Data Analytics: The Rhythm to Our Healthcare Blues

Abhinav Shashank
Tue 29 Aug 2017
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Numbers. It’s all in the numbers. As of 2017, the amount of information is growing much more rapidly than our understanding of what to do with it, or our ability to differentiate the useful information from the rest. On the other hand, the inflated health care costs in the U.S. are showing no clear signs of decline. So, we should be directing our focus towards smarter, data-driven solutions or more simply analytics, which will make the job of doctors a lot easier and manage the skyrocketing costs that come in the way of providing quality care to the population they serve. Digitized health information holds the potential to reduce treatment costs, avoid preventable diseases, and improve the quality of life in general. The sooner we optimize its utility, the better will be the care of the patients.

In the current scheme of things, where we have moved from a fee-for-service model to a fee-for-value one, doctors and insurance payers are required to work with data more than ever before. For now, storing data has become way cheaper than it used to be and since doctors are being paid based on patient outcomes, sharing it is all the more necessary. The twin benefits of this include, but are not limited to, improving the lives of patients and cutting costs for insurance payers.

In broader terms, hospitals and health systems with the use of data analytics can attain accuracy and gain useful insights to enhance performance. On top of this, they can track tasks on visual dashboards, compare performances of physicians, locate business opportunities and above all, support clinical decision making.

By optimizing data analytics to maximize quality, safety, and efficiency, we would be able to make huge strides in the healthcare realm. Here’s looking at some positive outlooks on the same:

  • Maximize cost effectiveness and sustainability of health systems
  • Analytics in healthcare can be used to further the goal of care management by incorporating qualitative information to more efficiently stratify patients as per the population.
  • Identify high risk patients and major cost drivers
  • Analytics makes the whole process a lot faster, thereby enhancing clinical judgment and truly improving health outcomes.

How does data analytics serve the purpose in healthcare?

The current trend in healthcare is bent towards four kinds of analytics approaches, namely, descriptive, predictive, prescriptive, and comparative.

Descriptive analysis is explanatory as it interprets findings in the context of the problem. Its most basic function is to assess historical data for insights on how to approach the future. Analytics of this kind helps health systems to find out the reasons as to what went wrong in the past.

Predictive analysis is about analyzing the likelihood that an event will occur. This analysis is performed by identifying patients based on their risk profile, determining whether they have chronic conditions and more. The result is a predictive forecast for getting improved outcomes.

Next, comes prescriptive analysis which is the most valuable when it comes to managing population health. This type of analysis moves beyond the ability just to predict an event but, actually tells you how you can make the future work for you.

Comparative analysis is a most interesting way to pit the performance of a health facility against another. Using this kind of analysis can help healthcare organizations measure the success rate of doctors, hospitals, and ACOs. With this, we can recommend the most economical treatments amongst physicians and hospitals for patients.

Some prerequisites to getting ahead with data analytics:

  • Getting access to data that’s only a matter of clicks away.
  • Ensuring that patient records are not fragmented
  • Ensuring adequate privacy and security of patient records
  • Choosing a large population size when analyzing data for making comparative reports because greater amount of data leads to a more authentic report
  • Adhering to strict and open standards to ensure users and sellers of EHRs work towards the same goal
  • Buying certified software to ensure that the EHRs meet basic quality, safety, and efficiency standards

The Road Ahead

Analytics in healthcare has the potential to reduce disparities that exist within. It can be harnessed to improve population and public health. With the assistance of analytics in the systems, any organization can increase its value by tenfold. Proper mining of clinical, claims and cost data combined with the right analytical approach can help health organizations get a better sense of patient outcomes, performance and how and where they can reduce costs.

The biggest opportunity, though, for the use of data in health care is care coordination. Analytics can better engage the patients and their families in the entire process of care delivery as it identifies the high-risk patient so they can be attended to at the earliest. What is also crucial is that physicians can make more informed and evidence-based decisions on the basis of analytical results.

All these achievements ultimately lead to the fulfillment of the Triple Aim of healthcare which is to the improve patient and population health while reducing the per capita cost.


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Tags: Accountable Care, Healthcare, Integration
Abhinav Shashank
Data Analytics: The Rhythm to Our Healthcare Blues

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