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Measuring the Functional Abilities of Children Aged 3-6 Years Old with Observational Methods and Computer Tools
Published on: June 20, 2020
Development of the Children With Disabilities Algorithm
Alyna T Chien1, Karen A Kuhlthau2, Sara L Toomey3
1Division of General Pediatrics, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts; Departments of Pediatrics, and alyna.chien@childrens.harvard.edu.
Insights
A new algorithm (CWDA) uses ICD-9-CM codes to identify children with disabilities (CWD) in databases. This tool accurately identifies CWD, enabling better quality of care assessments.
Area of Science:
- Health Services Research
- Pediatrics
- Health Informatics
Background:
- Identifying children with disabilities (CWD) in healthcare claims databases is challenging.
- A reliable method is needed to assess the quality of care for CWD.
Purpose of the Study:
- To develop and validate an algorithm (CWDA) using ICD-9-CM codes to identify CWD in claims data.
- To enable the assessment of healthcare quality for CWD.
Main Methods:
- A cross-sectional study classified 14,567 ICD-9-CM codes based on their likelihood of indicating CWD.
- Pediatricians (general and subspecialists) classified codes.
- The developed algorithm (CWDA) was triangulated against parent and physician assessments.
Main Results:
- The CWDA includes 669 ICD-9-CM codes with a ≥75% likelihood of indicating CWD.
- CWDA demonstrated high sensitivity (0.98) compared to physician assessment and good sensitivity (0.75) compared to parent report.
- Specificity was 0.86 for physician assessment and 0.50 for parent report.
Conclusions:
- ICD-9-CM codes can be effectively classified to identify CWD.
- The CWDA shows strong agreement with parent and physician assessments of disability.
- The CWDA is a valuable new tool for evaluating the quality of care provided to CWD.
Background:
A major impediment to understanding quality of care for children with disabilities (CWD) is the lack of a method for identifying this group in claims databases. We developed the CWD algorithm (CWDA), which uses International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes to identify CWD.
Methods:
We conducted a cross-sectional study that (1) ensured each of the 14,567 codes within the 2012 ICD-9-CM codebook was independently classified by 3 to 9 pediatricians based on the code's likelihood of indicating CWD and (2) triangulated the resulting CWDA against parent and physician assessment of children's disability status by using survey and chart abstraction, respectively. Eight fellowship-trained general pediatricians and 42 subspecialists from across the United States participated in the code classification. Parents of 128 children from a large, free-standing children's hospital participated in the parent survey; charts of 336 children from the same hospital were included in the abstraction study.
Results:
CWDA contains 669 ICD-9-CM codes classified as having a ≥75% likelihood of indicating CWD. Examples include 318.2 Profound intellectual disabilities and 780.72 Functional quadriplegia. CWDA sensitivity was 0.75 (95% confidence interval 0.63-0.84) compared with parent report and 0.98 (0.95-0.99) compared with physician assessment; its specificity was 0.86 (0.72-0.95) and 0.50 (0.41-0.59), respectively.
Conclusions:
ICD-9-CM codes can be classified by their likelihood of indicating CWD. CWDA triangulates well with parent report and physician assessment of child disability status. CWDA is a new tool that can be used to assess care quality for CWD.
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