Patient Experience Analytics for Optimal Patient Services Decision Making

How Patient Journey Analytics Contribute to Better Outcomes

• A complete view:
  Unlike business intelligence (BI) dashboards limited in the number of data sources and the data volume they can analyze, WhizAI is highly scalable. It can analyze billions of data points, from healthcare provider (HCP) referral patterns, NBRx, and optimal dosage and titration data to patient outcomes. Better yet, WhizAI can deliver the answer a patient services team needs in less than a second, regardless of how complex the question or how much data is required for a complete picture of a patient’s circumstances.
• Accessible, actionable insights:
  Few patient services team members are also data scientists. WhizAI understands that the people on your team need patient experience analytics insights to do their jobs effectively, regardless of data analytics or IT expertise. With our platform, users simply ask a question, and WhizAI, powered by artificial intelligence (AI), machine learning (ML), and natural language processing (NLP), responds. Users don’t have to memorize keywords or particular phrases to use the platform. WhizAI understands the way patient services professionals communicate.
• Automated visualizations:
  Life science company teams have busy schedules and juggle a variety of tasks. WhizAI automatically creates visualizations based on the information it’s presenting and user preferences. With WhizAI, users always have the most important information front and center and insights that lead to quick decisions on the best next steps.
• Invisible technology:
  WhizAI believes that your team deserves powerful patient experience analytics capabilities – but that they should never even realize they’re using a BI solution. Instead, we’ve designed our platform to be as easy to use as a social media app, moving technology to the background and making seamless user experiences the priority.

Case Study: WhizAI Helps Manage 20,000+ Patients and Keep Them On Track With Their Therapies

A top global pharmaceutical company with 50 products across 10 therapeutic areas serves more than 20,000 patients. The company created a comprehensive patient portal to enhance patient experiences. However, 25% of patients discontinued using the portal within 90 days, and 20% of patients never began their therapy. The pharma company identified the root cause of the issue as a lack of visibility into the patient landscape. The thorough analysis required using a range of data sources and quickly delivering the insights that patients needed.

The company deployed WhizAI for patient experience analytics and, in only six weeks, saw 100% adoption of the solution, greater visibility into each phase of the patient journey, and instant identification of patients at high risk of discontinuation. With WhizAI, the company improved adherence and reduced dependency on its IT department by 60%, saw a 50% reduction in analytics total cost of ownership (TCO), and a five-fold increase in productivity.

The Benefits of Patient Service Analytics

Fast Deployment

WhizAI is pretrained for life sciences, enabling deployment within weeks rather than the months it would take to train a generic AI solution for the industry. Also, once deployed, users need only a few minutes to familiarize themselves with the platform before they can begin getting the patient experience analytics insights that help them do their jobs successfully.

Anomaly Detection

Identifying outliers, patients at risk for discontinuing their medications, or spotting unanticipated changes are key to patient services. But monitoring data manually is impossible, particularly at the speed of business. WhizAI identifies anomalies in patient data from end-user medical devices such as glucose monitors and ECGs, prescription adherence, and patient histories, and alerts patient services teams.

Improved Efficiency

With technology that delivers patient experience analytics insights to users on-demand or proactively – employees have more time to focus on their core responsibilities rather than on using a BI solution. WhizAI’s ease of use also decreases reliance on a life science company’s IT and data teams, allowing resources to use their talents to help the company develop a stronger competitive position.

A Culture of Data

When patient services teams realize how easy WhizAI makes building data into daily workflows – and how outcomes improve – they’ll begin to make data-driven decision making standard practice and enjoy greater success in their jobs

Agility

The life sciences industry and patient landscape are constantly in flux. WhizAI takes only a fraction of the time required to adapt BI dashboards, allowing patient services teams to keep up with change and adapt quickly.

Frequently Asked Questions

What is embedded analytics?

Embedded analytics is the direct integration of advanced data analytics into business applications. As a result, analytics are available to users within their workflows. WhizAI integrates with the business application your team routinely uses, such as Microsoft Teams or Veeva.

How does WhizAI create a single source of truth?

WhizAI integrates, synchronizes, and manages disparate data sources to create a centralized system that everyone in your organization uses. This feature of our platform enhances communication, collaboration, and progress toward business goals.

Does WhizAI enable ad hoc analytics?

Yes. Users can analyze data on-demand with ease. WhizAI doesn’t use the dashboard as the unit of work and, therefore, doesn’t require the user to generate a report, add calculations – or call on the IT department to do so. With WhizAI, the unit of work is a question. Users ask. WhizAI answers.

Does WhizAI work on any device?

A patient services team can access WhizAI from within business applications on any device – from desktop computers to laptops, tablets, and smartphones.

Does WhizAI support multilanguage teams?

Yes, WhizAI is a valuable tool for international teams, enabling users to interact in their own language, which increases the quality of insights and user adoption.