MedlinePlus gives away its consumer health data in pieces: a daily XML file, a search API capped at 85 calls a minute, a code lookup capped at 100. We put the pieces together.
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Scoping starts with layers: daily topic snapshots with a change file, code crosswalks for your code sets, genetics records with every page section, test pages, recipes with nutrition panels, or all of them joined on MeSH, ICD-10-CM, SNOMED CT, RxCUI and LOINC. We extract MedlinePlus data from every public page, each section on its own schedule. You receive CSV, JSON, Parquet, XML or a hosted endpoint, a consumer health API of your own, with source URL and retrieval date on each row. When a project also pulls guarded commercial sources, such as pharmacy price pages, anti-bot handling, proxy rotation and CAPTCHA solving are part of the service; NLM's hosts need none of it.
MedlinePlus data is more structured than the pages suggest, once you know where each section keeps it.
Health topics. Health topics come in both languages, 1,017 English and 1,016 Spanish in September 2026. A record carries a numeric id, title, URL, language, creation date and meta description; the full summary as HTML; also-called synonyms and see references; MeSH descriptors with their D numbers; one or more of 44 groups; related topics; the matching topic in the other language; translations in over 50 languages; a primary NIH institute where one is assigned; and every curated link with its title, URL, organization, information category such as Start Here, Treatments and Therapies, Clinical Trials or Patient Handouts, and flags such as NIH, PDF, Video or Easy-to-Read.
Genetics. The MedlinePlus genetic conditions database currently covers 1,305 condition, 1,500 gene and 24 chromosome summaries plus mitochondrial DNA. A condition record gives name, synonyms, description, inheritance codes such as ad, ar, xr or m, related gene symbols, keys into OMIM, GTR, MeSH, SNOMED CT and ICD-10-CM, and reviewed and published dates; a gene record adds its normal function, NCBI Gene ID and the conditions that cite it.
Medical tests. Around 300 test pages per language, each answering the same questions: what the test is used for, why it is ordered, what happens, how to prepare, risks, what results mean, then dated references.
Recipes, drugs and supplements. All 238 recipes in 16 categories show a full Nutrition Facts panel; 202 also carry schema.org Recipe markup with times, yield, ingredients, steps and a credited source, and the other 36 are parsed from the page. About 2,060 drug pages per language are indexed by monograph number, title, brand-name cross-references and last-revised date. Herbs and supplements are no longer hosted: the 79 English entries link out to NCCIH, the NIH Office of Dietary Supplements and the National Cancer Institute.
Codes are what make MedlinePlus data joinable. Health topics carry MeSH descriptors with their D numbers; genetic condition records carry keys into OMIM, GTR, MeSH, SNOMED CT and ICD-10-CM; gene records carry the NCBI Gene ID; drug pages are indexed by monograph number with brand-name cross-references. On top of that we build a code crosswalk for EHRs and patient portals: ICD-10-CM, ICD-9-CM or SNOMED CT for problems, RxCUI or NDC for drugs, LOINC for lab tests, CPT or SNOMED CT for procedures, each mapped to its page in English or Spanish.
The crosswalk is a link layer rather than a corpus. A problem code brings back the matched topic or genetics page with title, URL, synonyms and full summary; a drug code brings the monograph title, URL and a short snippet; a LOINC code brings the test page and a snippet. Tracking tags are stripped from links before joining, and an unmatched code is marked rather than dropped.
A full crosswalk, every ICD-10-CM code or every RxCUI on a formulary mapped to its page, is tens of thousands of lookups, rerun when mappings move. SNOMED CT coverage centers on the CORE Problem List Subset, and the SNOMED CT and ICD-10-CM keys in genetics records are best treated as pointers.
MedlinePlus is the health information site of the U.S. National Library of Medicine, part of NIH, written for patients and families in English and Spanish. It is free, carries no advertising and endorses no product. The MedlinePlus database behind it has six public sections: health topics, drugs and supplements, genetics, medical tests, the A.D.A.M. medical encyclopedia and healthy recipes, plus easy-to-read material and translated handouts in more than 50 languages. No part of it needs an account.
The name invites a standing mix-up. MEDLINE is NLM's index of journal citations, the core of PubMed, built for researchers; MedlinePlus is plain-language reading for the public. The two meet in one place: almost every English health topic carries a Journal Articles link, a PubMed search that NLM librarians build on the topic's MeSH heading. Citations and abstracts are a PubMed project; this page is about the consumer layer.
Addresses are flat and stable. A topic is a slug such as medlineplus.gov/asthma.html, mirrored under /spanish/; a drug page is a monograph number such as /druginfo/meds/a696005.html, with an -es suffix in Spanish; genetics sits under /genetics/condition/, /gene/ and /chromosome/, inherited from Genetics Home Reference, which folded into MedlinePlus in October 2020; tests live under /lab-tests/ and encyclopedia articles under /ency/article/. Pages are static HTML, and one sitemap file lists roughly 25,600 addresses, most of them encyclopedia and drug pages.
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Full plan details →Every section keeps its data in its own shape. A genetics condition page carries frequency, causes, the inheritance narrative, the reference list with PubMed IDs and the related medical tests; a medical test page answers the same questions in the same order; a recipe carries a full Nutrition Facts panel. That is why teams scrape MedlinePlus pages section by section, with a parser for each.
Dates are the next trap. A topic record shows when it was created, while its last change sits in the page's DC.Date.Modified tag and Last updated line. The sitemap does not help, because its lastmod values are rebuild dates: a topic untouched for two years shows this month's date.
Then volume and parity. Finding which of roughly 53,000 curated links were added or retired means diffing one full collection against the last. Spanish is not a clean mirror: MeSH descriptors exist only on English records, genetics reaches Spanish only as the Help Me Understand Genetics handbook, and the Spanish herbs index is about a third of the English one. And there is no MedlinePlus price field anywhere, so price monitoring for the drugs it describes needs a pharmacy source joined on RxCUI or NDC.
Learn how to use web scraping to solve data problems for your organization
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
If you specialize in machine learning, you need to feed large amounts of data to the algorithms. Web scraping is the easiest and the most efficient method of collecting the data from all over the Internet.
ScrapeIt does the engineering: we write the collectors, give each MedlinePlus section its own schedule, compare every run with the one before and repair the pipeline when NLM moves a template, a section or an address. You receive data, not software to babysit.
We have no link to NLM, NIH or MedlinePlus. MedlinePlus holds no patient data, and we collect no personal data.
MedlinePlus is the National Library of Medicine's health information site for patients and families, in plain English and Spanish: health topics, drug information, genetics, medical tests, an encyclopedia and recipes. It is not MEDLINE. MEDLINE is NLM's index of biomedical journal citations, searched through PubMed and written for researchers. The two touch at one point: English health topics link to a librarian-built PubMed search. If your project is citations, abstracts or MeSH-indexed literature, it is a PubMed collection, and we scope it separately.
Yes. The ScrapeIt MedlinePlus API returns health topic summaries, MeSH descriptors, genetic condition records, medical test pages and drug page revision dates as JSON from an endpoint we host, refreshed on the schedule you set. The same data also comes as CSV, Parquet or XML files or straight into your database.
As patient education, yes. Health topic links are chosen against published selection criteria and checked daily for breakage, the site carries no advertising, genetics summaries are reviewed by genetics experts before posting, medical tests get a full review at least every three years, and encyclopedia and drug pages show a review or revision date. Summaries are written for lay readers, so they suit portals, apps and education products rather than clinical decision support. The practical risk is staleness on your side, which is why every row we deliver keeps the page's own modified date.
It depends on the section. Health topics refresh once a day, Tuesday to Saturday; drug pages are added and revised monthly; medical tests run on a three-year review cycle with fixes in between; genetics pages change with expert review. We follow those clocks: topics are diffed on every daily refresh, other sections are polled on their own cadence, and each run lands as a full MedlinePlus dataset plus a change file of added, edited and retired records. Formats are CSV, JSON, Parquet or XML, delivered to S3, SFTP, a database or an API endpoint.
Yes. Health topics, drug pages, genetics, medical tests, the encyclopedia and recipes are open to any visitor, and no part of the site needs an account. We collect only publicly available data - everything a visitor can see on MedlinePlus - and we collect it legally. MedlinePlus holds no patient data, and we collect no personal data.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
MedlinePlus data from €169/month. Free project assessment, reply within 1 business day.
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