Top 9 Ways Big Data Analytics is Changing Healthcare

Top 9 Ways Big Data Analytics Changing Healthcare

Big Data analytics in healthcare has pivoted to reach all new heights by touching more hardline providers who resisted changing the traditional way of making clinical judgments in the past. With collaboration becoming a prominent practice, it is increasingly hard for silo mentality to thrive. Thanks to big data analytics in healthcare the industry is on a path to change.

That said, an untold volume of hard data with fluctuating complexity and veracity is being produced every second. This heap of data with the potential to alter the course of the healthcare industry can be captured with cutting-edge healthcare data analytics applications. In a pursuit to carve out a niche in the healthcare markets, more providers are turning to Big Data and leveraging latest practices and applications of Big Data analytics in healthcare.

How is Big Data Analytics Changing the Healthcare?

After lagging other industries, healthcare is finally seeing big and exciting changes especially in the use of Big Data. This buzzword has brought a paradigm shift to such an extent that payors, single hospitals, and pharmaceutical companies are relying on a growing pool of health data to effectively communicate findings. It has enabled the healthcare industry to work with the uneven fabric of impediments and opportunities at an extraordinary rate. Here are 10 ways big data analytics is changing healthcare -

  1. Predicting Cardiovascular Diseases and Mitigating Mortality Rate

    Predicting Cardiovascular Diseases

    It is estimated by American Heart Association (AHA) that on an average, 2000 people in the US die every day due to cardiovascular diseases, and the startling death rate is attributed to an unhealthy lifestyle. By using remote monitoring tools and smartphone apps that exploit Big Data for cardiac monitoring, it is possible to see a gradual decrease in the mortality rate. Big Data has eliminated the need for cardiac monitoring at a healthcare facility by pairing patient's smartphone apps with single-lead EEG for efficient analysis of pulse data. Wearable adhesive patches are attached to the skin to remotely sense and transmit the information to a monitoring app. Since it is worn under the clothing it does not come in the way of mobility or other functions. The information collected by such devices can assist medical personnel to expediently respond in the event of a cardiac emergency.

  2. Diversifying the Role of CIO

    Diversifying the Role of CIO

    Until the recent past, the Chief Information Officer (CIO) was rarely needed in the healthcare industry. However, today, their role in invaluable thanks to the sprouting of vendor relationships and infrastructure development in healthcare.

    Big Data is redefining the process of collection, storage, and sharing of medical data so much so that CIOs are expected to become equal participants to the change. In an online poll, over 80% of CIOs admitted that their new responsibilities are centered around innovation and transformation overhaul in the healthcare industry.

  3. Fueling the Growth of Healthcare Data Pool

    Fueling the Growth of Healthcare Data Pool

    Digitization of healthcare data is the next big change to hit healthcare industry and Big Data is the driving force behind it. Medical records, medical imagery, and screening results are moved into the Cloud storage so that this enormous cache of medical data can be conveniently shared between professionals across the medical community for diagnosis, academic, and research purposes.

    Besides accelerating patient care, digitization of medical data can support the design and development of advanced surgical equipment. Today, predictive algorithm and machine learning are empowering healthcare industry to handle massive data pools with utmost simplicity. This is achieved by analyzing demographic data to identify specific patterns. However, without Big Data analytics and Artificial Intelligence (AI), it would have taken years of painstaking research for results to materialize.

  4. Enabling Advanced Research and Analysis of Patient Cases

    Research Analysis of Patient Cases

    Using predictive technologies along with Big Data can enable prediction of data points. By fusing medical records with predictive learning system, the artificial intelligence can be used as a prognosis tool to predict the high-risk group that are more vulnerable to sickness and the geographic areas that require scrutiny and preventive care to suppress health problems from becoming an outbreak.

    Predictive technology powered by Big Data can perform analysis at speeds that humans can't keep up. With speedy and early detection of medical conditions, the course of the healthcare industry can be rewritten one at a time.

  5. Improving Patient Wellness with Smart Gadgets

    Improving Patient Wellness with Smart Gadgets

    Wearable devices are becoming a boon for patients because it is compact and convenient against driving to a diagnostic facility and being strapped to scanning machines. From tracking pulse rate to monitoring calories there are wearable gadgets for a gamut of purposes that are powered by Big Data. With Big Data analytics in healthcare, your physician can have access to health records in an instant. Further, the analytics data coupled with prediction tool can help to identify medical conditions (if any) before it becomes an emergency.

  6. Personalizing Medication and Delivery Model

    Personalizing Medication and Delivery Model

    The best form of treatment is to have medications personalized by considering the patient's lifestyle, genetic endowment, and provenance. This makes the medication most effective against the patient's medical condition. By using Big Data analytics, it is possible to create a bespoke treatment plan and delivery model for a speedier recovery. The success story based on this approach is one where data sharing between pharmaceutical companies resulted in the discovery of a cure for certain types of lung cancer.

  7. Improving the Follow-up Care

    Improving the Follow-up Care

    Preventing lapse in treatment is possible with Big Data because its algorithm can predict if the patient belongs to a high-risk group with utmost accuracy. Using intelligent data, physicians can recommend an ideal medication and follow-up plan. The Big Data analytics can also be used to analyze the sleep pattern so that when irregularities are detected the doctor can be notified in advance. With a higher volume and quality of data, it is easier to diagnose and recommend follow-up care.

  8. Eliminating Silo Mentality in Healthcare Organization

    Eliminating Silo Mentality in Healthcare Organization

    To move in the right direction, it is important to have a unified view of the healthcare data and statistics rather than handling individual cases in isolation. This is made into reality through increased collaboration. Big Data analytics in the healthcare industry can facilitate evaluation of thousands of documented medical cases across a spectrum of classifications. With an enormous pool of relevant medical data, it is easier to draw an effective comparison and make an accurate clinical judgment. With the growth of Big Data analytics, physicians can consider a customized treatment plan based on the patient information as well as other medical cases with similar conditions.

  9. Successful Partnership between Apple and IBM on Health Cloud Analytics Services

    Health Cloud Analytics Services

    In 2014 the global tech giants Apple Inc. and IBM joined hands to combat challenges associated with the compartmentalized information. In 4 years, the collaboration has transpired into a sophisticated system that had successfully fueled the research to tackle medical conditions by leveraging the Big Data analytics in healthcare.

    The ongoing development in this system has already brought out more powerful medical insights for exploring new frontiers based on ethnicity, body types, lifestyle, and much more from millions of users. In this advanced medical system, Apple device users can share the medical data on IBM Watson Health Cloud analytics services. The objective behind this collaboration is to collect biometric data and discover fresh medical insights.

Big Data Analytics is Turning Healthcare from Reactive Care to Preventive Care System

Many healthcare providers have already sprung into action for using Big Data analytics as a tool to overhaul the healthcare industry and their numbers are on the rise. The number of healthcare providers using Big Data Analytics is estimated to grow by a whopping 70% by 2020.

However, for a time-constrained industry and society, Big Data analytics is an inevitable reality that is vigorously reforming the traditional healthcare by spurring patients to consider proactive care for a healthier living. And for providers, It boils down to choosing a qualified Big Data analytics company for helping under-served communities to come forward and take advantage of the convenience and quality healthcare service.

Outsource Big Data Analytics Services to Flatworld Solution - Leader in Healthcare Solutions

Big Data is paving way for huge cost savings and quality patient care in the healthcare industry. The phenomenal demand for Big Data is the proof that indicates the willingness of healthcare providers to reframe their mindset. Drawn to Big Data's potential in providing preventive care and eliminating silo mentality it is now the most sought-after requirement globally. This is where Flatworld Solutions come into the picture.

With tremendous expertise in Big Data analytics, we can streamline your practice so that practitioners can stay focused on patient care while being armed with freshest healthcare insights. With 15 years of experience in healthcare services and cutting-edge healthcare BPO technologies, we have fused skill and technology to bring you transformative healthcare services at an affordable rate. Our Big Data solutions are incomplete without reliable and timely support. So why wait?

Contact us and outsource Big Data analytics to FWS because in numerous ways big data analytics is changing healthcare and we believe you should be in front of the change than behind it.

Pricing

Pricing

Pricing is a critical factor to consider before outsourcing. Our pricing model allows you to keep your costs in control.

Case Studies

Case Studies

Read Case Studies to find out how we helped our clients with Healthcare BPO.

Free Quote

Get a Free Quote

Tell us your requirements and get a free quote.