Healthcare organizations garner humungous amount of data which includes both structured and unstructured data. The Electronic Health Record(EHR) provides structured data of a patient’s history of health conditions and prescriptions while the data collected from e-mail, social networking sites, doctors’ clinical notes are unstructured data.
Some facts and figures
- In 2012 worldwide digital health care data was estimated to be equal to 500 peta bytes and is expected to reach 25,000 peta bytes in 2020
- By 2025 between 100 million and 2 billion human genomes could have been sequenced. The data storage demands 40 exabytes. Storing and processing genomes data will exceed the computing challenges of running You Tube and Twitter
- Indian healthcare sector is growing at a 15 per cent CAGR to reach US$ 158.2 billion by 2017.
- Anecdotal studies indicate that the Indian healthcare sector is expected to contribute around 12 per cent of the big data generated in India. It is expected that this number will grow to 25 per cent of the overall data generated by 2017
- In terms of healthcare, this sector in India contributes about 20 percent of the volume of data generated in India
- In USA, health care spending is $2.2 trillion each year which accounts for about 17% of US GDP
- The US has not seen an increase in life expectancy to match its huge outlay on health care
- Over $30 billion was spent on unnecessary hospital admissions and re-hospitalization within 30 days of discharge
- The major classes of drugs only work in 30-60% of the people they are administered to
- US OMB estimated that $250 billion to $325 billion is spent annually on unwarranted care
Analytics can help Health care organizations to :-
Reduce costs
The health care services are rendered with a price and the business model is more focused on volume rather than value. As a result, there are repeat visits to healthcare providers and readmissions after discharge which has unnecessary cost implications on patients. Analytics can come up with a model where the provider would be paid for the value delivered based on the performance, determined by result instead of volume.
Improve Outcomes
A huge pile of data collected from disparate sources is an asset to healthcare organizations and analytics can help organizations to effectively mine this data to improve health outcomes. Information obtained from expert opinions, patient characteristics, research papers, clinical trial reports can help physicians make right intervention to right patient at the point of care.
Minimize Readmissions
Advanced analytics can play a significant role to minimize readmissions on improving after-treatment care by gaining insights into treatment trends and causes for readmission and designing interventions. The providers can give a proper regimen for the patients to follow post discharge.
Empower Patients
People become more responsible for their own health if they are sensitized with more relevant and timely data-driven insights obtained through the use of analytics. For instance, a monitoring system is available that monitors a medication prescribed for diabetes patients at prescribed intervals and sends text messages or makes phone calls as a therapeutic reminder.
Conclusion
Health care is a data-rich domain. Standard medical practice is moving from relatively ad-hoc and subjective decision making to evidence based healthcare and data with more complexities keep evolving. Health care data is rarely standardized, often fragmented or generated in legacy IT systems with incompatible formats. Real time Big data analytics is a key requirement in healthcare. Data mustered from all the disparate sources should be integrated to build a solid information foundation from which to draw both insights and foresights. If deployed properly, advanced analytics can play a significant role in reducing the inefficiencies and providing healthcare organizations with insights to manage their business more proactively and profitably.
