Artificial Intelligence (AI) and ChatGPT have become well-known household terms, being utilized for various tasks ranging from resume updates to speech writing.
While AI’s applications in healthcare depend on an organization’s appetite for innovation, and the investments and approach from technology providers, we have barely scratched the surface in leveraging machine learning (ML) and AI in the healthcare space, particularly within the senior living and long-term care industries.
With the challenges faced by LTC facilities such as staffing shortages, increasing care needs and a shift to value-based care, it is essential for providers to explore innovative solutions for providing high-quality care.
One proven avenue is leveraging artificial intelligence and the integration of remote monitoring technologies in skilled nursing facilities, as recognized by a survey conducted by the National Institutes of Health, where 79% of respondents believe AI and machine learning could enhance patient outcomes.
Monitoring changes in acuity and predicting risk of fall using AI
Falls present a significant concern among older adults, leading to a death every 20 minutes and an emergency department treatment every 13 seconds, according to the National Council on Aging.
The financial implications are staggering, with data showing that across assisted living communities and skilled nursing facilities, the annual direct cost of all falls is as high as $380,000 and could be even higher at enterprise communities, with an average $712,000 per facility. These statistics emphasize the urgent need for intervention in skilled nursing.
While several technologies exist to help identify a fall and speed-up response after a fall has occurred, providers should look for a solution that monitors change in acuity in near real-time and identifies residents that have a higher risk of falling, thereby allowing staff to take targeted and resident-specific preventive measures.
The AI/ML based remote monitoring and fall detection solutions have proven to improve clinical outcomes for residents in long-term care facilities. The near real-time and ongoing analysis of over 150 data points from the EHR allows us to continuously monitor a change in resident acuity and accurately assess their risk of a fall.
When implementing AI-driven technologies, MatrixCare has observed an 8% reduction in falls among an initial cohort of 200+ LTC communities, resulting in an estimated $12.9 million in savings across the cohort, or about $96,000 per operator, from costs associated with treating major falls.
Leveraging AI to improve care delivery and resident well-being
Another critical aspect of care includes monitoring mood changes and helping efforts to prevent the onset of depression. By analyzing associated data points and utilizing AI-based models for indicators in mood changes, we can minimize reliance on antipsychotic medications and cater to resident’s mental health needs in a proactive and controlled manner. This approach can help reduce rehospitalizations and penalties while alleviating staff burden. Integration of advanced technologies in long-term care facilities enhances resident well-being, resulting in improved outcomes.
One notable highlight is the substantial improvement in therapy outcomes and adherence to Centers for Medicare & Medicaid Services’ recommendations. Our analysis of the clinical data showed a 20% reduction in the administration of antipsychotic medication to residents, along with a 7% decrease in the usage of antianxiety or hypnotic medications, when MatrixCare’s AI model was used to monitor changes in resident acuity.
By embracing advanced technologies powered by AI/ML models that leverage EHR data, skilled nursing facilities can enhance therapy outcomes and help reduce reliance on medications, thus improving the quality of care and driving positive clinical outcomes for residents.
Embracing the future of long-term care
Artificial intelligence is evolving at an unprecedented rate and new applications are being developed every day. Long-term care providers must embrace this evolution and invest in technology that fosters secure, healthy and dignified living environments for our senior population.
By integrating AI and remote monitoring technologies into their facilities, they can unlock new opportunities to improve the well-being of residents and enhance the efficiency of healthcare providers. These innovations enhance resident health tracking, mitigate safety hazards, and hold the key to alleviating the challenges faced by today’s care professionals.
Bharat Monteiro is the General Manager, Senior Living & Long-Term Care for MatrixCare.
The opinions expressed in McKnight’s Long-Term Care News guest submissions are the author’s and are not necessarily those of McKnight’s Long-Term Care News or its editors.
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