Trends in suicidal ideation in an emergency department during COVID-19.

OBJECTIVE: This study aims to detail changes in presentations at a United States Emergency Department for suicidality before and after the outbreak of COVID-19. METHODS: A retrospective chart review was conducted of all adult patients who presented to an ED with suicidality and underwent psychiatric consultation during the study period. The cohorts consisted of patients who presented between December 2018 - May 2019 and December 2019 - May 2020. Information was collected on demographics, characteristics of suicidality, reasons for suicidality and disposition. The first wave from March - May 2020 was examined, using a difference-in-differences design to control for factors other than COVID-19 that may have influenced the outcomes' trend. RESULTS: Immediately following the pandemic outbreak there was a statistically significant increase in the proportion of undomiciled patients represented in visits for suicidality (40.7% vs. 57.4%; p-value <0.001). In addition, the proportion of patient visits attributed to social (18.0% vs. 29.2%; p-value 0.003) and structural (14.2% vs. 26.4%; p value <0.001) reasons for suicidality increased. Conversely, the proportion of visits due to psychiatric symptoms (70.5% vs 50.0%; p-value <0.001) decreased. Furthermore, patient visits were more likely to result in a medical admission (2.1% vs. 8.3%; p-value 0.002) and less likely to result in a psychiatric admission (68.4% vs 48.6%; p-value <0.001) during the initial phase of the pandemic. CONCLUSIONS: COVID-19 was associated with increased ED presentations for suicidality among undomiciled patients, as well as greater likelihood of social and structural reasons driving suicidality among all visits.

Awakenings? Patient and Hospital Staff Perceptions of Nighttime Disruptions and Their Effect on Patient Sleep.

STUDY OBJECTIVES: Although important to recovery, sleeping in the hospital is difficult because of disruptions. Understanding how patients, hospital physicians, and nurses perceive sleep disruptions and identifying which disruptions are associated with objective sleep loss can help target improvement initiatives. METHODS: Patients and hospital staff completed the Potential Hospital Sleep Disruptions and Noises Questionnaire (PHSDNQ). Cutoff points were defined based on means, and responses were dichotomized. Perceived percent disrupted for each item was calculated, and responses were compared across groups using chi-square tests. Objective sleep time of patients was measured using wrist actigraphy. The association between patient-reported disruptions and objective sleep time was assessed using a multivariable linear regression model controlling for subject random effects. RESULTS: Twenty-eight physicians (78%), 37 nurses (88%), and 166 of their patients completed the PHSDNQ. Patients, physicians, and nurses agreed that pain, vital signs and tests were the top three disrupters to patient sleep. Significant differences among the groups' perceptions existed for alarms [24% (patients) vs. 46% (physicians) vs. 27% (nurses), p < 0.040], room temperature (15% vs. 0% vs. 5%, p < 0.031) and anxiety (18% vs. 21% vs. 38%, p < 0.031). Using survey and actigraphy data from 645 nights and 379 patients, the presence of pain was the only disruption associated with lower objective sleep duration (minutes) [-38.1 (95% confidence interval -63.2, -12.9) p < 0.003]. CONCLUSION: Hospital staff and patients agreed that pain, vital signs and tests were top sleep disrupters. However, pain was associated with the greatest objective sleep loss, highlighting the need for proactive screening and management of patient pain to improve sleep in hospitals.

A tutorial on activity-based costing of electronic health records.

As the American Recovery and Restoration Act of 2009 allocates $19 billion to health information technology, it will be useful for health care managers to project the true cost of implementing an electronic health record (EHR). This study presents a step-by-step guide for using activity-based costing (ABC) to estimate the cost of an EHR. ABC is a cost accounting method with a "top-down" approach for estimating the cost of a project or service within an organization. The total cost to implement an EHR includes obvious costs, such as licensing fees, and hidden costs, such as impact on productivity. Unlike other methods, ABC includes all of the organization's expenditures and is less likely to miss hidden costs. Although ABC is used considerably in manufacturing and other industries, it is a relatively new phenomenon in health care. ABC is a comprehensive approach that the health care field can use to analyze the cost-effectiveness of implementing EHRs. In this article, ABC is applied to a health clinic that recently implemented an EHR, and the clinic is found to be more productive after EHR implementation. This methodology can help health care administrators assess the impact of a stimulus investment on organizational performance.