April 4, 2022 | Net Health

3 min read

Pressure Injury Monitoring: Using Technology in a Time of Overcrowding

Submitted by Wound Source

In the last two years, hospitals have seen unprecedented surges in admissions attributed to the COVID-19 pandemic sweeping across the world. Just in the United States, we saw a high of 116,243 weekly hospital admissions in mid-January of 2021. This dropped to a low of 13,424 in mid-June of 2021 and then bumped up again to 86,871 in August of 2021.1

With this fluctuation of numbers, along with staffing shortages and burnout, wound care professionals have seen significant overcrowding in many hospitals and facilities. Caregivers and clinicians are stretched thin. They are taking on more patients, who tend to be sicker and with more acute needs on a global scale. These patients tend to be at higher risk of developing a pressure injury (PI) because of prolonged illness, decreased activity, and increased intensive care unit stays.

Clinicians can rely on traditional methods to minimize the development of a PI, such as frequent repositioning, using proper offloading support surfaces, and ensuring cleanliness and nutritional needs, but these measures may not be possible in some cases. How can wound care professionals minimize the risk for PI development in these at-risk patients when they may simply not have enough time or staff to help reposition these patients as frequently as recommended? This is where clinicians can turn to some novel technologies to assist them.

Novel Tools

We currently rely on subjective tools, such as the Braden Scale, to assess risk for a PI in patients. What if clinicians can use novel tools, such as artificial intelligence (AI), as an assist? Although machines will never replace the careful eye of an experienced clinician, they can certainly assist them; particularly if staff is stretched to the limit. AI is a type of machine learning (ML) that can help to improve prognosis and diagnosis. It can also help to objectively identify patients at higher risk of developing a PI and alert staff to this risk. It can also be used to predict wound healing rates and risk of amputation.

Although EMRs are not as new as other technologies mentioned, they continue to evolve and improve. These systems allow for easy documentation of patient visits, interventions, dressing changes, and other interactions. These records ensure that all staff have access to the patient’s file and all relevant information and that no documents can be lost by falling out of a folder. Further, these records can often be transferred between facilities, thus allowing for continuity of care for the patient.

Imaging applications have evolved with technology, especially the advent of the smart phone. As smart phone cameras have improved in quality, so have these tools. Imaging applications allow for easy documentation of the wound. Many have auto-measuring software, allowing clinicians to save time by reducing the need for paper rulers and descriptions of how the measurements were taken. The photographs can then be uploaded to the EMR, thereby making them easily accessible the next time the patient is seen by a clinician.

In Summary

These tools help clinicians identify patients at higher risk and help prevent PIs. These solutions have the potential to allow staff to focus on the most at-risk patients. Although clinical judgment should never be superseded by these tools, it may be beneficial in the prioritization of needs. In addition to assisting clinical staff, these tools can also be used by patients themselves. If a patient is capable of repositioning on their own, these tools can help trigger an alert to them, letting them know that it’s time to move. Ultimately, the goal is to prevent PIs from developing. By increasing the overall efficiency of our time, we can hopefully manage our time and resources in a way that prevents increased burden on everyone.

The Future of Wound Care: Predictive Analytics

Changing the way wound care clinics operate and treat patients.

References

  1. Weekly new hospital admission for COVID-19. Our World in Data. Accessed November 4, 2021. https://ourworldindata.org/grapher/weekly-hospital-admissions-covid?time…
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