Nonindex Hospitals Research Articles

TCT-843 Burden of 30 Days Readmission After PCI to Non-Index Hospital vs. Index-Hospital in the United States: Insights From the Nationwide Readmission Database (NRD)

TCT-843 Burden of 30 Days Readmission After PCI to Non-Index Hospital vs. Index-Hospital in the United States: Insights From the Nationwide Readmission Database (NRD)

Readmissions After Acute Myocardial Infarction: How Often Do Patients Return to the Discharging Hospital?

BackgroundWhen patients require readmission after a recent myocardial infarction (MI), returning to the discharging (index) hospital may be associated with better outcomes as a result of greater continuity in care. However, little evidence exists to answer this frequent patient question.Methods and ResultsAmong Medicare patients aged ≥65 years discharged home alive post‐MI from 491 US hospitals in the ACTION (Acute Coronary Treatment Intervention Outcomes Network) Registry, we compared reason for readmission, duration of rehospitalization, and 30‐day mortality between patients readmitted to the index versus nonindex hospital within 30 days of index MI discharge. Among 53 471 MI patients, 7715 (14%) were readmitted within 30 days, and most readmitted patients (73%) returned to the discharging hospital. Reason for readmission was not significantly associated with location of readmission. In multivariable modeling, the strongest factors associated with readmission to a nonindex hospital were distance from the discharging hospital, transfer‐in during the index MI hospitalization, and frequency of nonindex hospital admissions in the year preceding to the index MI. Duration of rehospitalization did not differ significantly between patients readmitted to the index versus nonindex hospital (median, 4 versus 3 days; P=0.17). Mortality risk was also not significantly different between patients readmitted to the index versus nonindex hospital overall (7.4 versus 7.7%; adjusted odds ratio, 0.89; 95% CI, 0.73–1.10) and when stratified by reason for readmission (P for interaction=0.61).ConclusionsPost‐MI readmissions did not differ in reason for readmission, duration of rehospitalization, or associated mortality when compared between patients who returned to the discharging hospital and those who sought care elsewhere.

Fragmentation of postoperative care after surgical management of ovarian cancer at 30 days and 90 days

Fragmentation of care, wherein a patient is discharged from an index hospital and undergoes an unexpected readmission to a nonindex hospital, is associated with increased risk of adverse outcomes. Fragmentation has not been well-characterized in ovarian cancer. The objective of this study was to assess risk factors and outcomes that are associated with fragmentation of care among women who undergo surgical treatment of ovarian cancer. The Nationwide Readmission Database was used to identify all-cause 30-day and 90-day postoperative readmissions after surgical management of ovarian cancer from 2010-2014. Postoperative fragmentation was defined as readmission to a hospital other than the index hospital of the initial surgery. Multivariable regression analyses were used to identify predictors of fragmentation in both 30-day and 90-day readmissions. Similarly, multivariable models were developed to determine the association between fragmentation and death among women who were readmitted. A total of 10,445 patients (13.3%) were readmitted at 30 days, and 14,124 patients (18.0%) were readmitted at 90 days. Of these, there was a 20.8% and 25.7% rate of postoperative care fragmentation for 30-day and 90-day readmissions, respectively. Patient risk factors that were associated with fragmented postoperative care included Medicare insurance, lower income quartiles, and nonroutine discharge to facility. Hospital factors that were associated with decreased risk of fragmentation included operation at a metropolitan teaching hospital and performance of extended procedures. Cost and length of stay for the readmission were similar among those who had fragmented and nonfragmented readmissions at both 30 and 90 days. Although there was no association between death and fragmentation for patients who were readmitted within 30 days (odds ratio, 1.19; 95% confidence interval, 0.93-1.51), patients who had a fragmented readmission at 90 days were 22% more likely to die than those who were readmitted at 90 days to their index hospital (odds ratio, 1.22; 95% confidence interval, 1.00-1.49). Fragmentation of care is common in women with ovarian cancer who require postoperative readmission. Fragmented postoperative care is associated with an increased risk of death among women who are readmitted within 90 days of surgery.

A Nationally Representative Study of Nonindex Hospital Readmissions following Radical Prostatectomy: Implications for Bundled Payment Models

Implementing episode based payment models requires a detailed understanding of health care utilization throughout the 90-day postoperative episode. This includes nonindex hospital readmissions, which currently do not exist for patients treated with radical prostatectomy. We compared the causes, costs and predictors of index vs nonindex hospital readmissions after radical prostatectomy. We identified patients with prostate cancer who underwent radical prostatectomy from 2010 to 2014 in the Nationwide Readmissions Database. Sociodemographic factors, hospital costs and causes of 90-day readmissions were compared between index and nonindex hospital readmissions. Multivariable regression models were used to determine whether nonindex readmissions were more costly than index readmission for several causes of readmission and also to identify predictors of nonindex readmissions. Of the 214,473 patients treated with radical prostatectomy 12,316 (5.7%) experienced a 90-day readmission and 4,283 (30.6%) had a nonindex readmission. Nonindex readmissions were more likely for complications which were cardiovascular specific (16.6% vs 10.3%) and nonradical prostatectomy specific (49.4% vs 32.8%, each p <0.01). On multivariable modeling readmission costs were significantly higher for nonindex vs index readmissions ($10,751 vs $10,113, p <0.01). Cardiovascular and electrolyte related nonindex readmissions ($12,995 vs $10,108, p <0.001, and $4,962 vs $3,179, p=0.01, respectively) were more expensive. Nonindex hospital readmission predictors included minimally invasive radical prostatectomy (OR 1.28, 95% CI 1.03-1.58), radical prostatectomy done at a high volume institution (OR 2.02, 95% CI 1.41-2.89) and residence in a more rural location (less than 50,000 population OR 1.68, 95% CI 1.21-2.35). In this nationally representative study nonindex hospital readmissions were associated with higher readmission costs, which were driven by differences in a small subset of readmissions. The benefits of undergoing radical prostatectomy at a high volume center should be carefully balanced with the increased odds of nonindex hospital readmissions and higher costs associated with such centers as regionalization continues.

Causes, Risk Factors, and Costs of 30-Day Readmissions After Mitral Valve Repair and Replacement

Postsurgical readmissions are an increasingly scrutinized marker of health care quality. We sought to estimate the risk factors and costs associated with readmissions after mitral valve (MV) surgery in a large, nationally representative cohort. Adult patients undergoing MV repair or replacement were queried from the National Readmissions Database from 2010 to 2014. Data were collected on the prevalence and indications for readmission within 30 days as well as the hospital-, procedure, and patient-level risk factors as determined by multivariable logistic regression. Among 76,342 patients undergoing MV surgery, the rate of 30-day readmission was 17.0%. Those undergoing replacement procedures had significantly higher readmission rates (20.7% vs 13.1%; P < .001) compared with repair. Significant independent predictors of readmission after both MV repair and replacement included length of stay ≥8 days, chronic lung disease, chronic renal disease, and low hospital procedural volume for MV surgery. Readmissions to nonindex hospitals accounted for 26.6% of all readmissions. The most common indications for readmission were heart failure (21.4%), arrhythmia (17.0%) and respiratory diagnoses (15.0%), and infections (10.2%). The mean cost per readmission was $15,397, and among readmitted patients, the cost of readmission accounted for 17.8% of the total cost of the episode of care. Nearly 1 in 5 patients undergoing MV surgery are readmitted within 30 days. Treatment at a low-volume center was strongly associated with readmission, and much of the readmission burden falls on nonindex hospitals. Further characterization of readmissions may improve the quality of care associated with MV surgery.

Implications of Cystectomy Travel Distance for Hospital Readmission and Survival.

Regionalization of complex surgical care results in increasing need for patients to travel for complex oncologic procedures such as cystectomy in bladder cancer. We examined the association between travel distance to a cystectomy center, readmission, and survival. Using Surveillance, Epidemiology, and End Results (SEER)-Medicare data, we identified bladder cancer patients undergoing radical cystectomy during 2004-2011. Patients were grouped into quartiles of distance to cystectomy center in miles (< 6 [close], 6-16.9 [moderately close], 17-47.9 [moderately far],≥ 48 [far]). Multivariable logistic regression, accounting for clustering within hospitals, was used to assess the association between travel distance and readmission. A secondary analysis examined the association between travel distance and survival using multivariable proportional hazard regression. Among 4556 patients who underwent cystectomy, 1857 (41%) were readmitted, and 1251 (67%) of readmissions were to the index hospital. With increasing travel distance there was no significant difference in the overall rate of 90-day readmission. However, the farther a patient traveled, the lower the odds of being readmitted to the index hospital (adjusted odds ratio [95% confidence interval] as follows: moderately close, 0.43 miles [0.29-0.63]; moderately far, 0.14 miles [0.10-0.19]; and far, 0.07 [0.05-0.11]). Increasing travel distance was associated with improved survival. With greater distance traveled to a cystectomy center, rates of readmission to nonindex centers increased. Survival differences may be explained by the impact of travel burden on processes of care and case mix. Future efforts should focus on improving care coordination between index and nonindex hospitals and ensuring equitable access to cystectomy and other critical cancer services.

Frequency, predictors, and outcomes of readmission to index versus non-index hospitals after mechanical thrombectomy in patients with ischemic stroke

BackgroundStroke systems of care employ a hub-and-spoke model, with fewer centers performing mechanical thrombectomy (MT) compared with stroke-receiving centers, where a higher number offer high-level, centralized treatment to a large...

Nonindex Readmission After Ruptured Brain Aneurysm Treatment Is Associated with Higher Morbidity and Repeat Readmission

Aneurysmal subarachnoid hemorrhage (aSAH) requires complex multidisciplinary care. After initial treatment (index hospital), readmission to a different hospital (nonindex) can compromise quality of care, resulting in increased morbidity. We aimed to evaluate factors associated with nonindex readmission and evaluate association of nonindex hospital readmission on outcomes in patients with ruptured aneurysm. Readmissions within 90 days after aSAH treatment were identified in the 2010-2014 Nationwide Readmissions Database. Multivariable logistic regression identified patient and hospital characteristics associated with nonindex readmission. Separate multivariable models determined increased morbidity or risk of second readmission for nonindex readmissions. A total of 9254 patients who underwent treatment of ruptured aneurysms from 2010 to 2014 were identified. Of these, 1985 (21.5%) were readmitted within 90 days. Three hundred and fifty-five of these readmissions (17.9%) occurred to nonindex hospitals. Patients that were discharged to a skilled nursing or other facility (odds ratio [OR], 1.70; 95% confidence interval [CI], 1.27-2.28]) had higher odds of nonindex readmission, whereas patients with private insurance were associated with lower odds of nonindex readmission (OR, 0.65; 95% CI, 0.46-0.92). Patients readmitted to a nonindex (vs. index) hospital were associated with increased likelihood of major complications (OR, 1.71; 95% CI, 1.18-2.48) and second readmissions (OR, 1.51; 95% CI, 1.17-1.96). After treatment of a ruptured cerebral aneurysm, 17.9% of readmissions occurred at a nonindex hospital. These patients were at increased risk for major complications or subsequent readmissions, which may be because of care fragmentation. Interventions aimed at improving continuity of care may reduce higher morbidity associated with nonindex readmission.

Fragmentation of postoperative care after surgical management of ovarian cancer at 30 days and 90 days

Abstract Background Fragmentation of care, wherein a patient is discharged from an index hospital and undergoes an unexpected readmission to a non-index hospital, is associated with increased risk of adverse outcomes. Fragmentation is not well characterized in ovarian cancer. Objective The objective of this study was to assess risk factors and outcomes associated with fragmentation of care among women who undergo surgical treatment of ovarian cancer. Study Design The Nationwide Readmission Database was used to identify all-cause 30-day and 90-day postoperative readmissions following surgical management of ovarian cancer between 2010-2014. Postoperative fragmentation was defined as readmission to a hospital other than the index hospital of the initial surgery. Multivariable regression analyses were used to identify predictors of fragmentation in both 30-day and 90-day readmissions. Similarly, multivariable models were developed to determine the association between fragmentation and mortality among women who were readmitted. Results A total of 10,445 patients (13.3%) were readmitted at 30-days and 14,124 patients (18.0%) were readmitted at 90-days. Of these, there was a 20.8% and 25.7% rate of postoperative care fragmentation for 30-day and 90-day readmissions, respectively. Patient risk factors associated with fragmented postoperative care included Medicare insurance, lower income quartiles, and non-routine discharge to facility. Hospital factors associated with decreased risk of fragmentation included operation at a metropolitan teaching hospital, and performance of extended procedures. Cost and length of stay for the readmission were similar among those who had fragmented and non-fragmented readmissions at both 30 and 90-days. While there was no association between mortality and fragmentation for patients readmitted within 30-days (OR=1.19; 95% CI, 0.93-1.51), patients who had a fragmented readmission at 90-days were 22% more likely to die than those readmitted at 90-days to their index hospital (OR=1.22; 95% CI, 1.00-1.49) Conclusion Fragmentation of care is common in women with ovarian cancer who require postoperative readmission. Fragmented postoperative care is associated with an increased risk of mortality among women readmitted within 90-days of surgery.

Readmissions to an alternate hospital in patients undergoing vascular intervention for claudication and critical limb ischemia associated with significantly higher mortality

BackgroundHospital readmissions with 30 days after vascular surgical interventions have been associated with increased morbidity, mortality, and cost. Readmission rates, now a Centers for Medicare and Medicaid Services quality measure, have been studied in databases that have excluded certain payer types and states and have not accounted for readmission to a hospital different from that of the index admission. More accurate and nationally representative data are needed, because this fragmentation of care could lead to flawed conclusions. The purpose of the present study was to examine the incidence and risk factors for readmission to a nonindex hospital for patients admitted for claudication or critical limb ischemia (CLI). We also examined how this disruption of patient care affects mortality. MethodsThe 2013 to 2014 Nationwide Readmissions Database was queried for all patients admitted for claudication or CLI who had undergone angioplasty, lower extremity bypass, or aortobifemoral bypass. The outcomes of interest were 30- and 365-day readmission rates to any hospital, 30- and 365-day readmission rates to a nonindex hospital, and mortality rates. Multivariable logistic regression was used to identify risk factors for readmission to a nonindex hospital. The most common readmission diagnoses and diagnosis-related groups were identified. ResultsA total of 92,769 patients had been admitted with peripheral vascular disease (33,055 with claudication and 59,714 with CLI). The 30- and 365-day readmission rate was 8.97% and 21.49% and 19.26% and 40.36%, for claudication and CLI, respectively. Of the 30- and 365-day readmissions, 20.47% and 24.92% had occurred at a nonindex hospital, respectively. Significantly higher mortality rates were found for patients with 30- or 365-day readmissions to different hospitals (odds ratio, 1.4 and 1.8, respectively). Multivariable analysis revealed that procedural indication and angioplasty are not significant risk factors for readmission to a different hospital. However, female sex, length of stay >7 days, and Charlson Comorbidity Index >3 remained significant risk factors for nonindex readmissions. The most common disease groups for nonindex readmission were “septicemia and disseminated infections” (6.5%), “heart failure” (6.4%), “other vascular procedures” (6.1%), and “amputation of lower limb except toes” (4.0%). ConclusionsPreviously unreported, ≥1 in 4 readmissions after lower extremity vascular procedures for peripheral vascular disease will occur at a nonindex hospital. This fragmentation of care is associated with increased mortality and has serious implications for guiding outcome and quality measures. With a sizeable portion of patients missed by current metrics, concern exists that providers are using flawed data. Further study into social- and patient-specific risk factors might provide methods to prevent these readmissions and improve outcomes in this difficult patient population.

Differences in outcome between patients readmitted to index vs non-index hospital trusts after colorectal resection.

The clinical consequences of readmission following major surgery in the English National Health Service are unknown. This study aimed to determine differences in outcome between patients readmitted to index vs non-index trusts after major surgery. Adult patients who underwent colorectal resection in England in April 2006 to March 2017 were identified in the national Hospital Episodes Statistics dataset. Patients were included if they were readmitted as emergencies within 30days of initial discharge. The primary outcome measure was all-cause mortality within 90 days of readmission. Comparisons between patients readmitted to index vs non-index trusts were adjusted for confounders using multivariable logistic regression. Rectal resection patients were a planned subgroup. The readmission rate following colorectal resection was 15.1% (54680/364481), with 7.1% (3905/54680) readmitted to a non-index trust. The 90-day mortality following readmission was 7.1% (3874/54680) overall and 3.9% (652/16736) in the rectal resection subgroup. The reoperation rate was 19.2% (10498/54680) overall and 23.1% (3859/16736) after rectal resection. Mortality was significantly higher in non-index [10.9% (427/3905)] vs index trusts [6.8% (3447/50775), adjusted OR 1.50, 95% CI 1.34-1.68, P<0.001]. There was an annual average of 14.7 excess deaths in non-index trusts; only 1.9 of these followed surgical reoperation. In patients who underwent rectal resection, only 0.3 of the total 1.9 excess deaths each year in non-index trusts followed surgical reoperation. Despite a statistical difference, the absolute number of excess deaths attributable to readmission to a non-index trust is very low, particularly amongst patients requiring reoperation.

Incidence and predictors of readmissions to non-index hospitals after transcatheter aortic valve replacement and the impact on in-hospital outcomes: From the nationwide readmission database

IntroductionWhether readmission to non-index hospitals (where the initial procedure was not performed) could result in adverse outcomes and increased utilization of healthcare resources compared with readmission to index hospitals after transcatheter aortic valve replacement (TAVR) remains unclear. MethodsFrom January 2012 to September 2015, a nationwide readmission database was queried to identify those who were older than 50 years and had endovascular TAVR, using the International Classification of Disease, 9th Revision, Clinical Modification code 35.05. Elective readmissions were excluded. In-hospital outcomes were compared between the index and non-index hospital readmissions. A multivariable logistic regression analysis was performed to identify predictors of non-index hospital readmissions. ResultsA total of 6808 readmissions were identified of which 2564 (37.7%) were readmitted to non-index hospitals. Residents at smaller counties, metropolitan non-teaching hospitals, or hospitals at large metropolitan areas were predictors of non-index readmissions. In-hospital mortality (adjusted odds ratio [aOR] 1.27, p = 0.20), acute myocardial infarction (aOR 0.83, p = 0.53), pacemaker placement (aOR 0.97, p = 0.90), acute kidney injury (aOR 0.98, p = 0.84), and stroke (aOR 1.03, p = 0.90) were similar between index and non-index readmissions but bleeding events requiring transfusions were more frequently observed in readmissions at non-index hospitals (aOR 1.32, p = 0.025). Hospital cost (15,410 dollars vs. 16,390 dollars, p = 0.25) and length of stay (5.70 days vs. 5.65 days, p = 0.85) were comparable between groups. ConclusionsNon-index readmissions post-TAVR was relatively common but did not result in increased hospital mortality or healthcare utilization. Our results are reassuring for TAVR recipients with limited access to index hospitals.

MP29-04 READMISSION COSTS TO INDEX VS. NON-INDEX HOSPITALS FOLLOWING MAJOR UROLOGIC ONCOLOGY SURGERIES: IDENTIFYING SOURCES OF COST VARIABILITY

INTRODUCTION AND OBJECTIVES:Previous studies in non-urologic populations have demonstrated readmission to non-index hospitals can result in increased costs of care, and are a source of variation that can be targeted to decrease costs. However, this has not been well studied in urologic surgery populations. Therefore, our objective was to compare the cost of index vs. non-index readmissions following major urologic oncology surgeries.METHODS:Patients undergoing radical cystectomy (RC), prostatectomy (RP), nephrectomy (RN), and partial nephrectomy (PN) for urologic cancers were identified between 2010-2014 in the Nationwide Readmissions Database. Among patients who experienced readmission within the 90-day post-operative period, the cost of first readmission was compared between readmissions to index vs. non-index hospitals. Multivariable models controlling for patient, surgery, and hospital-level characteristics were used to determine if non-index readmission was associated with increased readmission costs...

Incidence of and risk factors associated with care fragmentation following bariatric surgery

BackgroundCurrent readmission rates do not account for readmissions to nonindex hospitals and may underestimate the actual burden of readmissions. ObjectiveUsing a nationally representative database, we sought to characterize nonindex readmissions following bariatric surgery and identify risk factors associated with readmission to a nonindex hospital. SettingPatients in the United States undergoing elective bariatric surgery. MethodsThe Nationwide Readmissions Database was used to identify a weighted sample of 545,377 patients undergoing elective bariatric surgery between 2010 and 2014. Multivariable logistic regression analysis was used to identify factors associated with readmission to a nonindex hospital. ResultsAmong all patients, 5.6% were readmitted at least once within 30 days. Within the subgroup of patients who were readmitted, 17.6% were readmitted to a different hospital than the index admission hospital. Factors independently associated with higher odds of readmission to a nonindex hospital were primary payor (Medicare: odds ratio [OR] = 1.48, 95% confidence interval [CI]: 1.24–1.75; Medicaid: OR = 1.56, 95% CI: 1.26–1.95), All Patients Refined Diagnosis Related Group severity of illness score (extreme versus minor: OR = 1.48; 95% CI: 1.04–2.09), primary procedure (laparoscopic sleeve gastrectomy versus laparoscopic gastric bypass: OR = 1.23; 95% CI: 1.05–1.44), hospital bed size (reference: small hospital, medium: OR = .52, 95% CI: .39–.70; large: OR = .47, 95% CI: .35–.63), hospital ownership (reference: private, nonprofit hospital, government: OR = 1.77, 95% CI: 1.32–2.37; private, investor-owned: OR = 1.33, 95% CI: 1.07–1.64), and hospital location (reference: metropolitan area >1 million population, metropolitan <1 million population: OR = .44, 95% CI: .34–.56; micropolitan/rural: OR = .44, 95% CI: .27–.73). ConclusionFailure to account for readmissions to different hospitals may underestimate readmission rates by approximately 18%.

INCIDENCE, PREDICTORS, AND IMPACT OF READMISSIONS TO NON-INDEX HOSPITALS AFTER TRANSCATHETER AORTIC VALVE REPLACEMENT ON IN-HOSPITAL OUTCOMES: FROM THE NATIONWIDE READMISSION DATABASE

Transcatheter aortic valve replacement (TAVR) patients often have multiple comorbidities and readmission rates within 30-days is relatively high. Readmission to non-index hospitals where the initial procedure was not performed could result in fragmentation of care and thus adverse outcomes and

Characteristics and clinical outcomes of index versus non-index hospital readmissions in Australian hospitals: a cohort study.

Objective Risk factors and clinical outcomes of non-index hospital readmissions (readmissions to a hospital different from the previous admission) have not been studied in Australia. The present study compared characteristics and clinical outcomes between index and non-index hospital readmissions in the Australian healthcare setting. Methods This retrospective cohort study included medical admissions from 2012 to 2016 across all major public hospitals in South Australia. Readmissions within 30 day to all public hospitals were captured using electronic health information system. In-hospital mortality and readmission length of hospital stay (LOS) were compared, along with 30-day mortality and subsequent readmissions among patients readmitted to index or non-index hospitals. Results Of 114105 index admissions, there were 20539 (18.0%) readmissions. Of these, 17519 (85.3%) were index readmissions and 3020 (14.7%) were non-index readmissions. Compared with index readmissions, patients in the non-index readmissions group had a lower Charlson comorbidity index, shorter LOS and fewer complications during the index admission and were more likely to be readmitted with a different diagnosis to the index admission. No difference in in-hospital mortality was observed, but readmission LOS was shorter and 30-day mortality was higher among patients with non-index readmissions. Conclusion A substantial proportion of patients experienced non-index hospital readmissions. Non-index hospital readmitted patients had no immediate adverse outcomes, but experienced worse 30-day outcomes. What is known about the topic? A significant proportion of unplanned hospital readmissions occur to non-index hospitals. North American studies suggest that non-index hospital readmissions are associated with worse outcomes for patients due to discontinuity of care, medical reconciliation and delayed treatment. Limited studies have determined factors associated with non-index hospital readmissions in Australia, but whether such readmissions lead to adverse clinical outcomes is unknown. What does this paper add? In the Australian healthcare setting, 14.7% of patients were readmitted to non-index hospitals. Compared with index hospital readmissions, patients admitted to non-index hospitals had a lower Charlson comorbidity index, a shorter index LOS and fewer complications during the index admission. At the time of readmission there was no differences in discharge summary completion rates between the two groups. Unlike other studies, the present study found no immediate adverse outcomes for patients readmitted to non-index hospitals, but 30-day outcomes were worse than for patients who had an index hospital readmission. What are the implications for practitioners? Non-index hospital readmissions may not be totally preventable due to factors such as ambulance diversions stemming from emergency department overcrowding and prolonged emergency department waiting times. Patients should be advised to re-present to hospital in case they experience recurrence or relapse of a medical condition, and preferably should be readmitted to the same hospital to prevent discontinuity of care.

Fragmented Care is Prevalent Among Inflammatory Bowel Disease Readmissions and is Associated With Worse Outcomes

Inflammatory bowel disease (IBD) is a complex chronic disease that often requires a multispeciality approach; thus, IBD patients are prone to care fragmentation. We aim to determine the prevalence of fragmentation among hospitalized IBD patients and identify associated predictors and visit-level outcomes. The State Inpatient Databases for New York and Florida were used to identify 90-day readmissions among IBD inpatients from 2009 to 2013. The prevalence of fragmentation, defined as a readmission to a non-index hospital, was reported. Characteristics associated with fragmented care were identified using multivariable logistic regression. Multivariable models were utilized to determine the association between fragmentation and outcomes (in-hospital mortality, readmission length of stay, and inpatient colonoscopy). Among IBD inpatients, 25,241 and 29,033 90-day readmission visits were identified, in New York and Florida, respectively. The prevalence of fragmentation was 26.4% in New York and 32.5% in Florida. Younger age, a non-emergent admission type, public payer or uninsured status, mood disorder, and substance abuse were associated with fragmented care, while female gender and a primary diagnosis of an IBD-related complication had an inverse association. Fragmented inpatient care is associated with a higher likelihood of in-hospital death, higher rates of inpatient colonoscopy, and a longer readmission length of stay. Over one in four IBD inpatient readmissions are fragmented. Disparities and differences in fragmentation exist and contribute to poor patient outcomes. Additional efforts targeting fragmentation should be made to better coordinate IBD management, reduce healthcare gaps, and promote high-value care.

Multilevel Analysis of Readmissions After Radical Cystectomy for Bladder Cancer in the USA: Does the Hospital Make a Difference?

BackgroundHospitals are increasingly being held responsible for their readmissions rates. The contribution of hospital versus patient factors (eg, case mix) to hospital readmissions is unknown. ObjectiveTo estimate the relative contribution of hospital and patient factors to readmissions after radical cystectomy (RC) for bladder cancer. Design, setting, and participantsWe identified individuals who underwent RC in 2014 in the Nationwide Readmissions Database (NRD). The NRD is a nationally representative (USA), all-payer database that includes readmissions at index and nonindex hospitals. Survey weights were used to generate national estimates. Outcome measurements and statistical analysisThe main outcome was readmission within 30 d after RC. Using a multilevel mixed-effects model, we estimated the statistical association between patient and hospital characteristics and readmission. A hospital-level random-effects term was used to estimate hospital-level readmission rates while holding patient characteristics constant. Results and limitationsWe identified a weighted sample of 7095 individuals who underwent RC at 341 hospitals in the USA. The 30-d readmission rate was 29.5% (95% confidence interval [CI] 27.8–31.2%), ranging from 1.4% (95% CI 0.6–2.2%) in the bottom quartile to 73.6% (95% CI 68.4–78.7) in the top. In our multilevel model, female sex and comorbidity score were associated with a higher likelihood of readmission. The hospital random-effects term, encompassing both measured and unmeasured hospital characteristics, contributed minimally to the model for readmission when patient characteristics were held constant at population mean values (pseudo-R2<0.01% for hospital effects). Surgical volume, bed size, hospital ownership, and academic status were not significantly associated with readmission rates when these terms were added to the model. ConclusionsAfter adjusting for patient characteristics, hospital-level effects explained little of the large between-hospital variability in readmission rates. These findings underscore the limitations of using 30-d post-discharge readmissions as a hospital quality metric. Patient summaryThe chance of being readmitted after radical cystectomy varies substantially between hospitals. Little of this variability can be explained by hospital-level characteristics, while far more can be explained by patient characteristics and random variability.

Patterns of readmission among the elderly after hepatopancreatobiliary surgery

BackgroundThe objective of this study was to examine risk factors and outcomes of hospital readmission following complex hepatopancreatobiliary (HPB) surgery among the elderly. MethodsThe Nationwide Readmissions Database was queried for patients ≥ 60 years who underwent HPB surgery during 2010–2015. ResultsThe incidence of 30- and 90-day readmission was similar among patients 60–74 vs. ≥75 (P > 0.05). Patients age 60–74 years with ≥2 comorbidities had an increased odds of 30-day (OR 1.13, p = 0.021) and 90-day (OR 1.13, p = 0.005) readmission. Patients ≥75 years with ≥2 comorbidities had the highest in-hospital mortality (5%) whereas patients 60–74 years with 0 or 1 comorbidity had the lowest in-hospital mortality on readmission (3%). ConclusionFollowing an HPB procedure, roughly 1 in 7 elderly patients were readmitted within 30 days and 1 in 4 patients within 90 days. Elderly patients with multiple comorbidities were more likely to be readmitted at non-index hospitals.

Frequency of hospital readmission and care fragmentation in gastroparesis: A nationwide analysis.

AIMTo evaluate rates and predictors of hospital readmission and care fragmentation in patients hospitalized with gastroparesis.METHODSWe identified all adult hospitalizations with a primary diagnosis of gastroparesis in the 2010-2014 National Readmissions Database, which captures statewide readmissions. We excluded patients who died during the hospitalization, and calculated 30 and 90-d unplanned readmission and care fragmentation rates. Readmission to a non-index hospital (i.e., different from the hospital of the index admission) was considered as care fragmentation. A multivariate Cox regression model was used to analyze predictors of 30-d readmissions. Logistic regression was used to determine hospital and patient factors independently associated with 30-d care fragmentation. Patients readmitted within 30 d were followed for 60 d post discharge from the first readmission. Mortality during the first readmission, hospitalization cost, length of stay, and rates of 60-d readmission were compared between those with and without care fragmentation.RESULTSThere were 30064 admissions with a primary diagnosis of gastroparesis. The rates of 30 and 90-d readmissions were 26.8% and 45.6%, respectively. Younger age, male patient, diabetes, parenteral nutrition, ≥ 4 Elixhauser comorbidities, longer hospital stay (> 5 d), large and metropolitan hospital, and Medicaid insurance were associated with increased hazards of 30-d readmissions. Gastric surgery, routine discharge and private insurance were associated with lower 30-d readmissions. The rates of 30 and 90-d care fragmentation were 28.1% and 33.8%, respectively. Younger age, longer hospital stay (> 5 d), self-pay or Medicaid insurance were associated with increased risk of 30-d care fragmentation. Diabetes, enteral tube placement, parenteral nutrition, large metropolitan hospital, and routine discharge were associated with decreased risk of 30-d fragmentation. Patients who were readmitted to a non-index hospital had longer length of stay (6.5 vs 5.8 d, P = 0.03), and higher mean hospitalization cost ($15645 vs $12311, P < 0.0001), compared to those readmitted to the index hospital. There were no differences in mortality (1.0% vs 1.3%, P = 0.84), and 60-d readmission rate (55.3% vs 54.6%, P = 0.99) between the two groups.CONCLUSIONSeveral factors are associated with the high 30-d readmission and care fragmentation in gastroparesis. Knowledge of these predictors can play a role in implementing effective preventive interventions to high-risk patients.