Negative Keywords for Health Campaigns: A Starter List

The fastest negative keyword list for a health campaign blocks six categories of searcher who will never book: job seekers, people looking for free or charity care, do-it-yourself and home-remedy researchers, students and academic researchers, litigation traffic, and people searching for a different service line than the one you sell. Add those before you add anything clever. Curve is the HIPAA-compliant tracking layer healthcare advertisers use to see which search terms actually produce booked patients, with per-destination field mapping and a signed BAA on every plan.

Why negative keywords do more work in healthcare than anywhere else

Health searches are unusually ambiguous. The same three words can come from a prospective patient, a nursing student, a plaintiff's attorney, and someone looking for a job at your clinic. Google cannot tell them apart from the query alone, and neither can you. What you can do is subtract the populations structurally incapable of converting.

Two things make this more urgent for clinics than for a general ecommerce advertiser.

First, healthcare cost per click is high and patient volumes are low. A dental implant or behavioral health click can cost more than most retailers pay for a sale. When the click is expensive, wasted clicks are not a rounding error, they are the difference between a campaign that funds itself and one that does not.

Second, low-volume accounts starve their bid strategies. Clicks from people researching a condition for a term paper do not just cost money, they also fail to produce the conversion signal that automated bidding needs to work at all.

There is a third reason, rarely stated. Your search terms report is a list of the exact health-related phrases real people typed before arriving at your site. That is a sensitive dataset. It is fine inside Google Ads, but once those terms start driving audience lists, exports, and CRM fields, you have created a health-adjacent record in systems never designed to hold one.

The starter list

Apply these as campaign-level or account-level negatives. Use phrase match unless noted, because phrase negatives catch the long tail without needing every variant enumerated.

Employment and careers

The single largest source of waste in clinic accounts, and almost always present before anyone looks. People searching for work use the same clinical vocabulary you do.

• job, jobs, hiring, careers, employment, vacancy, salary, wage
• resume, cv, apply, application, internship, intern, externship
• certification, certified, license, licensure, credential
• training, course, class, school, degree, program
• assistant, technician, hygienist, locum, per diem, travel nurse

The clinical job titles matter. A dental practice bidding on implant terms collects searches for dental assistant jobs unless it blocks them.

Free, cheap, and charity care

Not every clinic should block these. A community health center or a practice that accepts sliding-scale patients may want exactly this traffic. A private-pay aesthetics or fertility practice should block it on day one.

• free, no cost, no charge, donated, charity, charitable
• cheap, cheapest, low cost, discount, coupon, groupon, deal
• grant, financial assistance, financial aid, hardship
• county clinic, community clinic

Be careful with "affordable" and "cost." Cost queries often come from real prospective patients doing price research, and blocking them wholesale removes strong intent. Price shopping converts poorly for some practices and beautifully for others.

Do it yourself, home remedies, and self-treatment

• diy, at home, home remedy, natural remedy, natural cure
• how to fix, self treat, self treatment, without a doctor
• hack, trick, tips, essential oil, supplement

Education, research, and definitions

Informational intent. These searchers want to understand something, not buy anything. Some of them are future patients, which is an argument for a content strategy, not for a search ad.

• what is, meaning, definition, define, causes, symptoms of, stages of
• icd, icd 10, cpt code, coding, billing code
• study, research, journal, pubmed, article, statistics
• quizlet, textbook, pdf, powerpoint, essay, exam, nclex
• wikipedia, reddit, forum, quora, youtube, video, images, pictures

The "pictures" and "images" negatives are more valuable than they look. Image-seeking searches on cosmetic, dermatology, and dental terms are heavy, cheap-looking, and essentially never book.

Legal and litigation

Litigation traffic is expensive, does not convert, and puts your ad next to a query you would rather not be associated with.

• lawsuit, sue, suing, attorney, lawyer, legal
• malpractice, negligence, settlement, claim, compensation
• class action, litigation, court, sued, complaint
• board complaint, license complaint

Note that "complaints" and "reviews" overlap. Reputational searches such as "clinic name complaints" are worth keeping on brand campaigns, where you want to own the result. Block them on generic campaigns only.

Insurance, coverage, and government programs

Whether these belong on your list depends entirely on your payer mix. A cash-pay practice should block them. A practice that takes Medicaid should not.

• medicaid, medicare, chip, va, tricare, indian health
• does insurance cover, insurance cover, in network, out of network
• copay, deductible, prior authorization, eob

Wrong service line and wrong species

Every specialty collects adjacent-but-wrong traffic. Write these by hand, because the list is unique to you. Universal candidates:

• Veterinary terms: dog, cat, puppy, pet, animal, veterinary, vet
• Pediatric terms if you only see adults, and adult terms if you are pediatric-only
• Emergency terms if you are not urgent care: emergency room, er near me, urgent, 911, walk in
• Adjacent specialties you do not treat, named explicitly
• Product and retail terms if you provide a service: buy, order, amazon, ebay, walmart, cvs, walgreens, for sale, kit, online purchase

Prescription and regulated-product traps

Weight management, hormone, and telehealth advertisers collect a specific unqualified query: people looking for a drug rather than a clinician. Those clicks are expensive, and they drag your campaign toward ad copy that creates policy problems.

• Branded drug names you do not want to bid on, plus common misspellings
• without prescription, no prescription, buy online, overseas, canada pharmacy
• gray market, generic version, compounded alternative if you do not sell one
• side effects, interactions, dosage, dose, mg

The regulatory backdrop is real. The FDA sent 30 warning letters to telehealth companies over compounded GLP-1 claims on 3 March 2026 and 25 more the week of 15 June 2026. Keeping drug-shopping queries out of search is partly a performance decision and partly a decision about what your ads end up saying. Our guide to compounding pharmacy GLP-1 advertising restrictions covers the copy side in detail.

Adult, unrelated, and celebrity noise

Aesthetics, urology, women's health, and behavioral health accounts collect adult-intent traffic on ordinary anatomical terms. Add the obvious blockers plus celebrity names that trend alongside your treatments, a recurring problem for weight-loss and cosmetic advertisers.

Match types, and the mistake almost everyone makes

Negative keywords do not behave like positive keywords, and the differences cause silent failures.

Negative keywords do not match close variants. A negative for "job" will not block "jobs" in exact match, and misspellings are never caught automatically. Positive keywords match plurals, misspellings, and related forms. Negatives match literally. This is why phrase-match negatives are usually the right default, and why you should add plurals and the two or three misspellings you actually see in your reports.

Negative broad match requires every word to appear. A negative broad keyword of "free consultation" blocks queries containing both words in any order, but not "free consult." Negative phrase requires the words in order. Negative exact blocks only that exact query.

Order of operations matters. Account-level lists apply everywhere, campaign-level negatives apply to that campaign, and ad group negatives apply within it. Build shared lists at account level for the universal categories above, and reserve campaign-level negatives for service-line separation.

Do not over-block your own service. The most common self-inflicted wound is adding a broad negative that also removes converting traffic. Blocking "cost" removes price-shopping patients. Blocking "near me" removes local intent. Blocking a condition term because it appeared in one bad query removes the whole category. Check impression volume before adding anything broad.

Building your own list from the search terms report

The starter list gets you to a baseline in an hour. Everything after that comes from your own data.

1. Open the search terms report for the last 90 days, sorted by cost descending.
2. Filter to terms with clicks and zero conversions. This is where the money is.
3. Read them. Do not skim. Patterns show up in the actual language, not in aggregates.
4. Group what you find into the categories above, and add the category rather than the single term wherever you can.
5. Repeat weekly for the first month, then monthly. New query patterns appear constantly, especially as AI-assisted search changes how people phrase things.

One caution specific to healthcare. Search terms are health-adjacent data about identifiable intent, and the exports have a way of ending up in shared drives and analytics tools. Keep them in the ad platform, review them there, and resist the urge to build spreadsheets that pair query text with lead records. If you need to know which campaigns produce patients, get that from your attribution layer using neutral event names, not by joining query strings to people.

What negative keywords cannot fix

Be blunt about the limits, because negative keyword work sometimes gets treated as a compliance measure. It is not one.

Negative keywords control which queries trigger your ad. They do nothing about what your website sends to ad platforms after the click. If your landing page runs a Meta Pixel or a standard Google tag, that tag reports the page URL, referrer, and a persistent identifier to a company that does not sign a BAA for its advertising products. On a clinic site the URL frequently names the condition. That is the mechanism behind healthcare pixel litigation that has cumulatively crossed $100M in settlements.

A perfectly curated negative list on a site with a client-side pixel is a well-optimized compliance problem. The two issues are independent, and both need solving. Our explainer on why client-side pixels create HIPAA exposure walks through the specifics.

How Curve makes negative keyword work possible without leaking PHI

Negative keyword work depends on knowing which clicks became patients. That is a tracking problem, and in healthcare tracking usually breaks first, because the compliant answer to the pixel problem is often to turn tracking off and fly blind.

Curve is HIPAA-compliant ad tracking, attribution, and analytics built for healthcare. The tracking script installs in place of the Meta Pixel or Google tag. Events go to Curve's US-hosted infrastructure rather than straight to the ad platforms, and Curve decides what leaves.

• Per-destination field mapping. Only fields you explicitly map forward to a given platform. The default is that nothing goes, so page URLs, referrers, and form contents stay behind unless you deliberately send them.
• Identifier hashing. Email, phone, and name are SHA-256 hashed to each platform's conversion API requirements before forwarding.
• Neutral event aliases. Google Ads sees a neutral event name rather than one that identifies the service line, so your conversion labels do not describe what the patient came in for.
• Click ID capture and bridge tokens. The gclid is captured at landing and preserved, including across a jump to a separate booking or intake tool such as IntakeQ, Calendly, or Jane App, where attribution normally breaks.
• Offline conversion uploads. Appointments that are booked or attended weeks later can be uploaded in bulk from your CRM or EHR and matched back by click ID, so the conversion that finally reaches Google is the one you care about.
• PHI-pattern detection. Payloads are monitored for PHI-shaped values such as SSNs, MRN-style identifiers, and long numeric sequences, and flagged for review. This is a monitoring layer, not redaction. The protection comes from field mapping plus hashing.

The effect on negative keyword work is that your conversion column becomes trustworthy. You can look at a search term with 40 clicks and know whether any became a booked appointment, rather than guessing from form fills. Curve includes a signed BAA on every plan. See our walkthrough of server-side Enhanced Conversions without PHI leakage and the broader HIPAA-compliant conversion tracking setup.

Frequently asked questions

How many negative keywords should a clinic account have?

There is no target number, and treating it as a scoreboard produces bloated lists nobody maintains. A typical single-location practice runs a shared account-level list covering the categories above, plus a smaller campaign-level list per service line. Quality of grouping matters far more than count.

Should negative keywords be phrase or exact match?

Phrase for categories, exact for individual queries you want to remove without collateral damage. Phrase negatives catch the long tail, which is where most waste lives, but they can over-block if the phrase appears inside converting queries. Check before adding.

Do negative keywords work the same in Performance Max?

Not identically. Performance Max supports account-level negative keyword lists and campaign-level negatives, but gives less visibility into the search terms driving spend. Build the account-level list first if Performance Max is a meaningful share of budget.

Can negative keywords help with HIPAA compliance?

Only indirectly. They reduce the volume of health-related query data flowing into your account and keep your ads away from queries you do not want to be matched with. They do not affect what your website transmits to ad platforms, which is where the actual HIPAA exposure sits. Solve both separately.

How often should the list be reviewed?

Weekly for the first month of a new campaign, then monthly once the account is stable. Review more often after a service line launch or any period when a treatment you offer is in the news, because news cycles generate informational traffic on clinical terms.

Will blocking too much hurt automated bidding?

Over-blocking reduces the data the bid strategy learns from, which matters most in low-volume accounts. The fix is not to block less, it is to block precisely. Removing traffic that never converts helps a smart bidding strategy. Removing traffic that sometimes converts hurts it.

Do I need different lists for Google and Microsoft Ads?

Start with the same core list on both, then diverge based on each platform's own search terms report. Wasted-query patterns are not identical. Importing a Google campaign carries keywords across, but verify the shared negative lists came with it.

Where to start

Build the account-level shared list from the employment, DIY, education, legal, and retail categories first. Those are close to universally safe and usually account for the largest share of obviously wasted spend. Then read your own 90-day search terms report and add what is specific to your specialty.

After that, make sure the conversion data you are optimizing against is real. Run the free compliance scanner to see what tracking your site is currently loading and what it is sending to ad platforms. If you want conversion tracking that survives a compliance review and still tells you which search terms produce patients, visit curvecompliance.com and we will map your events with you.

Reviewed August 2026. Ad platform match-type behavior and Performance Max exclusion controls change regularly. Verify negative keyword behavior against current Google Ads and Microsoft Advertising documentation before large-scale changes.