Fewer new patients call your hematology/oncology practice after searching online because AI search tools like ChatGPT, Gemini, Perplexity, and Google AI Overviews now answer many of their questions directly in the search results. The patient gets a summary of symptoms, treatment options, or what a specialist does without clicking through to any practice website. If your practice isn't the source cited in that summary, you never enter the patient's decision process at all.
What zero-click means for a practice that depends on referrals and trust
A zero-click search is a search that ends without the user visiting any website; the person types a question, reads the answer on the results page itself, and moves on. For oncology practices, this matters because patients researching a new diagnosis, a second opinion, or treatment side effects used to land on practice websites to find that information. Now, an AI-generated summary often satisfies that need before a single click happens.
This shift hits specialty medical practices harder than most local businesses because the questions are research-heavy. Someone searching "what does a hematologist do for anemia" or "treatment options for stage 2 lymphoma" is looking for substantive information, not just a phone number. That is exactly the kind of query AI search tools are built to answer in-line, pulling from whatever sources they judge most authoritative and clear.
How answer engines summarize cancer care questions before a patient reaches you
Answer engines like AI Overviews and Perplexity build their responses by pulling and condensing content from multiple websites, then presenting one synthesized answer instead of a list of links. For a query about blood disorders or cancer treatment, the engine looks for pages that clearly explain the condition, the specialist's role, and what to expect, then cites or paraphrases the clearest source it finds. Practices whose websites answer these questions in plain language get pulled into that summary; practices that only list credentials do not.
This is a form of generative engine optimization (GEO), the practice of structuring content so AI tools can extract and cite it accurately, alongside the older discipline of answer engine optimization (AEO), which focuses on directly answering the specific questions patients type or speak. A hematology/oncology practice that has never organized its site around patient questions is invisible to this process even if its medical care is excellent.
What this shift changes about first contact with your oncology practice
The first contact a new patient has with your practice used to be a phone call or a website visit. Now, for many patients, the first contact is an AI-generated answer that already tells them what a hematologist or oncologist does, what a treatment involves, or what questions to ask at a first visit. By the time they do call, they've already formed an impression of the field and possibly of specific practices, based on whichever sources the AI tool trusted enough to summarize.
This changes what the phone call itself sounds like. Patients arrive further along in their research, sometimes with more confidence and sometimes with confusion from an oversimplified summary. It also means the practices that get chosen are increasingly the ones the AI tools already treated as credible sources, not necessarily the ones the patient would have found first through a traditional list of search results and reviews.
What to check first if new patient calls are dropping
If new patient call volume is down, the first thing to check is whether your practice's website and listings actually answer the specific questions patients are typing before they ever reach the phone. Look at your site's service pages and FAQ sections and ask honestly whether they explain conditions and treatments in plain language, or whether they only describe your practice in general marketing terms. AI search tools favor clear, direct answers over promotional copy.
Next, check whether your practice information is consistent and detailed across Google Business Profile, your website, and any directories, since inconsistent or thin listings give answer engines less to work with. Also check patient reviews for language that answers real questions, such as descriptions of wait times, bedside manner, or what a first appointment involved; AI tools increasingly draw on this kind of first-person detail when summarizing what a practice is like. A practice with strong care but a thin digital footprint will keep losing calls to competitors who simply describe themselves more clearly online.
Your existing website content is likely doing more of this work than you realize, or far less, and the easiest way to tell is to look at three things you probably already have.
Patient reviews are usually the strongest asset, because they contain specific, first-person language about symptoms, diagnoses, and what care actually felt like, exactly the kind of detail AI tools pull into summaries about what a practice is like. Read your most detailed reviews and notice whether they mention specific conditions or treatments; if they do, that content is already helping AI search describe your practice accurately.
FAQ sections and service pages are the second asset worth checking. Open your website and read your service descriptions as if you were the patient, not the practice. If a page reads like a credentials list rather than an answer to "what happens when I see a hematologist for low iron," it is contributing very little to how AI tools summarize your care. Rewriting even a handful of these pages around the plain-language questions patients actually ask is the fastest way to close the gap between the care you provide and what AI search tells patients about it.
Photos matter less for the informational questions AI tools answer, but they still support the decision after a patient has already found you, so they are worth keeping current without being the first place to focus attention. Start with reviews and service-page language, since those two assets carry the most weight in how AI search engines describe hematology and oncology practices to the patients searching for them right now.