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Titre : | Using Billing Codes to Create a Pediatric Functional Status e-Score for Children Receiving Inpatient Rehabilitation (2023) |
Auteurs : | Jennifer P. Lundine ; Jared D. Huling ; P. David Adelson ; Randall S. Burd ; Molly Fuentes ; Juliet Haarbauer-Krupa ; Kaitlin Hagen ; Cynthia Iske ; Christine Koterba ; Brad G. Kurowski ; Stephanie Petrucci ; Sean C. Rose ; Cristina L. Sadowsky ; Jennifer Westendorf ; Annie Truelove ; Julie C. Leonard |
Type de document : | Article |
Dans : | Archives of Physical Medicine and Rehabilitation (Vol. 104, n° 11, 2023) |
Article en page(s) : | p. 1882-1891 |
Note générale : | https://doi.org/10.1016/j.apmr.2023.03.025 |
Langues: | Anglais |
Descripteurs : |
HE Vinci Enfant (6-12 ans) ; Méthode Delphi ; Pédiatrie ; Réadaptation ; Recherche comparative sur l'efficacité |
Résumé : | Objective Provide proof-of-concept for development of a Pediatric Functional Status eScore (PFSeS). Demonstrate that expert clinicians rank billing codes as relevant to patient functional status and identify the domains that codes inform in a way that reliably matches analytical modeling. Design Retrospective chart review, modified Delphi, and nominal group techniques. Setting Large, urban, quaternary care children's hospital in the Midwestern United States. Participants Data from 1955 unique patients and 2029 hospital admissions (2000-2020); 12 expert consultants representing the continuum of rehabilitation care reviewed 2893 codes (procedural, diagnostic, pharmaceutical, durable medical equipment). Main Outcome Measures Consensus voting to determine whether codes were associated with functional status at discharge and, if so, what domains they informed (self-care, mobility, cognition/ communication). Results The top 250 and 500 codes identified by statistical modeling were mostly composed of codes selected by the consultant panel (78%-80% of the top 250 and 71%-78% of the top 500). The results provide evidence that clinical experts? selection of functionally meaningful codes corresponds with codes selected by statistical modeling as most strongly associated with WeeFIM domain scores. The top 5 codes most strongly related to functional independence ratings from a domain-specific assessment indicate clinically sensible relationships, further supporting the use of billing data in modeling to create a PFSeS. Conclusions Development of a PFSeS that is predicated on billing data would improve researchers? ability to assess the functional status of children who receive inpatient rehabilitation care for a neurologic injury or illness. An expert clinician panel, representing the spectrum of medical and rehabilitative care, indicated that proposed statistical modeling identifies relevant codes mapped to 3 important domains: self-care, mobility, and cognition/communication. |
Disponible en ligne : | Oui |
En ligne : | https://login.ezproxy.vinci.be/login?url=https://www.sciencedirect.com/science/article/pii/S0003999323002241 |