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Oakland, California-based Alameda Health System has named its new chief information officer. Mark Amey will relocate to the Bay Area from San Diego, where he was most recently associate CIO at University of California San Diego Health. Alameda Health appointed Amey in the same week that Sanford Health named former VA Secretary David Shulkin, MD, as its chief innovation officer. Much like Shulkin, Amey brings considerable familiarity with electronic health record implementations. Alameda cited its work to roll out a $200 million Epic EHR across the five-hospital public health system as among the reasons it brought Amey onboard. Amey has been working in health IT for more than two decades. Before his stint at UC San Diego, he served as Chief Technology Officer during another Epic rollout at Lucile Packard Children’s Hospital-Stanford Health. Prior to that, he also held CIO positions at University of Southern California Health, Ascension Health and Adventist Health. In San Diego, his day-to day responsibilities included oversight of its infrastructure teams, the project management office and security operations. It was at UCSD that Amey helped transition its on-premise Epic system to a hosted cloud model. The mover not only helped the health system be more agile and maintain disaster recovery capabilities, he explained at the time, but "by creating greater operational efficiencies, we can invest more time and resources in patient care." Other areas of expertise include management of outsourced IT vendors, conversion of services to in-house operations and more. "I am excited to join Alameda Health System at this pivotal time in the history of the organization," said Amey. "Having gone through similar projects in the past, I know this implementation will transform the care we provide, including the exchange of information and communications with patients and medical colleagues." Alameda Health partners with five other health systems in the Bay Area on an interoperability project designed to reduce emergency department usage but also boost the ED care that is delivered. With its new Epic rollout, it's hoping to spur easier data sharing among its own five hospitals. "Mark’s in-depth knowledge and impressive experience align with the future direction of Alameda Health System," said Alameda's CEO Delvecchio Finley in a statement. "As CIO, we are confident he will guide the organization through a smooth transition to electronic health records that will enhance our commitment to serve our patients with highest-quality care." Twitter: @MikeMiliardHITN Email the writer: mike.miliard@himssmedia.com

Former U.S. Department of Veterans Affairs Secretary David Shulkin, MD will join Dakotas-based Sanford Health as chief innovation officer. Shulkin will serve as lead innovation administrator, focusing on research and Sanford’s Imagentics, Chip, Profile and World Clinic, the system said. He’ll also continue the development of the health system’s clinical development and will serve as strategic advisor on national growth strategy and public policy. Shulkin will also join the Sanford International Board as a director and serve as an ambassador for Sanfords’s domestic and international projects. Sanford’s CEO Kelby Krabbenhoft called Shulkin “one of the most talented healthcare leaders in the country.” “His unique perspective, clinical expertise and powerful voice will further Sanford Health’s continued development and diversification, which is so critical to our ability to bring new treatments and cures to the patients we serve,” Krabbenhoft said in a statement. President Donald Trump fired Shulkin in March, after months of turmoil within the agency and reports Shulkin had fallen from Trump’s graces. His removal came amid a broader staffing shakeup within the presidency, including the removal of National Security Adviser, Lt. Gen. H.R. McMaster and Secretary of State Rex Tillerson. However, in his brief tenure, Shulkin helped to pass 11 Congressional bills that were all designed to bring much-needed change to the VA. He also launched a 24-hour hotline for veterans’ complaints, created an online platform that allows patients to track wait-times at the VA and jumpstarted the Anywhere to Anywhere telehealth program. Shulkin said Sanford was an “obvious choice” for its innovation and clinical integration around precision medicine. He received his MD from the Medical College of Pennsylvania, completing an internship at Yale University School of Medicine and a residency and fellowship at the University of Pittsburgh Presbyterian Medical Center. .jumbotron{ background-image: url("https://www.healthcareitnews.com/sites/default/files/u2231/Innovation-month-jumbotron.jpg"); background-size: cover; color: white; } .jumbotron h2{ color: white; } Focus on Innovation In September, we take a deep dive into the cutting-edge development and disruption of healthcare innovation. Twitter: @JF_Davis_ Email the writer: jessica.davis@himssmedia.com

The machine learning model uses 600 variables with patient's data whereas human-constructed models made predictions based on 27, researchers say.

Mercy Technology Services, the IT division of the sprawling St. Louis-based health system, has developed a new cloud-based imaging platform and is commercializing it for other hospitals to deploy. The picture archiving communication system comprises best-of-breed enterprise viewer, vendor neutral archive, workflow orchestrator, speech recognition and reporting, according to Mercy, bundled as a secure software-as-a-service model aimed a small and midsize hospitals. It's aimed as a way to help hospitals drive efficiency with their imaging processes, replacing outdated and far-flung PACS systems, that require radiologists to spend too much time tracking down imaging reports or switching between stations. Cloud-based PACS can allow for big time savings and cost efficiencies at cash-strapped small hospitals, such as the one in rural Kansas we reported on this past month, which was able to cut its imaging costs in half. Mercy, which operates 40 hospitals of various sizes across four states, consolidated its own imaging platform with help from MTS, distilling nine legacy PACS systems into a single hosted technology. The system, which combines server-side image processing from Visage, a workflow orchestrator from Medicalis and speech recognition from Nuance, has helped radiologists at the health system decrease turnaround time for their reports by up to 50 percent. Mercy is a longtime health IT leader, and one of the earliest adopters of Epic. Its technology knowhow over the years has enabled it to innovate new advances in telehealth, advanced analytics and more as it has scaled up its infrastructure. It's also allowed it to be able to share its expertise and tools with other providers. Its Epic accreditation enables allows it to share Epic and other technology with smaller hospitals. "We're a little bit unique from the standpoint that Mercy sells its IT services to other providers," Mercy CIO Gil Hoffman told Healthcare IT News in 2017. "We have commercialized our IT, and that has taken a lot of work, bringing some other health systems not only into our Epic services but our hosting services as well." Now, as the latest example of its ability to commercialize and host IT systems for other hospitals, MTS will offer this PACS-as-a-service, whether bundled or by the component, to hospitals across the country. "Having everything together and viewable with the click of a button – all prior studies, all modalities – means radiologists aren’t waiting and neither are patients," said Steve Bollin, Mercy’s vice president of radiology support services, in a statement For his part, Hoffman touted the PACS as an efficient and affordable platform, developed as a result of Mercy's own efforts to innovate its technology and workflows. .jumbotron{ background-image: url("https://www.healthcareitnews.com/sites/default/files/u2231/Innovation-month-jumbotron.jpg"); background-size: cover; color: white; } .jumbotron h2{ color: white; } Focus on Innovation In September, we take a deep dive into the cutting-edge development and disruption of healthcare innovation. Twitter: @MikeMiliardHITN Email the writer: mike.miliard@himssmedia.com

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Imagine knowing, in real time, whether a patient will suffer a surgical infection as a surgeon closes up a wound. That's the kind of clinical situation that machine learning is enabling at the University of Iowa Hospitals & Clinics. In a 3-year pilot study ending in 2016, in a subset of general and colorectal surgery, the health system's innovation with AI analytics has led to a 74 percent reduction in surgical site infection. At scale, this would translate to approximately $1.2 million in cost savings – not including savings from value-based purchasing because of the reduced surgical site infection rate. Iowa’s work with comes as more and more hospitals and tech vendors are undertaking innovative initiatives with machine learning and artificial intelligence. Johns Hopkins for instance, is using deep learning to improve how it handles pancreatic cancer and Amazon Web Services is harnessing machine learning to enable customers to better treat depression. Co-developing machine learning The university is co-developing the machine learning technology with vendor DASH Analytics. The system is called the DASH Analytics High-Definition Care Platform, or HDCP. Its proprietary design uses machine learning as it provides valuable data, metrics and decision support at critical moments during the point-of-care timeline. HDCP, the university said, helps lower the rate of surgical infections, reduces the risk of requiring a blood transfusion during surgery, saves lives from brain failure and saves lives from unrecognized sepsis. The technology combines several features, said John Cromwell, MD, associate chief medical officer and director of surgical quality and safety at the University of Iowa Hospitals & Clinics. "The system uses curated knowledge of where and when specific critical decisions that drive outcomes are being made by providers for numerous clinical conditions where there is massive room for improvement," he explained. "It is a machine learning system that integrates with the EHR using industry-standard and vendor-specific APIs and in real time measures individual patient risks and evaluates appropriate best practice based upon these risks." With those two features, HDCP integrates decision support within the provider's EHR workflow, and it generates feedback on how their use of the data changes their patient's outcomes, reinforcing high-value practices, he said. The system works silently in the background, monitoring for specific points in patient care where decision support may improve patient outcomes. At that point in time, the decision support becomes visible to the clinician or other front-line provider within their usual workflows in the EHR. It will present them with the specific risk for their specific patient along with actions to potentially mitigate that risk. "The risks are assessed by using best-in-class machine learning algorithms that use both real-time and historical data on individual patients," Cromwell said. "These risk models are calibrated specifically to patients in each individual hospital using the platform." Here's how it works The surgical site infection reduction module in HDCP is integrated within the World Health Organization Surgical Safety Checklist that virtually all hospitals use during surgery. The module is activated near the completion of a surgery as the circulating nurse is going through his or her routine closing checks. At the time of module activation, real-time data from the EHR such as the surgeon, case duration or estimated blood loss flows into the platform and is combined with historical data on the patient. All of this data then flows into the surgical site infection prediction model. "The machine learning model calculates the infection risk and links this risk to specific interventions that the surgeon may take at the time of wound closure to reduce the infection risk," Cromwell explained. "The risk information and possible interventions are then presented in an interactive interface back to the nurse at her workstation – the whole process takes mere seconds to complete – who then delivers the information to the surgeon." Using a single click, the nurse records whether the surgeon used the decision support recommendations. Ultimately the patient's outcome with respect to surgical site infection is returned to the platform and used to generate an aggregate report for the surgeon regarding his or her outcomes when recommendations were or were not used, thus reinforcing the use of appropriate decisions. "It is very difficult for surgeons to integrate the information necessary to determine whether a patient is at high risk for a surgical site infection," Cromwell said. "There are certainly obvious cases where there is a break in technique, contamination, or very high-risk patient factors, but these are the minority of the cases." There are interventions that can be done at the time of wound closure, but these can be costly or invasive. Would one do these interventions to 100 percent of patients if only a fraction can actually get a surgical site infection? "Selectively using these interventions in patients where it is warranted by objective markers of risk maximize the therapeutic effect, while minimizing the cost and potential risks to patients," Cromwell explained. "In this case, we were able to selectively use negative pressure wound therapy on patients with markers of high risk to achieve the 74 percent reduction. Without the system, we could not have known objectively which patients to use this costly therapy on." Ultimately, machine learning is critical for integrating hundreds or thousands of variables for individual patients in order to objectively measure risk, he added. "Integrating such massive amounts of information that is impossible for any individual caregiver to perform," said Cromwell. "And no matter how much experience one has, the exponential increase in medical knowledge makes it impossible for a caregiver to assimilate all of the data necessary to consistently apply best practices in every situation." A systematic approach to mitigating adverse outcomes or complications requires that one systematically identify the risks, he added. Machine learning algorithms, with few exceptions, are able to do this much more effectively than humans on a consistent basis, he said. "This removes the variation in risk assessment that one may get between different physicians," he said. "Once a provider has an objective assessment of risk, then they may move on to mitigating that risk. When best practices are known and supported by data, machine learning can identify which patients these best practices should be applied to, in a consistent manner. By approaching risks objectively and systematically, we can have an effect greater than any pharmaceutical can provide." Twitter: @SiwickiHealthIT Email the writer: bill.siwicki@himssmedia.com

Cerner President Zane Burke, who first joined the company in 1996 and held several executive roles there before being named president, will step down on Nov. 2. John Peterzalek, Cerner's executive vice president of worldwide client relationships, will take on Burke’s responsibilities, with the title of Chief Client Officer, the company said. Over his two-decades at Cerner, Burke had a range of executive positions, ranging from sales and finance to technology implementation and support. He was named president five years ago, reporting to Cerner founder and CEO Neal Patterson, who died in 2017. Brent Shafer, former CEO of Philips North America, was named CEO of Cerner early this year. In recent years at Cerner, Burke was instrumental in helping the company win two massive electronic health record modernization contracts, from the Departments of Defense and Veterans Affairs. In addition to helping grow the company's client base, he's also helped innovate its technology, whether it's by partnering with Apple to help move the needle on patient engagement and interoperability or touting the value of open APIs, a focus on consumerism or more innovative strategies for revenue cycle management. "We thank Zane for his contributions to Cerner across more than two decades," said Shafer in a statement. "Zane leaves the company with a strong client focus and commitment to continued innovation, partnership and sustainable growth deeply ingrained in our culture and leadership philosophy." Burke added that is he pleased with the disruptive accomplishments and positive change Cerner and its clients have achieved. "Complex and evolving challenges remain, and Cerner is positioned to continue innovating for the good of consumers and health care providers," Burke said.   This past week, the Kansas City Business Journal reported that Burke had exercised options to sell almost $10 million in company stock. Twitter: @MikeMiliardHITN Email the writer: mike.miliard@himssmedia.com