Enhanced Safety and Efficiency of Ambulatory Cardiology Admissions: A Quality Improvement Initiative.

Background: Pediatric cardiac patients have experienced evolving illnesses progressing to instability while awaiting inpatient admission from ambulatory settings. Admission delays and communication breakdowns increase the risk for tenuous patients. This quality improvement initiative aimed to improve safety and efficiency for patients admitted from an ambulatory Clinic to the Acute Cardiac Care Unit (ACCU) using standardized communication and admission processes within one year. Methods: An admission process map, in-clinic nurse monitoring, and communication pathways were developed and implemented. A standardized team handoff occurred via virtual huddle using illness severity, patient summary, action list, situational awareness, and synthesis. Escalation of care events and timeliness were compared pre- and postimplementation. Results: There was a reduction of transfers to the intensive care unit within 24 hours of ACCU admission from 9.2% to 3.8% (P = 0.26), intensive care unit evaluations (without transfer) from 5.6% to 0% (P = 0.06), and arrests from 3.7% to 0% (P = 0.16). After the pilot, clinic nurses monitored 100% of at-risk patients. Overall mean time from admission decision to virtual huddle decreased from 81 to 61 minutes and mean time to admission from 144 to 115 minutes, with 41% (n = 33) arriving ≤ 60 minutes (goal). The COVID-19 pandemic negatively affected admission timeliness while safety metrics remained optimized. Conclusions: Implementing a standardized admission process between the Clinic and ACCU enhanced safety by reducing admission wait time and escalation of care post-admission. Sustainable, reliable handoff processes, in-clinic monitoring, and standardized admission processes were established. The pandemic hindered admission efficiency without compromising safety.

Trading off accuracy and explainability in AI decision-making: findings from 2 citizens' juries.

OBJECTIVE: To investigate how the general public trades off explainability versus accuracy of artificial intelligence (AI) systems and whether this differs between healthcare and non-healthcare scenarios. MATERIALS AND METHODS: Citizens' juries are a form of deliberative democracy eliciting informed judgment from a representative sample of the general public around policy questions. We organized two 5-day citizens' juries in the UK with 18 jurors each. Jurors considered 3 AI systems with different levels of accuracy and explainability in 2 healthcare and 2 non-healthcare scenarios. Per scenario, jurors voted for their preferred system; votes were analyzed descriptively. Qualitative data on considerations behind their preferences included transcribed audio-recordings of plenary sessions, observational field notes, outputs from small group work and free-text comments accompanying jurors' votes; qualitative data were analyzed thematically by scenario, per and across AI systems. RESULTS: In healthcare scenarios, jurors favored accuracy over explainability, whereas in non-healthcare contexts they either valued explainability equally to, or more than, accuracy. Jurors' considerations in favor of accuracy regarded the impact of decisions on individuals and society, and the potential to increase efficiency of services. Reasons for emphasizing explainability included increased opportunities for individuals and society to learn and improve future prospects and enhanced ability for humans to identify and resolve system biases. CONCLUSION: Citizens may value explainability of AI systems in healthcare less than in non-healthcare domains and less than often assumed by professionals, especially when weighed against system accuracy. The public should therefore be actively consulted when developing policy on AI explainability.

Replication protein A subunit 3 and the iron efficiency response in soybean.

In soybean [Glycine max (L.) Merr.], iron deficiency results in interveinal chlorosis and decreased photosynthetic capacity, leading to stunting and yield loss. In this study, gene expression analyses investigated the role of soybean replication protein A (RPA) subunits during iron stress. Nine RPA homologs were significantly differentially expressed in response to iron stress in the near isogenic lines (NILs) Clark (iron efficient) and Isoclark (iron inefficient). RPA homologs exhibited opposing expression patterns in the two NILs, with RPA expression significantly repressed during iron deficiency in Clark but induced in Isoclark. We used virus induced gene silencing (VIGS) to repress GmRPA3 expression in the iron inefficient line Isoclark and mirror expression in Clark. GmRPA3-silenced plants had improved IDC symptoms and chlorophyll content under iron deficient conditions and also displayed stunted growth regardless of iron availability. RNA-Seq comparing gene expression between GmRPA3-silenced and empty vector plants revealed massive transcriptional reprogramming with differential expression of genes associated with defense, immunity, aging, death, protein modification, protein synthesis, photosynthesis and iron uptake and transport genes. Our findings suggest the iron efficient genotype Clark is able to induce energy controlling pathways, possibly regulated by SnRK1/TOR, to promote nutrient recycling and stress responses in iron deficient conditions.