Christina L. Cifra

Objectives: Inter-facility transfers to the pediatric intensive care unit (PICU) increase the risk of patient harm from communication breakdowns. We previously developed I-PASS-to-PICU, a structured inter-facility handoff program to improve information exchange during these transitions. However, it was not designed to optimize communication related to diagnosis (diagnostic handoff). This exploratory study evaluated how well I-PASS-to-PICU facilitated inter-facility diagnostic handoffs. Methods: Using mixed methods, we analyzed audio-recorded referral calls to a single PICU to characterize inter-facility diagnostic handoff communication before and after I-PASS-to-PICU implementation. Two pediatric intensivists trained to review calls indicated whether diagnosis-relevant information or activities were discussed. Discrepancies in review were resolved via consensus. Reviewers also provided qualitative observations on diagnosis-related discussions. Results: Forty-four referral calls were reviewed (16 pre-and 28 post-I-PASS-to-PICU implementation). Compared with unstructured handoffs, I-PASS-to-PICU use did not result in statistically significant differences in the communication of diagnosis-related information in inter-facility handoffs. However, we observed some absolute differences; there were more calls using I-PASS-to-PICU in which illness severity was discussed (75 % vs. 50 %) and the primary diagnosis was stated by the referring clinician (68 % vs. 44 %) or receiving PICU physician (39 % vs. 25 %). Qualitative analysis revealed that shared mental models were more effectively created when primary diagnoses and diagnostic uncertainty were discussed. Conclusions: I-PASS-to-PICU may support aspects of the inter-facility diagnostic handoff but needs further revision to facilitate consistent discussion of diagnoses and diagnostic uncertainty. Future work will focus on redesigning and evaluating I-PASS-to-PICU for improving the diagnostic handoff during inter-facility PICU transfers.

OBJECTIVES: To identify and describe changes in the geographic distribution of PICUs across the United States from 2001 to 2023. DESIGN: Cross-sectional study over three time points using geographic methods to calculate distances to the nearest PICU, change in distances to the nearest PICU over time, and changes in rates of access by census tract. SETTING: U.S. PICUs. PARTICIPANTS: None. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The primary outcome was the distance from a given U.S. census tract center to the nearest PICU. Distances were grouped by U.S. census regions and divisions. Most PICUs were located in urban areas. The median distance from census tract centers to the nearest PICU was 12.5 miles (interquartile range [IQR], 4.5–37.1 miles), 12.8 miles (IQR, 4.9–36.2 miles), and 13.3 miles (IQR, 5.2–36.0 miles) for 2001, 2016, and 2023, respectively. In all years, PICUs were localized to a single city in Arkansas, Nebraska, and Oregon, and there were no PICUs in Wyoming. In 2023, the median distance to a PICU from the nearest census tract was 7.4 miles in the Middle Atlantic division (NJ, NY, and PA) and 30.1 miles in the East South Central division (AL, KY, MS, and TN). The distance to a PICU was shorter for coastal regions compared with large areas of the Mountain and Pacific divisions. CONCLUSIONS: The geographic distribution of PICUs across the U.S. varied over time, with PICU beds remaining concentrated in urban areas, whereas rural areas were farther from the nearest PICU. This results in inequitable access for critically ill children, particularly in the western U.S. Understanding the variation in geographic access to PICUs is an essential step toward ensuring equitable access to life-saving care for all children.

Introduction: The inter-facility transfer of a critically ill child to the pediatric intensive care unit (PICU) is a highly stressful time for families. This exploratory study aimed to identify care practices important to patients/families during urgent transfers of children from frontline settings to a higher level of care. Methods: We conducted a mixed methods study using surveys and interviews of parents/guardians of children transferred to a single PICU from external institutions. Participants were surveyed about their perceived importance of transfer-related care practices, specifically those addressing families' understanding of transfer, communication, family presence, and patient/family needs. A subset of parents were interviewed to characterize their transfer experience and identify improvement opportunities. Results: Of 23 patient-parent dyads who consented, 13 parents completed the initial survey, 11 completed the follow-up survey, and four participated in interviews. From the surveys, three care practices were identified as most important to responding families: 1) providing parents/guardians with verbal information about their child's condition, 2) providing patients the ability to request their parents/guardians during transfer, and 3) immediately contacting families with significant patient status changes. Interviews revealed that communication with healthcare teams is a substantial factor affecting families' experience of a smooth vs. stressful inter-facility transfer. Conclusions: In this exploratory study, care practices ensuring that timely information about a child's clinical condition is relayed to their parents/guardians were most important to families of critically ill children undergoing inter-facility transfer to the PICU. Communication between families and healthcare teams plays a significant role in families' experiences of transfer.

Background: Improving paediatric diagnosis by addressing errors (Safety-I) is insufficient for diagnostic excellence. Resilience engineering’s approach to understanding adaptations to achieve success in everyday work may elucidate how individuals and systems manage diagnostic complexity to achieve diagnostic success (Safety-II). Our objective was to characterise resilience-promoting behaviours of patients/families and clinicians and resilient organisational properties in outpatient diagnosis of children with medical complexity. Methods: This ethnographic study included observations of outpatient visits and semistructured interviews of parents/guardians and providers. Resilience engineering frameworks informed data collection and analysis. We prospectively sampled patients <18 years old with medical complexity presenting with acute problems in clinics at three academic health systems from 25 January 2024 to 26 February 2025. We qualitatively coded field notes and interview transcripts, focusing on individual resilient behaviours and instances of organisational resilience. We identified resilience themes using directed content analysis and described the frequency and types of resilience concepts. Results: We observed 258 unique resilience-promoting behaviours and organisational properties in 31 of 33 (94%) patient visits, with an average of 7.8 resilient behaviours/properties per visit. Of these, 178 (69%) reflected patient/family and clinician activities to promote diagnostic resilience and 80 (31%) reflected organisational resilience relevant to diagnosis. The most frequently identified resilience behaviours/properties were anticipation (prediction of future events and contingency planning), monitoring (vigilant observation for clinical evolution), robustness (comprehensiveness and redundancy in the diagnostic process) and graceful extensibility (stretching resources to meet diagnostic needs). Conclusions: Resilient behaviours by patients/families and clinicians and resilient organisational properties supporting diagnostic excellence can be prevalent in outpatient paediatrics for children with medical complexity. Future research should characterise diagnostic resilience’s impact on diagnostic safety and patient/family outcomes.

Background Efforts to improve diagnosis should reflect the unique needs of children; however, there is no consensus on paediatric-specific priority areas. Methods An expert panel of 25 United States (US) paediatric diagnostic excellence researchers, patient safety leaders and family partners from 15 institutions participated in a modified Delphi panel. Panellists participated in generating a literature-derived list of topics relevant to improving diagnosis. Panellists then rated agreement on each topic as a research or operational improvement priority. Topics that achieved consensus (≥75% of panellists rating them as high priority) were subsequently rated based on feasibility for implementation at the respondent’s institution. Results Literature review identified 24 topics relevant to paediatric diagnostic safety and quality, which were expanded to 62 topics during the initial panel discussion and grouped into 25 survey topics. Consensus was reached on 6 topics as research priorities and 11 as operational improvement priorities. Of these, three were deemed highly feasible for research and three for operational improvement. Research priorities included: identifying paediatric conditions at high risk for diagnostic error, developing communication methods to enhance the diagnostic process and establishing diagnostic process feedback mechanisms. Operational improvement priorities included: identifying care delivery or health services scenarios at high risk for diagnostic error, establishing interdisciplinary, structured review of cases of diagnostic error and encouraging reporting of missed opportunities for improving diagnostic safety. Conclusion Experts successfully prioritised important and feasible topics in research and practice for improving paediatric diagnosis in US academic medical centres.

Objectives: Interfacility transfers from frontline settings to the PICU can place children at risk for harm due to handoff miscommunication. We aimed to evaluate the effectiveness of a structured interfacility handoff program in improving communication between referring and receiving clinicians and across the PICU admitting team. Design: Prospective intervention study using a mixed-methods approach (surveys, chart review, and semistructured interviews) before and after I-PASS-to-PICU implementation. Setting: Academic tertiary referral PICU. Patients: Children of 0–18 years old referred by external hospitals for urgent PICU admission. Intervention: Structured handoff program (I-PASS-to-PICU) based on elements of high-quality handoffs adapted for interfacility PICU transfers Measurements and Main Results: A total of 220 patients were included (110 preintervention and 110 postintervention). Multivariable regression analysis adjusting for potential confounders showed no association between use of I-PASS-to-PICU and receiving PICU physician reports of key handoff information omissions (OR, 0.92; 95% CI, 0.30–2.82; p = 0.88 ). However, there was a decrease in the proportion of admitting PICU staff per patient who did not receive key handoff information (mean, 16% [ sd , 21%]; preintervention, 10% [ sd , 16%] vs. postintervention; p = 0.032). There were also more patients for whom receiving PICU physicians reported being well-prepared before admission (95% preintervention vs. 100% postintervention; p = 0.026). Postintervention, 94 patients (86%) had a completed I-PASS-to-PICU note; however, only a median of 50% (IQR, 34–66%) of admitting PICU staff per patient viewed the note before admission. Stakeholders identified barriers and facilitators of I-PASS-to-PICU implementation. Conclusions: A structured interfacility handoff program improved communication of key information across PICU admitting team members and increased reported preparedness of receiving PICU physicians. Identified barriers and facilitators of implementation can be used to inform, redesign, and adapt this program for uptake and use in other PICUs.

Learning about critically ill children's outcomes after transfer to the pediatric intensive care unit (PICU) can help emergency department (ED) physicians improve future performance. However, there are no standard processes in place to systematically provide this information; thus, most ED physicians obtain inconsistent feedback. We aimed to determine the effect of delivering patient outcome feedback through the electronic health record (EHR) on the frequency of ED physicians' re-access of patients' EHRs after PICU transfer. We performed a retrospective cohort study at an academic tertiary referral hospital before and after implementing an EHR-based system delivering individual patient outcome feedback to ED physicians who admitted children from the ED to the same institution's PICU (2019–2021). A total of 180 patients transferred to the PICU by 30 unique ED physicians were included (100 pre- and 80 postintervention). After implementing the feedback system, the proportion of patients for whom ED physicians re-accessed the EHR increased from 26% preintervention to 80% postintervention (p < 0.001). Propensity score-adjusted multivariable modeling accounting for patient, clinician, encounter, and diagnostic covariates showed a significant association between receipt of patient outcome feedback reports and ED physicians' EHR re-access, with the rate of EHR re-access 2.58 times higher in the postintervention cohort (p < 0.001). The estimated marginal means, which provide an adjusted average outcome for each cohort, showed a significantly higher number of EHR re-access episodes per patient postintervention (0.44 [95% CI: 0.3, 0.66] pre- vs. 1.14 [95% CI: 0.86, 1.51] postintervention, p < 0.001). Receipt of consistent patient outcome feedback increased ED physicians' re-access of patients' EHRs after PICU transfer, potentially allowing them to obtain information that can be used to improve future clinical performance. Further study is needed to determine the effectiveness of feedback systems in improving clinician practice and outcomes of critically ill children.

Since the National Academies of Sciences, Engineering, and Medicine (NASEM) report Improving Diagnosis in Health Care , various research efforts have accelerated progress to understand and improve diagnostic safety. In this opinion piece, we summarize two decades of progress in methods for identifying and learning from diagnostic errors and provide recommendations for future research. Multiple methods have been used to quantify diagnostic errors in various clinical settings, thereby facilitating a deeper understanding of the nature and magnitude of the problem and enabling studies of contributing factors. However, the use of standardized definitions of a diagnostic error and/or diagnostic safety event, a shared mental model for measurement, and more universal application of tools to measure these events across the research enterprise are still needed. We highlight progress in selected research methods and applications, such as co-development with patients, inclusion of multidisciplinary perspectives (such as those from informatics, human factors, and social and cognitive sciences), and the use of sociotechnical approaches. Specific areas where research should be prioritized include the application of cognitive science to the real-world study of diagnostic errors, understanding the costs associated with diagnostic safety, developing and implementing interventions related to patient engagement, evaluating and integrating artificial intelligence, and implementing system-related interventions to improve diagnosis. To promote broad-scale improvement in diagnostic safety over the next decade, we provide several actionable steps and recommendations for various audiences, including researchers, research funders, safety professionals, and policymakers, involved in research and implementation activities for reducing preventable diagnostic harm.

Objectives: Children receiving care in pediatric intensive care units (PICUs) are vulnerable to decompensation and diagnostic error due to the complex and dynamic nature of pediatric critical illness. In the PICU, the few clinical decision support (CDS) tools that have been implemented to support diagnostic accuracy (i.e., the ability to detect the presence of a condition) have not led to an increase in clinician adoption of desired practices nor demonstrated clear clinical benefit. Methods: The DISCOVER Learning Lab analyzed workflow and failure modes in diagnosing and managing clinical decompensation in the PICU, using systems safety engineering and human factors to examine intersections with established CDS. Methods employed included qualitative interviews, workflow mapping, immersive virtual reality (VR) systems testing via a digital twin environment, and a failure modes effect analysis. Results: Workflow mapping and qualitative interviews revealed barriers to communication, workflow inefficiencies, and limited access to up-to-date clinical information during critical events in the PICU. The immersive VR systems testing elucidated how PICU staff members currently interact with CDS tools and how various tools could better integrate into or influence clinical workflows. Critical failure modes were identified with corresponding opportunity areas for intervention. Conclusions: The application of a systems safety engineering and human factors approach to problem analysis, partnered with novel use of immersive VR and digital twin technology, led to valuable insights into common failure modes and potential opportunity areas to improve diagnostic accuracy and care delivery in a quaternary referral center PICU.