Improving the quality of pressure ulcer management in a skilled nursing facility.

Pressure ulcers (PUs) are a serious health care problem for nursing home residents and a key quality metric for regulators. Three initiatives were introduced at a 128-bed facility to improve PU prevention. First, a Quality Assurance and Performance Improvement project and a Root Cause Analysis were conducted to improve the facility's wound care programme. Second, a digital wound care management solution was adopted to track wound management. Third, the role of skin integrity coordinator was created as a central point of accountability for wound care-related activities and related performance metrics. Improvements in PU prevention were tracked using Centers of Medicare and Medicaid data, specifically (a) the percentage of long-stay high-risk residents with PUs and (b) the percentage of short-stay residents with PUs that are new or have worsened. PU prevalence for long-stay high-risk residents was 12.99% (Q4 2016), and upon implementation of these initiatives, the facility saw continued reductions in PU prevalence to 2.9% (Q4 2017), while PUs for short-stay residents were maintained at zero throughout this period. This study highlights the power of effective management combined with real-time data analytics, as enabled by digital wound care management, to make significant improvements in health care delivery.

Trends in pressure injury prevalence rates and average days to healing associated with adoption of a comprehensive wound care program and technology in skilled nursing facilities in the United States.

INTRODUCTION: A large SNF system in the United States adopted a holistic wound care model that included an AI DWMS to improve PI care. OBJECTIVE: To compare the trend in PI point prevalence rates and average days to healing linked to adopting technology in practice from 2021 to 2022, and to assess the rate of received PI F686 citations in facilities that adopted the technology compared with those that did not. METHODS: The study used the DWMS database to compare anonymized PI data assessed in 2021 (15 583 patients) vs 2022 (30 657 patients) from all SNF facilities that adopted the technology in 2021 and 2022. F686 citations data were provided by the SNF organization. RESULTS: There was a 13.1% reduction in PI prevalence from 2021 to 2022 across all PI stages. Facilities that adopted the technology demonstrated a significant reduction in days to healing from 2021 to 2022, with an average of 17.7 days saved per PI or a 37.4% faster healing rate (P < .001). A significant reduction in the average days to healing was noted for all PI stages, with the most significant savings observed for stages 3 and 4, with an average savings of 35 days (stage 3) and 85 days (stage 4) in 2022 vs 2021 (P < .001). From 2021 to 2022, facilities that adopted the technology reported an overall 8.2% reduction in F-686 citations severity >G compared to those that did not adopt the technology. CONCLUSION: Use of technology as part of a comprehensive wound care program has the potential to not only improve patient care and quality of life, but to realize considerable annual savings in additional PI out-of-pocket expenses (up to $1 410 000) and of clinicians' time (44 808 hours).

Towards an AI-Based Objective Prognostic Model for Quantifying Wound Healing.

Chronic wounds affect millions of people worldwide every year. An adequate assessment of a wound's prognosis is critical to wound care, guiding clinical decision making by helping clinicians understand wound healing status, severity, triaging and determining the efficacy of a treatment regimen. The current standard of care involves using wound assessment tools, such as Pressure Ulcer Scale for Healing (PUSH) and Bates-Jensen Wound Assessment Tool (BWAT), to determine wound prognosis. However, these tools involve manual assessment of a multitude of wound characteristics and skilled consideration of a variety of factors, thus, making wound prognosis a slow process which is prone to misinterpretation and high degree of variability. Therefore, in this work we have explored the viability of replacing subjective clinical information with deep learning-based objective features derived from wound images, pertaining to wound area and tissue amounts. These objective features were used to train prognostic models that quantified the risk of delayed wound healing, using a dataset consisting of 2.1 million wound evaluations derived from more than 200,000 wounds. The objective model, which was trained exclusively using image-based objective features, achieved at minimum a 5% and 9% improvement over PUSH and BWAT, respectively. Our best performing model, that used both subjective and objective features, achieved at minimum an 8% and 13% improvement over PUSH and BWAT, respectively. Moreover, the reported models consistently outperformed the standard tools across various clinical settings, wound etiologies, sexes, age groups and wound ages, thus establishing the generalizability of the models.

Measuring enactment of innovations and the factors that affect implementation and sustainability: moving toward common language and shared conceptual understanding.

This article describes research that focuses on the concern that researchers are unable to fully realize the potential value of their collective efforts because they do not have shared conceptual or operational tools for communicating assumptions, ideas, research strategies, or findings with others outside, or even within their disciplines. This research, through the lens of measuring implementation of educational programs, has taken steps toward bringing researchers' varied pictures of understanding into a coherent landscape. This article describes a conceptual framework for describing aspects of implementation, a conceptual framework for describing the factors that affect implementation, and tools for measuring each. It describes the challenges addressed in the development of these approaches, and the application of these approaches to current studies in education and other fields in the social sciences. In doing so, it demonstrates that meaningful communication between researchers and accumulation of knowledge across fields is possible, and necessary.