Vascular surgeon-hospitalist comanagement improves in-hospital mortality at the expense of increased in-hospital cost.

OBJECTIVE: We have shown that vascular surgeon- hospitalist co management resulted in improved in-hospital mortality rates. We now aim to assess the impact of the hospitalist co management service (HCS) on healthcare cost. METHODS: A total of 1558 patients were divided into three cohorts and compared: 516 in 2012, 525 in 2013, and 517 in 2014. The HCS began in January 2013. Data were standardized for six vascular surgeons that were present 2012-2014. New attendings were excluded. Ten hospitalists participated. Case mix index (CMI), contribution margin, total hospital charges (THCs), length of stay (LOS), actual direct costs (ADCs), and actual variable indirect costs (AVICs) were compared. Analysis of variance with post-hoc tests, t-tests, and linear regressions were performed. RESULTS: THC rose by a mean difference of $14,578.31 between 2012 and 2014 (P < .001) with a significant difference found between all groups during the study period (P = .0004). ADC increased more than AVIC; however, both significantly increased over time (P = .0002 and P = .014, respectively). A mean $3326.63 increase in ADC was observed from 2012 to 2014 (P < .0001). AVIC only increased by an average $392.86 during the study period (P = .01). This increased cost was observed in the context of a higher CMI and longer LOS. CMI increased from 2.25 in 2012 to 2.53 in 2014 (P = .006). LOS increased by a mean 1.02 days between 2012 and 2014 (P = .016), and significantly during the study period overall (P = .018). After adjusting for CMI, LOS increases by only 0.61 days between 2012 and 2014 (P = .07). In a final regression model, THC is independently predicted by comanagement, CMI, and LOS. After adjusting for CMI and LOS, the increase in THC because of comanagement (2012 vs 2014) accounts for only $4073.08 of the total increase (P < .001). During this time, 30-day readmission rates decreased by ∼7% (P = .005), while related 30-day readmission rates decreased by ∼2% (P = .32). Physician contribution margin remained unchanged over the 3-year period (P = .76). The most prevalent diagnosis-related group was consistent across all years. Variation in the principal diagnosis code was observed with the prevalence of circulatory disorders because of type II diabetes replacing atherosclerosis with gangrene as the most prevalent diagnosis in 2013 and 2014 compared with 2012. CONCLUSIONS: In-hospital cost is significantly higher since the start of the HCS. This surge may relate to increased CMI, LOS, and improved coding. This increase in cost may be justified as we have observed sustained reduction in in-hospital mortality and slightly improved readmission rates.

An anatomic risk model to screen post endovascular aneurysm repair patients for aneurysm sac enlargement.

BACKGROUND: Follow-up computed tomography angiography (CTA) scans add considerable postimplantation costs to endovascular aneurysm repairs (EVARs) of abdominal aortic aneurysms (AAAs). By building a risk model, we hope to identify patients at low risk for aneurysm sac enlargement to minimize unnecessary CTAs. METHODS: 895 consecutive patients who underwent EVAR for AAA were reviewed, of which 556 met inclusion criteria. A Probit model was created for aneurysm sac enlargement, with preoperative aneurysm morphology, patient demographics, and operative details as variables. RESULTS: Our final model included 287 patients and had a sensitivity of 100%, a specificity of 68.9%, and an accuracy of 70.4%. Ninety-nine (35%) of patients were assigned to the high-risk group, whereas 188 (65%) of patients were assigned to the low-risk group. Notably, regarding anatomic variables, our model reported that age, pulmonary comorbidities, aortic neck diameter, iliac artery length, and aneurysms were independent predictors of post-EVAR sac enlargement. With the exception of age, all statistically significant variables were qualitatively supported by prior literature. With regards to secondary outcomes, the high-risk group had significantly higher proportions of AAA-related deaths (5.1% versus 1.1%, P = 0.037) and Type 1 endoleaks (9.1% versus 3.2%, P = 0.033). CONCLUSIONS: Our model is a decent predictor of patients at low risk for post AAA EVAR aneurysm sac enlargement and associated complications. With additional validation and refinement, it could be applied to practices to cut down on the overall need for postimplantation CTA.

The Protective Effects of Diabetes Mellitus on Post-EVAR AAA Growth and Reinterventions.

BACKGROUND: This study aims to investigate the effect of diabetes on post-endovascular aneurysm repairs (EVARs) of abdominal aortic aneurysms (AAAs). METHODS: A total of 1,479 consecutive patients who underwent AAA EVAR were reviewed. The cohorts were divided based on their diabetes status and compared. Preoperative demographic and comorbidity data were analyzed using the t-test and chi-squared test, whereas post-EVAR outcomes were analyzed using Probit multivariate model, followed by Kaplan-Meier survival curve and Cox regression. RESULTS: Of our 1,479 patients, 993 met inclusion criteria. One hundred eighty-three were diabetics (18.4%) compared with 810 nondiabetics (81.6%). Coronary artery disease (CAD; diabetics: 70.49%, nondiabetics: 60.76%, P = 0.014) and hypertension (HTN; diabetics: 90.16%, nondiabetics: 79.46%, P = 0.0008) were the only comorbidities analyzed, including follow-up length, which had any significant differences between the diabetic and nondiabetic groups. Probit multivariate analysis using a combined cohort follow-up mean of 51 months showed a significant decrease in aneurysm sac enlargement in diabetic patients (diabetics: 13.11%, nondiabetics: 19.43%, model estimate: 0.3058; 95% confidence interval [CI]: 0.0486-0.5629, Pr > ChiSq = 0.0198) and trended toward significantly fewer reinterventions (diabetics: 23.50%, nondiabetics: 28.41%, model estimate: 0.1990; 95% CI: -0.0262 to 0.4243, Pr > ChiSq = 0.0833). In the Cox regressions, diabetes had a significant protective factor on reinterventions (hazard ratio [HR]: 0.697, Pr > ChiSq = 0.0151), and was trending toward significance for aneurysm sac enlargement (HR: 0.750, Pr > ChiSq = 0.1961). There was no significant difference across diabetic status in any other outcomes, including mortality and endoleak occurrence. CONCLUSIONS: Although a higher proportion of diabetic patients present with HTN and CAD, they have decreased long-term rates of aneurysm sac enlargement after EVAR. As a result, this cohort trends toward a lower need for reintervention after EVAR.