Healthcare Technology Blogs by Innovaccer

Big Data: The Underestimated Pill for the American Healthcare

Big Data,’ there are a lot of notions for it. Some people call it a buzzword, some call it a revolution, and some call it data management master. But to truly understand what Big Data is and what it has done for us, we need to know how we have progressed in recent years. Has Big Data made the world a better place?

The best way to see how Big Data has made the world a better place is to observe the advancements we have made in the last decade in healthcare. Why healthcare? Because it has the most profound impact on us.

What seemed like an impossible job 30 years ago, would take only minutes today! We have real-time monitoring for folks, smartphones to share information, and virtual care assistance at home, anytime. This is all great on an individual level, but the true impact can be seen on a macro scale. At a population scale!

With Big Data, we can understand the critical science behind each disease, find out the best practices, and apply it to the large population to get results that were never seenbefore.

The digital age has seen many industries being transformed with this technology. But what is the difference between other industries applying Big Data and Healthcare leveraging it?

 

Source: https://www.dhdf.eu

What is the difference between other industries applying Big Data and Healthcare leveraging it?

It is very fundamental. Other industries have leveraged Big Data to solve their biggest problems. For instance, Banking uses Big Data for tick analytics, card fraud detection, archival of audit trails, enterprise credit risk reporting, and others. And frankly, they have done it quite well. However, on the other hand, healthcare’s biggest issues are:

  1. Unaffordable cost of care
  2. Inequitable care access
  3. Patient’s and caregiver’s experience

These three challenges have been persistent throughout the decade and healthcare hasn’t been able to solve them. Today, the US healthcare spends over $10,000 per person, but do we see equally effective results?

As evident in the graph alongside, Big Data is mostly utilized by Software/computing and healthcare is towards the end. This is alarming because healthcare generates very complex data, which has a lot of implications and is at the same time very sensitive.

There are so many use cases that can be solved, and we know it. But still, the application of Big Data in healthcare is very much limited!

Why is healthcare data more complex than other sectors? And why does it need Big Data?

In the digital world, there are 5Vs to understand the data today.

Healthcare data is a mix of all five. The volume of data in healthcare is huge. From clinical to pharmacy, the range of healthcare data keeps on increasing and goes way beyond the Internet of Things and makes it humongous in nature. On top of this, healthcare data is updated on a daily basis and holds value to a single datum.

 

Source: http://jcsites.juniata.edu

But more importantly, it is critical that care teams are able to make sense out of the complex data. Most of the healthcare data is unstructured and needs cleansing, normalizing, and structuring for it to make sense.

Too much data can lead to analysis-paralysis, which is why healthcare needs:

  1. Structured data
  2. Accuracy
  3. Analytics
  4. Sharing capability

Healthcare technology does not end at storing data in the EHRs. It needs to go way beyond this ‘tradition.’

Going digital in healthcare was predominantly marked by the beginning of the EHR era. Everyone adopted a system of record and started storing data, but not much thought was spared on the later use of data. This created another set of problems, which we are still addressing today. Nearly one-third of individuals who went to a doctor in the past 12 months reported experiencing a gap in information exchange.

In a survey, 95% of the providers had reported that they have some form of challenge with the current information exchange. This is a big problem for health care because it is driven by teams. And if teams can’t understand each other’s work then efficiency goes down tremendously, let alone the dreams of synergy.

 

Source: Office of the National Coordinator for Health Information Technology. ‘Gaps in Individuals’ Information Exchange,’ Health IT Quick-Stat #56. dashboard.healthit.gov/quickstats/pages/consumers-gaps-in-information-exchange.php. April 2018.

But it is an even bigger problem when patients face gaps in care because of missing information. Either they can carry the vital information along with them or it remains hidden from the tending physician. Of all the value data holds, this is the most critical among all.

What should be the priority with Big Data in healthcare?

There are a lot of articles, papers, and interviews answering this question. But if one were to summarize it in one line it would be – “make healthcare simple again.” Doctors should stay doctors and not perform data entry. It is very important that everyone stays on top of their license. For instance, a doctor can perform a foot exam for a diabetic patient and enter the record into the EHR. But does he/she need to do that? Is that the best usage of their time and license? No.

Technology in healthcare needs to be much more advanced. With Big Data at the backend, automation of hospital operations should be the goal. Real-time health systems are needed and for that, a proper IT infrastructure is needed.

1 .Understanding each patient is understanding population

As healthcare grows every day with each patient, the complexity of data increases. We need to be able to take care delivery from ‘a sickness treating’ model to ‘a preventing disease model.’ Care teams need to know how healthy their patients are? Who is most likely to fall sick in the coming years?

If the US is spending 17.5% of its GDP on healthcare, what are its major contributors? We need to be able to drill down from a population-level to patient-level and see the distinction for ourselves. In a research, it was found that US healthcare’s extravagant spending of over $3 trillion flows on very few patients. Only about 5% of people are doing half of the spending!It is even more critical to know which areas are the ones where people are falling sick even after getting timely care. What is making them come back every time? Do they need a community resource to work on that problem? With Big Data, we can find correlations we had never seen, answer questions we didn’t know existed, and more importantly, see the bigger picture.We can bring data from multiple sources together and make lives healthier. Today clinicians don’t have to restrict themselves just to clinical or claims data, they can now integrate pharmacy, immunization, ADT, and others to get real-time information.

2. Accuracy that was never achieved before, with Big Data it is for everyone to meet.

The biggest advantage of having Big data is that we can now meet the accuracy we have always desired. When you go to a doctor with an issue you are facing, chances are that the medicine he/she will prescribe you is a result of Big Data analytics. We can now accurately cure people because with data-sharing arrangements we have had major breakthroughs in pharma. For instance, the discovery of desipramine as a cure for types of lung cancer besides being an antidepressant. The initiative of precision medicine is now possible because of the success in the field of Big Data. In his famous speech on precision medicine, Former President Obama said,

Doctors have always recognized that every patient is unique, and doctors have always tried to tailor their treatments as best they can to individuals. You can match a blood transfusion to a blood type — that was an important discovery. What if matching a cancer cure to our genetic code was just as easy, just as standard? What if figuring out the right dose of medicine was as simple as taking our temperature?

Big Data has the capability to deliver advanced analytics on the data of millions and billions which itself is a limitless possibility. We can make way for new discoveries, relations, and characteristics and each possibility translated to endless opportunities of making a better health care.

3. Running the practices efficiently

With huge data backing a system, the possibilities can be many. Firstly, imagine a practitioner uses a ‘best practice’ for one of the procedure out of many ways. It can be picked up by data as an outlier and made a standard for future cases. Secondly, it can be fed into Machine Learning algorithms and Artificial Intelligence can be leveraged for the automation of many operational activities and finding out important correlations.

All of this is good, but what next? Getting the priorities right.

Amazon, Google, Uber, and others have revolutionized their respective spaces with a data-first approach. That is, they first gathered the data on their consumers and based on that, they innovated. Similarly, healthcare needs to get its priorities right. As a patient-centered space, we need to understand the importance of bringing patients to the heart of operations. We need applications based on the requirement not what a “good” vendor was able to create.

A solid foundation of data layer should be the first step towards the value-based world. As we cannot improve what we cannot measure! And healthcare needs to know where innovation is most needed. The first priority should be data integration. No matter how hackneyed it might sound, but it is quite fundamental and frankly not a lot of people have their data right!

It is a major concern for all of us if most of the people are working without the retrospection of what went right or what went wrong, then the scope of improvement in the future is bleak.

Data needs to tell us:

  1. What is the status of my population health?
  2. What are my expenditure trends?
  3. What are the lowest hanging fruits for me?
  4. How can I capture these opportunities?

What is the promise for the future?

Big Data in healthcare has a huge promise for everyone. Patients don’t have to worry about their care procedures’ accuracy. They can easily stay connected. Care teams don’t have to bother about getting contextualized information. They can just focus on what they do best and leave all the rest to data.

30 years ago we didn’t imagine a lot of things we are doing today. And that is the difference! We need to start imagining the future. We are not here just to cure today, we are here to make sure our future generations are healthier and happier. Because some 20 years ago the generation before them was focused with a 20-year long vision for health care.

To know more about how a unified healthcare data platform can deliver the right information at the right time, get a demo.

Join Dr. Paul Grundy, the ‘Godfather’ of Patient-Centered Medical Home revolution and Dr. David Nace, CMO at Innovaccer for a webinar on “Using Teams to Drive Value: A Successful Approach to Population Health” on Tuesday, October 30, 2018, 10 AM PT / 12 Noon CT / 1 PM ET. Register here.

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Abhinav Shashank

Abhinav Shashank

Chief Executive Officer & Co-Founder - Innovaccer.

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