Improve Patient Outcome

Predictive and preventative healthcare requires real-time accurate information, a personal medical profile/history, and intelligent processing algorithms capable of recognizing critical health factors and making appropriate interventions at the right time. In today’s health-care system, critical information on a patient’s real-time and predicted future health status is often missing or incomplete. With rapid advances in digital technologies for collecting, monitoring, processing, and communicating health-care data, digitally enabled prediction will become a central input into decision-making in healthcare.

Digital continuous care is a key and cost-effective mechanism, able to generate information we do not currently have, especially outside a hospital environment. It has many different components and functionalities and can be uniquely configured for each specific use case. However, the ability to generate and analyze the patient real-time data, build a dynamic baseline, and predict future complications is the common denominator and a critical link in focusing on patient outcomes. It clearly defines patients at risk, accelerates care delivery, and optimizes access to care for chronic patients. Augmented medical algorithms can identify critical health issues at an early stage and deliver proactive, data-driven decision support. This technology creates some short-term and long-term opportunities as well as transactional opportunities to make processes increasingly more efficient. Being able to collect and process patient’s outcome information in real time is an invaluable resource when assessing the cost-effectiveness of healthcare.