Preventive medicine is the future of medicine.
What We Do
30% of hospitalizations of adults over 65 are due to an Adverse drug reaction (ADR), most of them are preventable.
ADR predictor gives healthcare organization the most important information about high risk patients of ADR: which patients require an intervention, a checkup by a healthcare professional to avoid an ADR which may result with hospitalization or an ER visit.
ADR predictor knows when a patient is in high risk of hospitalization and points to parameters which indicated on high risk to assist healthcare professionals with the intervention process.
Our technology is based on medical research and advanced data science, a powerful combination that yields better prediction results by analyzing Electronic medical records and derivatives of electronic Medical records to get optimal approximation to a prediction of a high risk ADR that can lead to hospitalization or readmission.
Mydimed Personal interaction checker is the first drug interaction checker that recieves input about drugs, diseases and side effects and returns a personal report of possible drug interactions, covering drug-drug, drug-disease, drug-food & drug-cannabis interactions.
the personal interaction checker serves population health programs and encourage the general public to self test and see their doctor if they find a correlation between the symptoms they feel and the interactions found in the report.
How it works?
From a flag on a data set to saving lives
We use machine learning algorithms to scan medical records and generate a risk score for a high probability of hospitalization or reaching the ER due to an ADR. The systems also provides the reason for flagging a high risk patients, so healthcare professionals know why a patient is at risk and where should they intervine.
"Targeting interventions to a subset of patients considered at greatest risk of an ADE, such as elderly patients, Polypharmacy patients, and/or patients with many co-morbid conditions, may be of highest yield.”
Source: Hospital-based Medication Reconciliation Practices: A Systematic Review
Measurable and Scalable
Mydimed machine learning algorithms are trained to yield optimal results and reduce false positive intervention. The system learns from intervention results by every cohort to mesure it's prevention success rate and produce better accuracy with the following cohort.