New iQueue product suite features powered by AI/ML will help hospitals and health systems tackle major challenges, including shrinking healthcare staff, rising patient demands, and poor utilization.
SANTA CLARA, Calif. – Dec. 8, 2022 — LeanTaaS, Inc., a Silicon Valley-based technology innovator and market leader that transforms core operational processes to increase patient access, decrease wait times, reduce healthcare delivery costs, and improve revenue, today announced new enhancements, powered by predictive and prescriptive analytics, to its iQueue products for operating rooms, infusion centers, and inpatient beds. The announcement was made at LeanTaaS’ fourth hospital operations virtual summit, Transform, hosted in partnership with Becker’s Healthcare. Enhancements to LeanTaaS’ iQueue products were developed to help hospitals and health systems tackle their most urgent challenges, including diminishing healthcare staff, rapidly rising patient demands, and poor utilization.
The severe staffing shortage is the biggest crisis facing healthcare today. Earlier this year, hospital CEOs shared that for the first time in 17 years, staffing is their number one concern. The labor crisis extends beyond the well-known nursing shortage and across the entire healthcare ecosystem, from medical assistants and technicians to physicians and home health aids, impacting hospitals, infusion centers, skilled nursing facilities, and more. With innovation and customer feedback at the forefront, LeanTaaS is releasing new enhancements to help healthcare providers manage staff and resources effectively, efficiently, and according to cutting-edge lean principles. Product enhancements include:
New iQueue for Operating Rooms Features:
- Automated Guidance for OR Staffing and Roster Management to Reduce Burnout and Improve Resource Allocation: iQueue for Operating Rooms will soon launch a feature that helps perioperative nurse managers predict how many OR employees will be required each day up to 30 days in the future and for how long each day. Additionally, this new feature will allow nurse managers to ensure the right team is assigned to the right OR, specialty, or physician based on experience and preferences. Currently, perioperative nurse leaders struggle to match the supply of OR staff to future demands of unpredictable surgery schedules, assign the right team to the right OR, and reallocate resources in a timely manner. Ongoing staffing shortages have compounded an already complex and time-consuming planning process, making this new enhancement a must for today’s perioperative leaders.
- Case Length Estimator to Reduce Schedule Disruptions: iQueue for Operating Rooms’ new Case Length Estimator is the most advanced case length prediction tool on the market, delivering accurate predictions for even the most complex cases. The tool utilizes machine learning and text recognition to significantly outperform current industry best practices, resulting in a major reduction in over and under scheduled cases. For example, spine cases are some of the most difficult to schedule accurately, and due to their long durations, case scheduling discrepancies are highly impactful. iQueue’s case length predictor is able to extract the number of bone levels and types of approaches from the free-text procedure description to make significantly more accurate recommendations than humans or other tools on the market. Improving scheduling accuracy results in reduced patient wait time, reduced surgeon wait time, reduced overtime, improved staff satisfaction, and reduced loss of revenue due to overbooking.
- Benchmarking to Compare Operational Performance: iQueue for Operating Rooms is offering a new Benchmarking feature to better understand operational performance and goals. With Benchmarking, users can view specific operational metrics like FCOTS, turnover, prime time utilization, and more, and compare them to sites with a similar case mix, and by specialty. This helps users gain a better understanding of expected performance for their specific hospitals. iQueue benchmarking has anonymized data across 4,000 ORs from 600+ perioperative locations to allow for one of the most comprehensive perioperative benchmarking capabilities available in the market.
New iQueue for Infusion Centers Feature:
- Linked Arrivals to Maximize the Number of On Time Patient Arrivals: iQueue for Infusion Centers is offering a new diagnostic tool that aims to increase the number of patients arriving on time to their infusion appointment, offer insights into how patients are arriving to their infusion appointments after a linked clinic visit, and provide recommendations on how far apart appointments should be scheduled from the clinic appointment to maximize the number of patients arriving on time. Infusion centers manage unique challenges due to patients’ specialized treatment plans, making arrivals difficult to gauge when linked clinic visits are scheduled before infusion. This new feature provides insights to see where patients are arriving too early or too late and offers gap recommendation charts to make data-driven decisions on how to increase patient on-time arrivals.
New iQueue for Inpatient Beds Feature:
- Patient Level Discharge Barrier Prediction Pilot with Over 80% Accuracy: Proactive, highly accurate, and timely identification of discharge barriers powered by AI/ML allow care teams to address barriers before they create delays, optimizing patient flow. This helps reduce costly avoidable days and provides patients and providers with a smoother care journey. In a pilot study, hospital customers who use iQueue for Inpatient Beds achieved marked success in identifying potential discharge barriers earlier in the patient’s stay. These early results indicate that iQueue for Inpatient Beds identifies post-acute care issues, procedure or imaging delays, and consultant delays following discharge barriers with over 80% accuracy. These predictions are supported by the data available in EHR systems and require no additional manual inputs.
“Healthcare challenges continue to mount, including a rising demand for patient care coupled with shrinking reimbursements and staff shortages. The patient experience is diminishing even further and hospital economics are dire, which is creating a tough reality for health systems and hospitals,” said Sanjeev Agrawal, LeanTaaS President and COO. “Our new iQueue features were designed based on direct feedback from our base of 140+ health system customers , and will offer innovative uses of AI/ML to meet these challenges head on and improve OR, patient flow, and infusion center operations.”
LeanTaaS’ AI and ML based solutions have now been deployed in more than 500 leading hospitals and 140 health systems across the U.S., including 13 of the top 20 health systems in the country. These hospitals use LeanTaaS’ iQueue platform to optimize capacity utilization in infusion centers, operating rooms, and inpatient beds. iQueue for Operating Rooms is used by more than 3,000 ORs to improve surgical capacity utilization, attract new surgical volume, and improve the patient experience. iQueue for Infusion Centers is used by nearly 500 infusion centers, with over 11,500 chairs with a customer base that includes over 80% of the National Comprehensive Cancer Network and nearly 60% of National Cancer Institute-Designated Cancer Centers. iQueue for Inpatient Beds, launched in 2021, is scaling rapidly and is now used in more than 4,000 inpatient beds in the U.S.
About LeanTaaS
LeanTaaS provides software solutions that combine lean principles, predictive and prescriptive analytics, and machine learning to transform hospital and infusion center operations. The company’s software is being used by over 140 health systems across the nation, which all rely on the iQueue cloud-based solutions to increase patient access, decrease wait times, reduce healthcare delivery costs, and improve revenue. LeanTaaS is based in Santa Clara, California, and Charlotte, North Carolina. For more information about LeanTaaS, please visit https://leantaas.com/, and connect on Twitter, Facebook and LinkedIn.
LeanTaaS Media Contact
Kate Soden