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OneWorld provides quality affordable health care, and individuals are welcome with or without insurance, including Medicaid and Medicare. OneWorld operates 13 clinical locations in Omaha; including the clinics at the Historic Livestock Exchange Campus, OneWorld West, Northwest Omaha, Cass Family Medicine, OneWorld Bellevue, Crossroads to Health and Recovery at Community Alliance, two mobile dental clinics, four school-based health centers and the South Omaha Learning Community Centers. Established in 1970, OneWorld Community Health Centers, in partnership with the community, provides culturally respectful, quality health care with special attention to the underserved. OneWorld is a federally qualified health center (FQHC) and provides comprehensive primary health care, dental, mental health/ substance abuse services, and affordable medications.
Future Health Concepts Inc is a Sanford, FL-based company in the Healthcare, Pharmaceuticals, and Biotech sector.
Cellenkos is an early stage clinical biotechnology company that focuses on cord blood-derived T-regulatory cellular therapies for the treatment of autoimmune diseases and inflammatory conditions. Cellenkos is founded on the technologies arising from the laboratory investigations of Simrit Parmar, M.D. Cellenkos` lead product CK0801 delivers clinically meaningful doses of allogeneic cord blood T-regulatory cells to overcome immune dysfunction.
Canadian Dental Service Plans Inc. is a North York, ON-based company in the Healthcare, Pharmaceuticals, and Biotech sector.
Carta empowers hospitals to personalize the delivery of care to the individual needs of each patient. Our insight here is that personalizing care is not only good from an outcome/clinical perspective (where most people focus in the context of personalization) but is also the best way to optimize operations. Currently, hospitals have to over provision their resources because they are set up to serve the generic patient; planning ahead for exactly the resources needed– no more, no less– is the best way to gain efficiency. The approach we`re advocating and enabling is to: 1) Find past patients similar to the current one being treated 2) Quantify what exactly happened to them during their journey through the hospital (this is where our model comes in) 3) Use machine learning to project what the particular patient in question will need, and what the patient can expect their experience to be in the hospital We`re applying this approach now to two use cases– supplies projection and bed usage projection– and we have a bunch of other use cases we`re planning on addressing in the future.