Medium-volume Centers Research Articles

Thirty-day readmission rates, trends and its impact on liver transplantation recipients: a national analysis

Reduction of early hospital readmissions is a declared goal in the United States economic and quality improvement agenda. A retrospective study was performed using the Nationwide Readmissions Database from 2010 to 2014. Our primary aim was to study the rate of early readmissions and its predictors in liver transplant recipients (LTRs). Our secondary aims were to determine the trends of LT, reasons for readmission, costs and predictors of calendar year mortality. Multivariable logistic regression and Cox proportional hazards models were utilized. The 30-day readmission rate was 30.6% among a total of 25,054 LTRs. Trends of LT were observed to be increased in patients > 65 years (11.7–17.8%, p < 0.001) and decreased in 40–64 years (78.0–73.5%, p = 0.001) during study period. The majority of 30-day readmissions were due to post transplant complications, with packed red blood cell transfusions being the most common intervention during readmission. Medicaid or Medicare insurance, surgery at low and medium volume centers, infections, hemodialysis, liver biopsy, and length of stay > 10 days were the predictors of 30-day readmission. Moreover, number of early readmission, age > 64 years, non-alcoholic cirrhosis, and length of stay > 10 days were significant predictor of calendar year mortality in LTRs. Approximately one third of patients require early admission after LT. Early readmission not only increases burden on healthcare, but is also associated with calendar year mortality. Strategies should be implemented to reduce readmission in patients with high risk of readmission identified in our study.

Re-defining a high volume center for pancreaticoduodenectomy

BackgroundThe purpose of this study was to re-evaluate the previously utilized definitions of high volume center for pancreaticoduodenectomy to determine/establish an objective, evidence based threshold of hospital volume associated with improvement in perioperative mortality. MethodsPatients who underwent pancreaticoduodenectomy were identified using the National Cancer Database from 2004 to 2015. The relationship between hospital volume and 90-day mortality was assessed using a logistic regression model. Receiver Operator Characteristic analysis was performed and Youden's statistic was utilized to calculate the optimal cut offs. Results42,402 patients underwent elective Pancreaticoduodenectomy at 1238 unique hospitals. A logistic regression was performed which showed a significant inverse linear association between institutional volume and overall 90 day mortality. The maximum improvement in 90 day mortality is seen if the average annual hospital volume was greater than 9 (OR = 0.647 (0.595–0.702), p < 0.0001). When analysis is limited to hospitals that performed >9 cases per year, the maximum improvement in 90 day mortality was noticed at 36 cases per year (OR = 0.458 (0.399–0.525), p < 0.0001). ConclusionsBased on our results, we recommend defining low, medium, and high volume centers for pancreaticoduodenectomy as hospitals with average annual volume less than 9, 9 to 35, and more than 35 cases per year, respectively.

Impact of Mitral Valve Repair Case Volume on Postoperative Mortality - A Nationwide Korean Cohort Study.

Although mitral valve repair is recommended over replacement due to better outcomes, repair rates vary significantly among centers. This study examined the effect of institutional mitral valve repair volume on postoperative mortality. All cases of adult mitral valve repair performed in Korea between 2009 and 2016 were analyzed. The association between case volume and 1-year mortality was analyzed after categorizing centers according to the number of mitral valve repairs performed as low-, medium-, or high-volume centers (<20, 20-40, and >40 cases/year, respectively). The effect of case volume on cumulative all-cause mortality was also assessed. In all, 6,041 mitral valve repairs were performed in 86 centers. The 1-year mortality in low-, medium-, and high-volume centers was 10.1%, 8.7%, and 4.7%, respectively. Low- and medium-volume centers had increased risk of 1-year mortality compared with high-volume centers, with odds ratios of 2.80 (95% confidence interval [CI] 2.15-3.64; P<0.001) and 2.66 (95% CI 1.94-3.64; P<0.001), respectively. The risk of cumulative all-cause mortality was also worse in low- and medium-volume centers, with hazard ratios of 1.96 (95% CI 1.68-2.29; P<0.001) and 1.77 (95% CI 1.47-2.12; P<0.001), respectively. Lower institutional case volume was associated with higher mortality after mitral valve repair. A minimum volume standard may be required for hospitals performing mitral valve repair to guarantee adequate outcome.

Association between institutional case volume and mortality following thoracic aorta replacement: a nationwide Korean cohort study

BackgroundThe inverse relationship between case volume and postoperative mortality following high-risk surgical procedures have been reported. Thoracic aorta surgery is associated with one of the highest postoperative mortality. The relationship between institutional case volume and postoperative mortality in patients undergoing thoracic aorta replacement surgery was evaluated.MethodsAll thoracic aorta replacement surgeries performed in Korea between 2009 and 2016 in adult patients were analyzed using an administrative database. Hospitals were divided into low (< 30 cases/year), medium (30–60 cases/year), or high (> 60 cases/year) volume centers depending on the annual average number of thoracic aorta replacement surgeries performed. The impact of case volume on in-hospital mortality was assessed using the logistic regression.ResultsAcross 83 hospitals, 4867 cases of thoracic aorta replacement were performed. In-hospital mortality was 8.6% (191/2222), 10.7% (77/717), and 21.9% (422/1928) in high, medium, and low volume centers, respectively. The adjusted risk of in-hospital mortality was significantly higher in medium (odds ratio [OR], 1.56; 95% confidence interval [CI], 1.16–2.11, P = 0.004) and low volume centers (OR, 3.12; 95% CI, 2.54–3.85, P < 0.001) compared to high volume centers.ConclusionsPatients who had underwent thoracic aorta replacement surgery in lower volume centers had increased risk of in-hospital mortality after surgery compared to those in higher volume centers. Our results may provide the basis for minimum case volume requirement or regionalization in thoracic aorta replacement surgery for optimal patient outcome.

Higher Institutional Volume Reduces Mortality in Reoperative Proximal Thoracic Aortic Surgery.

Objective This study aims to determine the impact of institutional volume on mortality in reoperative proximal thoracic aortic surgery patients using national outcomes data. Methods The Nationwide Inpatient Sample was queried from 1998 to 2011 for patients with diagnoses of thoracic aneurysm and/or dissection who underwent open mediastinal repair. A total of 103,860 patients were identified. A total of 1,430 patients had prior cardiac surgery. Patients were further stratified into groups by institutional aortic volume: low (<12 cases/year), medium (12–39 cases/year), and high (40+ cases/year) volume. Multivariable risk-adjusted analysis accounting for emergent status and aortic dissection among other factors was performed to determine the impact of institutional volume on mortality. Results Overall mortality was 12% in the reoperative population. When the redo cohort was divided into tertiles, high-volume group had a 5% operative mortality compared with 9 and 15% for the medium- and low-volume groups, respectively. Multivariable analysis revealed that patients operated on at low- (odds ratio [OR] = 5.0, 95% confidence interval [CI]: 2.6–9.6, p < 0.001) and medium-volume centers (OR = 2.1, 95% CI: 1.1–4.2, p = 0.03) had higher odds of mortality when compared with patients operated on at high-volume centers. Conclusions High-volume aortic centers can significantly reduce mortality for reoperative aortic surgery, compared with lower volume institutions.

Thoracic Endovascular Aneurysm Repair Trends and Outcomes in Over 27,000 Medicare Patients for Descending Thoracic Aneurysms

Since United States Food and Drug Administration approval in 2005, thoracic endovascular aneurysm repair (TEVAR) has replaced open surgery to become the preferred treatment for descending thoracic aneurysms (DTAs). This study investigated TEVAR trends during the previous 15 years regarding patient and hospital characteristics and their effect on survival. Between 2000 and 2014, 27,079 Medicare patients underwent TEVAR for DTA. We analyzed TEVAR trends during this period and stratified hospitals based on the number of cases completed during the previous 5 years: low (0-19 cases), medium (20-99 cases), and high (≥100 cases) volume. Trends over time were calculated using Poisson regression to determine the average annual percentage changes (aAPC). Survival was calculated using a multivariate Cox regression and adjusted logistic regression with a restricted cubic spline. TEVAR volume significantly increased from 81 cases in 2000 to 3478 cases in 2014 (aAPC, 16.2%; P<.001). During the study period, the proportion of cases performed at medium-volume centers increased (aAPC, 5.2%; P < .001). Thirty-day mortality after TEVAR increased in the recent period (2013-2014) to 8.8% as compared with 6.6% in the early years (2004-2006) of TEVAR (P < .001), and a significant contribution was due to increased patient comorbidity score (aAPC, 1.6%; P < .001). Lastly, TEVAR center volume was significantly associated with 30-day survival when fewer than 33 cases were done in the prior 5 years. From 2000 to 2014, TEVAR volume accelerated, and centers are gaining more experience. TEVAR patients have become more acute, and mortality has increased over this period. Patient selection and procedural experience are critical to improving outcomes.

Disposable chlorine dioxide wipes for high-level disinfection in the ENT department: A systematic review.

Nasopharyngoscope reprocessing methods should be effective, rapid and reproducible with moderate cost. Tristel Trio Wipes system (TTWS) is a manual reprocessing method based on chlorine dioxide that has lately emerged in ENT department. This review aims to collect evidence on this system. The PubMed, Web of Science and Cochrane Library databases were searched for all the studies on TTWS or one of its components. Data were grouped according to the study type. Ten articles were included in the review. TTWS ensured high-level disinfection in laboratory and clinical setting. Although the limitations of the manual systems, TTWS proved to be faster than automated endoscope reprocessing (AER) and safe for patients and health-care workers. TTWS represented cheaper system than AER or sheaths in low- and medium-volume centers. TTWS could be a valid, safe and fast HLD method for nasopharyngoscopes, with reasonable costs for medium-low reprocessing volumes.

P205 THREE YEARS EXPERIENCE OF THE FIRST SPECIALIZED ESOPHAGEAL CENTER IN EGYPT

Abstract Introduction Subspecialty policy is increasing all over the world aiming to improve the results of heavy esophageal surgeries. Aim To define the impact of having surgical specialized esophageal unit on the volume of patients and the results. Methodology We reviewed all esophageal cases managed in our esophageal specialized department (from May 2016 to May 2019 Group A) and we compared the results to previous 3 years (from May 2013 to May 2016 Group B) and to the international results. Results Esophageal surgeries performed during this period was 394 cases in group A compared to 104 cases in group B. One hundred eighty operations were performed for Gastro esophageal reflux disease (GERD) in group a (45.7%) compared to 61 cases in group B (68.7%). Forty two (10.7%) modified Heller’s cardiomyotomy (Open and laparoscopic) for achalasia were performed in group A compared to 17 cases (16.3%) in group B. Surgeries for malignant lesions were performed for 122 cases (30.9%) in group A compared to 13 cases (12.5%) in group B. Other Esophageal operations were also done for 50 cases (12.7%) in group A compared to 13 cases (12.5%) in group B. Mortalities in group A was 5 cases in benign diseases (1.8%) and 13 cases for malignant cases (10.7%) compared to 7 cases in benign diseases (7.7%) and 5 cases for malignant conditions (23%) in group B. Morbidities in group A was 46 cases in benign diseases (16.9%) and 31cases for malignant cases (25.4%) Compared to 23 cases in the benign diseases (25.2%) and 5 cases for malignant conditions (38.5%) in group B. Our results in group A are comparable to Hospital mortality rates for patients in medium-volume centers (7.5%)(1).Also we approach the International results for morbidities of benign esophageal disease (5.7 to- 12.7%) for fundoplication (2). Conclusion Having a specialized esophageal unit resulted in increase of the volume of patients and improvement of the results.

Evaluation of Risk Factors for Heart-Lung Transplant Recipient Outcome: An Analysis of the United Network for Organ Sharing Database.

Heart-lung transplantation (HLTx) is an effective treatment for patients with advanced cardiopulmonary failure. However, no large multicenter study has focused on the relationship between donor and recipient risk factors and post-HLTx outcomes. Thus, we investigated this issue using data from the United Network for Organ Sharing database. All adult patients (age ≥18 years) registered in the United Network for Organ Sharing database who underwent HLTx between 1987 and 2017 were included (n=997). We stratified the cohort by patients who were alive without retransplant at 1 year (n=664) and patients who died or underwent retransplant within 1 year of HLTx (n=333). The primary outcome was the influence of donor and recipient characteristics on 1-year post-HLTx recipient death or retransplant. Kaplan-Meier curves were created to assess overall freedom from death or retransplant. To obtain a better effect estimation on hazard and survival time, the parametric Accelerated Failure Time model was chosen to perform time-to-event modeling analyses. Overall graft survival at 1-year post-HLTx was 66.6%. Of donors, 53% were male, and the mean age was 28.2 years. Univariable analysis showed advanced donor age, recipient male sex, recipient creatinine, recipient history of prior cardiac or lung surgery, recipient extracorporeal membrane oxygenation support, transplant year, and transplant center volume were associated with 1-year post-HLTx death or retransplant. On multivariable analysis, advanced donor age (hazard ratio [HR], 1.017; P=0.0007), recipient male sex (HR, 1.701; P=0.0002), recipient extracorporeal membrane oxygenation support (HR, 4.854; P<0.0001), transplant year (HR, 0.962; P<0.0001), and transplantation at low-volume (HR, 1.694) and medium-volume centers (HR, 1.455) in comparison with high-volume centers (P=0.0007) remained as significant predictors of death or retransplant. These predictors were incorporated into an equation capable of estimating the preliminary probability of graft survival at 1-year post-HLTx on the basis of preoperative factors alone. HLTx outcomes may be improved by considering the strong influence of donor age, recipient sex, recipient hemodynamic status, and transplant center volume. Marginal donors and recipients without significant factors contributing to poor post-HLTx outcomes may still be considered for transplantation, potentially with less impact on the risk of early postoperative death or retransplant.

Impact of mitral valve repair case volume on postoperative mortality: a population-based observational study

Introduction Although mitral valve repair is recommended over replacement when feasible due to its better outcomes, repair rates vary remarkably between cardiac surgery centers. The aim of this study is to examine the effect of institutional case volume on mortality after mitral valve repair. Methods We analyzed all cases of adult mitral valve repair performed in Korea between 2007 and 2016 using administrative data. The association between case volume and 1-year mortality after mitral valve repair was analyzed after categorizing centers depending on the number of mitral valve repairs performed; low- ( 20 and 40 cases/year, reference) volume centers. The effect of case volume on cumulative all-cause mortality was also assessed. Results A total of 6041 cases were performed in 86 centers. One-year mortality was 10.1% (175/1728), 8.7% (93/1067), and 4.7% (153/3246) in low-, medium-, and high-volume centers, respectively. Low- and medium-volume centers showed increased risk of 1-year mortality compared to high-volume centers (OR [95% CI]; 2.80 [2.15–3.64] and 2.66 [1.94–3.64], respectively.). The risk of cumulative all-cause mortality of up to 10 years was also worse in low- and medium-volume centers (HR [95% CI]; 1.96 [1.68–2.29] and 1.77 [1.47–2.12], respectively.). Discussion Lower case-volume was associated with higher risk of mortality after mitral valve repair. A minimum case volume may be required for hospitals performing mitral valve repair to guarantee adequate patient outcome.

Introduction of a mobile device based tertiary survey application reduces missed injuries: A multi-center prospective study

BackgroundMissed injuries during the initial assessment are a major cause of morbidity after trauma. The tertiary survey is a head-to-toe exam designed to identify any injuries missed after initial resuscitation. We designed a novel mobile device application (Physician Assist Trauma Software [PATS]) to standardize performance and documentation of the tertiary survey. This study was undertaken to assess the feasibility of introducing PATS into routine clinical practice, as well as its capacity to reduce missed injuries. MethodsPrior to implementation of PATS, the missed injury rates at a higher-volume and a medium-volume level I trauma center were assessed. The PATS program was implemented simultaneously at both centers. Missed injuries were tracked during the study period. Compliance and tertiary survey completion rates were evaluated as a marker of feasibility. ResultsAt the higher-volume trauma center, the missed injury rated decreased from 1% to 0% with the introduction of the PATS program (p = 0.04). At the medium-volume trauma center, the missed injury rate decreased from 9% to 1% (p < 0.001). Compliance and documentation increased from 68% to 100%, and from no formal documentation to 60% compliance at the higher- and medium-volume centers respectively. ConclusionsThe implementation of a mobile tertiary survey application significantly reduced missed injuries at both a higher- and medium-volume trauma center. The use of this application resulted in a significant improvement in compliance with documentation of the tertiary survey.

Site Experience and Outcomes in the Trevo Acute Ischemic Stroke (TRACK) Multicenter Registry.

Background and Purpose- It remains unclear how experience influences outcomes after the advent of stent retriever technology. We studied the relationship between site experience and outcomes in the Trevo Acute Ischemic Stroke multicenter registry. Methods- The 24 sites that enrolled patients in the Trevo Acute Ischemic Stroke registry were trichotomized into low-volume (<2 cases/month), medium-volume (2-4 cases/month), and high-volume centers (>4 cases/month). Baseline features, imaging, and clinical outcomes were compared across the 3 volume strata. A multivariable analysis was performed to assess whether outcomes were influenced by site volumes. Results- A total of 624 patients were included and distributed as low- (n=188 patients, 30.1%), medium- (n=175, 28.1%), and high-volume (n=261, 41.8%) centers. There were no significant differences in terms of age (mean, 66±16 versus 67±14 versus 65±15; P=0.2), baseline National Institutes of Health Stroke Scale (mean, 17.6±6.5 versus 16.8±6.5 versus 17.6±6.9; P=0.43), or occlusion site across the 3 groups. Median (interquartile range) times from stroke onset to groin puncture were 266 (181.8-442.5), 239 (175-389), and 336.5 (221.3-466.5) minutes in low-, medium-, and high-volume centers, respectively (P=0.004). Higher efficiency and better outcomes were seen in higher volume sites as demonstrated by shorter procedural times (median, 97 versus 67 versus 69 minutes; P<0.001), higher balloon guide catheter use (40% versus 36% versus 59%; P≤0.0001), and higher rates of good outcome (90-day modified Rankin Scale [mRS], ≤2; 39% versus 50% versus 53.4%; P=0.02). There were no appreciable differences in symptomatic intracranial hemorrhage or 90-day mortality. After adjustments in the multivariable analysis, there were significantly higher chances of achieving a good outcome in high- versus low-volume (odds ratio, 1.67; 95% CI, 1.03-2.7; P=0.04) and medium- versus low-volume (odds ratio, 1.75; 95% CI, 1.1-2.9; P=0.03) centers, but there were no significant differences between high- and medium-volume centers (P=0.86). Conclusions- Stroke center volumes significantly influence efficiency and outcomes in mechanical thrombectomy.

National Practice Patterns and Early Outcomes of Aortic Valve Replacement in Children and Teens

Several options exist for aortic valve replacement (AVR) in children and teens, but contemporary practice patterns and outcome data are lacking. We describe national AVR practice patterns and early outcomes. Children (aged 1 to 18 years) in The Society of Thoracic Surgeons Congenital Heart Surgery Database undergoing AVR from 2000 to 2016 were included. Preoperative characteristics, operative data, and outcomes were described. To evaluate practice patterns, centers were assigned tertiles by aortic valve surgical volume. Statistical comparisons included Mann-Whitney U statistic, Kruskal-Wallis, χ2 test, and gamma testing. In total, 3446 operations (46% children aged 1 to 12 years; 54% teens aged 12 to 18 years) were included. Preoperative risk factors were present in 23%, and 46% had a prior sternotomy. Valve utilization included autograft (64% child, 37% teen), mechanical (19% child, 35% teen), bioprosthetic (8% child, 20% teen), and homograft (9% child, 7% teen). Autografts were utilized more often for teenage girls than for teenage boys (odds ratio 1.3, 95% confidence interval: 1.05 to 1.66, P < .05). Overall, inpatient mortality and major complications affected 1% and 10%, respectively, and these rates were highest for homografts (5%, P < .001, and 13%, P < .05). Autograft utilization varied widely across centers (10th to 90th percentile: 21% to 71% of total AVR volume). More autografts were utilized at high-volume centers vs low- or medium-volume centers (53% ± 2.3% vs 46% ± 2.6%, P < .001). Practice patterns for AVR in children and teens vary across centers, age groups, and sexes. Although early outcomes were similar across valve types, homografts had higher morbidity and mortality. Valve choice was related to aortic valve surgical volume. Further efforts are needed to understand and optimize AVR practice patterns and long-term outcomes.

Relation of Hospital Volume With In-Hospital and 90-Day Outcomes After Transcatheter Mitral Valve Repair Using MitraClip

MitraClip therapy has shown increasing use since it was commercially adopted among US hospitals in October 2013. However, the relation of institutional MitraClip volume with outcomes is unclear. This study sought to examine the association between hospital volume and outcomes after transcatheter mitral valve repair using the MitraClip device. Using the Nationwide Readmissions Database, we identified all patients who underwent a MitraClip procedure and categorized hospitals into tertiles based on their annual procedure volume: low (≤3 procedures/year), medium (4 to 13/year), and high (≥14/year) volume centers. Multivariable logistic and Cox regression analyses were performed to examine the impact of institutional MitraClip volume on in-hospital and 90-day outcomes, respectively. From 2014 to 2015, a total of 3,420 procedures were performed at 266 hospitals with a median annual procedural volume of 5 per hospital. Low (n = 81), medium (n = 86), and high (n = 99) volume hospitals performed 147 (4.3%), 403 (11.8%), and 2,870 (83.9%) MitraClip procedures, respectively. The low versus high hospital volume was independently associated with increased in-hospital mortality (7.8% vs 3.0%; adjusted odds ratio [aOR] 2.64; p = 0.04), acute myocardial infarction (10.2% vs 2.2%; aOR 2.93; p = 0.02), and acute respiratory failure (19.3% vs 7.7%; aOR 2.24; p = 0.02) during index admission as well as 90-day all-cause readmissions (37.8% vs 26.6%; adjusted hazard ratio 1.54; p = 0.03), and 90-day infective endocarditis (2.4% vs 0.3%; adjusted hazard ratio 10.06; p = 0.003). In conclusion, low hospital MitraClip volume is an independent determinant of worse outcomes including in-hospital mortality and 90-day readmissions.

Transplant Volume Is Associated With Graft Acceptance Threshold and Center Resource Availability

Heart transplant volume varies significantly among centers. We hypothesized that centers where the transplant team routinely accepts organs previously declined by other centers and where operating room availability is unrestricted have higher transplant volumes. We used the potential transplant recipient sequence number in the United Network for Organ Sharing database as a surrogate for graft acceptance threshold and the number of transplantations occurring on weekends and 8 major holidays as a marker of center resource availability. Centers were classified as low-, medium-, or high-volume if the average annual number of transplants were, respectively, <10, 10-30, or >30 over a 10-year period. From July 12, 2006, to December 31, 2015, 19,054 transplants were performed by 142 centers. There were 59 low-volume centers, 69 medium-volume centers, and 14 high-volume centers with median potential transplant recipient sequence numbers for transplanted candidates of 7 (interquartile range 3-11), 7 (5-10), and 15 (7-40), respectively (P = .002). The median proportion of off-hours transplantations performed by medium-volume centers was 28% (25%-31%) compared with 32% (29%-33%) by high-volume centers (P = .009). Five-year survival was equivalent among all centers (P = .053). Transplants for candidates with high sequence numbers and unrestricted operating room availability are associated with increased center volume without sacrificing post-transplantation survival.

Impact of Center Volume on Post Heart Transplant Survival

Purpose Previous studies have shown reduced 1-year post-transplant survival in low volume centers. We aimed to evaluate impact of center volume on post heart transplant survival in recent era of streamlined care. Methods The United Network of Organ Sharing (UNOS) database was queried for patients aged ≥ 18 years undergoing heart transplant between 2007-2016. The database was then merged to 2010 US census data and CDC 2015 heart failure mortality data. Center volume was available in encrypted center codes and divided in terciles ( 22-high) after removing centers that did not transplant organs since 2014. The available data was then evaluated with a cox-regression model to identify impact of center volume, UNOS regions, adjusting for individual patient level factors. Kaplan-Meier curves were computed to evaluate survival differences in center volume by UNOS regions. Results There were 111 centers included in the final dataset. There were 23 low, 52 medium and 36 high volume centers that performed 1084 (5%), 7995 (35%) and 13520 (60%) heart transplants respectively. Low volume centers had equivalent survival to medium and high volume centers across all UNOS regions except region 10 (Figure 1). A cox-regression model adjusting for recipient and donor factors showed that high volume centers in regions 2 (HR=0.79 (0.67-0.94)), 4 (HR=0.65 (0.46-0.92)) and 10 (HR=0.44 (0.30-0.63)) had significantly better survival whereas in region 8 they had worse survival (HR=2.0 (1.2-3.4))(Figure 2). Conclusion Post heart transplant survival at low and medium volume centers across all UNOS regions is comparable to high volume centers except in regions 2, 4 and 10.

Effect of Institutional Kidney Transplantation Case-Volume on Post-Transplant Graft Failure: a Retrospective Cohort Study.

BackgroundThe impact of institutional case volume to graft failure rate after adult kidney transplantation is relatively unclear compared to other solid organ transplantations.MethodsA retrospective cohort study of 13,872 adult kidney transplantations in Korea was performed. Institutions were divided into low- (< 24 cases/year), medium- (24–60 cases/year), and high- (> 60 cases/year) volume centers depending on the annual case volume. One-year graft failure rate was defined as the proportion of patients who required dialysis or re-transplantation at one year after transplantation. Postoperative in-hospital mortality and long-term graft survival were also measured.ResultsAfter adjustment, one year graft failure was higher in low-volume centers significantly (adjusted odds ratio [aOR], 1.50; 95% confidence interval [CI], 1.26–1.78; P < 0.001) and medium-volume centers (aOR, 1.87; 95% CI, 1.57–2.23; P < 0.001) compared to high-volume centers. Low-volume centers had significantly higher mortality (aOR, 1.75; 95% CI, 1.15–2.66; P = 0.01) than that of high-volume centers after adjustment. Long-term graft survival of up to 9 years was superior in high-volume centers compared to low- and medium-volume centers (P < 0.001).ConclusionHigher-case volume centers were associated with lower one-year graft failure rate, lower in-hospital mortality, and higher long-term graft survival after kidney transplantation.

Effect of Institutional Case Volume on In-Hospital and Long-Term Mortality in Critically Ill Patients Requiring Mechanical Ventilation for 48 Hours or More.

BackgroundThe purpose of this study was to evaluate whether institutional case volume affects clinical outcomes in patients receiving mechanical ventilation for 48 hours or more.MethodsWe conducted a nationwide retrospective cohort study using the database of Korean National Healthcare Insurance Service. Between January 2007 and December 2016, 158,712 adult patients were included at 55 centers in Korea. Centers were categorized according to the average annual number of patients: > 500, 500 to 300, and < 300.ResultsIn-hospital mortality rates in the high-, medium-, and low-volume centers were 32.6%, 35.1%, and 39.2%, respectively. After adjustment, in-hospital mortality was significantly higher in low-volume centers (adjusted odds ratio [OR], 1.332; 95% confidence interval [CI], 1.296–1.368; P < 0.001) and medium-volume centers (adjusted OR, 1.125; 95% CI, 1.098–1.153; P < 0.001) compared to high-volume centers. Long-term survival for up to 8 years was better in high-volume centers.ConclusionCenters with higher case volume (> 500 patients/year) showed lower in-hospital mortality and long-term mortality, compared to centers with lower case volume (< 300 patients/year) in patients who required mechanical ventilation for 48 hours or more.

Effect of Institutional Case Volume on In-Hospital Mortality After Deceased Donor Liver Transplantation: A Nationwide Retrospective Cohort Study in Korea

BackgroundThere is still controversy as to whether the case volume affects clinical outcomes after liver transplantation. This nationwide retrospective cohort study aimed to investigate the relationship between institutional case volume and post-transplant outcomes after deceased donor liver transplantation. Material and MethodsThe data was extracted from the database of Korean National Healthcare Insurance Service. A total of 2648 adult deceased donor liver transplantations were performed at 54 centers in Korea from January 2007 to December 2016. Centers were divided into high-, medium-, and low-volume centers according to the average annual number of deceased donor liver transplantations as follows: < 10, 10–30, and >30. ResultsIn-hospital mortality rates in high-, medium-, and low-volume centers were 10.3%, 14.3%, and 17.1%, respectively. Multivariable logistic regression analysis revealed that low-volume centers (adjusted odds ratio 1.953; 95% confidence interval, 1.461–2.611; P < .001) and medium-volume centers (adjusted odds ratio 1.480; 95% confidence interval, 1.098–1.994; P = .010) had a significantly higher in-hospital mortality compared to high-volume centers. Long-term mortality rates were also higher in low-volume centers (P = .007). ConclusionCenters with higher volume showed better in-hospital mortality and long-term survival after deceased donor liver transplantation compared to centers with lower volume.

Incidence and Predictors of 30-Day Readmissions Following Autologous Hematopoietic Cell Transplantation (auto-HCT) in the US

Background: Readmissions within 30 days after index hospitalization is a quality, and cost-containment metric. It is now a major issue for hospitals, physicians and policy makers. Financial penalties to hospitals with high rates of risk adjusted readmissions have been expanded beyond medical conditions like heart failure and pneumonia. Auto-HCT is a widely used therapeutic strategy in the management of various hematological disorders, particularly multiple myeloma (MM) and non-Hodgkin lymphoma (NHL) in the US. However, auto-HCT readmission rates are poorly described in the literature and often limited to single center studies. To better address the incidence and underlying predictors of 30-day readmission following auto-HCT, we performed an analysis of the Nationwide Readmission Database(NRD).Methods: NRD data was queried from 2012-2014 to identify patients >18 years of age discharged from the hospital after auto-HCT (identified as presence of any ICD-9 procedure codes 41.00, 41.01, 41.04, 41.07, or 41.09). Survey weighted domain analysis was conducted to study incidence of 30-day readmission by center volume. Annual hospital case volume was calculated as the sum of all discharges with auto-HCT within the calendar year; low, medium, and high annual case volume groups were created based on (survey weighted) tertiles of patients (pts.) in the analytic data domain (Figure 1). Rates, causes, and costs of 30-day readmissions were compared between low-, medium-, and high-volume hospitals. The analysis was limited to urban teaching hospitals, and pts. admitted during month of December were excluded. The primary outcome was the unplanned 30-day re-admission following auto-HCT. Multiple logistic regression was used to model each 30-day readmission outcome including hospital case volume with other predictors (age, sex, disease type, primary insurance, median income, discharge disposition, co-morbidity, length of stay (LOS) and infection at index hospitalization).Results: A total of 28,356 (weighted) auto-HCTs were performed during the time period and MM remains the most common indication (~60%). Baseline characteristics of pts. in low (<78/yr.)-, medium (78-187/yr.)- and high-volume (>187/yr.) hospitals were comparable as shown in Table 1. The overall rates of readmissions were significantly higher in low volume 15.7% (SE, 1.5) compared to medium 9.9% (1.5) and high volume 9.5% (1.8), p=0.002 centers. The mean time to readmission in low vs. medium vs. high volume centers was (8.3 [0.41] days vs. 10.7 [0.78] days vs. 8.9 [0.26] days; p <0.001); however, readmission LOS was significantly longer in low and medium volume centers (mean [SD], 7.2 [0.30] days vs. 8.3 [0.62] days vs. 6.2 [0.25] days; p=<0.001) respectively. Consequently, cost per readmission was significantly higher in low volume centers (mean [SD], $ 65,815 [3492] vs. $ 65,662 [5896] vs. $ 48,914 [4162]; p<0.001).Readmission rates in low volume and medium volume centers compared to high volume centers were: adjusted odds ratio (aOR) 1.68, 95% CI 1.07-2.6; p =0.02 and 1.06 95% CI, 0.61-1.83; p=0.82, respectively. Other significant predictors of readmission included younger age (≥50 vs. <49) (aOR 0.81, 95% CI 0.68-0.98; p=0.03), female sex (aOR 1.20, 95% CI 1.06-1.36; p=0.003), disease type (others vs. MM) (aOR 1.37 95% CI 1.07-1.55; p= 0.018); and Elixhauser co-morbidity index (≥20 vs. 0; aOR 1.5, 95% CI 1.16-1.92; p= 0.00). Patients with non-routine discharges (discharges other than home) (aOR 1.3, 95% CI 1.1-1.7, p= 0.005), and shorter index LOS (aOR 0.94, 95% CI 0.89-0.98; p=0.01) were associated with higher readmission rates. The most common causes of readmission included: fever, neutropenia, infections, pneumonia, hyovolemia, nausea, vomiting and acute kidney injury.Conclusions: This is the largest study till date reporting on the incidence and predictors of 30-day readmissions following auto-HCT in the US. The overall 30-day readmission rates following auto-HCT was ~12%. We report an inverse association with hospital auto-HCT volume (<78/yr.) and 30-day readmissions. Shorter LOS at index admission was associated with higher rates of readmission, which was associated with significantly higher cost to the health care system. These data should provide guidance when developing quality indicators and any policies penalizing hospitals for auto-HCT readmission. [Display omitted] DisclosuresDhakal:Celgene: Consultancy, Honoraria; Takeda: Honoraria; Amgen: Honoraria. Shah:Lentigen Technology: Research Funding; Oncosec: Equity Ownership; Exelexis: Equity Ownership; Miltenyi: Other: Travel funding, Research Funding; Juno Pharmaceuticals: Honoraria; Geron: Equity Ownership. D'Souza:Takeda: Research Funding; Merck: Research Funding; Celgene: Research Funding; Prothena: Consultancy, Research Funding; Amgen: Research Funding. Hari:Spectrum: Consultancy, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Kite Pharma: Consultancy, Honoraria; Sanofi: Honoraria, Research Funding; Janssen: Honoraria; Amgen Inc.: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding. Hamadani:Celgene Corporation: Consultancy; Ostuka: Research Funding; Cellerant: Consultancy; ADC Therapeutics: Research Funding; Janssen: Consultancy; MedImmune: Consultancy, Research Funding; Sanofi Genzyme: Research Funding, Speakers Bureau; Takeda: Research Funding; Merck: Research Funding.