Hospitals and health systems are looking at AI-enabled solutions that target their most urgent pain points: staffing shortages, clinician burnout, rising costs, and patient bottlenecks. These operational realities keep leadership up at night, and AI solutions must directly address them. For instance, hospitals and health systems are eager for AI tools that can reduce documentation burden for physicians and nurses. Natural language processing (NLP) solutions that auto-generate clinical notes or streamline coding to free up time for direct patient care are far more compelling pitches than generic efficiency gains. Similarly, predictive analytics that help optimize staffing levels or manage patient flows can directly address operational workflow and improve throughput.

Building a new smart hospital or smart room in a hospital presents the opportunity to create market differentiation and grow market share. In planning for new construction, many organizations think about offering state-of-the-art clinical technology, and increasingly organizations are also thinking about the patient's experience as a differentiator. The building of a new tower for a health system is an investment that brings that health system distinction and market differentiation. It is an opportunity to invest in cutting-edge clinical technology and architectural design to attract patients and talent.. But while there is no shortage of transformative clinical technology, much of the industry continues to struggle to provide some of the most basic comforts to patients in a modern way.

During the inaugural HIMSS State of Healthcare digital event on Tuesday, Thomas Kiesau, director and digital health leader at The Chartis Group offered some useful benchmarking for hospitals and health systems wondering how their IT investments and digital maturity compare to their peers. The Chartis Group surveyed 226 health system executives nationwide, at hospitals and health systems of all shapes and sizes. They were asked their perspectives on digital health, artificial intelligence and machine learning – and about the financial health of their respective organizations. The health system execs had generally positive sentiments about digital health. Most agreed with the sentiments, said Keisau: "It should be integrated into the care model. It will advance care over the long term. It can create a competitive advantage. It can help close care disparities. Across the board what we saw from our respondents was that they believe those relatively strongly."

Improving operating room capacity management through data analytics and machine learning will be the breakfast keynote topic of discussion at the upcoming 2020 OR Business Management Conference. Ashley Walsh, senior director of client services at LeanTaaS, Inc., a Silicon Valley software innovator that increases patient access and transforms operational performance for healthcare providers, and Melissa Pressley, management engineer at Duke University Health System (DUHS), will address the audience on Thursday, Jan. 30, at 7:30 a.m. in the Global Ballroom of the Bonaventure Resort & Spa in Weston, Florida. "Improving OR utilization and improving surgeon access to OR time significantly enhances the financial results for hospitals and health systems, increases patient access, and facilitates surgeon recruitment and retention" "DUHS has leveraged EHR data to improve OR access with mobile and web technologies and increase accountability with surgeon-centric metrics and reporting to help our surgeons better understand the "why" behind OR metrics," said Pressley. "I'm looking forward to sharing how DUHS and LeanTaaS have enhanced the patient experience while balancing surgeon needs, among other improvements." DUHS is among several leading health systems in the U.S. that have deployed the LeanTaaS iQueue for Operating Rooms solution to effect data-driven changes to their approach to capacity management.

How can AI tools--such as deep learning and neural networks--be used to predict unplanned hospital and skilled nursing facility admissions and adverse events? In the Artificial Intelligence (AI) Health Outcomes Challenge, the Centers for Medicare & Medicaid Services (CMS) is dangling up to $1.65 million in prize money to the innovators who can figure it out. Six hospitals and health systems are among the 25 participants who were selected from a field of more than 300 submissions. The ultimate goal is to harness AI solutions to predict health outcomes for healthcare providers and clinicians, as well as potential use in CMS Innovation Center innovative payment and service delivery models. "Artificial Intelligence is a vehicle that can help drive our system to value--proven to reduce out-of-pocket costs and improve quality," said CMS Administrator Seema Verma in a news release.

Reductions in patient length of stay have been shown to reduce costs and improve outcomes. There are a number of ways for hospitals and health systems to reduce length of stay, the majority of which are time-intensive and center on restructuring existing operations. To help bolster and streamline efforts to reduce length of stay, systems such as New York City-based NewYork-Presbyterian have turned to artificial intelligence technology from Qventus to automate care coordination, which not only improves efficiency but also eases the administrative burden on hospital staff. During an Aug. 6 webinar hosted by Becker's Hospital Review and sponsored by Qventus, Courtney Vose, DNP, MBA, RN, APRN, NEA-BC, vice president and chief nursing officer of NewYork-Presbyterian, and Ryan Starks, MBA, senior product marketing manager at Qventus, discussed how NewYork-Presbyterian deployed the Qventus platform and the three most important lessons the health system learned in the process. Systems like Qventus' may be high-tech, but traditional leadership roles are still necessary in order to glean the most benefit from these platforms and drive actual change, according to Mr. Starks.

Change Healthcare AI can help providers identify problem claims and prevent denials before they happen, avoiding costly rework, delays, and improving revenue flow. Today Change Healthcare announced that it has applied its Claims Lifecycle Artificial Intelligence (AI) technology to its claims management suite with the introduction of Assurance Reimbursement Management Denial Propensity Scoring and Revenue Performance Advisor Denial Prevention. With performance enhanced by Claims Lifecycle AI, providers of any size can now proactively identify problem claims that could result in denials, and remediate potential issues before the claims are filed. The AI infused in these applications can now help customers predict denials, optimize claims submissions, and provide actionable recommendations that enable providers to better mitigate denials before a claim is submitted. Change Healthcare's analysis of 2018 data spanning more than 500 million service lines showed that Change Healthcare Claims Lifecycle AI could identify and flag up to 35% of denials prior to submission.

The healthcare sector has long been an early adopter of and benefited greatly from technological advances. These days, machine learning (a subset of artificial intelligence) plays a key role in many health-related realms, including the development of new medical procedures, the handling of patient data and records and the treatment of chronic diseases. As computer scientist Sebastian Thrum told the New Yorker in a recent article titled "A.I. Versus M.D., "Just as machines made human muscles a thousand times stronger, machines will make the human brain a thousand times more powerful." Despite warnings from some doctors that things are moving too fast, the rate of progress keeps increasing. And for many, that's as it should be. "AI is the future of healthcare," Fatima Paruk, CMO of Chicago-based Allscripts Analytics, said in 2017. She went on to explain how critical it would be in the ensuing few years and beyond -- in the care management of prevalent chronic diseases; in the leveraging of "patient-centered health data with external influences such as pollution exposure, weather factors and economic factors to generate precision medicine solutions customized to individual characteristics"; in the use of genetic information "within care management and precision medicine to uncover the best possible medical treatment plans." "AI will affect physicians and hospitals, as it will play a key role in clinical decision support, enabling earlier identification of disease, and tailored treatment plans to ensure optimal outcomes," Paruk explained. "It can also be used to demonstrate and educate patients on potential disease pathways and outcomes given different treatment options.

Health IT vendors galore have been introducing new products this week at HIMSS19. Here is another selection of some of the announcements. AMAX, a global artificial intelligence, deep learning and enterprise IT technology vendor, has launched its AI/Deep Learning Compute Cluster systems and Virtual Desktop Infrastructure platforms for the healthcare industry. The company's AI/Deep-Learning Compute Cluster systems for healthcare are optimized for research, development and large-scale deployments in data centers. Systems address the increasing demand for fully integrated high-performance compute and GPU accelerated compute as well as high-performance storage specific to healthcare applications that are based on AI and deep learning, the company explained.

If ever a technology was the opposite of plug-and-play, artificial intelligence is it. Beyond the obvious table stakes – having sound information and a smart data strategy – getting AI right requires a broad array of closely interrelated technologies to work well together. And it demands that each organization be able to tailor its deployments to their own particular needs. The data literacy part of the equation is hard enough to get right, for instance. "Very few health systems that I have seen and talked to have figured out their data strategies," said Nevenka Dimitrova, chief technology officer for oncology informatics and genomics at Philips Healthcare, speaking at the HIMSS Precision Medicine Summit this spring.