Before we dig into the data that will show you the importance of why it matters what data you use when improving your hospitals hand hygiene compliance, we need to look at hand hygiene from a bigger perspective.
Healthcare-associated infections are a global problem
In hospitals, contaminated hands due to poor hygiene compliance is the leading cause of healthcare-associated infections (HAIs). Period. If you improve hand hygiene, infections are prevented. Thus, every major accreditation and infection control body has a statement that reflects this. Despite this, many physicians and hospital leaders are surprised by the large impact hand hygiene can have.
Sadly, this is nothing new; the well-established principle of hand hygiene has been known for over 150 years when Dr. Semmelweis discovered that puerperal fever (“childbed fever”) could be prevented by the use of hand disinfection in obstetrical clinics. Yet, despite all the accumulated evidence since then, we are still engaging in the same dialogue that frustrated Dr. Semmelweis all those years ago. Improving hand hygiene compliance is difficult.
A data-driven approach is key to success
Infection preventionists need high-quality data on how good the organization is performing – data that can be both expensive and difficult to obtain. Since the dawn of modern infection prevention the golden standard have been performing direct observations of staff to gather hand hygiene compliance data. But since the discovery of how invalid the data is due to several factors such as the Hawthorne effect, it is becoming less popular. Instead, several electronic solutions have been proposed, tested and commercialized to provide ways to gather this data cheaper and easier. But as technology has limitations so does these solutions. To develop solutions that are both unobtrusive to workflow and technologically feasible, new indicators for hand hygiene compliance have been pushed from the industry. But before we introduce you to what these new indicators are and what limitations they have, we need to agree on what impacts infection prevention in hand hygiene – and what does not.
The Hand Hygiene Guidelines
Let us be honest, hand hygiene guidelines are not very easy to comprehend and the “Five Moments of Hand Hygiene”-illustration does not make it any easier. But what the guidelines basically want to avoid is cross-contamination, i.e. the transportation of bacteria from unclean hands to the patients. The hands of healthcare workers are the best place to start because they pose the greatest risk of cross-contamination due to frequent contact between many patients and due to the unclean procedures involved with patient care. This is why the hygiene guidelines setup a list of rules that enforce hand sanitation before clean procedures and after dirty procedures, i.e. procedures related to patient contact, toilet visits, handling of medicine etc. In order to fulfill these guidelines, healthcare workers have to sanitize a great number of times each day. One of the biggest complaints from healthcare workers is actually their frustration over the many times they have to sanitize their hands. This number can easily be more than 50 times a day. By using an automated hand hygiene monitoring system, you can actually reduce number of times you sanitize while still increasing the compliance rate – simply because you learn when sanitization is needed. But – and yes there is a “but” – it depends on the solution you chose to implement.
The industry’s indicators for hand hygiene
Electronic systems are a good way to gather hand hygiene data. You simply set up rules and the system check if the rules are being followed or not. But the devil is in the detail. To ensure a less complex installation and setup, current solutions have made the detail of the data more simple. Instead of measuring patient contact, toilet visits or handling of medicine they count the number of times healthcare workers sanitize and compare it with the rooms they enter. The claim is that this data can be used as true indicators for hand hygiene compliance. We will like to challenge that claim.
Validating the new indicators
What makes the Sani Nudge solution unique is that even though the installation is simple it is still able to provide very detailed data. In contrast to the other simple solutions, the Sani Nudge hand hygiene monitoring solution can measure if healthcare workers are in patient contact and if they perform hand hygiene before or after that. This is what WHO’s Five Moments for Hand Hygiene Guidelines uses to determine true hand hygiene compliance rates and what is the golden standard today. We used this method to compare how often a healthcare worker sanitized without being in a situation that required it. The results were used to compare if the number of hand sanitations is a valid indicator of the overall compliance rate.
Method
We compared data from the 23.07.2018 until 27.01.2019 (week 30, 2018 to week 4, 2019) obtained at a Danish hospital. During the period, the healthcare workers entered patient rooms more than 20,000 times.
Result
1) Number of hand sanitations compared to patient contact compliance rate:
Figure 1 shows the rate of times a nurse remembered to sanitize hand before and after being in patient contact illustrated as a percentage number on the right Y-axis (compliance rate). This is compared to the average number of sanitations (counts) done by the same nurses in that period shown on the left Y-axis.
Figure 1. No correlation between compliance rate and the number of sanitizations. Source: Data from the Sani Nudge system from Danish hospitals.
Interestingly, Figure 1 shows that there is no correlation between the compliance rate and the number of times the nurses sanitized.
This makes it clear that the number of sanitizations by healthcare workers cannot be used as validator of a hand hygiene compliance rate.
2) Hand sanitations at room entry/exit compared to patient contact compliance rate:
Some solutions use a combination of hand sanitations and room visits to determine a hand hygiene compliance rate. The hypothesis is that a healthcare worker’s compliance rate is 100% if they sanitize their hands before entering and after exiting a patient room. Because these solutions do not measure patient contact or differentiate between rooms with multiple beds, they will never allow insight into how well healthcare workers are at sanitizing between procedures and between patient contact (interpatient contact).
Figure 2 Source: Data from the Sani Nudge system from Danish hospitals.
Figure 2 shows that there is no correlation between the average compliance rate using patient contact (Y-axis) and average compliance rate using only room entry/exit. There are two noteworthy differences:
- The overall compliance rate is significantly higher when only measuring compliance at room level, i.e. entry and exist (compliance rate in room). The likely reason is that this rule is a lot simpler, as it does not take any action/procedures in the patient room into account.
- When measuring compliance rates at room level , the compliance fluctuates considerably more, which is most likely due to lower number of data points as fewer hygiene situations are captured.
This makes it clear that using room entry/exit instead of before/after patient contact cannot be used as validator of a hand hygiene compliance rate.
If we compare three hospitals using each method we will find the following results:
- Hospital A – measures hand hygiene by the number of times staff sanitize hands
- Hospital B – measures hand hygiene by the number of times staff sanitize hands at patient room entry/exit.
- Hospital C- measures hand hygiene by the number of times staff sanitize hands before/after patient contact.
Hospital A will have a very high hand hygiene compliance rate as they measured their hand hygiene according to how much they improved the number of hand sanitations. An improvement of 250% must be a clear indicator of perfect hand hygiene compliance. In reality it hand hygiene compliance improved by 27%.
Hospital B will also show a better hand hygiene compliance. The difference will be more accurate, but they will have an average compliance rate of 78% instead of the actual compliance rate of 49%.
Hospital C will know exactly how good staff is at sanitizing hands before or after being in patient contact. The compliance rate will be lower and more stable, but it will clearly show if the staff is compliant to the rules important to avoid infections.
