[et_pb_section fb_built=”1″ admin_label=”section” _builder_version=”4.16″ da_disable_devices=”off|off|off” global_colors_info=”{}” da_is_popup=”off” da_exit_intent=”off” da_has_close=”on” da_alt_close=”off” da_dark_close=”off” da_not_modal=”on” da_is_singular=”off” da_with_loader=”off” da_has_shadow=”on”][et_pb_row admin_label=”row” _builder_version=”4.21.0″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_image src=”https:\/\/inspiren.com\/wp-content\/uploads\/2024\/02\/Amia-based-blog-final.png” alt=”case study – AMIA 2023 presentation” title_text=”Amia based blog – final” align=”center” align_tablet=”center” align_phone=”center” align_last_edited=”on|phone” admin_label=”Image” _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][et_pb_text admin_label=”Text” _builder_version=”4.21.0″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n
More than 1.5 million elderly adults in the US reside in nursing homes and 1 million in assisted living facilities (ALFs).\u00a0<\/span><\/p>\n For falls in the ALFs, the challenge lies in accurately documenting and understanding the activities of both patients and staff. A recent study, presented at the <\/span>2023 AMIA Annual Symposium<\/span><\/a>, sheds light on how remote monitoring data from hybrid sensing devices, such as AUGi, can revolutionize patient safety in ALFs by <\/span>benchmarking and accurately tracking falls as well as resident and staff activity.<\/span><\/p>\n Titled Staff and Patient Interactions at An Assisted Living Facility: A Longitudinal Descriptive Study<\/em>, the study was conducted in a New York City ALF, and employed AUGi technology to capture a comprehensive view of nurse interactions with patients over a 170-day period.\u00a0<\/span><\/p>\n The study group was made up of 215 residents, primarily elderly with an average age of 85, and with multiple chronic conditions.\u00a0<\/span><\/p>\n The following findings were built from data around rounding by staff, frequency and duration of interactions with patients, as well as interactions at each bed from the AUGi device. This rich data provides invaluable insights into staff activities, resident interactions, and the potential benefits of remote surveillance.<\/span><\/p>\n Some key findings from the data include:<\/b><\/p>\n <\/p>\n Over the study period, care teams were provided AI-driven alerts and had access to virtually round via a privacy-enabled live view functionality. Ensuring resident images were obfuscated, however context was available to the care team to triage alerts and workflow. The study noted that this ability to respond to alerts and check in on residents remotely could reduce redundant visits, streamline response times, and alleviate staff burden providing more effective and efficient care.<\/span> The conclusion of the study further touches upon how implementation of such technology contributes to predictive modeling aimed at reducing falls. It also allows for the development of benchmarking data to accurately track staff and resident behaviors, as well as resident harms – such as falls – in ALFs.<\/span><\/p>\n To learn about more results from this study and see how AUGi can support your ALF\u2019s goals, reach out to us <\/span>here<\/strong><\/span><\/a>.<\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" A new study provides insights into staff activities and resident interactions, and the potential benefits of remote surveillance in ALFs specifically.<\/p>\n","protected":false},"author":6,"featured_media":2459,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":" Efficient and effective care delivery of front line staff is paramount to promote consistent and high quality care. With mounting challenges of workforce shortages and increasing resident acuity, the integration of AI-driven and hybrid sensing technology is ushering in a new era of administering care. This innovative approach not only streamlines operations and boosts staff efficiency but also ensures compliance with safety protocols, ultimately leading to better outcomes.\u00a0<\/span><\/p> Before delving into the benefits of AI-driven hybrid sensing technology, it's important to understand what it is. Hybrid sensing technology like <\/span>AUGi<\/span><\/a> uses a combination of sensors contained in a single device, all powered by AI, to passively monitor resident activity and provide insights at the point of care. Staff are notified in real-time of resident safety risks and real-time resident resident behavioral data helps create a feedback loop that enables assisted living facilities (ALFs) and\/or hospitals to enhance their plan of care.<\/span><\/p> In a recent research, published in the <\/span>Journal of Informatics Nursing<\/span>\u24c7<\/span><\/a>, AUGi was shown to enhance Safety Protocol Compliance by achieving a significant increase in hourly rounding (HR) and bedside shift report (BSR) events by staff throughout the study period. It also highlighted how the technology and platform helped improve staff efficiency, even during the height of the pandemic and its consequent staffing shortages coupled with heightened healthcare environment.\u00a0\u00a0<\/span><\/p> Here are 3 ways in which AI-driven hybrid sensing technology is revolutionizing healthcare by improving staff efficiency and safety protocol compliance.<\/b><\/p> The healthcare industry continues to face staffing shortages, increased strain on existing resources, and resultantly, high turnover rates. These challenges often have an impact on aspects of care delivery, including resident rounding. Rounding is in fact included as a best practice for caregivers, and they are trained to purposefully round on assigned residents based on acuity to enhance resident experience and safety. Additionally, bedside shift report (BSR) is an important activity to ensure the proper information of patient and resident behavior is shared from shift to shift to reduce errors in care. AUGi helps facilitate that workflow.<\/span><\/p> For instance in the published study, the Valley Hospital implemented AUGi initially in a med-surg unit and later expanded to six other hospital units of varying medical needs and acuity. The mobile application reminds staff to check in on patients and residents if enough time has passed without a purposeful rounding event and also provides historical context to notifications and events to aid in patient and resident report handoff.<\/span><\/p> In the midst of staffing shortages and high turnover rates, staff need all possible help to continue to deliver safe and consistent care. AUGi has proven to be a powerful tool for staff. Despite the 2022 Omicron surge that caused a shortage of staff and increasing patient acuity, the Valley Hospital demonstrated that the staff maintained compliance of their safety protocols compared to baseline levels before the surge, enabling staff to do more with less.<\/span><\/p> The overall clinical workflow improved with the use of the Multi-Live View via AUGi that provided a de-identified view into all patient rooms at the central nurses station. Use of Live View in response to call bell activations and remote bed alarm checks improved patient satisfaction and staff teamwork.\u00a0<\/span><\/p> In fact, the de-identified mobile Live View not only protects resident privacy, especially when residents are sleeping or resting, but also the staff can institute remote sitter workflows to monitor high risk residents from a central location <\/span>without needing additional FTEs<\/span><\/a>.<\/span><\/p>\n
<\/span><\/p>\nWhat is AI-Driven Hybrid Sensing Technology<\/span><\/h2>
1. Improve staff visit and rounding compliance\u00a0<\/span><\/h2>
2. Enhance staff efficiency and workflow<\/span><\/h2>
3. Analytics for early intervention and data-driven decision-making<\/span><\/h2>