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PURPOSE Acute care use (ACU) is a major driver of oncologic costs and is penalized by a Centers for Medicare & Medicaid Services quality measure, OP-35. Targeted interventions reduce preventable ACU; however, identifying which patients might benefit remains challenging. Prior predictive models have made use of a limited subset of the data in the electronic health record (EHR). We aimed to predict risk of preventable ACU after starting chemotherapy using machine learning (ML) algorithms trained on comprehensive EHR data. METHODS Chemotherapy patients treated at an academic institution and affiliated community care sites between January 2013 and July 2019 who met inclusion criteria for OP-35 were identified. Preventable ACU was defined using OP-35 criteria. Structured EHR data generated before chemotherapy treatment were obtained. ML models were trained to predict risk for ACU after starting chemotherapy using 80% of the cohort. The remaining 20% were used to test model performance by the area under the receiver operator curve. RESULTS Eight thousand four hundred thirty-nine patients were included, of whom 35% had preventable ACU within 180 days of starting chemotherapy. Our primary model classified patients at risk for preventable ACU with an area under the receiver operator curve of 0.783 (95% CI, 0.761 to 0.806). Performance was better for identifying admissions than emergency department visits. Key variables included prior hospitalizations, cancer stage, race, laboratory values, and a diagnosis of depression. Analyses showed limited benefit from including patient-reported outcome data and indicated inequities in outcomes and risk modeling for Black and Medicaid patients. CONCLUSION Dense EHR data can identify patients at risk for ACU using ML with promising accuracy. These models have potential to improve cancer care outcomes, patient experience, and costs by allowing for targeted, preventative interventions.

228 Background: Use of anti-cancer therapies in the last 14-30 days of life may worsen patient outcomes and increase cost; accordingly, rate of chemotherapy use near EOL is an important quality measure. Contemporary benchmarks are needed, with transparent methods describing the cohort in which the measure is assessed, and criteria for calculation. Methods: Data on chemotherapy use, mortality, and cancer diagnosis was sourced from electronic health records (EHRs) of >8,000 patients seen between 2014-2016 at two large US academic centers, for whom dates of death were available. Death dates were sourced from the EHR and public records (e.g., obituaries). Patients were grouped by diagnosis using ICD-10 codes. Rates of infusional chemotherapy receipt within 14 or 30 days of death were calculated. Results: Across 10 tumor types, 3-7% of patients received chemotherapy within 14d of death, and 6-16% received it within 30d. Rates were stable from 2014-2016 and did not differ by cancer center. Rates were highest in diseases where patients may experience rapid clinical decline near EOL: in pancreatic and rectal cancer, 30d rates were 16% and 13%. The 30d rate was lowest (6%) in kidney cancer. When the cohort was restricted to only treated patients (who received >=5 chemotherapy administrations at the center), rates of chemotherapy use at EOL increased to 6-12% (14d) and 17-28% (30d). Conclusions: This study provides baseline estimates of current rates of EOL chemotherapy use at academic centers. Transparency in methodology is critical; for example, when the whole population of cancer patients seen at a center is considered, rates are low, but when the analysis is limited to patients who received chemotherapy there, rates nearly double. Further studies should focus on whether this quality measure is a meaningful driver of patient and health system outcomes. This work also demonstrates that it is possible to assess this metric across multiple centers; this approach could be easily scaled to all oncology practices integrated in a data sharing network. [Table: see text]

Background Understanding the salient features that draw focus when assessing aesthetics is important for maximizing perceived outcomes. Eye-tracking technology provides an unbiased method for determining the features that draw attention when evaluating aesthetic plastic surgery. This study aimed to characterize viewing patterns of plastic surgery patients and laypeople when assessing facial cosmetic procedure images. Methods Twenty women who previously underwent cosmetic procedures and twenty women without a history of cosmetic procedures were shown sixteen pairs of preprocedure and postprocedure images of patients who underwent laser resurfacing or lip augmentation. Image pairs were randomized to whether preprocedural or postprocedural images came first. Participants viewed each image until they decided upon an aesthetic rating (scored 1–10), while an eye-tracking device recorded participants' gaze. Results The patient group's average ratings were 8.2% higher for preprocedural images and 13.3% higher for postprocedural images (P < 0.05 for both). The patient group spent 20.4% less time viewing images but spent proportionally more time evaluating the relevant features of each procedure (41.7% vs 23.3%, P < 0.01), such as the vermillion border of the upper lip, labial commissure, or periorbital region (P < 0.05 for each). For both groups, the most common site of first fixation was the nose for laser resurfacing images (26.6%) and the labial commissure for lip augmentation images (37.7%). Both groups spent more time fixated on nasolabial folds, marionette lines, and the periorbital region when viewing pre–laser resurfacing images than postprocedural images. Overall, each group had similar viewing patterns for time to first fixation on and frequency of fixations for a particular feature. Conclusions Women who previously underwent cosmetic procedures view postprocedural images more favorably and require less time to assess images, likely related to familiarity with aesthetic procedures. These women spend more time fixated on relevant features, such as the vermillion border of the upper lip, the labial commissure, and the periorbital region, than the control group. Notably, each group spent less time focused on regions associated with wrinkles, such as the marionette and periorbital areas in post–laser resurfacing images, suggesting that the procedure reduces attention-drawing features in these areas.

PurposeThe literature assessing outcomes of partial adrenalectomy (PA) among patients with pheochromocytoma patients is largely limited to isolated, single-institution series. We aimed to perform a population-level comparison of outcomes between patients undergoing PA versus those undergoing total adrenalectomy (TA). Methods The Surveillance, Epidemiology, and End Results (SEER) database was queried to identify adults with pheochromocytoma who underwent either PA or TA. Survival was assessed using multivariable Cox proportional hazards regression, Fine and Gray competing-risks regression, propensity score matching, Kaplan-Meier analysis, and cumulative incidence plots. Results 286 patients (PA: 101, TA: 185) were included in this study. As compared to those undergoing TA, patients undergoing PA had fewer tumors ≥ 8 cm in size (28.7% versus 42.7%, p = 0.048) and were more likely to have localized disease (61.4% versus 44.3%, p = 0.01). In multivariable analysis, patients undergoing PA demonstrated similar all-cause mortality (HR = 0.71, 95% CI 0.44-1.14, p = 0.16) and cancer-specific mortality (HR = 0.64, 95% CI 0.35-1.17, p = 0.15) compared to those who underwent TA. Following 1:1 propensity score matching, Kaplan-Meier analysis revealed no difference in overall survival between PA and TA groups (p = 0.26) nor was there a difference in the cumulative incidence of cancerspecific mortality (p = 0.29). Conclusions In this first population-level comparison of outcomes among patients with pheochromocytoma undergoing PA and those undergoing TA, we found no long-term differences in any survival metric between groups. PA circumvents the need for lifelong corticoid replacement therapy and remains a promising option for patients with bilateral or recurrent pheochromocytoma.