Katherine E. Bates

A tool to measure shared clinical understanding following handoffs to help evaluate handoff quality.

BACKGROUND Information exchanged during handoffs contributes importantly to a teams shared mental model. There is no established instrument to measure shared clinical understanding as a marker of handoff quality. OBJECTIVE To study the reliability, validity, and feasibility of the pediatric cardiology Patient Knowledge Assessment Tool (PKAT), a novel instrument designed to measure shared clinical understanding for pediatric cardiac intensive care unit patients. DESIGN To estimate reliability, 10 providers watched 9 videotaped simulated handoffs and then completed a PKAT for each scenario. To estimate construct validity, we studied 90 handoffs in situ by having 4 providers caring for an individual patient each complete a PKAT following handoff. Construct validity was assessed by testing the effects of provider preparation and patient complexity on agreement levels. SETTING A 24-bed pediatric cardiac intensive care unit in a freestanding childrens hospital. RESULTS Video simulation results demonstrated score reliability. Average inter-rater agreement by item ranged from 0.71 to 1.00. During in situ testing, agreement by item ranged from 0.41 to 0.87 (median 0.77). Construct validity for some items was supported by lower agreement rates for patients with increased length of stay and increased complexity. DISCUSSION Results suggest that the PKAT has high inter-rater reliability and can detect differences in understanding between handoff senders and receivers for routine and complex patients. Additionally, the PKAT is feasible for use in a real-time clinical environment. The PKAT or similar instruments could be used to study effects of handoff improvement efforts in inpatient settings.

Trends in infective endocarditis hospitalisations at United States children's hospitals from 2003 to 2014: impact of the 2007 American Heart Association antibiotic prophylaxis guidelines.

OBJECTIVE National organisations in several countries have recently released more restrictive guidelines for infective endocarditis prophylaxis, including the American Heart Association 2007 guidelines. Initial studies demonstrated no change in infective endocarditis rates over time; however, a recent United Kingdom study suggested an increase; current paediatric trends are unknown. METHODS Children (5 years of age. Interrupted time series analysis was used to evaluate rates over time indexed to total hospitalisations. RESULTS A total of 841 cases were identified. The median age was 13 years (interquartile range 9-15 years). In the pre-guideline period, there was a slight increase in the rate of infective endocarditis by 0.13 cases/10,000 hospitalisations per semi-annual period. In the post-guideline period, the rate of infective endocarditis increased by 0.12 cases/10,000 hospitalisations per semi-annual period. There was no significant difference in the rate of change in the pre- versus post-guidelines period (p=0.895). Secondary analyses in children >5 years of age with CHD and in children hospitalised with any type of infective endocarditis at any age revealed similar results. CONCLUSIONS We found no significant change in infective endocarditis hospitalisation rates associated with revised prophylaxis guidelines over 11 years across 29 United States childrens hospitals.

Development and Preliminary Testing of the Coordination Process Error Reporting Tool (CPERT), a Prospective Clinical Surveillance Mechanism for Teamwork Errors in the Pediatric Cardiac ICU

BACKGROUND Patient safety reporting systems (PSRSs) may not detect teamwork or coordination process errors that affect all dimensions of quality defined by the Institute of Medicine. This study aimed to develop and observe the performance of a novel tool, the Coordination Process Error Reporting Tool (CPERT), as a prospective clinical surveillance mechanism for teamwork errors in the pediatric cardiac ICU. METHODS Providers and parents used the qualitative nominal group technique to identify coordination process error examples. Using categories developed from these discussions, the CPERT was designed and observed to assess agreement among providers and with the PSRS. For each patient at the end of each observed shift, the nurse, frontline clinician, and attending physician were invited to complete the CPERT online. Responses among providers were compared to assess interobserver agreement. Patients with errors identified by the CPERT were matched 1:1 with patients without CPERT errors within the same shift. The PSRS and medical record were reviewed to judge whether a coordination process error occurred and whether patients with CPERT errors differed from controls. RESULTS Eight categories of errors were identified and incorporated into the CPERT. During 10 shifts (218 patients), the CPERT completion rate was 74%. Fifty-one patient shifts had errors identified by the CPERT (23%); these patients did not differ significantly from those without CPERT- reported errors. Only 5 CPERT-reported errors (10%) were identified by two or more providers. Of the 51 CPERT- reported errors, 43 (84%) were not documented in the PSRS. CONCLUSION The CPERT detects coordination process errors not identified through PSRS, making it or similar tools potentially useful for improvement efforts.

Risk Factors for Unanticipated Readmissions During the Interstage: A Report From the National Pediatric Cardiology Quality Improvement Collaborative

This study describes unanticipated interstage readmissions in patients with hypoplastic left heart syndrome, identifies independent risk factors for unanticipated interstage readmissions, and evaluates variation in unanticipated readmission rates among collaborative centers. Retrospective data of patients enrolled in the National Pediatric Cardiology Quality Improvement Collaborative registry from July 2008 to July 2013 were analyzed. Risk factors present at the beginning of the interstage were captured. Competing risks time to event analyses determined the association between these factors and unanticipated interstage readmission. Readmission center variation was examined using funnel plots. Unanticipated interstage readmissions occurred in 66% of 815 patients at 50 centers. The median readmission length of stay was 2 days (interquartile range: 0-6) and median time to first readmission was 29 days (interquartile range: 9-63). Most readmissions were prompted by minor changes in clinical status (64%), whereas only 6% were major adverse event readmissions. Independent readmission risk factors included genetic syndrome (HR = 1.40, 95% CI: 1.05-1.88), center volume (small vs large HR = 1.32, CI: 1.04-1.66, medium vs large HR = 1.35, CI: 1.09-1.68), preoperative ventricular dysfunction (HR = 2.02, CI: 1.31-3.10), tricuspid regurgitation (HR = 1.36, CI: 1.08-1.72), duration of circulatory arrest (HR = 0.99, CI: 0.989-0.998), and undergoing Hybrid procedure relative to Norwood/right ventricle to pulmonary artery conduit (HR = 1.40, CI: 1.02-1.93). There was significant center variation in the number of readmissions and duration of readmissions. Unanticipated readmissions are common during the interstage period with notable center variation. However, these readmissions are short and are rarely in response to major adverse events.