Reducing Hospital Readmissions

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The costs of readmitting a recent patient into a hospital are significant. For example one study found 20% of Medicare patients discharged from a hospital were readmitted within 30 days with a potentially preventable cost of 15 to 20 billion dollars per year [1,2]. Many variables may prove helpful in predicting the chances of readmission for a given patient including things like the patient’s health condition [3], insurance type [4], and demographic information [5].  Using our Mayetrix machine learning platform, we can help you predict and prevent hospital readmissions leading to more efficient use of scarce hospital resources while improving the overall quality of care that patients receive.

Interested in using AI to reduce hospital readmissions? Contact us and lets dig in together.

References

  1. Rehospitalizations among patients in the Medicare fee-for-service program. - Jencks SF, Williams MV, Coleman, N Engl J Med. 2009;360(14):1418.

  2. Medicare & Medicaid Statistical Supplement. Baltimore: Centers for Medicare & Medicaid Services, 2007. Available at: www.cms.hhs.gov/MedicareMedicaidStatSupp/downloads/2007Table5.1b.pdf

  3. Agency for Healthcare Research and Quality (AHRQ) Study on readmissions from 2011

  4. Risk factors for 30-day hospital readmission in patients ≥65 years of age, Silverstein et al, Proc (Bayl Univ Med Cent). 2008 Oct; 21(4): 363–372.

  5. Patient Factors Predictive of Hospital Readmissions Within 30 Days - Kroch, Eugene; Duan, Michael; Martin, John; Bankowitz, Richard A., Journal For Healthcare Quality: March/April 2016 - Volume 38 - Issue 2 - p 106–115

  6. Photo by icathing / CC BY