AI and Innovation in Home-Based Care: The Goal Isn't Less Human Care - It's More Time for Itby Jamie Daugherty, Executive Director Artificial intelligence is no longer something healthcare leaders can put in the “someday” category. AI is already appearing in documentation tools, scheduling systems, revenue cycle platforms, clinical decision support, remote monitoring, compliance programs, and everyday administrative work. At the federal level, the U.S. Department of Health and Human Services has made AI adoption and innovation a strategic priority, including using technology to reduce administrative burden and modernize healthcare delivery. For home health, hospice, and home care providers, that creates both an opportunity and an important responsibility. The question is no longer whether AI will affect home-based care. The better question is: How do we use it well? Home-Based Care Has a Capacity Problem Much of the conversation about AI focuses on futuristic technology. But some of its most valuable applications in home-based care may be much less dramatic. Our workforce spends an enormous amount of time on tasks that do not involve directly caring for patients. Clinicians document visits. Managers review charts. Intake teams process referrals. Schedulers try to match patients, geography, availability, and clinical needs. Billing teams investigate denials. Quality teams review records. Leaders analyze reports, draft policies, prepare education, and respond to an ever-growing list of regulatory requirements. Meanwhile, agencies continue to face workforce shortages and increasing administrative demands. That makes AI particularly interesting for our sector. If technology can give clinicians and staff time back, that time can be redirected toward patients. Where AI May Help Today AI does not have to make clinical decisions to be valuable. For many organizations, the best starting point may be using technology to support the administrative and operational work surrounding care. Examples include:
CMS itself has explored AI's ability to predict outcomes including unplanned hospital and skilled nursing facility admissions and adverse events among Medicare beneficiaries. These tools should support professional judgment—not replace it. AI Could Be Especially Important for Rural Oregon The potential benefits deserve particular attention in rural communities. A rural agency may not have separate departments for compliance, quality, education, informatics, scheduling, human resources, and revenue cycle management. Sometimes several of those responsibilities belong to the same person. Technology that saves a large organization ten hours of administrative work may be helpful. Technology that saves a small rural provider ten hours may help preserve access to care. AI also has the potential to improve scheduling and routing across large geographic territories, support staff who do not have immediate access to specialized resources, and help organizations use limited workforce capacity more effectively. That does not mean technology solves Oregon's rural healthcare workforce challenges. But it may become one part of the solution. The Federal Government Is Paying Attention This is not simply an industry trend. HHS released an Artificial Intelligence Strategy in December 2025 outlining five areas of focus, including governance and risk management, workforce development and burden reduction, and modernization of care and public health delivery. HHS has also sought stakeholder input on how federal policy, reimbursement, regulation, and research could accelerate responsible AI adoption in clinical care. CMS describes technology-enabled care as having the potential to improve outcomes, quality, accessibility, and efficiency. In other words, providers should expect AI and technology policy to become increasingly connected to broader conversations about healthcare delivery and payment. Innovation Also Creates Risk Enthusiasm for AI should not eliminate healthy skepticism. Healthcare organizations work with extraordinarily sensitive information. AI tools can produce incorrect information. Algorithms may contain bias. Staff may assume an AI-generated answer is accurate when it is not. And consumer AI products are not automatically appropriate environments for protected health information. Organizations considering AI should therefore ask basic questions before adopting a tool: What information is being entered into the system? Where does that information go? Is protected health information involved? Who can access the data? How is the vendor using or retaining it? Who verifies the AI's output? Could the tool influence a clinical, employment, coverage, or other consequential decision? And perhaps most importantly: Is a human still accountable for the final decision? “AI generated it” cannot become an excuse for inaccurate documentation, inappropriate care decisions, privacy violations, or compliance failures. Start With the Problem, Not the Technology Organizations do not need an “AI strategy” simply because AI is popular. Start with a problem. Ask your team: What repetitive work consumes time without adding much value? Maybe nurses are spending too much time documenting after hours. Maybe referral information must be manually entered into multiple systems. Maybe schedulers spend hours trying to optimize routes. Maybe managers review hundreds of pages looking for missing documentation. Maybe your billing team repeatedly encounters the same preventable denials. Identify the problem first. Then determine whether technology can help solve it. That approach is much more likely to produce meaningful innovation than purchasing the newest AI product because everyone is talking about it. A Good AI Policy May Soon Be as Important as the AI Tool Organizations experimenting with generative AI should consider developing clear internal expectations now rather than waiting for a problem. At minimum, leaders should determine:
Governance does not have to prevent innovation. Good governance makes responsible innovation possible. Innovation Should Give Us More Time to Care There is understandable concern that artificial intelligence will make healthcare less personal. For home-based care, we should pursue exactly the opposite outcome. A nurse sitting at a kitchen table with a patient should be focused on that patient—not thinking about the documentation waiting later that evening. A hospice clinician should have time to sit with a family. A scheduler should have better tools for getting a clinician to a patient living 60 miles away. A small rural agency should not need an enormous administrative department simply to keep up with the complexity of modern healthcare. If AI can reduce unnecessary administrative work, identify problems sooner, make information easier to understand, and help our workforce spend more time doing the work only humans can do, then innovation has served its purpose. The future of home-based care should not be technology instead of people. It should be technology that helps people provide better care. For Oregon's home health, hospice, and home care community, that is the AI conversation worth having. |