Objective: We sought to 1) validate the accuracy of pre-encounter hospital designation as a novel way to identify unplanned pediatric readmissions, and 2) describe the most common diagnoses for unplanned readmissions among children. Methods:We examined all hospital discharges from two tertiary care children's hospitals excluding deaths, normal newborn discharges, transfers to other institutions, and discharges to hospice. We performed blinded medical record review on 641 randomly selected readmissions to validate the pre-encounter planned/unplanned hospital designation. We identified the most common discharge diagnoses associated with subsequent 30-day unplanned readmissions.Results: Among 166,994 discharges (Hospital A: n=55,383; Hospital B: n=111,611), the 30-day unplanned readmission rate was 10.3% (Hospital A) and 8.7% (Hospital B). The hospital designation of "unplanned" was correct in 98% (Hospital A) and 96% (Hospital B) of readmissions; the designation of "planned" was correct in 86% (Hospital A) and 85% (Hospital B) of readmissions. The most common discharge diagnoses for which unplanned 30-day readmissions occurred were oncologic conditions (up to 38%) and non-hypertensive congestive heart failure (about 25%), across both institutions.Conclusions: Unplanned readmission rates for pediatrics, using a validated, accurate, pre-encounter designation of "unplanned," are higher than previously estimated. For some pediatric conditions unplanned readmission rates are as high as readmission rates reported for adult conditions. Anticipating unplanned readmissions for high-frequency diagnostic groups may help focus efforts to reduce the burden of readmission for families and facilities.3

BACKGROUND: An estimated 10% of Americans experience a diagnostic error annually, yet little is known about pediatric diagnostic errors. Physician reporting is a promising method for identifying diagnostic errors. However, our pediatric hospital medicine (PHM) division had only 1 diagnostic-related safety report in the preceding 4 years. We aimed to improve attending physician reporting of suspected diagnostic errors from 0 to 2 per 100 PHM patient admissions within 6 months. METHODS: Our improvement team used the Model for Improvement, targeting the PHM service. To promote a safe reporting culture, we used the term diagnostic learning opportunity (DLO) rather than diagnostic error, defined as a “potential opportunity to make a better or more timely diagnosis.” We developed an electronic reporting form and encouraged its use through reminders, scheduled reflection time, and monthly progress reports. The outcome measure, the number of DLO reports per 100 patient admissions, was tracked on an annotated control chart to assess the effect of our interventions over time. We evaluated DLOs using a formal 2-reviewer process. RESULTS: Over the course of 13 weeks, there was an increase in the number of reports filed from 0 to 1.6 per 100 patient admissions, which met special cause variation, and was subsequently sustained. Most events (66%) were true diagnostic errors and were found to be multifactorial after formal review. CONCLUSIONS: We used quality improvement methodology, focusing on psychological safety, to increase physician reporting of DLOs. This growing data set has generated nuanced learnings that will guide future improvement work.

BACKGROUND: Diagnostic uncertainty may be a sign that a patient’s working diagnosis is incorrect, but literature on proactively identifying diagnostic uncertainty is lacking. Using quality improvement methodologies, we aimed to create a process for identifying patients with uncertain diagnoses (UDs) on a pediatric inpatient unit and communicating about them with the interdisciplinary health care team. METHODS: Plan-do-study-act cycles were focused on interdisciplinary communication, structured handoffs, and integration of diagnostic uncertainty into the electronic medical record. Our definition of UD was as follows: “you wouldn’t be surprised if the patient had a different diagnosis that required a change in management.” The primary measure, which was tracked on an annotated run chart, was percentage agreement between the charge nurse and primary clinician regarding which patients had a UD. Secondary measures included the percentage of patient days during which patients had UDs. Data were collected 3 times daily by text message polls. RESULTS: Over 13 months, the percentage agreement between the charge nurse and primary clinician about which patients had UDs increased from a baseline of 19% to a median of 84%. On average, patients had UDs during 11% of patient days. CONCLUSIONS: We created a novel and effective process to improve shared recognition of patients with diagnostic uncertainty among the interdisciplinary health care team, which is an important first step in improving care for these patients.

BackgroundA quality improvement initiative at our institution resulted in a new process for prospectively identifying pediatric hospital medicine (PHM) patients with uncertain diagnoses (UD). This study describes the clinical characteristics and healthcare utilization patterns of patients with UD.MethodsThis single center cross-sectional study included all PHM patients identified with UD during their admission. A structured chart review was used to abstract patient demographics, primary symptoms, discharge diagnoses, and healthcare utilization patterns, including consult service use, length of stay (LOS), escalation in care, and 30-day healthcare reutilization. Appropriate descriptive statistics were used for categorical and continuous variables.ResultsThis study includes 200 PHM patients identified with UD. Gastrointestinal symptoms were the primary finding in 45% of patients with UD. Consult service use was highly variable, with a range of 0–8 consult services for individual patients. The median LOS was 1.6 days and only 5% required a rapid response team evaluation. As for reutilization, 7% of patients were readmitted within 30 days.ConclusionsThis descriptive study highlights the heterogeneity of patients with uncertain diagnoses. Ongoing work is needed to further understand the impact of UD and to optimize the care of these patients.

OBJECTIVE: Diagnosis is a complex, iterative, and nonlinear process, often occurring over time. When presenting signs, symptoms, and diagnostic testing cannot be integrated into a diagnosis, clinicians are confronted with diagnostic uncertainty. Our aim was to study the self-reported cognitive, communication, and management behaviors of pediatric emergency medicine (PEM) and pediatric hospital medicine (PHM) physicians regarding diagnostic uncertainty. METHODS: A qualitative study was conducted through focus groups with PEM and PHM physicians in a large academic pediatric medical center. Four focus groups were conducted. Interviews were recorded, deidentified, and transcribed by a team member. Thematic analysis was used to review the transcripts, highlight ideas, and organize ideas into themes. RESULTS: Themes were categorized using the model of the diagnostic process from the National Academy of Sciences. “Red flags” and “gut feelings” were prominent during the information, integration, and interpretation phases. To combat diagnostic uncertainty, physicians employed strategies such as “the diagnostic pause” and having a set of “fresh eyes” to review the data. It was important to all clinicians to rule out any “cannot miss” diagnoses. Interphysician communication was direct; communication with patient and families about uncertainty was less direct because of physician concern of being thought of as untrustworthy. Contingency planning, “disposition over diagnosis” by ensuring patient safety, the “test of time,” and availability of resources were techniques used by physicians to manage diagnostic uncertainty. CONCLUSIONS: Physicians shared common mitigation strategies, which included consulting colleagues and targeting cannot miss diagnoses, but gaps remain regarding communicating diagnostic uncertainty to families.