Big Data in Healthcare Delivery: The Power of HEDIS

Big Data in Healthcare Delivery: The Power of HEDIS

First in a Series

By Patrick K. Wier

This summer’s never ending debate on healthcare in the halls of Capitol Hill and the virtual halls on the internet is so complex it’s hard to wrap your head around. Why are costs so high? Why do there appear so many inefficiencies? The queries go on and on. One place to begin a greater understanding is the revolution that is taking hold in industry overall, however, at a slower pace in healthcare- big data.

Big Data: HEDIS
Big Data: HEDIS: Patrick Knight Weir dMann Training Technologies

Patients, providers, payors and vendors alike have a shared experience within the system through management of patient data in the form of huge stores of physical folders or electronic health records (EHR). Slowly and at large sums of investment practitioners are transitioning to one of the many forms of an EHR. This is an effort to capture the powerful effect of big data. Effectively utilized big data along with other interconnected electric devices the industry seeks to improve health outcomes while lowering costs associated with managing health conditions.

Leveraging technology to connect patients to providers to payors by linking multitudes of patient data while abiding by HIPPA regulations can bring about significant improvements in leading health complications like congestive heart failure, COPD and diabetes. Understanding patient information in a real time manner while learning constraints on the system can lead to more effective utilization of resources and reduce wasteful spending such as needless testing.

Payors and patients can learn which providers deliver greater results through established metric ratings developed by the Center for Medicare and Medicaid Services (CMS). An example of this is seen in the Healthcare Effectiveness Data and Information Set (HEDIS) which collects performance measures across 80 different dimensions of care and service. Insurers are constantly collecting data and rating all providers across the country to assess the effectiveness of health care delivery. Through the use of this scoring system health systems are constantly squeezing increased value in business results aligned with improved health outcomes for numerous health complications.

In conclusion, as more and more providers switch to EHRs payors can adjust payout rates to practitioners and deliver improved health outcomes which ultimately trickles down to the patient. Big data is the driver of progress in the industry and needs to be considered in our national conversation and on Capitol Hill when assessing how we carry out one of the most costly concerns in all individuals and families.

What other means can big data serve and address current inefficiencies in the U.S. healthcare system?  Please leave your thoughts in the comments section.  We would love to hear from you.  You can also contact us at jerrydmann@dmanntraining.com

Understanding Big Data in Healthcare

Big Data in Healthcare Gerald Jerry George Mannikarote dMann Training Technologies

by Gerald George Mannikarote, MBBS MBA

I’ve been consulted on several occasions to assist with various healthcare companies’ entry into Big Data management.  The most common question is how to translate the data they own into something meaningful. However, often the challenge for most businesses is making something meaningful from that data.

Translating Big Data into something meaningful is more than just hiring a consultant.  It also takes understanding what data you have.  The data collected has to be related to something that helps define the company and their customers’ needs.

Meaningful Data

What most of the companies I’ve worked with are happy to inform is that their patient outcomes are very good.  So what does that mean?  What do they mean by good outcomes?  How does that help their customers?

If you keep in mind that the end user is a patient, but your customer provides care for the patient, this better defines how to use Big Data.  So you must better define your customer.  Is your customer a physician, a healthcare provider system, or a healthcare payer?  By defining who your customer is, you will be able to define how you use your Big Data.

Big Data in Healthcare Gerald Jerry George Mannikarote dMann Training Technologies
How do you make your Big Data meaningful?

Let’s take a healthcare provider system for example.  Assume the provider system is interested in reducing readmissions.  In such a case, you will need to find a way to show how your Big Data correlates with reducing readmissions.

In the case of physicians, it may be something different.  Let’s say the physician is interested in reducing patient expenses.  In such a situation, your Big Data needs reflect how it reduces costs for the patient.

What about payers?  How do you tailor Big Data for such an audience?  Maybe the payer is interested in improved clinical outcomes with lower healthcare costs.  Then you must be able to demonstrate that your Big Data can not only improve healthcare outcomes but also lower healthcare costs.

Providing Value

By successfully demonstrating how Big Data is meaningful to your customer, you will be able to provide your customer with a meaningful solution.  A meaningful solution provides value to your customer.  Providing value demonstrates understanding.  This will then demonstrate your understanding of Big Data in Healthcare.

Big Data in Healthcare Gerald Jerry George Mannikarote dMann Training Technologies
Big Data in Healthcare. It’s world wide

I encourage you to analyze the your Big Data.  Are you making your Big Data meaningful to your customers?  Does your Big Data bring value to your customers? How have you been able to demonstrate meaningful Big Data to your customer?  Please leave your thoughts in the comments section.  I would love to hear from you.  You can also contact me at jerrydmann@dmanntraining.com