Content 1. Big Data Analytics in Healthcare 2. 7 key benefits of using Big Data Analytics in Healthcare   2.1 Improves patient healthcare   2.2 Predicts patients at higher risk quickly & efficiently   2.3 Eases patient diagnostics with EHRs   2.4 Ensures to reduce overall healthcare costs   2.5. Delivers greater insights into patient cohorts   2.6 Enables improved healthcare with fitness devices   2.7 Generates real-time alerting 3. Conclusion

In today’s world, it is a fact that digitization has been adopted across industries such as telecom, banking, pharmaceuticals, healthcare, FinTech, EdTech, etc. The adaptation of digitization of healthcare has more significance than other sectors as it contains the medical data related to patients, their diagnosis, treatment schedules, imaging results etc. which generates huge volumes of data which has been collectively named as big data.

Big Data Analytics in Healthcare

Typically, this big data refers to the abundant health data amassed from numerous ways of electronic health records (EHRs), medical imaging, genomic sequencing, X-rays, and diagnostic reports, etc.

Importantly, big data has changed the way doctors and healthcare professional use, manage, and analyze this critical data to ensure better patient outcomes. Interestingly, to analyze these numerous amounts of big data, effective techniques of statistical analysis is required.

This statistical analysis or the big data analytics helps to predict hidden information and this healthcare analytics has the potential to deliver numerous advantages to patients.

Big data Analytics Stats

According to Allied Market Research, Big data analytics in healthcare is the complex process of examining big data to discover information including hidden patterns, market trends, unknown correlations, and customer preferences, which can help organizations to make informed clinical and business decisions.

The global big data analytics in healthcare market size was valued at $16.87 billion in 2017, and is projected to reach $67.82 billion by 2025, growing at a CAGR of 19.1% from 2018 to 2025.

Hence, by using new technological improvements like Big data analytics, the enormous volumes of big data in healthcare are converted into useful, and actionable information that continues to deliver great insights to doctors, healthcare providers and patients in an effective way. The usage of big data analytics in healthcare brings about lot of positive and life-saving patient outcomes. Leveraging big data analytics in healthcare brings in many more benefits which have been detailed below.

7 key benefits of using Big Data Analytics in Healthcare

1. Improves patient healthcare:

The significant benefit from the knowledge derived from big data analytics delivers greater clinical insights to various healthcare providers. These cutting-edge analytics improves patient care in the healthcare system as this data facilitates doctors to prescribe effective treatment and make clinical decisions more accurate further eliminating any ambiguity involved in the treatment.

Big data analytics seems to bring in a change in healthcare which is moving towards bringing in better patient outcomes as the data is used to discover which practices are most effective for patients.

2. Predicts patients at higher risk quickly & efficiently:

While considering the population-wide data for a particular area, specifically predictive analytics pinpoints which segment of the patients are at higher risk for diseases and hints for early intervention to protect them. This sort of prediction is more suitable for depictions with respect to certain chronic diseases.

Predictive analytics is drawn by aggregating data that are related to a variety of factors which includes patient’s medical history, demographic area data, socio-economic profile data, patient’s comorbidities existing in the area, etc.

3. Eases patient diagnostics with EHRs:

This is the most widespread application of big data in enabling effective patient diagnostics with every patient having their own electronic health records (EHRs). This EHRs includes the demographics, medical history, allergies of patients, diagnostic test results of current and previous illnesses along with other details.

These EH records are shared through secured information systems and are easily accessible by doctors and other healthcare professionals. They can access these files and the personal data cannot be modified but the diagnostics and treatment can be updated by the doctors. The EHRs can also trigger notifications alerting the patients about their forthcoming doctors or diagnostic visits and even track their prescriptions.

4. Ensures to reduce overall healthcare costs:

Healthcare providers can leverage the electronic health records (EHRs) which significantly helps to identify large patterns that lead to a greater understanding of patient’s health patterns. This in turn can essentially help cut costs by reducing unnecessary care or hospitalization.

Typically, the greater insights this analytics data gives to physicians truly translates to better patient care. This data also pinpoints them for shorter hospital stays, and in some cases for fewer admissions or re-admissions. This further helps patients with healthcare cost reduction due to lesser hospitalizations.

Moreover, by using predictive analytics, the data helps to estimate individual patient costs and helps to maximize healthcare efficiency enormously by carefully planning the treatment.

5. Delivers greater insights into patient cohorts:

By analyzing healthcare big data, it draws a greater insight into patient cohorts that are at greatest risk for various illnesses, and in a way helps to take out some proactive prevention measures.

Interestingly, this sort of analytics data can effectively be used to educate, inform and carefully motivate patients to take the responsibility for their own wellbeing. Moreover, by bringing over the clinical data together, it helps to bring in more effectiveness into the patient treatment plans which ensures better patient outcomes.

6. Enables improved healthcare with fitness devices:

Today, many consumer fitness products are available like Fitbit, and Apple Watch, etc. which keep a track on the physical activity levels of the users. The data thus collected by numerous devices used by people is sent to cloud servers, which is categorically being used by physicians to know the overall health and can even accordingly plan for individual’s wellness programs.

This analytical fitness products user data is analyzed which can be accessed by physicians to know about their physical activity levels and the data can also be used to know about specific health-related trends.

7. Generates real-time alerting:

There are specific medical healthcare decision support software that analyzes medical data on the spot that deliver real-time alerting to help healthcare providers who in turn use that real-time data to deliver better prescriptive decisions.

Doctors, in order to reduce the patient visits to hospitals are insisting on patients to use wearables which will collect patient’s health data continuously and sends the data to cloud. This data is accessed by doctors to prescribe medicines based on the results and values.

Conclusion

In today’s competitive world, latest technologies like big data analytics, artificial intelligence, machine learning are being used by healthcare organizations to gain real-time patient insights with huge data available in place.

Specifically, by using big data analytics in healthcare, it empowers with actionable insights on patient’s data and outcomes and ensures to reduce overall healthcare costs, predict high risk patients more quickly, generate real-time alerting and so on.

Healthcare solutions providers must ensure that their applications are high-performing and delivering great customer experience by enabling end-to-end digital testing of these healthcare solutions by leveraging next-gen testing services (www.testingxperts.com).

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With the growing demand for regulatory compliance, interoperability and the end-user technology compliance, the healthcare industry has witnessed major changes in the last few years. Technology has been the major transformation point in this industry, wherein applications are being created to deliver quick service anytime anywhere.

Contents 1. 4 major benefits of software testing in the healthcare industry 2. Testing Healthcare Applications Challenges 3. How TestingXperts Can Help!?

Digitalization, being one of the major revolutions seen by this industry, has been helping experts to deliver their services even from a distance. The growing number of healthcare products, such as wearables and the applications associated with them, have created a huge market and had a remarkable effect on the economy.

In fact, over the course of relatively few years, the healthcare and insurance markets have seen rapid, fundamental changes. Some of the changes have been listed below. Thus, healthcare products have the prerequisite to provide precision and accuracy, which has created the need for an extensive healthcare application testing. Software testing is a concept that covers all aspects that can individually impact the quality of the product.

4 major benefits of software testing in the healthcare industry:

Application Security

The sensitive data of patients, including their health info, requires a lot of protection. Healthcare application, if not given proper security, can lead to major breaches. In order to make the application secure and fail-safe, security testing is imperative. It helps in making the application sustainable and foolproof in all sorts of challenging situations.

Effective Execution and Expertise

In order to serve the patients better and effectively, expertise and efficiency are much needed in healthcare systems. Seeing the complex nature of the healthcare applications, it is important to ensure that they function smoothly without any disruptions. Software testing ensures that the application works seamlessly, providing a comprehensive experience to the users.

Big Data Handling

Healthcare industry comprises of a huge amount of data, containing extensive patient information and their respective health conditions. This data holds high importance to the healthcare institutions, as it helps in developing the right strategy and producing relevant products. Big data solutions help in providing informed decisions involving disease cure, research and development, and much more. It is imperative that this data gets tested for a flawless implementation – leading to expected outcomes.

Usability Testing

Usability Testing is crucial to building various user scenarios and features that are faced by the doctors and other staff during their working hours. In usability testing, the same instances are emulated and checked in real-time as well as virtually. These days, automation has made this task easier for testers as it simplifies the whole process. Usability testing also helps in enhancing the user interface and overall experience of the healthcare applications.

However, the new monitoring tools and approaches are posing unexpected challenges and making it more and more difficult to test the healthcare applications. Given below are some challenges that are regularly faced while testing healthcare applications.

Testing Healthcare Applications Challenges

1. Domain and System Understanding

Testers should have appropriate knowledge of the functionality, the clinical usage and the environment in which the software will be used while testing healthcare applications.

2. Security and Vulnerabilities

The healthcare application requires proper security to keep the patient’s records and other confidential data safe. The health app also contains financial data which needs proper security. Testers need to keep the data safe and secure to prevent any hack.

3. Cross Dependency of Software

Complex software has various layers and components. Any change in one component or layer can lead to cause side effects on the other. Testers must ensure that there are no side effects on the other layers whenever any change is made.

Testing in the healthcare industry requires agility and more experienced testers. They must be rigorous and experienced in regards to data integrity, data scrubbing and database queries. In addition, they must be able to leverage automation to generate data and AI to alleviate the risks associated with testing in the healthcare industry.

How TestingXperts Can Help!?

The healthcare industry has entered the dynamic era of new regulations and therapies that require a change in the line of work. TestingXperts, with its excellent domain knowledge, assures clients of one-stop testing services. Our strong QA and test automation capabilities, ideal for testing their enterprise applications and technology infrastructure, is helping our clients in producing world-class health applications.

Our in-house test labs have the necessary talent and infrastructure capable of performing multifaceted and complex testing activities, including R&D software testing, healthcare billing software testing and necessary IT improvements for clinical systems. We are carrying out global healthcare software testing, supporting regulatory requirements and reducing testing costs across the world.

The post 4 Major Benefits of Software Testing in the Healthcare Industry first appeared on TestingXperts.

Technology trends and digital disruption is transforming the insurance industry immensely. Thus, insurers have been feeling distressed and pressurized to digitize their workflow, and also streamline business processes. These disruptions have been challenging the traditional ways by which the insurance agents and brokers have done business in the past.

Contents 1. Top Technology Trends Transforming the Insurance Industry 2. Cloud-based Infrastructure 3. Leveraging Big Data and Analytics 4. Use of Artificial Intelligence (AI) 5. Conclusion

The insurance industry is executing a modernized workflow, which demands a considerable expansion in the use of technology and that can only be managed by means of hybrid and on-premise cloud infrastructure. The cloud-based infrastructure is guaranteeing flexibility to clients. Besides, it is also helping the insurance sector to comply with the evolving regulatory standards within the industry.

The current application driven economy is all about data. Insurance is an industry that is data-driven which produces huge amounts of structured and unstructured data. Thus, insurance companies are relying on the Internet of Things (IOT) to gather more and more data relating to the behavior of their clients. On the other hand, Big Data and Analytics help insurers take important decisions based on the analysis of gathered data.

Gartner, Inc. forecasts that “8.4 billion connected things will be in use worldwide in 2017, up 31 percent from 2016, and will reach 20.4 billion by 2020. Total spending on endpoints and services will reach almost $2 trillion in 2017.

Regionally, Greater China, North America and Western Europe are driving the use of connected things and the three regions together will represent 67 percent of the overall Internet of Things (IoT) installed base in 2017”

AI has been helping insurance companies develop systems that require manual processing and human intelligence. The advent of Artificial Intelligence in the insurance industry has made it easier for insurance agents to deliver efficient and flawless automation of existing claim processes. In the upcoming days, Artificial Intelligence will be more disruptive and will be used to evaluate and recognize emerging risks.

Gartner predicts that by 2020, AI will be a top five investment priority for more than 30 percent of CIOs.

Source: Gartner, Press Release “Gartner Says AI Technologies Will Be in Almost Every New Software Product by 2020” July 18, 2017

The key to moving towards a digital environment and improving customer service is to automate workflows where required. While standard direct interaction may not be so common between insurance entities, however, their relationship with the client is as important. Intrinsically, insurers need more time to interact with their clients and less time scrolling down documents and sorting papers. This is where automation of workflows helps.

To implement these technology initiatives in the existing and continuously growing technology environment, software testing is imperative.  To be able to cope with the cumulative intricacies of systems and applications, insurance companies need a reliable testing partner.

Conclusion

TestingXperts (Tx) is extensively helping global insurers in their digital transformation and helping them deliver improved customer experience and gain competitive advantage. Tx’s testing services portfolio and unparalleled track record have proved it as a preferred technology partner for the Insurance clients. Connect with us to know more about our testing services specific to the insurance industry.

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Over the last few decades, the world has experienced extensive availability of data, and this exponential growth has been described as ‘Big Data.’ It is a term used to broadly classify the complex and large data sets where data processing applications are considered insufficient.

The evolution of big data has been extraordinary, but it has led to the rise of bad data as well. In this infographic, we will discuss the importance of Big Data Testing in 2017.

Significance of Big Data Testing

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Providing new insights into various industries, Big Data is no longer confined to just being a technology and rather is becoming a business enabler. The insights gleaned from Big Data are playing an integral part in providing solutions to the longstanding challenges of the insurance industry.

Contents 1. Insurance Big Data & Analytics 2. Major areas where Big Data and analytics can make a huge difference 3. The Bottom Line

Insurance Big Data & Analytics

Insurance firms undergo a process of evaluating risks of insuring a person and consequently setting up the premium for the policy. They hold great quantities of data that helps them get acquainted with the existing customers and reach new customers as well. While the industry has made immense progress by analyzing and capturing structured data, the unstructured and untapped data like social media, real-time news feeds, and other channels etc. are also considered as valuable.

In order to succeed in the ever-changing and competitive insurance industry, it’s a no-brainer that insurers must leverage Big Data and analytics. Algorithms based on Big Data can help insurance companies to meet compliance changes, minimize losses and reduce costs.

Five major areas where Big Data and analytics can make a huge difference:

1. Fraud Detection: One of the significant reasons why insurers go through each and every page of the data is to detect fraudulent claims. This process is not only carried out when the claims are registered but also at the onset and at the revival of the lapsed policies. The overburdened job of the insurers makes it difficult for them to manually gather information and sort each one of them. Predictive analysis through big data can help insurers spot the fraudulent material quickly. Methodologies in data analytics like database searches, modeling, text mining & exception reporting can be used in order to identify fraudulent claims.

2. Proper Fund Balancing: There are huge funds maintained by the insurers against potential claims. It is nearly impossible to predict the size of claims or forecast when a claim will arise. Optimization of the reserve fund is, therefore, a huge task that entails a relentless assessment of risk. Insurers, though, spend a decent amount of time in these tasks, predictive and trending analytic tools can release the pressure of this herculean task from the insurers, helping them make correct judgments about optimization and fund balancing.

3. Customer Segmentation: Calculations of the premiums are based on the claim experience of the group of customers. Usually, customers are grouped by the similar age, sex and the term of insurance. Within a particular group, it is possible that customers are present with varying levels of risk. If there is same premium for the whole group, it is possible that customers with low-risk compensate for customers with high-risk. Big data analysis, therefore, can help insurers group their customers better and calculate customized risk-based premiums.

4. Underwriting: Underwriting insurance policies is a huge task for the insurers as it requires assessing a large amount of data. Obtaining the data in the digital form from the proposer can eliminate human errors and also provide greater authenticity in the data. Analysis and processing of the data can also be automated using BI tools and presented in a suitable format to the underwriter. This process significantly accelerates the process of underwriting, further making it error free.

5. Settlement: Complex claims are the ones that take most of the time and it makes sense in putting the most experienced adjuster on that claim. Usually, claims are settled based on various factors such as age, sex, history of the applicant, duration of the insurance etc. Analyzing all factors associated with the insurance and providing claim to the customer becomes a humongous task for the adjuster. Settlement needs a fast-track process that can settle the claims quickly by analyzing the claim histories. Using data analytics, insurers can fast-track the process of claims and garner superior customer satisfaction.

Interesting #blog: 5 Key Areas in the #Insurance Industry where #BigData can make a huge Impact https://t.co/q7AqSWG79L

— TestingXperts (@TestingXperts) September 6, 2016

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A TCoE is constituted of diverse testing processes, people, and tools operating as a shared services function to provide software testing services with maximum benefits across the entire test organization.

An Infographic on our Testing Center of Excellence (TCoE)

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