Distinct components of alert fatigue in physicians' responses to a noninterruptive clinical decision support alert.

OBJECTIVE: Clinical decision support (CDS) alerts may improve health care quality but "alert fatigue" can reduce provider responsiveness. We analyzed how the introduction of competing alerts affected provider adherence to a single depression screening alert. MATERIALS AND METHODS: We analyzed the audit data from all occurrences of a CDS alert at a large academic health system. For patients who screen positive for depression during ambulatory visits, a noninterruptive alert was presented, offering a number of relevant documentation actions. Alert adherence was defined as the selection of any option offered within the alert. We assessed the effect of competing clinical guidance alerts presented during the same encounter and the total of all CDS alerts that the same provider had seen in the prior 90 days, on the probability of depression screen alert adherence, adjusting for physician and patient characteristics. RESULTS: The depression alert fired during 55 649 office visits involving 418 physicians and 40 474 patients over 41 months. After adjustment, physicians who had seen the most alerts in the prior 90 days were much less likely to respond (adjusted OR highest-lowest quartile, 0.38; 95% CI 0.35-0.42; P < .001). Competing alerts in the same visit further reduced the likelihood of adherence only among physicians in the middle two quartiles of alert exposure in the prior 90 days. CONCLUSIONS: Adherence to a noninterruptive depression alert was strongly associated with the provider's cumulative alert exposure over the past quarter. Health systems should monitor providers' recent alert exposure as a measure of alert fatigue.

Low prevalence (0.13%) of COVID-19 infection in asymptomatic pre-operative/pre-procedure patients at a large, academic medical center informs approaches to perioperative care.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has resulted in reduced performance of elective surgeries and procedures at medical centers across the United States. Awareness of the prevalence of asymptomatic disease is critical for guiding safe approaches to operative/procedural services. As COVID-19 polymerase chain reaction (PCR) testing has been limited largely to symptomatic patients, health care workers, or to those in communal care centers, data regarding asymptomatic viral disease carriage are limited. METHODS: In this retrospective observational case series evaluating UCLA Health patients enrolled in pre-operative/pre-procedure protocol COVID-19 reverse transcriptase (RT)-PCR testing between April 7, 2020 and May 21, 2020, we determine the prevalence of COVID-19 infection in asymptomatic patients scheduled for surgeries and procedures. RESULTS: Primary outcomes include the prevalence of COVID-19 infection in this asymptomatic population. Secondary data analysis includes overall population testing results and population demographics. Eighteen of 4,751 (0.38%) patients scheduled for upcoming surgeries and high-risk procedures had abnormal (positive/inconclusive) COVID-19 RT-PCR testing results. Six of 18 patients were confirmed asymptomatic and had positive test results. Four of 18 were confirmed asymptomtic and had inconclusive results. Eight of 18 had positive results in the setting of recent symptoms or known COVID-19 infection. The prevalence of asymptomatic COVID-19 infection was 0.13%. More than 90% of patients had residential addresses within a 67-mile geographic radius of our medical center, the median age was 58, and there was equal male/female distribution. CONCLUSION: These data demonstrating low levels (0.13% prevalence) of COVID-19 infection in an asymptomatic population of patients undergoing scheduled surgeries/procedures in a large urban area have helped to inform perioperative protocols during the COVID-19 pandemic. Testing protocols like ours may prove valuable for other health systems in their approaches to safe procedural practices during COVID-19.

International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium.

We leveraged the largely untapped resource of electronic health record data to address critical clinical and epidemiological questions about Coronavirus Disease 2019 (COVID-19). To do this, we formed an international consortium (4CE) of 96 hospitals across five countries (www.covidclinical.net). Contributors utilized the Informatics for Integrating Biology and the Bedside (i2b2) or Observational Medical Outcomes Partnership (OMOP) platforms to map to a common data model. The group focused on temporal changes in key laboratory test values. Harmonized data were analyzed locally and converted to a shared aggregate form for rapid analysis and visualization of regional differences and global commonalities. Data covered 27,584 COVID-19 cases with 187,802 laboratory tests. Case counts and laboratory trajectories were concordant with existing literature. Laboratory tests at the time of diagnosis showed hospital-level differences equivalent to country-level variation across the consortium partners. Despite the limitations of decentralized data generation, we established a framework to capture the trajectory of COVID-19 disease in patients and their response to interventions.