Impact of rural status on lower extremity bypass outcomes for patients with chronic limb threatening ischemia

OBJECTIVES

Previous studies noted that the rural population experienced higher peripheral artery disease (PAD) related mortality than their urban counterparts. Our study aimed to assess the impact of rural status on lower extremity bypass (LEB) outcomes for patients with chronic limb threatening ischemia (CLTI).

METHODS

We analyzed data from the Blue Cross Blue Shield Michigan Cardiovascular Consortium (BMC2) registry data from 2016 to 2022. Primary exposure included patient's residence based on rural-urban commuting area (RUCA) codes. Primary outcome was major adverse cardiac events (MACE). Secondary outcomes include 30-day and 1-year mortality, hospital readmission, bypass revision, wound complications, amputations, and 30-day renal failure requiring dialysis. We conducted univariate and multivariate analysis to evaluate association between rural status and LEB outcomes.

RESULTS

Rural patients tended to be White (p<.001), had insurance (p<.001), were current smokers (p<.001), had hyperlipidemia (p<.001), prior CHF (p=.031), COPD (p<.001), prior CVD/TIA (p=.005), and take pre-procedure aspirin (p=.011) and statin (p=.007), and were less likely to live in a distressed community (p<.001). They were not at increased risks of 30-day and 1-year MACE. They had higher odds of bypass revision (p=.028) at 1-year. However, they did not have higher odds of amputation at 30-days and 1-year.

CONCLUSIONS

Rural status does not impact LEB outcomes. Rural patients achieve comparable outcomes compared their urban counterparts due to overwhelmingly White rural demographics, optimal medical therapy, socioeconomic status (SES) and increased healthcare utilization.

Retrospective Cohort Study to Determine the Effect of Socioeconomic Status and Distance to Hospital on Negative Appendicectomy Rates in a Rural Setting

BACKGROUND

The impact of socioeconomic status and distance to hospital on negative appendicectomy rates is unknown. These factors have been shown to be important predictors of health in a rural setting.

OBJECTIVE

To determine whether socioeconomic status and road distance to hospital were risk factors for negative appendicectomy.

METHODS

A retrospective analysis of all appendicectomies at a large rural hospital in Australia between January 2018 and December 2022 was performed. Patients' data were extracted from electronic medical records. Regression modelling was performed to determine whether socioeconomic status and road distance to hospital were risk factors for negative appendicectomy. The surgical outcomes for negative and positive appendicectomies were compared.

RESULTS

A total of 830 patients were included in our analysis, of which 106 (12.8%) had negative appendicectomy. The rate of negative appendicectomy was not significantly impacted by socioeconomic status (OR = 1.004, 95% CI 0.989-1.20, p = 0.583) or road distance to hospital (OR = 1, 95% CI 0.998-1.001, p = 0.635). There was no significant difference in complications and 30-day readmission rates between patients in the negative and positive appendicectomy groups.

CONCLUSIONS

In a rural setting, the risk of negative appendicectomy does not increase with lower socioeconomic status and longer road distance to hospital. This challenges the prevailing notion that rural surgeons have a lower threshold to operate on patients with lower socioeconomic status or who live further away from hospitals due to the perception that these patients have less access to healthcare.

Geographic disparities in hospital readmissions: a retrospective cohort study among patients with chronic disease in rural China

BACKGROUND

Frequent hospital readmissions place a significant burden on patients, families, and society. Many high-income countries have implemented financial incentives to reduce readmissions. In China, readmission metrics have also been introduced as part of the performance evaluation for secondary hospitals. However, the understanding of hospital readmissions, particularly in rural and remote areas of China, remains limited. This study aims to analyze geographic disparities in hospital readmissions among high-need patients.

METHODS

This retrospective cohort study used anonymized hospital discharge data from January 1, 2017, to December 31, 2021, from three public secondary county hospitals. We included rural patients aged 15 and older with hypertension or type 2 diabetes. The outcomes were 30-day, 90-day, and annual readmissions. The explanatory variable was the travel distance to county hospitals, calculated based on the longitude and latitude of registered addresses. Covariates included patient demographics (gender, age, marital status, and ethnicity); health status (Charlson comorbidity score, types of chronic diseases, surgery, and length of stay); and other factors (health insurance and admitted departments). We first reported unweighted readmissions stratified by travel distances (< 40 km versus ≥ 40 km). Multiple logistic regression models were then used to examine the relationship between travel distances and readmissions.

RESULTS

The 30-day, 90-day and annual readmission rates for hypertension or type 2 diabetes were 8.5%, 19.1%, and 39.7%, respectively. Patients living far away were more vulnerable - older (aged 65 and older 59.1% versus 58.5%, P < 0.001), predominantly minorities (Minority 55.6% versus 29.4%, P < 0.001), and having more hypertension and diabetes-related complications, as well as undergoing more surgeries (surgery 29.4% versus 23.3%, P < 0.001) compared to those living nearby. After adjusting covariates and weights, patients living 40 km away had 11% decrease in the odds of being readmitted within 30 days (OR = 0.89, 95%CI = 0.83-0.96), 10% decrease in the odds of 90-day readmissions (OR = 0.90, 95%CI = 0.85-0.94), and 13% decrease in the odds of annual readmissions (OR = 0.87, 95%CI = 0.84-0.91) compared to those living within 40 km.

CONCLUSION

We found significant geographic disparities in hospital readmissions among high-need patients. Patients living farther from hospitals had significantly lower odds of readmissions. Readmission rates reflect patients' healthcare utilization patterns in rural and remote areas. Policymakers should address the geographic access barriers and be cautious when using readmission rates as a measure of hospital performance.

The impact of travel distance in patient outcomes following revascularization for chronic limb-threatening ischemia

BACKGROUND

Patient travel distance to the hospital is a key metric of individual and social disadvantage and its impact on the management and outcomes following intervention for chronic limb-threatening ischemia (CLTI) is likely underestimated. We sought to evaluate the effect of travel distance on outcomes in patients undergoing first-time lower extremity revascularization at our institution.

METHODS

We retrospectively reviewed all consecutive patients undergoing first-time lower extremity revascularization, both endovascular and open, for CLTI from 2005 to 2014. Patients were stratified into 2 groups based on travel distance from home to hospital greater than or less than 30 miles. Outcomes included reintervention, major amputation, restenosis, primary patency, wound healing, length of stay, length of follow-up and mortality. Kaplan-Meier estimates were used to determine event rates. Logistic and cox regression was used to evaluate for an independent association between travel distance and these outcomes.

RESULTS

Of the 1293 patients were identified, 38% traveled >30 miles. Patients with longer travel distances were younger (70 years vs 73 years; P = .001), more likely to undergo open revascularization (65% vs 41%; P < .001), and had similar Wound, Ischemia, foot Infection stages (P = .404). Longer distance travelled was associated with an increase in total hospital length of stay (9.6 days vs 8.6 days; P = .031) and shorter total duration of postoperative follow-up (2.1 years vs 3.0 years; P = .001). At 5 years, there was no definitive difference in the rate of restenosis (hzard ratio [HR], 1.3; 95% confidence interval [CI], 0.91-1.9; P = .155) or reintervention (HR, 1.4; 95% CI, 0.96-2.1; P = .065), but longer travel distance was associated with an increased rate of major amputation (HR, 2.1; 95% CI, 1.2-3.7; P = .011), and death (HR, 1.6; 95% CI, 1.2-2.2; P = .002). Longer travel distance was also associated with higher rate of nonhealing wounds (HR, 2.3; 95% CI, 1.5-3.5; P = .001).

CONCLUSIONS

Longer patient travel distance was found to be associated with a lower likelihood of limb salvage and survival in patients undergoing first-time lower extremity revascularization for CLTI. Understanding and addressing the barriers to discharge, need for multidisciplinary follow-up, and appropriate postoperative wound care management will be key in improving outcomes at tertiary care regional specialty centers.

Impact of Telehealth on Health Disparities Associated With Travel Time to Hospital for Patients With Recurrent Admissions: 4-Year Panel Data Analysis

BACKGROUND

Geographic, demographic, and socioeconomic differences in health outcomes persist despite the global focus on these issues by health organizations. Barriers to accessing care contribute significantly to these health disparities. Among these barriers, those related to travel time-the time required for patients to travel from their residences to health facilities-remain understudied compared with others.

OBJECTIVE

This study aimed to explore the impact of telehealth in addressing health disparities associated with travel time to hospitals for patients with recurrent hospital admissions. It specifically examined the role of telehealth in reducing in-hospital length of stay (LOS) for patients living farther from the hospital.

METHODS

We sourced the data from 4 datasets, and our final effective sample consisted of 1,600,699 admissions from 536,182 patients from 63 hospitals in New York and Florida in the United States from 2012 to 2015. We applied fixed-effect models to examine the direct effects and the interaction between telehealth and patients' travel time to hospitals on LOS. We further conducted a series of robustness checks to validate our main models and performed post hoc analyses to explore the different effects of telehealth across various patient groups.

RESULTS

Our summary statistics show that, on average, 22.08% (353,396/1,600,699) of patients were admitted to a hospital with telehealth adopted, with an average LOS of 5.57 (SD 5.06) days and an average travel time of about 16.89 (SD 13.32) minutes. We found that telehealth adoption is associated with a reduced LOS (P<.001) and this effect is especially pronounced as the patients' drive time to the hospital increases. Specifically, the coefficient for drive time is -0.0079 (P<.001), indicating that for every additional minute of driving time, there is a decrease of 0.0079 days (approximately 11 minutes) in the expected LOS. We also found that telehealth adoption has a larger impact on patients frequently needing health services, patients living in high internet coverage areas, and patients who have high virtualization potential diseases.

CONCLUSIONS

Our findings suggest that telehealth adoption can mitigate certain health disparities for patients living farther from hospitals. This study provides key insights for health care practitioners and policy makers on telehealth's role in addressing distance-related disparities and planning health care resources. It also has practical implications for hospitals in resource-limited countries that are in the early stages of implementing telehealth.

A state-level analysis of macro-level factors associated with hospital readmissions

Investigation of the factors that contribute to hospital readmissions has focused largely on individual level factors. We extend the knowledge base by exploring macrolevel factors that may contribute to readmissions. We point to environmental, behavioral, and socioeconomic factors that are emerging as correlates to readmissions. Data were taken from publicly available reports provided by multiple agencies. Partial Least Squares-Structural Equation Modeling was used to test the association between economic stability and environmental factors on opioid use which was in turn tested for a direct association with hospital readmissions. We also tested whether hospital access as measured by the proportion of people per hospital moderates the relationship between opioid use and hospital readmissions. We found significant associations between Negative Economic Factors and Opioid Use, between Environmental Factors and Opioid Use, and between Opioid Use and Hospital Readmissions. We found that Hospital Access positively moderates the relationship between Opioid Use and Readmissions. A priori assumptions about factors that influence hospital readmissions must extend beyond just individualistic factors and must incorporate a holistic approach that also considers the impact of macrolevel environmental factors.

Variation in Hospital Mortality After Complex Cancer Surgery: Patient, Volume, Hospital or Social Determinants?

INTRODUCTION

We sought to define the individual contributions of patient characteristics (PCs), hospital characteristics (HCs), case volume (CV), and social determinants of health (SDoH) on in-hospital mortality (IHM) after complex cancer surgery.

METHODS

The California Department of Health Care Access and Information database identified patients who underwent esophagectomy (ES), pneumonectomy (PN), pancreatectomy (PD), or proctectomy (PR) for a malignant diagnosis between 2010 and 2020. Multi-level multivariable regression was performed to assess the proportion of variance explained by PCs, HCs, CV and SDoH on IHM.

RESULTS

A total of 52,838 patients underwent cancer surgery (ES: n = 2,700, 5.1%; PN: n = 30,822, 58.3%; PD: n = 7530, 14.3%; PR: n = 11,786, 22.3%) across 294 hospitals. The IHM for the overall cohort was 1.7% and varied from 4.4% for ES to 0.8% for PR. On multivariable regression, PCs contributed the most to the variance in IHM (overall: 32.0%; ES: 21.6%; PN: 28.0%; PD: 20.3%; PR: 39.9%). Among the overall cohort, CV contributed 2.4%, HCs contributed 1.3%, and SDoH contributed 1.2% to the variation in IHM. CV was the second highest contributor to IHM among ES (5.3%), PN (5.3%), and PD (5.9%); however, HCs were a more important contributor among patients who underwent PR (8.0%). The unexplained variance in IHM was highest among ES (72.4%), followed by the PD (67.5%) and PN (64.6%) patient groups.

CONCLUSIONS

PCs are the greatest underlying contributor to variations in IHM following cancer surgery. These data highlight the need to focus on optimizing patients and exploring unexplained sources of IHM to improve quality of surgical care.

Variations in Travel Patterns Affect Regionalization of Complex Cancer Surgery in California

INTRODUCTION

Regionalization of complex surgical procedures may improve healthcare quality. We sought to define the impact of regionalization on access to high-volume hospitals for complex oncologic procedures in the state of California.

METHODS

The California Department of Health Care Access and Information Database (2012-2016) identified patients who underwent esophagectomy (ES), pneumonectomy (PN), pancreatectomy (PA), or proctectomy (PR). Geospatial analysis was conducted to determine travel patterns. Clustered multivariable regression was performed to assess the probability of receiving care at a high-volume center.

RESULTS

Among 25,070 patients (ES: n = 1216, 4.9%; PN: n = 13,247, 52.8%; PD: n = 3559, 14.2%; PR: n = 7048, 28.1%), 6575 (26.2%) individuals resided within 30 min, 11,046 (44.1%) resided within 30-60 min, 7125 (28.4%) resided within 60-90 min, and 324 (1.3%) resided beyond a 90-min travel window from a high-volume center. Median travel distance was 13.4 miles (interquartile range [IQR] 6.0-28.7). On multivariable regression, patients residing further away were more likely to bypass a low-volume center to undergo care at a high-volume hospital (odds ratio 1.32, 95% confidence interval 1.12-1.55) versus individuals residing closer to high-volume centers. Approximately one-third (29.7%) of patients lived beyond a 1-h travel window to the nearest high-volume hospital, of whom 5% traveled over 90 min. While hospital mortality rates across different travel time windows did not differ, surgery at a high-volume center was associated with an overall 1.2% decrease in in-hospital mortality.

CONCLUSIONS

Regionalization of complex cancer surgery may be associated with a significant travel burden for a large subset of patients with complex cancer.

Impact of Community Privilege on Access to Care Among Patients Following Complex Cancer Surgery

OBJECTIVE

We sought to define the impact of community privilege on variations in travel patterns and access to care at high-volume hospitals for complex surgical procedures.

BACKGROUND

With increased emphasis on centralization of high-risk surgery, social determinants of health play a critical role in preventing equitable access to care. Privilege is a right, benefit, advantage, or opportunity that positively impacts all social determinants of health.

METHODS

The California Office of State-wide Health Planning Database identified patients who underwent esophagectomy (ES), pneumonectomy (PN), pancreatectomy (PA), or proctectomy (PR) for a malignant diagnosis between 2012 and 2016 and was merged using ZIP codes with the Index of Concentration of Extremes, a validated metric of both spatial polarization and privilege obtained from the American Community Survey. Clustered multivariable regression was performed to assess the probability of undergoing care at a high-volume center, bypassing the nearest and high-volume center, and total real driving time and travel distance.

RESULTS

Among 25,070 patients who underwent a complex oncologic operation (ES: n=1216, 4.9%; PN: n=13,247, 52.8%; PD: n=3559, 14.2%; PR: n=7048, 28.1%), 5019 (20.0%) individuals resided in areas with the highest privilege (i.e., White, high-income homogeneity), whereas 4994 (19.9%) individuals resided in areas of the lowest privilege (i.e., Black, low-income homogeneity). Median travel distance was 33.1 miles (interquartile range 14.4-72.2). Roughly, three-quarters of patients (overall: 74.8%, ES: 35.0%; PN: 74.3%; PD: 75.2%; PR: 82.2%) sought surgical care at a high-volume center. On multivariable regression, patients residing in the least advantaged communities were less likely to undergo surgery at a high-volume hospital (overall: odds ratio 0.65, 95% CI 0.52-0.81). Of note, individuals in the least privileged areas had longer travel distances (28.5 miles, 95% CI 21.2-35.8) to reach the destination facility, as well as over 70% greater odds of bypassing a high-volume hospital to undergo surgical care at a low-volume center (odds ratio 1.74, 95% CI 1.29-2.34) versus individuals living in the highest privileged areas.

CONCLUSIONS AND RELEVANCE

Privilege had a marked effect on access to complex oncologic surgical care at high-volume centers. These data highlight the need to focus on privilege as a key social determinant of health that influences patient access to and utilization of health care resources.

Sociocultural and Demographic Factors Predict Readmissions for General Surgery Patients

INTRODUCTION

Readmission is a poor outcome for both patients and healthcare systems. The association of certain sociocultural and demographic characteristics with likelihood of readmission is uncertain in general surgical patients.

METHOD

A multi-centre retrospective cohort study of consecutive unique individuals who survived to discharge during general surgical admissions was conducted. Sociocultural and demographic variables were evaluated alongside clinical parameters (considered both as raw values and their proportion of change in the 1-2 days prior to admission) for their association with 7 and 30 days readmission using logistic regression.

RESULTS

There were 12,701 individuals included, with 304 (2.4%) individuals readmitted within 7 days, and 921 (7.3%) readmitted within 30 days. When incorporating absolute values of clinical parameters in the model, age was the only variable significantly associated with 7-day readmission, and primary language and presence of religion were the only variables significantly associated with 30-day readmission. When incorporating change in clinical parameters between the 1-2 days prior to discharge, primary language and religion were predictive of 30-day readmission. When controlling for changes in clinical parameters, only higher comorbidity burden (represented by higher Charlson comorbidity index score) was associated with increased likelihood of 30-day readmission.

CONCLUSIONS

Sociocultural and demographic patient factors such as primary language, presence of religion, age, and comorbidity burden predict the likelihood of 7 and 30-day hospital readmission after general surgery. These findings support early implementation a postoperative care model that integrates all biopsychosocial domains across multiple disciplines of healthcare.

Rural-Urban Disparities in Hospital Admissions and Mortality Among Patients with COVID-19: Evidence from South Carolina from 2021 to 2022

Although rural communities have been hard-hit by the COVID-19 pandemic, there is limited evidence on COVID-19 outcomes in rural America using up-to-date data. This study aimed to estimate the associations between hospital admissions and mortality and rurality among COVID-19 positive patients who sought hospital care in South Carolina. We used all-payer hospital claims, COVID-19 testing, and vaccination history data from January 2021 to January 2022 in South Carolina. We included 75,545 hospital encounters within 14 days after positive and confirmatory COVID-19 testing. Associations between hospital admissions and mortality and rurality were estimated using multivariable logistic regressions. About 42% of all encounters resulted in an inpatient hospital admission, while hospital-level mortality was 6.3%. Rural residents accounted for 31.0% of all encounters for COVID-19. After controlling for patient-level, hospital, and regional characteristics, rural residents had higher odds of overall hospital mortality (Adjusted Odds Ratio - AOR = 1.19, 95% Confidence Intervals - CI = 1.04-1.37), both as inpatients (AOR = 1.18, 95% CI = 1.05-1.34) and as outpatients (AOR = 1.63, 95% CI = 1.03-2.59). Sensitivity analyses using encounters with COVID-like illness as the primary diagnosis only and encounters from September 2021 and beyond - a period when the Delta variant was dominant and booster vaccination was available - yielded similar estimates. No significant differences were observed in inpatient hospitalizations (AOR = 1.00, 95% CI = 0.75-1.33) between rural and urban residents. Policymakers should consider community-based public health approaches to mitigate geographic disparities in health outcomes among disadvantaged population subgroups.

Coronary Artery Bypass Surgery Among Medicare Beneficiaries in Health Professional Shortage Areas

OBJECTIVE

Health professional shortage areas (HPSAs) were created by the Health Resources and Services Administration to identify communities with a shortage of clinical providers. For medical conditions, these designations are associated with worse outcomes. However, far less is known about patients undergoing high-complexity surgical procedures, such as coronary artery bypass grafting (CABG).

BACKGROUND

The aim was to compare postoperative surgical outcomes of high-complexity surgery in beneficiaries living in HPSA versus non-HPSA designated areas.

METHODS

This study is a retrospective cohort review of Medicare beneficiaries who underwent CABG between 2014 and 2018. The authors compared risk-adjusted 30-day mortality, complication, reoperation, and readmission rates for beneficiaries living in a designated HPSA versus non-HPSA using a multivariable logistic regression model accounting for patient (eg, age, sex, comorbidities, surgery year) and hospital characteristics (eg, patient-to-nurse ratio, teaching status). Patient travel burden was measured based on the time and distance required to travel from the beneficiary's home zip code to the hospital zip code.

RESULTS

Of the 370,532 Medicare beneficiaries who underwent CABG, 30,881 (8.3%) lived in a HPSA. Beneficiaries in HPSAs were found to experience comparable 30-day mortality (3.50% vs. 3.65%, P <0.001), complication (32.67% vs. 33.54%, P <0.001), reoperation (1.58% vs. 1.66%, P <0.001), and readmission (14.72% vs. 14.86%, P <0.001) rates. Beneficiaries experienced greater mean travel times (91.2 vs. 64.0 minutes, P <0.001) and mean travel distances (85.0 vs. 59.3 miles, P <0.001).

CONCLUSIONS

Medicare beneficiaries living in designated HPSA experienced comparable surgical outcomes after CABG surgery but a significantly greater travel burden. The greater travel burden experienced by patients living in designated shortage areas to obtain comparable surgical care for complex procedures demonstrates important tradeoffs between access and quality.

The Influence of Rural Healthcare Systems and Communities on Surgery and Recovery: A Qualitative Study

INTRODUCTION

Successful recovery after surgery is complex and highly individual. Rural patients encounter greater barriers to successful surgical recovery than urban patients due to varying healthcare and community factors. Although studies have previously examined the recovery process, rural patients' experiences with recovery have not been well-studied. The rural socioecological context can provide insights into potential barriers or facilitators to rural patient recovery after surgery.

METHODS

We conducted semi-structured qualitative interviews with a purposeful sample of 30 adult general surgery patients from rural areas in the Mountain West region of the United States. We used the socioecological framework to analyze their responses. Interviews focused on rural participants' experiences accessing healthcare and the impact of family and community support during postoperative recovery. Interviews were transcribed verbatim and coded using content and thematic analysis.

RESULTS

All participants commented on the quality of their rural healthcare systems and its influence on postoperative care. Some enjoyed the trust developed through long-standing relationships with providers in their communities. However, participants described community providers' lack of money, equipment, and/or knowledge as barriers to care. Following surgery, participants recognized that there are advantages and disadvantages to receiving family and community support. Some participants worried about being stigmatized or judged by their community.

CONCLUSIONS

Future interventions aimed at improving access to and recovery from surgery for rural patients should take into account the unique perspectives of rural patients. Addressing the socioecological factors surrounding rural surgery patients, such as healthcare, family, and community resources, will be key to improving postoperative recovery.

Identifying individual social risk factors using unstructured data in electronic health records and their relationship with adverse clinical outcomes

Objective

To determine the prevalence of individual-level social risk factors documented in unstructured data from electronic health records (EHRs) and the relationship between social risk factors and adverse clinical outcomes.

Study setting

Inpatient encounters for adults (≥18 years) at the University of Virginia Medical Center during a 12-month study period between July 2018 and June 2019. Inpatient encounters for labor and delivery patients were excluded, as well as encounters where the patient was discharged to hospice, left against medical advice, or expired in the hospital. The study population included 21,402 inpatient admissions, representing 15,116 unique patients who had at least one inpatient admission during the study period.

Study design

We identified measures related to individual social risk factors in EHRs through existing workflows, flowsheets, and clinical notes. Multivariate binomial logistic regression was performed to determine the association of individual social risk factors with unplanned inpatient readmissions, post-discharge emergency department (ED) visits, and extended length of stay (LOS). Other predictors included were age, sex, severity of illness, location of residence, and discharge destination.

Results

Predictors of 30-day unplanned readmissions included severity of illness (OR = 3.96), location of residence (OR = 1.31), social and community context (OR = 1.26), and economic stability (OR = 1.37). For 30-day post-discharge ED visits, significant predictors included location of residence (OR = 2.56), age (OR = 0.60), economic stability (OR = 1.39), education (OR = 1.38), social and community context (OR = 1.39), and neighborhood and built environment (OR = 1.61). For extended LOS, significant predictors were age (OR = 0.51), sex (OR = 1.18), severity of illness (OR = 2.14), discharge destination (OR = 2.42), location of residence (OR = 0.82), economic stability (OR = 1.14), neighborhood and built environment (OR = 1.31), and education (OR = 0.79).

Conclusions

Individual-level social risk factors are associated with increased risk for unplanned hospital readmissions, post-discharge ED visits, and extended LOS. While individual-level social risk factors are currently documented on an ad-hoc basis in EHRs, standardized SDoH screening tools using validated metrics could help eliminate bias in the collection of SDoH data and facilitate social risk screening.

Association of Socioeconomic Area Deprivation Index with Hospital Readmissions After Colon and Rectal Surgery

BACKGROUND

Risk adjustment for reimbursement and quality measures omits social risk factors despite adversely affecting health outcomes. Social risk factors are not usually available in electronic health records (EHR) or administrative data. Socioeconomic status can be assessed by using US Census data. Distressed Communities Index (DCI) is based upon zip codes, and the Area Deprivation Index (ADI) provides more granular estimates at the block group level. We examined the association of neighborhood disadvantage using the ADI, DCI, and patient-level insurance status on 30-day readmission risk after colorectal surgery.

METHODS

Our 677 patient cohort was derived from the 2013-2017 National Surgical Quality Improvement Program at a safety net hospital augmented with EHR data to determine insurance status and 30-day readmissions. Patients' home addresses were linked to the ADI and DCI.

RESULTS

Our cohort consisted of 53.9% males and 63.8% Hispanics with a 22.9% 30-day readmission rate from the date of discharge; > 50% lived in highly deprived neighborhoods. Controlling for medical comorbidities and complications, ADI was associated with increased risk of 30 days from the date of discharge readmissions among patients living in medium (OR = 2.15, p = .02) or high (OR = 1.88, p = .03) deprived areas compared to less-deprived neighborhoods, but not insurance status or DCI.

CONCLUSIONS

The ADI identified patients living in deprived communities with increased readmission risk. Our results show that block-group level ADI can potentially be used in risk adjustment, to identify high-risk patients and to design better care pathways that improve health outcomes.

Trends in the Geospatial Distribution of Inpatient Adult Surgical Services across the United States

OBJECTIVE

The aim of this study was to define trends in the geographic distribution of surgical services in the United States to assess possible geographic barriers and disparities in access to surgical care.

SUMMARY BACKGROUND DATA

Despite the increased need and utilization of surgical procedures, Americans often face challenges in gaining access to health care that may be exacerbated by the closure and consolidation of hospitals. Although access to surgical care has been evaluated relative to the role of insurance, race, and health literacy/education, the relationship of geography and travel distance to access has not been well studied.

METHODS

The 2005 and 2015 American Hospital Association annual survey was used to identify hospitals with surgical capacity; the data were merged with 2010 Census Bureau data to identify the distribution of the US population relative to hospital location, and geospatial analysis tools were used to examine a service area of real driving time surrounding each hospital.

RESULTS

Although the number of hospitals that provided surgical services slightly decreased over the time periods examined (2005, n = 3791; 2015, n = 3391; P<0.001), the number of major surgery hospitals increased from 2005 (n = 539) to 2015 (n = 749) (P<0.001). The geographic location of hospitals that provided surgical services changed over time. Specifically, although in 2005 852 hospitals were located in a rural area, that number had decreased to 679 by 2015 (P<0.001). Of particular note, from 2005 to 2015 there was an 82% increase in the number of people who lived further than 60 minutes from any hospital (P<0.001). However, the number of people who lived further than 60 minutes from a major surgery hospital decreased (P<0.001).

CONCLUSIONS

Although the number of rural hospitals decreased over the last decade, the number of large, academic medical centers has increased; in turn, there has been an almost doubling in the number of people who live outside a 60-minute driving range to a hospital capable of performing surgery.

Association of for-profit hospital ownership status with intracranial hemorrhage outcomes and cost of care

OBJECTIVE

Much of the current discourse surrounding healthcare reform in the United States revolves around the role of the profit motive in medical care. However, there currently exists a paucity of literature evaluating the effect of for-profit hospital ownership status on neurological and neurosurgical care. The purpose of this study was to compare inpatient mortality, operation rates, length of stay, and hospital charges between private nonprofit and for-profit hospitals in the treatment of intracranial hemorrhage.

METHODS

This retrospective cohort study utilized data from the National Inpatient Sample (NIS) database. Primary outcomes, including all-cause inpatient mortality, operative status, patient disposition, hospital length of stay, total hospital charges, and per-day hospital charges, were assessed for patients discharged with a primary diagnosis of intracranial (epidural, subdural, subarachnoid, or intraparenchymal) hemorrhage, while controlling for baseline demographics, comorbidities, and interhospital differences via propensity score matching. Subgroup analyses by hemorrhage type were then performed, using the same methodology.

RESULTS

Of 155,977 unique hospital discharges included in this study, 133,518 originated from private nonprofit hospitals while the remaining 22,459 were from for-profit hospitals. After propensity score matching, mortality rates were higher in for-profit centers, at 14.50%, compared with 13.31% at nonprofit hospitals (RR 1.09, 95% CI 1.00-1.18; p = 0.040). Surgical operation rates were also similar (25.38% vs 24.42%; RR 0.96, 95% CI 0.91-1.02; p = 0.181). Of note, nonprofit hospitals appeared to be more intensive, with intracranial pressure monitor placement occurring in 2.13% of patients compared with 1.47% in for-profit centers (RR 0.69, 95% CI 0.54-0.88; p < 0.001). Discharge disposition was also similar, except for higher rates of absconding at for-profit hospitals (RR 1.59, 95% CI 1.12-2.27; p = 0.018). Length of stay was greater among for-profit hospitals (mean ± SD: 7.46 ± 11.91 vs 6.50 ± 8.74 days, p < 0.001), as were total hospital charges ($141,141.40 ± $218,364.40 vs $84,863.54 ± $136,874.71 [USD], p < 0.001). These findings remained similar even after segregating patients by subgroup analysis by hemorrhage type.

CONCLUSIONS

For-profit hospitals are associated with higher inpatient mortality, lengths of stay, and hospital charges compared with their nonprofit counterparts.

Trends in the Geospatial Distribution of Adult Inpatient Surgical Cancer Care Across the United States

INTRODUCTION

The relationship and trends of geography and travel distance to access surgical cancer care has been poorly characterized. The objective of the study was to define the geographic distribution of access to hospital-based operative cancer care across the USA.

METHODS

A cohort analysis was performed using the 2005 and 2015 American Hospital Association Annual Survey, Census Bureau Data for 2010, and the American Community Survey 5-year estimates for 2011 to 2016.

RESULTS

The number of hospitals that provided surgical services with an approved American College of Surgeons (ACS) cancer program slightly increased over the time periods examined (2005, n = 1203 vs. 2015, n = 1284; p = 0.7210). Based on geospatial analysis, 18,214,994 (5.9%) people lived more than 60 min from a hospital with a cancer program in 2005 compared with 34,630,516 (11.2%) by 2015. Communities within a 60-min drive time were more likely to be composed of individuals who completed high school (85.9% vs. 84.2%), were employed (62.7% vs. 57.1%), had a higher median household income ($67.4 k vs. $53.2 k), and lived within states that had expanded Medicaid (62.5% vs. 48.9%) (all p < 0.0001). In contrast, communities outside of a 60-min drive time had a greater proportion of individuals below the federal poverty level (18.3% vs. 16.5%; p < 0.0001).

CONCLUSIONS

While the number of hospitals with ACS approved cancer program designation increased over the last decade, the number of people living greater than 60 min from an approved cancer programs nearly doubled. These data highlight worrisome geospatial trends that may make access to cancer care for certain patient populations increasingly challenging.

Association of Neighborhood Characteristics with Utilization of High-Volume Hospitals Among Patients Undergoing High-Risk Cancer Surgery

INTRODUCTION

As high-risk cancer surgery continues to become more centralized, it is important to understand the association of neighborhood characteristics relative to access to surgical care. We sought to determine the neighborhood level characteristics that may be associated with travel patterns and utilization of high-volume hospitals.

METHODS

The California Office of Statewide Health Planning database was used to identify patients who underwent pancreatectomy (PD), esophagectomy (ES), proctectomy (PR), or pneumonectomy (PN) for cancer between 2014 and 2016. Total minutes (m) traveled as well as whether a patient bypassed the nearest hospital that performed the operation to get to a higher-volume center was assessed. Data were merged with the Centers for Disease control social vulnerability index (SVI).

RESULTS

Overall, 26,937 individuals (ES: 4.7%; PN: 53.5% PD: 13.9% PR: 27.9%) underwent a complex oncologic operation. Median travel time was 16 m (interquartile range [IQR] 8.3-30.24) [ES: 21.8 m (IQR 10.6-46.9); PN: 14 m (IQR 7.8-27.0); PD: 21.2 m (IQR 10.6-42.6); PR: 15 m (IQR 8.1-28.4)]. Nearly three-quarter of patients (ES: 34%; PN: 73%; PD: 72%; LR: 81%) underwent an operation at a high-volume hospital. For all four operations, patients who resided in a county with a high overall SVI were less likely to have surgery at a high-volume hospital (ES: odds ratio [OR] 0.39, 95% confidence interval [CI] 0.24-0.65; PN: OR: 0.67, 95% CI 0.51-0.88; PD: OR 0.61, 95% CI 0.44-0.84; PR: OR 0.76, 95% CI 0.58-0.98).

CONCLUSIONS

Patients residing in communities of high social vulnerability were less likely to undergo high-risk cancer surgery at a high-volume hospital. The identification of society-based contextual disparities in access to complex surgical care should serve to inform targeted strategies to direct additional resources toward these vulnerable communities.

Variation in value among hospitals performing complex cancer operations

BACKGROUND

While variation in outcomes has driven centralization of complex cancer surgery, variation in cost and value remains unexplored. We evaluated outcomes relative to cost among hospitals performing esophageal and pancreatic resection for cancer.

METHODS

Using 100% Medicare claims data, we identified fee-for-service Medicare patients undergoing elective esophagectomy and pancreatectomy for cancer from 2014 to 2016. Risk- and reliability-adjusted, price-standardized payments for the surgical episode from admission through 30 days post discharge, as well as risk- and reliability-adjusted complication rates for each hospital, were calculated. Hospitals were separated into quintiles relative to payments and outcomes. Highest-value hospitals were defined as hospitals in the top 2 quartiles for both cost and outcomes.

RESULTS

Among 11,586 Medicare beneficiaries who underwent a complex oncologic operation between 2014 and 2016, 66% had a pancreatic neoplasm, while 33% had an esophageal neoplasm. Overall, 31.1% patients underwent an operation at a high-value hospital. Among patients who underwent pancreatectomy, the risk-adjusted postoperative complication rate was 31.4% at the lowest-value hospitals vs 22.7% at highest-value hospitals (odds ratio: 0.57, 95% confidence interval 0.47-0.70). The esophagectomy, risk-adjusted postoperative complication rate was 48.3% at lowest-value hospitals versus 29.8% at highest-value hospitals (odds ratio: 0.36, 95% confidence interval 0.27-0.47). The average difference in episode cost of care for an esophagectomy at lowest- versus highest-value hospitals was $5,617; the difference for pancreatectomy was $2,748.

CONCLUSION

There was wide variation in complication rates and average costs among lowest- versus highest-value hospitals performing esophagectomy and pancreatectomy for cancer. Even among highest quality hospitals, wide variation in average episode costs was noted. Surgeons should seek to better understand practice variation to standardize care and decrease variation in outcomes, utilization, and costs.

Accessing surgical care for esophageal cancer: patient travel patterns to reach higher volume center

While better outcomes at high-volume surgical centers have driven the regionalization of complex surgical care, access to high-volume centers often requires travel over longer distances. We sought to evaluate the travel patterns among patients undergoing esophagectomy to assess willingness of patients to travel for surgical care. The California Office of Statewide Health Planning database was used to identify patients who underwent esophagectomy between 2005 and 2016. Total distance traveled, as well as whether a patient bypassed the nearest hospital that performed esophagectomy to get to a higher volume center, was assessed. Overall 3,269 individuals underwent an esophagectomy for cancer in 154 hospitals; only five hospitals were high volume according to Leapfrog standards. Median travel time to a hospital that performed esophagectomy was 26 minutes (IQR: 13.1-50.7). The overwhelming majority of patients (85%) bypassed the nearest providing hospital to seek care at a destination hospital. Among patients who bypassed a closer hospital, only 36% went to a high-volume hospital. Of the 2,248 patients who underwent esophagectomy at a low-volume center, 1,491 patients had bypassed a high-volume hospital. Of the remaining 757 patients who did not bypass a high-volume hospital, half of the individuals would have needed to travel less than an additional hour to reach a high-volume center. Nearly two-thirds of patients undergoing an esophagectomy for cancer received care at a low-volume center; 85% of patients either bypassed a high-volume hospital or would have needed to travel less than an additional hour to reach a high-volume center.

Priorities for peri-operative research in Africa

Deaths following surgery are the third largest contributor to deaths globally, and in Africa are twice the global average. There is a need for a peri-operative research agenda to ensure co-ordinated, collaborative research efforts across Africa in order to decrease peri-operative mortality. The objective was to determine the top 10 research priorities for peri-operative research in Africa. A Delphi technique was used to establish consensus on the top research priorities. The top 10 research priorities identified were (1) Develop training standards for peri-operative healthcare providers (surgical, anaesthesia and nursing) in Africa; (2) Develop minimum provision of care standards for peri-operative healthcare providers (surgical, anaesthesia and nursing) in Africa; (3) Early identification and management of mothers at risk from peripartum haemorrhage in the peri-operative period; (4) The role of communication and teamwork between surgical, anaesthetic, nursing and other teams involved in peri-operative care; (5) A facility audit/African World Health Organization situational analysis tool audit to assess emergency and essential surgical care, which includes anaesthetic equipment available and level of training and knowledge of peri-operative healthcare providers (surgeons, anaesthetists and nurses); (6) Establishing evidence-based practice guidelines for peri-operative physicians in Africa; (7) Economic analysis of strategies to finance access to surgery in Africa; (8) Establishment of a minimum dataset surgical registry; (9) A quality improvement programme to improve implementation of the surgical safety checklist; and (10) Peri-operative outcomes associated with emergency surgery. These peri-operative research priorities provide the structure for an intermediate-term research agenda to improve peri-operative outcomes across Africa.

Accessing surgical care for pancreaticoduodenectomy: Patient variation in travel distance and choice to bypass hospitals to reach higher volume centers

BACKGROUND

While better outcomes at high-volume surgical centers have driven regionalization of complex surgical care, access to high-volume centers often requires travel over longer distances. We sought to evaluate travel patterns of patients undergoing pancreaticoduodenectomy (PD) for pancreatic cancer to assess willingness of patients to travel for surgical care.

METHODS

The California Office of Statewide Health Planning database was used to identify patients who underwent PD between 2005 and 2016. Total distance traveled, as well as whether a patient bypassed the nearest hospital that performed PD to get to a higher-volume center was assessed. Multivariate analyses were used to identify factors associated with bypassing a local hospital for a higher-volume center.

RESULTS

Among 23 014 patients who underwent PD, individuals traveled a median distance of 18.0 miles to get to a hospital that performed PD. The overwhelming majority (84%) of patients bypassed the nearest providing hospital and traveled a median additional 16.6 miles to their destination hospital. Among patients who bypassed the nearest hospital, 13,269 (68.6%) did so for a high-volume destination hospital. Specifically, average annual PD volume at the nearest "bypassed" vs final destination hospital was 29.6 vs 56 cases, respectively. Outcomes at bypassed vs destination hospitals varied (incidence of complications: 39.2% vs 32.4%; failure-to-rescue: 14.5% vs 9.1%). PD at a high-volume center was associated with lower mortality (OR = 0.46 95% CI, 0.22-0.95). High-volume PD ( > 20 cases) was predictive of hospital bypass (OR = 3.8 95% CI, 3.3-4.4). Among patients who had surgery at a low-volume center, nearly 20% bypassed a high-volume hospital in route. Furthermore, among patients who did not bypass a high-volume hospital, one-third would have needed to travel only an additional 30 miles or less to reach the nearest high-volume hospital.

CONCLUSION

Most patients undergoing PD bypassed the nearest providing hospital to seek care at a higher-volume hospital. While these data reflect increased regionalization of complex surgical care, nearly 1 in 5 patients still underwent PD at a low-volume center.

Travel distance and regional access to cardiac valve surgery

OBJECTIVE

Evidence in other surgical subspecialties suggests patients traveling farther to undergo surgery have worse outcomes. We sought to determine the impact of travel distance and travel beyond closest center on outcomes after valve surgery.

METHODS

Patients who underwent valve surgery ±CABG with a Society of Thoracic Surgeons (STS) predicted risk and zip code were extracted from a statewide STS database (2011-016). Patients were stratified by those receiving care greater than or equal to 20 miles from the closest surgical center (Traveler) or at the closest center (Non-Traveler). Multivariate logistic regression assessed the effects of travel distance and traveler status on mortality and major morbidity adjusted for STS predicted risk, median income by zip code, and payer status.

RESULTS

Median travel distance for all patients (n = 4765) was 19 miles and after risk-adjustment increasing distance was associated with reduced operative mortality (odds ratio [OR], 0.94 [0.89-1.00], P = .049) with no impact on major morbidity. Travelers (445 patients, 9.3%) had lower median income, higher self-pay and reoperative status, but similar urgent/emergent status and STS risk as Non-Travelers. Travelers had lower operative mortality (1.6% vs 4.3%, P = .005) which remained statistically lower after risk-adjustment (OR, 0.32 [0.14-0.75], P = .009). This mortality difference was particularly pronounced in patients with postoperative complications (3.1% vs 7.9%, P = .005).

CONCLUSIONS

Contrary to other surgical subspecialties, farther travel distance and bypassing the nearest surgical center were associated with lower rates of operative mortality and failure to rescue. Either referral patterns or financials reasons may result in Travelers ending up at high performing centers that prevent escalation of complications.

Geographic Distribution of Adult Inpatient Surgery Capability in the USA

INTRODUCTION

Access to timely, quality, and affordable surgical services is an important component of health care systems. A better understanding of the geographic distribution of surgical services in the USA may help identify disparities in access to surgery.

METHODS

Using the 2015 American Hospital Association Annual Survey, the 2010 Census Bureau Data, and the American Community Survey 5-year estimates from 2011 to 2016, all hospitals with surgical capabilities were geocoded with 30 straight-line mile service areas around each hospital using geospatial analysis. Major surgical hospitals were defined as meeting three of the four following criteria: bed size ≥ 45, ≥ 8600 operations per year, ≥ 12 operating rooms, and academic medical center. The distribution of the US population based on proximity to a hospital capable of performing adult inpatient surgery and a major surgical hospital was then analyzed and compared.

RESULTS

Overall, 3409 hospitals were identified that had the capacity to perform adult inpatient surgery of which 1373 were defined as major surgical hospitals. Based on geospatial analysis, 10% of the US population was found to reside outside of a linear 30-mile radius of a surgical hospital. Younger age (OR 0.97, CI 0.96-0.97), female sex (OR 4.6, CI 4.3-5), African-American race (OR = 5.4, CI 4.7-6.2), Hispanic/Latino race (OR 5.5, CI 4.8-6.3), having completed high school or greater (OR = 3.6, CI 3-4.2), being employed (OR 4.8, CI 4.6-4.9), and having any type of health insurance were significantly associated with living in a service area.

CONCLUSION

A significant proportion of the US population lives greater than 30 straight-line miles from a major surgical hospital. Common demographic and socioeconomic factors highlight disparities in access to surgical care.

Development of a Novel Emergency Department Mapping Tool

OBJECTIVES

Develop a built environment mapping workflow. Implement the workflow in the emergency department (ED). Demonstrate the actionable representations of the data that can be collected using this workflow.

BACKGROUND

The design of the healthcare built environment impacts the delivery of patient care and operational efficiency. Studying this environment presents a series of challenges due to the limitations associated with existing technology such as radio-frequency identification. The authors designed a customized mapping workflow to collect high-resolution spatial, temporal, and activity data to improve healthcare environments, with emphasis on patient safety and operational efficiency.

METHOD

A large, urban, academic medical center ED collaborated with an architecture firm to create a data collection, and mapping workflow using ArcGIS tools and data collectors. The authors developed tools to collect data on the entire ED, as well as individual patients, physicians, and nurses. Advanced visual representations were created from the master data set.

RESULTS

In 48 consecutive hourly snapshots, 5,113 data points were collected on patients, physicians, nurses, and other staff reflecting the operations of the ED. Separately, 84 patients, 10 attending physicians, 10 resident physicians, and 17 nurses were tracked.

CONCLUSIONS

The data obtained from this pilot study were used to create advanced visual representations of the ED environment. This cost-effective ED mapping workflow may be applied to other healthcare settings. Further investigation to evaluate the benefits of this high-resolution data is required.

Geospatial, Clinical, and Social Determinants of Hospital Readmissions

Unnecessary hospital readmissions increase patient burden, decrease health care quality and efficiency, and raise overall costs. This retrospective cohort study sought to identify high-risk patients who may serve as targets for interventions aiming at reducing hospital readmissions. The authors compared geospatial, social demographic, and clinical characteristics of patients with or without a 90-day readmission. Electronic health records of 42 330 adult patients admitted to 2 Midwestern hospitals during 2013 to 2016 were used, and logistic regression was performed to determine risk factors for readmission. The 90-day readmission percentage was 14.9%. Two main groups of patients with significantly higher odds of a 90-day readmission included those with severe conditions, particularly those with a short length of stay at incident admission, and patients with Medicare but younger than age 65. These findings expand knowledge of potential risk factors related to readmissions. Future interventions to reduce hospital readmissions may focus on the aforementioned high-risk patient groups.

Outcomes and costs of pediatric appendectomies at rural hospitals

BACKGROUND/PURPOSE

Despite policy efforts to support rural hospitals, little is known about the quality and safety of pediatric surgical care in geographically remote areas. Our aim was to determine the outcomes and costs of appendectomies at rural hospitals.

METHODS

The Kids' Inpatient Database (2003-2012) was queried for appendectomies in children <18 years at urban and rural hospitals. Outcomes (disease severity, laparoscopy, complications, length of stay (LOS), cost) were analyzed with bivariate and multivariable regression analysis.

RESULTS

Rural hospitals performed 13.6% of appendectomies. On multivariable analysis, rural hospitals were associated with higher negative appendectomy rates (OR 1.49, 95% CI 1.39-1.60, p < 0.001), decreased appendiceal perforation rates (OR 0.86, 95% CI 0.83-0.89, p < 0.001), less laparoscopy use (OR 0.48, 95% CI 0.47-0.50, p < 0.001), higher complication rates (OR 1.29, 95% CI 1.19-1.39, p < 0.001), shorter LOS (IRR 0.90, 95% CI 0.89-0.91, p < 0.001), and slightly increased costs (exponentiated log$ 1.02, 95% CI 1.01-1.02, p < 0.001) CONCLUSIONS: Rural hospitals care for fewer patients with advanced appendicitis but are associated with higher negative appendectomy rates, lower laparoscopy use, and higher complication rates. Additional studies are needed to identify factors that drive this disparity to improve the quality of pediatric surgical care in rural settings.

TYPE OF STUDY

Treatment/Cost Study (Outcomes).

LEVEL OF EVIDENCE

Level III.

Assessing outcomes and costs of appendectomies performed at rural hospitals

BACKGROUND

The purpose of our study was to assess the outcomes and costs of appendectomies performed at rural and urban hospitals.

METHODS

The National Inpatient Sample (2001-2012) was queried for appendectomies at urban and rural hospitals. Outcomes (disease severity, laparoscopy, complications, length of stay (LOS), and cost) were analyzed.

RESULTS

Rural patients were more likely to be older, male, white, and have Medicaid or no insurance. Rural hospitals were associated with higher negative appendectomy rates (OR = 1.26,95%CI = 1.18-1.34,p < 0.01), less laparoscopy use (OR = 0.65,95%CI = 0.58-0.72,p < 0.01), and slightly shorter LOS (OR = 0.98,95%CI = 0.97-0.99,p < 0.01). There was no consistent association with perforated appendicitis and no difference in complications or costs after adjusting for hospital volume. Yearly trends showed a significant increase in the cases utilizing laparoscopy each year at rural hospitals.

CONCLUSIONS

Rural appendectomies are associated with increased negative appendectomy rates and less laparoscopy use with no difference in complications or costs compared to urban hospitals.

Nonclinical Barriers to Care for Neurogenic Patients Undergoing Complex Urologic Reconstruction

OBJECTIVE

To identify nonclinical factors affecting postoperative complication rates in patients with neurogenic bladder undergoing benign genitourinary (GU) reconstruction.

METHODS

Adult patients with neurogenic bladder undergoing benign GU reconstruction between October 2010 and November 2015 were included. Patients were excluded if a diversion was performed for malignancy, if patients had a history of radiation or if a new bowel segment was not utilized at the time of the operation. Clinical and nonclinical factors were abstracted from the patients' electronic medical records. Health literacy was assessed via the Brief Health Literacy Screen (BHLS), a validated 3-question assessment. Education, marital status, and distance from the medical center were also queried.

RESULTS

Forty-nine patients with a neurogenic bladder undergoing complex GU reconstruction met inclusion and exclusion criteria. On average, patients lived 111 miles (standard deviation 89) from the hospital. Overall, mean BHLS score was 10.4 (standard deviation 4.6) with 35% of patients scoring a BHLS of ≤9. Mean years of educational attainment was 9.7, and only 31% of patients completed high school education. In the first month after surgery, 37 patients (76%) experienced a complication, and 22% were readmitted; however, analysis of complication data did not identify an association between any nonclinical variables and complication rates.

CONCLUSION

Nonclinical factors including unmarried status, poor health literacy, and marked distance from quaternary care are prevalent in patients with neurogenic bladder undergoing complex GU reconstruction. To mitigate these potential risk factors, the authors recommend acknowledgment of these factors and multidisciplinary support perioperatively to counteract them.