Background The COVID-19 pandemic has broader geographic spread and potentially longer lasting effects than those of previous disasters. Necessary preventive precautions for the transmission of COVID-19 has resulted in delays for in-person health care services, especially at the outset of the pandemic. Objective Among a US sample, we examined the rates of delays (defined as cancellations and postponements) in health care at the outset of the pandemic and characterized the reasons for such delays. Methods As part of an internet-based survey that was distributed on social media in April 2020, we asked a US–based convenience sample of 2570 participants about delays in their health care resulting from the COVID-19 pandemic. Participant demographics and self-reported worries about general health and the COVID-19 pandemic were explored as potent determinants of health care delays. In addition to all delays, we focused on the following three main types of delays, which were the primary outcomes in this study: dental, preventive, and diagnostic care delays. For each outcome, we used bivariate statistical tests (t tests and chi-square tests) and multiple logistic regression models to determine which factors were associated with health care delays. Results The top reported barrier to receiving health care was the fear of SARS-CoV-2 infection (126/374, 33.6%). Almost half (1227/2570, 47.7%) of the participants reported experiencing health care delays. Among those who experienced health care delays and further clarified the type of delay they experienced (921/1227, 75.1%), the top three reported types of care that were affected by delays included dental (351/921, 38.1%), preventive (269/921, 29.2%), and diagnostic (151/921, 16.4%) care. The logistic regression models showed that age (P<.001), gender identity (P<.001), education (P=.007), and self-reported worry about general health (P<.001) were significantly associated with experiencing health care delays. Self-reported worry about general health was negatively related to experiencing delays in dental care. However, this predictor was positively associated with delays in diagnostic testing based on the logistic regression model. Additionally, age was positively associated with delays in diagnostic testing. No factors remained significant in the multiple logistic regression for delays in preventive care, and although there was trend between race and delays (people of color experienced fewer delays than White participants), it was not significant (P=.06). Conclusions The lessons learned from the initial surge of COVID-19 cases can inform systemic mitigation strategies for potential future disruptions. This study addresses the demand side of health care delays by exploring the determinants of such delays. More research on health care delays during the pandemic is needed, including research on their short- and long-term impacts on patient-level outcomes such as mortality, morbidity, mental health, people’s quality of life, and the experience of pain.
Adopting an interdisciplinary perspective, this article reports new evidence on the impact of age and experience on work unit performance. Two types of experience that increase with age are “general” and “firm-specific.” The focus here is on the influence of general human capital (which increases with time spent in the workforce) and firm-specific human capital (which increases with tenure with the current employer) on work unit performance. Although age–performance relationships have been investigated extensively in two research literatures, psychology and economics, neither addresses such relationships at the unit-within-organization level of analysis, concentrating instead on age–performance relationships at individual, organizational, or national levels. Using a unique data set comprised of large-sample, long-duration, multivariate studies of unit performance within firms this meta-analysis synthesizes partial effect sizes for the effects of age and tenure. A key finding is that tenure positively affects unit performance whereas age has no effect. Work unit leaders’ tenure but not age was found to positively affect unit performance. The lack of evidence of an age–performance relationship is consistent with psychological research at the individual level but contravenes economics research literature which, at all levels of analysis, generally reports negative relationships between age and performance. Neither the heterogeneity of tenure nor age was related to performance nor was there evidence of nonlinearities in relationships. Practical implications of the findings are discussed regarding ageism and employers’ use of gig or contract workers. Implications for future research and theory focus on interdisciplinary theory development and the scientific contribution of organizationally based research.
BACKGROUND The COVID-19 pandemic has broader geographic spread and potentially longer lasting effects than those of previous disasters. Necessary preventive precautions for the transmission of COVID-19 has resulted in delays for in-person health care services, especially at the outset of the pandemic. OBJECTIVE Among a US sample, we examined the rates of delays (defined as cancellations and postponements) in health care at the outset of the pandemic and characterized the reasons for such delays. METHODS As part of an internet-based survey that was distributed on social media in April 2020, we asked a US–based convenience sample of 2570 participants about delays in their health care resulting from the COVID-19 pandemic. Participant demographics and self-reported worries about general health and the COVID-19 pandemic were explored as potent determinants of health care delays. In addition to all delays, we focused on the following three main types of delays, which were the primary outcomes in this study: dental, preventive, and diagnostic care delays. For each outcome, we used bivariate statistical tests (<i>t</i> tests and chi-square tests) and multiple logistic regression models to determine which factors were associated with health care delays. RESULTS The top reported barrier to receiving health care was the fear of SARS-CoV-2 infection (126/374, 33.6%). Almost half (1227/2570, 47.7%) of the participants reported experiencing health care delays. Among those who experienced health care delays and further clarified the type of delay they experienced (921/1227, 75.1%), the top three reported types of care that were affected by delays included dental (351/921, 38.1%), preventive (269/921, 29.2%), and diagnostic (151/921, 16.4%) care. The logistic regression models showed that age (<i>P</i><.001), gender identity (<i>P</i><.001), education (<i>P</i>=.007), and self-reported worry about general health (<i>P</i><.001) were significantly associated with experiencing health care delays. Self-reported worry about general health was negatively related to experiencing delays in dental care. However, this predictor was positively associated with delays in diagnostic testing based on the logistic regression model. Additionally, age was positively associated with delays in diagnostic testing. No factors remained significant in the multiple logistic regression for delays in preventive care, and although there was trend between race and delays (people of color experienced fewer delays than White participants), it was not significant (<i>P</i>=.06). CONCLUSIONS The lessons learned from the initial surge of COVID-19 cases can inform systemic mitigation strategies for potential future disruptions. This study addresses the demand side of health care delays by exploring the determinants of such delays. More research on health care delays during the pandemic is needed, including research on their short- and long-term impacts on patient-level outcomes such as mortality, morbidity, mental health, people’s quality of life, and the experience of pain.
Recognition and treatment of maternal hypotension during epidural anesthesia administration for intrapartum cesarean delivery preserves maternal-fetal perfusion. A case that required quality assurance review uncovered lapses in maternal hemodynamic monitoring during the transition to intrapartum cesarean delivery anesthesia. To address this, a practice outline was designed for trainee’s education describing intrapartum epidural dosing for cesarean delivery and adequate blood pressure monitoring. The time-lapse between epidural dosing and subsequent blood pressure was evaluated before and after the introduction of our educational tool. The time-lapse between blood pressure measures decreased to <10 minutes (10.78–13.92 vs 8.8–9.76 minutes).
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