Do-Med
Software to help GP’s and Endocrinologists choose treatment based on clinical parameters, research and actual patient observation data. A platform that could serve any medical area in the future.
The treatment of Diabetes is a growing challenge with the dozens of drugs (over 50 medication possibilities) that have been developed over the past decade. In order to tailor the optimal personalized treatment, the physician is required to take into consideration the patient stage of disease as well as other morbidities, the medication cost and reimbursement.
Currently there are over 50 medication possibilities to treat diabetes type 2. With metformin as a gold standard first line treatment and abundance of possibilities and variables that affects the clinical judgment. With clinical inertia that causes patient to stay on same non effective treatment for too long, overflow of new data for each drug and clinical trials for the drugs, the result is uncontrolled diabetes in tremendous numbers.
When prescribing, clinicians are confronted by increasing amounts of clinical data for each patient they treat as well as an exponentially increasing volume of relevant medical research. Even when a diagnosis is instantly clear, a physician needs to spend several minutes of each medical visit, to review a patient’s medical chart, to ensure the correct medication is prescribed for each individual based on his medical history. Medications typically have contra-indications limiting them from being prescribed, to certain patients who do not fit the recommended values for either their overall medical condition or for their known blood test results, such as: BMI, measured kidney function, lipid profile, hemoglobin level, etc.
Additionally, patients suffering from chronic diseases may have a plurality of medical conditions which contraindicate prescription of one or many medications which would have otherwise been suitable for one of those
Inventors
![](https://mor-research.com/wp-content/uploads/2024/01/doron-netzer-e1707431436214.jpg)
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Contact info
![](https://mor-research.com/wp-content/uploads/2024/01/avital-pritz.png)
Avital Pritz, Director of Medical Devices and Digital Health
For further information please contact:
sari@mor-research.comThe new technology is a software solution for aiding a physician in selecting the optimal medication for a patient having a specific medical history. The preference of a specific medication may be defined by a system administer according to predefined rules appropriate to HMO directives or to medical board recommendations.
The system uses an advanced algorithm integrating medical data and patient’s parameters to provide tailored made recommendation. The platform will simplify clinical decision for a variety of chronic diseases and conditions with a minimal effort from the HCP.
The clinical decision support systems (CDSS) market is projected to reach USD 1,519.2 Million by 2021 from USD 856.3 Million in 2016, at a CAGR of 12.2% from 2016 to 2021. North America dominates the global market for clinical decision support systems. This is due to early adoption by healthcare service providers, availability of advanced technologies and rising investment from healthcare IT players. China, India and Japan are expected to show high growth rate, due to increase in aging population and rising number of chronic diseases. In addition, increase in government funding for healthcare IT systems are also expected to drive growth in these markets.
The first version of the software developed and tested with endocrinologists.
US granted patent