RESUMEN
Anecdotal reports indicate that many animal shelters experienced increased adoption and foster care rates during the COVID-19 pandemic, yet peer-reviewed evidence is lacking. In this pilot survey of 14 animal shelters in the Northeastern United States, we aimed to investigate the impact of the COVID-19 pandemic on animal intakes, foster care and five outcome types and describe operational changes reported by shelters in response to COVID-19. Paired sample t-tests and Wilcoxon signed-rank tests were used to compare intake, adoption, euthanasia and foster care rates and numbers between March-June 2019 and 2020. The number of dogs and cats that entered shelters was significantly lower during the COVID-19 pandemic compared with the same months of 2019 (t = 3.41, p = 0.01, t = 2.69, p = 0.02). Although the overall rate of adoption and euthanasia did not differ, the numbers adopted and euthanized decreased significantly for both dogs and cats, reflecting the significantly decreased intake. We also found significant variability between shelters. During the pandemic, several shelters sought to expand their foster care networks through operational changes (n = 6) and statements made to the public (n = 7). However, the proportion of dogs and cats housed in foster care did not differ between March-June 2019 and 2020 in our sample. Our findings offer preliminary insights regarding the impact of a worldwide pandemic on the functioning of animal shelters.
RESUMEN
OBJECTIVE: To identify features of clinical decision support systems critical for improving clinical practice. DESIGN: Systematic review of randomised controlled trials. DATA SOURCES: Literature searches via Medline, CINAHL, and the Cochrane Controlled Trials Register up to 2003; and searches of reference lists of included studies and relevant reviews. STUDY SELECTION: Studies had to evaluate the ability of decision support systems to improve clinical practice. DATA EXTRACTION: Studies were assessed for statistically and clinically significant improvement in clinical practice and for the presence of 15 decision support system features whose importance had been repeatedly suggested in the literature. RESULTS: Seventy studies were included. Decision support systems significantly improved clinical practice in 68% of trials. Univariate analyses revealed that, for five of the system features, interventions possessing the feature were significantly more likely to improve clinical practice than interventions lacking the feature. Multiple logistic regression analysis identified four features as independent predictors of improved clinical practice: automatic provision of decision support as part of clinician workflow (P < 0.00001), provision of recommendations rather than just assessments (P = 0.0187), provision of decision support at the time and location of decision making (P = 0.0263), and computer based decision support (P = 0.0294). Of 32 systems possessing all four features, 30 (94%) significantly improved clinical practice. Furthermore, direct experimental justification was found for providing periodic performance feedback, sharing recommendations with patients, and requesting documentation of reasons for not following recommendations. CONCLUSIONS: Several features were closely correlated with decision support systems' ability to improve patient care significantly. Clinicians and other stakeholders should implement clinical decision support systems that incorporate these features whenever feasible and appropriate.