When a patient is hospitalised the ultimate goal is to get them back to health and fit to continue their life. When the patient winds up back in the hospital less than 30 days after being discharged, family members, clinicians and hospital administrators alike are apt to ask the same question: What went wrong?

Big data analytics allows clinicians and administrators to distinguish between readmissions that are necessary and those that could have been prevented. Based on this same analysis clinicians can develop an appropriate readmission prevention strategy for each individual patient.

Inside you'll discover how advanced analytics can help healthcare professionals:

  • Prioritise which conditions should be targeted for readmissions prevention
  • Determine which patients would benefit most from readmissions prevention
  • Move from a reactive to proactive readmissions prevention
  • Provide an individualised readmissions prevention services
  • And much much more…
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