Big Data helps to simplify, manage, analyse and leverage data across many industries especially in the healthcare sector. Big Data Analytics can help to reduce medical costs, predict future pandemics, avoid preventable diseases and improve the overall quality of life. It also helps to organise and hold in all the data that is obtainable in healthcare which traditional electronic methods cannot do.
Big data refers to various large and complex data that are difficult to analyse and manage with traditional software or hardware. In medicine and healthcare, big data analytics allows for easy analysis of large datasets from thousands of patients, identifying correlations between various datasets and developing predictive models using data mining techniques. Big data analytics in medicine and healthcare consolidates information from several scientific areas such as bioinformatics, medical imaging, sensor informatics, medical informatics and health informatics.
There are many ways in which Big Data helps to make the healthcare system a lot easier.
Electronic Health Records (EHR)
Every patient has their own digital record which includes demographics, medical history, allergies, laboratory test results, scans, previous prescriptions and medications etc. These records can be easily shared with the corresponding healthcare provider. Every record has a file that can be easily modified, allowing doctors to add necessary information over time with no paperwork and no danger of data replication. The Digital Health ID was established to help doctors all over India to be able to access patient files with ease.
Real-time alerting and remote patient management
Through various tracking devices, any kinds of changes in the patient’s vitals will be immediately relayed to the respective healthcare professional who can then formulate a solution to help the patient out.
Smart devices and patient engagement
Many tracking devices monitor the step count, heartbeat rate, sleeping activity etc on a continuous basis. All this vital information helps to identify potential health risks lurking. Patients are directly involved in the monitoring of their own health, and incentives from health insurance can urge them to lead a healthy lifestyle
The use of big data in healthcare allows for strategic planning thanks to better insights into people’s motivations. Care managers can analyze hospital visit patterns among different demographic groups and identify what factors discourage people from taking up treatment. Big data can also help with assigning the necessary staff to various patients at a given point in time.
Understand and maybe cure several diseases
Medical researchers can use data on treatment plans and recovery rates of cancer patients in order to find which treatments work the best. Researchers can examine tumor samples from biobanks and study how certain mutations and cancer proteins interact with different therapeutic drugs.
Telemedicine has come into full force with the arrival of online video conferences, smartphones, wireless devices, and wearables. Clinicians use telemedicine to provide personalized treatment plans and prevent hospitalization or re-admission. Such use of healthcare data analytics can be linked to the use of predictive analytics. It allows clinicians to predict acute medical events in advance and prevent deterioration of patient’s conditions. Through telemedicine platforms, patients can consult doctors from the ease of their homes.
Understanding Medical Imaging
Big data can develop algorithms by analyzing hundreds of thousands of images that could help identify specific patterns in the pixels. Instead of decoding the images, radiologists can analyze the outcomes of the algorithms thus providing a more accurate diagnosis.
Efficient management of hospital personnel
A cohesive, engaged workforce is required to ensure that the best patient care is provided. With big data tools in healthcare, staff management activities can be organised and streamlined for more efficiency. By working with the right analytics, medical institutions can optimize staffing while taking care of operating room demands, streamlining patient care as a result.
Improving supply chain management
Descriptive and predictive analytics models can enhance decisions for negotiating pricing, reducing the variation in supplies, and optimizing the ordering process as a whole. Through this medical institutions can deliver the best treatment to patients without any roadblocks.
Developing new therapies
Big data analysis in healthcare has the power to assist in new therapy and innovative drug discoveries. Utilizing a mix of historical, real-time, predictive metrics and data visualization techniques, healthcare experts can identify potential strengths and weaknesses in trials or processes.
Big data analytics in medicine and healthcare integrates, explores and analyses large amounts of complex heterogeneous data of different nature: biomedical data, experimental data, electronic health records data and social media data. This process has very promising prospects and can thus help to increase the efficiency of various parts of healthcare organizations.