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WellSheet: Enabling Optimized Clinical Workflow
Craig Limoli, Co-founder & CEO, WellSheet
With the increasing demand for quality care, practitioners are focusing more on improving their practice performance. The need to manage the practice efficiently has driven demand for optimized clinical workflows driven by technology. Craig Limoli, while working as a former strategy consultant in the IBM Watson Health division, found that the new healthcare technologies, while powerful, tended to fall short in understanding physicians’ needs for improved workflow. The predicament inspired Limoli to team up with Justin Larkin, an MD/MBA and an expert in healthcare solution design, and establish WellSheet, a company that excels in delivering analytics for practitioners to optimize clinical workflow. WellSheet’s platform touts an intuitive UI, designed to passively collect a physician’s actions throughout the decision-making process, capturing the clinical mindset, and uses deep-learning techniques that make the platform even more effective over time.
Focused on physicians’ productivity, WellSheet ensures that the practitioners get the required information conveniently and consistently. “Applying the latest developments in artificial intelligence and machine learning to understand practitioners at a deeper level, WellSheet creates a personalized experience for physicians,” says Limoli, Co-founder and CEO at WellSheet. The WellSheet platform combines the physician’s practicing process, the patient’s medical history, and clinical practice guidelines to present a customized, one-sheet view of a patient that fits a care provider’s workflow, instead of the current multi-screen, non-contextualized data directly from the EHR. Further, partnerships with major EHR vendors have enabled WellSheet’s solution to exist within the EHR, which is designed to fit into a physician’s workflow seamlessly, increasing the convenience.
WellSheet’s solution is focused on areas where there is more time spent by a physician. Chart review, order-entry, and documentation are some of the main areas of physician workflow that WellSheet has introduced improvements for. Once the patient data is recorded, WellSheet’s solution runs the analytics by taking into consideration all the patient information and clinical guidelines to predict the required data. With this information, practitioners can identify the quality requirements and deliver optimum treatment for effective health outcomes.
For the documentation part of the workflow, WellSheet predicts the relevant information—comprising the data that exists in a patient’s record and the observations made—that has to be included in the physician's notes. WellSheet pre-generates this content and fills in the gaps for the physician’s interpretation. With a simplified integration leveraging the latest APIs from the EHR vendors, WellSheet enables a physician to easily access their interface, unlike the other solutions in the market which require them to navigate a new portal and re-identify the patient in a separate system. With a growing customer base, WellSheet can procure particulars of patients and relevant big data, which are then integrated into the physician workflow.
For instance, WellSheet deployed their solution for a neurology clinic in Wyoming. The practice had challenges in dealing with constantly changing neurology guidelines. WellSheet integrated the specific neurological guidelines into their own algorithms that allowed the practice to easily find those that are applicable to a particular patient. WellSheet’s solution helped to proactively identify the most relevant guidelines, intelligently directing the physicians to make informed decisions quickly in order to deliver quality care.
WellSheet is expanding their team to deliver their solution for practitioners who are struggling with the existing EHRs. Equipped with a team of talented developers and machine learning experts, WellSheet is creating a differentiated product for practitioners to deliver care swiftly by leveraging the company’s predictive capabilities.
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