Transforming clinician experiences
Healthcare organizations are struggling to reduce clinician burnout and improve clinical workflow efficiencies. To improve the clinician experience, organizations need to look beyond EHR and point solutions.
Balancing patient care with a myriad of routine daily tasks. It’s no surprise clinicians can become frustrated. Especially when faced with the inability to access meaningful, patient-specific data that is aggregated and presented in an actionable format at the point of care. Inefficient, manual workflows prevent clinicians from working top of license, They lead to increasing burnout and dissatisfaction.
To remove common friction points and improve the quality and timeliness of care, health systems need digital solutions that leverage existing technology investments in intelligent ways.
Automation and simplification
Many of the technologies implemented by health systems over the past decade have inadvertently created hours of burdensome administrative tasks for clinicians. While EHR optimization and the addition of point solutions have provided some relief, most workflows are still predominantly manual.
Health systems can alleviate clinicians’ most time-consuming and repetitive workflows by augmenting existing IT investments with next-generation technologies like AI, ML and IoT.
Leveraging the data
Our Data Analytics and AI/ML teams work with you to aggregate data across multiple, disparate sources, delivering proactive insights to clinicians at the point of care.
Harvesting discrete and narrative data from sources like the EHR, sensors, devices and laboratory systems provides a holistic view of the patient in real time.
Next-generation clinical decision support
Digitally-driven, new diagnostic and treatment approaches are continuously being identified. Traditional clinical decision support tools cannot keep pace. Clinicians are also struggling to keep up.
We work with leading healthcare organizations to implement next-generation clinical decision support solutions. Leveraging technologies that include computer vision, AI and ML. Enabling clinicians to significantly improve speed and accuracy of diagnosis, while achieving better patient outcomes.