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Top Ten Tech Trends 2018: Health System Transformation Requires Rethinking Data Infrastructure

September 6, 2018
by David Raths, Contributing Editor
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Analytics teams are working with increasingly sophisticated data warehouses, data lakes
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Editor’s Note: Throughout the next week, in our annual Top Ten Tech Trends package, we will share with you, our readers, stories on how we gauge the U.S. healthcare system’s forward evolution into the future.

Once health systems got most of their data into electronic and structured format, the next logical step was the development of data warehouses and analytics platforms, and capabilities to learn from all that data. Today those efforts are still in their adolescence in many organizations, but investments in warehousing and analytics continues, with a goal of identifying and solving institutional inefficiencies and clinical variance.

Handling all this new data also requires CIOs to rethink their data infrastructure strategy with an eye on shrinking data centers, hybrid cloud and public cloud solutions.

Seeing all these analytics needs coming down the pike, Minneapolis-based Allina Health entered into a tight partnership with vendor Health Catalyst in 2015, in which Allina took an investment stake in the company and some Allina employees became Health Catalyst employees. “It allowed us to start to accelerate our capabilities in the data space, in terms of warehouse, analytics, toolsets and talent to maximize our potential,” says Jonathan Shoemaker, Allina’s senior vice president and chief information officer.

Among other things, he says, Health Catalyst developed data transformation tools on the back end that can take raw data sets from more than 70 different sources and bring them into the data warehouse in an efficient manner. “The cycle time on that used to be fairly long,” Shoemaker recalls.

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Now the health system is working to get better at analytics and change management. “You are only as good as your ability to execute on what the data says,” Shoemaker says. “We are thinking about how we can mature to the next level on our use of data at the physician level. We are starting to be able to put the power of data into the hands of individual providers.”

Jonathan Shoemaker

Besides the traditional enterprise data warehouse, some health systems are starting to create data “lakes,” which may contain new data types not found in traditional hospital clinical and financial data sets. “With a data warehouse you have to know ahead of time and plan out what the data structure is going to be so you can insert it,” explains Michael Gil, chief technology officer with Temecula, Calif.-based consulting firm Axene Health Partners. “With a data lake, you drop the data in in whatever file format it is in. It might be environmental or geographical data. You can start to pull that together without a pre-defined schema.”

Vijay Venkatesan, former senior vice president and chief data officer at Seattle-based Providence St. Joseph Health, told Healthcare Informatics in June 2018, when he was still working at the health system, that Providence created a data lake where it invited its other data asset owners to contribute their data into the lake, in exchange for data they want or don’t have access to. “We created a culture of convergence, to bring data in one place and share each other’s information so that the collective organizations benefit.”

Vijay Venkatesan

The second step, he says, involves creating a harmonizing data layer. “Think about it as your iTunes data catalog, where your albums in iTunes are categorized by rock, pop, alternative, etc. It’s the same idea. Now that we have data in one place, how do we create albums from the data?”

Shoemaker says that bringing in social determinant data is a key priority for Allina this year. “Consumer insights is another one we have put energy into,” he explains. “Hospital-centric data is necessary, but thinking of it from a retail experience level and understanding your role in the market you are trying to serve is relatively new to healthcare. We are trying to build that insights practice.” Another strong focus is on patient-reported outcomes, he adds.

Cynthia Burghard, research director of IDC Health Insights in Framingham, Mass., says CIOs tend to have a more short-term focus and are looking for analytics solutions that solve specific problems. If a CIO in a health system with tiny margins asks to invest $5 million for the next five years to build a data lake, they might be out of a job, she says. “But if that same CIO hears that the health system is getting penalized heavily for its readmission rates and can find something to help solve that problem analytically, that is a much more compelling argument.” In other words, CIOs are less focused on pristine infrastructure to do analytics than on getting help to solve today’s problems.

Of course, there is a personnel and talent management side to analytics as well. During a recent webinar talk, Shakeeb Akhter, director of the enterprise data warehouse at Northwestern University’s Feinberg School of Medicine, described what has worked well there. “When you’re first starting down the data warehousing and analytics path, it is important to find people who have a blend of experience with clinical operations, with the EHR workflows, and some business intelligence background,” he says. “We’ve hired people who have some sort of clinical background or have been application analysts. We made them data architects and started training them to think about things on a much larger scale from a data warehousing perspective.”

The proliferation of data, including large data sets involving genomics and research, is forcing CIOs to reconsider the traditional data center model and focus more on hybrid cloud and public cloud offerings from vendors such as Amazon and Microsoft. A recent blog post by David Cappuccio, a Gartner research vice president, was titled “The Data Center Is Dead.”  He wrote that “the role of the traditional data center is being relegated to that of a legacy holding area, dedicated to very specific services than cannot be supported elsewhere, or supporting those systems that are most economically efficient on-premises.” He wrote that Gartner estimates that by 2025, 80 percent of enterprises will have shut down their traditional data center, versus 10 percent today.

In healthcare, however, one challenge is that many departmental systems, such as lab systems, were developed in older architectures. “You can’t just press a button and throw it up into the cloud,” IDC Health Insights Burghard says. “The application vendor has to modernize the software. Ripping and replacing a pharmacy system is not top of mind for CIOs these days. If they can limp along with it, they probably
are going to.”

Allina serves as a good example. It built a data center six years ago, which made business sense at the time, Shoemaker says. When it needed a second new data center, it chose a co-location design. “So far, we haven’t moved away from data center management, but we are always looking at when cloud-based management of our data stores makes more sense than on-premises solutions.” It requires regular re-assessment, he adds, “because the world does change every 18 months or so.”


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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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