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 patient...
| Publicado en: | Academic Pediatrics Vol. 23; no. 8; pp. 1553 - 1561 |
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| Autores principales: | , , , , , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Elsevier B.V.
Nov/Dec2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=175060074&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 175060074 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 18762859 8NBK jtl: Academic Pediatrics issn: 18762859 maglogo: N pubinfo: dt: Nov/Dec2023 vid: 23 iid: 8 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 175060074 175060074 175060074 10.1016/j.acap.2023.07.010 175060074 ppf: 1553 ppct: 8 formats: fmt: @attributes: type: P tig: atl: 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. aug: au: Larson, Ingrid A. Zaniletti, Isabella Gupta, Rupal Wright, S. Margaret Winterer, Courtney Toburen, Cristy Williams, Kristi Goodwin, Emily J. Northup, Ryan M. Roderick, Edie Hall, Matt Colvin, Jeffrey D. affil: Administration, Children's Mercy Hospital Kansas, Overland Park sug: subj: Critical Illness In Infancy and Childhood Chronic Disease In Infancy and Childhood Point-of-Care Testing Algorithms Child, Medically Fragile Primary Health Care Pediatric Care Human Comparative Studies Random Sample Odds Ratio Confidence Intervals Descriptive Statistics Sensitivity and Specificity Child Health Services Health Services Needs and Demand Funding Source Clinical Assessment Tools Child Child: 6-12 years ab: 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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