Abstract
Introduction
Real-time pressure mapping devices may help prevent hospital-acquired pressure injury (HAPI) in Burn ICU (BICU) patients who are at a high baseline risk for HAPIs. While prior studies have demonstrated the utility of pressure monitoring devices in preventing pressure injuries, there has been little investigation into using pressure mapping data to better understand HAPI development, and to determine specific predictors of HAPIs. Such data could help risk stratify patients upon admission to the BICU and result in improved patient care as well as cost savings. This study retrospectively investigated the utility of pressure mapping data in predicting/preventing pressure injury among BICU patients, and estimated HAPI-related cost savings associated with the implementation of pressure monitoring.
Methods
This was a retrospective chart review of real-time pressure mapping in the BICU. Incidence of HAPIs and costs of HAPI-related care were determined through clinical record review, before and after implementation of pressure mapping. Multivariable-adjusted logistic regression was used to determine predictors of HAPIs, in the context of pressure mapping recordings.
Results
In total, 122 burn ICU patients met inclusion criteria during the study period, of whom 57 (47%) were studied prior to implementation of pressure mapping, and 65 (53%) were studied after implementation. The HAPI rate was 18% prior to implementation of pressure monitoring, which declined to 8% after implementation (chi square: p=0.10). HAPIs were more likely to be less severe in the post-implementation cohort (p< 0.0001). Upon multivariable-adjusted regression accounting for known predictors of HAPIs in burn patients (BMI, length of stay, co-morbidities, age, total body surface area burned, mobility), having had at least 12 hours of sustained pressure loading in one area significantly increased odds of developing a pressure injury in that area (odds ratio 1.3, 95%CI 1.0–1.5, p=0.04). When comparing patients who developed HAPIs to those who did not, pressure mapping demonstrated that patients who developed HAPIs were significantly more likely to have had unsuccessful repositioning efforts prior to HAPI development, defined as persistent high pressure in the at-risk area (60% versus 17%, respectively; p=0.02). Finally, implementation of pressure mapping resulted in significant cost savings ($2,063 prior to implementation, versus $1,082 after implementation, p=0.008).
Conclusions
The use of real-time pressure mapping decreased incidence of HAPIs in the burn ICU patients and resulted in significant cost savings.
Estimating the additional indirect cost savings of a procalciton-algorithm in adult icu patients with sepsis, as achieved through reduction in antibiotic resistance and c. Difficile infections
