Big Data in Healthcare: Examples, Advantages and Disadvantages


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Big Data in Healthcare

Big data solutions usage is permeating every facet of human activity. The healthcare is rapidly adopting the use of big data apps significantly faster than other industries. The asset management is another sector that is fast adopting the use of big data in fund management. Big data solutions made for the healthcare industry are benefitting both physicians and patients. Big data applications for healthcare industry have enormous capabilities in making medical care better planned, preventive, personalized, and affordable. Using smart technologies, working with data analytics help reduce the laborious work and error associated with manual data handling, and  healthcare workers can then focus on forecast and avert infection outbreaks, decrease death rates, cut operations expenses, and improve patient outcomes.

Hospitals and other healthcare companies are expending so much on the smart technology that makes use of algorithms to predict one's future healthcare challenges by analyzing their previous behavours and visits to the doctors and clinics.

Significant Characteristics of Big Data in Healthcare

  • Size: Big Data technology handles large data quantity. Healthcare services involve huge data. So to create value-based and personalized healthcare services, hospitals need customized solutions operating huge quantities of data.
  • Speed: Collection, processing and management of data is time consuming. But with customized software solutions, collection, processing collected data is done with ease and speedily.
  • Sources: Medical statistics are usually from different sources in different formats. To perform predictive analytics on these data, customized solutions handle data from numerous sources in varied forms.
  • Staidness: to downsize the danger of data deception, the customized ML-based solutions need well-organized and standardized data input.
  • Accuracy
  • Reliability

Big data applications have transformed the healthcare industry landscape completely especially in the areas of electronic health records (EHR), telemedicine, medical imaging, surgery robots, etc. New digital solutions are implementing big data technologies and operating massive data input to open new horizons for the healthcare market. Predictive analytics technologies can optimize cost, reduce time spent on paperwork, provide accurate and reliable data records, and initiate the creation of new big data products.

Read also: Best 13 Statistical Software for Medical Research

Advantages and Disadvantages of Big Data in Healthcare

Benefits of Big Data Analytics in Healthcare Industry

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The benefits of big data in healthcare industry are evident in the practical examples of application of big data in healthcare

Predictive medicine

Big data algorithms are structured to assist doctors in carrying out more accurate clinical diagnostics. The customized solutions can process    large data working with prognostic analytics, and predictive modeling techniques. Big data analytics helps to detect diseases at the early stage and make suggestion for the right treatments. Doctors can quickly identify patients who are likely to develop a certain condition, prevent the disease from worsening, and forecast epidemics before they break out. Predictive modeling algorithms can be helpful in diagnosing illnesses like diabetes at their very early stage, or forecasting the possible spread of viruses to avert epidemics.

For example, using genomic data helps in developing a more exact vision of the further progress of cancer. Genomics data are becoming more available, making their accessibility and affordability easier.

Early intervention

High quality healthcare

Fraud detection

Effective management of population health


Telemedicine is the application telecommunication technology in rendering healthcare service remotely. This type of medical service delivery has been around for over 40 your now, but with the revolution in smart technology for online video call, smartphone, mobile apps etc telemedicine is now gaining more prominence in healthcare industry.

 Personal Health data records


Risk management

Medical imaging

In summary, the benefits of big data technologies in healthcare are as follows:

  • Patients’ records can be accessed at a click.
  • Doctors can be able to monitor and consult patients remotely giving doctors less physical examinations and desk work.
  • Reduces waiting time for patients to consult with doctors (ER Visits)
  • Healthcare personnel can receive alert on emergencies and acute medical cases and respond immediately
  • Hospitals can cut costs
  • Efficient healthcare delivery
  • Healthcare delivery becomes available to the general population 

Challenges of Big Data in Healthcare

Big data analytics have been quite helpful in healthcare industries in offering quality and efficient healthcare delivery in the areas of preventing diseases, predicting medical outcome, reducing medical errors, and boosting all aspect of healthcare. Nevertheless, there remain some underlining disadvantages and challenging discouraging healthcare providers from applying big data technologies in their healthcare delivery operations.

Some of the challenging facing the use of big data analytics in healthcare delivery which pose as disadvantages include:

Man Power

Applying big data solutions in healthcare requires special skills, and such kills are scarce. Handling of big data requires the combination of medical, technological and statistical knowledge.


One of the major drawbacks in the application of big data in healthcare industry is the issue of lack of privacy. Application of big data technologies involves monitoring of patient's data, tracking of medical inventory and assets, organizing collected data, and visualization of data on the dashboard and the reports. So visualization of sensitive medical data especially that of the patients creates negative impression of big data as it violets privacy laws. Big data gives doctors unhindered access to a patient's private records from anywhere, and this does not give the patient any freedom. Medical big data experts have said that technology takes ways one's privacy for greater good.   There exist laws relating to medical record privacy, but some of these laws did not capture big data sharing. But then, visualization is very critical for creating images, diagrams, animations to pass medical information in an understandable form.

Quality of Data Input

Big data solutions for healthcare can process and analyze data speedily, but the accuracy and reliability of such information largely depend on the quality of the data that were supplied to them. Where the input data is incorrect the results obtained from customized big data technologies therefore will be misleading which can lead to wrong diagnosis and misapplication of medical treatment. Data are usually gathered from different sources and forms, handling these sensitive personal data is quite challenging. Input data must therefore be standardized, unified, free from duplicates and any form of mistakes. There should be a system that will automatically check and test all prepared data regularly. Healthcare personnel have to be in touch with one another to crosscheck all data while sharing to avoid sharing duplicates or wrong data.

Data Safety

Data security is another challenge in applying big data in healthcare. Big data storage is usually targets of hackers. This endangers the safety of medical data. Healthcare organisations are very much concerned about the safety of patients' sensitive personal data. For this, all healthcare applications must meet the requirement for data security and be HIPAA compliant before they can be deployed for healthcare services.

Replacing Medical Personnel

Application of technology in every sphere of human life is improving the way things are done. These technologies are are also posing some threat to world of works. Robotics are replacing human labour. In same manner, customized solutions like big data could take over the jobs of medical personnel. Although big data has not gotten to the point where it can auto-run itself and lacks personal touch of doctors, but as technologies advance, robotics can begin to perform some, functions of doctors and other healthcare providers. Some experts say that the growth of big data could potentially undermine doctors and having patients turn to technology for medical solutions instead of patronizing licensed human doctors. It is a fact that big data cannot be avoided in healthcare, as more hospitals and healthcare companies continue to make much investment in big data technology. But then, its disadvantage as regards to taking over the jobs of medical personnel need to be taken into consideration.

Read also: Top 25 Medical Inventory Management Software

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