Literature DB >> 34320414

Validation of Neurologic Impairment Diagnosis Codes as Signifying Documented Functional Impairment in Hospitalized Children.

Katherine E Nelson1, Vishakha Chakravarti2, Catherine Diskin3, Joanna Thomson4, Eyal Cohen5, Sanjay Mahant6, Chris Feudtner7, Kimberley Widger8, Eleanor Pullenayegum9, Jay G Berry10, James A Feinstein11.   

Abstract

OBJECTIVE: To assess the performance of previously published high-intensity neurologic impairment (NI) diagnosis codes in identification of hospitalized children with clinical NI.
METHODS: Retrospective study of 500 randomly selected discharges in 2019 from a freestanding children's hospital. All charts were reviewed for 1) NI discharge diagnosis codes and 2) documentation of clinical NI (a neurologic diagnosis and indication of functional impairment like medical technology). Test statistics of clinical NI were calculated for discharges with and without an NI diagnosis code. A sensitivity analysis varied the threshold for "substantial functional impairment." Secondary analyses evaluated misclassified discharges and a more stringent definition for NI.
RESULTS: Diagnosis codes identified clinically documented NI with 88.1% (95% confidence interval [CI]: 84.7, 91) specificity, and 79.4% (95% CI: 67.3, 88.5) sensitivity; negative predictive value (NPV) was 96.7% (95% CI: 94.8, 98.0), and positive predictive value (PPV) was 49% (95% CI: 42, 56.1). Including children with milder functional impairment (lower threshold) resulted in NPV of 95.7% and PPV of 77.5%. Restricting to children with more severe functional impairment (higher threshold) resulted in NPV of 98.2% and PPV of 44.1%. Misclassification was primarily due to inclusion of children without functional impairments. A more stringent NI definition including diagnosis codes for NI and feeding tubes had a specificity of 98.4% (95% CI: 96.7-99.3) and sensitivity of 28.6% (19.4-41.3).
CONCLUSIONS: All scenarios evaluated demonstrated high NPV and low-to-moderate PPV of the diagnostic code list. To maximize clinical utility, NI diagnosis codes should be used with strategies to mitigate the risk of misclassification.
Copyright © 2021 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  clinical validation; health administrative data; neurologic impairment

Mesh:

Year:  2021        PMID: 34320414      PMCID: PMC8786975          DOI: 10.1016/j.acap.2021.07.014

Source DB:  PubMed          Journal:  Acad Pediatr        ISSN: 1876-2859            Impact factor:   2.993


  36 in total

1.  Identifying priorities in methodological research using ICD-9-CM and ICD-10 administrative data: report from an international consortium.

Authors:  Carolyn De Coster; Hude Quan; Alan Finlayson; Min Gao; Patricia Halfon; Karin H Humphries; Helen Johansen; Lisa M Lix; Jean-Christophe Luthi; Jin Ma; Patrick S Romano; Leslie Roos; Vijaya Sundararajan; Jack V Tu; Greg Webster; William A Ghali
Journal:  BMC Health Serv Res       Date:  2006-06-15       Impact factor: 2.655

2.  Estimating Neurologic Prognosis in Children: High Stakes, Poor Data.

Authors:  Monica E Lemmon; Peter A Ubel; Annie Janvier
Journal:  JAMA Neurol       Date:  2019-08-01       Impact factor: 18.302

3.  Costs and complications of hospitalizations for children with cerebral palsy.

Authors:  N A Murphy; C Hoff; T Jorgensen; C Norlin; P C Young
Journal:  Pediatr Rehabil       Date:  2006 Jan-Mar

4.  STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 2-More complex methods of adjustment and advanced topics.

Authors:  Pamela A Shaw; Paul Gustafson; Raymond J Carroll; Veronika Deffner; Kevin W Dodd; Ruth H Keogh; Victor Kipnis; Janet A Tooze; Michael P Wallace; Helmut Küchenhoff; Laurence S Freedman
Journal:  Stat Med       Date:  2020-04-03       Impact factor: 2.373

Review 5.  STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 1-Basic theory and simple methods of adjustment.

Authors:  Ruth H Keogh; Pamela A Shaw; Paul Gustafson; Raymond J Carroll; Veronika Deffner; Kevin W Dodd; Helmut Küchenhoff; Janet A Tooze; Michael P Wallace; Victor Kipnis; Laurence S Freedman
Journal:  Stat Med       Date:  2020-04-03       Impact factor: 2.373

6.  Pediatric Critical Care Resource Use by Children with Medical Complexity.

Authors:  Titus Chan; Jonathan Rodean; Troy Richardson; Reid W D Farris; Susan L Bratton; Jane L Di Gennaro; Tamara D Simon
Journal:  J Pediatr       Date:  2016-07-21       Impact factor: 4.406

7.  Inpatient growth and resource use in 28 children's hospitals: a longitudinal, multi-institutional study.

Authors:  Jay G Berry; Matt Hall; David E Hall; Dennis Z Kuo; Eyal Cohen; Rishi Agrawal; Kenneth D Mandl; Holly Clifton; John Neff
Journal:  JAMA Pediatr       Date:  2013-02       Impact factor: 16.193

8.  Pneumonia Prevention Strategies for Children With Neurologic Impairment.

Authors:  Jody L Lin; Keith Van Haren; Joseph Rigdon; Olga Saynina; Hannah Song; MyMy C Buu; Yogita Thakur; Nivedita Srinivas; Steven M Asch; Lee M Sanders
Journal:  Pediatrics       Date:  2019-09-19       Impact factor: 9.703

9.  Parents Are the Experts: A Qualitative Study of the Experiences of Parents of Children With Severe Neurological Impairment During Decision-Making.

Authors:  Jori F Bogetz; Amy Trowbridge; Hannah Lewis; Kelly J Shipman; Danielle Jonas; Julie Hauer; Abby R Rosenberg
Journal:  J Pain Symptom Manage       Date:  2021-06-17       Impact factor: 3.612

10.  Estimating the current and future prevalence of life-limiting conditions in children in England.

Authors:  Lorna K Fraser; Deborah Gibson-Smith; Stuart Jarvis; Paul Norman; Roger C Parslow
Journal:  Palliat Med       Date:  2020-12-15       Impact factor: 4.762

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