Walgreens (NYSE: WAG) (Nasdaq: WAG) is expanding its relationship with Inovalon Inc. a leading technology company to implement its patient assessment tool and technology platform to support improvements in care quality and risk score accuracy programs across more than 400 Healthcare Clinic at select Walgreens locations.
The convergence of Inovalon’s data-driven patient assessment tool Electronic Patient Assessment Solution Suite (ePASS®) and Healthcare Clinic at select Walgreens creates a unique offering within the health plan and retail clinic industry. With the implementation Inovalon’s analysis of more than 8.3 billion medical events brings analytic insights to Healthcare Clinic programs.
“By integrating data analytics we can gain even deeper insights to help improve patient care and ultimately outcomes” said Heather Helle divisional vice president Healthcare Clinic. “We continue to expand the scope of services capabilities and footprint at Healthcare Clinics. These types of innovative solutions enable our nurse practitioners and physician assistants to play an increasingly important role as part of a patient’s care team.”
Healthcare Clinic at select Walgreens improves members’ choice providing a convenient community-based access point for member assessments versus the traditional in-home model.
The combination of Inovalon’s advanced analytics and Healthcare Clinic’s nurse practitioners and physician assistants as well as its laboratory and immunization resources provides a superior solution to health plans ACOs and integrated care delivery organizations seeking to achieve goals in improving quality outcomes and risk score accuracy.
“Bringing advanced analytics to the point of care in real time is a powerful benefit for patients being seen in today’s highly complex health care environment” said Keith Dunleavy M.D. president and chief executive officer of Inovalon. “We are proud to be working with Walgreens on this industry leading initiative supporting its commitment to improve health care outcomes for Healthcare Clinic partners and patients nationwide.”
Inovalon’s ePASS system delivers a patient assessment tool with individualized predictive analytics to the point of care supporting advanced insight and efficient resolution of gaps in quality care patient assessment documentation and risk score accuracy. The risk score models of Medicare Advantage Commercial Health Insurance Exchange and state managed Medicaid are each supported within the ePASS system. Similarly the industry’s wide array of quality outcomes programs including HEDIS® CMS Stars state Medicaid programs and commercial accreditation requirements of NCQA and URAC are supported within the platform provided at Healthcare Clinic at select Walgreens locations.
As the nation's largest drugstore chain with fiscal 2013 sales of $72 billion Walgreens (www.walgreens.com) vision is to be the first choice in health and daily living for everyone in America and beyond. Each day Walgreens provides more than 6 million customers the most convenient multichannel access to consumer goods and services and trusted cost-effective pharmacy health and wellness services and advice in communities across America. Walgreens scope of pharmacy services includes retail specialty infusion medical facility and mail service along with respiratory services. These services improve health outcomes and lower costs for payers including employers managed care organizations health systems pharmacy benefit managers and the public sector. The company operates 8200 drugstores in all 50 states the District of Columbia Puerto Rico and the U.S. Virgin Islands. Take Care Health Systems is a Walgreens subsidiary that is the largest and most comprehensive manager of worksite health and wellness centers provider practices and in-store convenient care clinics with more than 750 locations throughout the country.
About Inovalon Inc.
Inovalon is a leading technology company that combines advanced data analytics with highly targeted interventions to achieve meaningful impact in clinical and quality outcomes utilization and financial performance across the healthcare landscape. Inovalon’s unique achievement of value is delivered through the effective progression of Turning Data into Insight and Insight into Action®. Large proprietary datasets advanced integration technologies sophisticated predictive analytics and deep subject matter expertise deliver a seamless end-to-end platform of technology and nationwide operations that bring the benefits of big data and large-scale analytics to the point of care. Driven by data Inovalon uniquely identifies gaps in care quality data integrity and financial performance – while also bringing to bear the unique capabilities to resolve them. Touching more than 540000 physicians 220000 clinical facilities and more than 140 million Americans this differentiating combination provides a powerful solution suite that drives high-value impact improving quality and economics for health plans ACOs hospitals physicians patients and researchers. For more information visit www.inovalon.com.
While almost two-thirds of organizations across the healthcare ecosystem have analytics strategies in place, our research shows that only a fifth are driving analytics adoption across the enterprise.
The IBM Institute for Business Value has been listening to what members of the healthcare ecosystem around the world have been saying about their experiences with analytics. We have surveyed 555 executives within the healthcare industry and are about to launch our latest point-of-view, Analytics across the ecosystem: A prescription for optimizing healthcare outcomes. This blog briefly explores just one of the aspects covered in the paper; ‘Importance of enabling organizational strategies with analytics’
The healthcare ecosystem is the convergence of otherwise separate entities, such as life sciences organizations, providers and payers, as well as social and government agencies. Going foreword, gaining and sharing meaningful insights from data across the entire healthcare ecosystem will be a necessity to correlate cost and quality of care. For example, increased interaction among providers, payers, life sciences organizations and patients can help reduce unplanned adverse events. Patients can benefit from more individualized care. Insights from analytics can facilitate continuous learning and promote quality improvement. However, organizations are still struggling with using advanced analytics for gaining such insights. Only 34% of our study’s respondents said they think in terms of analytics that can help gain actionable insight from data.
Enabling organizational strategies using analytics can lead to a significant impact. For example, in a recent IBM Institute for Business Value study about big data, the percentage of respondents in the healthcare and life sciences industries reporting a competitive advantage from analytics rose from 35% in 2010 to 72% in 2012, a 106% increase in two years.
To derive the most value, analytics must become an increasingly important factor in corporate strategy decisions. To position analytics accordingly, organizations must define the enabling analytics strategy, prioritize their roadmaps to address internal requirements and create strategies for future collaborative partnerships across the healthcare ecosystem. A comprehensive plan for governance is a foundational to drive adoption of any analytics strategy. High-level sponsorship of key analytics projects is an important success factor. The most effective analytics initiatives embed small, action-oriented analytics into key decision points of specific business processes that are used widely across the ecosystem. Metrics to measure success should be in place from day one and be tracked. To get the most out of these projects, organizations should focus on early insights that enable refinement of processes over time.
The point-of-view will explore this topic in further detail taking into context the requirements within the organization as well as across the entire ecosystem. So please revisit this page to read further blogs; get invites to webcast and receive a copy of the white paper. For more information e-mail me at email@example.com
The Era of Big Data Analytics in Healthcare HIT Consultant Big data analytics in healthcare splashed onto the front page of the Wall Street Journal earlier this summer, heralding its arrival as a new and important topic for mainstream media to...
The digital hospital is as much a way of thinking about the future of healthcare as it is about technology. It’s not about the EMR or about the data. There is no single “solution” for digital hospitals to implement, no magic data integration that suddenly creates a digital hospital. Digital hospital is not a technology story. It’s about the customer value mindset and those healthcare organizations that are offering their traditional and very new global customers a more compelling patient, client, or member experience than a visit to the local doctor’s office or Emergency department. Here’s an example of the digital hospital in action. At the Ottawa Hospital in Canada, care teams were struggling with very high occupancy and highly variable manual processes. As a result, patients experienced delays in their care, clinicians were frustrated, and the hospital was not satisfied with the overall patient experience they could offer. The hospital equipped every physician with a tablet and implemented IBM’s care process orchestration engine to model the readiness for discharge process from admission to post discharge. The system dynamically creates communication and knowledge links between a patient and the circle of care providers around them and allows automatic texting and videoconferencing between members of the team to help the physicians, nurses and therapists review what the patient can and can’t do and make different therapy decisions or revise the date of discharge. Combined with business intelligence tools, the clinicians are doing extensive analytics – to see what days of week are heavy, to track how many consults each therapist has and to balance their workflow – and are moving into rapid cycle testing of new hypotheses and improvements of the process – eg does early referral of social work help to hit estimated discharge dates. Dale Potter, senior vice president and chief information officer, of The Ottawa Hospital says, “What we are doing is putting process orchestration and process models in place, so that you can literally see the characteristics of the hospital system. You can see, for example, that the flow in the emergency department is too fast to be taken up in the admitting units, and you can then influence that.” In this version of the digital hospital combining mobile communication tools, care process modeling and analytics, patients are given accurate information about their care process and their predicted length of stay, the hospital is better managed and clinicians are more satisfied “Personally, I am going to spend more time focusing on the right things and less time focusing on the mechanics, the bureaucracy, the paperwork and other things,” says Glen Geiger, chief medical information officer at The Ottawa Hospital. “I am not spending time chasing information, I am spending time dealing directly with the patients.”
Alere Analytics Provides Healthcare Insights on the Future of Patient ... DailyFinance Dr. Fauzia Khan to Share Vision on How Connectivity Technologies Can Help Providers and Patients Better Manage Their Own Health Across the Continuum of Care.
After Watson won on the TV quiz show Jeopardy!, a lot of people didn’t really understand what “Watson” was. They thought it was a particular piece of hardware: a glowing blue supercomputer that IBM built in one of its labs.
But now, as Watson comes of age and makes the transition from science experiment to a force to be reckoned with in business and society, I think it’s time to give people a new way of thinking about it. So here goes:
Watson is a cognitive capability that resides in the computing cloud — just like Google and Facebook and Twitter. This new capability is designed to help people penetrate complexity so they can make better decisions and live and work more successfully. Eventually, a host of cognitive services will be delivered to people at any time and anywhere through a wide variety of handy devices. Laptops. Tablets. Smart phones. You name it.
In other words, you won’t need to be a TV producer or a giant corporation to take advantage of Watson’s capabilities. Everybody will have Watson — or a relative of the Watson technologies — at his or her fingertips.
Indeed, Watson represents the first wave in a new era of technology: the era of cognitive computing. This new generation of technology has the potential to transform business and society just as radically as today’s programmable computers did so over the past 60+ years. Cognitive systems will be capable of making sense of vast quantities of unstructured information, by learning, reasoning and interacting with people in ways that are more natural for us.
You may be familiar with the first steps for Watson after the Jeopardy! victory. Our scientists and engineers have been working with Memorial Sloan Kettering Cancer Center, Cleveland Clinic,WellPoint and other healthcare institutions. The goal is to help professionals and organizations deal with the deluge of medical information and transform how medicine is taught, practiced and paid for. For patients, the quality and speed of care will be improved through individualized, evidence based medicine.
But healthcare is just the start. IBM is working with companies in a wide range of industries to bring new cognitive capabilities to the way they do business. In a next step, we recently announced a new service called IBM Watson Engagement Advisor, which is being used by companies in retail, banking, insurance and telecommunications, to crunch big data in real time and transform the way they engage clients via customer service, marketing and sales.
Many more applications will come:
–In a big city, cognitive systems will help city leaders react, prioritize and respond to citizens more effectively by using data to gain insights into complex systems.
–In the home, intelligent assistant apps on smart phones will help elderly citizens and their health care providers better manage chronic diseases and promote wellness.
–In companies, cognitive systems will help engineers and designers create new products and services that respond better to the demands of consumers or even anticipate their needs.
IBM will create some of these services and continue to play a major role as the cognitive era unfolds. Our clients will embed Watson-like technologies in many aspects of how they run their businesses: from supply chain management and manufacturing, to accounting and market research.
We also anticipate that many other companies will develop new capabilities enabled by cognitive technologies. In addition, independent software and services companies will build new cognitive services on top of IBM’s technology platform. You can think of these as cognitive apps, just like Apple offers apps made by others to run on its iPhones and iPads.
So, don’t think of Watson as something that’s locked up in a box. Rather, think of it as a cloud service, available anywhere. And think of it as the foundation for an ecosystem of innovative companies — all of them focused on bringing new capabilities to individuals, businesses and society.
If you’re like to learn more about cognitive technologies and their impact on the world, you can download a free chapter of the upcoming book, Smart Machines: IBM’s Watson and the Era of Cognitive Computing, by IBM Research Director John E. Kelly III.
As IBM General Manager of Watson Solutions, Manoj Saxena is responsible for the commercialization efforts of IBM’s Watson technology globally. Prior to this role, Saxena held several other leadership positions at IBM. Before joining IBM in 2006, Saxena was an active member of the IT venture capital community and led two successful venture-backed software companies.
Healthcare vertical can leverage big data analytics to achieve better prognosis, effectively do remote patient monitoring and dig into combined clinical and genomics research data to suggest personalized treatments for patients
In a bid to deliver high quality healthcare care and improve patient satisfaction, public and private sector hospitals are today looking at streamlining workflow processes, integrating healthcare related data and securing information exchange. Like many developing nations, India too is exploring all ways and means in providing good, cost effective healthcare to its citizens. In doing so, healthcare organizations are increasingly realizing that IT solutions can actually help them meet this challenge by optimising resource allocation and plugging inefficiencies that cause delay in treatment.
One of the technology solutions that can be leverage quite effectively by healthcare organizations is big data analytics which can go a long way in reducing the cost of healthcare care and improving patient outcomes which in turn could pave the way for a new age in healthcare. Let us look at some of the ways in which healthcare vertical could leverage big data and analytics for providing high quality of patient care both for inpatients and outpatients.
The healthcare industry is fast moving away from a paper based systems to Electronic Medical Record (EMR) systems. So far, much of this data was locked in a system designed to treat patients on an episodic fashion, and may not have contained the full longitudinal health record of the patient. But with the maturing of some solutions based on big data architectures, the ability to unlock and analyze this information is now possible. The Chief Medical Information Officer or Chief Research Officer at many healthcare organizations are using these tools to derive scientific evidence that will help them validate the treatment being given to a patient as the most effective and efficient care at the best cost.
Remote patient monitoring
In many countries, technology is enabling healthcare providers to closely monitor patients in their home on a real time basis. The care givers are monitoring home devices such as glucometers, weight scales, pedometers and others to understand how the patient is faring day to day. For example, if a patient is suffering from a chronic disease such as diabetes or congestive heart failure, the ability to monitor him for weight gain, blood sugar levels and exercise attempts will allow the care team to proactively contact the patient and provide help or recommend his report to an emergency room for immediate treatment if need be.
Another example where real time in-home devices can be used is, for independent living. Just because many countries are experiencing an ageing population, does not mean that the people will want to give up the ability to live alone. In such a situation having the ability to covertly monitor the person, with their permission, provides a level of safety to determine if someone has fallen, not gotten out of bed, or has been missing meals.
The facilities to extend the healthcare system into the home of a person allows for a much better quality of life for the patient as well as to reduce operational cost for hospitals. However the volume and velocity of the data being collected, as well as the real time nature of the analysis and action require health care organisations to put in place a big data solution.
Tapping into clinical and genomics research data for personalized treatments
Advances in medical technology have changed the way doctors monitor and treat patients. With the cost of DNA sequencing becoming affordable in many parts of the world, the emergence of personalized medicine is becoming a reality. There are many drug therapies that have been found to be effective for a certain group of patients with specific gene expressions. The ability to determine if a patient has the genetic gene expression before treatment begins allows for a better prognosis.
Many research institutes, academic medical centres, drug makers and contract research organization are looking for technology solutions that will help them combine clinical and genomics research data in order to determine the effectiveness of personalized treatments. In order to achieve this, many hospitals will be looking at adopting solutions such as big data analytics, over the next few years.
No-where is the transformative power of big data analytics more meaningful than in the health care sector. The need is to identify the potential that big data analytics holds in itself to transform the way healthcare vertical has been traditionally responding to the patients needs, so far.
CIO — BOSTON—The increasing digitization of healthcare data means that organizations often add terabytes' worth of patient records to data centers annually.
At the moment, much of that unstructured data sits unused, having been retained largely (if not solely) for regulatory purposes. However, as speakers at the inaugural Medical Informatics World conference suggest, a little bit of data analytics know-how can go a long way.
It isn't easy, namely because the demand for healthcare IT skills far outpaces the supply of workers able to fill job openings, but a better grasp of that data means knowing more about individual patients as well as large groups of them and knowing how to use that information to provide better, more efficient and less expensive care.
Feature: 13 Healthcare IT Trends and Predictions for 2013
Here are six real-world examples of how healthcare can use big data analytics.
1. Ditch the Cookbook, Move to Evidence-Based Medicine
Cookbook medicine refers to the practice of applying the same battery of tests to all patients who come into the emergency department with similar symptoms. This is efficient, but it's rarely effective. As Dr. Leana Wan, an ED physician and co-author of When Doctors Don't Listen, puts it, "Having our patient be 'ruled out' for a heart attack while he has gallstone pain doesn't help anyone."
Dr. John Halamka, CIO at Boston's Beth Israel Deaconess Medical Center, says access to patient data—even from competing institutions—helps caregivers take an evidence-based approach to medicine. To that end, Beth Israel is rolling out a smartphone app that uses a Web-based- drag-and-drop UI to give caregivers self-service access to 200 million data points about 2 million patients.
Analysis: Is Healthcare IT Interoperability (Almost) Here?
Admittedly, the health information exchange process necessary for getting that patient data isn't easy, Halamka says. Even when data's in hand, analytics can be complicated; what one electronic health record (EHR) system calls "high blood pressure" a second may call "elevated blood pressure" and a third "hypertension." To combat this, Beth Israel is encoding physician notes using the SNOMED CT standard. In addition to the benefit of standardization, using SNOMED CT makes data more searchable, which aids the research query process.
Two new research partnerships whose participants range from pharmaceutical companies to IT vendors are taking aim at improving disease treatment via data analysis.
It’s no secret that medical research and health care have already benefited pretty significantly from the technologies and analytic techniques that comprise big data, and two new partnerships underscore the promise.
One is a five-year research partnership between the Berg pharmaceutical company and the Icahn School of Medicine at Mount Sinai, which is focused on using data to derive new therapies for cancer, as well as central nervous system and endocrine disorders. The other is a $2 million grant from the National Institutes of Health to IBM, Sutter Health and Geisinger Health System to study how electronic health records can help predict heart failure.
The Berg-Mount Sinai partnership is particularly interesting because of its scope. It’s focused on analyzing so-called “multi-omic” biology, which means the study of various systems and fields, including genomics, proteomics and metabolomics. According to Icahn professor Eric Schadt, in the press release announcing the partnership, “Working with Berg, we plan to analyze big data and create predictive models to discern similarities and differences in disease patterns, identify the most effective treatment and diagnostics, and ultimately, provide better care for our patients.”
The IBM-Sutter-Geisinger partnership is actually an extension of earlier work into this same area — identifying symptoms that often result in heart failure years before any serious issues might occur. According to that press release, “The NIH funding allows the team to look deeper into the progression of factors that are predictors of heart failure so clinicians can implement timely care-management plans to improve health outcomes. They will begin testing predictive methods for heart failure in clinical practice over the next several years.”
Seton Healthcare (an IBM customer, actually) has already reaped the benefits of this exact type of analysis. I wrote about it in 2012:
“Following a CEO mandate to find better ways to detect congestive heart failure early in order to save the exorbitant costs of treatment as the disease progresses, [Seton Healthcare VP of Analytics Ryan] Leslie’s team analyzed a stockpile of data ranging from billing records to patient charts. It found that a distended jugular vein — something that can be spotted during any routine physical exam — is a particularly high risk factor.”
It’s likely we’re just seeing the tip of the iceberg of what’s possible with big data and health care, though. Obamacare places a heavy emphasis on electronic health records and better data collection, generally, and patients are now able totrack an increasing number of potentially valuable data points using smartphones and wearable devices. Health care is huge business tied to lots of IT spending, so if there’s data that can help health care organizations do their jobs better, there will be plenty of researchers and companies willing to help analyze it.
One of the cruelest truths about cancer is that even after you beat the disease, it can still come back to kill you. A tumor growing in the prostate gland, breast, or any other organ can shed cancerous cells into the blood. These cancerous seeds travel the body and can take root nearly anywhere, growing into a new cancer threat even after the initial cancer is treated.
The rule of thumb with cancer is that the earlier you can detect the disease, the more effective the treatment, and hence better potential outcomes.
Currently, doctors draw a patient's blood and analyze it using special antibodies to detect the presence of the seeds, called circulating tumor cells (CTCs). This works well if CTCs are present in large numbers, but may fail to detect smaller numbers released by earlier tumors.
Now, a team of engineers, scientists and doctors from Stanford is developing a mini-microscope that might be able to noninvasively detect the CTCs earlier than ever, allowing for earlier interventions.
"There has been a huge push to increase sensitivity," said Bonnie King, an instructor at Stanford School of Medicine. "We suspect that CTCs often circulate in numbers below our current threshold of detectability."
A major advantage with the microscopic technique, King said, is the ability to screen much larger volumes of blood, rather than just a small vial collected from a patient. This will be done using a method called in vivo flow cytometry – a laser-based technology for counting cells in a live subject.
A little empathy goes a long way in an overcrowded emergency room.You don’t have to be a medical professional to know that affordable healthcare in America is complicated business. The system is so (Rethinking affordable healthcare in America with...
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Electronic medical records. DNA sequencing. Big data. These technology trends are changing the way medicine is practiced today — but what’s coming next?
From artificial intelligence to natural language to processing to MEMS, here are some technologies that will change the future of healthcare.
Artificial intelligence/algorithm medicine
Predictive analytics tools that use data to help healthcare administrators identify high-risk patients and make efficient decisions are already in place in many hospitals. Now companies are developing decision support tools for clinicians that compare an individual patient’s data to large amounts of historical outcomes data.
Internet of things
This concept takes remote patient monitoring to the next level, involving multiple connected devices that can coordinate with each other through a wireless network without human intervention. Sharp, who’s in charge of clinical informatics research at Cleveland Clinic, says hospitals have just scratched the surface of this with smart infusion pumps and RFID tagging. “There’s potential for a lot of these things to talk to each other and raise alerts when something is out of whack, and potentially even detect infections,” he said.
Short for micro electro mechanical systems, MEMS involves the use of miniaturized sensors, actuators and electronics that are smaller than the thickness of a human hair. Such technology has already penetrated the research market, with speedier, more precise tools for biologists and chemists. Now companies like CardioMems and MicroCHIPS are working on commercial implantable devices that can transmit data outside of the body for clinical use. However, regulation remains a big question here.
Wearable medical devices
We’re not just talking about the fitness bands you wear around your wrist. We’re talking flexible electronics — lightweight, portable sensors that could be, for example, adhered to the skin to collect biometric data. Or swallowable (not technically wearable, but it’s the same idea) smart pills that let clinicians know when patients aren’t taking their medications. The hope is that these devices could help patients and clinicians manage chronic diseases.
Natural language processing
The medical scribe business is hot. But another way of easing the burden of collecting patient data – especially the kind that’s anecdotal – is also heating up. Some EHR vendors have embedded voice transcription technologies into their products, and more advanced products that give structure to unstructured data are on the way. Some say natural language processing could change the way we interact with healthcare data, the same way that Siri has changed the way people interact with their cellphones.
Nokia and XPRIZE are hunting for a medical tricorder, armed with $10 million as a reward, but this movement is much bigger than the contest. Sensors, mobile technology and at-home medicine meet in this concept, which calls for development of a portable screening device consumers could use to self-diagnose medical conditions a la Star Trek. Scanadu’s Scout is the most high-profile device under development, but there are dozens of teams across the world working toward this goal.
From targeted cancer drugs to molecular diagnostics, advances in genome sequencing are driving precision medicine. It’s defined by Pfizer as “an approach to discovering and developing medicines and vaccines that deliver superior outcomes for patients, by integrating clinical and molecular information to understand the basis of disease.”
Some use precision medicine synonymously with personalized medicine. Others say it’s a better term that captures the idea of personalized medicine more clearly: Not as medical care that’s tailored to an individual but rather the ability to classify individuals into smaller populations that might be more susceptible to certain diseases or respond to drugs differently. This term has been slowly gaining steam since 2011.
Time-consuming administrative tasks like medical billing, revenue cycle management and inventory management are prime targets for automating IT solutions. As more data becomes digital rather than paper-based, more opportunities open for innovation in this area to save time in hospitals and physician practices.
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