The Use of Big Data in Healthcare
Changes in software are making it easier for healthcare professionals to extrapolate and use findings from big data distribution. Professionals should expect big data to be different from EMR information and learn how best to use and manipulate the data. Specifics on the use of big data in Healthcare Made Simple: Where it Stands Today and Where It’s Going, helps hospitals and providers understand the structure of big data. Learn about big data, how to manipulate it and current examples of implementation.
How Can Big Data Impact the Practice?
Big data is exciting as to its potential impact on the quality of data gathered and the way it can advance patient care. Dr. Russell Richmond, big data analytics and healthcare informatics expert and consultant at McKinsey & Company, said:
“More information yields more granular diagnosis, which creates the opportunity for more precise treatment.”
He believes that providers will benefit by being able to deliver more personalized and precise care with more details on patients and populations. There is also the opportunity to identify high-risk patients prior to the start of a health issue.
What to Know When Planning to Use Big Data
Big data is different than data in relational databases. Within the current system, know that:
There is little structure.
- Do not expect a table-and-column structure. Data is stored in a huge and less organized file system. Data is stored across numerous data nodes in a hierarchical form of directories in the Hadoop Distributed File System.
The data is raw.
- Expect little cleansing or application of business rules. Typically data is not altered until it is as close as possible to the application layer.
The data is cheaper.
- It is less expensive to own and use a big data system as compared to a traditional relational database. Big data systems do not require much in the way of design work and are relatively easy to maintain.
There is no traditional schema.
- Query languages are more complex but new data tools like SparkSQL make it easier to use conventional SQL.
Big data is cheaper to own and use but can be less user-friendly. As we've seen prices come down when it comes to upping the amount of storage that a computer can hold, the same is also true on a more massive scale, precisely like the data that the healthcare industry is gathering on a daily basis. This is to be expected with innovative systems and continued progress that will make querying and transformation of data easier for everyone involved, whether it is the healthcare professionals pulling up data or patients as they become more tech savvy and access their own information in a healthcare portal.
Examples of Big Data in Use within the Industry
The healthcare industry has been implementing big data already in a number of instances. Real use of big data in healthcare is already underway. In fact, the true potentials are only just beginning to emerge and as the years go by, more and more revelations on possibilities will be uncovered.
- Explorys uses big data to offer tools for at-risk patient population management, cost of care measurement and clinical support. They can offer solutions from their database that aid clinicians in analyzing data from disparate sources, i.e. EHRs and payor financial data. Data mining with their analytics tools offers information on variations among patients and treatments and how they influence outcomes. Improvements of treatment plans are possible with the additional input.
- Propeller Health focuses on asthma management. Providers are able to identify at-risk asthma patients prior to an attack. The asthma inhalers are equipped with sensors, alongside mobile applications and analytics to alert providers to a changing status. The Propeller Health app offers providers information on each patient’s inhaler use, allowing them the ability to predict and prevent attacks. Propeller Health cares about the collection of air quality data and has partnered with Louisville, Kentucky and Walgreens to gather information regarding asthma exacerbations and identify potential risk factors. The intriguing potential of big data is in the way it can predict and respond to trends in populations and areas.
- InterSystems’ HealthShare Active Analytics helps providers improve cost savings and health management outcomes. Rhode Island partnered with InterSystems to collect and analyze patient data statewide. They discovered that 10% of major lab tests performed were unnecessary. This awareness allows Rhode Island to reduce spending and improve quality of care.
There is a $3 trillion healthcare industry that can benefit from improvements in healthcare management and patient outcomes. Big data may be the way to ensure that hospitals have adequate resources based on their patient populations. Big data potentially can reduce unnecessary expense while improving patient care. Use of the raw data and improvements in software will allow providers to generate solutions to the questions of the future.
This is not something to fear, but it can be truly overwhelming, especially in the beginning to get to know. Surrounding yourself with people that either know or are willing to learn will help to bridge the gap and implement the changes withing the industry to make the leaps forward.