Providers and payers have become increasingly dependent on analytics to learn how they can deliver better outcomes for their patients or members and drive financial success for themselves. While we’ve seen incredible impact in some areas, the healthcare industry is still often seen as data rich and insights poor. But, there’s good news coming.

As technology continues to evolve and data grows more complex, many executives are championing augmented analytics as a way to revolutionize their processes and advance on clinical, operational and financial goals.

In this guide, we'll explore what augmented analytics is, the benefits it can bring to healthcare, and tips for leveraging it.

Augmented analytics applies technologies like machine learning and AI to support data preparation and analysis processes.

These capabilities help:

  • front-end users operate more effectively in their day-to-day workflows
  • data scientists deploy automations that save time and avoid human error
  • managers track and transform performance with rules engines and alert triggers
  • executives get a high-level view of complex trends with narratives and visualizations

Creating measurable impact by using augmented analytics is not only possible but necessary for organizations today.

You may be thinking, ‘I’ve been hearing about advanced technologies for years, what has changed that deserves attention?’

Great question. Our answer is: outlook and expectations.

As an industry, we eagerly overestimated the short-term effects analytics and AI would have in healthcare—yet critically underestimated their long-term impact on the entire landscape.

As Lyle Berkowitz, MD, FACHP, FHIMSS noted at the 2022 Impact Summit, “This general sentiment has been applied across many industries for many innovations. It serves to remind us that though situations did not change overnight, the landscape is progressively shifting. We saw this happen with telehealth capabilities, and we will continue to see it as analytics and AI slowly transform care delivery. The question is merely, when will you adopt these technologies and how extensively will you use them?”

The business purpose of analytics is to take data from a hoard of numbers to a holistic plan for improving outcome.

The path from raw data to real action is comprised of four flavors of analytics:

Descriptive analytics is already playing a significant role in healthcare organizations, and is likely the most recognizable form of data. For example, in a given month, descriptive analytics would convey metrics including:
  • Number of admits
  • Number of hospital-acquired infections
  • Average length of stay
  • Percentage of discharged patients utilizing home health
  • Most diagnosed disease
Though it simply describes what has happened, this historical data is essential as it lays the groundwork for all the other types of analysis.
Diagnostic analytics is also fairly common in the healthcare space, as it allows organizations to drill a bit deeper into the reasons behind recorded happenings. Diagnostic analytics could answer questions such as:
  • Why are certain patients not following their medication plans?
  • For what reasons are patients being readmitted?
  • What factors are affecting length of stay?
Both descriptive and diagnostic analytics can be represented in auto-generated smart narratives that supplement traditional charts and graphs and help drive focus on the most important details of the data.

Predictive analytics can be used to predict a slew of critical metrics, including:

  • claim denials
  • future cash flows
  • future PMPM
  • patients that will eventually be high-cost claimants (HCC)
  • avoidable emergency visits

While the use cases for predictive analytics are innumerable, we've identified two simple ways that healthcare providers can dip their toes in.

First, predictive analytics can be used to deliver better insights into the effectiveness of treatments and medications—based on both clinical data and socioeconomic factors.

Second, predictive analytics can be deployed to identify high-risk patients and proactively deliver meaningful interventions.

Unlike the other flavors of analytics, prescriptive analytics gives healthcare providers and payers methods of determining which processes must evolve to achieve improvement goals. This technique takes the forecasting and simulations data of predictive analytics and leverages rules and outcome-driven constraints to produce recommended decisions and important restrictions.

Prescriptive analytics holds much promise for helping healthcare organizations make better decisions in clinical settings, business operations, and the supply chain.

Where traditional analytics requires highly skilled subject matter experts to methodically organize and interpret data, augmented analytics takes massive amounts of information and surfaces valuable insights rapidly and accurately. Augmented analytics—in all its forms and flavors—promises many benefits to the healthcare industry.

Healthcare organizations have more data than they know what to do with, and it is captured from a variety of sources in a wide array of formats. Augmented analytics offers a simple way to sift through this data, organize it sensibly, and deliver actionable insights back to users.

Challenges in hiring and retaining staff extend far beyond clinical settings; health plans have also been struggling to fill roles. Augmented analytics offers the tools necessary to reduce manual effort while enhancing efficiency and output quality.

Augmented analytics can help providers to identify and diagnose patients more quickly and accurately, reducing the cost of care and improving patient outcomes. It can also help providers to better manage their practice and provide the best possible interventions.

Payers can deploy augmented analytics to examine the effectiveness of providers and interventions—and pinpoint ways to improve. Equipped with this knowledge, payers can construct a stronger network and devise better plan offerings to ultimately drive positive member outcomes.

Use this resource to ensure you’re realizing the full value of augmented analytics.

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