healthcare data analytics

In today’s new value-driven reality, it is vital that health care providers identify and implement strategies to ensure long-term, value-based reimbursement (VBR) success. The new VBR payment models tie quality performance metrics to reimbursement in order to incentivize health care providers to maximize value for patients while achieving the best outcomes at the lowest cost.
 
The new reimbursement models present a fundamental consequence to how health care providers manage care. Health systems and providers must now manage all activities across the continuum of care, not just what happens at one site. To produce enhanced quality and sustainable costs, providers must use a quantitative method to closely monitor, expose and act upon performance opportunities to ensure that the highest reimbursement levels are achieved.

The Impact of Analytics on Value

Health care providers that invest in a strong data analytics strategy can get the most out of their value-based reimbursement. The Centers for Medicare and Medicaid Services (CMS) determines the reimbursement amount a provider will receive, based on a variety of quality indicators. Through analytics, the quality metrics and payment incentives tied to them can be identified, monitored and reported.
 
Data analytics helps physicians understand the impact of their health care decisions on cost and profitability, and reveals where they stand in relationship to their peers. Health care providers that exceed the performance benchmarks of their peers will receive greater compensation. Health care providers that find success under value-based reimbursement recognize that an effective, well-executed analytics strategy is key to achieving success.

As you begin to build your VBR analytics strategy, it is important to have a basic understanding of the different types of analytics and the insights that can be gained by each. But keep in mind, health care data is not like other industry data. Health care data is in constant flux; business rules and definitions can come and go so engaging health-care specific analytics is vital to a successful transformation.

Monitoring Analytics

Monitoring analytics allows an organization to routinely check key metrics that are happening in real-time against quality standards. It can reveal what happened, why it happened and what to know.

Monitoring analytics provides deeper, more concentrated visibility into key insights to develop and execute a winning value-based reimbursement strategy. It ensures that organizations won’t be caught off guard at the end of the quality performance reporting period. Instead, opportunities for improvement are identified and adjustments can be made along the way.

Predictive Analytics

Predictive analytics can estimate future outcomes based on the use of statistical techniques. It can show what is likely to happen in the future, what is likely to be the best activity or performance measure(s) to address and what the forecasts illustrate based on historical significance.

As health care providers pursue optimum quality performance outcomes, predictive analytics can be utilized to predict the future and help steer performance in the right direction.

Comparative Analytics

Comparative analytics measures historical data over time to identify key similarities or differences in data patterns. It can show recent changes and compare against industry standards and benchmarks.

When it comes to health care transformation, it is not only how much you improve but how your rate of improvement compares to your peers. Comparative analytics helps organizations to track progress and assess their rate of improvement.

Real-time Analytics

Real-time analytics illustrates what is happening now. It helps organizations identify what can be done now to make a positive change.

Through the automation of data collection and measurement, real-time analytics can provide immediate insight into the patient journey to help improve performance and superior quality scores.

Engage Now in Data Analytics

Data analytics plays an essential role in today’s health care environment. McKinsey & Company estimates that data analytics could account for $300 to $400 billion in cost savings, which is upwards of 17 percent of the total national health care expenditure. No matter which type of analytics you use, hidden opportunities and other insights will be revealed to help health care organizations meet or exceed their quality metric goals, thereby lowering costs and enhancing quality. It’s no surprise that many organizations name data analytics as their most strategic asset.

To learn more about nThrive’s robust health care data analytics tools that help reveal opportunities for quality improvement, go here.