Standardizing the classification of skin tears: validity and reliability testing of the International Skin Tear Advisory Panel Classification System in 44 countries

H Van Tiggelen, K LeBlanc, K Campbell, K Woo, S Baranoski, Y Y Chang, A M Dunk, M Gloeckner, H Hevia, S Holloway, P Idensohn, A Karadağ, E Koren, J Kottner, D Langemo, K Ousey, A Pokorná, M Romanelli, V L C G Santos, S Smet, G Tariq, K Van den Bussche, A Van Hecke, S Verhaeghe, H Vuagnat, A Williams, D Beeckman, H Van Tiggelen, K LeBlanc, K Campbell, K Woo, S Baranoski, Y Y Chang, A M Dunk, M Gloeckner, H Hevia, S Holloway, P Idensohn, A Karadağ, E Koren, J Kottner, D Langemo, K Ousey, A Pokorná, M Romanelli, V L C G Santos, S Smet, G Tariq, K Van den Bussche, A Van Hecke, S Verhaeghe, H Vuagnat, A Williams, D Beeckman

Abstract

Background: Skin tears are acute wounds that are frequently misdiagnosed and under-reported. A standardized and globally adopted skin tear classification system with supporting evidence for diagnostic validity and reliability is required to allow assessment and reporting in a consistent way.

Objectives: To measure the validity and reliability of the International Skin Tear Advisory Panel (ISTAP) Classification System internationally.

Methods: A multicountry study was set up to validate the content of the ISTAP Classification System through expert consultation in a two-round Delphi procedure involving 17 experts from 11 countries. An online survey including 24 skin tear photographs was conducted in a convenience sample of 1601 healthcare professionals from 44 countries to measure diagnostic accuracy, agreement, inter-rater reliability and intrarater reliability of the instrument.

Results: A definition for the concept of a 'skin flap' in the area of skin tears was developed and added to the initial ISTAP Classification System consisting of three skin tear types. The overall agreement with the reference standard was 0·79 [95% confidence interval (CI) 0·79-0·80] and sensitivity ranged from 0·74 (95% CI 0·73-0·75) to 0·88 (95% CI 0·87-0·88). The inter-rater reliability was 0·57 (95% CI 0·57-0·57). The Cohen's Kappa measuring intrarater reliability was 0·74 (95% CI 0·73-0·75).

Conclusions: The ISTAP Classification System is supported by evidence for validity and reliability. The ISTAP Classification System should be used for systematic assessment and reporting of skin tears in clinical practice and research globally. What's already known about this topic? Skin tears are common acute wounds that are misdiagnosed and under-reported too often. A skin tear classification system is needed to standardize documentation and description for clinical practice, audit and research. What does this study add? The International Skin Tear Advisory Panel Classification System was psychometrically tested in 1601 healthcare professionals from 44 countries. Diagnostic accuracy was high when differentiating between type 1, 2 and 3 skin tears using a set of validated photographs.

© 2019 The Authors. British Journal of Dermatology published by John Wiley & Sons Ltd on behalf of British Association of Dermatologists.

Figures

Figure 1
Figure 1
The International Skin Tear Advisory Panel (ISTAP) Classification System.

References

    1. LeBlanc K, Christensen D, Cook J et al Prevalence of skin tears in a long‐term care facility. J Wound Ostomy Continence Nurs 2013; 40:580–4.
    1. Skiveren J, Bermark S, LeBlanc K, Baranoski S. Danish translation and validation of the International Skin Tear Advisory Panel Skin Tear Classification System. J Wound Care 2015; 24:388–92.
    1. Bermark S, Wahlers B, Gerber AL et al Prevalence of skin tears in the extremities in inpatients at a hospital in Denmark. Int Wound J 2018; 15:212–17.
    1. LeBlanc K, Baranoski S. Skin tears: best practices for care and prevention. Nursing 2018 2014; 44:36–46.
    1. LeBlanc K, Campbell K, Beeckman D et al Best practice recommendations for the prevention and management of skin tears in aged skin. Available at: (accessed 1 November 2019).
    1. LeBlanc K, Baranoski S. Skin tears: finally recognized. Adv Skin Wound Care 2017; 30:62–3.
    1. LeBlanc K, Baranoski S. Skin tears: state of the science: consensus statements for the prevention, prediction, assessment, and treatment of skin tears. Adv Skin Wound Care 2011; 24:2–15.
    1. Serra R, Ielapi N, Barbetta A, de Franciscis S. Skin tears and risk factors assessment: a systematic review on evidence‐based medicine. Int Wound J 2018; 15:38–42.
    1. Strazzieri‐Pulido KC, Peres GRP, Campanili TCGF et al Incidence of skin tears and risk factors. J Wound Ostomy Continence Nurs 2017; 44:29–33.
    1. Chaplain V, Labrecque C, Kevin YW, LeBlanc K. French Canadian translation and the validity and inter‐rater reliability of the ISTAP Skin Tear Classification System. J Wound Care 2018; 27:S15–20.
    1. McErlean B, Sandison S, Muir D et al Skin tear prevalence and management at one hospital. Prim Intent 2004; 12:83.
    1. McLane KM, Bookout K, McCord S et al The 2003 National Pediatric Pressure Ulcer and Skin Breakdown Prevalence Survey: a multisite study. J Wound Ostomy Continence Nurs 2004; 31:168–78.
    1. Santamaria N, Carville K, Prentice J. Woundswest: identifying the prevalence of wounds within western Australia's public health system. EWMA J 2009; 9:13–18.
    1. Hsu M, Chang S. A study on skin tear prevalence and related risk factors among inpatients. Tzu Chi Nurs J 2010; 9:84–95.
    1. Lopez V, Dunk AM, Cubit K et al Skin tear prevention and management among patients in the acute aged care and rehabilitation units in the Australian Capital Territory: a best practice implementation project. Int J Evid Based Healthc 2011; 9:429–34.
    1. Chang YY, Carville K, Tay AC. The prevalence of skin tears in the acute care setting in Singapore. Int Wound J 2016; 13:977–83.
    1. Amaral AFdS, Pulido KCS, Santos VLCdG. [Prevalence of skin tears among hospitalized patients with cancer] Rev Esc Enferm USP 2012; 46:44–50 (in Portuguese).
    1. Maida V, Ennis M, Corban J. Wound outcomes in patients with advanced illness. Int Wound J 2012; 9:683–92.
    1. Carville K, Lewin G. Caring in the community: a wound prevalence survey. Prim Intent 1998; 6:54–62.
    1. Carville K, Smith J. A report on the effectiveness of comprehensive wound assessment and documentation in the community. Prim Intent 2004; 12:41–9.
    1. Koyano Y, Nakagami G, Iizaka S et al Exploring the prevalence of skin tears and skin properties related to skin tears in elderly patients at a long‐term medical facility in Japan. Int Wound J 2016; 13:189–97.
    1. Woo KY, Sears K, Almost J et al Exploration of pressure ulcer and related skin problems across the spectrum of health care settings in Ontario using administrative data. Int Wound J 2017; 14:24–30.
    1. LeBlanc K. Skin Tear Prevalence, Incidence and Associated Risk Factors in the Longterm Care Population. Kingston, ON: Queen's University, 2017.
    1. Skiveren J, Wahlers B, Bermark S. Prevalence of skin tears in the extremities among elderly residents at a nursing home in Denmark. J Wound Care 2017; 26:S32–6.
    1. Woo K, LeBlanc K. Prevalence of skin tears among frail older adults living in Canadian long‐term care facilities. Int J Palliat Nurs 2018; 24:288–94.
    1. Strazzieri‐Pulido KC, Peres GRP, Campanili TCGF, Santos VLCdG. Skin tear prevalence and associated factors: a systematic review. Rev Esc Enferm USP 2015; 49:674–80.
    1. LeBlanc K, Baranoski S. Skin tears: the underappreciated enemy of aging skin. Wounds Int 2018; 9:6–10.
    1. Van Tiggelen H, Van Damme N, Theys S et al The prevalence and associated factors of skin tears in Belgian nursing homes: a cross‐sectional observational study. J Tissue Viability 2019; 28:100–6.
    1. Payne RL, Martin ML. The epidemiology and management of skin tears in older adults. Ostomy Wound Manage 1990; 26:26–37.
    1. White MW, Karam S, Cowell B. Skin tears in frail elders: a practical approach to prevention. Geriatr Nurs 1994; 15:95–9.
    1. Bank D, Nix D. Preventing skin tears in a nursing and rehabilitation center: an interdisciplinary effort. Ostomy Wound Manage 2006; 52:38–46.
    1. Bajwa AA, Arasi L, Canabal JM, Kramer DJ. Automated prone positioning and axial rotation in critically ill, nontrauma patients with acute respiratory distress syndrome (ARDS). J Intensive Care Med 2010; 25:121–5.
    1. Carville K, Leslie G, Osseiran‐Moisson R et al The effectiveness of a twice‐daily skin‐moisturising regimen for reducing the incidence of skin tears. Int Wound J 2014; 11:446–53.
    1. Sanada H, Nakagami G, Koyano Y et al Incidence of skin tears in the extremities among elderly patients at a long‐term medical facility in Japan: a prospective cohort study. Geriatr Gerontol Int 2015; 15:1058–63.
    1. LeBlanc K, Baranoski S, Holloway S et al A descriptive cross‐sectional international study to explore current practices in the assessment, prevention and treatment of skin tears. Int Wound J 2014; 11:424–30.
    1. Payne R, Martin M. Defining and classifying skin tears: need for a common language. Ostomy Wound Manage 1993; 39:16–26.
    1. Carville K, Lewin G, Newall N et al STAR: a consensus for skin tear classification. Prim Intent 2007; 15:18.
    1. LeBlanc K, Baranoski S, Christensen D et al International Skin Tear Advisory Panel: a tool kit to aid in the prevention, assessment, and treatment of skin tears using a simplified classification system. Adv Skin Wound Care 2013; 26:459–76.
    1. LeBlanc K, Baranoski S, Holloway S, Langemo D. Validation of a new classification system for skin tears. Adv Skin Wound Care 2013; 26:263–5.
    1. Skiveren J, Bermark S, LeBlanc K, Baranoski S. Danish translation and validation of the international skin tear advisory panel skin tear classification system. J Wound Care 2015; 24:388–92.
    1. Källman U, LeBlanc K, Bååth C. Swedish translation and validation of the international skin tear advisory panel skin tear classification system. Int Wound J 2018; 16:13–18.
    1. da Silva CVB, Campanili TCGF, LeBlanc K et al Cultural adaptation and content validity of ISTAP Skin Tear Classification for Portuguese in Brazil. Rev Estima 2018; 16:1–7.
    1. R Core Team . R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing, 2018.
    1. Rotondi MA, Donner A. A confidence interval approach to sample size estimation for interobserver agreement studies with multiple raters and outcomes. J Clin Epidemiol 2012; 65:778–84.
    1. Rotondi MA. Package ‘kappaSize’. Available at: (accessed 1 November 2019).
    1. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977; 33:159–74.
    1. Sun Q, He Y, Liu K et al Recent advances in terahertz technology for biomedical applications. Quant Imaging Med Surg 2017; 7:345.
    1. Chai J, Ge J, Zou J. Effect of Autologous platelet‐rich plasma gel on skin flap survival. Med Sci Monit 2019; 25:1611–20.
    1. Beeckman D, Schoonhoven L, Fletcher J et al Pressure ulcers and incontinence‐associated dermatitis: effectiveness of the Pressure Ulcer Classification education tool on classification by nurses. Qual Saf Health Care 2010; 19:e3.
    1. Edsberg LE, Black JM, Goldberg M et al Revised National Pressure Ulcer Advisory Panel pressure injury staging system: revised pressure injury staging system. J Wound Ostomy Continence Nurs 2016; 43:585.
    1. European Pressure Ulcer Advisory Panel . Guide to Pressure Ulcer Grading. EPUAP Rev 2002; 3:75.
    1. Beeckman D, Schoonhoven L, Fletcher J et al EPUAP classification system for pressure ulcers: European reliability study. J Adv Nurs 2007; 60:682–91.
    1. Defloor T, Schoonhoven L, Katrien V et al Reliability of the European pressure ulcer advisory panel classification system. J Adv Nurs 2006; 54:189–98.
    1. Beeckman D, Van den Bussche K, Alves P et al Towards an international language for incontinence‐associated dermatitis (IAD): design and evaluation of psychometric properties of the Ghent Global IAD Categorization Tool (GLOBIAD) in 30 countries. Br J Dermatol 2018; 178:1331–40.
    1. Benner P. From novice to expert. Am J Nurs 1982; 82:402–7.

Source: PubMed

3
Tilaa