Big Data is still in its early stage and is already changing the course of business sector all across the globe. Big Data can be described as a set of electronic data so complex and large in volume that it is very difficult to manage it using traditional software or hardware. It can neither be easily managed with basic data management tools. Big Data Analytics has enormous potential to influence healthcare industry positively by meliorating the quality of care, reducing costs and avoiding preventable deaths. On a fundamental level, implementing Big Data in an organization makes it more productive, efficient and cost-friendly.
The Indian healthcare industry has already started using Hospital Information Systems (HIS) and Electronic Health Records (EHR) to make their organization more profitable and productive. The industry is engaged in producing zettabytes of data every day by capturing exuberant amount of patient care records, diagnostic tests, prescriptions, insurance claims, monitoring vital signs, and most importantly the medical research information. The growth of these records will be explosive in the coming couple of years, which makes Big Data intervention in the healthcare industry utterly crucial.
Big Data Analytics in healthcare segment amalgamates clinical innovation and technology. This promising technology supports an array of healthcare functions to improve services and handle problems of the healthcare sector. It has introduced new ways for organizations to formulate actionable insights, boost up outcomes, reduce time to value and organize their future vision. The evaluated results can be very fruitful to enhance decision making capacity of the management. Big Data Analytics in healthcare can significantly lift the bar of different variants in the sector.
There are many new analytic platforms which enable automatic customer profiling by capturing very localized data of supply and demand thus enabling big data analytics on individual customers of any area. These analytics platforms also capture the essence of seasonality including Category Stocking thus helping pharmacies to stock medicines and other healthcare products well in advance which helps in keeping a track of freshness quotient.
These technologies provide POS solution to pharmacies to streamline the payment process, both online and offline. Their ERP solution is linked to the inventory of the pharmacy, enabling real-time availability of medicines and OTC products. The ERP solution uses the localized demand analytics data helping them in predictive inventory management for greater savings and better stock management. A strong consumer focused app not only allows consumers to buy medicines but also create a transparency by allowing them to know their medicine needs better – side effects, salt details, dosage limits, cheaper substitutes and complimentary OTC products to buy along. The recommendation algorithm study, the browsing behavior and buying pattern to suggest products most needed by the consumers.
Pharmacy sector, specifically, is always overwhelmed with data complexity. Data analytics can help pharmacy sector align manufacturer’s data requirements with its business needs, pharmacy capabilities, and therapy category. Making use of Big Data in this sector help you get efficient data quality management and better business utilization.
With increasing supply of information, data analytics should take the key role in any speciality pharmacy and other healthcare wings. Tying analytics with this sector allows reporting on demand. Manufacturers, providers, and payers can use this data to improve their understanding of obstacles and gaze opportunities to improve healthcare.
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