nontransferred patients at referral hospitals.

RESEARCH DESIGN

This is a retrospective cohort study.

SUBJECTS

Fee-for-service Medicare claims from 2011 for patients hospitalized with a primary diagnosis of AMI, at hospitals admitting at least 15 patients in transfer.

MEASURES

Hospital-specific risk-standardized 30-day mortality rates (RSMRs) for 2 groups of patients: those admitted through transfer from another hospital, and those natively admitted without a preceding or subsequent interhospital transfer.

RESULTS

There were 304 hospitals admitting at least 15 patients in transfer. These hospitals cared for 77,711 natively admitted patients (median, 254; interquartile range, 162-321), and 11,829 patients admitted in transfer (median, 26; interquartile range, 19-46). Risk-standardized mortality rates were higher for natively admitted patients than for those admitted in transfer (mean, 11.5%±1.2% vs. 7.2%±1.1%). There was weak correlation between hospital performance as assessed by RSMR for patients natively admitted versus those admitted in transfer (Pearson r=0.24, P<0.001); when performance was arrayed by quartile, 102 hospitals (33.6%) differed at least 2 quartiles of performance across the 2 patient groups.

CONCLUSIONS

For Medicare patients with AMI, hospital-specific RSMRs for natively admitted patients are only weakly associated with RSMRs for patients transferred in from another hospital. Current AMI performance metrics may fail to provide guidance about hospital quality for transferred patients.

Interhospital Transfer Center Model: Components, Themes, and Design Elements

OBJECTIVE

Timely access to advanced and specialist treatment often requires rapid interhospital transfer of patients from community hospitals to tertiary care centers. Transfer systems are variable in structure and process and are described in the literature as being fragmented, complex, and difficult to navigate.

METHODS

Nonparticipant observation at 10 tertiary care transfer systems.

RESULTS

Identified core components (ie, primary transfer system answering point, bed management coordination, and transport team dispatch) are essential elements of an interhospital tertiary care transfer center.

CONCLUSION

The Interhospital Transfer Center Model provides a useful framework to guide the design, implementation, and evaluation of interhospital transfer systems.

Constructing Episodes of Inpatient Care: How to Define Hospital Transfer in Hospital Administrative Health Data?

BACKGROUND

Hospital administrative health data create separate records for each hospital stay of patients. Treating a hospital transfer as a readmission could lead to biased results in health service research.

METHODS

This is a cross-sectional study. We used the hospital discharge abstract database in 2013 from Alberta, Canada. Transfer cases were defined by transfer institution code and were used as the reference standard. Four time gaps between 2 hospitalizations (6, 9, 12, and 24 h) and 2 day gaps between hospitalizations [same day (up to 24 h), ≤1 d (up to 48 h)] were used to identify transfer cases. We compared the sensitivity and positive predictive value (PPV) of 6 definitions across different categories of sex, age, and location of residence. Readmission rates within 30 days were compared after episodes of care were defined at the different time gaps.

RESULTS

Among the 6 definitions, sensitivity ranged from 93.3% to 98.7% and PPV ranged from 86.4% to 96%. The time gap of 9 hours had the optimal balance of sensitivity and PPV. The time gaps of same day (up to 24 h) and 9 hours had comparable 30-day readmission rates as the transfer indicator after defining episode of care.

CONCLUSIONS

We recommend the use of a time gap of 9 hours between 2 hospitalizations to define hospital transfer in inpatient databases. When admission or discharge time is not available in the database, a time gap of same day (up to 24 h) can be used to define hospital transfer.

Interhospital Transfer Delays Appropriate Treatment for Patients With Severe Sepsis and Septic Shock: A Retrospective Cohort Study

OBJECTIVE

To test the hypothesis that interhospital transfer causes significant delays in the administration of appropriate antibiotics and compliance with the completion of Surviving Sepsis Bundle elements.

DESIGN

Single-center retrospective cohort study.

SETTING

A comprehensive 60,000-visit emergency department at a 711-bed Midwestern academic medical center.

PATIENTS

Patients with severe sepsis and septic shock treated between 2009 and 2014 were identified by International Classification of Diseases,9th Revision, Clinical Modification, codes, then divided into two cohorts: 1) transfer patients who arrived at the tertiary academic center after receiving care in a local community hospital and 2) control patients who presented directly to the tertiary academic center emergency department.

INTERVENTIONS

None.

MEASUREMENT AND MAIN RESULTS

One hundred ninety-three patients were included. Transfer patients were more likely to require surgery in the hospital (p < 0.001) and require ICU care (p = 0.001) but had similar illness severity based on (Acute Physiology and Chronic Health Evaluation II, 17.7 vs 17.5; p = 0.662). Antibiotic administration at 1 and 3 hours was comparable between the two cohorts, but initial antibiotic appropriateness was lower in transfer patients (34% vs 79%; p < 0.001). Transfer patients were less likely to have fluid resuscitation started by 3 hours (54% vs 89%; p < 0.001), but they were not less likely to receive an adequate fluid bolus (30 mL/kg) by the time of hospital admission (p = 0.056). There were no differences in ICU length of stay or mortality.

CONCLUSIONS

Interhospital transfer significantly delays administration of appropriate initial antibiotics and resuscitation therapy. Future studies are needed to identify strategies of providing regional sepsis care prior to transfer to tertiary centers and to continue care pathways during the interhospital transfer process.

Expansion of invasive cardiac services in the United States

BACKGROUND

The number of hospitals offering invasive cardiac services (diagnostic angiography, percutaneous coronary intervention, and coronary artery bypass grafting) has expanded, yet national patterns of service diffusion and their effect on geographic access to care are unknown.

METHODS AND RESULTS

This is a retrospective cohort study of all hospitals in fee-for-service Medicare, 1996 to 2008. Logistic regression identified the relationship between cardiac service adoption and the proportion of neighboring hospitals within 40 miles already offering the service. From 1996 to 2008, 397 hospitals began offering diagnostic angiography, 387 percutaneous coronary intervention, and 298 coronary artery bypass grafting (increasing the proportion with services by 3%, 11%, and 4%, respectively). This capacity increase led to little new geographic access to care; the population increase in geographic access to diagnostic angiography was 1 percentage point; percutaneous coronary intervention 5 percentage points, and coronary artery bypass grafting 4 percentage points. Controlling for hospital and market characteristics, a 10 percentage point increase in the proportion of nearby hospitals already offering the service increased the odds by 10% that a hospital would add diagnostic angiography (odds ratio, 1.102; 95% confidence interval, 1.018-1.193), increased the odds by 79% that it would add percutaneous coronary intervention (odds ratio, 1.794; 95% confidence interval, 1.288-2.498), and had no significant effect on adding coronary artery bypass grafting (odds ratio, 0.929; 95% confidence interval, 0.608-1.420).

CONCLUSIONS

Hospitals are most likely to introduce new invasive cardiac services when neighboring hospitals already offer such services. Increases in the number of hospitals offering invasive cardiac services have not led to corresponding increases in geographic access.

Fibrinolytic therapy versus primary percutaneous coronary interventions for ST-segment elevation myocardial infarction in Kentucky: time to establish systems of care?

BACKGROUND

Fibrinolytic therapy is recommended for ST-segment myocardial infarctions (STEMI) when primary percutaneous coronary intervention (PPCI) is not available or cannot be performed in a timely manner. Despite this recommendation, patients often are transferred to PPCI centers with prolonged transfer times, leading to delayed reperfusion. Regional approaches have been developed with success and we sought to increase guideline compliance in Kentucky.

METHODS

A total of 191 consecutive STEMI patients presented to the University of Kentucky (UK) Chandler Medical Center between July 1, 2009 and June 30, 2011. The primary outcome was in-hospital mortality and the secondary outcomes were major adverse cardiovascular events, extent of myocardial injury, bleeding, and 4) length of stay. Patients were analyzed by presenting facility-the UK hospital versus an outside hospital (OSH)-and treatment strategy (PPCI vs fibrinolytic therapy). Further analyses assessed primary and secondary outcomes by treatment strategy within transfer distance and compliance with American Heart Association guidelines.

RESULTS

Patients presenting directly to the UK hospital had significantly shorter door-to-balloon times than those presenting to an OSH (83 vs 170 minutes; P < 0.001). This did not affect short-term mortality or secondary outcomes. By comparison, OSH patients treated with fibrinolytic therapy had a numeric reduction in mortality (4.0% vs 12.3%; P = 0.45). Overall, only 20% of OSH patients received timely reperfusion, 13% PPCI, and 42% fibrinolytics. In a multivariable model, delayed reperfusion significantly predicted major adverse cardiovascular events (odds ratio 3.87, 95% confidence interval 1.15-13.0; P = 0.02), whereas the presenting institution did not.

CONCLUSIONS

In contemporary treatment of STEMI in Kentucky, ongoing delays to reperfusion therapy remain regardless of treatment strategy. For further improvement in care, acceptance of transfer delays is necessary and institutions should adopt standardized protocols in association with a regional system of care.

Comparing hospital mortality--how to count does matter for patients hospitalized for acute myocardial infarction (AMI), stroke and hip fracture

Background

Mortality is a widely used, but often criticised, quality indicator for hospitals. In many countries, mortality is calculated from in-hospital deaths, due to limited access to follow-up data on patients transferred between hospitals and on discharged patients. The objectives were to: i) summarize time, place and cause of death for first time acute myocardial infarction (AMI), stroke and hip fracture, ii) compare case-mix adjusted 30-day mortality measures based on in-hospital deaths and in-and-out-of hospital deaths, with and without patients transferred to other hospitals.

Methods

Norwegian hospital data within a 5-year period were merged with information from official registers. Mortality based on in-and-out-of-hospital deaths, weighted according to length of stay at each hospital for transferred patients (W30D), was compared to a) mortality based on in-and-out-of-hospital deaths excluding patients treated at two or more hospitals (S30D), and b) mortality based on in-hospital deaths (IH30D). Adjusted mortalities were estimated by logistic regression which, in addition to hospital, included age, sex and stage of disease. The hospitals were assigned outlier status according to the Z-values for hospitals in the models; low mortality: Z-values below the 5-percentile, high mortality: Z-values above the 95-percentile, medium mortality: remaining hospitals.

Results

The data included 48 048 AMI patients, 47 854 stroke patients and 40 142 hip fracture patients from 55, 59 and 58 hospitals, respectively. The overall relative frequencies of deaths within 30 days were 19.1% (AMI), 17.6% (stroke) and 7.8% (hip fracture). The cause of death diagnoses included the referral diagnosis for 73.8-89.6% of the deaths within 30 days. When comparing S30D versus W30D outlier status changed for 14.6% (AMI), 15.3% (stroke) and 36.2% (hip fracture) of the hospitals. For IH30D compared to W30D outlier status changed for 18.2% (AMI), 25.4% (stroke) and 27.6% (hip fracture) of the hospitals.

Conclusions

Mortality measures based on in-hospital deaths alone, or measures excluding admissions for transferred patients, can be misleading as indicators of hospital performance. We propose to attribute the outcome to all hospitals by fraction of time spent in each hospital for patients transferred between hospitals to reduce bias due to double counting or exclusion of hospital stays.

The incomplete infrastructure for interhospital patient transfer

OBJECTIVE

Interhospital transfer of critically ill patients is a common part of their care. This article sought to review the data on the current patterns of use of interhospital transfer and identify systematic barriers to optimal integration of transfer as a mechanism for improving patient outcomes and value of care.

DATA SOURCE

Narrative review of medical and organizational literature.

SUMMARY

Interhospital transfer of patients is common, but not optimized to improve patient outcomes. Although there is a wide variability in quality among hospitals of nominally the same capability, patients are not consistently transferred to the highest quality nearby hospital. Instead, transfer destinations are selected by organizational routines or non-patient-centered organizational priorities. Accomplishing a transfer is often quite difficult for sending hospitals. But once a transfer destination is successfully found, the mechanics of interhospital transfer now appear quite safe.

CONCLUSION

Important technological advances now make it possible to identify nearby hospitals best able to help critically ill patients, and to successfully transfer patients to those hospitals. However, organizational structures have not yet developed to insure that patients are optimally routed, resulting in potentially significant excess mortality.

Hospital-level variation in the use of intensive care

OBJECTIVE

To determine the extent to which hospitals vary in the use of intensive care, and the proportion of variation attributable to differences in hospital practice that is independent of known patient and hospital factors.

DATA SOURCE

Hospital discharge data in the State Inpatient Database for Maryland and Washington States in 2006.

STUDY DESIGN

Cross-sectional analysis of 90 short-term, acute care hospitals with critical care capabilities. DATA COLLECTION/METHODS: We quantified the proportion of variation in intensive care use attributable to hospitals using intraclass correlation coefficients derived from mixed-effects logistic regression models after successive adjustment for known patient and hospital factors.

PRINCIPAL FINDINGS

The proportion of hospitalized patients admitted to an intensive care unit (ICU) across hospitals ranged from 3 to 55 percent (median 12 percent; IQR: 9, 17 percent). After adjustment for patient factors, 19.7 percent (95 percent CI: 15.1, 24.4) of total variation in ICU use across hospitals was attributable to hospitals. When observed hospital characteristics were added, the proportion of total variation in intensive care use attributable to unmeasured hospital factors decreased by 26-14.6 percent (95 percent CI: 11, 18.3 percent).

CONCLUSIONS

Wide variability exists in the use of intensive care across hospitals, not attributable to known patient or hospital factors, and may be a target to improve efficiency and quality of critical care.