Advanced Health Assessment & Clinical Diagnosis In Primary Care 6th Edition – Arnaoutakis DJ, Sculli RE, Sharma G Influence of body mass index and gender on wound complications after lower extremity arterial surgery. J Vasc Surg. 2017; 65:(6)1713-1718.e1 https://doi.org/10.1016/j.jvs.2016.12.116
Bale S, Tebble N, Jones V, Price P. Benefits of implementing a new skin care protocol in nursing homes. J Tissue Viability. 2004; 14:(2)44-50 https://doi.org/10.1016/S0965-206Ks(04)42001-4
Advanced Health Assessment & Clinical Diagnosis In Primary Care 6th Edition
Bergstrom N, Braden BJ, Laguzza A, Holman V. Braden scale for predicting the risk of pressure ulcers. Nurs Res. 1987; 36:(4)205-210 https://doi.org/10.1097/00006199-198707000-00002
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Fumarola S, Allaway R, Callaghan R Overlooked and underestimated: medical adhesive-related skin injuries. J Wound care. 2020; 29:S1-S24 https://doi.org/10.12968/jovc.2020.29.Sup3c.S1
Kottner J, Lichterfeld A, Blume-Peitavi U. Maintaining skin integrity in old age: a systematic review. Br J Dermatol. 2013; 169:(3)528-542 https://doi.org/10.1111/bjd.12469
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Skin is often described in fictional literature as a window to the soul. It is the largest organ in the body and is an integral part of physical and psychosocial health. A complete skin assessment is essential for holistic care and must be performed regularly by nurses and other healthcare professionals. Providing information to patients and relatives about good skin hygiene can improve skin integrity and reduce the risk of damage from pressure and skin tears.
The skin is the largest organ in the body and accounts for 15% of the total body weight. It is an integral part of both physical and psychosocial health and can have an impact on patients’ quality of life (Wounds UK, 2018). In a healthy person, the skin is strong, resilient and has an exceptional ability to repair itself. It consists of three layers (picture 1). The epidermis, the outermost layer, provides a waterproof barrier, the dermis lies beneath the epidermis, has a rich blood supply, and contains tough connective tissue, hair follicles, sweat glands, and sensory nerve endings; the hypodermis (deep subcutaneous tissue) is made up of fat and connective tissue.
Damage can occur if the skin becomes susceptible to external and internal injury due to aging and altered physiology (Moncrieff et al, 2013). Changes to the skin can be external, for example pressure, shear or friction, or it can be caused by environmental damage. The latter can be caused by regular use of detergent or exposure to the sun. Internal factors can also affect the skin, for example psoriasis, atopic eczema or an underlying disease. The aging process significantly affects the skin: it becomes thinner, loses elasticity and moisturizing factors, blood flow decreases and the amount of fat under the skin decreases (Moncrieff, 2013). This can cause the skin to become fragile, vulnerable and dry (Kottner et al, 2013).
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Gender also affects skin integrity, and sex hormones can inhibit skin repair. Research in mice suggests that females recover faster than males due to estrogen and testosterone deficiency (Peter et al, 2012). However, in women, the menopausal transition involves a period of hormonal instability that affects the skin. These changes lead to a decrease in collagen content, water content, elasticity and thickness, which affects the quality of all skin layers (Reus et al, 2020).
Early recognition of people who are at risk of developing skin damage is an essential part of prevention. Assessment of skin condition should be part of a holistic approach and should be carried out regularly in practice. When evaluating:
Soap removes lipids from the surface of the skin, which can lead to dryness. The use of emollients and soap substitutes is recommended to help improve skin health, reduce dryness and improve symptoms of itching and tightness. The use of emollients applied twice daily is also a key part in the prevention of skin tears and superficial pressure ulcers (Bale et al, 2004).
Identify whether the patient has risk factors for sensitive skin. Complete a complete skin examination from head to toe, paying particular attention to any areas of redness, discoloration, dryness, sensitivity, irritation, or rash.
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Protein is essential for skin health to enable optimal production of keratin (an important protein in the epidermis). Keratin’s function is to hold cells together and form a protective layer on the outside of the skin. If there is a lack of protein, and therefore a reduced amount of keratin, the risk of skin breakdown increases. Fatty acids help to lubricate and moisturize the skin, and other essential vitamins such as C and A play an important role in strengthening and regenerating tissues (NHS Quality Improvement Scotland, 2010).
Risk factors for skin tears include: extreme age, dry/brittle skin, previous skin tearing, history of falls, reduced mobility, mechanical trauma, and dependence on assistance with daily activities. General health, comorbidities, polypharmacy, malnutrition, and impairment or changes in cognition are also risk factors.
Where possible, it is recommended that a full skin assessment be carried out face-to-face with the patient. However, the current COVID-19 pandemic has affected patient consultations and moved many of them online. For an online skin assessment, nurses must provide the following:
Good skin health is essential for personal health and well-being. The skin is often a “window” into a patient’s overall health and should be assessed regularly as part of a holistic assessment. Early recognition of skin changes and interventions can have a significant impact on the patient’s quality of life and will reduce the risk of pressure damage and skin tears. Authors: Julia Adler-Milstein, Nakul Aggarwal, Mahnoor Ahmed, Jessica Castner, Barbara J. Evans, Andrew A. Gonzalez, Cornelius A. James, Stephen Lynn, Kenneth D. Mandle, Michael E. Matheny, Mark P. Sendak, Carmel Shachar and Asia Williams
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Clinical diagnosis is essentially a data collection and analysis activity through which clinicians seek to gather and synthesize enough information about a patient to determine their condition. The art and science of clinical diagnosis dates back to ancient times, with the earliest diagnostic practices relying primarily on clinical observations of the patient’s condition, along with methods of palpation and auscultation (Mandl and Bourgeois, 2017; Berger, 1999). After a period of stagnation in clinical diagnostic practice, the 17th to 19th century was marked by a period of discovery that transformed modern clinical diagnostics, with the appearance of microscopes, laboratory analytical techniques, and more precise physical examination and recording tools (eg stethoscope). , ophthalmoscope, X-ray and electrocardiogram) (Walker, 1990). These fundamental achievements, among many others, laid the foundation for modern clinical diagnostics. However, the volume and breadth of data that clinicians are responsible for has grown exponentially, creating challenges for the human cognitive capacity to assimilate.
Computerized decision support (DDS) tools have emerged to alleviate the burden of data overload, improve clinicians’ decision-making abilities, and standardize care delivery processes. DDS tools are a subcategory of clinical decision support (CDS) tools, with the difference that DDS tools focus on diagnostic functions, while CDS tools may more broadly offer diagnostic, treatment, and/or prognostic recommendations. Debuting in the 1970s and 1980s, expert-based DDS tools such as MICIN, Iliad, and Quick Medical Reference worked by encoding current disease knowledge through a series of codified rules, which provided a diagnostic recommendation (Miller and Geissbuhler, 2007 .) Although these early DDS tools initially achieved pockets of success, the promise of many of these tools waned as several shortcomings became evident. Most prominently, data collection capacity and complexity of knowledge representation prevented accurate representation of pathophysiological relationships between disease and treatment. Programmed with a limited set of information and decision rules, several expert-based DDS tools could not be generalized to all settings and cases. Some also suffered from performance issues, often struggling to generate a result or giving the wrong diagnosis. Moreover, users were frustrated. Because these tools existed outside of mainstream clinical information systems, clinicians had to re-enter a long list of information to use them, creating significant friction in their workflows. Similarly, updating the DDS system’s knowledge base often required heavy manual input. Finally, there was a lack of incentives to encourage adoption. Therefore, provider acceptance remained low, and expert-based DDS tools faded from use (Miller, 1994).
The revitalization of the field of artificial intelligence (AI)—the ability of computer algorithms to perform tasks that typically require human intelligence—offers an opportunity to augment human diagnostic capabilities and address the limitations of expert-based DDS tools (Iu, Beam, & Kohane, 2018). Current AI
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