PatientX360 Product and Feature Update for February 2022

PatientX360 ^TM  is a one-stop-shop solution for multiple stakeholders including patients, healthcare practitioners, healthcare providers (Hospitals, Accountable Care Organisations (ACOs), Preferred Provider Organisations (PPOs), Health Maintenance Organisations (HMOs), group practices, Integrated Delivery Networks (IDNs), etc.), insurance companies and MedTech organizations. The PatientX360 ™ solution is a patient engagement and management platform that offers a single source of truth regarding the patient to different types of stakeholders. It is designed to be highly flexible and easily configurable to best fit the wide variety of settings in healthcare. This way, you get the data you need to address your business challenges.

PatientX360 ™ as Communication PaaS platform (CPaaS)

PatientX360™ can be used as a Communication PaaS plugin that lets you add voice, video, and messaging features through APIs.

There are numerous capabilities of PatientX360™ as a Communication PaaS, some of which are:

• Outbound voice calls
• WebRTC-based calling
• Text messaging (SMS)
• Multimedia and video messaging
• Social media messaging (WhatsApp)

Some of the use cases for which PatientX360™ can be used as a CPaaS are:

• Appointment confirmations and fulfillment updates
• Fraud and abuse mitigation
• Automated customer interactions, through chatbots

PatientX360™ as a Tracking and Monitoring Plugin, with My Schedule

PatientX360™ can be used as a standalone tracking and monitoring plugin. The solution can be used for patient monitoring in the following ways:

1. Patients can utilize the My Schedule feature to track and monitor their health outcomes.
2. Healthcare Providers can connect their standalone systems to the My Schedule feature so that information written in their system can be exchanged to the My Schedule feature for patients to receive the information (electronic flow of information).
3. The My Schedule feature can also be integrated with EHR/EMR systems so that any medication reminders, vital reminders, and diet intake timings within the EHR/EMR can be captured through the My Schedule feature.
4. Wearable medical monitoring devices can also be integrated with the My Schedule feature so that the output of such devices can be captured in the Calendar view for patients to monitor their health outcomes over time.

PatientX360 ™ as an Analytics Platform

Picture credit: ArborMetrix

PatientX360™, with the help of OSG Dynamo, our big data analytics technology, can do wonders when it comes to understanding healthcare data through various aspects of data analysis. The following are the capabilities of PatientX360 ™ as an Analytics Platform:

1. Descriptive Analytics: It allows us to understand what happened historically and answer questions, such as:
   1. How many patients were hospitalized last week?
   2. What percent of patients dropped home therapy in the last month?
   3. What are the average bone mineral metabolism (BMM) laboratory values for the patient population?

These types of questions can be answered by looking at historical data and using simple statistical measures such as counts, percentages, averages, and standard deviation. In general, these descriptive, analytical measures can be tracked over time to see if a practice is meeting its goals.

2. Diagnostic Analytics: It allows us to understand why an event happened and answer questions, such as:
   1. Why did these patients go to the hospital last week?
   2. Why did patients leave home therapy?
   3. Why do patients not meet BMM targets?

These types of questions allow us to dig into the data a bit more, usually to understand or explain the answers found in descriptive analytics. For example, if we are trying to grow our home therapy program, we may discover from descriptive analytics that 10 percent of the population drops each month. The next logical question is why these patients dropped. In diagnostic analytics, we investigate the discharge reasons and measure the distribution of categories such as peritonitis, partner burnout, psychosocial issues, etc., by using statistical techniques to understand those reasons.

3. Predictive Analytics: It allows us to understand what will happen, creating predictions, such as:
   1. Which patients will have the highest risk of hospitalization next week.
   2. Which patients are likely to switch from home therapy to in-center next month.
   3. Next month’s BMM values for each patient.

In predictive analytics, data scientists use historical data to train models to predict future events by employing advanced computational techniques such as machine learning. These models can take advantage of thousands of data elements in the electronic record for each patient and identify patterns from all patients in the database. By using predictive models, we can calculate risk scores for each patient and identify which patients may need additional attention.

4. Prescriptive Analytics: It allows us to understand what actions are needed to change the prediction, as in the following examples:
   1. An extra treatment may help prevent the predicted fluid overload admission for this patient
   2. A home visit from a social worker may help prevent home therapy discharge for this patient
   3. A different BMM therapy may help this patient with medication adherence issues

We can dig into predictive analytics to understand the factors that drive each model. By determining which factors can be changed to lower the score, we can start to create prescriptive interventions that will lead to better outcomes. Prescriptive analytics is the most advanced healthcare analytic because they allow us to make specific recommendations on patient care delivery interventions.

Getting Started with PatientX360™

Want to learn more about how PatientX360™ can help your organization handle and analyze healthcare data? Reach out to our sales team today for more information about how our technology can work for you!