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: While medical complexity is associated with pediatric readmission risk, less is known about how increases in medical complexity during hospitalization affect readmission risk. METHODS: We conducted a five-year retrospective, case-control study of pediatric hospitalizations at a tertiary care children’s hospital. Cases with a 30-day unplanned readmission were matched to controls based on admission seasonality and distance from the hospital. Complexity variables included the number of medications prescribed at discharge, medical technology, and the need for home healthcare services. Change in medical complexity variables included new complex chronic conditions and new medical technology. We estimated odds of 30-day unplanned readmission using adjusted conditional logistic regression. RESULTS: Of 41,422 eligible index hospitalizations, we included 595 case and 595 control hospitalizations. Complexity: Polypharmacy after discharge was common. In adjusted analyses, being discharged with ≥2 medications was associated with higher odds of readmission compared with being discharged without medication; children with ≥5 discharge medications had a greater than four-fold higher odds of readmission. Children assisted by technology had higher odds of readmission compared with children without technology assistance. Change in complexity: New diagnosis of a complex chronic condition (Adjusted Odds Ratio (AOR) = 1.75; 1.11-2.75) and new technology (AOR = 1.84; 1.09-3.10) were associated with higher risk of readmission when adjusting for patient characteristics. However, these associations were not statistically significant when adjusting for length of stay. CONCLUSION: Polypharmacy and use of technology at discharge pose a substantial readmission risk for children. However, added technology and new complex chronic conditions do not increase risk when accounting for length of stay

Costs of completing the recommended immunization schedule have increased over the last decade. Access to prophylactic vaccines may become limited due to financing obstacles within current delivery systems. Vaccine prices reflect research and development expenses incurred by vaccine manufacturers, including costs associated with evaluating candidate vaccines in human subjects. If the number of subjects in clinical trials is increasing over time and associated with vaccine price, this may help explain increases in prices of vaccine series. We examined whether: (A) the initial public- and private-sector prices for recommended prophylactic vaccine series licensed and recommended in the US increased from 2000–2011, (B) the number of human subjects per licensed vaccine increased during the time period, and (C) the number of human subjects was associated with the initial public–and private–sector prices of the vaccine series. In regression analyses of 13 vaccines, approval year was not significantly associated with the number of human subjects, initial public-sector prices, or initial private-sector prices. While the number of phase II subjects was not significantly associated with prices, the numbers of phase III and combined late phase (phases II + III) subjects were significantly associated with initial public- and private-sector series prices (p < 0.05). The association between number of subjects and initial prices demonstrated diminishing marginal increases in price with increasing numbers of subjects. These findings may help guide the number of subjects required by the FDA in clinical trials, in order to reduce expenses for manufacturers and thereby help mitigate increases in initial vaccine series prices.

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