Hospice Care and AI

In recent years, the healthcare industry has seen a rapid advance in the use of artificial intelligence (AI) technology. Grand View Research reports that the global healthcare AI market is expected to reach 188 billion by 2030, growing at a compounded annual growth rate of more than 35 percent between 2024 and 2030.

According to estimates, 1 out of 5 healthcare organizations have adopted AI solutions. Hospice agencies have also begun to incorporate AI into their clinical and administrative operations, hospice software integrations, and other systems to enhance the quality of care provided to patients and families. AI has the potential to revolutionize the field of hospice care by increasing efficiency, compliance, and overall patient outcomes.

Predictive analytics, robotic processing automation (RPA), and machine learning constitute integral parts of artificial intelligence.

• Predictive analytics uses data, statistical algorithms, and machine learning techniques to forecast future outcomes and trends based on historical data. This enables AI systems to make informed predictions and decisions, thereby optimizing processes and outcomes.
• Robotic Processing (RPA) automates repetitive tasks and workflows by mimicking human actions and decision-making, freeing up human resources by enhancing efficiency. “Bots” can work 24 hours 7 days a week to augment the human workforce.
• Machine learning, another subset of AI, enables systems to learn from data, identify patterns, and make decisions without explicit programming. This allows AI systems to adapt and improve over time.

Here are 5 ways that hospice agencies are using AI:

1.  Personalized Care Plans

Hospices can use AI to create personalized care plans for individual patients. By analyzing a patient’s medical history, symptoms, preferences, and other relevant data, AI algorithms can generate tailored care plans that address the specific needs and goals of the patient. This personalized approach ensures that patients receive the most appropriate and effective care, leading to improved quality of life.

AI can also help hospices continuously monitor and adjust care plans based on real-time data and feedback. By tracking changes in a patient’s condition, AI algorithms can identify potential issues or opportunities for improvement and recommend adjustments to care plans. This dynamic, adaptive approach ensures that patients receive the best possible support.

2.  Scheduling Optimization

At a time when shifting demographics are increasing demand for end-of-life care, a significant portion of the clinical workforce in the U.S. is approaching retirement age. In a tight labor market with increasing demand, hospice agencies must allocate resources effectively to deliver financially sustainable, high-quality care. AI has numerous applications when it comes to optimizing the deployment of various resources, such as staffing and equipment. AI algorithms can analyze historical data to predict patient needs and can use the information for optimal scheduling and workload distribution.

For example, hospice agencies strive to be there for their patients in the last week of life.  Machine learning (ML) algorithms have been able to identify patients likely to be in the last 7 days of life.  By scanning charts for data on signs such as lack of appetite, lethargy, etc., AI can be used to identify individual patient decline, so that hospices can ensure nurse visits and other support for families. This in turn drives patient and family satisfaction scores and other quality measures. It also maximizes reimbursement in the form of SIA payments, which provide additional revenue incentives for hospices providing nursing and social worker services to patients during the last week of life.

3.  Human Resources

Human Resources serves as another example of how AI can be leveraged by hospice agencies. In an industry facing workforce shortages and high turnover, AI can assist hospice HR teams by streamlining recruitment, enhancing employee engagement, and optimizing workforce management. AI-powered tools and platforms can help healthcare organizations attract top talent by automating the recruitment process, from screening resumes to scheduling interviews. By using AI algorithms to analyze candidate data and predict job fit, hospice HR teams can identify the most qualified candidates more efficiently, reducing time to fill and improving the quality of new hires, which ultimately mitigates costs and improves patient experience.

4.  Prior Authorizations

Burdensome prior authorization requirements consume resources, with each payer often having its own forms and requirements. Lack of prior authorization can result in substantial losses from denied claims. Robotic process automation (RPA) has been deployed by healthcare organizations to perform repetitive tasks such as prior authorization requests. In addition to improving efficiency, AI can also improve accuracy by flagging potential errors and identifying missing information in the documentation sent to insurers. In this way, AI can help hospices prevent denials, reduce rework, and expedite the approval process, ultimately minimizing overhead costs.  

5.  Reducing Hospital Admissions

AI can also help hospice providers proactively prevent hospitalizations. When patients elect the hospice benefit, they forego Medicare Part A, and hospices pick up the bill for any hospitalizations related to the terminal illness. A Clare Medical study found that hospital admissions could be avoided by implementing AI tools to identify patients most likely to experience medical events leading to hospitalization. AI algorithms can continuously analyze a wide range of patient data, including vital signs, symptoms, and medical history, to predict and prevent complications before they escalate and result in hospital admission.

AI-powered predictive analytics can also help hospice agencies identify patients who are more likely to require hospitalization based on their health status and historical data. By stratifying patients according to risk levels, hospices can prioritize and allocate resources to those in need of additional support, such as medication adjustments or additional home visits. This targeted approach using AI enables hospice teams to deliver personalized, proactive care, thereby reducing the likelihood of hospital admission and the associated costs.

The Takeaway

Projections suggest that AI could help reduce U.S.  healthcare costs by $13 billion by 2025. At a time when hospices are struggling with inflation and staffing shortages, AI solutions can better position hospice agencies for success and sustainability. The five examples above are only a few of the many innovative ways that hospices can leverage AI the gain efficiencies, reduce costs, and improve quality of care.

Author’s Note: Views, information, and guidance in this blog are intended for information only. We are not rendering legal, financial, accounting, medical, or other professional advice. Alora disclaims any liability to any third party and cannot make any guarantee related to the content.

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