Use Data Transparency With IC Outcomes to Engage Staff

by Ivan W. Gowe, MS, BS, MLS(ASCP)^CM, CIC

Healthcare workers do not set out to harm patients, yet our industry is responsible for 161,000 avoidable deaths every year (Leapfrog Group, 2019). Staff and patients know of the dangers of hospital-acquired conditions, but not the extent because that information is not readily available. Data transparency will help put a spotlight on how those incidents occur. However, communication of the data can and should be more immediate.

A non-intensive care nurse takes care of five or six patients at a time (Livanos, 2018). Add a few discharges and admissions, and that nurse will touch more than 20 patients in a workweek. Infection prevention (IP) and quality department surveillance and data abstractions are usually deferred by some weeks. Feedback on adverse events is delayed so that by the time clinicians go back to the nursing unit to report events, they have cared for so many patients that their memory of particular lapses in care is fuzzy or missing.

Think of it in terms of what happens with motorcycle accidents, half of which occur because a driver just did not see the motorcyclist (National Highway Traffic Safety Administration, n.d.; Nazemetz et al., 2019). When an accident occurs, there are police reports, there is insurance company involvement, and there may even be court proceedings. It is immediate and jarring feedback. Even a near miss is enough to improve one’s motorcycle awareness for at least a few months.

In healthcare, workers likely do not know when they harm patients. As you craft a program to get more information to your staff, consider these points:

1. Hospitals have a reputation to maintain. The sharing of infection (or other bad outcome data) is not yet commonplace. When I shared outcomes data with staff, I was once informed, “We do not want [them] to think our hospital is not safe.” Multiple studies have shown the importance of feedback in reducing bad outcomes in other industries (Karan & Kopelman, 1987; Alvero, Bucklin, & Austin, 2001). Banners in warehouses and factories stating the number of days since the last accident are an example of feedback mechanisms in these studies. We can easily do likewise in our hospitals—the number of days since the last infection, fall, medication error, etc.

There are very few clinicians who would agree that they provide substandard care, let alone harm their patients, but our outcomes data says otherwise. In their defense, the majority of frontline staff do not see the outcomes data, nor do they know what HAC, CAUTI, or Life Safety Code® even mean. Data transparency must begin either by using common language or educating staff on the jargon. As long as outcomes data is not shared, nurses and physicians will continue to see every hospital-acquired infection as another condition to treat, rather than a reason to pause and determine how the patient was injured and ensuring the situation does not reoccur. The more this information is publicized, the more the staff will realize there is room for improvement. The more transparent leaders are, the more staff will know of the organization’s safety status, and the more they will listen to infection preventionists, quality directors, patient safety officers, and others when we share organizational deficiencies.

So what? Find metrics that the organization and the staff care about. Post the metrics and their definitions conspicuously. Discuss the metrics in meetings, review them in orientation, etc. so that everyone knows about that data. It will be a source of pride or a kick in the pants.

2. Celebrate the wins. When you have found something to track, celebrate when teams have done well. The only fortune cookie slip I have ever kept says, “Do not let ambitions overshadow small successes.” Cookies or pizza go a long way to encourage staff, especially when delivered by the leaders involved. One hospital created stiff competition in their hand hygiene program by giving a big, tacky trophy to the department with the highest compliance and observations. This trophy changes hands at the end of every month with some pomp and ceremony. They celebrate a simple (but effective) prevention measure in a simple (but effective) way.

Infection preventionists tend to be harbingers of doom, and rightly so. The majority of my emails involve a problem that must be addressed. So I make it a point to send messages sharing good outcomes, such as “Congratulations, your unit had no infections last month!” When these messages reach the frontline staff, I hear about it when I do rounds. They are proud, but also express how they thought they were doing well for their patients all along (see #1). This becomes a moment to educate on CMS safety measures, perception of patient harm, and prevention programs in place or in development.

So what? Celebrate the wins, however small. It is encouraging, it shows that staff are valued, and it makes bad news more palatable.

3. Healthcare workers do not always know how they harm patients. There are many instances when healthcare workers take shortcuts and (as far as they know) nothing bad happens to the patient. The absence of a known, directly linked bad outcome validates the shortcut so it will be propagated and repeated. If we report bad outcomes quicker, staff can provide more useful information in event reviews. Real-time feedback (or as close to it as possible) has been shown in studies to encourage safer behaviors (Karan & Kopelman, 1987; Alvero et al., 2001; Spooner et al., 2007), as our own life experiences can corroborate. Part of the problem, as earlier mentioned, is that clinicians take care of a lot of patients. Infection surveillance software enables quicker reporting of infections. This should prompt closer to real-time reviews so that any lapses in care are promptly identified, communicated, and halted.

So what? Infection surveillance software/reporting systems enable closer-to-real-time event reporting if we choose to move away from the monthly reporting systems many of us are accustomed to. The key is reviewing cases as soon as they are identified and involving frontline staff, not just managers and directors. Culture algorithms are excellent tools to keep this review from becoming a witch hunt (Boysen, 2013).

4. Customize the copy of a basic unit-based infection report (see PDF) that I have used for a few years. When the staff looks at it, they should see exactly how their unit is contributing to the infection burden of the facility. I created it using a free Canva.com account, but I have used Microsoft PowerPoint®, Microsoft Publisher®, and Adobe InDesign® too. The leaders at my facility recently approved a banner showing days since the last infection and other quality metrics. This will be out for patients and staff to see. It should motivate staff and reinforce our focus on safety.

When healthcare workers and their patients know of safety events and their causes, they will be more mindful of infection/safety risk and relevant prevention measures. Our hospitals will be that much safer. Data transparency will not solve the HAI problem, just as daytime running lights have not solved motorcycle fatalities, but it will increase awareness. That is how change begins, because healthcare workers do not set out to hurt patients.

Gowe is an infection preventionist in quality services at Margaret R. Pardee Memorial Hospital in Hendersonville, North Carolina. Originally published in Inside Accreditation & Quality.

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• Boysen, P. G., 2nd. (2013). Just culture: A foundation for balanced accountability and patient safety. The Ochsner Journal, 13(3), 400–406.
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• Livanos, N. (2018). A broadening coalition: Patient safety enters the nurse-to-patient ratio debate. Journal of Nursing Regulation, 9(1), 68–70.
• Leapfrog Group. (2019, May 14). Lives lost and lives saved. Retrieved from https://www.hospitalsafetygrade.org/your-hospitals-safety-grade/LivesLost
• National Highway Traffic Safety Administration. (n.d.). Traffic safety facts: 2008 data: Motorcycles. Retrieved from https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/811159
• Nazemetz, J. W., Bents, F. D., Perry, J. G., Thor, C. P., Tan, C., & Mohamedshah, Y. M. (2019). Motorcycle crash causation study: Final report (No. FHWA-HRT-18-064). Retrieved from https://www.fhwa.dot.gov/publications/research/safety/18064
• Spooner, B. B., Fallaha, J. F., Kocierz, L., Smith, C. M., Smith, S. C. L., & Perkins, G. D. (2007). An evaluation of objective feedback in basic life support (BLS) training. Resuscitation, 73(3),17–424.
• Boysen P. G., 2nd (2013). Just culture: a foundation for balanced accountability and patient safety. The Ochsner journal, 13(3), 400–406.