Terry  Tremblay

Terry Tremblay

1598440740

Role of Big Data in Healthcare - DZone Big Data

Much like the ‘complexity’ involved in a surgery, the volatility involved in healthcare data is so uniquely complex, that a holistic approach is needed to handle the structured and unstructured data from disparate sources within an ever-changing regulatory environment.

With the future beckoning more sources of healthcare data from patient-generated tracking from electronic devices like monitors and sensors, healthcare delivery organizations (HDOs) are under tremendous pressure to reduce the ‘cost’ of operations and storage; ‘control’ escalating costs to improve revenue & profitability; improve governance & risk management through ‘compliance,’ resulting in improved ‘cash’ flows.

Given the plethora of healthcare systems, data aggregation is essential. Organizations have been analyzing patient cost and quality data for years. Still, as healthcare moves from volume-based to value-based payment, HDOs are on the threshold of exploiting the population health hype provided they can build critical data and analytic capabilities.

Organizations work with data aggregators to pull in data from internal systems and external partners (e.g., providers pulling insurance claim data) so they can have a complete view of a patient’s or population’s data on which they can risk, stratify, and analyze quantitative and qualitative data.

Payers and providers, with an increasing need to understand complex data sets, are rapidly installing data aggregators. The industry is moving from simply looking at structured data to incorporating unstructured data, which has driven organizations to evaluate current solutions and, in many cases, rip and replace current installations with new technologies.

Organizations see value in data aggregation, but the amount of work it takes to move the data into actionable insights is substantial. The desire to infuse unstructured data and the growth of new technologies in big data in general, coupled with an industrywide need to better understand patient data, will drive significant growth. Health clouds provide a cost-effective and secure way for healthcare organizations to scale.

Information life cycle management (ILM) is finally starting to be put in practice within the HDO in targeted, practical ways. ILM used to be about controlling precipitous storage costs through better storage resource management — now it is more about recognizing that the value of information changes over time, and about how systems of record will enforce information life cycle policies.

Payers and providers rely on a variety of analytic solutions to help them understand business performance, patient populations, and provider performance. These tools allow for qualitative and quantitative analysis retrospectively, and increasingly, predictively. This area is seeing significant growth from both payers and providers, particularly as organizations seek to analyze unstructured data and do more with predictive modeling. When well implemented, analytic capabilities allow organizations to identify gaps in care and performance readily and to quantify dollars at risk.

Analytics, more than EHRs, will drive insights to action for payers and providers and help move the industry forward.

Patients or customers can get a 360-degree view of their healthcare data, thanks to digitalization. It is a win-win situation both for hospitals and the patients as they taste success using smartphones with healthcare apps and wearables. Devices that are not expensive are now part of patients’ day-to-day life. It is time HDOs expand their horizons and focus on integration and analytics rather than focusing on internal systems.

Bid data will help HDOs create a plethora of opportunities to enhance customer value and revenue as they face the ‘customer explosion’ in healthcare. As the numbers rise, big data will be the key cost differentiator either in providing care, managing population, or detecting fraud.

#big data #big data analtics #big data analysis #big data in healthcare #data science

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Role of Big Data in Healthcare - DZone Big Data
Terry  Tremblay

Terry Tremblay

1598440740

Role of Big Data in Healthcare - DZone Big Data

Much like the ‘complexity’ involved in a surgery, the volatility involved in healthcare data is so uniquely complex, that a holistic approach is needed to handle the structured and unstructured data from disparate sources within an ever-changing regulatory environment.

With the future beckoning more sources of healthcare data from patient-generated tracking from electronic devices like monitors and sensors, healthcare delivery organizations (HDOs) are under tremendous pressure to reduce the ‘cost’ of operations and storage; ‘control’ escalating costs to improve revenue & profitability; improve governance & risk management through ‘compliance,’ resulting in improved ‘cash’ flows.

Given the plethora of healthcare systems, data aggregation is essential. Organizations have been analyzing patient cost and quality data for years. Still, as healthcare moves from volume-based to value-based payment, HDOs are on the threshold of exploiting the population health hype provided they can build critical data and analytic capabilities.

Organizations work with data aggregators to pull in data from internal systems and external partners (e.g., providers pulling insurance claim data) so they can have a complete view of a patient’s or population’s data on which they can risk, stratify, and analyze quantitative and qualitative data.

Payers and providers, with an increasing need to understand complex data sets, are rapidly installing data aggregators. The industry is moving from simply looking at structured data to incorporating unstructured data, which has driven organizations to evaluate current solutions and, in many cases, rip and replace current installations with new technologies.

Organizations see value in data aggregation, but the amount of work it takes to move the data into actionable insights is substantial. The desire to infuse unstructured data and the growth of new technologies in big data in general, coupled with an industrywide need to better understand patient data, will drive significant growth. Health clouds provide a cost-effective and secure way for healthcare organizations to scale.

Information life cycle management (ILM) is finally starting to be put in practice within the HDO in targeted, practical ways. ILM used to be about controlling precipitous storage costs through better storage resource management — now it is more about recognizing that the value of information changes over time, and about how systems of record will enforce information life cycle policies.

Payers and providers rely on a variety of analytic solutions to help them understand business performance, patient populations, and provider performance. These tools allow for qualitative and quantitative analysis retrospectively, and increasingly, predictively. This area is seeing significant growth from both payers and providers, particularly as organizations seek to analyze unstructured data and do more with predictive modeling. When well implemented, analytic capabilities allow organizations to identify gaps in care and performance readily and to quantify dollars at risk.

Analytics, more than EHRs, will drive insights to action for payers and providers and help move the industry forward.

Patients or customers can get a 360-degree view of their healthcare data, thanks to digitalization. It is a win-win situation both for hospitals and the patients as they taste success using smartphones with healthcare apps and wearables. Devices that are not expensive are now part of patients’ day-to-day life. It is time HDOs expand their horizons and focus on integration and analytics rather than focusing on internal systems.

Bid data will help HDOs create a plethora of opportunities to enhance customer value and revenue as they face the ‘customer explosion’ in healthcare. As the numbers rise, big data will be the key cost differentiator either in providing care, managing population, or detecting fraud.

#big data #big data analtics #big data analysis #big data in healthcare #data science

Siphiwe  Nair

Siphiwe Nair

1622516462

What is Big Data in Healthcare and How is it Used?

The pandemic is having an enormous impact on the healthcare sector. Between overwhelming hospitalization rates, intensifying cybersecurity threats, and an aggravating number of mental illnesses due to strict lockdown measures, hospitals are desperately searching for help. Big data in healthcare seems like a viable solution. It can proactively provide meaningful, up-to-date information enabling clinics to address pressing issues and prepare for what’s coming.

Hospitals are increasingly turning to big data development service providers to make sense of their operational data. According to Healthcare Weekly, the global big data market in the healthcare industry is expected to reach $34.3 billion by 2022, growing at a CAGR of 22.1%.

So, what is the role of big data analytics in healthcare? Which challenges to expect? And how to set yourself up for success?

How Big Data Can Help Solve Healthcare Problems

Big data has several accepted definitions. Here are two popular ones:

Douglas Laney’s definition. Laney is a former Chief Data Officer at Gartner. He states that big data is characterized by 3 Vs: volume, velocity, and variety. The volume stands for large amounts of data. Velocity refers to the speed of collecting data and making it accessible, while variety indicates the different types of data, such as text, video, logs, audio, etc.McKinsey’s definition. The renowned consulting firm defines big data as datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze.

According to an IDC report, the volume of big data is expected to reach 175 Zettabytes by 2025. To put it in perspective, it will take 1.8 billion years to download this amount of data with the average internet speed available nowadays.

#big-data #big-data-analytics #healthcare-and-big-data #healthcare-tech #medical-software-development #healthcare-software #big-data-processing #healthcare-software-solution

Siphiwe  Nair

Siphiwe Nair

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Big Data Consulting Services | Big Data Development Experts USA

Big Data Consulting Services

Traditional data processing application has limitations of its own in terms of processing the large chunk of complex data and this is where the big data processing application comes into play. Big data processing app can easily process complex and large information with their advanced capabilities.

Want to develop a Big Data Processing Application?

WebClues Infotech with its years of experience and serving 350+ clients since our inception is the agency to trust for the Big Data Processing Application development services. With a team that is skilled in the latest technologies, there can be no one better for fulfilling your development requirements.

Want to know more about our Big Data Processing App development services?

Visit: https://www.webcluesinfotech.com/big-data-solutions/

Share your requirements https://www.webcluesinfotech.com/contact-us/

View Portfolio https://www.webcluesinfotech.com/portfolio/

#big data consulting services #big data development experts usa #big data analytics services #big data services #best big data analytics solution provider #big data services and consulting

Silly mistakes that can cost ‘Big’ in Big Data Analytics

Big Data has played a major role in defining the expansion of businesses of all kinds as it helps the companies to understand their audience and devise their business techniques in accordance with the requirement.

The importance of ‘Data’ has been spoken very highly in the modern-day business. Thus, while using big data analysis, the companies must keep away from these minor mistakes otherwise it could have a major impact on their performances. Big Data analysis can be the silver bullet that can answer your questions and help your business to scale newer heights.

Read More: Silly mistakes that can cost ‘Big’ in Big Data Analytics

#top big data analytics companies #best big data service providers #big data for business #big data technology #big data mistakes #big data analytics