Accuracy of the Exeter Hospitalizations-Office Visits-Medical Conditions-Extra Care-Social Concerns Index for Identifying Children With Complex Chronic Medical Conditions in the Clinical Setting.

OBJECTIVE: Our objective was to determine the accuracy of a point-of-care instrument, the Hospitalizations-Office Visits-Medical Conditions-Extra Care-Social Concerns (HOMES) instrument, in identifying patients with complex chronic conditions (CCCs) compared to an algorithm used to identify patients with CCCs within large administrative data sets. METHODS: We compared the HOMES to Feudtner's CCCs classification system. Using administrative algorithms, we categorized primary care patients at a children's hospital into 3 categories: no chronic conditions, non-complex chronic conditions, and CCCs. We randomly selected 100 patients from each category. HOMES scoring was completed for each patient. We performed an optimal cut-point analysis on 80% of the sample to determine which total HOMES score best identified children with ≥1 CCC and ≥2 CCCs. Using the optimal cut points and the remaining 20% of the study population, we determined the odds and area under the curve (AUC) of having ≥1 CCC and ≥2 CCCs. RESULTS: The median (interquartile range [IQR]) age was 4 (IQR: 0, 8). Using optimal cut points of ≥7 for ≥1 CCC and ≥11 for ≥2 CCCs, the odds of having ≥1 CCC was 19 times higher than lower scores (odds ratio [OR] 19.1 [95% confidence interval [CI]: 9.75, 37.5]) and of having ≥2 CCCs was 32 times higher (OR 32.3 [95% CI: 12.9, 50.6]). The AUCs were 0.76 for ≥1 CCC (sensitivity 0.82, specificity 0.80) and 0.74 for ≥2 CCCs (sensitivity 0.92, specificity 0.74). CONCLUSIONS: The HOMES accurately identified patients with CCCs.

Effectiveness of Screening for Household Gun Ownership in an Urban Primary Care Clinic.

Gun-related suicide and homicide are leading causes of death among children. Little is known about the effectiveness of screening for gun ownership in primary care. We examined positive gun ownership screens over a 2.5-year period in a pediatric primary care clinic. The main outcome was a positive screen for gun ownership. The main predictors included insurance type, neighborhood median income, number of clinic visits, and other social needs. Of 19 163 patients, 474 (2.5%) screened positive for gun ownership. Patients with private insurance and from higher income neighborhoods had 2 to 3 times higher odds of a positive screen. Patients with more visits and with food insecurity had approximately 2 to 4 times the odds of a positive screen for household gun ownership. In conclusion, the rate of positive gun ownership screens was very low and far below known gun ownership rates. Improved screening methods could better identify opportunities for gun safety advocacy.