In the United States, about 1 in 7 major surgical procedures involves a complication. This translates to over 4 million complications per year and additional costs of at least $80 billion per year (some sources estimate additional costs at over $160 billion).
Presaj identifies the specific care steps with the highest risk of complications and errors based on each patient’s risk factors. Using a proprietary database of risk analyses, Presaj quantifies the risk for each patient at each care step in order to identify exactly how and why things might go wrong before problems occur.
By combining cross-functional clinical expertise with proven systems engineering principles and existing big data, Presaj improves outcomes for patients, reduces costs for care facilities, provides insights on best practices to care teams, and helps insurance companies reduce premiums.
Big data from surgery databases, risk algorithms, and data analytics systems show that patient risk factors can generally increase the risk of complications for care processes. However these resources don't identify the specific care steps where risk occurs or provide insights about how providers can mitigate that risk.
We’re building upon big data in order to pinpoint the steps with risk for each patient at the point of care. While collecting this data is challenging and labor-intensive, it makes Presaj unique because it both alerts clinicians to the existence of risk and empowers them to reduce it.