There is a plethora of healthcare data that is available today, and it only continues to pile up making it difficult for us to use that unstructured data to make any decisions. The ultimate goal of any healthcare organization would be to provide quality treatment at a reasonable cost for its patients. However, that has been a big challenge and hence the need for data science in healthcare.
Let me share some alarming facts with you about healthcare which calls out why healthcare needs data science.
- About 5% of adult patients are misdiagnosed each year in the US. This totals over 12 million people
- By 2021, spending on health care each year in the US is expected to be $4.8 trillion
- 80% of data is unstructured and stored in various forms such as labs, results, medical transcripts and images. Large amounts of meaningless data
- India’s doctor-to-patient ratio is significantly lower than the World Health Organizations average of 2.5 doctors for every 1000 people
- One of the world’s major diseases – Diabetes mellitus is growing rapidly in number and has affected an estimate of 143 million people worldwide
Hence the application of data science in hospitals has extremely positive and lifesaving outcomes. Hospitals can work on multiple health data science projects to make effective operational decisions using data analytics tools. Needless to forget that insurance company to play a critical role in making this happen.
To apply Data science in Healthcare you need to go through the Intellipaat Data Scientist certification course that places a high focus on healthcare data. By applying data science in health insurance, you will be able to detect fraud, optimize cost, risk assessment, claims prediction and many more. Data Science and medicine are working for a hand in glove to aid in drug discovery, genetic disease exploration and computerizing medical records.
Data Science medicine also helps in looking into the past records of the patients and providing predictive medicines, thus improving the quality of life for patients.
There are various biomedical data too that impacts how data science works in the space of healthcare and medicine. So, what is Biomedical data? It is any data related to or involving biological, medical or physical science. Some examples of biomedical data are patient’s information, laboratory data, genetic data and like-wise.
Going one more step further, Biomedical Data Science which is an interdisciplinary approach to study the effective use of biomedical data for scientific inquiry that helps in problem-solving and making efficient data-driven decisions to improve human health.
With very sensitive information available at hand, of course with the patient’s consent, there is a humongous amount of data that is available to apply big data in biomedical research which in turn will help in providing timely and appropriate medical care for the needy patients. Applying big data analytics in biomedical research has had its own challenges, to mention the least, storing, managing and analyzing huge datasets.
Artificial intelligence, along with some data mining tools has been able to help in these challenges. Infrastructures involving parallel computing and cloud computing have played an important role in biomedical data analysis.
So, how is data science transforming healthcare? Why do hospitals need data science? Here’s why:
1. Predictive and preventive medicine will rise rapidly
2. Improved staffing by analyzing patients visit patterns thus enhancing operational efficiency
3. Appropriate maintenance of patients records through Electronic Health Records(EHRs)
4. With the Internet of Things connecting devices, medicines and products will link a patient’s wellness to their lifestyles
5. Optimization of Robots. From being programmed to delivering supplies and samples, robotic surgeries are also catching pace in recent times
6. Enhancing patients’ engagements through devices that monitor their health and provide real-time alerts through cloud data when in the hospital
7. Reduce fraud cases and help patients in claiming insurance through a streamlined process
8. Doctors will become more tech savvy and will have access to more data to help them diagnose the disease and provide appropriate treatment to patients
9. Will help Pharma R&D to maybe find the cure for cancer or Ebola patients or any other fatal diseases
10. Data integration across areas in the healthcare industry will boost the quality of healthcare and maintain high standards of service.
To conclude, the benefits of big data in healthcare is life changing. However, for starters, hospitals need to maintain all patient’s records – doctor’s notes, prescriptions, reports, tests results, and discharge summaries so that they may be used with efficiency and ease.
For these and other necessary reasons, healthcare providers must have good data scientists on board and leverage Big data technology to help the quality of human life.