Saving lives with Big Data: MedAware case study
While working in IT industry with Big Data we came across a real-life start-up which impressed us with its innovation and significance. We’re gladly presenting MedAware – technology created to save lives and bring qualitative changes into healthcare treatment.
Fancy US only producing 1,2 billion clinical documents every year, as a life scientist and a doctor what would you do with such huge volumes of health-related but unstructured patient information? It sounds like not an easy task for an individual but luckily, data scientists found the way to structure and analyze it in a way it opens up new opportunities for revolutionized and more efficient healthcare.
MedAware, an Israeli start-up in the field of healthcare based on a thorough research and immense work of data scientists, has already proven to be an invaluable contribution to the future of the industry.
Improving patient safety through the prevention of medication errors is one of the highest priorities concerning the healthcare system today. In the US alone, medication errors harm at least 1.5 million people every year and cause the annual premature death of more than 220,000 patients. Adverse drug events are among the most common medical errors. Out of the 4 billion medical prescriptions that are written up annually in the US, 8 million contain life-threatening errors.
The introduction of Electronic Medical Records (EMRs) and electronic prescribing systems, combined with clinical decision support systems, has only somewhat helped in reducing the number of prescription errors. However, these solutions detect only a fraction of the actual errors and suffer from a high false-alarm rate, leading to ‘alert fatigue’.
MedAware provides an innovative solution to the need for detecting and eliminating prescription errors. MedAware’s patent-pending technology uses big data analytics and machine learning algorithms to analyze large scale data of Electronic Medical Records (EMRs).
Advantages of the system
Among MedAware advantages are the following:
- High error identification: it identifies and prevents more prescription error types than any other solution, particularly drug mix-up and patient mix-up.
- Low ‘alert fatigue’: false alert rate is lower than 10%. MedAware’s system is self-learning. Based on the physician’s response to the alert, it automatically fine-tunes the model, so that an alert, which has been repetitively rejected, will not be repeated, thus avoiding alert fatigue.
- Fully personalized: response is based on the patient’s specific data.
- Low maintenance: no content updates with associated lag-time and costs.
- Significant cost reduction: the system eliminates unnecessary hospitalizations and re-admissions, as well as excessive hospitalization length of stays.
By identifying and preventing prescription errors in real-time, MedAware’s solution saves lives, improves patient safety and significantly reduces healthcare costs resulting from prescription errors and adverse drug events. MedAware targets healthcare providers, pharmacy benefit management companies, as well as pharmacy chains.
All things considered, the role of Big Data in healthcare is difficult to overestimate, whether it’s monitoring and prevention of health problems using wearable data or advancing pharmaceutical research to find cure for cancer and Ebola. And while data science provides tools and methods to extract real value from clinical information, it eventually contributes to making healthcare more efficient, accessible and personalized.