Tag: analytics in healthcare

healthcare analytics

How Healthcare Analytics Helped a Client to Unravel Many Facets of the Oncology Drugs Segment to Successfully Launch a New Product | A Quantzig Success Story

The client is a leading player in the specialty drugs market based out of the United States. With several years of expertise in drug development, they were looking at leveraging healthcare analytics to make a remarkable entry into the oncology drugs segment through the introduction of a new oncology drug.

The Business Challenge

The healthcare industry today is amidst major tectonic shifts. The ongoing regulatory changes coupled with far-reaching patient protection and affordable care act in the United States are prompting leading players to change their status quo. Besides the increasing costs of regulatory compliance, healthcare players are also facing rising research and development costs. Though the increased regulatory supervision has turned out to be a major burden. Such regulatory requirements are putting in place a solid foundation for healthcare analytics, which, in turn, can be used to drive major organizational transformations. By using this opportunity organizations can extract additional value from patient data and leverage it to create a competitive differentiation.

Though the specialty drugs market continues to exhibit a massive sales growth with the introduction of more targeted therapies, it has become increasingly challenging to monitor and understand how therapies are being utilized by physicians. This challenge is further compounded by the complexity of the oncology drugs market where treatment decision options are highly personalized to each patient’s genetic profile. Facing similar predicaments, a leading pharma company approached Quantzig to leverage its healthcare analytics expertise to successfully launch their new oncology drug.

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Top Challenges Faced by the Client

Problem Statement 1

The client needed to adopt a sophisticated analytics-based approach to gain detailed insights into physician and customer journeys. Limited insights into market dynamics and understanding of customer decision making prevented them from gaining a complete view of the market.

Problem Statement 2

Though the new product launch strategy looked promising, the client had to gain better insights on stakeholder interactions and process data, as multiple stakeholders were involved in the oncology drugs segment.

Problem Statement 3

The company also needed to develop a post-launch analytics strategy to assess the marketing effectiveness and commercial success of the new drug. This proved to be a major challenge as it required the client to devise a long-term, holistic approach encompassing enterprise-level capabilities, technology, analytics, and data management skills.

Analyzing the Complex Pharma Landscape with the Help of Healthcare Analytics

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Solution Offered and Value Delivered

To gain the desired insights and to support the information needs of the oncology drugs segment, the healthcare analytics experts at Quantzig adopted a comprehensive three-pronged approach.

Phase 1

The initial phase of this healthcare analytics engagement focused on analyzing patient datasets to offer a comprehensive view of patient journeys. Such an approach not only helped unravel the different facets of the oncology drugs landscape but also helped the client to better understand the current prescribing and utilization patterns, which, in turn, helped them identify physician practices that presented the greatest opportunity for improving patient care.

Phase 2

In the second phase, a dedicated team of healthcare data analytics experts and data scientists were assigned the task of assessing the impacts of prescribed therapies and their clinical outcomes. Leveraging healthcare analytics helped bring about ground-breaking results by offering meaningful insights that empowered the client to further strengthen their drug development approach and improve the marketing effectiveness of the new drug.

Phase 3

The third phase of this healthcare analytics engagement focused on leveraging predictive analytics to gauge the impact of the new product launch.

The healthcare analytics solutions coupled with predictive health analytics offered timely, targeted insights that aided the client’s drug development process. Along with identifying the factors driving therapies, drug development, and treatment selection, the offered solutions also helped the client to identify barriers to utilization. Equipped with such granular insights the client was better positioned to gauge marketing effectiveness and the success ratio of its new product prior to its launch.

Why is Data Analytics Important 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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Pharmacovigilance and Its Importance in Healthcare

What is pharmacovigilance? 

Pharmacovigilance also known as drug safety, refers to the detection, assessment, understanding, and prevention of adverse effects or any other possible drug-related problem. Here ‘adverse effects’ refer to any untoward medical occurrence which happens to either a patient or a subject in a clinical investigation when a pharmaceutical product has been given to them. This includes any signs which are unfavorable and unexpected for the patient or subject, including any abnormal laboratory findings. Information received via pharmacovigilance agreements (PVAs) from patients and healthcare providers, as well as other sources such as the medical literature, plays a critical role in providing the necessary information for undertaking pharmacovigilance. In fact, in order to market or to test a pharmaceutical product, most countries have mandated the requirement for adverse event data received by the license holder (usually a pharmaceutical company). This data is required to be submitted to the local drug regulatory authority. Let’s examine some of the key importance of pharmacovigilance in healthcare:

Importance of pharmacovigilance 

Clinical trial regulation

One of the importance of pharmacovigilance is that it facilitates clinical trial regulation. The recent years have witnessed a skyrocketing increase in clinical trials in the United States alone. Furthermore, the increase in the complexity of clinical trials is leaving regulators with several challenges to face. Clinical trials are mostly contracted to clinical research organizations and patient recruitment agencies. These agencies act as intermediaries between the sponsors of the study, the investigators, and the patients. The importance of pharmacovigilance can also be established from the fact that it enables improved and more rapid changes in labeling or even withdrawal of a new drug from the market. Furthermore, a standardized reporting system for safety concerns arising during clinical trials can be established. Pharmacovigilance also plays a vital role in ensuring patient safety and strict compliance with prescribed regulatory requirements that would substantially improve standards of clinical trials.

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Monitoring post-marketing safety

A part of the process of evaluating drug safety should ideally take place in the post-marketing phase. Safety monitoring is not only limited to the cases of new drugs or significant therapeutic advances. The importance of pharmacovigilance is notable in the introduction of generic medicines, and in the review of the safety profile of older medicines already available, where new safety issues may have arisen. Spontaneous reporting is a cornerstone of pharmacovigilance in the regulatory environment is indispensable for signal detection. The need for more active surveillance has also become increasingly clear in recent years. Without reliable and autheRequest Proposalntic information on utilization and the extent of consumption, spontaneous reports do not make it possible to determine the frequency of an ADR related to a product or its safety.

Promotional activities

There has been an increased spending in direct to consumer advertising by pharmaceutical manufacturers. This results in national regulations on advertising to become ineffective. Several websites now enable buying and selling of prescription drugs such as benzodiazepines without controls. These developments in communication have a significant impact on the safety of medicine. Such issues suggest the need for more thorough monitoring of drug safety and scrutiny of advertising. This highlights the importance of pharmacovigilance.


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data and analytics

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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3 Amazing Ways Data Analytics Can Help in Reducing Healthcare Costs

Are you looking for ways to provide the best care to each patienContact USt at your healthcare organization at lower costs? Reducing healthcare costs can often be a tough and challenging task for healthcare providers. But it is achievable! Today, there are some new tools and strategies that are being employed to help bring down the healthcare costs. And analytics is one of those tools. The advent of big data and AI has enabled healthcare professionals to capture and analyze heaps of digitized healthcare data to unveil new insights. Analytics is also ushering in a new era of premium quality healthcare that is available at lower costs.

With the help of the analytics experts at Quantzig, we have highlighted five amazing ways analytics can help in reducing healthcare costs. (more…)

predictive analytics

3 Trends That’ll Make a Big Difference with Your Healthcare Analytics

Healthcare analytics has the potential to transform decision making using predictive algorithms and accurate forecasts. But there is little doubt that other industries have used the power of predictive analytics to boost the strategic growth and margin enhancement that healthcare needs to keep up with. But how can this potential be leveraged by the healthcare leaders? To help you better understand the benefits, we have identified three trends that will help healthcare leaders to boost profits with healthcare analytics:Get more info

Upcoming trends in healthcare analytics

 

Efficiency by artificial intelligence and machine learning

Artificial intelligence and machine learning have become significant in demonstrating results in specific cases. Such developments will help clinicians to get more insights from healthcare analytics and data. Various things like care coordination, protocols for patient education, and other processes will start to deliver dividends in patient outcomes. Understanding of population risk stratification by leveraging healthcare analytics will help in getting better insights into treatment protocols and making decisions on a per person basis. This trend will help healthcare analytics to be more accurate and helpful in understanding the requirement based on the patient’s needs.Get more info

More empowered clinical analysts

Healthcare companies will witness an increase in the number of doctors, physicians, clinicians and nurses who are well versed with healthcare analytics. This trend will help the healthcare workers to ask and answer their own questions and there will be a paradigm shift in the data-driven decision-making process. This kind of immediate access to real-time insights certifies to provide more accurate medication and helps in mitigating risk.Get more info

Genomics and cloud analytics

Today, the use of genomics and cloud analytics is becoming more common and will bring about a revolution in the biotech, pharmaceutical, and life sciences industries. Next-generation sequencing (NGS) is making it possible for human genomes to be profiled in record time and with great precision and accuracy; thus, helping researchers to bring out and analyze more types of abnormalities caused by genes than they would be able to with conventional DNA sequencing technologies which are not less than a revolution in healthcare analytics. Genomics data is very helpful when it comes to precision in medicine. Such data can be captured in the cloud and can be later analyzed, which will help in gaining demonstrable results when it comes to the specific case. This upcoming healthcare analytics trend is going to help in identifying specific biomarkers and then proactively detect and manage life-threatening diseases and chronic disorders.

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5 Healthcare Inventory Management Techniques to Cut down Cost

The developments of new technology in healthcare is growing at a rapid rate. The healthcare industry revolves around thousands of daily tasks. Numerous patients get admitted every hour who require constant supervision. In the effort to provide superior service and, healthcare companies often ignore keeping track of their inventories. Healthcare companies possess inventories that comprise of perishable goods as well as medical instruments which need to be stocked correctly. Same is the case of miscellaneous hospital equipment which tends to go missing if unsupervised. Often, hospitals lack the capability to accurately estimate the quantity of hospital equipment required at a specific time. Meanwhile, having excess of rental equipment like stretchers and X-ray machines take up space and add to costs. To streamline inventory management techniques and automate supply and medication distribution, hospital executives need to implement best practices such as investing in a hospital supply management system and streamlining inventory management tasks. One of the most critical aspects of any hospital inventory management system is the maximization of technological resources. Here are five tips for healthcare companies to improve inventory management techniques and reduce their overall costs:Free demo

Collect data from the supply chain

Using supply chain data can save healthcare companies billions of dollars. The data can be used to determine if the inventory management techniques used are as cost-effective as they could be. According to a recent survey, supply data has been siloed in the past. However, more healthcare companies are looking to build IT systems that use value-based reimbursement models. Using these value-based models, organizations can more accurately link supplies needed and patient outcomes.

Make responsibilities clear

Employees involved in inventory management must have a strong understanding of his or her role in the function. Be it cleaning the rooms, ordering the supplies, or checking the purchase orders for accuracy; it is essential that the staff in healthcare companies understand what their role is and how it contributes to the success of inventory management techniques.

Better organize supply room

A hospital supply area that is not well maintained can pose a serious hindrance to healthcare inventory management. Disorganization is a bad situation for any supply room of healthcare companies leading to problems ranging from lost revenue caused due to misplaced supplies to not having an ability to tell how much of a particular item is available. It is advisable to organize the supplies in a linear fashion, which makes the frequently used tools easy to find. In order to reduce the amount of wasted materials, try placing products that will expire the soonest towards the front when organizing the supplies.

Adopt a lean strategy 

The inventory management techniques used by healthcare companies have costs outside of the supplies purchasing. There are several factors to be considered in the price. For instance, movement and management costs, expired products, excess supplies, and purchase price variance. A better understanding of the expenses can, in turn, save healthcare companies more money. Implementing a lean supply chain will ensure that healthcare companies have the right number of supplies at the right place when and where they are required.


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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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4 Compelling Reasons Why Analytics Is Important in Healthcare

“The healthcare system is in desperate need of reform, and technology is one of the tools that can help.” – Charles Doarn

The impact analytics and big data on the healthcare industry is an epitome of how new age technology is changing the world as we know it. The benefits that analytics offer to the healthcare sector are numerous. Some of the well-known advantages of analytics in the healthcare industry include reduced price, higher profits, and improved quality of life. Large amounts of heterogeneous medical data have become readily available in various companies in the healthcare industry. This data could be used for deriving insights, improving care delivery, and reducing waste. The enormity and complexity of these datasets present significant challenges in analysis and subsequent applications to a practical clinical environment. Analytics help companies in the healthcare industry to organize this data and leverage them to derive meaningful insights.

Importance of analytics in the healthcare industry

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Prevention is better than cure

There is increasing awareness among the general public on fitness and well-being. This has fueled the market for gadgets like wearable tech which will help consumers easily keep tabs on their health without having to undergo regular medical checkups. Recent studies have shown that the use of wearable tech helps to increase patient engagement by enabling them to keep track of their daily regime. Also, several top companies in the healthcare industry vouch for the fact that there has been a considerable positive ROI through big data analytics. To stay profitable in the long run, companies in the healthcare industry need to tweak their business plans to include big data and analytics in their long-term growth strategies by leveraging apps and wearable tech markets.Contact US

Facilitates diagnosis

With the help of analytics, it becomes easier to analyze large volumes of healthcare data created on a daily basis and derive essential insights about the ailments which would otherwise prove impossible to predict. In fact, doctors will soon be making use of analytics to know the complete history of their patients, thus administering better treatments at a micro level. At a macro scale, access to a vast pool of national healthcare data will aid governments to spot epidemics and outbreaks, hence developing coping strategies in advance.

Reduces Fraud

Fraud and abuse can lead to rising costs in the healthcare industry. Common frauds can be in the form of multiple prescriptions being issued in the same person’s name, patients receiving treatment from numerous hospitals simultaneously, etc. Analytics helps to safeguard companies in the healthcare industry from such abuse by using predictive analytics to detect exceptions and patterns. Once these patterns are identified, healthcare industry players can take preventive action and save themselves from massive losses.

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Real-time monitoring

Analytics proves handy to monitor in real-time the health of patients. Doctors can be notified of any sudden fluctuations in the patient’s conditions to help them respond to emergencies and take crucial life-saving decisions faster. Also, advanced wearable tech can detect any future hospitalization requirements even before the doctors realize the need for the same. For instance, For example, the weight of the patients suffering from obstructive heart disease can be tracked to detect fluid retention. This will help identify the need to visit the hospital for check-ups.


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