• Post Graduate Program in Analytics and Artificial Intelligence
    Co-created with Coding Ninjas
    4.8 out of 5 by 4610 learners
    12 X industry demand
  • Machine Learning and Deep Learning Prodegree
    Co-created with IBM
    4.7 out of 5 by 2750 learners
    32 X industry demand
  • Post Graduate Program In Data Analytics
    4.7 out of 5 by 3600 learners
    14 X industry demand
  • Data Science Prodegree
    Co-created with KPMG
    4.8 out of 5 by 6071 learners
    16 X industry demand

There are multiple perks to Big Data analytics. Specifically, in the domain of healthcare, Big Data analytics can result in lower care costs, increased transparency to performance, healthier patients, and consumer satisfaction among many other benefits. However, achieving these outcomes with meaningful analytics has already proven to be tough and challenging. What are the major issues slowing down the process and how are they being resolved? We will discuss the top 10 in this article. 
Top 10 Challenges of Big Data Analytics in Healthcare
 

  • Capturing Accurate Data

 
The data being captured for the analysis is ideally expected to be truly clean, well-informed, complete and accurate. But unfortunately, at times, data is often skewed and cannot be used in multiple systems. To solve this critical issue, the health care providers need to redesign their data capture routines, prioritise valuable data and train their clinicians to recognise the value of relevant information. 
 

  • Storage Bandwidth

 
Typically, conventional on-premises data centres fail to deliver as the volume of healthcare data once reaches certain limits. However, the advancement in cloud storage technology is offering a potential solution to this problem through its added capacities of information storage. 
 

  • Cleaning Processes

 
Currently, the industry relies on manual data cleaning processes which takes huge amounts of time to complete. However, recently introduced scrubbing tools for cleaning data have shown promise is resolving this issue. The progress in this sector is expected to result in automated low-cost data cleaning. 
 

  • Security Issues

 
The recurring incidents of hacking, high profile data breach and ransomware etc are posing credibility threats to Big Data solutions for organisations. The recommended solutions for this problem include updated antivirus software, encrypted data and multi-factor authentication to offer minimal risk and protect data.
 

  • Stewardship

 
Data in healthcare is expected to have a shelf life of at least 6 years. For this, there is a need an accurate and up-to-date metadata of details about when, by whom and for what purposes the data was created. The metadata is required for efficient utilisation of the data. A data steward should be assigned to create and maintain meaningful metadata.

  • Querying Accesses

Biggest challenges in querying the data are caused by data silos and interoperability problems. They prevent querying tools from accessing the whole repository of information. Nowadays, SQL is widely being used to explore larger datasets even though such systems require cleaner data to be fully effective.
 

  • Reporting

 
A report that is clear, concise and accessible to the target audience is required to be made after the querying process. The accuracy and reliability of the report depend on the quality and integrity of data.
 

  • Clear Data Visualization

 
For regular clinicians to interpret the information, a clean and engaging data visualization is needed. Organisations use data visualization techniques such as heat maps, scatter plots, pie charts, histogram and more to illustrate data, even without in-depth expertise in analytics.
 

  • Staying Up-to-Date

 
The dynamic nature of healthcare data demands regular updations to keep it relevant. The time interval between each update may vary from seconds to a couple of years for different datasets. It would be challenging to understand the volatility of big data one is handling unless a consistent monitoring process is in place.
 

  • Sharing Data

 
Since most patients do not receive all their care at the same location, sharing data with external partners is an important feature. The challenges of interoperability are being met with emerging strategies such as FHIR and public APIs. 
 Therefore, for efficient and sustainable Big Data ecosystem in healthcare, there are significant challenges are to be solved, for which solutions are being consistently developed in the market. For organisations, it is imperative to stay updated on long-term trends in solving Big Data challenges

For Online Course Enquiries
About Imarticus
Imarticus Learning is India’s leading professional education institute that offers training in Financial Services, Data Analytics & Technology. We’ve successfully transformed careers of over 35,000+ individuals globally through our Certification, Prodegree, and Post Graduate programs offered in association with leading and renowned global organisations in the Financial Services, Data Analytics & Technology domain.
Related course
  • POST GRADUATE PROGRAM
    Post Graduate Program in Analytics and Artificial Intelligence
    Co-created with Coding Ninjas
    Course duration(Weeks)
    28
    Upcoming batches
    1
    Organizations enrolled
    20
    4.8 out of 5 by 4610 learners
    12 X industry demand
    Upcoming Batches
    Date Location Schedule
    23rd-May THANE Weekend
    Date Location Schedule
  • Prodegree
    Machine Learning and Deep Learning Prodegree
    Co-created with IBM
    Course duration(Months)
    4
    Upcoming batches
    1
    Organizations enrolled
    20
    4.7 out of 5 by 2750 learners
    32 X industry demand
    Upcoming Batches
    Date Location Schedule
    None CHENNAI Weekend
    Date Location Schedule
  • Post Graduation
    Post Graduate Program In Data Analytics
    Course duration(Months)
    5
    Upcoming batches
    2
    Organizations enrolled
    20
    4.7 out of 5 by 3600 learners
    14 X industry demand
    Upcoming Batches
    Date Location Schedule
    4th-May THANE Weekday
    Date Location Schedule
    20th-May HYDERABAD Weekday
  • Prodegree
    Data Science Prodegree
    Co-created with KPMG
    Course duration(Months)
    2-4
    Upcoming batches
    5
    Organizations enrolled
    20
    4.8 out of 5 by 6071 learners
    16 X industry demand
    Upcoming Batches
    Date Location Schedule
    4th-Apr GURGAON Weekend
    9th-May THANE Weekend
    23rd-May ONLINE Weekend
    Date Location Schedule
    27th-April CHENNAI Weekend
    23rd-May CHENNAI Weekend