A human body contains nearly  150Tr gigabytes of information, an equivalent of 75Bn fully-loaded 16GB Apple iPads. Multiply that to number of people visiting hospitals for different health conditions, what does that mount to?

Healthcare industry has been generating large amounts of data for mainly three reasons:-

  • Keeping regular records,
  • Compliance & regulatory requirements, and
  • Patient care.

This data is spread among multiple

  1. Healthcare systems
  2. Health insurers
  3. Researchers
  4. Government entities

And after decades of technological laggard, the field of medicine has begun to acclimatize to today’s digital data age, namely to DATA ANALYTICS.

Data Analytics provides tools to healthcare that are driven to “Accumulate, Arrange, Analyze, and Assimilate” the large volume of unstructured data, produced during daily healthcare operations, ranging from complex MRI’s to daily clinical prescriptions.

It enables health care experts to see complex data in simpler ways, so decisions can be made with the help of data, and not by ‘intuition’, ‘gut feel’ or ‘expert opinion’.

Big Fight with ‘Big Data’: Improving Nationwide Healthcare with Data Analytics

The integration of Data Analytics into healthcare is helping countries to overcome obstacles that have been shunting their growth when it came to providing right facilities to citizens.

Take, for example, USA.

The healthcare expenditures of United States are the highest when compared to other developed countries, at 15.3% of GDP, and still it doesn’t seem to improve health outcomes.

Researchers found that the USA does not spend healthcare money efficiently, and argued that the rising cost of medical care and health insurance is impacting the livelihood of many Americans; and this is where Data Analytics could work miracles.

Global Institute suggests that if US healthcare were to use Data Analytics effectively, the sector could create more than $300 billion in value every year, two-thirds of the value would be in the form of reducing US healthcare expenditure.

While on the other hand experts in UK are of belief that an efficient Data analysis can cure there ailing NHS (National Health Service) that has been under pressure since it began in 1948.  Around 8.4% of the UK’s gross domestic product (i.e., approximately 0.18984 trillion GBP) is spent on healthcare. (Source: NHS UK)

As the life expectancy in UK has gone up, per person visit to hospitals has increased too, causing an NHS overload with 243 million NHS appointments annually (over 460 appointments each minute). But by implementing data analytics into healthcare, as experts suggest, a proper track and record of individuals could be maintained that will be of help to health care personals in consulting proper medications, diet plans, exercises, and therapies too.  

But India seems to be lagging behind the developed nations when it comes to implementing Data Analytics in healthcare. The country is expected to be an industry worth $280 billion by the year 2020, but it’s still not excused by ill management that it has been facing for decades.

There is a 24-38% shortfall in the availability of medical personnel at primary health centres and sub centres across India, according to the latest audit.

There is a 24-38% shortfall in the availability of medical personnel at primary health centres and sub centres across India, according to the latest audit.

The cost of healthcare in India is increasing at 20% every year. There is a shortage of 1.5 million doctors and 2 million Hospital beds. And only around 5% of the middle class have health coverage.

India definitely needs a ‘Big’ data shock to wake up from its ‘unhealthy’ slumber and catch up with the pace of developing nations in terms of healthcare

A Little Taste of Own Medicine: Treating ‘Uncomplaining DNA with Data Analytics

Other than helping countries to improve upon their healthcare facilities, Data Analytics is also helping medical researchers to come up with solutions to fight diseases and overcoming complex medical research problems.

Take, for instance, the field of human genetic research. The cost to sequence the human genome (made up of 30,000 to 35,000 genes) is rapidly decreasing with the development of high-throughput sequencing technology.

For another example, take Cancer research, as it’s in close contact with genome sequencing. Researchers can now examine tumor samples in bio-banks that are linked up with patient treatment records. Using this data, they can see things like how certain mutations and cancer proteins interact with different treatments, and can find trends that will lead to better patient outcomes.

How Data Analytics Actually Works in General Healthcare

But how Data Analytics is actually applied to the field of Health sector?  To answer that, we have to first take note of how medical personnel had been working until Data Analytics emerged on the scene

Physicians have traditionally used their judgment when making treatment decisions, while  medical research till now have generally focused on the investigation of disease states based on the changes in physiology in the form of a confined view of certain singular modality of data. Although this approach to understanding diseases is essential, research concentrating on such small sample size couldn’t trace the variations and inter-connectedness that defines the real nature of a medical condition.

On the other hand, we have already experienced a decade of progress in digitizing medical records, as pharmaceutical companies and other organizations aggregate years of research and development data in electronic databases.

What Data Analytics actually does is that it mines this data, and predicts what treatments are most effective for particular conditions, identifies patterns related to drug side effects or hospital readmission, and gains other important information that can help patients, and hence reduce costs.

And to achieve such magical feats, Data scientists need to have hold upon many sources, like:-

  • Clinical data (physician’s prescriptions, medical imaging, laboratory, pharmacy, insurance)
  • Patient’s data in electronic patient records (EPRs)
  • Machine generated data( CAT scans, MRI)
  • Data that show patient’s behavior and sentiments, from social media platforms
  1. Twitter feeds
  2. Blogs
  3. Facebook status updates
  4. Web pages
  • Wearable health monitoring gadgets

After Data scientists are done with data collection, cleaning, and at last with its analysis, there are multiple ways in which individuals doctors or healthcare organizations could benefit from, like:

  •  Allotting the right number of doctors for the right shifts of day, saving unnecessary labor costs
  • Regular monitoring of patient health with having them to visit hospitals regularly with help of wearable and other health apps.
  • Prescribing exact medication to the individuals.
  • Avoiding overuse and abuse of drugs.
Benefits Of Integrating Data Analytics into Healthcare

Data Analytics can help boost healthcare in following ways:

1. Efficient Utilization of Medical Resources

A well connected  patient database, consisting of previous health records of multiple patients, can help doctors to come up with a more certain diagnosis.

2. Visualizing  Clinical Database

Data visualization of big and complicated hospitals can help even those healthcare personals who are not that techno savvy, come up with better monitoring techniques.

3. Programming Appointments

This one is the top most concern for health care teams around the world. Giving appointment timings that are suitable for both patients and the doctors is always something that plays a vital role in proper healing of patients. But with regular monitoring of patients health conditions by their wearables, like smartwatches and smart bands, it would be easier for hospitals and clinics to know the exact time a patient could need a certain kind of health examination.

4. Creating Health Alerts

Continuous monitoring of people health through IOT devices and sentimental analysis could help health experts predict, and hence in return alert, about probable health problems.

5. Research & Study

Big data helps doctors and researchers connect  dots and understand pattern of occurring or recurring of certain kinds of diseases. As experts could analyse various aspects like, geography, food habits, lifestyle, etc., of many people to understand how a particular disease could be handled

Summing It Up!

The focus of healthcare has shifted from the acute hospitals towards preventive and post-illness care of the community in recent years. With Data analytics, healthcare organisations have the ability to establish a platform to let multiple hospitals exchange information, leading to a 360 view of their patients, so doctors could diagnose them more accurately than ever.

The demand for such tools is also spurred by a shift to evidence-based medicine as opposed to subjective clinical decisions.  Such advance technological measures help health care organization to determine and implement appropriate treatment paths for patients, support clinical improvement, monitor the safety of healthcare systems, assure managerial control, and promote health system accountability to the public.

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