Cancer patients are presumed to be at increased risk from COVID-19 infection fatality due to underlying malignancy, treatment-related immunosuppression, or increased comorbidities. A total of 218 COVID-19 positive patients from March 18th-April 8th, 2020 with a malignant diagnosis were identified. A total of 61 (28%) cancer patients died from COVID-19 with a case fatality rate (CFR) of 37% (20/54) for hematologic malignancies and 25% (41/164) for solid malignancies. 6/11 (55%) lung cancer patients died from COVID-19 disease. Increased mortality was significantly associated with older age, multiple comorbidities, need for ICU support, and elevated levels of D-Dimers, LDH and lactate on multivariable analysis. Ageadjusted CFRs in cancer patients compared to non-cancer patients at our institution and NYC reported a significant increase in case fatality for cancer patients. These data suggest the need for proactive strategies to reduce likelihood of infection and improve early identification in this vulnerable patient population.Research.on June 9, 2020.
Wrong-patient electronic orders occur frequently with computerized provider order entry systems, and electronic interventions can reduce the risk of these errors occurring.
Because there can be no delay in providing identification wristbands to newborns, some hospitals assign newborns temporary first names such as Babyboy or Babygirl. These nondistinct naming conventions result in a large number of patients with similar identifiers in NICUs. To determine the level of risk associated with nondistinct naming conventions, we performed an intervention study to evaluate if assigning distinct first names at birth would result in a reduction in wrong-patient errors.
The risk of wrong-patient orders in the NICU was significantly higher than in non-NICU pediatric units. Implementation of a combined ID reentry intervention and distinct naming convention greatly reduced this risk.
IMPORTANCE Recommendations in the United States suggest limiting the number of patient records displayed in an electronic health record (EHR) to 1 at a time, although little evidence supports this recommendation. OBJECTIVE To assess the risk of wrong-patient orders in an EHR configuration limiting clinicians to 1 record vs allowing up to 4 records opened concurrently. DESIGN, SETTING, AND PARTICIPANTS This randomized clinical trial included 3356 clinicians at a large health system in New York and was conducted from October 2015 to April 2017 in emergency department, inpatient, and outpatient settings. INTERVENTIONS Clinicians were randomly assigned in a 1:1 ratio to an EHR configuration limiting to 1 patient record open at a time (restricted; n = 1669) or allowing up to 4 records open concurrently (unrestricted; n = 1687). MAIN OUTCOMES AND MEASURES The unit of analysis was the order session, a series of orders placed by a clinician for a single patient. The primary outcome was order sessions that included 1 or more wrong-patient orders identified by the Wrong-Patient Retract-and-Reorder measure (an electronic query that identifies orders placed for a patient, retracted, and then reordered shortly thereafter by the same clinician for a different patient). RESULTS Among the 3356 clinicians who were randomized (mean [SD] age, 43.1 [12.5] years; mean [SD] experience at study site, 6.5 [6.0] years; 1894 females [56.4%]), all provided order data and were included in the analysis. The study included 12 140 298 orders, in 4 486 631 order sessions, placed for 543 490 patients. There was no significant difference in wrong-patient order sessions per 100 000 in the restricted vs unrestricted group, respectively, overall (90.7 vs 88.0; odds ratio [OR], 1.03 [95% CI, 0.90-1.20];
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.