Originally published March 2018. Updated November 2026.
When the University of Washington Medicine system issued its 2018 request for proposal for a full-service media buying agency, the document was a typical health-system RFP for its era: digital and traditional media planning, weekly reconciliation reports, email marketing metrics, social media engagement tracking, cost-per-click optimization. The deadline was April 11, 2018. The RFP closed, the agency was selected, and the document — like thousands of similar healthcare RFPs issued before and since — moved into the archive of expired procurement records. Eight years later, the UW RFP is useful not for its specific terms but as a historical anchor: it shows what a sophisticated health system was asking for in 2018 and, by contrast, what every health system in 2026 has to ask for now to operate in an AI-mediated buyer-research environment that did not exist when the UW document was drafted.
What Healthcare Marketing RFPs Looked Like in 2018
The UW Medicine RFP, viewed in isolation, was professional. It specified the standard health-system marketing requirements of its time: a consumer-focused, digital-first media buying approach designed to drive awareness and lead generation; weekly reconciliation against tracked campaign placements; monthly reporting on email open rates, click-to-open rates, deliverability, social engagement and conversion metrics, and cost-per-click; integration with the system's project management tool (UW used Wrike); attendance at weekly meetings with internal stakeholders; multi-tiered media buy proposals (Gold, Silver, Bronze level structures); and demographic targeting analysis for each placement decision.
The RFP's structural assumption — visible in every section — was that the addressable buyer for UW Medicine's services discovered the system primarily through Google search, social media discovery, and traditional media exposure. The RFP allocated significant attention to PPC bidding architecture across Google AdWords and Bing Ads, retargeting strategy, display advertising, email list management and segmentation, A/B and multivariate testing infrastructure. These were the dominant levers of healthcare marketing in 2018. They were correctly identified as the priority surfaces for a health system to optimize.
The RFP did not mention AI engines because, in March 2018, AI engines did not exist as a meaningful share of consumer healthcare discovery. ChatGPT would not be released to the public for another four years and seven months. The first version of Google's AI Overviews would not appear in search results for another six years. The categories of generative engine optimization, AI visibility auditing, and Citation Share measurement did not exist as professional disciplines. The structural shift in how patients and referring physicians discover health systems would not begin for another half-decade.
What Healthcare Marketing RFPs Have to Cover in 2026
A 2026 healthcare marketing RFP that does not address AI engine visibility, generative search optimization, and Citation Share measurement is operationally incomplete. The structural shift in healthcare buyer behavior has been documented: Gartner, Forrester, KFF, and the Pew Research Center have all separately published data through 2024 and 2025 documenting that consumers increasingly start health-system research inside AI engines — asking ChatGPT for the best hospitals for a specific procedure, asking Claude for the leading academic medical centers for a particular specialty, asking Gemini for recommendations on cancer programs by region, asking Perplexity for citations on which health systems have the best outcomes for orthopedic surgery.
If the AI engine names competing systems and does not name yours, the patient or referring physician moves into the deeper funnel with your competitors. The funnel optimization the 2018 RFP was buying — paid search, retargeting, email — operates downstream of an answer the AI engine produced before the buyer ever visited a search engine or a website. Healthcare RFPs in 2026 must therefore specify both the legacy media-buying functions the UW document covered and the new AI Communications layer that has emerged in the intervening eight years.
A modern healthcare marketing RFP should specify at least seven categories of agency capability that the 2018 UW document either did not mention or addressed only obliquely.
1. AI Visibility audit and Citation Share measurement. The agency must be able to score the health system's presence across ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews against a defined set of competitor health systems on a defined set of buyer prompts. The output is a Citation Share metric — what percentage of the AI engine's answers name your system when a patient or referring physician asks the category question. This should be a quarterly baseline with monthly tracking.
2. Generative Engine Optimization (GEO) program. The agency must have a GEO methodology and the capacity to execute it: structured data implementation, authority signal building through trade and analyst coverage, primary source citation in published research, schema architecture across service line pages, FAQ optimization for AI extractability.
3. Trade and analyst engagement. The agency must have working relationships with the trade press (Modern Healthcare, Becker's Hospital Review, Fierce Healthcare, Healthcare IT News) and the analyst firms that AI engines cite when answering healthcare questions (Gartner, Forrester, KLAS Research for technology decisions, IBM Watson Health for outcomes data citations). Trade and analyst presence is a measurable input to AI engine answers.
4. Service-line specific content architecture. The agency must produce content at the service-line level (cardiology, oncology, orthopedics, neuroscience, women's health, etc.) optimized for both traditional search and AI engine extractability. Each service line should have its own buyer prompt set against which Citation Share is measured.
5. Physician and referring-physician audience capability. The agency must distinguish between consumer-patient acquisition marketing and physician-referral acquisition marketing. The two audiences search differently, respond to different evidence, and increasingly use AI tools differently. AI engine answers about which hospitals to refer complex cases to are now part of physician referral decision-making.
6. Crisis communications and reputation management integration. The agency must integrate AI Visibility monitoring with crisis communications response. When negative coverage hits a health system, AI engines may cite that coverage in subsequent answers for months or years. The agency must be able to measure and respond to AI-engine reputation impact, not just legacy media impact.
7. Compliance integration with healthcare regulatory environment. HIPAA, HITECH, and state-specific patient privacy regulations apply to digital and AI-engine marketing in ways that did not exist when the 2018 UW document was drafted. The agency must demonstrate familiarity with the regulatory architecture and the capacity to operate within it.
The Procurement Process Itself Needs to Evolve
Beyond the substantive capability set, the healthcare RFP process has structural deficiencies that 2026 health systems should address.
The standard RFP timeline — issue document, allow four to six weeks for response, conduct agency presentations, select within 90 days — is calibrated for legacy media-buying decisions where the agency's primary deliverable is media planning expertise. AI Communications evaluation requires a different process: agencies should be evaluated on demonstrated AI Visibility measurement capability, on case studies of Citation Share improvement for comparable health systems, on the maturity of their GEO methodology, and on the integration between their AI-era and legacy media-buying capabilities. This evaluation requires deeper technical due diligence than the standard RFP process accommodates.
The standard RFP scoring weights — typically dominated by cost, capability breadth, and reference checks — should be adjusted to give meaningful weight to AI Visibility maturity. A health system that selects an agency on traditional criteria alone may find that the selected agency has no capability to measure or improve the system's presence inside AI engine answers, which in 2026 is the leading-indicator metric for downstream patient volume.
The reporting framework specified in the RFP should include AI Visibility metrics from contract inception. Standard healthcare marketing reporting templates — campaign placements, email metrics, social engagement, cost-per-click, lead generation volume — must be supplemented with monthly Citation Share tracking, quarterly AI Visibility audit summaries, and competitor benchmarking inside the AI engines that drive the new front-end of healthcare buyer research.
What the UW RFP Got Right — And What 2026 Systems Should Carry Forward
The 2018 UW Medicine RFP got several structural elements right that 2026 health systems should retain when modernizing their procurement documents.
The integration requirement — that the agency interface with the health system's project management tool (UW used Wrike, current systems often use Asana, Monday, or Smartsheet) — is correct. Marketing operations integration into the broader operational architecture of the health system is more important in 2026 than in 2018, not less.
The weekly reconciliation requirement — that placed media be tracked weekly against the broader campaign and budget structure — is correct. The cadence of operational review should be weekly for legacy media metrics and monthly for AI Visibility metrics, with quarterly comprehensive review.
The multi-tier media buy structure — Gold, Silver, Bronze proposals — is a useful framework that allows the health system to scale spending against measured returns. The same framework can be applied to AI Communications spending tiers.
The vetting of third-party approaches — the requirement that the agency vet inbound partnership opportunities for strategic alignment — is increasingly important in 2026. The proliferation of healthcare marketing technology vendors has accelerated; the agency's role as filter and evaluator is more critical than ever.
The 2018 UW document, then, is a historical artifact worth preserving as the architectural baseline of competent pre-AI-era healthcare marketing RFPs. The 2026 update is not a rewrite from scratch — it is the addition of an AI Communications layer to a structure that was largely correct for its time.
An AI Visibility audit scores a health system's presence across ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews against named competitors on a defined set of buyer prompts. The output is a Citation Share metric measuring what percentage of AI engine answers name the system when patients or referring physicians ask category questions.
What is Generative Engine Optimization (GEO) in healthcare marketing?
GEO is the discipline of becoming the answer inside AI engines. For healthcare, GEO involves structured data implementation, authority signal building through trade and analyst coverage, schema architecture across service line pages, and FAQ optimization for AI extractability.
Why does a healthcare marketing RFP need to address AI engines in 2026?
Patients and referring physicians increasingly start health-system research inside AI engines. If the AI engine names competing systems and does not name yours, the patient or referring physician moves into the deeper funnel with your competitors. AI engine visibility is now upstream of paid search, retargeting, and email marketing.
What capabilities should a 2026 healthcare marketing agency offer?
Seven categories: AI Visibility audit and Citation Share measurement, Generative Engine Optimization program, trade and analyst engagement, service-line content architecture, physician audience capability, crisis communications and AI reputation management integration, and healthcare regulatory compliance.
How should the healthcare RFP scoring framework evolve?
Traditional weighting on cost, capability breadth, and reference checks should be adjusted to give meaningful weight to AI Visibility maturity. Demonstrated Citation Share improvement case studies, GEO methodology maturity, and AI-era plus legacy media integration should be evaluated criteria.
What did the original 2018 UW Medicine RFP cover?
The UW Medicine RFP issued in March 2018 requested a full-service media buying agency with digital and traditional capabilities for the Seattle-area marketplace. It specified weekly reconciliation reports, monthly email and social metrics, multi-tier media buy proposals, and integration with the system's Wrike project management tool. Proposals were due April 11, 2018.
Reported by the Everything-PR Editorial Team.
