Risk factors associated with heel pressure ulcer development in adult population: A systematic literature review

Aims The main aim of this systematic literature review was to identify risk factors for development of heel pressure ulcers and quantify their effect. Background Pressure ulcers remain one of the key patient safety challenges across all health care settings and heels are the second most common site for developing pressure ulcers after the sacrum. Design Quantitative systematic review. Methods Data sources: Electronic databases were searched for studies published between 1809 to March 2020 using keywords, Medical Subject Headings, and other index terms, as well as combinations of these terms and appropriate synonyms. Study eligibility criteria: Previous systematic literature reviews, cohort, case control and cross-sectional studies investigating risk factors for developing heel pressure ulcers. Only articles published in English were reviewed with no restrictions on date of publication. Participants: patients aged 18 years and above in any care setting. Study selection, data extraction, risk of bias and quality assessment were completed by two independent reviewers. Disagreements were resolved by discussion. Results Eleven studies met the eligibility criteria and several potential risk factors were identified. However, eligible studies were mainly moderate to low quality except for three high quality studies. Conclusions There is a paucity of high quality evidence to identify risk factors associated with heel pressure ulcer development. Immobility, diabetes, vascular disease, impaired nutrition, perfusion issues, mechanical ventilation, surgery, and Braden subscales were identified as potential risk factors for developing heel pressure ulcers however, further well-designed studies are required to elucidate these factors. Other risk factors may also exist and require further investigation

Evaluating the impact of a ward environment with 20 single occupancy rooms and two four-bedded bays on patient and staff experiences and outcomes in an acute NHS Trust: A mixed methods study protocol.

Introduction Traditionally, wards in acute care hospitals consist predominately of multi-occupancy bays with some single rooms. There is an increasing global trend towards a higher proportion of single rooms in hospitals, with the United Kingdom (UK) National Health Service (NHS) advocating for single room provision in all new hospital builds. There is limited evidence on the impact of a ward environment incorporating mostly single and some multi-occupancy bays on patient care and organisational outcomes. Methods and analyses This study will assess the impact of a newly designed 28-bedded ward environment, with 20 single rooms and two four-bedded bays, on patient and staff experiences and outcomes in an acute NHS Trust in East England. The study is divided into two work packages (WP) – WP1 is a quantitative data extraction of routinely collected patient and staff data, while WP2 is a mixed methods process evaluation consisting of one-to-one, in-depth, semi-structured interviews with staff, qualitative observations of work processes on the ward and a quantitative data evaluation of routinely collected process evaluation data from patients and staff. Ethics and dissemination Ethical approval was obtained from the UK Health Research Authority (IRAS ID: 334395). Study findings will be shared with key stakeholders, published in peer-reviewed high impact journals, and presented at relevant conferences. Strengths and Limitations of this Study • A multi-method study using innovative and interdisciplinary approaches to explore the impact of a new ward environment on patient and staff experiences and outcomes. • Using a mixed methods approach provides an opportunity to gain rich and meaningful data from patients and staff over three different clinical areas. • Study findings will inform future hospital design at the research setting and potentially, other NHS Trusts. • Being a single site study and the sampling technique in qualitative interviews may limit transferrability and applicability of study findings

A predictive model for identifying patients at risk of delayed transfer of care: a retrospective, cross-sectional study of routinely collected data

Background: Delays to the transfer of care from hospital to other settings represent a significant human and financial cost. This delay occurs when a patient is clinically ready to leave the inpatient setting but is unable to because other necessary care, support or accommodation is unavailable. The aim of this study was to interrogate administrative and clinical data routinely collected when a patient is admitted to hospital following attendance at the emergency department, to identify factors related to delayed transfer of care when the patient is discharged. We then used these factors to develop a predictive model for identifying patients at risk for delayed discharge of care. Methods: This is a single centre, retrospective, cross-sectional study of patients admitted to an English National Health Service university hospital following attendance at the emergency department between January 2018 and December 2020. Clinical information (e.g., NEWS scores), as well as administrative data that had significant associations with admissions that resulted in delayed transfers of care, were used to develop a predictive model using a mixed-effects logistic model. Detailed model diagnostics and statistical significance, including receiver operating characteristic analysis, were performed. Results: Three-year (2018-20) data were used; a total of 92,444 admissions (70%) were used for model development and 39,877 (30%) admissions for model validation. Age, gender, ethnicity, National Early Warning Score, Glasgow admission prediction score (GAPS), Index of Multiple Deprivation decile, arrival by ambulance and admission within the last year were found to have a statistically significant association with delayed transfers of care. The proposed eight-variable predictive model showed good discrimination with 79% sensitivity (95% confidence intervals: 79%, 81%), 69% specificity (95% CI: 68%, 69%) and 70% (95% confidence intervals: 69%, 70%) overall accuracy of identifying patients who experienced a delayed transfer of care. Conclusion: Several demographic, socio-economic and clinical factors were found to be significantly associated with whether a patient experiences a delayed transfer of care or not following an admission via the emergency department. An eight-variable model has been proposed, which is capable of identifying patients who experience delayed transfers of care with 70% accuracy. The eight-variable predictive tool calculates the probability of a patient experiencing a delayed transfer accurately at the time of admission