SCIENCE, PRACTICE AND EDUCATION Table 1: Skin Tear Classification Systems Skin Tear Classification System Payne-Martin 3 ISTAP 8 Skin Tear Category Category 1: No tissue loss - linear Category 1: No tissue loss - flap Category 2: Partial tissue loss (<25%) Category 2: Partial tissue loss (>25%) Category 3: Complete skin loss Category 1: No skin loss Category 2: Partial flap loss Category 3: Total flap loss happen among neonates, the critically ill or disabled populations. 6,8 Internationally, the prevalence and incidence of skin tears across skilled nursing facilities (SNF) (long-term care and nursing organisations) and hospitals have been explored. Evidence showed that SNFs record the highest incidence rate of skin tears, accounting for up to 92%, and a prevalence rate of up to 26% 8 in traditional studies. tice, or that they lack standardised terminology. 11 Therefore, the International Skin Tear Advisory Panel (ISTAP) Classification System was developed to sim- plify assessment. 8 The system is based on the severity of the skin flap’s loss and categorises skin tears with no skin/flap loss as Type 1, tears with partial skin/ flap loss as Type 2 and those with complete skin/flap loss as Type 3. 8 A comprehensive understanding of skin tears’ preva- lence in SNFs is necessary to inform comprehensive prevention and management strategies that sup- port standardised assessment and better treatment plans. Delayed or inappropriate management and prolonged care may negatively impact the quality of patient care. 9 The high prevalence and incidence of skin tears poses a challenge to SNFs. An international study from 16 countries found organisations reported that a lack of reliable assessment tools, poor documentation of skin tears and systematic under-reporting are common barriers to the proper management of these wounds. More than two-thirds of clinicians reported substan- tial issues with their classification and documenta- tion. 10 Currently, at least three scales classify skin tears (Table 1). One of these tools ranks skin tears based on the percentage of tissue loss (the Payne-Martin classifi- cation). Another adds a skin flap colour distinction (Skin Tear Audit Research [STAR] Classification system). 8 However, evidence suggests that clinicians found these tools too complicated to use in prac- A number of studies have explored the frequency of skin tears across different facilities (Table 2). The data from these studies reflect a wide geographical loca- tion, but are generally limited to single facilities, are smaller in size and are mainly cross-sectional. Digitally collected health information for clinical documentation offers real-world evidence obtained directly from clinical practice in significantly larger numbers than traditional trials. With appropriate controls and analysis in place, regulators, such as the U.S. Food and Drug Administration, are begin- ning to accept these data sets as compelling evidence to support indications for medical interventions. 20 Using data generated by clinical practice can lower barriers to studying issues and provide access to in- formation about populations that may be excluded from randomised controlled trials, though the chal- lenges of using big data need to be considered. Still, real-world data may address limitations and biases faced by traditional studies (e.g., inclusion criteria, selection bias, information bias). 20 A wound management solution (Swift Skin and Wound, Swift Medical Inc.) comprised of a smart- JOURNAL OF WOUND MANAGEMENT OFFICIAL JOURNAL OF THE EUROPEAN WOUND MANAGEMENT ASSOCIATION 88
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