There are frequent bottlenecks of patients at chemo-infusion centers at cancer-treatment facilities and at imaging centers, radiology and primary-care clinics.
But, says this MedCity News article, “predictive analytics company Lean TaaS, thinks its approach can make the case loads more manageable…. The company has raised $3 million in its first institutional round of funding led by Sedgwick Claims Management Services to support the rollout of its predictive analytics platform iQueue. It has also received investment from angel investors in the Silicon Valley. Although it sees an opportunity for cancer centers, it believes its analytics tool is relevant to other aspects of healthcare.”
The problems to be addressed include patient access as well as care coordination; the company asserts that iQueue offers a way to manage both.
The company’s analytics system calculates a wide range of factors to optimize patient appointments. Sanjeev Agrawal, the company’s president, said:
“The problem with [current practice] is it is typically first come, first serve. That is the worst way possible of scheduling.”
“We look at historical patterns for types of therapy people have come in for. We look at extensive modeling of patient types and impose real world constraints. How many doctors are available? How many nurses? How long is a shift? Are they using these beds for something outside of a chemo unit? Very few of the current options maximize patient efficiency.”
