Clinical decision-making has always been at the heart of home-based care. Every visit requires clinicians to interpret small changes, dissect complex information and make timely decisions that directly affect patient outcomes. Today’s clinicians are being asked to make critical decisions all while managing heavier caseloads, navigating growing documentation demands and evolving regulatory requirements.
In a recent Axxess and SimiTree white paper, Augmenting Human-Centered Care Through Artificial Intelligence, authors Christina Andrews, Associate Vice President of Professional Services at Axxess, and Mike Brents, former Managing Director of Technology Consulting at SimiTree, highlight how artificial intelligence (AI) strengthens clinical judgment and empowers clinicians. They note that when designed and implemented thoughtfully, AI becomes a partner in care, enhancing accuracy, reducing cognitive load and improving patient outcomes. To explore how organizations are adopting and using AI, you can review our AI webinar series here.
AI and Clinical Judgment
Andrews and Brents outline throughout the white paper that AI should amplify, not override, clinical expertise. The authors emphasize that AI’s role should be to support clinicians in making more informed decisions, especially in environments where time and information are limited.
“I think of artificial intelligence as that little clinician who is running behind the scenes, really helping individuals to work at the top of his or her skill set or license,” Andrews said.
The white paper highlights several ways in which AI supports clinical decision-making:
Diagnostic Assistance: AI-powered tools can evaluate patient symptoms, history and data to suggest possible conditions or risks, helping clinicians determine the most appropriate diagnostic pathways.
Predictive Analytics for Early Intervention: AI can analyze patterns in vital signs, documentation and historical data to identify early signs of deterioration. These insights help clinicians intervene sooner, reducing hospitalizations and improving patient outcomes.
Natural Language Processing (NLP): NLP tools, like voice assistants, extract key insights from unstructured notes, messages and assessments. This helps clinicians quickly identify trends or concerns that might otherwise be buried in documentation.
AI-Driven Triage: In the ability to analyze patient data, AI can help determine whether a patient is appropriate for home-based care, needs a higher level of support or requires immediate intervention.
Personalized Care Recommendations: AI can tailor care plans to each patient’s health history, medications and daily routines, giving clinicians clearer insights and stronger support when making care decisions at home.
“AI really builds upon the competence clinicians had coming into the field,” Andrews said. “It’s that constant reinforcement that you’re doing exactly what’s needed or that you need to consider doing this instead.”
Reducing the Cognitive and Documentation Load on Clinicians
Clinical decision-making is impacted when clinicians are overwhelmed. The white paper explores that AI should reduce the cognitive burden that leads to errors and inefficiencies. The authors note that AI provides a second set of eyes that reduces that burden and enables clinicians to make more informed decisions. This is especially important in home-based care, where clinicians are working independently and must rely on their own judgment in real time.
“AI is a tool that provides the clinician with the right information at the right time,” Andrews said. “It’s real-time risk stratification and identification, giving them competent and compliant care planning techniques.”
Aside from cognitive burden and burnout, AI-powered tools also help clinicians save time on documentation, one of the most time-consuming tasks in care at home. Andrews and Brents highlight that the right AI tool can capture documentation without interrupting the patient-clinician connection, enabling clinicians to speak naturally and thoughtfully during visits while the tool handles transcription and compliance checks. This not only improves accuracy in documentation but also helps organizations maintain audit-ready records with less effort.
“It [AI] also helps with documentation,” Andrews said. “It helps clinicians compliantly document the care they delivered based upon what was ordered. It also helps them free up more time.”
The Future of Care
The authors conclude the white paper by positioning AI as a catalyst for more efficient, effective and human‑centered care. Andrews emphasizes that early AI adopters will gain a significant advantage, noting that providers who embrace new technologies will be better equipped to differentiate their organizations and stay ahead of the curve, while those who don’t risk falling behind.
“AI has to be a foundation in all elements of your business,” Andrews said. “That’s going to enable you to keep a seat at the table, to work effectively with less risk.”
To read the white paper, click here.
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