The cost-effectiveness of sub-epidermal moisture scanning to assess pressure injury risk in U.S. health systems

Objective Hospital-acquired pressure injuries harm over 2.5 million patients at a U.S. cost of $26.8 billion. Sub-epidermal moisture scanning technology supports clinicians to anatomically identify locations at-risk of developing hospital-acquired pressure injuries. Our objective was to evaluate the cost-effectiveness of adopting sub-epidermal moisture scanners in comparison to existing hospital-acquired pressure injury prevention guidelines structured around subjective risk assessments.Methods A Markov cohort model was developed to analyze the cost-effectiveness of sub-epidermal moisture scanners in comparison to existing prevention guidelines, based on current clinical trial data from the U.S. health care sector perspective in the acute, acute rehabilitation and skilled nursing facility settings. A hypothetical cohort was simulated over a time horizon of one year. An incremental cost-effectiveness ratio was measured using U.S. dollars per quality-adjusted life year at a willingness-to-pay threshold of $100,000/quality-adjusted life year, and uncertainty was tested using probabilistic sensitivity analysis.Results Integration of sub-epidermal moisture scanners yielded cost-savings of $4054 and 0.35 quality-adjusted life years gained per acute care admission, suggesting that sub-epidermal moisture scanners are a dominant strategy compared to standard care and producing a net monetary benefit of $39,335. For every 1000 admissions in high-risk acute care, sub-epidermal moisture scanners could avert around seven hospital-acquired pressure injury-related deaths and decrease hospital-acquired pressure injury-related re-hospitalization by approximately 206 bed-days.Conclusions Acute care, acute rehabilitation and skilled nursing settings that adopt sub-epidermal moisture technology could achieve a return on investment in less than one year. Providers may want to consider these types of technology that aid clinical judgment with objective measures of risk in quality improvement bundles.