# Physician relationship mapping that finds warm introductions through people you know > Find warm introductions to US physicians through the physicians you already know, with every path scored by connection strength. 30 days free. Source: https://dmand.ai/platform/relationship-mapping · Last updated: 2026-10-20 Physician Network Discovery starts from the physicians you already know, your customers, advisors and KOLs, and finds the physicians they trained, worked, published or ran trials with. When a strong path exists, ask your contact for an introduction before the first email goes out. [Start free trial](https://app.dmand.ai/signup?from=platform&src=platform%3A%2Fplatform%2Frelationship-mapping&cta=hero) [Book a demo](https://dmand.ai/book-a-demo) - 30 days free - Self-serve - No credit card Illustration: three physicians a team knows, each linked to an invented target physician leader by how they know each other. - Customers Teams selling into US healthcare use Dmand AI - Innovaccer - Marvix AI - [Circle Health G2 review](https://www.g2.com/products/dmand-ai/reviews) Circle Health · G2 review I like Dmand AI’s extremely curated and comprehensive healthcare database, which you won’t find on any other platform with this level of detail. Anupam D. Founder & CEO, StratAnalyze (for Circle Health) - Castle Connolly Private Health Partners - G5 Medical - Prente Health - Bassett - Mark Enlow Inc. - [NextDimension AI G2 review](https://www.g2.com/products/dmand-ai/reviews) NextDimension AI · G2 review It’s like having a hyper-personalized mail writer that’s unbelievably efficient. Simran K. Co-founder & CEO, NextDimension AI - [Customer stories](https://dmand.ai/customers) Paths in your network ## Physician Network Discovery shows who in your network already knows the physicians you want to reach Dmand AI checks where US physicians trained, worked, published and ran clinical trials to find the people who connect you to a target. Every connection shows how the two physicians know each other and how strong the tie is. - [7.4M+](https://dmand.ai/data/physicians-and-hcps) HCPs Training, affiliations, publications and clinical trials, matched to one record per physician. Explore HCP data - [6.2K+](https://dmand.ai/hospitals/) Hospitals Current coworkers and past colleagues at the same hospital count as a warm path. Browse hospitals - [181K+](https://dmand.ai/medical-groups/) Medical groups Members of the same medical group count as a warm path to each other. Browse medical groups How teams look for warm intros today ## Asking around, LinkedIn mutual connections and CRM relationship tools miss how physicians know each other Most teams look for a warm path to a physician in one of three ways. Here is what each one finds, next to what Dmand AI finds for the same target. _Illustration: for each common approach, what it finds next to what Dmand AI finds for the same invented target physician._ - ### Asking around the team reaches only what people remember A rep posts "Does anyone know the oncology chair at Harlow?" and the answer depends on who reads it and what they recall that day. - ### LinkedIn mutual connections show a link, not how two people know each other A shared connection could be a close colleague or someone who accepted a request years ago, and the network shows no difference. - ### CRM relationship tools see only your own team's email and calendar They map who your reps have already emailed, so they miss the physicians your advisors trained or published with. Asking around the team reaches only what people remember From people you know to an introduction ## Find warm introductions to physicians, starting from the people you already know Follow one health IT rep from adding the physicians his team knows to asking for an introduction. Each person and organization in the scenes is made up for this example. Illustration: four invented physicians a team knows, added as the starting point for network discovery. 01 ### Add the physicians you already know Theo adds Ferncliff's clinical advisors, customer physicians and a KOL the team works with, then runs Discover Network. 02 ### See the physicians they connect you to, scored by strength Dmand AI lists every physician linked to Theo's contacts with a connection strength from 0 to 100, and Theo narrows the list to Harlow Health to find the chair he wants to meet. 03 ### Read how each of your contacts knows the target Dr. Elena Voss is connected with three of the added physicians, through a shared fellowship, papers written together and a clinical trial run together, so Theo picks the strongest path. 04 ### Ask for the introduction, or start a sequence when no path is strong Theo uses the AI talking points to ask Dr. Haddad for an introduction, saves Dr. Voss as a contact, and adds the targets with weak paths to a sequence. How warm paths work ## Warm introductions to physicians come from shared hospitals, groups, training, papers and trials Relationship selling in healthcare works when the person making the introduction has real history with the physician you want to meet. - ### Six kinds of warm path to a physician Current coworkers at the same hospital, past colleagues at the same hospital, members of the same medical group, graduates of one medical school, residency or fellowship program, co-authors of a paper, and co-investigators on a clinical trial. - ### Warm path strength depends on how recent and repeated the tie is The strongest paths run through colleagues who work together today, several papers or trials together, or the same training program in nearby years. Warm paths by team ## Healthcare sales teams start warm paths from the physicians they already work with Each team turns a different group of physicians into warm leads. Health IT and services ### Reach a CMIO or department chair through a physician champion Add the physician champions at your customer hospitals and see which of them trained or worked with the leader you want to meet. [Dmand AI for Health IT](https://dmand.ai/solutions/health-it) Test it on your network ## Test Physician Network Discovery on physicians whose careers you know Add a few physicians you know well and check whether the paths match what you already know about them. 1. ### Start a free trial No credit card and no sales call. 2. ### Add physicians you know Customers, advisors or KOLs work best. 3. ### Run Discover Network See who they connect you to. 4. ### Check paths you can confirm Look for colleagues and co-authors you already know about. [Start free trial](https://app.dmand.ai/signup?from=platform&src=platform%3A%2Fplatform%2Frelationship-mapping&cta=try_it) 30 days free · Self-serve Illustration: a checklist for one physician a team knows, with coworkers, classmates and co-authors checked, and trial co-investigators still to check. Before and after the introduction ## Dmand AI capabilities to use before and after a warm introduction - [Healthcare Universe](https://dmand.ai/platform/healthcare-universe) Read a physician's procedures, trials, papers and every site they work at before you ask for the introduction. - [Org Hierarchy Explorer](https://dmand.ai/platform/hospital-org-chart) See where your target sits in their health system and who else signs off on the deal. - [Zeus AI SDR](https://dmand.ai/platform/ai-sdr) Write a personal email for each target with no warm path, ready for your rep to review. - [Sales Engagement Suite](https://dmand.ai/platform/sales-engagement) Run email, call and LinkedIn task steps for every target without a warm path. Warm introduction questions ## Physician relationship mapping and warm introduction FAQs What sales and partnership leaders ask before they ask for an introduction. Not here? Email [hello@dmand.ai](mailto:hello@dmand.ai). **What is relationship mapping in healthcare sales?** Relationship mapping is a picture of who knows whom around the people you want to reach: colleagues, classmates, co-authors and past coworkers. In healthcare sales it shows which of your customers, advisors or KOLs can introduce you to a physician or physician leader. Dmand AI builds that map from where physicians trained, worked, published and ran clinical trials. **How do I get a warm introduction to a physician?** Find someone the physician already knows well, such as a colleague, a classmate from residency or a co-author, and ask that person for a short introduction that says why the meeting is worth their time. In Dmand AI, add the physicians you know, run Discover Network and pick the contact with the strongest path. Ask for introductions; never pay for them. **What connections does Physician Network Discovery find?** It finds six kinds of path: current coworkers at the same hospital, past colleagues at the same hospital, members of the same medical group, shared training at a medical school, residency or fellowship, co-authors of published papers, and co-investigators on clinical trials. Each connection shows which of these paths links the two physicians. **How is connection strength scored?** Every physician found gets a connection strength from 0 to 100 with a label such as Very strong. The score is higher when the tie is recent, repeated or shared with more of the physicians you added, for example a current coworker or a co-author on several papers. **Can I start from a physician I want to meet instead of the people I know?** Yes. Open the physician's profile in Dmand AI and go to the Warm Path tab to see the paths that lead to them. Discover Network works the other way, starting from the physicians you know. **Which physicians should I add as my network?** Add the physicians who already like working with you: physician champions at customer sites, clinical advisors, KOLs and investigators you work with, and physicians on your own team. The more of them you add, the more paths Dmand AI can find. **How is this different from LinkedIn mutual connections or a relationship intelligence platform?** LinkedIn shows that two people are connected, not how they know each other. Most relationship intelligence platforms read your team's own email and calendar. Physician Network Discovery uses healthcare records of training, affiliations, publications and clinical trials, so it finds paths through physicians your team has never emailed. **Can I find warm paths to hospital executives?** Yes, when the executive is a physician with an NPI, such as a chief medical officer, CMIO or department chair. For non-clinical executives, use Org Hierarchy Explorer to see who works with them at each hospital and site. **Where does Dmand AI's network data come from?** Hospital and medical group affiliations come from the CMS provider registry and CMS enrollment records, training from medical school, residency and fellowship records, co-authorship from PubMed and trial co-investigators from ClinicalTrials.gov. Dmand AI matches them to one record per physician. **What if there is no warm path to my target?** Reach the physician directly. Add them to a sequence with email steps, calls and LinkedIn tasks, or let Zeus AI write a personal first email for your rep to review. Run Discover Network again as you add customers and advisors. **Is Physician Network Discovery part of the free trial?** Yes. The trial is 30 days free, self-serve and needs no credit card, and it previews the full dataset with trial credits. Plans and credits after the trial are on the pricing page. Physician Network Discovery Find out who already knows the physicians on your target list Add the physicians you know, run Discover Network and ask for your first warm introduction. [Start free trial](https://app.dmand.ai/signup?from=platform&src=platform%3A%2Fplatform%2Frelationship-mapping&cta=cta) [Book a demo](https://dmand.ai/book-a-demo) - 30 days free - Self-serve - No credit card