Gartner, Inc. has announced the winners of the 2020 Gartner Eye on Innovation Award for healthcare and life sciences. The award recognizes innovative use of technology-enabled capabilities in three areas: technology innovation with a health outcome; technology innovation with a cost or operational outcome; and innovative use of an emerging technology.
Finalists from the providers, payers and life sciences sectors presented their case studies during a Gartner webinar on November 4, 2020, and attendees voted on and selected three winners. The finalists’ presentations can be viewed on demand here.
Stanford Medicine: The New Stanford Hospital — Stanford built an intelligent hospital with technology at its operational core, integrating advanced technologies, care delivery and operations to improve the patient experience and care outcomes, increase efficiency and reduce clinical burnout, and to establish an innovation platform to advance research and care. By making the entire hospital operation “smart” – from automated patient check in to pharmacy robots – Stanford has improved patient engagement, integrated processes, and improved resource utilization. Key results include an estimated $2 million in cost savings by eliminating duplicate documentation and automation of routine tasks, such as alarm management, increased ER capacity, increased operating room volumes, and care team response time has been reduced from 12 minutes to 2 minutes.
Humana: Allie Intelligent Virtual Assistant — To help ease the excessive administrative burden that clinicians face, Humana empowered its clinicians as citizen developers who developed and implemented an intelligent virtual assistant called Allie. While Allie uses intelligence automation software to automate tasks to enable frontline clinicians to optimize products and services around patients, the Citizen Developer Program accelerated digital transformation across the enterprise by empowering frontline associates, reducing reliance on IT, promoting cross-disciplinary teams, optimizing human and system resource utilization, and aligning the program initiatives to strategy. Clinicians are now saving up to 15% of their day to focus on improving members' health.
Sanofi: Novel Treatment Indications via AI — Finding new treatment indications for an approved therapy is of immense value to pharma for drug re-purposing efforts, R&D candidate prioritization, and overall productivity. Sanofi wanted to develop an AI based indication searching approach that relies on real-world data thus bringing a higher confidence and reducing biases. Sanofi applied unsupervised machine learning to create a phenotypic cluster of patients in order to identify relevant indications that worked across clusters. The pipeline crunched nearly 17 million patients with 2,700 characteristics derived from electronic health records (EHRs) The initial results of the novel approach recovered 90% of known indications and identified many more deemed credible by development teams producing a higher level of confidence in results and a reduction in cost and time to market, with fewer, faster and more targeted trials, while minimizing attrition and risk.
Banner Health: AI Care Decisions and Virtual Waiting Room — Sixty percent of consumers don’t know which care setting is best for their needs and typically go through two waiting rooms for each healthcare visit. Solving these problems is critical to gain the trust of patients who need in-person medical care. Banner Health implemented a conversational AI to help direct patients to the right care setting, help identify potentially positive COVID-19 patients, and allow patients to wait in their cars and be notified to step inside the facility when the physician is ready and waiting for them. Additionally, touchless, digital waiting rooms launched system-wide, allowing all 29 Banner hospitals and 300 clinics in 6 states to easily comply with social distancing protocols, and with less waiting room space needed, Banner Health is now planning to expand its treatment spaces.
Cigna: Proactive and Personalized Stress Management — A rise in workplace stress, currently exacerbated by the COVID-19 pandemic, often leads to loss of employee productivity. Organizations need to focus on being proactive and predictive to manage employee stress. Cigna is using the Internet of Things (IoT), through wearables and machine learning (ML) to proactively create personalized algorithms to detect vital sign baselines and stressful moments. Cigna offers a team of wellness coaches and a tailored set of stress management tools to help employees proactively manage their stress. Between November 2019 - June 2020, Cigna saw a consistent decrease in reported stress month-to-month, with an overall decrease of 21%.
CVS Health: AVAIL (Adding Value thru AI and Learning) Pharmacy Benefits Management — Incoming information from client benefit set up requirements came in multiple formats, unstructured request and instructions and was a manually intensive process, measured in weeks and months. CVS Health introduced AVAIL to automate end-to-end pharmacy benefits management (PBM). CVS has seen a reduction in costs and processing time, improved quality & customer satisfaction, with a budgeted return on investment savings of $1.1 million from coding and testing automation alone.
Johnson & Johnson: AI Translation Platform — Existing manual translation process for adverse events (AE) was failing to meet the increase in translation demands and created a compliance risk with newly released restrictive regulations. Johnson & Johnson customized an AI translation platform trained with years of domain data and aligned its capabilities with J&J’s strategy to deliver regulatory compliance excellence amid demand surge. The AI translation platform is available 24x7 all year long and helps reduce turnaround time. Within a few months after deployment, significant cost savings were realized, and it improves translation quality and reduces the risk of human errors.
Johnson & Johnson Medical Devices Companies: 3D Printed Knee Osteotomy Guiding Block Platform — To ease lengthy end-to-end process for service delivery, improve clinical outcomes and shorten surgeons learning curve, Johnson & Johnson Medical Devices created a personalized 3D-printed knee osteotomy guiding block platform for high tibia osteotomy (HTO). The platform allows Johnson & Johnson Medical Devices to collaborate with surgeons via the interactive digital platform to accelerate design speed and standardize and optimize internal business processes across various departments, while managing patient specific products workflow. It also ensures improved product delivery time and faster patient treatments.
King Faisal Specialist Hospital and Research Center: COVID-19 Decision Support Machine Learning Platform — To assist with developing operational readiness and responsiveness towards the immediate impact of increasing numbers of COVID-19 patients on the healthcare system, King Faisal Specialist Hospital and Research Center created an analytical platform with self-learning AI models that projected future case movements based on variables (current positive COVID-19 levels, public & private quarantine measures, government regulations, etc). The self-learning AI models functioned at a 9% absolute error rate which contributed to zero stock medication incidents, PPE incidents, beds shortages, ventilator shortages and staff shortages, as well as proactive leadership, operational response and readiness.
The identification of a Gartner award winner or finalist is not an endorsement by Gartner of any company, vendor, product or service.