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RSNA 2017: The Year of Image Augmentation

December 5, 2017
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Last week was the conclusion of the annual Radiological Society of North America (RSNA) in Chicago.  The RSNA has always been an imaging-heavy affair, but this year it seems to have been afflicted with a dose of augmentation.  While imaging is still the primary focus, it seems that radiology has awoken to the age of population health management and value-based care, and vendors are beginning to place greater emphasis on how imaging diagnostics can be augmented by artificial intelligence and machine learning.

Artificial Intelligence/Machine Learning

Everywhere you looked there were examples of how artificial intelligence (AI), or machine learning could improve the diagnostic capabilities of the radiologist.  To be fair, most of these discussions emphasized “works-in-progress,” describing applications still in development.  But it is evident that vendors are beginning to understand the reality of today’s environment, and they are actively pursuing ways to assist the radiologist. 

In past years, there has been buzz about the prospects of AI displacing the radiologist for primary diagnosis.  That seemed to be missing from this year’s meeting, with the primary emphasis on assisting the radiologist with AI/machine learning tools to make them more productive, or as some have coined it, “Augmented Intelligence.” 

Most vendors seem to be struggling with how best to balance their own developments with those of third parties and academic centers through application program interfaces (API’s) or partnerships.  This is refreshing, as in the past there has sometimes been a “not invented here” mentality amongst the vendors

One major hurdle to be overcome is the Food and Drug Administration (FDA), as in the past the FDA has tended to require pre-market approval of new applications that involve patient image applications.  The balance is trading off the fear that an application might adversely affect patient safety with the speed of getting such applications to market.

Workflow Orchestration

As providers continue to consolidate in this ever-changing healthcare environment, vendors continue to address how to accommodate reading imaging studies across multiple facilities, and multiple PACS (Picture Archive and Communications System).  The most common approach to this has been to present the radiologist with an “enterprise” or “unified” worklist. 

The typical approach to doing so is by means of rule sets for assignment of studies to a radiologist based on such parameters as the type of modality to be read, the shift they might be on, specific SLA’s (service level agreement) for determining the time interval within which a study must be read, etc.  Vendors are applying AI/Machine Learning to worklists to more intelligently present the information to the radiologist to assist reading. 

For example, some vendors are intelligently mining the EHR (electronic health record) for related patient and study information that might be relevant to the radiologist reading that study.  Clinical, pathology, and surgery results might be made available to the radiologist to effect a more accurate and efficient diagnosis.  Another novel approach to this is to intelligently present studies to the radiologist.  For example, of the radiologist just completed reading an MRI of the knee, and there is another MRI of the knee waiting to be read.  There may be benefit in forwarding this study next to the same radiologist to read. 

Another approach might be to eliminate the worklist altogether.  By means of AI/Machine Learning, it may be possible to consider a number of parameters in automatically presenting the next case to the radiologist, without a worklist of waiting studies.

While many vendors are experimenting with workflow orchestration, the reality is that many of the EHR vendors are encompassing this function into the EHR – the so-called EHR-centric PACS workflow.  If the PACS vendors can demonstrate added value to intelligent worklists, they might be able to offset the worklist actually being the purveyance of the EHR vendor.

Clinical Decision Support

Efforts to grow the use of clinical support tools in the pre-authorization process are also coming to the forefront.  Led by companies such as the National Decision Support Company (http://nationaldecisionsupport.com/), which is licensed to market the American College of Radiology’s (ACR) decision support criteria, more studies are being scrutinized by decision criteria at the time of the order. 

Unfortunately, it seems as if most of the imaging companies don’t see a key role in this for them, choosing instead to work on “back-end” applications to assess appropriate use criteria (AUC).  Most vendors are aware of the impending impact of the Protecting Access to Medicare Act of 2014 (PAMA) legislation that eventually will require physicians ordering certain imaging services to consult appropriate use criteria applicable to the imaging modality.  However, the legislation has been pushed back in terms of implementation time frame.  While PAMA will ultimately impact how studies are ordered, it will have more impact on the EHR vendors than the imaging informatics vendors according to several vendors.

Often overlooked is the value radiology can add via mechanisms to provide feedback from back-end diagnostic practices to the front-end decision support criteria, thereby adding value to decision support.

Cloud

The cloud is becoming more relevant to imaging, particularly with respect to augmenting applications.  Rather than purchasing each AI application, it may be advantageous for providers to consider utilizing cloud-based services on a subscription basis, according to several vendors.

Google (https://www.google.com/intl/en_us/health/about/) has announced several relationships, the latest with Change Healthcare (https://www.prnewswire.com/news-releases/change-healthcare-announces-strategic-relationship-with-google-cloud-300561591.html) in which Change Healthcare will leverage Google’s cloud for image analytics.

Other

Another interesting trend is the transference of advanced imaging technologies down to the acquisition device, such as GE Healthcare’s (https://www.intel.com/pressroom/archive/releases/2009/20090402corp.htm) intent to embed Intel graphical processing capability within its imaging equipment for more rapid advanced visualization at the point of acquisition for more timely and productive decisions. 

This is an exciting time for imaging!  There is a growing need to provide greater interoperability with EHR’s, while at the same time utilize artificial intelligence/machine learning to enhance the diagnostic process.  The radiologist isn’t quite extinct, and these developments will assure they have a role to play in healthcare’s future.

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/article/analytics/how-data-driven-approach-can-bolster-fight-against-opioid-abuse

How a Data-Driven Approach Can Bolster the Fight Against Opioid Abuse

October 12, 2018
by Steve Bennett, Ph.D., Industry Voice
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I want to tell you about Andy. Andy’s mom, Pam, is a colleague of mine. Growing up an only child, Andy was a happy kid. He was a straight-A student, loved to play the violin, and spent a year as an exchange student in Europe. Andy had two loving parents. But Andy suffered an injury in college, and needed to have some minor surgery performed to repair his sinuses. Following that surgery, his doctor prescribed opioid pain medication for him, to which he became addicted. Despite several years of effort, Andy was unable to shake the addiction, and tragically lost his life to a heroin overdose two years after his surgery. This was a normal kid with a normal family, like mine, and like yours.

Andy’s story is an important story. The opioid epidemic has led to the deadliest drug overdose crisis in the history of the United States, killing more than 64,000 people in 2016 alone – the last year numbers were available. This is a true national epidemic, and one that continues to get worse. For the first time in nearly 60 years, life expectancy for Americans has dropped for two years in a row due to the opioid epidemic.

The opioid crisis has been so difficult to curtail, in part, because of the inability to integrate data from various stakeholders and systems. With so many players and data sources, today’s information is partial, fragmented, and often not actionable.

While this disconnect applies directly to the opioid epidemic it is a systematic problem that affects the healthcare community at large. Better data and analytics can help develop better treatment protocols for a wide array of medical and public health challenges that affect the general public. For opioids, that could be to develop better pain management programs or for better, more-targeted remediation and rehabilitation for those that become dependent on drugs.

A Data-Driven Healthcare Approach: Making Information Real

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Ample data has been collected on the opioid epidemic, but disparate sources are not communicating with one another. Addressing this disconnect and lack of communication is something that can provide researchers, lawmakers and the public with improved insights.

Data-driven healthcare can help provide this guidance by using available data and analytics to help create programs that can make a tangible difference on population areas that need the most help. By looking at the data, lawmakers, hospital administrators and doctors can begin to make impactful changes throughout the system.

While much can be learned from this data, most of it is not being analyzed in a way that brings true benefits. It has been put in a silo and/or it is not organized in a way that is interoperable with other data systems.

The 21st Century Cures Act, which established the Health Information Technology Advisory Committee, shows the commitment of national leaders to improving healthcare information sharing. Analytics can take this data and turn it into something real. Subsequent visualization of this analyzed data presents the information in a way that can truly tell a story, making sense of data that analysts sometimes miss. Analytics can arrange and organize data in different ways and pick up previously undetected trends or anomalies. This information can be turned into real programs that produce real outcomes for those affected.

The data management and integration process can also help us understand where our knowledge gaps are, revealing flaws in data quality and availability. Organizations may learn that they lack sufficient data in a certain area where they want to learn more, but are currently limited. They can then make changes to data collection efforts or seek out different sources to fill these larger gaps. They can resolve data quality issues across systems and arrive at a consistent, reliable version of the truth.

As organizations get better at assembling and managing the data, automating processes to generate standard reports and file exchanges can ease the burden on analysts. Streamlining the user interfaces for prescription drug monitoring programs and other systems allows analysts and medical informatics staff to spend less time working on the data itself and more time enabling and encouraging the use of predictive modeling and “what-if” scenario capabilities.

Helping to Solve a Problem

The national opioid epidemic is a terrible and complex issue. It is not something that can be solved with just one action, approach or program. It is a layered issue that will require systematic changes to how patients are treated and how the healthcare system operates. Some of the nation’s best continue to work on providing operational solutions to these problems, but as the statistics show, they need more help.

A data-driven approach can be that help. Using data analytics to find better and deeper insights into the root problems of this epidemic can help decision-makers make real change. While opioids are the focus now, there will come a day when a new problem emerges. Having data and analytic solutions in place can prepare these organizations to tackle these future challenges as well.

64,000 people died in 2016 as a result of opioid abuse. But 64,000 is more than a large number – it’s also Andy and his family. With analytics and a data-driven approach, government and healthcare leaders can make better decisions that can help people in need.

Steve Bennett, Ph.D., is the director of SAS' global government practice. He is the former director of the National Biosurveillance Integration Center within the Department of Homeland Security


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DOJ Approves CVS-Aetna $69B Merger, On Condition Aetna Divest Part D Business

October 10, 2018
by Heather Landi, Associate Editor
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The Department of Justice (DOJ) has approved a $69 billion merger between mega-pharmacy retailer CVS Health and health insurer Aetna, after Aetna entered into an agreement with the DOJ to divest is Medicare Part D prescription drug plan business.

According to a statement released by the DOJ on Wednesday, the settlement, in which Aetna will sell off its Part D business, was a condition of the merger’s approval and resolves the DOJ’s “competition concerns.”

The deal is the latest in a wave of combinations among healthcare companies, including many pharmacy benefit manager (PBM) and insurer integrations. Last month, the Justice Department approved Cigna’s $67 billion takeover of Express Scripts.

CVS Health announced in early December 2017 its intention to acquire Aetna in a $69 billion-dollar merger, marking the largest ever in the health insurance industry. Woonsocket, R.I.-based CVS operates the nation’s largest retail pharmacy chain, owns a large pharmacy benefit manager called Caremark, and is the nation’s second-largest provider of individual prescription drug plans, with approximately 4.8 million members. CVS earned revenues of approximately $185 billion in 2017. Aetna, headquartered in Hartford, Connecticut, is the nation’s third-largest health-insurance company and fourth-largest individual prescription drug plan insurer, with over two million prescription drug plan members. Aetna earned revenues of approximately $60 billion in 2017.

Following news of the deal back in December, there was speculation that antitrust regulators might not approve the deal. Back in January 2017, a federal judge blocked a merger that would have resulted in Aetna acquiring Louisville, Ky.-based insurer Humana, which at the time was the largest acquisition of its type in the history of health insurance in the U.S., reported at $37 billion. At the time, U.S. District Judge John D. Bates in Washington said that proposed deal would “violate antitrust laws by reducing competition among insurers.” Similarly, a proposed combination of two other health insurers, Anthem and Cigna, was also shot down last year.

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According to the DOJ’s statement issued today on the CVS-Aetna deal, the Justice Department’s Antitrust Division had significant concerns about the anticompetitive effects of the merger with regards to the Medicare Part D businesses. CVS and Aetna are significant competitors in the sale of Medicare Part D prescription drug plans to individuals, together serving 6.8 million members nationwide, according to the DOJ.

In a press release issued today, CVS Health said, “DOJ clearance is a key milestone toward finalizing the transaction, which is also subject to state regulatory approvals, many of which have been granted.” CVS Health's acquisition of Aetna remains on track to close in the early part of Q4 2018, the company said.

“DOJ clearance is an important step toward bringing together the strengths and capabilities of our two companies to improve the consumer health care experience,” CVS Health president and CEO Larry J. Merlo, said in a statement. “We are pleased to have reached an agreement with the DOJ that maintains the strategic benefits and value creation potential of our combination with Aetna. We are now working to complete the remaining state reviews.”

Merlo also said, “CVS Health and Aetna have the opportunity to combine capabilities in technology, data and analytics to develop new ways to engage patients in their total health and wellness. Our focus will be at the local and community level, taking advantage of our thousands of locations and touchpoints throughout the country to intervene with consumers to help predict and prevent potential health problems before they occur. Together, we will help address the challenges our health care system is facing, and we'll be able to offer better care and convenience at a lower cost for patients and payors.”

Following the close of the transaction, Aetna will operate as a standalone business within the CVS Health enterprise and will be led by members of its current management team.

The American Medical Association (AMA), an industry group that has been opposed to the merger, issued a statement saying the agreement that Aetna divest its Part D business doesn't go far enough to protect patients.

"While the AMA welcomes the U.S. Department of Justice (DOJ) requiring Aetna to divest its Medicare Part D drug plan business, we are disappointed that the DOJ did not go further by blocking the CVS-Aetna merger," Barbara L. McAneny, M.D., president, American Medical Association, said in a statement. "The AMA worked tirelessly to oppose this merger and presented a wealth of expert empirical evidence to convince regulators that the merger would harm patients. We now urge the DOJ and state antitrust enforcers to monitor the post-merger effects of the Aetna acquisition by CVS Health on highly concentrated markets in pharmaceutical benefit management services, health insurance, retail pharmacy, and specialty pharmacy."

Agreement with DOJ Resolves “Competition Concerns”

Late last month, Aetna agreed to sell its Part D business to WellCare. According to a Securities and Exchange Commission (SEC) filing from WellCare Health Plans last month, WellCare entered into an asset purchase agreement with Aetna to acquire the company’s entire standalone Medicare Part D prescription drug plan business, which has 2.2 million members. According to the agreement, Aetna will provide administrative services to and retain the financial risk of the Part D business through 2019. In that filing, it states that Aetna is divesting its Part D business as part of CVS Health’s proposed acquisition of Aetna.

“Today’s settlement resolves competition concerns posed by this transaction and preserves competition in the sale of Medicare Part D prescription drug plans for individuals,” Assistant Attorney General Makan Delrahim of the Justice Department’s Antitrust Division, said in a statement. “The divestitures required here allow for the creation of an integrated pharmacy and health benefits company that has the potential to generate benefits by improving the quality and lowering the costs of the healthcare services that American consumers can obtain.”

In its statement, the DOJ referred to WellCare as “an experienced health insurer focused on government-sponsored health plans, including Medicare Part D individual prescription drug plans.”

The Department’s Antitrust Division, along with the offices of five state attorneys general, today filed a civil antitrust lawsuit in the U.S. District Court for the District of Columbia to enjoin the proposed transaction, along with a proposed settlement that, if approved by the court, would fully resolve the Department’s competitive concerns. The participating state attorneys general offices represent California, Florida, Hawaii, Mississippi, and Washington.

In a complaint filed to the U.S. District Court, DOJ attorneys argued that without the divestiture, the combination of CVS, which markets its Medicare Part D individual prescription drug plans under the “SilverScript” brand, and Aetna would cause “anticompetitive effects, including increased prices, inferior customer service, and decreased innovation in sixteen Medicare Part D regions covering twenty-two states.” DOJ attorneys also argued that the loss of competition between CVS and Aetna would result in “lower-quality services and increased costs for consumers, the federal government, and ultimately, taxpayers.”

Under the terms of the proposed settlement, Aetna must divest its individual prescription drug plan business to WellCare and allow WellCare the opportunity to hire key employees who currently operate the business.  Aetna must also assist WellCare in operating the business during the transition and in transferring the affected customers through a process regulated by the Centers for Medicare and Medicaid Services (CMS).

 


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A Data-Driven Effort to Tackle Indiana’s COPD Problem

October 9, 2018
by Rajiv Leventhal, Managing Editor
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One patient care organization in Indiana has leveraged a robust data analytics platform to reduce avoidable COPD readmissions and improve the overall health of the community

Although reduction in avoidable readmissions after chronic obstructive pulmonary disease (COPD)-related hospitalizations is a national objective, in one Indiana community it’s moved its way up to the very top of the healthcare priority list.

In Jackson County, Indiana, the COPD population is roughly two times the national average. And considering that COPD is the third-leading cause of death in the U.S., working to fix the problem has taken precedence at local hospitals—including Schneck Medical Center, a community hospital in Seymour. Says Susan Zabor, vice president of clinical services at the medical center, “We have a high obesity population and a high smoking population, so in Jackson County, COPD is very prevalent. When we looked at our 2014 data, we knew it was an issue and we knew that it was a high-volume diagnosis for us, ranking second in our [hospital] readmissions.”

Indeed, at the time, Schneck Medical Center had a raw readmissions rate of nearly 14 percent for the specific COPD patient population, and these re-hospitalizations were leading to substantial added readmissions costs—upwards of $300,000 per year, according to Zabor. “We needed to put a focused intervention in place,” she attests.

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Susan Zabor

The fines for failure to meet the Centers for Medicare & Medicaid Services’ (CMS’) avoidable readmissions reduction criteria, as part of the government’s Hospital Readmission Reduction Program (HRRP), focus on six conditions: heart attack, congestive heart failure, pneumonia, COPD, elective hip and knee replacements, and for the first time starting in 2016—coronary artery bypass graft surgery. The current focus in the HRRP is on readmissions occurring after initial hospitalizations for these selected conditions, and hospitals with 30-day readmission rates that exceed the national average are penalized by a reduction in payments across all of their Medicare admissions.

As such, it’s clear that in healthcare’s future of value-based care, treating patients outside of an organization’s four walls will be critical to an organization’s success. What’s more, drilling down into the data and being able to specifically predict and target patients who are at high risk for readmissions has become a key point of emphasis for many hospitals.

At Schneck Medical Center, clinical IT leaders launched a data analytics initiative with IBM Watson Health, whereby they were able to analyze treatment patterns, costs, and outcomes data for their own hospital and compare those with peer group hospitals around the country. It was this analysis which showed that Schneck was experiencing much higher than average numbers of complications, readmissions, and patient deaths related to COPD.

Zabor notes that the hospital was “doing well on process measures and publicly-reported measures, but we weren’t doing so well on some bigger issues like complications, mortality and length-of-stay, and we leaned on CareDiscovery [a Watson Health solution] to give us actionable data that was as close to real time as possible to help us improve.”

Using this data, hospital leadership was able to pull together teams focused on closing those gaps. Schneck’s organizational efforts for COPD patients included developing a long-term care practice, which currently includes a physician medical director, a full-time physician, three nurse practitioners and two medical assistants, as well as the hospital’s respiratory care department. This team makes weekly respiratory care visits, incorporates sleep studies into its observations and conducts patient discharge planning. In addition, the hospital put in place new protocols that included the installation of a transition team to help with patient discharge, follow-ups with recently discharged patients, and annual facility education regarding COPD.

Indeed, the data available in the Watson Health’s CareDiscovery solution helped the hospital focus efforts to improve care for COPD patients, eventually resulting in an 80-percent reduction in its unplanned COPD readmission rate and hundreds of thousands of dollars in savings—representing a 99-percent decrease in costs related to readmissions.

“We started doing a better job of managing patients’ chronic illness in whatever setting they were in— be it long-term care, home care, or primary care. Before long, they didn’t need to come into the hospital,” Zabor says. To this end, the hospital also witnessed a 55-percent decrease in patients admitted with a COPD diagnosis from 2014 to 2017. Zabor notes that reducing primary admissions actually was an unplanned result of the organization’s efforts, but one they were happy with nonetheless.

As many hospitals and health systems remain in a position today in which they are straddling two payment worlds—fee-for-service and pay-for-performance—one might ponder if it’s truly in the organization’s best interest to keep patients away. But Zabor says that for Schneck Medical Center’s executive leadership, it was never a question. “For our patients and our community, keeping them out of the hospital is the best thing to do, whether you are making money or not,” she says.

“Zabor adds, “We [do have] one foot in value and one in volume, which is difficult, but we have a patient-first culture here. Yes, have a finance pillar, but it does not overpower our quality of care or customer experience pillars, which all support that patient-first culture.”

 

 


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