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Category : Big Data

Latest Big Data Healthcare News

3 reasons why health care data is such a security risk — and what health
This week, the FBI reminded the health care industry that it's a huge target for hackers. The briefing obtained by Reuters came on the heels of a wide-scale attack on Franklin, Tennesse-based Community Health Systems Inc. Millions of patient records …
Read more on Washington Business Journal (blog)

Update: Intel To Apply Big Data Into Medicine (INTC)
The data generated by IoT in healthcare can drive new efficiencies, while advancing research and improving care. Intel's Big Data analytics platform is capable of integrating a number of software components, including Cloudera CDH – an open-source …
Read more on Seeking Alpha (registration)

Celebs gin up votes for midterm push
In 2010, the under-30 vote dropped 27 percent since Obama first sailed to victory two years earlier, according to CIVIC analysis of Census data. Bernstein's group hopes to engage these so-called … A big push for the youth vote will be National Voter …
Read more on The Hill (blog)

Richardson cloud provider takes military approach to protect against cyberattacks
… boardrooms, FireHost executives say. And that leaves a big opening for a company like FireHost. … FireHost is focused on industries that deal with sensitive data and privacy compliance regulations, such as health care and retail. But executives …
Read more on Dallas Morning News

Latest Big Data Healthcare News

Medical white paper using big data to be drawn up
By releasing an analysis of such “big data,” which shows what kinds of medical treatment patients have received at hospitals, the government hopes local governments burdened with massive health care expenditures will be prompted to trim costs.
Read more on The Japan News

Failure of Aetna's CarePass platform might be a bad omen for Apple HealthKit
Last week, the health insurance giant Aetna said it would discontinue its CarePass consumer health data platform by the end of 2014. And when a player as big as Aetna dumps its health data platform, it's cause for discussion, if not concern, in digital …
Read more on VentureBeat

Pentagon Accepts Bids on Long-Awaited Health Records Contract
Major data gaps in patient records frequently occur when health care is delivered to DOD beneficiaries outside of the DOD network. That's been a big problem considering about half of the nearly 10 million DOD beneficiaries choose their care outside the …
Read more on Nextgov

Cell-Phone Data Might Help Predict Ebola's Spread

Cell-Phone Data Might Help Predict Ebola's Spread
The model created using the data is not meant to lead to travel restrictions, but rather to offer clues about where to focus preventive measures and health care. Indeed, efforts to restrict people's movements, such as Senegal's decision to close its …
Read more on MIT Technology Review

My Fitbit experience: Lost 27 pounds, gained a lot of questions
Despite not setting an intention for weight loss, I have lost weight. That wasn't a big surprise. After all, I'm doing more than 15,000 steps and 10 flights of stairs almost ever day — way more than the 6,000 to 7,000 steps a day that I was doing when …
Read more on CITEworld

Latest Big Data Healthcare News

Will the worlds of Hadoop and Big Data combine or collide? | #HPBigData2014
As far as Blue Cross Blue Shield was concerned, the health insurance provider never saw a risk of database collision with Big Data. Quite the contrary, it anticipated that things were all converging for the purposes of data management. Vellante wanted …
Read more on SiliconANGLE (blog)

The Morning Download: What CIOs Understand About the Plight of the 'Data
You can get The Morning Download emailed to you each weekday morning by clicking here. Good Morning. Companies are chasing Big Data technology and talent in a bid to tease business advantages out of a variety of databases, sensors and documents.
Read more on Wall Street Journal (blog)

The exchange factor: Electronic data system points to a future of managing
The health care and business communities in Michigan may be on the cusp of realizing the ultimate benefit of the free flow of online medical electronic data: Managing the health of patients as they move through the health care delivery system across …
Read more on Crain’s Detroit Business

Lahman: Wearable tech will change health care

Lahman: Wearable tech will change health care
Wearable electronics reflect a convergence among three major technological advances of this generation: the miniaturization of hardware and ability to put remarkable amounts of processing power in very small devices; big data's ability to collect and …
Read more on Rochester Democrat and Chronicle

Why Big Data Isn't Enough: Tomorrow's Technology Will Be Built Around
A new generation of technologies are starting to enable this scenario and changing the way healthcare and other data are mined and utilized, pulling data from various sources to create actionable real-time care plans for patients and providers based on …
Read more on Wired

4 recommendations to harness big data
The number of participants and records to analyze matters in health data networks. Stakeholders must create incentives for health care providers to participate and adopt standards of interoperability. Providers must be committed to educating patients …
Read more on FierceHealthIT

Four Ideas to Leverage the Maximum Potential of Data in Health Care
It is critical to design privacy controls into the structure of large data systems. This will give patients confidence about the security of their data. Because of the unique nature of medical data, it is also difficult to provide restitution in the …
Read more on Brookings Institution (blog)

Latest Big Data Healthcare News

Hated the Facebook experiment? You'll hate what's next for health care.
I. Glenn Cohen: There are different definitions, but essentially "big data" in health care refers to the idea — particularly with the shift to electronic health records — that we have millions and millions of patient records that are now in the …
Read more on Vox

Predictive big data analytics in healthcare
The health sector is a leader in the deployment of big data technologies. Computing spoke to US health analytics firm Amara Health Analytics about the role of big data in hospital alert systems, and also to UK provider FlyingBinary about progress in …
Read more on Computing

Jvion Releases Top Three Lessons in Predictive Population Health Analytics

Atlanta, GA (PRWEB) July 31, 2014

Atlanta-based Jvion, a leader in clinical predictive algorithms and machine learning, released their top three lessons in predictive population health analytics as part of an ongoing series dedicated to understanding and applying predictive analytics in healthcare. Ritesh Sharma, Jvion COO, commented, “it is critical that we work together as an industry to understand the impact of and potential within predictive analytics. There is a lot of information out there and a good portion of it is conflicting or confusing. The effectiveness of predictive capabilities in improving health outcomes starts with understanding where we can effectively apply these new and powerful technologies. When applied right, predictive analytics empower hospitals to proactively do a lot of things.”

Top Three Lessons – Summary Findings

Why focus on population health?

Population health initiatives have the overarching goal of targeting specific at risk populations to apply low cost interventions across the care continuum. New value-based payment models and systems like accountable care organizations are forcing many providers to rethink their approach to prevention and evaluate the effectiveness of predictive technologies in targeting specific, high and rising-risk segments of the community.

What role do predictive analytics play in population health?

There are three types of population health solutions in the market: first, traditional analytic solutions (retrospective data analysis); second, Enterprise Data Warehouse (EDW) based predictive analytics; and third, (new) Machine Learning algorithm powered solutions. Traditional analytic solutions involve retrospective data analysis, benchmarks, and trending and are primarily focused on looking back in time to understand how things worked in the past. The problem with this approach is that it only helps maintain a scorecard; it does not provide enough actionable information for organizations to proactively plan and change future results.

The other two forms of population health solutions are predictive: EDW and Machine Learning. EDW based solutions compile large amounts of data into a single data warehouse. This data is then consolidated and analyzed for patterns that lead to predictive insights. Machine Learning based solutions start by building models and clusters, and analyzing individual risk levels for all patients across a population. This individual-level risk is then aggregated and stratified into risk cohorts that can be targeted for specific interventions.

Feedback and findings suggest that Machine Learning solutions are better suited for the healthcare industry because they tend to deliver more detailed and more accurate results that don’t require a heavy investment in an EDW. The time it takes to deliver value is also significantly different. EDW solutions take a minimum of 18-24 months to stand up whereas Machine Learning solutions can start to deliver outputs in weeks. Additionally, the more advanced Machine Learning solutions currently available are able to use publically and readily available data elements to quickly stratify risk and define cohorts at accuracy levels that are much higher than earlier generation models.

How do you articulate the Return on Investment (ROI) for these solutions?

The ROI for a predictive analytic solution can seem a little “fuzzy” because it is about cost avoidance. The abstracted benefits of population health initiatives are well known. Employers benefit from lower absenteeism and injury rates, and the subsequent increase in productivity. Taxpayers benefit by lowering the number of chronic conditions treated through the Medicare and Medicaid systems. And communities benefit from the overall strengthening of the economy and associated influx of federal investment/benefits.

For individual hospitals, the numbers can get a little blurry and slippery if they are not already proactively managing population health. However, with risk-based and value-based contracting practices becoming more prevalent across payors, population health initiative ROI becomes much more straightforward and concrete for hospitals. In addition, findings suggest that predictive analytics actually enable better ROI measures. This is because they can quickly and comprehensively analyze historical data to determine the dollars saved if preventative measures were applied based on predicted risk insights. Using this approach, a hospital can assign a hard dollar ROI not only to population health overall, but down to a specific disease and subset of a risk stratified cohort.

For more information on Jvion and their population health solutions, please click here. And for information on the firm’s entire suite of predictive analytic solutions, please visit

About Jvion

Jvion is a healthcare technology company that develops software designed to predict and prevent patient-level disease and financial losses leading to increased waste. The company offers a suite of big-data enabled solutions that combine clinical intelligence with deep machine learning to help providers protect their revenues while improving patient health outcomes. The objective is simple—stop the waste of resources and lives by predicting and stopping losses before they ever happen.


Meditology Outlines Top 5 Technology Strategies for Population Health and Engagement

(PRWEB) July 29, 2014

Meditology Services LLC, a leading professional services company focused exclusively on serving healthcare organizations, today announced the appointment of Erin Carey as Director of Healthcare IT Consulting. As a former executive with Kaiser Permanente GA, Blue Cross Blue Shield NC and St. Vincent’s Hospital and Medical Center of New York, Carey is a recognized industry thought leader and brings extensive healthcare experience to the fast growing firm – including the successful execution of Meaningful Use programs to achieve clinical process improvement.

In addition, Meditology has published the “Top 5 Technology Strategies for Population Health and Patient Engagement,” based on its leadership’s decades of combined experience, spanning hundreds of healthcare clients.

Population health and patient engagement is becoming an emerging focus, as it is widely acknowledged that there are not enough clinicians available to take care of future patient populations. Therefore, it is becoming critical that healthcare providers take full advantage of the available technologies in order to care for common health issues efficiently and in a way that effectively engages all patients including an increasingly tech savvy patient base. This will help enable physicians to focus their time and skills on the groups of patients who need it the most, such as those with severe chronic diseases.

“Surprisingly there is technology available today that goes a long way toward advancing population health and engagement when used intelligently. For example EHRs and Meaningful Use functionality, combined with robust business intelligence and data mining tools, can help physicians automate the management of their patient populations and ‘be the conductor of their orchestra’ in order to take care of each patient’s needs. And, ultimately, this helps health systems nationally achieve The Triple Aim – improve the experience of care, improve the health of populations, and reduce costs,” said Carey.

Top 5 Technology Strategies for Population Health and Engagement

Meditology’s leadership recommend these technology approaches to improve the experience of care, improve the health of populations, and reduce costs:

1.    Vision and Strategy

Have a comprehensive technology strategy.

    A broad strategy will encompass all organizational needs with an agile framework that is capable of expanding for future technology. Key components should include assessment of clinical needs including Quality program criteria; Capabilities to support all methods of patient communication preferences; HIE; Application data integration, enterprise data warehouse and business intelligence; Patients and providers bringing their own device (BYOD), telehealth, wearable bio medical/health devices, and emerging capabilities like Google Glasses and contacts; Last but not least, mitigate security risks by ensuring alignment with HIPAA and state regulations.

2.    One Size Does Not Fit All

A single method of physician-patient communication will miss a lot of patients.

    To engage patients for the best possible care outcome and meet patient expectations, providers should ask patients how they would like to communicate outside the office, and should communicate with each patient according the patient’s personal preference. For example, some people don’t open paper mail or email frequently, know how to text message, and assume all those messages on their answering machines are from telemarketers.

3. Leverage Technology for Provider Efficiency

Support Providers in becoming the conductor of their orchestra by providing a comprehensive view of all patients and efficient tools to manage the care each population needs.

    Automation – Automate patient reminders for preventive and follow up care, chronic care reminders, patient visit questionnaires, and appointment reminders by integrating EHR functionality, clinical decision support tools, business intelligence, disease registries, and predictive analytics capabilities.
    Embrace evolution – Meaningful Use technology has provided new business intelligence capabilities that integrate into the clinician’s EHR workflow, these tools support providers in efficiently managing patient populations. Traditional clinical reporting departments should expand their mental mindset to collaborate with IT on using integrated EHR reporting capabilities to positively impact care outcomes.

4. Workflow Integration

Align People, Process, and Technology.

    Creating workflows in silos, not involving key players and not mapping out all goals and steps in the organizational process is a common point of inefficiency, redundancy and failure. Involve all key stakeholders, map out current and future state workflows, configure all systems to align with the new process, and apply process improvement methodologies such as PDSA Cycles after implementation to ensure the optimal design.

5. Security and Compliance Risk Mitigation

Mitigate your risk and liabilities with the right security framework.

    A comprehensive strategy will involve a myriad of data and information traveling into and out of your organization; use comprehensive policies, encryption of information, and ongoing assessment of your breach vulnerabilities.
    It will also involve achieving standards such as Meaningful Use, Patient Centered Medical Home (PCMH), Accountable Care Organizations (ACO) quality measures, CMS quality measures, Health Employer Data Information Set (HEDIS), Coordination of Care programs, and other quality accreditations.

To download the model titled “Designing a Technology Strategy to Support Population Health and Patient Engagement” please visit:

“Creating a cohesive population health and patient engagement strategy – supported through people, process and technology – should be an integral element of nearly every health system’s strategic agenda. But, figuring out where to start can be daunting. I am excited to move into this role with Meditology, whose vision, top-notch talent, knowledge and clients are critical to the advancement of the industry,” added Carey.

“We are thrilled to add Erin and her unique expertise to help our clients achieve these goals while aligning their security, privacy and compliance programs. Following on the recent appointment of Nadia Fahim-Koster, CISSP, CHPS and former CISO for Piedmont Healthcare, this announcement continues the momentum for Meditology as the premier healthcare privacy and security firm,” said Cliff Baker, Managing Partner at Meditology

Carey brings 19 years of a vast array of healthcare leadership experience to Meditology. She has held roles in informatics, finance, business intelligence and reporting, and implementation and optimization of Electronic Health Record and Practice Management systems, as well as leading telehealth and innovation programs to explore technology and processes that optimize the healthcare delivery structure. She holds a Bachelor of Science in Public Health, multiple Epic EHR Certifications and is a speaker at national healthcare conferences as well as a guest lecturer at the University of Georgia.

About Meditology Services

Meditology Services is a leading professional services company with an exclusive focus on the healthcare industry offering two core service lines: IT Risk Management and Healthcare IT Consulting. Meditology’s success stems from the deep and extensive expertise of its leadership team, representing a mix of Big Four consulting, provider, payor and vendor experience. Clients include many of the nation’s largest healthcare companies. Visit Meditology at or follow on Twitter (@Meditology) and LinkedIn.

Text Analytics Market Projected to $4.90 Billion by 2019 – New Report by MarketsandMarkets

(PRWEB) July 24, 2014

The report, “Text Analytics Market by Applications (Enterprise, Web-based and Software, Data Analysis, Search-based, Others), by Users (SMBs, Enterprises), by Deployment Model (Cloud, On-Premise) – Market Forecasts and Analysis (2014-2019),” defines and segments the global Text Analytics Market into various sub-segments with an in-depth analysis and forecasting of market sizes. The report also identifies the factors driving this market, and the restraints and opportunities impacting it along with the adoption trends.

Browse 68 market data tables and 41 figures spread through 166 pages and in-depth TOC on “Text Analytics Market:”

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MarketsandMarkets forecasts the global Text Analytics Market to grow from $ 1.64 billion in 2014 to $ 4.90 billion in 2019, at a CAGR of 18.1%. In terms of regions, North America is expected to be the biggest market in terms of market size, while Europe and Asia Pacific (APAC) are expected to experience increased market traction during the forecast period.

MarketsandMarkets broadly segments the global Text Analytics Market by regions: North America (NA), Europe, Asia Pacific (APAC), Middle East and Africa (MEA), and Latin America (LA); by applications: enterprise, web-based and software, data analysis, search-based and others; by deployment model: cloud and on-premise; by users: Small And Medium-sized Businesses (SMBs) and enterprises; by industry verticals: Banking, Financial Services, and Insurance (BFSI), consumer packaged goods, healthcare and pharma, high-tech, manufacturing, retail and hospitality, telecommunications and others.

The vendors in the Text Analytics Market are constantly innovating and remodeling the existing architecture in order to develop more efficient software. Major vendors in the Text Analytics Market include IBM, HP, Microsoft, Oracle, and SAP. The major forces driving this market are better customer understanding and improved decision-making using the insights obtained from data analysis.

Technologies like big data analytics and predictive analytics in the Text Analytics Market have promising growth opportunities for industry players. Text analytics offers a more tactical approach by providing actionable insights from analyzed data. Organizations have realized that in order to keep up with this enormous amount of information, they need to automate their data analysis. Text analytics has huge potential in improving customer experience through Customer Relationship Management (CRM) and exercising marketing and branding activities more efficiently and effectively.

Text analytics has empowered organizations to extract valuable business insights from textual sources such as survey responses, email and messaging, contact center notes, traditional and social media, etc. For a customer-centric approach, text analytics could be the answer to survey analysis for attending to the needs of customers by understanding their responses better and in a more competent way. Social media platforms are among the top contributors for large amount of data which could be beneficial for many organizations if analyzed with the appropriate tools.

Text analytics with multi-lingual support is the key to removing language barrier between a customer and a company which will help the company to establish and expand globally. Lack of awareness in terms of end use and software handling could hamper the growth of text analytics. Issues like deployment cost and non-compliance with existing Information Technology (IT) infrastructure could challenge the credibility of this technology.

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Related Big Data Healthcare Press Releases

Latest Big Data Healthcare News

Booz Allen Experts Share Views on Big Data and Health Care in Health Affairs
To further extend the conversation around the importance of big data and health care, several expert contributors to the July Health Affairs issue will also participate in Using Big Data to Transform Care, a National Press Club event on Wednesday, July …
Read more on Wall Street Journal

Turning big data into better health outcomes
Population health management is a multifaceted, many-layered endeavor that nevertheless has a common theme: the need for data and the ability to mine it for actionable information. A broad spectrum of health care players — individual providers …