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Background: Cognitive computing has promising potential to assist trial matching efficiency and accuracy by utilizing natural language processing and performing background analytics. The Watson for Clinical Trial Matching (CTM) cognitive system derives patient and tumor attributes from unstructured text in the electronic health record that can be matched to complex eligibility criteria in trial protocols. The Watson for CTM system was trained by Mayo Clinic subject matter experts in collaboration with IBM computer scientists/engineers and implemented in the Breast Oncology practice in July 2016. Metrics have shown an average monthly enrollment increase of 84% for breast systemic therapy trials. Methods: Training of Watson for CTM has continued with inclusion of additional cancers and expansion of trial types including Phase 1, supportive care, biomarker and observational trials. Watson for CTM was piloted in Lung Oncology in July 2018 and fully implemented in October 2018. Clinical research coordinators (CRCs) validated Watson-derived clinical trial matches on the day prior to patient clinic visits. A list of matched trials for each patient was given to providers to facilitate treatment decision making at point of care. Screening and timing metrics were tracked and compared with manual screening methods. Results: Watson for CTM facilitated screening of all lung cancer patients against 42 trials. Based on preset criteria, matches were validated by CRCs and provided to lung oncology providers in 69% (1818/2637) of patients' visits from July through December 2018. Watson CTM-assisted patient matches resulted in a more complete list of potentially eligible trials and were completed in less than 50% of the time as compared to the traditional manual method. Enrollment data to define the impact of Watson for CTM and a screening team in the lung oncology practice is immature and will be subsequently reported. Conclusions: Implementation of the Watson for CTM system with a screening team enabled high volume patient screening for a large number of clinical trials in an efficient manner and promoted awareness of clinical trial opportunities within the lung oncology practice.

Background: Anemia management in chronic hemodialysis (HD) has been affected by the implementation of the prospective payment system (PPS) and changes in clinical guidelines. These factors could impact red blood cell (RBC) transfusion in HD patients. Our distinctive care system contains complete records for all RBC transfusions among our HD patients. Aims: To determine RBC transfusions in patients with prevalent chronic HD, site of administration (inpatient or outpatient), and ordering physician specialty for inpatients; compare pre- and post-PPS RBC transfusions; and compare RBC transfusions during changes in desired outpatient hemoglobin (Hb) range for patients with chronic HD. Methods: Retrospective analysis of medical and blood bank records for patients with prevalent chronic HD July 2009 through June 2013. Results: In total, 310-356 patients were studied. Mean (SD) units of RBCs per 100 patients per month for the study's 48 months were outpatient, 2.6 (1.5), and inpatient, 9.4 (4.6). Outpatient pre-PPS RBC units transfused were 2.1 (0.6) vs. post-PPS of 2.6 (1.5; p = 0.22, t test); for inpatients pre-PPS, 7.9 (4.5) RBC units per month vs. post-PPS, 11.5 (5.1; p = 0.11, t test). Inpatient RBC transfusions accounted for 75.2% (14.2%) of all RBC transfusions; 67.3% (16.3%) of inpatient transfusions were ordered by nonnephrologists. Changes in desired Hb range for outpatient HD patients did not lead to changes in RBC transfusions. Conclusions: No changes in RBC transfusions occurred among our patients with chronic HD with PPS implementation and in desired Hb range during the study period. Most transfusions were given in inpatient settings by nonnephrologists.