Chandra Tekwani, Core Mobile Inc.'s founder, learned firsthand about the need for healthcare collaboration and post discharge care coordination when caring for his son during multiple surgeries.
He witnessed ineffective care coordination between surgeons, anesthesiologists, and nurses. All day long, Chandra watched people continually input/access information, order tests, and repeatedly try reaching people for consults or information. He witnessed hours of wasted time doing manual coordination.
The problem became more evident when he received overly complex discharge instructions, that resulted with a wound dressing change that was missed because is was difficult to decipher the lengthy type-written instructions.
Chandra had spent 20+ years in mobile and internet security technologies, including serving as VP and Head of Juniper Network’s Worldwide Mobile Carrier Business, Director of Engineering for Nokia/CheckPoint, and Director of Solutions at Netscreen Technologies. Chandra founded Core Mobile with a seed investment from Citrix combined with guidance from anesthesiologists, surgeons, and primary care providers. Based on his research, Chandra patented the technology to make Engaged Efficiency™ possible.
Core Mobile starts with a context-driven engine to provide relevant information on providers’ and patients’ mobile devices. Content can be related to a procedure, diagnosis, schedule, location, phone call, or test results.
- Patients can view instructions, images, and videos.
- Providers can view patient records from multiple EMRs, PACS and other clinical systems.
Then, information is made actionable:
- Patients can communicate with providers via text, voice-to-text, images, and videos.
- Providers can order clinical tests and prescriptions; set reminders for prescriptions; and make new information available to patients and the provider team.
The collected information is used to coordinate care. Messages can be sent between team members using one-to-one messages or team messages. Communications also can be directed to the patient and family members.
The combined information and actions drive a predictive analytics engine to further streamline workflow and care activities.
The key success measurements are:
- Reduction of OR turnover times between 5 and 15 minutes per patient.
- Increase in patient throughput between 5% and 20%.
- Reduction in readmissions and revisits between 5% and 20%.
This technology is further enhanced by integration with wearables from Apple, Samsung, and Jawbone.
The technology was successfully tested by more than 1,000 users prior to implementation in the healthcare industry in 2014.