Surgical Transfer Decision Making: How Regional Resources are Allocated in a Regional Transfer Network

Inner Deliberations of Surgeons Treating Critically-ill Emergency General Surgery Patients: A Qualitative Analysis

BACKGROUND

30% of elderly patients who require emergency general surgery (EGS) die in the year after the operation. Preoperative discussions can determine whether patients receive preference-sensitive care. Theoretically, surgeons frame their conversations after systematically assessing the risks and benefits of management options based on the clinical characteristics of each case. However, little is known about how surgeons actually deliberate about those options.

OBJECTIVE

To identify variables that influence surgeons' assessment of management options for critically-ill EGS patients.

METHODS

We conducted semi-structured interviews with 40 general surgeons in western Pennsylvania who worked in a variety of hospital settings. Interviews explored perioperative decision-making by asking surgeons to think aloud about selected memorable cases and a standardized case vignette of a frail patient with acute mesenteric ischemia. We used constant comparative methods to analyze interview transcripts and inductively developed a framework for the decision-making process.

RESULTS

Surgeons averaged 13 years (standard deviation (SD) 10.4) of experience; 40% specialized in trauma/acute care surgery. Important themes regarding the main topic of "perioperative decision-making" included many considerations beyond the clinical characteristics of cases. Surgeons described the importance of variables ranging from the availability of institutional resources to professional norms. Surgeons often remarked on their desire to achieve individual flow, team efficiency, and concordant expectations of treatment and prognosis with patients.

CONCLUSIONS

This is the first study to explore how surgeons decide among management options for critically-ill EGS patients. Surgeons' decision-making reflected a broad array of clinical, personal, and institutional variables. Effective interventions to ensure preference-sensitive care for EGS patients must address all of these variables.

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.

Association of insurance status with potentially avoidable transfers to an academic emergency department: A retrospective observational study

BACKGROUND

Interfacility transfers between emergency department (EDs) are common and at times unnecessary. We sought to examine the role of health insurance status with potentially avoidable transfers.

METHODS

We conducted a retrospective observational analysis using hospital electronic administrative data of all interfacility ED-to-ED transfers to a single, quaternary care adult ED in 2018. We defined a potentially avoidable transfer as an ED-to-ED transfer in which the patient did not receive a procedure from a specialist at the receiving hospital and was discharged from the ED or the receiving hospital within 24 hours of arrival. We constructed a multivariable logistic regression model to examine whether insurance status was associated with potentially avoidable transfers among all ED-to-ED transfers adjusting for patient demographics, severity, mode of arrival, clinical condition, and rurality.

RESULTS

Among 7508 transfers, 1862 (25%) were potentially avoidable and were more likely to be uninsured (20% vs 9%). In the multivariable analysis, among ED-to-ED transfers for adults aged 18-64 years old who were uninsured (vs any insurance) were significantly more likely to be potentially avoidable (adjusted odds ratio [aOR] 2.1 [1.7, 2.4]) and there is a significant interaction with age. Potentially avoidable transfers increased with younger age, male sex, black (vs white), small rural classification (vs urban), and arrival by ground ambulance (vs flight).

CONCLUSIONS

Potentially avoidable transfers comprised 1 in 4 transfers. Patients who lack insurance were more than twice as likely to be classified as potentially avoidable even after evaluating for confounders and interactions. This effect was most pronounced among younger patients. Further research is needed to explore why uninsured patients are disproportionately more likely to experience potentially avoidable transfers.

Factors associated with Interhospital transfers of emergency general surgery patients from emergency departments

BACKGROUND

Emergency general surgery (EGS) conditions account for over 3 million or 7.1% of hospitalizations per year in the US. Patients are increasingly transferred from community emergency departments (EDs) to larger centers for care, and a growing demand for treating EGS conditions mandates a better understanding of how ED clinicians transfer patients. We identify patient, clinical, and organizational characteristics associated with interhospital transfers of EGS patients originating from EDs in the United States.

METHOD

We analyze data from the Agency for Healthcare Research and Quality Nationwide Emergency Department Sample (NEDS) for the years 2010-2014. Patient-level sociodemographic characteristics, clinical factors, and hospital-level factors were examined as predictors of transfer from the ED to another acute care hospital. Multivariable logistic regression analysis includes patient and hospital characteristics as predictors of transfer from an ED to another acute care hospital.

RESULTS

Of 47,442,892 ED encounters (weighted) between 2008 and 2014, 1.9% resulted in a transfer. Multivariable analysis indicates that men (Odds ratio (OR) 1.18 95% Confidence Interval (95% CI) 1.16-1.21) and older patients (OR 1.02 (95% CI 1.02-1.02)) were more likely to be transferred. Relative to patients with private health insurance, patients covered by Medicare (OR 1.09 (95% CI 1.03-1.15) or other insurance (OR 1.34 (95% CI 1.07-1.66)) had a higher odds of transfer. Odds of transfer increased with a greater number of comorbid conditions compared to patients with an EGS diagnosis alone. EGS diagnoses predicting transfer included resuscitation (OR 36.72 (95% CI 30.48-44.22)), cardiothoracic conditions (OR 8.47 (95% CI 7.44-9.63)), intestinal obstruction (OR 4.49 (95% CI 4.00-5.04)), and conditions of the upper gastrointestinal tract (OR 2.82 (95% CI 2.53-3.15)). Relative to Level I or II trauma centers, hospitals with a trauma designation III or IV had a 1.81 greater odds of transfer. Transfers were most likely to originate at rural hospitals (OR 1.69 (95% CI 1.43-2.00)) relative to urban non-teaching hospitals.

CONCLUSION

Medically complex and older patients who present at small, rural hospitals are more likely to be transferred. Future research on the unique needs of rural hospitals and timely transfer of EGS patients who require specialty surgical care have the potential to significantly improve outcomes and reduce costs.

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.

Potentially preventable urinary tract infection in patients with type 2 diabetes - A hospital-based study

Aim

To investigate the prevalence of urinary tract infections in hospitalized patients with type 2 diabetes mellitus and identify corresponding risk factors.

Methods

We conducted a cross-sectional study on 7.347 patients with type 2 diabetes mellitus as the principal diagnosis, using hospitalization discharge summary data from January 1 to December 31, 2015. Disease stages were classified as stages 1, 2, and 3.

Results

Of 7.347 patients, 16.2% had urinary tract infections. The urinary tract infection prevalence was 24.4% in 428 patients in stage 1 and 4.8% in 2.840 patients in stage 2; it was higher among patients who underwent medical procedures than among those who underwent surgery (24.4% vs 4.8%). In multivariate regression analysis, age (OR = 1.031; 95% CI = 1.02-1.04), length of hospitalization (OR = 1.018; 95% CI = 1.013-1.024), sex (woman) (OR = 2.248; 95% CI = 1.778-2.842), comorbidity of stage 3 cerebrovascular disease (OR = 1.737; 95% CI = 1.111-2.714), and comorbidity of stage 1 colorectal cancer (OR = 2.417; 95% CI = 1.152-5.074) were found to be the risk factors of urinary tract infection in the ten hospitals considered.

Conclusions

Our findings suggest that urinary tract infection prevalence was higher in women without evidence of organ injury and those receiving medical treatment. Comorbidities (cerebrovascular disease and colorectal cancer) were identified as risk factors.

Impact of transfer status on real-world outcomes in nonelective cardiac surgery

OBJECTIVE

Transfer from hospital to hospital for cardiac surgery represents a large portion of some clinical practices. Previous literature in other surgical fields has shown worse outcomes for transferred patients. We hypothesized that transferred patients would be higher risk and demonstrate worse outcomes than those admitted through the emergency department.

METHODS

All patients undergoing cardiac operations with a Society of Thoracic Surgeons Predicted Risk of Mortality were evaluated from a multicenter, statewide Society of Thoracic Surgeons database. Only patients requiring admission before surgery were included. Patients were stratified by admission through the emergency department or in transfer. Transfers were further stratified by the cardiothoracic surgery capabilities at the referring center.

RESULTS

A total of 13,094 patients met the inclusion criteria of admission before surgery. This included 7582 (57.9%) transfers, of which 502 (6.6%) were referred from cardiac centers. Compared with emergency department admissions, transfers had increased hospital costs despite lower operative risk (Predicted Risk of Mortality 1.5% vs 1.6%, P < .01) and equivalent postoperative morbidity (15.6% vs 15.3% P = .63). In risk-adjusted analysis, transfer status was not independently associated with worse outcomes. Patients transferred from centers that perform cardiac surgery are higher risk than general transfers (Predicted Risk of Mortality 2.5% vs 1.5, P < .01), but specialized care results in excellent risk-adjusted outcomes (observed/expected: mortality 0.81; morbidity or mortality 0.90).

CONCLUSIONS

Transfer patients have similar rates of postoperative complications but increased resource use compared with patients admitted through the emergency department. Patients transferred from centers that perform cardiac surgery represent a particularly high-risk subgroup.

Modifying Interhospital Hepatopancreatobiliary Transfers Based on Predictive Analytics: Moving from a Center of Excellence to a Health-Care System of Excellence

Regionalization of complex surgical care has increased interhospital transfers to quaternary centers within large health-care systems. Risk-based patient selection is imperative to improve resource allocation without compromising care. This study aimed to develop predictive models for identifying low-risk patients for transfer to a fully integrated satellite hepatopancreatobiliary (HPB) service in the northeast region of the health-care system. HPB transfers to the quaternary center over 15 months from hospitals in proximity to the satellite HPB center. A predictive tool was developed based on simple pretransfer variables and outcomes for 30-day major complications (Clavien grade ≥ 3), readmission, and mortality. Thresholds for “low risk” were set at different SDs below mean for each model. Predictive models were developed from 51 eligible northeast region patient transfers for major complications (Brier score 0.1948, receiver operator characteristic (ROC) 0.7123, P = 0.0009), readmission (Brier score 0.0615, ROC 0.7368, P = 0.0020), and mortality (Brier score 0.0943, ROC 0.7989, P = 0.0023). Thresholds set from 2 SD below the mean for all models identified 2 as “low risk.” Adjusting the threshold for the serious complication model to only 1 SD below the mean increased the “low-risk” cohort to five patients. These models demonstrate an easy-to-use tool to assist surgeons in identifying low-risk patients for diversion to a fully integrated satellite center. Improved interhospital transfers within a region could begin a transition from centers of excellence toward health-care systems of excellence.