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Figure.  Frequencies of High-Intensity Neurological Impairment (HI-NI) Diagnostic Categories
Frequencies of High-Intensity Neurological Impairment (HI-NI) Diagnostic Categories

The most common diagnosis within each HI-NI diagnostic category and the relative percentage of patients within that category are as follows. Epilepsy (29.7%), including unspecified, not intractable, and without status epilepticus; static (31.6%), including cerebral palsy and unspecified; anatomic (9.4%), including hydrocephalus and unspecified; peripheral (10.2%), including quadriplegia and unspecified; genetic (45.6%), including Down syndrome and unspecified; metabolic (19.9%), including lipoprotein deficiency; progressive or movement (22.8%), including cerebral infarction; and stroke or hemorrhage (15.4%), including extrapyramidal and movement disorder and unspecified.

Table.  Health Care Spending and Utilization of Services for Children With Neurological Impairment
Health Care Spending and Utilization of Services for Children With Neurological Impairment
1.
Berry  JG, Poduri  A, Bonkowsky  JL,  et al.  Trends in resource utilization by children with neurological impairment in the United States inpatient health care system: a repeat cross-sectional study.  PLoS Med. 2012;9(1):e1001158. doi:10.1371/journal.pmed.1001158PubMedGoogle ScholarCrossref
2.
Slonim  AD, LaFleur  BJ, Ahmed  W, Joseph  JG.  Hospital-reported medical errors in children.  Pediatrics. 2003;111(3):617-621. doi:10.1542/peds.111.3.617PubMedGoogle ScholarCrossref
3.
Feudtner  C, Christakis  DA, Connell  FA.  Pediatric deaths attributable to complex chronic conditions: a population-based study of Washington State, 1980-1997.  Pediatrics. 2000;106(1 Pt 2):205-209.PubMedGoogle Scholar
4.
Simon  TD, Cawthon  ML, Stanford  S,  et al; Center of Excellence on Quality of Care Measures for Children with Complex Needs (COE4CCN) Medical Complexity Working Group.  Pediatric medical complexity algorithm: a new method to stratify children by medical complexity.  Pediatrics. 2014;133(6):e1647-e1654. doi:10.1542/peds.2013-3875PubMedGoogle ScholarCrossref
5.
Feinstein  JA, Russell  S, DeWitt  PE, Feudtner  C, Dai  D, Bennett  TD.  R package for pediatric complex chronic condition classification.  JAMA Pediatr. 2018;172(6):596-598. doi:10.1001/jamapediatrics.2018.0256PubMedGoogle ScholarCrossref
6.
Raebel  MA, Schmittdiel  J, Karter  AJ, Konieczny  JL, Steiner  JF.  Standardizing terminology and definitions of medication adherence and persistence in research employing electronic databases.  Med Care. 2013;51(8)(suppl 3):S11-S21. doi:10.1097/MLR.0b013e31829b1d2aPubMedGoogle ScholarCrossref
Research Letter
August 19, 2019

Identification of Children With High-Intensity Neurological Impairment

Author Affiliations
  • 1Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
  • 2Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio
  • 3Adult and Child Consortium for Health Outcomes Research & Delivery Science, Children’s Hospital Colorado, University of Colorado, Aurora
  • 4Children’s Hospital Association, Lenexa, Kansas
  • 5Division of General Pediatrics, Department of Pediatrics, Monroe Carell Jr Children’s Hospital at Vanderbilt, Vanderbilt University Medical Center, Nashville, Tennessee
  • 6Pediatric Housestaff, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
  • 7Complex Care Service, Division of General Pediatrics, Department of Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts
JAMA Pediatr. 2019;173(10):989-991. doi:10.1001/jamapediatrics.2019.2672

Children with neurological impairment frequently experience unmet health care needs, high-severity acute illnesses, coexisting condition exacerbations, adverse medical events, and disproportionately high health care utilization and spending.1,2 Our clinical experience within the clinical spectrum of neurological impairment has suggested that children with high-intensity neurological impairment have increased severity of health problems, needs, and care. Best practices for managing the acute and chronic health care needs of children with high-intensity neurological impairment are underdeveloped, partly owing to the limited methods of distinguishing these patients.

Existing pediatric classification systems for identifying complex neurological conditions (eg, cerebral palsy) in administrative data sets do not include disorders with neurological impairment originating from genetic, metabolic, and other organ systems (eg, trisomy 18, glutaric acidemia).3,4 Current classification systems that focus on neurological impairment include heterogeneous arrays of conditions with varied severity levels, which make studying patients with these conditions as 1 cohort challenging (eg, a child with mild intellectual disability and no functional limitations vs a nonverbal child with profound hypotonia and respiratory failure from Pompe disease).1

In the present study, we aimed to improve the method of distinguishing children with high-intensity neurological impairment by refining the classification of underlying neurological impairment diagnoses. We compared the high-intensity neurological impairment classification system’s performance with that of an existing classification scheme to assess whether children with high-intensity neurological impairment had higher multimorbidity, polypharmacy, and health care utilization and spending.

Methods

This cross-sectional study involved children 1 to 18 years of age who had neurological impairment and were continuously enrolled in Medicaid in 2016 according to records from 10 states in the IBM MarketScan Medicaid Database. The institutional review board of Cincinnati Children's Hospital Medical Center exempted this study from review as it used deidentified data. Informed consent was also waived for this reason.

We updated the most widely used neurological impairment coding system, International Classification of Diseases, Ninth Revision, Clinical Modification,1 to International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, diagnostic codes using General Equivalence Mappings, which was developed by the National Center for Health Statistics. Two of us (J.A.F. and J.E.T.) independently identified codes indicative of high-intensity neurological impairment, defined as a neurological diagnosis reasonably expected to last longer than 12 months and result in substantial functional impairments that require subspecialty medical care. Discrepancies were arbitrated by one of us (J.G.B.) and resolved by group consensus. High-intensity neurological impairment diagnoses and codes are available elsewhere (https://www.childrenshospitals.org/Research-and-Data/Pediatric-Data-and-Trends/2019/High-Intensity-Neurologic-Impairment-Codes).

We used χ2 and Wilcoxon rank sum tests to compare demographic details, clinical information, and use of health services between children with high-intensity neurological impairment and children with lower-intensity neurological impairment diagnoses.

Results

Of the 302 383 children with neurological impairment, 120 121 (39.7%) were classified as having high-intensity neurological impairment. The most frequent high-intensity neurological impairment categories included epilepsy (100 357 [83.6%]), static (56 479 [47.0%]), and anatomic (54 004 [45.0%]) (Figure). Compared with children with lower-intensity neurological impairment, children with high-intensity neurological impairment were 4.8 times more likely to have 6 or more body systems with chronic condition indicators (17.2% vs 3.6%; P < .001) and 9.9 times more likely to have 3 or more organ systems with complex chronic conditions5 (10.9% vs 1.1%; P < .001). Children with high-intensity neurological impairment had 2 times the exposure to 15 or more unique medications annually (6.8% vs 3.1%; P < .001) and 1.6 times the exposure to 5 or more chronic medications6 (13.5% vs 8.4%; P < .001).

Children with high-intensity neurological impairment had higher use of health care services across all domains, with 2.0 times more inpatient admissions (22 029 [18.3%] vs 17 011 [9.3%]; P < .001), 5.2 times more home health services (7989 [6.7%] vs 2446 [1.3%]; P < .001), and 1.7 times more therapy needs (57 279 [47.7%] vs 50 329 [27.6%]; P < .001) (Table). The 39.7% of children with high-intensity neurological impairment accounted for 61.3% ($2 946 765 384) of total health care costs and had 2.4 times the per-member-per-year spending ($24 532 vs $10 205) of those with lower-severity neurological impairment (Table).

Discussion

Distinguishing children with high-intensity neurological impairment from those with lower-intensity neurological impairment is important, as evidenced by their greater multimorbidity, polypharmacy, and health care use and spending. Although inherent limitations exist when using diagnostic codes, the results of this study suggest that high-intensity neurological impairment codes may allow health care systems and payers such as Medicaid to efficiently identify these medically complex children with unique, higher-intensity needs. We believe the use of high-intensity neurological impairment codes could enable the prioritization of comparative effectiveness, health outcomes, and pharmaceutical research in this vulnerable population.

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Article Information

Accepted for Publication: April 5, 2019.

Corresponding Author: Joanna E. Thomson, MD, MPH, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, 3333 Burnet Ave, ML 9016, Cincinnati, OH 45229 (joanna.thomson@cchmc.org).

Published Online: August 19, 2019. doi:10.1001/jamapediatrics.2019.2672

Author Contributions: Dr Hall had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Thomson, Feinstein, Hall, Berry.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Thomson, Feinstein, Hall, Berry.

Critical revision of the manuscript for important intellectual content: Feinstein, Gay, Butts, Berry.

Statistical analysis: Thomson, Feinstein, Hall.

Obtained funding: Thomson, Feinstein, Berry.

Administrative, technical, or material support: Gay, Butts, Berry.

Supervision: Gay, Berry.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was funded by award K08HS025138 from the Agency for Healthcare Research and Quality (AHRQ) (Dr Thomson) and award K23HD091295 from the Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD) of the National Institutes of Health (Dr Feinstein). Drs Berry and Hall were supported by grant HRSA-17-060-147599 (Children with Special Healthcare Needs Research Network) from the Maternal and Child Health Bureau.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the AHRQ, NICHD, National Institutes of Health, or the Maternal and Child Health Bureau.

References
1.
Berry  JG, Poduri  A, Bonkowsky  JL,  et al.  Trends in resource utilization by children with neurological impairment in the United States inpatient health care system: a repeat cross-sectional study.  PLoS Med. 2012;9(1):e1001158. doi:10.1371/journal.pmed.1001158PubMedGoogle ScholarCrossref
2.
Slonim  AD, LaFleur  BJ, Ahmed  W, Joseph  JG.  Hospital-reported medical errors in children.  Pediatrics. 2003;111(3):617-621. doi:10.1542/peds.111.3.617PubMedGoogle ScholarCrossref
3.
Feudtner  C, Christakis  DA, Connell  FA.  Pediatric deaths attributable to complex chronic conditions: a population-based study of Washington State, 1980-1997.  Pediatrics. 2000;106(1 Pt 2):205-209.PubMedGoogle Scholar
4.
Simon  TD, Cawthon  ML, Stanford  S,  et al; Center of Excellence on Quality of Care Measures for Children with Complex Needs (COE4CCN) Medical Complexity Working Group.  Pediatric medical complexity algorithm: a new method to stratify children by medical complexity.  Pediatrics. 2014;133(6):e1647-e1654. doi:10.1542/peds.2013-3875PubMedGoogle ScholarCrossref
5.
Feinstein  JA, Russell  S, DeWitt  PE, Feudtner  C, Dai  D, Bennett  TD.  R package for pediatric complex chronic condition classification.  JAMA Pediatr. 2018;172(6):596-598. doi:10.1001/jamapediatrics.2018.0256PubMedGoogle ScholarCrossref
6.
Raebel  MA, Schmittdiel  J, Karter  AJ, Konieczny  JL, Steiner  JF.  Standardizing terminology and definitions of medication adherence and persistence in research employing electronic databases.  Med Care. 2013;51(8)(suppl 3):S11-S21. doi:10.1097/MLR.0b013e31829b1d2aPubMedGoogle ScholarCrossref
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