Bryan Dickerson brings 30 years of healthcare experience, particularly in product management and software solutions, to his current role as healthcare AI partner LeanTaaS’ Director of Client Services for Inpatient Flow.
Dickerson has worked with hundreds of health systems to improve their inpatient staffing and scheduling strategies. Now an expert in applying AI solutions in practical ways, he helps health systems address the specific challenges they face and optimize and empower staff to an unprecedented degree through technology. Several of these organizations will share their success at the upcoming Transform Hospital Operations Summit, a free virtual industry event co-hosted by Becker’s and LeanTaaS happening June 6-7, 2023.
Question 1: Health systems are universally operating with less staff than they have been accustomed to in the past. How have you noticed health systems addressing this, and what has the impact been?
Bryan Dickerson: While operating with reduced staff is a normality for health systems at this point, many are still struggling to implement the effective, up-to-date processes and technology needed to proactively help people and account for system-wide staffing needs.
A direct impact of this mismatch is that staff themselves, because they are not deployed efficiently, are more burdened than ever with both higher patient loads and increased repetitive tasks like note taking and reporting. Nursing staff in particular are not able to dedicate satisfying levels of time and energy to their patients, and all are at increased risk for burnout. In turn, organizations risk losing the staff they already have, meaning a dearth of mentors and support systems for potential new staff, as well as reduction in efficiency overall.
Recently, more and more healthcare organizations have begun taking new approaches to staffing and adopting the technology they need to execute them. To gain the centralized, forward-looking perspective they need to proactively assign more appropriate levels of staff across the whole organization, health systems must strategically leverage their own internal data, obtain visibility into staffing details in all units and utilize predictive analytics. At the same time, nursing leaders need intelligent automated workflows to reduce repetitive tasks and apply their focus and energy more constructively.
Only AI technology offers solutions powerful enough to address these areas successfully, supporting fully informed decisions about staff utilization that improve patient care and protect the bottom line. AI can also streamline clinical workflows while supporting higher satisfaction for staff.
Q2: How does AI apply to health systems’ managing staffing from the “top down”, on the organizational level? How does it support frontline staff?
BD: AI-powered technology supports the centralized, proactive optimization of staff, offering a full picture of staffing needs across the organization and predictions on how these are likely to change. It can also streamline staff workflows and offer decision support to alleviate burden.
From the “top down”, AI tools such as LeanTaaS’ iQueue for Inpatient Flow can help health systems fully utilize available staff. Health system leaders can use the technology’s insights, gleaned from their own data, to assign nursing resources based on the upcoming patient care needs the following day or throughout the upcoming week. They can determine optimal staff allocations to improve nurse-patient ratios, ensure units with the greatest patient care needs are appropriately staffed and create consistency in the use of incentive pay shifts when staffing levels are predicted to be unavoidably low.
These AI-supported staffing workflows are built in alignment with the organization-wide patient census, both present and future. Nurses and other frontline staff are deployed equitably to the areas of greatest patient care needs. Further, the intelligent workflows AI provides can automate routine tasks and also support more involved, complex functions, like identifying and addressing potential barriers to discharge in inpatient units, and so reduce daily meeting time needed to perform them.
When these tools alleviate burden, and augment rather than replace human expertise and interaction, staff and providers can perform their best while feeling fully engaged and satisfied. By thus assisting staff day-to-day, as well as ensuring needed inpatient units are staffed and patients are discharged more efficiently, tools like iQueue for Inpatient Flow drive exponential improvements in patient access, operational performance and staff satisfaction.
Q3: What advice would you offer to a health system considering implementing AI technology to support staffing optimization? What factors should they consider?
BD: Any new technology inevitably involves a financial and human cost. With limited resources, health systems must be selective in the solutions they invest in, and implement these strategically for best use. Otherwise investments might yield limited ROI, along with disrupted operations, frustrated staff and other harmful outcomes.
When choosing an AI technology solution, leadership must be sure the benefits are clearly defined, address real problems in the organization and outweigh the costs. They must examine the processes that work best for their organization and assess if and how the technology supports these. Most importantly when implementing, they must also align their people with the process and technology. A partner who deeply understands both the technology and the needs of the health system can help to oversee this crucial change management, and achieve this transformation.
The right AI technology does not disrupt existing staffing processes that work well, or disturb aspects of the work environment that already provide satisfaction. To help develop a centralized staffing approach, a solution should provide a single, continually updated source of truth on staffing needs that offers complete transparency and streamlines communication among leadership and teams. They should also actually remove or automate specific burdensome tasks. Such solutions generally require a light lift for implementation and quickly deliver ROI.
Q4: What are some results you’ve seen from health systems who have successfully used AI to transform their staffing processes, and support their staff?
BD: Health systems who have successfully implemented AI solutions to improve their staffing processes have increased access for patients without spending on further resources, and given notable time and energy back to their staff.
MercyOne Medical Center, after deploying iQueue for Inpatient Flow for six months, gave each of their nursing leaders back more than 10 hours per week to focus on patient care. In around the same time frame, HealthFirst streamlined communications enough to allow more than 2,600 staff hours to be repurposed weekly for other tasks. An Indiana health system, in 18 months, was able to create more than 250 days of usable hospital capacity by improving staff allocation.
By embracing AI and the centralized, transparent and streamlined staffing approaches it supports, health systems can drive higher revenue, increased capacity and more supportive work environments for staff themselves, all contributing to improved care and outcomes for patients.
To learn more about the strides health systems are making in deploying AI technology toward staffing, register for the free Transform Virtual Operations Summit happening June 6-7, 2023.