Tag: Big Data In Healthcare

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Predictive Analytics in Healthcare: A Pathway to Personalized Patient Care

Every industry today is transformed virtually by predictive analytics and the healthcare industry is no exception. Predictive analytics in healthcare is advancing patient care significantly by offering detailed insights into the medical history of patients. However, there are many healthcare organizations that are yet to tap into the full potential of predictive analytics in healthcare. Deploying predictive capabilities in extracting actionable, forward-looking insights from the growing pool of data is still a daunting task for many healthcare companies.

However, realizing the power of predictive analytics in healthcare is highly essential as predictive analytics platforms can help healthcare companies to transform medical wisdom into real-world insights. Leveraging predictive analytics in healthcare can help companies to move into the new era of medicine. Consequently, this can improve hospital care, help in the management of chronic diseases and enhance supply chain processes.

At Quantzig, we understand the difference that leveraging predictive analytics solutions can create in the healthcare industry. And to help companies in the healthcare sector stay ahead of the curve, our team of analytics experts have highlighted the ways in which predictive analytics can improve healthcare and also have explained a few use cases for predictive analytics in healthcare.

Are you looking for ways to gain consolidated insights to mitigate risks and resolution of issues for medical cost management and improved patient care? Get in touch with our experts now!

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Weekly Round-Up: A Storyboard on Healthcare Analytics and its Importance in a Fast-Changing World

LONDON: Quantzig, a leading analytics services provider, has announced the release of their new storyboard on the growing importance of healthcare analytics. These downloadable resources explain how healthcare analytics have helped healthcare players to reduce inefficiencies, minimize cost, and forecast future healthcare plans.

Today the healthcare industry is facing the heat of skyrocketing cost of care. Companies in the healthcare sector are trying to address the critical challenges by enhancing data sharing across the value chain. This is the reason why they are looking to leverage healthcare analytics solutions to improve business operations, patient experience, and healthcare outcomes. Analytics in healthcare can help companies to build multidimensional predictive models, enhance healthcare outcomes, and reduce the cost of care.

Quantzig’s analytics solutions have helped companies in the healthcare sector including medical devices, pharma, diagnostics, and healthcare delivery to gain actionable insights into patient care, mitigate risks, medical cost management, and improve payment accuracy. Below, we have summarized some of Quantzig’s free resources that highlight ways in which healthcare analytics have solutions helped healthcare businesses to gain a competitive market advantage.

Digitization has empowered healthcare businesses to gauge the impact of analytics on patient experience and outcomes. Wondering how?  Get in touch with us right now!

#1. How is healthcare analytics transforming the healthcare sector? Do you think maximizing profit by reducing healthcare costs is a herculean task? If yes, then it is time for you to leverage healthcare analytics solutions. Healthcare analytics can help businesses to implement a new model of payment on the basis of performance. Here the healthcare providers can receive the value determined by outcomes. Also, customized analytics tools and real-time dashboards can help in scrutinizing the supply chain to optimize healthcare service and patient care.

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Are you wondering how to optimize healthcare service and maintenance operations? Analytics in healthcare and real-time dashboard can help. Request a free proposal to know more about our healthcare analytics solutions.

#2. Learn how healthcare analytics can modernize the patient journey?  Today healthcare companies may question the value of improving patient experience amidst multiple priorities. But with analytics in healthcare, it seems to be a simpler task. Healthcare analytics can also help map the patient’s journey and assist healthcare companies in bridging gaps that result in leakages in the patient experience.

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Maximizing sales and marketing insights that can be obtained out of every patient interaction is a tough nut to crack and we understand that. Our healthcare analytics solutions provide best-in-class frameworks to assist healthcare organizations in enhancing patient care and outcomes. Request a free demo for more insights.

#3. Customer lifetime value models hold the solution to rising consumerism in the healthcare sector: Customer lifetime value models have always been of great importance for the retail sector, but these models have the potential to solve critical challenges in the healthcare sector too. You must be wondering how? Healthcare analytics by leveraging customer lifetime value models can help companies to enhance their relationship with patients and can lead to more compassionate patient experience.

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Healthcare Analytics: How is It Improving Healthcare Operations Globally?

What is Healthcare Analytics?

Healthcare analytics aims at offering insights into patient records, hospital management, costs, and diagnoses. It covers a broad swath of the healthcare industry, offering insights on both the micro and macro level. Healthcare analytics, when combined with data visualization tools and business intelligence suites, helps healthcare companies operate better by offering real-time information that can support decision making and deliver actionable insights.

Are you facing difficulties in dealing with regulatory pressures in the healthcare industry and constantly changing market dynamics? Get in touch with us to know how healthcare analytics can help you deal with all your issues.

Why is Data Analytics Important in Healthcare?

With the adoption of digital tools like electronic health records (EHRs), data has become more structured. Furthermore, it has improved the analysis to a large extent. Moreover, the emergence of machine learning and artificial intelligence have made inferences and predictions easier than ever before.  The dramatically positive impact data analytics can have on the pressure health systems is more efficient and promises to enhance clinical outcomes. Ideas such as doctor-on-demand, video calls, and Wi-Fi-enabled blood pressure monitors were a fantasy a decade ago. But today they are mainstream and real. This is encouraging both consumers and healthcare providers to adopt healthcare analytics rapidly to lower costs, improve efficiency and enhance patient satisfaction.

Healthcare analytics provides consolidated and actionable insights and helps in risk mitigation and resolution of issues facilitating efficiency and accuracy in the process.

Benefits of Health Analytics

Benefit #1: Identifying and targeting the right people

Health plan serves a diverse group of people who may be at any point along the continuum of health and wellness. Healthcare analytics helps the healthcare companies to identify people who are at risk and could benefit from weight management, additional screenings or smoking cessation programs. Furthermore, healthcare analytics aids in providing care to those who need it best. This starts by analyzing multiple sources such as claims data, health risk assessments and a lot more. Without healthcare analytics, health plans would have to wait to find who requires careful coordination. Additionally, health plans can leverage healthcare analytics to analyze what are the factors that motivate people and how to change their behavior. Also, it helps in taking a closer look at screening rates among people in different demographic groups. This can further help in identifying barriers to screening and determining the best way to encourage target groups to complete the recommended screenings.

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Are you wondering how to address key challenges, reduce costs, increase margins, and gain a competitive market advantage? Leveraging healthcare analytics solutions may help. Request a free proposal here to check out our portfolio of healthcare analytics solutions.

Benefit #2: Increasing productivity with real-time healthcare analytics

Healthcare analytics offers relevant data that elevates operational efficiency. This is the reason why proactive healthcare organizations are turning to healthcare analytics for right-time data feeds to track costs and outcomes and improve decision-making. Furthermore, it also facilitates the standardization of staffing with real-time data that allows physicians to focus on one patient-centered activity at a time. Top healthcare organization has realized an improvement of 50 percent in its variance from benchmark lengths of stay and a reduction of 10 percent in readmissions for heart attacks and heart failure.

Benefit #3: Reducing inefficiencies in the supply chain

Healthcare companies accumulate a huge amount of data which is stored in silos across the entire enterprise. Data silos make it difficult to spot the opportunities of savings in the thousands of daily supply chains. Healthcare analytics helps in connecting these islands of information which leads to smarter and wiser buying decisions. Additionally, it provides the ability to gather and blend data on a common field. By leveraging healthcare analytics, companies can create dashboards with data from multiple sources. Furthermore, this will offer 360-degree assessments of supply chains and help in more accurate visuals, eliminating excess and obsolete inventory while reducing the involvement of clinical staff in replenishment and ordering.

Benefit #4: Automating ad hoc visual analysis

Healthcare analytics helps in automating spreadsheets for ad hoc financial reporting in healthcare. This rule out the tendency of mistakes that are made at the expense of accuracy, efficiency, and time. Data visualization thus allows to quickly automate processes that used to consume a large amount of time. Furthermore, by leveraging healthcare analytics and artificial intelligence, providers can see a significant improvement in revenue, patient access, lower cost, patient experience, and increased asset utilization.

We understand the challenges companies face in data-driven decision making and solving operational problems. Our analytics solutions provide best-in-class frameworks to introduce innovations frequently and strive for better clinical outcomes. Request a free demo below for more insights.

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Top 3 Benefits of Data Analytics That Can Take Wearable Technology to the Next Level

From fitness and activity trackers to “smart clothing” and smartwatches, the possibilities are practically limitless within the industry for wearable technology. And this growth is further enhanced by the promise of high monetary rewards. But design and data collection are only a small component of the potential that wearables offer to both companies and consumers. Taking wearable technology to the next level of usefulness requires companies to build in additional analysis features that increase engagement levels, improves the usefulness of the wearable technology, and provides an unparalleled experience to the consumer. In other words, the benefits of data analytics can help companies to effectively determine what the wearable technology is actually doing for their consumers. But the question that arises here is, what are the benefits of data analytics and how can it help wearable technology to become even more popular. This article has answers to this question. Here, we have discussed in detail some of the significant benefits of data analytics that have potential to take wearable technology to the next level in 2019.

Benefits of Data Analytics

Detailed insights from collected data

One of the most crucial benefits of data analytics is that it can turn collected data into the foundation needed for actionable insights, and in doing so provides additional company and consumer benefits. For example, a sleep tracking device might collect data on how and when a consumer is sleeping. But without the analysis of the collected data, the device only helps in identifying the hours that a consumer sleeps or fails to reach a REM cycle. Does this knowledge help consumers in any way? The answer is simple, no! It is in this context that the real benefits of data analytics are realized.

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Personalized services based on habits 

By leveraging the benefits of data analytics, wearable devices can provide personalized offers to consumers. By analyzing the data captured by wearable technologies, companies can create marketing offers that are customized to each consumer. For example, a step-tracker can reveal that a consumer takes the most steps around lunch time. By leveraging this information viaRequest Proposal personalized offers, companies can encourage the consumer to take more steps throughout the day. 

Improved employee health and productivity

One of the key benefits of data analytics is their ability to improve the health and productivity of employees. Wearable technology can collect the data needed for a company to analyze the productive hours of the day of their employees. Additionally, the devices can also monitor employees’ health, so that the company can mitigate risks associated with lack of sleep, high levels of stress, and other health symptoms that contribute to an ineffective and unhappy workforce.


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3 Common Mistakes to Avoid in Big Data Analytics

Today, big data analytics is one of the most crucial processes for any business, big or small. For data scientists, it acts as a pair of glasses that helps them see the actual reality of a business’ performance, beyond scattered numbers in graphs. A proper, solid, and reliable analysis allows you to make fact-based and rational decisions, but if mistaken, advanced data analytics can lead you astray and you might end suffering a huge loss. So, it can be safely presumed that it is not enough to have good quality data unless you use the datasets efficiently. However, there are many hurdles that businesses might encounter along the way. While implementing a new strategy to strengthen your business with advanced data analytics, mistakes can prevent you from realizing its complete potential. So, in this article, we have summed up some of the common blunders businesses should avoid while developing a big data analytics strategy.

Mistakes to Avoid in Big Data Analytics

Being rigid in processes and products

If you are rigid with your process and product, you are committing a big mistake. You should begin your project in a way that is both strategic in vision and agile in execution. Therefore, you need to pick technologies that are open and expandable. For example, you must avoid vendor lock-in by using open source tools. For obtaining optimum results from advanced data analytics, it is important to foster a culture that fosters failing fast and learning from mistakes. You must avoid letting egos drive your project and understand that if your team experiments on ten things, eight of them might not work. You should get people on board in your data project team who can thrive in this sort of DevOps style of work.

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Neglecting security and governance at the beginning

Today, security and governance are extremely important, as privacy is one of the major concerns in almost every industry. Businesses still tend to start big data analytics projects as pilots, with just a handful of people working on them, and without security and governance baked in. This is a huge mistake when it comes to big data analytics. You must get compliance, governance, and security conversations started on the very first day of the project. You must carefullRequest Proposaly choose the right governance strategies, as well as the right technology of governance.

Relying on the same KPI’s always

As things are constantly changing and your business is subjected to constant dynamics, so you must learn to adapt to the ever-changing environment. This is how you can prosper. So, try not to hold on to the old performance indicators that are used to measure your success in the past. You need to use newer and more suitable tools to make advanced data analytics tools reflect the current performance of your business and identify what really drives your business forward.

Quantzig’s Advantage

Being a leader in offering big data analytics services, Quantzig helps businesses to manage, store, and integrate huge datasets. Also, we help businesses to gain predictive insights that facilitate proactive business decisions and pre-emptive planning. Additionally, Quantzig promises to deliver best-in-class frameworks for multi-dimensional data aggregation and utilizes visualization-based data discovery tools for insight generation.


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Top 5 Challenges Facing the Pharmaceutical Industry and Solutions to Combat Them Effectively

There have been several speculations about the stationary growth of the pharmaceutical industry, but recent technological advancements are expected to encourage the growth of this industry in the years to come. Click To Tweet

The recent population shift to urban areas and increasing accessibility of people to healthcare services has opened the doors for companies in the pharmaceutical industry to a broader target market. These emerging markets are becoming extremely important for pharma companies. However, for companies in the pharmaceutical industry, it becomes very essential to shift from a sales and marketing-focused model to an access-driven commercial model. Additionally, with healthcare becoming a priority for governments in several countries, the pharmaceutical industry seems to have a bright future. But on the flipside, there are several factors like consumer attitudes, drug availability, affordability, policies of governments, which might not entirely be in the favor of pharma companies and are challenging the growth of pharmaceutical industry. In this article, we have talked about several critical challenges faced by the big players in the pharmaceutical industry. and have highlighted steps that will help companies to combat each of those challenges.

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Pharmaceutical Sector market analysis – How big data analytics solutions helped a pharmaceutical firm to evaluate effectiveness of new drugs

QZ PR templateLONDON: Quantzig, a global analytics services provider, has recently completed their latest big data analytics solution for a pharmaceutical firm. The global pharmaceutical industry incorporates businesses involved in the research, development, manufacturing, distribution, and marketing of medicines. The medicines manufactured by these pharmaceutical industries are essential for the smooth functioning of the medical sector. the drugs include OTC, prescription-based, and biologically-derived drugs. Additionally, the industry is witnessing a high demand for innovation for new drugs.

“The big data analytics solution offered by Quantzig assisted the pharmaceutical client to improve their ability to measure and monitor whether medications are being used as prescribed or not.” says an industry expert from Quantzig.

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The big data analytics solution focused on analyzing the number of drugs manufactured against supply data and market demand data, and the effect of drug counterfeiting on their overall business. Additionally, the solution also helped the client to understand the effectiveness of drugs by measuring social media sentiment.

Additional Benefits of the Marketing Mix Optimization Solution

  • Evaluate the efficacy and effectiveness of new drugs
  • Devise robust risk management strategies to help make informed business decisions
  • Decrease inventory write-downs and improve margins as volume increases.
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Big Data in Healthcare: Trends You Must Know About

The healthcare industry is experiencing a major data transformation due to the rising popularity of advanced analytics and big data technologies. The use of big data in healthcare is helping players in this sector to improve patient outcome while simultaneously reducing cost. Medical data encompasses different hospitals from various regional or geographical locations. They include several administrative systems. This necessitates the use of new tools that can help data providers and data users to collaborate with each other. With so many advanced technologies and innovations paving the way for themselves into healthcare, the path ahead lFree demoooks promising for healthcare companies. Here are some trends influencing the use of big data in healthcare:

Patient-centric care

Most healthcare companies today are focusing on improving the quality of patient care. More doctors are finding incentives in providing individual patient-related data. Today, the data quality relates to the quality of patient care. This is becoming beneficial for the patient since it is improving the quality of healthcare that is consistent with the professional experience and knowledge. It has also reduced the health care costs and provided support for payment structures. This shift to value-based payments corresponds with a focus on patient-centric care. Healthcare professionals and health insurers need to work together to deliver personal care that is efficient, bring about transparency in billing, and improve patient satisfaction. 

Healthcare IoT

For healthcare companies, IoT devices monitor patient behavior, ranging from glucose levels to heart function to blood pressure. Most of this data is often unstructured. Smart devices that communicate with each other, combined with machine learning could transform this process, potentially replacing a doctor’s visit with a phone call from a nurse.   

Fraud reduction

Reducing fraud, wastage, and abuse is another important application of big data in healthcare. Using advanced analytical tools such as predictive analytics, healthcare companies can prevent a large number of fraudulent and unfair practices and save huge amounts of money. Analyzing large unstructured datasets of historical claims and to use machine learning algorithms to detect anomalies and patterns is the key to identifying fraud. Healthcare organizations can analyze these patterns and easily identify anomalies.

Real-time patient monitoring

Using big data in healthcare can help healthcare companies to provide proactive care to their patient by continuously monitoring vital signs. Data from these monitors can be analyzed in real time, and if a patient’s condition changes, a care provider can be alerted immediately. Physicians can gain useful patient insights and make lifesaving decisions by processing real-time events with machine learning algorithms.

Improved patient outcome with predictive analytics

The use of technologies like big data in healthcare is gaining more popularity with the increasing adoption of electronic health records (EHR) due to the increasing amount of patient data. This gives physicians greater access to patient records, resulting in improved diagnosis and better treatment. The ability to analyze structured and unstructured data across multiple sources aids in the accuracy of diagnosing patient conditions, matching treatments with outcomes, and predicting patients at risk for disease or readmission. 


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Can Big Data Finally Bring an End to Cancer?

Cancer is a disease that is as old as the human civilization itself. At present, it is the second leading cause of death after cardiovascular disease. Looking at the advancements in modern medicine, one may wonder, why haven’t we found a cure for cancer yet? Cancer is a complex disease and can affect various parts of the body. A single tumor can have billions and billions of cells with each cell capable of acquiring mutations individually. To find a cure, it is almost impossible to study each variation individually. Additionally, the disease is always changing, evolving, and adapting. The best chance of studying the disease is to understand the genetic makeup of the tumor, which has billions of genomic codes. Such studies are far beyond human comprehension and require a technology that can process such vast amount of information. Big data can make such calculations possible and aid in the cancer Free demotreatment.

Understanding cancer

Cancer is a genetic disease, and is caused by certain mutations in the genes that control our cell’s functioning, especially how they grow and divide. Variation or a fault in some genes can cause the cells to grow in an uncontrolled manner. Such errors can occur due to exposure to carcinogens, radiation, and surrounding biophysical environment.

Why is it so challenging to study cancer?

Its now clear that to study cancer, physicians must understand the make-up of a particular gene. However, for an extended period of time, it has been an almost impossible task. Consider this; the human gene is composed of four different types of chromosomes. The DNA in the largest chromosome, chromosome number 1, consists of approximately 220 million base pairs. Cancer can result from mutation or alteration in any one of such base pairs. Similarly, mutations can occur in any combination of such base pairs. As a result, it is impossible for humans to devise an effective cancer treatment plan by studying all such mutations.

How can big data help in finding cancer treatment?

Big data has the capability to analyze such a broad array of information not only across a single gene but also across genetic makeup across large samples of a cancer patient. It can find out the correlation between certain factors that cause a particular type of cancer. So how can big data aid the healthcare industry to find a cure for cancer?

Targeted treatments

Targeted treatment can be used to target cancer’s specific genes and proteins that fuel the growth of cancer cells. By testing a sample of the tumor, patients can be given new drugs and targeted therapy to figure out whether the tumor has a specific target. By analyzing samples across a large population, physicians will be able to improve the efficiency of such targeted treatments.

AI-driven diagnosis

One of the pioneers in the field of cancer treatment using AI is the supercomputer, IBM Watson. Since each cancer is different, and each person has different genes, Watson can recommend a cancer drug that will most likely treat a particular patient’s cancer. It is because the supercomputer is programmed with specific details on how thousands of medicines interact with the human body. From there, Watson can make recommendations on which medication interacts beneficially with the cell affected by the cancer-causing mutation.

Genomic data

It is evident that genomic data is enormous. It takes around 200GB of storage to capture the raw code output by a genome sequencer. The cure for cancer lies in such databases. Using comparative analysis, researchers can isolate the factors that lead to cancer. However, it is not as simple as it looks, it requires huge storage and immense computing power to perform such analysis. Big data can assist healthcare professionals to compute, harvest, and decode such significant amount of data and consequently contribute towards cancer treatment.

Radiation therapy

For now, radiotherapy is the major treatment mode for cancer along with surgery and chemotherapy. A large majority of cancer patients receive radiotherapy as a part of their treatment. However, there’s a problem with such treatment mode. Physicians need to know the exact amount of radiation required, too little and it won’t work, and too much can cause side-effects and damage healthy cells as well. Analyzing historical radiation data could be used to guide radiotherapy safety thereby improving treatment efficacy.

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