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FoundationDx is partnering with organizations interested in discovering new value in their data to rapidly drive outcomes.

Please contact us if interested in a research agreement which covers:

  1. data mining activity to expose relationships within your data associated with outcomes of interest
  2. the degree of predictivity within your data.

 Current research and pilot programs include:

  1. HCAHPS scores improvement through tactical process adjustment from learned outcome factors
  2. Drug and alcohol recovery program optimal candidate selection and Left Without Completing Treatment (LWCT) prediction
  3. Improvements in hospital re-admission risk modeling using LACE data 
  4. Anomaly detection in multidimensional data
  5. Long Term Care
    • Growing Patient Acuity*
      • What factors are associated with resident hospitalizations?  Consider resident demographics, comorbidities, nutritional metrics from lab data, care management personnel, medications, etc…
    • Track and monitor quality measures
      • What factors or which types of residents will provide less than desired assessments regarding their stay.
      • What quality measures are in place and what factors are associated with outcomes of interest?
      • What factors are associated with a patient’s happiness with the facility?  Staff, room, food, age, neighbors, friends, comorbidities, medical appointment timeliness, etc.
    • Reduce Readmissions
      • What factors are associated with patients who are readmitted to the hospital for any cause within 30 days of a hospital discharge verses those who are not.Clustering Long-Term-Care (LTC) populations to facilitate holistic care plan design
    • Lack of Clinical Staff*
      • RNs and LPNs tend to take on management roles and less skilled personnel have more patient contact.  How do we select the best candidates for these less skilled positions.**
    • Lack of geriatric nursing skills
      • Identify key markers of geriatric health and geriatric nutritional science and match these factors with residents identified to be at risk for poor or deteriorating health.  

References:

*http://lippincottsolutions.lww.com/blog.entry.html/2015/05/05/three_challengesof-R4Gi.html

** https://www.washingtonpost.com/health/2019/10/14/elderly-care-staff-accused-pitting-residents-against-each-other-dementia-fight-club/

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