Healthcare providers are facing increasing pressures from a variety of angles. The ongoing digital revolution is catching up to challenge legacy technologies and processes in the industry. Patients are catching up to these trends, entrepreneurs are innovating, and available data is exploding. As patients begin to act more like traditional consumers, healthcare providers must adapt to these expectations to deliver a personalized patient experience that matches other industry standards all while optimizing clinical outcomes and managing costs.
At SpringML, we help providers tackle these challenges by providing insights and empowering them to make data-driven decisions that aim to improve outcomes and the patient experience. We do this by connecting legacy data sources, organizing the data for analysis, applying our vast experience in analytics and modeling, and ultimately presenting this information to end users at the point of action. This path unlocks the insights from data and allows providers to operationalize these insights through AI and guided recommendations. It’s about going from data to knowledge to wisdom.
One area where we have seen Salesforce invest in the assisting healthcare providers is in Health Cloud. Health Cloud provides a managed package that includes an extension of the Service Cloud data model to address healthcare specific data attributes and a variety of platform features such as Lightning Flows and VisualForce pages to create a robust Patient Engagement platform. Last week (early March 2020), Salesforce announced an extended package of Einstein Analytics templated apps that further enhance Health Cloud capabilities.
These templated apps contain over a dozen dashboards that provide insights in Health Cloud. For providers, this provides an out-of-the-box mechanism to look at patient segmentation, care performance, referral analytics, readmission and risk analytics, and deeper understanding of social determinants of patient outcomes. Some of these areas also include pre-built predictive models that supplement visualization insights and drive recommended actions such as tasks, marketing activities, and new care plans.
Templated apps provide a great starting point for provider organizations to get started with Einstein Analytics. However, in our experience, most organizations have nuances in their data model, Salesforce configuration, or other factors that drive a need for additional customization. Einstein Analytics (which also includes Einstein Discovery for building predictive models) can be extended to handle these customizations, connect to other data sources, and build predictive models that go beyond the out-of-the-box Health Cloud data model.
Einstein Analytics Use Cases
Here is a sampling of provider use cases that can be tackled using Einstein Analytics:
- Optimizing case workloads by understanding the type of case, predicting its attributes, and routing them appropriately to the right agent
- Providing agents with a 360-degree patient view, embedded in their workflow in Salesforce, along with recommended actions to improve their experience
- Create care plan templates to better match care plans to patients based on clinical outcome history via predictive analytics
- Inform patient outreach and engagement tactics to increase care plan adherence or minimize appointment cancellations
- Share data and insights across provider network relationships and use predictive analytics to maximize referrals
There are numerous ways that the Salesforce platform and, specifically, Einstein Analytics can assist providers as they tackle the challenges they face today. From data integration to visualization and driving insights and recommended actions to end users, SpringML can help drive the AI-led digital transformation that is necessary to improve patient outcomes, experiences, and manage costs for healthcare providers.
To understand more about how providers can use technology and machine learning to serve their patients better watch SpringML’s Patient 360 Analytics for Providers recorded webinar.
SpringML’s Patient 360 analytics leverages advanced analytics and Machine Learning to bring key insights to providers, and helps them achieve their goal of providing high value, personalized care to their patients. If you still have questions, drop us a line at [email protected] or tweet us @springmlinc.