Citations

Background: External ear melanoma (EEM) is a rare condition with controversies in the literature. We analyzed patients with EEM in the United States compared to other head and neck melanomas (OHNMs). Methods: The National Cancer Database (NCDB) was used to select patients with head and neck melanoma from January 1, 2004 to December 31, 2015. Mann–Whitney and χ 2 tests were used to estimate statistical significance, and multivariate logistic regression to identify independent associations adjusted for confounders. Results: A total of 137,233 patients met the study criteria. Among them, 16,991 (12.4%) had EEM and 120,242 (87.6%) had OHNM. For patients with EEM, the mean (standard deviation) age was 66.26 (15.798) years. Most of the patients with EEM were men (85.5%), insured by Medicare (52.4%), and treated in Academic/Research Programs (47.7%) or Comprehensive Community Cancer Programs (32.3%). Most of the EEM tumors had invasive behavior (68.0%) were Stages 0 (30.3%) or I (40.3%), and were without ulceration (76.9%). Mean time to receive any treatment was 14.1 days for EEM compared with 14.6 days for OHNM (P < 0.001). We noticed a greater proportion of EEM in men (14.8%; adjusted odds ratio [aOR] 2.72 [2.605–2.852]; P < 0.001) compared to women (6.22%; reference). EEM was an independent factor for tumor Stage I (14.47%; aOR 1.61 [1.101–1.224], P < 0.001) and invasive behavior (13.86%; aOR 1.268 [1.15–1.389]; P < 0.001) compared to OHNM. Conclusion: EEM was associated with higher odds of invasive behavior compared to OHNM. Furthermore, men were found to have a higher likelihood to develop EEM compared to women.

ABSTRACT Background and purpose: Daily chest radiographs (CXRs) have long been a routine part of care. However, evidence as well as changing technology has promoted on-demand CXRs as beneficial to patient care. We found that a substantial number of routine daily CXRs were being ordered, with some of the orders staying active even after extubation. Methods: Within a 19-bed adult medical ICU, we prospectively utilized 3 intervention phases from October 1, 2014, to February 28, 2018, to reduce routine CXRs. Nurse Practitioners (NP) initiated this quality improvement (QI) project, aiming to reduce the number of unnecessary of CXRs. Interventions included staff survey, routine CXR order removal, duplicate alerts, visual reminders, and an electronic clinical decision support tool. Monthly education of appropriate CXRs and bedside ultrasound were facilitated by NPs. The outcome measures of interest include: the number of CXRs per patient-day, the number of routine and on-demand CXRs, mortality rate, ICU length of stay, and ventilator days, radiation and cost. Conclusions: Total number of CXRs per patient-day decreased by 36.1%. The proportion of routine CXRs decreased from 55.37% to 13.18%; on-demand orders increased, from 44.63% to 86.82%; and calculated radiation-exposure per census decreased, from 0.011 to 0.008 mSv. In addition, charges to patients for CXRs decreased by $7,750/month. ICU mortality and ventilator days per census remained stable. Implications for practice: By an orchestrated process that included creating awareness and desire to change CXR ordering practices, we were able to decrease routine CXRs and increase on-demand utilization while maintaining counterbalance measures.

Objective: To perform a feasibility pilot study comparing the usefulness of EEG electrode cap versus standard scalp EEG for acquiring emergent EEGs in emergency department, inpatient, and intensive care unit patients. Background: Nonconvulsive status epilepticus (NCSE) is a neurological emergency diagnosed exclusively by EEG. Nonconvulsive status epilepticus becomes more resistant to treatment 1 hour after continued seizure activity. EEG technologists are alerted “stat” when there is immediate need for an EEG during oncall hours, yet delays are inevitable. Alternatively, EEG caps can be quickly placed by in-house residents at bedside for assessment. Design/Methods: EEG caps were compared with standard-of-care “stat” EEGs for 20 patients with suspected NCSE. After the order for a stat EEG was placed, neurology residents were simultaneously alerted and placed an EEG cap prior to the arrival of the on-call out-of-hospital technologist. Both EEG cap recordings and standard EEG recordings were visually reviewed at 10 and 20 minutes in a blinded manner by two electroencephalographers. The timing, accuracy of interpretation, and diagnosis between the two techniques were then compared. Results: Of the 20 adult patients, 70% (14 of 20) of EEG cap recordings were interpretable, whereas 95% (19 of 20) standard EEGs were interpretable; three had findings consistent with NCSE on both the EEG cap and standard EEG recordings. In the time analysis, 16 patients were included. EEG cap placement was significantly more time efficient than an EEG performed by technologist using the usual “stat” EEG protocol, with the median EEG cap electrode placement occurring 86 minutes faster than standard EEG (22.5 minutes vs. 104.5 minutes; P < 0.0001; n = 16). Conclusions: New rapid EEG recording using improved EEG caps may allow for rapid diagnosis and clinical decision making in suspected NCSE.

Background: Eyelid melanoma (EM) is a rare condition that accounts for <1% of all cutaneous melanomas. In this analysis, patients diagnosed with EM in the United States were compared to those with other melanomas in the head and neck. Methods: The National Cancer Database was used to select patients with head and neck melanoma from 2004 to 2015. Results: A total of 137,233 patients met the criteria of the study. Among them, 2694 were diagnosed with EM (2%) and 134,539 in other head and neck locations (98%). Regarding the patients with EM, the mean age was 68.56 years (standard deviation 14.04). A greater number of them were treated in Academic/Research Programs (53.6%), insured by Medicare (55.7%), tumor in situ (52.2%), stage 0 (49%), and without ulceration (75.9%). The mean time to treatment commencement was 18.96 days for EM compared to 14.4 days for other melanoma in the head and neck regions (P < 0.001). There was a greater proportion of EM in female patients (odds ratio [OR] 2.371 [2.191–2.566], P < 0.001), compared to male; age greater than 80 years (OR 1.622 [1.360–1.934], P < 0.001) compared to 0 to 49 years. Moreover, EM was an independent predictor for treatment in Academic/Research Programs (OR 1.258 [1.160–1.365], P < 0.001) and diagnosis at autopsy (OR 1.414 [1.083–1.847], P = 0.011) compared to other melanoma in the head and neck region. Conclusion: These novel findings have the potential to guide clinical decision making in head and neck melanoma management.

PURPOSE: Quality payment programs aim to adjust payments on the basis of quality and cost; however, few quality metrics exist in radiation oncology. This study evaluates and predicts the top spenders (TS) after radiation therapy (RT). MATERIALS AND METHODS: Patient characteristics, cancer details, treatments, toxicity, and survival data were collected for patients treated with RT at Mayo Clinic from 2007 to 2016. Standardized costs were obtained and adjusted for inflation. TSs were identified as those with greater than 93rd percentile costs (≥ $120,812). Prediction models were developed to predict TSs using training and validation sets using information available at consultation, after RT, and at last follow-up. RESULTS: A total of 15,131 patients were included and 1,065 TSs identified. Mean cost overall was $55,290 (median, $39,996) for all patients. Prediction models 1, 2, and 3 had concordance statistics of 0.83 to 0.83, 0.85 to 0.85, and 0.87 to 0.88, respectively in training and validation, indicating excellent prediction of TSs. Factors that were most predictive of TSs included stage N/A and stage 4 ( v stage 0; odds ratio [OR], 18.23 and 8.44, respectively; P < .001); hematologic, upper GI, skin and lung cancers ( v breast; OR, 11.45, 7.69, 3.81, and 2.43, respectively; P < .01); immunotherapy, surgery, and chemotherapy use (OR, 4.36, 2.51, and 1.61, respectively; P < .01); hospitalizations within 90 days of RT (OR, 2.26; P < .01); or death during the episode (OR, 1.56; P < .01). CONCLUSION: This is the first study of its kind to predict with high accuracy the highest spenders in radiation oncology. These patients may benefit from pre-emptive management to mitigate costs, or may require exclusion or adjustment from quality payment programs.

6633 Background: Quality based payment programs in medicine are currently being introduced nationally, aimed to improve care and reduce cost. This study aimed to evaluate the top spenders (TS) after cancer diagnosis and predict TS at two separate time points using predictive analytics. Methods: Patient characteristics, cancer details, treatments, adverse events, and outcomes were collected for patients treated for cancer at Mayo Clinic from 2007 - 2017. Standardized costs over a 2 year period after first treatment were obtained from the Mayo Clinic Cost Data Warehouse with Medicare reimbursements assigned to all services and adjusted to the 2017 GDP Implicit Price Deflator for inflation. TS were identified as those with greater than 93rd percentile costs (≥$113,158) due to a sharp rise in cost at that level. Descriptive statistics and univariate analysis were used for comparison. A prediction model with a training (80%) and validation set (20%) using multivariate selection was used to predict TS and was repeated using information available at 1) the time of consultation and 2) at last follow-up. Results: A total of 80,385 patients were included and 5,626 TS were identified. Mean cost (25th, 75th percentile) overall was $44,953 ($16,776, $51,889). Prediction models at time 1 and 2 had ROC AUC statistics of 0.82 and 0.89 in training and 0.82 and 0.88 in the validation indicating good prediction of high costs. Factors most predictive of TS included need for blood transfusions within 90 days of treatment (OR 5.3), bone marrow transplant (OR 4.0), mild liver disease (OR 3.5), hemiplegia (OR 3.4), weight loss > 10% within 90 days of treatment (OR 3.3), upper GI cancer (OR 3.0), ‘other’ cancer type (OR 2.8), immunotherapy use (OR 2.7), and hospitalizations within 90 days (OR 2.4), all p < 0.001, among others. The largest costs were due to hospital services in the TS and non-TS groups, mean costs $114,258 and $13,185 respectively. Conclusions: This is the first study to predict with high accuracy the top spenders in Oncology. Patient comorbidities and toxicities were among the strongest predictors of high costs, along with certain treatments (bone marrow transplant and immunotherapy). Our findings suggest that quality payment programs should adjust for comorbidities, and that reducing toxicity may be an effective method at reducing costs.