ABSTRACT
BACKGROUND: Morbidity after pancreaticoduodenectomy (PD) has been reported to be about 30-53%. These complications can double hospital costs. We sought to explore the financial implications of complications after PD in a large institutional database. METHODS: A retrospective analysis of patients undergoing PD from 2010-2017 was performed. Costs for index hospitalization were divided into categories: operating room, postoperative ward, radiology and interventional radiology. Complications were categorized according to the Clavien-Dindo classification. Univariable and mutivariable analysis were performed. RESULTS: Median cost of index admission for 997 patients who underwent PD was $23,704 (range $10,988-$528,531). Patients with major complications incurred significantly greater median costs compared to those without ($40,005 vs $21,306, p < 0.001). Patients with postoperative pancreatic fistula (POPF) grade A, B and C had progressively increasing costs ($32,164, $50,264 and $102,013, p < 0.001). On multivariable analysis ileus/delayed gastric emptying, respiratory failure, clinically significant POPF, thromboembolic complications, reoperation, duration of surgery >240 minutes and male sex were associated with significantly increased costs. CONCLUSION: Complications after PD significantly increase hospital costs. This study identifies the major contributors towards increased cost post-PD. Initiatives that focus on prevention of complications could reduce associated costs and ease financial burden on patients and healthcare organizations.
Subject(s)
Pancreatic Fistula , Pancreaticoduodenectomy , Humans , Male , Pancreatectomy/adverse effects , Pancreatic Fistula/etiology , Pancreaticoduodenectomy/adverse effects , Postoperative Complications/etiology , Retrospective StudiesABSTRACT
BACKGROUND: Postoperative healthcare use and readmissions are common among the hepatopancreatobiliary (HPB) population. We evaluated the surgical volume required to sustain advanced practice providers (APPs) in the perioperative setting for cost reduction. STUDY DESIGN: Using decision analysis modeling, we evaluated costs of employing dedicated perioperative APP navigators compared with no APPs navigators. Simulated subjects could: (1) present to an emergency department, with or without readmission, (2) present for direct readmission, (3) require additional office visits, or (4) require no additional care. We informed our model using the most current available published data and performed sensitivity analyses to evaluate thresholds under which dedicated perioperative APP navigators are beneficial. RESULTS: Subjects within the APP navigator cohort accumulated $1,270 and a readmission rate of 6.9%, compared with $2,170 and 13.5% with no APP navigators, yielding a cost savings of $905 and 48% relative reduction in readmission. Based on these estimated cost savings and national salary ranges, a perioperative APPs become financially self-sustaining with 113 to 139 annual HPB cases, equating to 2 to 3 HPB cases weekly. Sensitivity analyses revealed that perioperative APP navigators were no longer cost saving when direct readmission rates exceeded 8.9% (base case 3.7%). CONCLUSIONS: We show that readmissions are reduced by nearly 50% with an associated cost savings of $900 when employing dedicated perioperative APPs. This position becomes financially self-sufficient with an annual HPB case load of 113 to 139 cases. High-volume HPB centers could benefit from postdischarge APP navigators to optimize outcomes, minimize high-value resource use, and ultimately save costs.
Subject(s)
Aftercare , Patient Readmission , Humans , Patient Discharge , Salaries and Fringe BenefitsABSTRACT
BACKGROUND: Postoperative returns to acute care represent fragmented care, are costly, and often evolve into readmission. Reduction of postoperative readmissions and emergency department visits represents an opportunity to improve quality of care and decrease resource use. The aim of this study was to assess the impact of 2 failure modes and effects analysis-guided quality improvement interventions on return to acute care within 30 days postoperatively. METHODS: An American College of Surgeons NSQIP database analysis of adult patients treated by a single hepatopancreatobiliary surgeon at a quaternary academic center was performed. Two failure modes and effects analysis-guided quality improvement interventions were assessed in a staged fashion, including a post-discharge phone call follow-up, and a preoperative clinic visit to discuss plans of care. The primary end point of interest was return to acute care (readmission or emergency department use) within 30 days from postoperative discharge. RESULTS: During the 4-year study period, 684 patients underwent a hepatopancreatobiliary operation. After the implementation of the failure modes and effects analysis interventions, the baseline 30-day readmission rate was reduced by 48% post intervention (13.5% vs 6.9%; p = 0.011). This impact was sustained, with a readmission rate below the lowest baseline in 5 of 6 postintervention quarters. Short-stay readmissions were reduced by > 76% after the interventions (28.5% vs 6.6%). Post-discharge emergency department visits were also reduced by nearly 40% after initiation of both failure modes and effects analysis-guided quality improvement interventions (11.3% vs 6.9%; p = 0.125), which showed similar sustained response. CONCLUSIONS: The results from this study can be used to help identify, develop, and test interventions to optimize emergency department use and readmission to reduce healthcare costs and improve patient quality of life.
Subject(s)
Biliary Tract Surgical Procedures , Emergency Service, Hospital/statistics & numerical data , Hepatectomy , Pancreatectomy , Patient Readmission/statistics & numerical data , Perioperative Care/standards , Quality Improvement/organization & administration , Adult , Facilities and Services Utilization/statistics & numerical data , Humans , Patient Discharge/standards , Perioperative Care/methods , Quality Assurance, Health Care/methods , Quality Assurance, Health Care/organization & administration , Quality Improvement/statistics & numerical data , Retrospective StudiesABSTRACT
BACKGROUND: Literature is varied regarding risk factors associated with diabetes development after major pancreatic resection. The aim was to develop and validate a scoring index that preoperatively predicts the development of diabetes after pancreaticoduodenectomy and distal pancreatectomy. STUDY DESIGN: In this prospective study, perioperative fasting and postprandial (OGTT, oral glucose tolerance test) plasma glucose, glycated hemoglobin A1c (HbA1c), insulin, and c-peptide were measured in select consecutive patients undergoing pancreaticoduodenectomy and distal pancreatectomy by the senior author, from 2007 to 2018. American Diabetes Association definitions were used for glycemic classifications. Statistical analyses included multivariate generalized estimated equation for factor identification and variable weighting; area under the receiver operating curve (ROC) c-statistic for predictive ability, and survival analysis risk score grouping. RESULTS: Of 1,083 included patients with preoperative normoglycemia (253; 23.4%), prediabetes (362; 33.4%), and diabetes (468; 43.2%), the overall postoperative incidence of each diabetic class at 120 months was 152 (14.0%), 466 (43.0%), and 465 (42.9%), respectively. The development and validation groups included 1,023 and 60 patients, respectively. Five factors were identified predicting diabetes development, with a total possible score of 8. The C-statistics for development and validation groups were 0.727 (CI 0.696 to 0.759, p < 0.001) and 0.823 (CI 0.718 to 0.928, p < 0.001), respectively. At a cut point of 3 (sensitivity 0.691, specificity 0.644) the Post-pancreatectomy Diabetes Index (PDI) independently predicted diabetes in development (odds ratio [OR] 4.298, relative risk [RR] 2.486, CI 1.238 to 5.704, p < 0.001) and validation (OR 6.970, RR 2.768, CI 2.182 to 22.261, p < 0.001) groups. The PDI similarly predicted pre-diabetes in development (OR 1.961, RR 1.325, CI 1.202 to 2.564, p < 0.001) and validation (OR 4.255, RR 1.798, CI 1.247 to 14.492, p = 0.021) groups. CONCLUSIONS: The Post-pancreatectomy Diabetes Index predicts the development of diabetes and pre-diabetes in patients undergoing major pancreatectomy using routine endocrine laboratories and pre-surgical clinical data.