MedCity Influencers, Health Tech

How hospitals can address provider burnout and staffing issues through digitization

Health systems must seek digital solutions that make the most of existing staff while also prioritizing their wellbeing. A platform that uses sophisticated math and intelligent, continual learning algorithms can unlock value for hospitals, staff and patients.

The healthcare industry as a whole has been strained by Covid-19, and health systems continue to grapple with lingering effects and new variants like Omicron. On top of this, hospitals are now dealing with another round of elective surgeries that are being postponed to free up essential resources and beds. With all of these factors in play, it’s no secret that health systems have struggled to manage not only their assets but also the valuable time and wellbeing of clinicians and staff.

These challenges have accumulated to create the current main crisis: the nursing shortage. The already high demand for nurses has been exacerbated by Covid-19, with more early retirement and illness among senior nurses and increased reliance on travel nurses to supplement short-staffed health systems. A study by the International Council of Nurses found that 76% of healthcare workers have experienced exhaustion and burnout since the start of the pandemic, and Reuters shares that rates of “intention to leave” have doubled to 20-30%, indicating that the shortage will be long term.

Statistics like these are jarring for healthcare providers, patients, hospital executives and partners alike. These structural, long-term problems cannot be solved through a hiring push alone. Instead, health systems must seek digital solutions that make the most of existing staff while also prioritizing their wellbeing. Below are key suggestions and areas of opportunity for providers to target:

Support front line staff with a real-time, digital assistant 

Front line staff is especially hard pressed to perform effectively, particularly in areas like inpatient units, where situations change rapidly and unpredictably and placing patients in the right space at the right time is critical. These circumstances were already stressful in “peacetime” and became highly exacerbated when Covid-19 created a short supply of emergency and intensive care units and staff.

Often these staff spends hours in team huddles attempting to predict how the day will unfold, which units they will need and how many specialized staff should be assigned, and when patients can be transferred or discharged. EHR dashboards or “command centers” are of little help. They provide information that gets stale in five minutes and only admire the problem rather than solve it. With no clear predictive data, they are forced to rely on handwritten processes, spreadsheets, and intuition. Staff are knowledgeable about what they do and generally make the right decisions using the resources they have, but these manual methods available are time-consuming, inefficient, and lead to burnout.

Giving staff on-demand digital tools with predictive analytics and tailored prescriptive recommendations helps them make the right decisions quickly. This looks like a platform that incorporates past patient flow data to predict likely upcoming surges, then uses machine learning and AI-based algorithms to calculate and visualize the most efficient ways to allocate inpatient beds to accommodate them. A platform that also functions as a “virtually distributed” command center can send alerts and communications to staff via mobile devices, in real time, ensuring everyone on the floor is connected, updated, and united in navigating the day.

Staff using these digital “assistants” can trust they are receiving the most accurate information as they work with colleagues to make decisions. Health systems that have implemented such digital support for bed staff report a high increase in confidence, which in turn contributes to a positive experience for staff and supports retention.

Rethink systems to align with staff preferences and needs 

Many healthcare providers operate on the assumption that all staff preferences are the same, and that to ensure liked and disliked tasks are distributed evenly, work must be allocated on a one-size-fits-all basis. Infusion centers, for instance, tend to run on a patient “push” basis, where nurses are assigned a similar patient load for every shift. In fact, infusion nurses have widely varied perspectives on which types of patients or procedures they prefer. For example, some nurses prefer new patients while others prefer regular patients, some enjoy clinical trial patients, and other nurses prioritize consistent, balanced schedules over all else. Instituting a “pull” system, in which patients arrive in one virtual queue and nurses can choose which one to take as they are ready, meets the diverse needs of nurses.

A “pull” system also reduces bottlenecks. In a “push” system, unforeseen patient problems or linked clinic appointment delays disrupt not only the assigned nurse’s schedule but the entire center’s queue. In a “pull” system, disruptive impacts are limited to just the assigned nurse, who is then under no pressure to “pull” another patient until the first patient is discharged.

Putting a “pull” system into practice requires an investment in the right kind of digital platform that displays the patient queue, that shows scheduled appointments and confirmed arrivals as well as patient types and expected length of treatment, and allows nurses to select their patient immediately. A predictive and prescriptive capacity management tool that adapts to unexpected outcomes and learns the patterns of the center’s nurses, patients, and appointments is what’s needed.

Under a “pull” system, not only are nurses free to take on their preferred workloads, but also are freed from the anxiety and stress that comes from not knowing if bad outcomes will derail a given day. Prioritizing staff wellbeing and work-life balance in this way is also key to retention and reducing burnout.

Empower available staff to reasonably meet upcoming patient demand

The ongoing staff shortage is a chronic problem that health systems must continue to address for the foreseeable future. Many hospitals have seen their staff levels drop throughout Covid-19, while demand for care is exploding in many parts of the system, leading to overwork and increased burnout.

Furthermore, one of the greatest challenges for providers emerging from the pandemic will be accommodating a backlog of deferred cases, especially as many states have again mandated a pause on elective surgeries. Health systems will either need to go through a glut of postponed cases or encourage patients to return who may be hesitant or have fallen behind on regular healthcare visits. Providers must be ready to respond to this increased demand for capacity.

To work through these backlogs, staff such as those in perioperative spaces must be prepared to know exactly which resources are available and how to best distribute them. The right digital tools to predict, visualize, schedule, and communicate available rooms or time blocks make it easier for staff, nurses, and surgeons to direct the resources they have to the patients who need them. One major health system saw a nearly 10% higher volume of participation from splitter surgeons after seven months of offering a platform that supported operational decisions for staff.

In summary

A system that uses sophisticated math and intelligent, continual learning algorithms can unlock value for your hospital, your staff, and your patients. It will enable your front line to automatically and rapidly make smarter decisions that consistently match the supply and demand for each of your hospital’s assets throughout the day and on every single day.

Photo: Hiraman, Getty Images

This post appears through the MedCity Influencers program. Anyone can publish their perspective on business and innovation in healthcare on MedCity News through MedCity Influencers. Click here to find out how.