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Establishing risk-adjusted quality indicators in surgery using administrative data-an example from neurosurgery.

Stephanie SchipmannJulian VargheseTobias BrixMichael SchwakeDennis KeurhorstSebastian LohmannEric Suero MolinaUwe Max MauerMartin DugasNils WarnekeWalter Stummer
Published in: Acta neurochirurgica (2019)
All previously discussed quality indicators are easily derived from administrative data. Administrative data alone might not be sufficient for adequate risk adjustment as they do not reflect the endogenous risk of the patient and are influenced by certain complications during inpatient stay. Appropriate concepts for risk adjustment should be compiled on the basis of prospectively designed registry studies.
Keyphrases
  • electronic health record
  • big data
  • minimally invasive
  • mental health
  • palliative care
  • case report
  • risk factors
  • machine learning
  • data analysis
  • deep learning