EHR downtime events pose patient safety hazards, and we highlight critical areas for downtime procedure improvement.

Objective To identify physiological correlates to stress in intensive care unit nurses. Background Most research on stress correlates are done in laboratory environments; naturalistic investigation of stress remains a general gap. Method Electrodermal activity, heart rate, and skin temperatures were recorded continuously for 12-hr nursing shifts (23 participants) using a wrist-worn wearable technology (Empatica E4). Results Positive correlations included stress and heart rate (ρ = .35, p < .001), stress and skin temperature (ρ = .49, p < .05), and heart rate and skin temperatures (ρ = .54, p = .0008). Discussion The presence and direction of some correlations found in this study differ from those anticipated from prior literature, illustrating the importance of complementing laboratory research with naturalistic studies. Further work is warranted to recognize nursing activities associated with a high level of stress and the underlying reasons associated with changes in physiological responses. Application Heart rate and skin temperature may be used for real-time detection of stress, but more work is needed to validate such surrogate measures.

Electronic health record downtimes are any period where the computer systems are unavailable, either for planned or unexpected events. During an unexpected downtime, healthcare workers are rapidly forced to use rarely-practiced, paper-based methods for healthcare delivery. In some instances, patient safety is compromised or data exposed to parties seeking profit. This review provides a foundational perspective of the current state of downtime readiness as organizations prepare to handle downtime events. A search of technical news media related to healthcare informatics and a scoping review of the research literature were conducted. Findings ranged from theoretical exploration of downtime to empirical direct comparison of downtime versus normal operation. Overall, 166 US hospitals experienced a total of 701 days of downtime in 43 events between 2012 and 2018. Almost half (48.8%) of the published downtime events involved some form of cyber-attacks. Downtime contingency planning is still predominantly considered through a top-down organizational focus. We propose that a bottom-up approach, involving the front-line clinical staff responsible for executing the downtime procedure, will be beneficial. Significant new research support for the development of contingency plans will be needed.

Introduction Electronic health record (EHR) downtime is any period during which the EHR system is fully or partially unavailable. These periods are operationally disruptive and pose risks to patients. EHR downtime has not sufficiently been studied in the literature, and most hospitals are not adequately prepared. Objective The objective of this study was to assess the operational implications of downtime with a focus on the clinical laboratory, and to derive recommendations for improved downtime contingency planning. Methods A hybrid qualitative–quantitative study based on historic performance data and semistructured interviews was performed at two mid-Atlantic hospitals. In the quantitative analysis, paper records from downtime events were analyzed and compared with normal operations. To enrich this quantitative analysis, interviews were conducted with 17 hospital employees, who had experienced several downtime events, including a hospital-wide EHR shutdown. Results During downtime, laboratory testing results were delayed by an average of 62% compared with normal operation. However, the archival data were incomplete due to inconsistencies in the downtime paper records. The qualitative interview data confirmed that delays in laboratory result reporting are significant, and further uncovered that the delays are often due to improper procedural execution, and incomplete or incorrect documentation. Interviewees provided a variety of perspectives on the operational implications of downtime, and how to best address them. Based on these insights, recommendations for improved downtime contingency planning were derived, which provide a foundation to enhance Safety Assurance Factors for EHR Resilience guides. Conclusion This study documents the extent to which downtime events are disruptive to hospital operations. It further highlights the challenge of quantitatively assessing the implication of downtimes events, due to a lack of otherwise EHR-recorded data. Organizations that seek to improve and evaluate their downtime contingency plans need to find more effective methods to collect data during these times.