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:
- data mining activity to expose relationships within your data associated with outcomes of interest
- the degree of predictivity within your data.
Current research and pilot programs include:
- HCAHPS scores improvement through tactical process adjustment from learned outcome factors
- Drug and alcohol recovery program optimal candidate selection and Left Without Completing Treatment (LWCT) prediction
- Improvements in hospital re-admission risk modeling using LACE data
- Anomaly detection in multidimensional data
- 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.