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The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the staggering mismatch between healthcare system capacity and patient demand. The healthcare industry has been a relatively slow adopter of digital innovation due to the conventional belief that humans need to be at the center of healthcare delivery tasks. However, in the setting of the COVID-19 pandemic, artificial intelligence (AI) may be used to carry out specific tasks such as pre-hospital triage and enable clinicians to deliver care at scale. Recognizing that the majority of COVID-19 cases are mild and do not require hospitalization, Partners HealthCare (now Mass General Brigham) implemented a digitally-automated pre-hospital triage solution to direct patients to the appropriate care setting before they showed up at the emergency department and clinics, which would otherwise consume resources, expose other patients and staff to potential viral transmission, and further exacerbate supply-and-demand mismatching. Although the use of AI has been well-established in other industries to optimize supply and demand matching, the introduction of AI to perform tasks remotely that were traditionally performed in-person by clinical staff represents a significant milestone in healthcare operations strategy., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objective: The aim of this study was to evaluate whether preoperative diabetes management can improve glycemic control and clinical outcomes after elective surgery., Background: There is lack of data on the importance of diabetes treatment before elective surgery. Diabetes is often ignored before surgery and aggressively treated afterwards., Methods: Patients with diabetes were identified and treated proactively before their scheduled surgeries. Data for all elective surgeries over 2 years before and 2 years after implementation of the program were collected., Results: Out of 31,392 patients undergoing first surgery, 3909 had diabetes; 2072 before and 1835 after the program. Mean blood glucose on the day of surgery was 146.4 ± 51.9 mg/dL before and 139.9 ± 45.6 mg/dL after the program (P = 0.0028). Proportion of patients seen by the inpatient diabetes team increased. Mean blood glucose during hospital stay was 166.7 ± 42.9 mg/dL before and 158.3 ± 46.6 mg/dL after program (P < 0.0001). The proportion of patients with hypoglycemic episodes (<50 mg/dL) was 4.93% before and 2.48% after the program (P < 0.0001). Length of hospital stay (LOS) decreased among patients with diabetes (4.8 ± 5.3 to 4.6 ± 4.3 days; P = 0.01) and remained unchanged among patients without diabetes (4.0 ± 4.5 and 4.1 ± 4.8, respectively; P = 0.42). Changes in intravenous antibiotic use, patients discharged to home, renal insufficiency, myocardial infarction, stroke, and in-hospital mortality were similar among diabetic and nondiabetic groups., Conclusions: Preoperative and inpatient diabetes management improves glycemic control on the day of surgery and postoperatively and decreases the incidence of hypoglycemia. These changes may eventually improve clinical outcomes. Although statistically significant, the decrease in LOS was of equivocal clinical significance in this study.