No abstract

ObjectiveTo conduct a systematic review and meta-analysis to ascertain the impact of operating room (OR) to intensive care unit (ICU) handoff interventions on process-based and clinical outcomes.MethodWe included all English language, prospective evaluation studies of OR to ICU handoff interventions published as original research articles in peer-reviewed journals. The search was conducted on 11 November 2019 on MEDLINE, CINAHL, EMBASE, Scopus and the Cochrane Central Register of Controlled Trials databases, with no prespecified criteria for the type of comparison or outcome. A meta-analysis of similar outcomes was conducted using a random effects model. Quality was assessed using a modified Downs and Black (D&B) checklist.Results32 studies were included for review. 31 studies were conducted at a single site and 28 studies used an observational study design with a control. Most studies (n=28) evaluated bundled interventions which comprised information transfer/communication checklists and protocols. Meta-analysis showed that the handoff intervention group had statistically significant improvements in time to analgesia dosing (mean difference (MD)=−42.51 min, 95% CI −60.39 to −24.64), fewer information omissions (MD=−2.22, 95% CI −3.68 to –0.77), fewer technical errors (MD=−2.38, 95% CI −4.10 to –0.66) and greater information sharing scores (MD=30.03%, 95% CI 19.67% to 40.40%). Only 15 of the 32 studies scored above 9 points on the modified D&B checklist, indicating a lack of high-quality studies.DiscussionBundled interventions were commonly used to support OR to ICU handoff standardisation. Although the meta-analysis showed significant improvements for a number of clinical and process outcomes, the statistical and clinical heterogeneity must be accounted for when interpreting these findings. Implications for OR to ICU handoff practice and future research are discussed.

Objective The Anesthesiology Control Tower (ACT) for operating rooms (ORs) remotely assesses the progress of surgeries and provides real-time perioperative risk alerts, communicating risk mitigation recommendations to bedside clinicians. We aim to identify and map ACT-OR nonroutine events (NREs)—risk-inducing or risk-mitigating workflow deviations—and ascertain ACT’s impact on clinical workflow and patient safety. Materials and Methods We used ethnographic methods including shadowing ACT and OR clinicians during 83 surgeries, artifact collection, chart reviews for decision alerts sent to the OR, and 10 clinician interviews. We used hybrid thematic analysis informed by a human-factors systems-oriented approach to assess ACT’s role and impact on safety, conducting content analysis to assess NREs. Results Across 83 cases, 469 risk alerts were triggered, and the ACT sent 280 care recommendations to the OR. 135 NREs were observed. Critical factors facilitating ACT’s role in supporting patient safety included providing backup support and offering a fresh-eye perspective on OR decisions. Factors impeding ACT included message timing and ACT and OR clinician cognitive lapses. Suggestions for improvement included tailoring ACT message content (structure, timing, presentation) and incorporating predictive analytics for advanced planning. Discussion ACT served as a safety net with remote surveillance features and as a learning healthcare system with feedback/auditing features. Supporting strategies include adaptive coordination and harnessing clinician/patient support to improve ACT’s sustainability. Study insights inform future intraoperative telemedicine design considerations to mitigate safety risks. Conclusion Incorporating similar remote technology enhancement into routine perioperative care could markedly improve safety and quality for millions of surgical patients.

Background Handoffs or care transitions from the operating room (OR) to intensive care unit (ICU) are fragmented and vulnerable to communication errors. Although protocols and checklists for standardization help reduce errors, such interventions suffer from limited sustainability. An unexplored aspect is the potential role of developing personalized postoperative transition interventions using artificial intelligence (AI)-generated risks. Objectives This study was aimed to (1) identify factors affecting sustainability of handoff standardization, (2) utilize a human-centered approach to develop design ideas and prototyping requirements for a sustainable handoff intervention, and (3) explore the potential role for AI risk assessment during handoffs. Methods We conducted four design workshops with 24 participants representing OR and ICU teams at a large medical academic center. Data collection phases were (1) open-ended questions, (2) closed card sorting of handoff information elements, and (3) scenario-based design ideation and prototyping for a handoff intervention. Data were analyzed using thematic analysis. Card sorts were further tallied to characterize handoff information elements as core, flexible, or unnecessary. Results Limited protocol awareness among clinicians and lack of an interdisciplinary electronic health record (EHR)-integrated handoff intervention prevented long-term sustainability of handoff standardization. Clinicians argued for a handoff intervention comprised of core elements (included for all patients) and flexible elements (tailored by patient condition and risks). They also identified unnecessary elements that could be omitted during handoffs. Similarities and differences in handoff intervention requirements among physicians and nurses were noted; in particular, clinicians expressed divergent views on the role of AI-generated postoperative risks. Conclusion Current postoperative handoff interventions focus largely on standardization of information transfer and handoff processes. Our design approach allowed us to visualize accurate models of user expectations for effective interdisciplinary communication. Insights from this study point toward EHR-integrated, “flexibly standardized” care transition interventions that can automatically generate a patient-centered summary and risk-based report.

Circulating tumor cells (CTC) in cerebrospinal uid (CSF) are a quantitative diagnostic tool for leptomeningeal metastases (LM) from solid tumors, but their prognostic signi cance is unclear. Our objective was to evaluate CSF-CTC quanti cation in predicting outcomes in LM. MethodsThis is a single institution retrospective study of patients with solid tumors who underwent CSF-CTC quanti cation using the CellSearch® platform between 04/2016-06/2019. Information on neuroaxis imaging, CSF results, and survival was collected. LM was diagnosed by MRI and/or CSF cytology. Survival analyses were performed using multivariable Cox proportional hazards modeling, and CSF-CTC splits associated with survival were identi ed through recursive partitioning analysis. ResultsOut of 290 patients with CNS metastases, we identi ed a cohort of 101 patients with newly diagnosed LM. In this group, CSF-CTC count (median 200 CTCs/3ml) predicted survival continuously (HR = 1.005, 95% CI: 1.002-1.009, p = 0.0027), and the risk of mortality doubled (HR = 2.84, 95% CI: 1.45-5.56, p = 0.0023) at the optimal cutoff of ≥ 61 CSF-CTCs/3ml. Neuroimaging ndings of LM (assessed by 3 independent neuroradiologists) were associated with a higher CSF-CTC count (median CSF-CTCs range 1.5-4 for patients without radiographic LM vs 200 for patients with radiographic LM, p<0.001), but did not predict survival. ConclusionOur data shows that CSF-CTCs quanti cation predicts survival in newly diagnosed LM, and outperforms neuroimaging. CSF-CTC analysis can be used as a prognostic tool in patients with LM and provides quantitative assessment of disease burden in the CNS compartment.