Balanced Clinical Workloads Help Prevent Caregiver Burnout

Finding and keeping great talent is challenging in any industry. But the stakes are especially high in hospitals where lives depend on having a high performing team.

In recent years, staff acquisition and retention have become a big issue for nursing leaders. Stress and fatigue are taking a serious toll, and burnout among nurses has become a real and present danger. Nurses are leaving the profession faster than at any other time in history. So much so, the American Journal of Medical Quality predicts a nationwide nursing shortage by 2030 as nurses leave the profession to preserve their sanity.

The root causes for burnout are varied, ranging from intense emotional empathy to the demands of the job. And studies show that nurses that care the most are the most vulnerable.

How can hospital leaders stem the tide of burnout and retain the best and brightest? Using real time data to make hospital staffing decisions can have a tremendous impact on preventing caregiver burnout.

Savvy chief nursing officers look at staffing holistically, but far too often, staffing decisions are made on a hunch rather than hard evidence. If an RN leaves, is it really a foregone conclusion that they should be replaced by another RN? Or could there be a better fit that will balance the workload while allowing every caregiver to operate at the top of their license? And what is causing staff to leave in the first place? Are undetected performance issues bringing high performers down?

Clear and actionable data provides the valuable insight nursing leaders need make objective staffing decisions to balance clinical workloads and create a culture of engagement.

The ability to make data-driven staffing decisions is one of the prime benefits of new technology. It wasn’t that long ago that nursing leaders assessing staffing workloads used a complex series of steps to gather material.

A World Health Organization study published in 1999 detailed five ways of accumulating data to determine workloads in health care facilities:

1. Direct observation of staff activities

2. Self-monitoring using a log or a diary

3. Questionnaires

4. Interviewing relevant staff

5. Expert opinion

Technology has made these methods seem extremely outdated in a relatively short period of time.

Technology-driven data provides a more accurate picture of what is needed. Virtually every industry now has a metric to determine appropriate staffing levels. A company that sells widgets may use a factor of sales. A call center may look at call loads and abandoned calls.

Hospitals can track patient demands. What do patients need and when? Can patient demands be met by an aide, or does it require a higher level of care?

Of course, data on its own cannot guarantee the right decisions. Harvard Business Review says:

“Many organizations lack a coherent, accessible structure for the data they’ve collected. They’re like libraries with no card catalog and no covers on their books. The rise of social media, new selling channels, and devices such as tablets and smartphones has made it even harder to manage analytic content. Fewer than 44% of employees say they know where to find the information they need for their day-to-day work.”

Data for data’s sake isn’t the answer. Organizations need a strategic roadmap for how they will use data to make decisions. They also need easy access to data in a reporting platform that provides clear and actionable insight.

Amplion Alert provides data and a powerful reporting platform to improve quality outcomes and to help hospitals make strategic staffing decisions to achieve balanced clinical workloads. It captures every instance when a patient is visited. It closes care loops, documenting not only when care was requested, but also when care was delivered. This leads to accountable care, allowing patients and families to clearly see what care was provided and when. But over the course of days, weeks, even months, it also provides unprecedented insight into what occurs on the floor day in and day out.

What are the patient demands at any given time? How is the team performing? What care mix is needed to deliver an optimum patient experience and provide quality outcomes? Being able to see patient demand in real time and rebalance the workload as needed makes a huge difference in patient and caregiver satisfaction. Identifying low performers and quickly addressing issues as they arise improves employee morale, promotes caregiver engagement and prevents burnout. Highly satisfied caregivers lead to highly satisfied patients. And a highly satisfied and engaged workforce leads to less staff turnover.

Want to learn how Amplion can help you assess and balance your staff workloads while improving patient and caregiver experience? We would love to show you our reporting capabilities and discuss how our platform could be a game-changer for your organization.

Are You Ready for TJC 2016 Alarm Management Deadline?

The headline asks a question, but odds are, the most likely answer is no.

As we meet with facilities around the country—most recently during the Association for the Advancement of Medical Instrumentation (AAMI) conference—I would estimate that only about 20 percent are truly on top of this deadline. Another 20 percent have no clue that it’s coming while the remainder is aware of the deadline but will admit that they are woefully unprepared.

For facilities in the “no clue” category, here’s a refresher: in 2014 The Joint Commission set a public safety goal regarding alarms. That same year, hospitals were required to identify the most important alarms to manage based on their internal criteria. By 2016, facilities will be required to determine the most critical alarms, when alarms can be disabled, and who in the facility can set or change alarm parameters.

It would be easy to be lulled into complacency. Since The Joint Commission audits occur every three years, only about a third of facilities will be judged on how they’ve met this standard in 2016. The day of reckoning will occur for others during audits in 2017 and 2018.

But, of course, hospitals focused on patient safety already understand the risk that dependency on audible alarm recognition and response entails.

Through the years, research has documented a number of patient deaths due to alarm fatigue. The number of alarms in hospitals have also increased, creating a maddening cacophony on every floor, every shift. Given the constant blare of meaningless alarms, important ones may not be heard. Is it any wonder ECRI lists alarm hazards as the number one safety issue for healthcare organizations in 2015?

We recently consulted with a facility that tapped Amplion to inventory its devices and provide reports on the volume of alarm activity. Using listening devices in every unit in the hospital, we were able to identify thousands and thousands of alarms by device, alarm type, and duration. When we showed the report to the clinical team—those who are forced to listen to alarms day in and day out— they were stunned by the number. It didn’t take long to come to the conclusion that no person can be expected to keep up with that sort of alarm volume. It is just not physically possible.

We found that in most cases, only 10 percent of alarms were actionable. So caregivers were spending time responding to alarms that, nine times out of 10, were non-actionable. The care team had no way of knowing the severity of the situation until they tracked down where the sound was coming from and physically entered the room. Literally a “cry-wolf” syndrome, and after many times with a patient, naturally the nurse might assume that any given alarm is also a false positive—until it isn’t, and an event happens.

Looking at the data, we also learned, for example, that 90 percent of the time a pulse oximeter alarm went off, it cleared itself within seven seconds. We found it was often something as simple as a patient’s movement that triggered it. Clinicians determined that they did not need to know about alarms that cleared so quickly—unless it happened a number of times to the same patient.

That alone eliminated a significant number of alarms. But it still did not address the other major issue we see with alarms. Caregivers often have no idea of where the noise is coming from—and whether it is a patient assigned to their care.

Because Amplion Alert routes alarm messages to the nurse assigned to a specific room, the caregiver knows when he or she receives a message, that it is their patient and something they need to pay attention to. Targeted communications mean that the right caregiver is confident that he or she is getting a valid alarm message and can respond with the appropriate sense of urgency.

That takes us to another important issue that came up during AAMI, and it’s a question that facilities have been raising since The Joint Commission first included alarm management in its patient safety initiatives. Where does alarm data come from? Some devices can be connected through a common server, but more often than not, data is being housed inside the specific device. That means someone has to physically go to each piece of equipment, download or print something out of the memory. Then there are the devices that are not connected and don’t store any information. What can be done about those?

It’s a conundrum to be sure. Facilities that are fortunate enough to have an effective way to collect the data still must figure out what they must do with the data. How to turn that insight into action?

And most importantly, how can a facility—already tasked with implementing EMRs and addressing a myriad of other safety issues be expected to add one more project onto a full plate while maintaining the quality of patient care?

It’s a complex set of questions that facilities must begin tackling. It’s not about the The Joint Commission audit, or even improving patient satisfaction—which better alarm management has been shown to do. It’s about ensuring the safety of patients every time. Alarm fatigue is a real threat. The most skilled caregivers on the planet can’t be expected to navigate thousands and thousands of alarms over the course of a shift.

It’s time to get serious about alarm management. Yes, 2016 is still a few months away. But let’s not wait until a page turns on a calendar to do something. Patients’ lives are at stake—and facilities simply are not ready. Not sure where to start? Give us a call. We can help!

Clinical Staffing Decisions – Better with Data

One of the most perplexing tasks that clinical leadership undertakes each shift is staffing. It’s a delicate balance – ensuring that there are enough nurses, nurse assistants and respiratory therapists to properly meet patient demands. And then there’s the ever-present wild card of not knowing what the day may actually bring.

In many cases, it is a shot in the dark, based on gut feeling, recent patient demand and the location of patients in the unit.

The availability of data can remove the guessing game. But, despite the availability of more data than ever, it often remains an untapped resource when making clinical staffing decisions.

Two articles written by nursing leader Kathy Douglas, MHA, RN, president of the Institute for Excellence and Innovation, provide some insight on the disconnect between the availability of data and the use of it to make decisions. Douglas wrote two articles for Nursing Economic$ three years apart—in 2011 and 2014. A comparison reveals both growth and missed opportunities in using data to inform decision-making.

Douglas in 2011:

“In nursing, we are still learning the world of technology and developing the strength of our voice in getting what we need and want from it. We are still evolving our understanding of technology, its nature as a tool, and its relationship to a bigger picture of outcomes, goals and cultural and business objectives. To make the shift from our past and lead the charge on staffing excellence that is grounded in an evidence-based framework will require shifting how we look at staffing and scheduling. We must give staffing technology its rightful place as a top strategic priority and then allow it the leadership attention all top priorities enjoy.”

Three years later, Douglas again wrote:

“There has been much work in the area of staffing. There is more research than ever to guide us. We have grown in our business acumen as well as in our care delivery models and technology, but we can do better. We have been slow to leverage what we have. We have spent countless dollars on new technologies but they are often poorly adopted, leaving their powerful benefits of supporting evidence-based decision-making, data collection, business intelligence and advanced communication on the table. We have not mastered the translation of evidence on staffing to influencing budgets, adjusting policies and procedures, and changing cultures as rapidly as we need to.”

It’s somewhat remarkable that over the course of a few years, Douglas noted a widespread growth in understanding of technology—but a failure to fully harness the opportunity.

Healthcare is not lacking for data or technology. But the industry remains somewhat behind others in translating that into action. Other industries do offer some insight in how nursing leadership might better use technology to drive decisions.

Business analytics giant SAS created a white paper aimed at educational leadership. It included this telling quote:

“The adage that schools are ‘data rich’ and ‘information poor,’ while ironic, is often true. School systems are flooded with data. Leading by assumptions and hunches from a single view of multidimensional issues does not ensure that one is focusing on the right issues at the right time in the right fashion. Rather than guessing or hoping for the best, leaders can use data effectively to develop and foster a culture in which all members of the district understand, apply and manage data as a dynamic entity to support the district’s focus and improve outcomes for students, staffs and schools.”

It wouldn’t be much of a stretch to apply the same to healthcare, especially related to data-driven staffing decisions. We, too, have the data, but often lack the information.

That same white paper suggests a myriad of methods for effectively implementing data-driven decisions. Of the suggestions listed, these three are key:

    • Establish a clear vision. How are you going to use data to make the most insightful decisions about staffing of caregivers? Are there any problems that you are trying to solve going in? Understand that exploring data may reveal hidden issues.
    • Review existing data. Do you already have systems in place that may serve in one capacity but could offer insight into staffing needs? Amplion Alert users look to us for alarm management or nurse call systems. But our robust reporting system provides the insight needed to ensure the best care at the proper staffing workloads.
    • Ensure buy-in and commitment. This can be one of the biggest challenges when it comes to implementing any new technology. Be open with what you hope to gain and how you’ll use the information. Let managers know how this will ease the burden of decision-making. And let frontline caregivers understand how this can improve their jobs.

Above all, the most important aspect of implementing data-driven clinical staffing decisions is to just do it. After that, you must make it a priority and be consistent. The technology is available, and may even be already in place. But it’s incumbent upon you as a clinical leader to drive this insight into action. Healthcare has become too complex for guessing games and gut reactions. It’s time to let data take a more prominent role.

Three Important Ways Data is Transforming Patient Care

It can be difficult to grasp what is happening in every corner of a healthcare facility on any given day. CEOs have trusted advisors who should be able to provide insight. But increasingly, CEOs and other hospital leaders are turning to sophisticated streams of data to get the information they need to fully understand performance of the operation and take action to improve patient care.

Technological advances are increasing the flow of information at an exponential rate. Recent statistics show that more than 90% of the world’s data has been collected in just the past two years. Retailers leverage data to know who their best customers are and why. Website and social media companies use data to understand how their users navigate the Internet. And now hospitals are stepping into the data revolution that has transformed so many other industries.

But data usage isn’t just about understanding customers—or in the case of healthcare, patients. It also provides valuable operational insight—the second most important reason that companies of all types are using data.

So how is data being used to solve critical issues in a healthcare facility?

1. Data can help improve financial performance without sacrificing patient safety and quality. Mayo Clinic recently provided a case study detailing how it is using data to inform decision-making, cut costs and improve patient care while keeping safety at the forefront.

“Sometimes you get pigeonholed as an efficiency expert, which can sometimes mean downsizing,” said Dr. Tom Rohleder, the associate scientific director of Mayo’s Health Systems Engineering Program. “I think that one of the things that we knew we had to do was make it clear that whenever we’re doing an analysis, we’re factoring in patient quality [and] patient safety. When we’re doing our systems engineering work, even though we are talking about becoming more efficient, we’re not doing it at the expense of the patient.”

Patient safety can actually be improved by data. For instance, purposeful rounding has been shown to reduce pressure ulcers and reduce falls. Does this happen in the facility every day, every shift, every patient? Data reveals the truth.

2. Data can improve patient satisfaction. There is a direct correlation between response time to a call light and patient satisfaction. This might seem obvious – if a caregiver meets my needs quickly, I will be more impressed by my overall experience at the facility. It’s actually a bit more complex than that. As with purposeful rounding, quick responses mean patients are less likely to get out of bed to address their needs. That leads to fewer falls, which in turn lessens hospital-acquired injuries.

How quickly does the facility staff respond? And if they think they respond within a set amount of time, how often do they actually hit that goal? Again, objective data can show how a facility is meeting or exceeding marks in this area.

3. Data provides insight into staffing needs. Hospitals exceed the national average for staff turnover. Data provides insight into why this might be happening and helps hospitals develop strategies for retaining their best and brightest talent. Are RNs operating at the top of their license? Are they providing clinical care or blankets? Are patient care requests being routed to aides when appropriate? Are care loads distributed properly to prevent caregiver burnout? Are low performing caregivers causing undue stress on high performers who must take up the slack? Data reveals how staff is responding to the most common patient care requests. This can help nursing leadership provide adequate staffing. And it can help the facility ensure that it has the right mix of caregivers.

Many of today’s advanced healthcare technologies already have the ability to provide this data. Amplion Alert, for instance, captures every turn and every round. It provides actionable data for improving patient safety, patient satisfaction and appropriate staffing levels. It can also help manage alarm fatigue—another important factor that improves patient and caregiver satisfaction.

In the Mayo Clinic case study, experts offered a tip for facilities: start small. The sheer amount of what can be measured can be overwhelming. By focusing on a few core areas, facilities can make a tremendous impact on financial performance without sacrificing the quality of patient care and outcomes.