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A growing number of renal transplant recipients have a body mass index ≥40. While previous studies have shown that patient and graft survival are significantly decreased in renal transplant recipients with body mass indexes ≥40, less is known about perioperative outcomes and resource utilization in morbidly obese patients. We aimed to analyze the effects of morbid obesity on these parameters in renal transplant.Using a linkage between the Scientific Registry of Transplant Recipients and the databases of the University HealthSystem Consortium, we identified 29,728 adult renal transplant recipients and divided them into 2 cohorts based on body mass index (40 vs ≥40 kg/mBody mass index ≥40 recipients incurred greater direct costs ($84,075 vs $79,580, P .01), index admission costs ($91,169 vs $86,141, P .01), readmission costs ($5,306 vs $4,596, P = .01), and combined costs ($99,590 vs $93,939, P .001). Thirty-day readmission rates were also greater among body mass index ≥40 recipients (33.92% vs 26.9%, P .01). Morbid obesity was not predictive of stay (odds ratio 1.01, P = .75).Morbidly obese renal transplant recipients incur greater costs and readmission rates compared with nonobese patients. Recognition of increased resource utilization should be accompanied by appropriate, risk-adjustment reimbursement.

Background and Objectives Pasireotide decreases leak rates after pancreatic resection, though significant drug cost may be prohibitive. We conducted a cost-effectiveness analysis to determine whether prophylactic pasireotide possesses a reasonable cost profile. Methods A cost-effectiveness model compared pasireotide administration after pancreatic resection versus usual care, populated by probabilities of clinical outcomes from a randomized trial and hospital costs (2013 US$) from a university pancreatic disease center. Sensitivity analyses were performed to identify influential clinical components of the model. Results With the cost of pasireotide included, per patient costs of pancreatectomy, including those for readmission, were lower in the intervention arm (41,769 versus 42,159$; net savings of 390$, or 1%). This was associated with a 56% reduction in pancreatic fistula/pancreatic leak/abscess (PF/PL/A; 21.9–9.2%). Pasireotide cost would need to increase by over 15.4% to make the intervention strategy more costly than usual care. Sensitivity analyses exploring variability of key model inputs demonstrated that the three strongest drivers of cost were (i) cost of pasireotide; (ii) probability of readmission; and (iii) probability of PF/PL/A. Conclusions Prophylactic pasireotide administration following pancreatectomy is cost savings, reducing expensive post-operative sequealae (major complications and readmissions). Pasireotide should be utilized as a cost-saving measure in pancreatic resection. J. Surg. Oncol. © 2016 Wiley Periodicals, Inc.

Background The rate and consequences of reoperation after liver transplantation (LT) are unknown in the United States. Study Design Adult patients (n = 10,295; 45% of all LT) undergoing LT from 2009 through 2012 were examined using a linkage of the University HealthSystem Consortium and Scientific Registry of Transplant Recipients databases providing recipient, donor, center, hospitalization, and survival details. Median follow-up was 2 years. Reoperations were identified within 90 days after LT. Results Overall 90-day reoperation rate after LT was 29.3%. Risk factors for 90-day reoperation included recipients with a history of hemodialysis, severely ill functional status, government insurance, increasing Model for End-Stage Liver Disease score, and increasing donor risk index. Reoperation within 90 days was found to be an independent predictor of adjusted 1-year mortality (odds ratio = 1.8; 95% CI, 1.5–2.1), as was government-provided insurance and increasing donor risk index. Additionally, patients undergoing delayed reoperative intervention (after 30 days) were found to have increased risk of 1-year mortality compared with those undergoing early reoperative intervention (odds ratio = 1.96; 95% CI, 1.4–2.7; p Conclusions This is the first national study reporting that nearly one-third of transplant recipients undergo reoperation within 90 days of LT. Although necessary at times, reoperation is associated with increased risk of death at 1 year; however, it appears that the timing of these interventions can be critical, due to the type of intervention required. Early reoperative intervention does not appear to influence long-term outcomes, and delayed intervention (after 30 days) is strongly associated with decreased survival.

Urgent colectomy is a common procedure with a high mortality rate that is performed by a variety of surgeons and hospitals. We investigated patient, surgeon, and hospital characteristics that predicted mortality after urgent colectomy.The University HealthSystem Consortium was queried for adults undergoing urgent or emergent colectomy between 2009 and 2013 (n = 50,707). Hospitals were grouped into quartiles according to risk-adjusted observed-to-expected (O/E) mortality ratios and compared using the 2013 American Hospital Association Annual Survey. Multiple logistic regression was used to determine patient and provider characteristics associated with in-hospital mortality.The overall mortality rate after urgent colectomy was 9 %. Mortality rates were higher for patients with extreme severity of illness (27.6 %), lowest socioeconomic status (10.6 %), weekend admissions (10.7 %), and open (10.5 %) and total (15.8 %) colectomies. Hospitals with the lowest O/E ratios were smaller and had lower volume and less teaching intensity, but there were no significant trends with regard to financial (expenses, payroll, capital expenditures per bed) or personnel characteristics (physicians, nurses, technicians per bed). On multivariate analysis, mortality was associated with patient age (10 years: OR 1.31, p 0.01), severity of illness (extreme: OR 34.68, p 0.01), insurance status (Medicaid: OR 1.24, p 0.01; uninsured: OR 1.40, p 0.01), and weekend admission (OR 1.09, p = 0.04). Surgeon volume was associated with reduced mortality (per 10 cases: OR 0.99, p 0.01), but hospital volume was not (per case: OR 1.00, p = 0.84).Mortality is common after urgent colectomy and is associated with patient characteristics. Surgeon volume and practice patterns predicted differences in mortality, whereas hospital factors did not. These data suggest that policies focusing solely on hospital volume ignore other more important predictors of patient outcomes.

Efforts to regionalize surgery based on thresholds in procedure volume may have consequences on the cost of health care delivery. This study aims to delineate the relationship between hospital volume, case mix, and variability in the cost of operative intervention using colectomy as the model.All patients undergoing colectomy (n = 90,583) at 183 academic hospitals from 2009-2012 in The University HealthSystems Consortium Database were studied. Patient and procedure details were used to generate a case mix-adjusted predictive model of total direct costs. Observed to expected costs for each center were evaluated between centers based on overall procedure volume.Patient and procedure characteristics were significantly different between volume tertiles. Observed costs at high-volume centers were less than at middle- and low-volume centers. According to our predictive model, high-volume centers cared for a less expensive case mix than middle- and low-volume centers ($12,786 vs $13,236 and $14,497, P .01). Our predictive model accounted for 44% of the variation in costs. Overall efficiency (standardized observed to expected costs) was greatest at high-volume centers compared to middle- and low-volume tertiles (z score -0.16 vs 0.02 and -0.07, P .01).Hospital costs and cost efficiency after an elective colectomy varies significantly between centers and may be attributed partially to the patient differences at those centers. These data demonstrate that a significant proportion of the cost variation is due to a distinct case mix at low-volume centers, which may lead to perceived poor performance at these centers.

Background Metabolic syndrome is increasing among patients undergoing liver transplantation. Nonalcoholic steatohepatitis is a manifestation of metabolic syndrome and is an increasingly common cause of end-stage liver disease necessitating orthotopic liver transplantation. We sought to determine the effect of preoperative risk factors on the development of post-transplant metabolic syndrome, complications, readmissions, and mortality. Methods We conducted a review of 114 orthotopic liver transplantations at our institution from May 2012 to April 2014. Results Patients with (n = 19) and without (n = 95) metabolic syndrome were similar with regard to age, race, and model for end-stage liver disease at time of transplant. Donor and operative factors also were similar between the groups. Preoperative diabetes was found to be associated with an increased rate of readmission (odds ratio 3.45, P = .03). While preoperative metabolic syndrome itself was not a significant predictor of worse outcomes, postoperative metabolic syndrome was associated with significantly greater readmissions in the first year. Major predictors of new onset metabolic syndrome after orthotopic liver transplantation included preoperative diabetes and obesity (odds ratio 8.54 and odds ratio 5.49, P Conclusion Efforts to decrease the incidence of postoperative metabolic syndrome after orthotopic liver transplantation may decrease readmissions and improve outcomes, along with decreasing resource utilization.

With the increasing complexity of modern medical therapies, it is becoming imperative to recognize the marginal cost and gains of increasingly sophisticated (and expensive) interventions. By understanding the incremental cost of a given intervention, investigators must help answer questions about healthcare resource utilization that are not answered by randomized clinical trials. The continued funding of biomedical research and pharmaceuticals will require more objective study of the return on investment for any given treatment modality, and cost-effectiveness analyses will be instrumental in providing solutions to the inequalities in healthcare delivery.