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A big data approach to evaluate receipt of optimal care in childhood cerebral palsy.

Alexis MitelpunktMegan A StodolaJilda Vargus-AdamsBrad G KurowskiKelly GreveSurbhi BhatnagarBruce AronowJanet ZahnerAmy F Bailes
Published in: Disability and rehabilitation (2023)
ROCSs demonstrate variation in real-world care delivered over time and differentiate between components of care. ROCSs reflect overall function and quality of life. The ROCS methods developed are novel, robust, and scalable and will be tested in a larger sample.IMPLICATIONS FOR REHABILITATIONOptimal practice, with an emphasis on integrated multidisciplinary care, can be defined and quantified utilizing evidence-based recommendations.Receipt of optimal care for childhood cerebral palsy can be scored using existing electronic health record data.Big Data approaches can contribute to the understanding of current care and inform approaches for improved care.
Keyphrases
  • big data
  • healthcare
  • palliative care
  • quality improvement
  • cerebral palsy
  • machine learning
  • artificial intelligence
  • pain management
  • affordable care act
  • primary care
  • clinical decision support