Sleep medicine traffic comes from queries like "home sleep study near me Cigna" or "in-lab polysomnography Chicago," combinations of study type, city, and insurance acceptance. A patient suspecting sleep apnea has already been told by a primary care doctor or a partner that something is wrong, and they search for a sleep specialist who runs the right kind of study and is in network.

SleekRank reads the provider roster, a Google Sheet, a CSV export from the credentialing system, or a REST API from the practice's EHR, and uses one base WordPress page as the template. Each row becomes a URL with the physician's name, board certification, hospital affiliation, study types offered, CPAP follow-up policy, oral appliance referrals, and accepted insurance carriers mapped in. A new sleep technologist or physician joins the practice, add a row.

Study type is the column that drives intent. Map studyTypes as a JSON array, render it as a badge strip, and generate per-study hubs at /sleep-doctors/home-sleep-testing/{city}/ for patients who specifically want HSAT. Cache duration of 24 hours keeps the directory current, and the 404 on deletion keeps the sitemap clean.

Sleep medicine sits in a strange spot in the patient journey. Diagnosis usually starts with a primary care visit or a partner complaint, not with the patient deciding they need a sleep doctor unprompted. By the time they search, they already know they need a study, and the question is which study and where.

A patient who has been told to get a home sleep test does not want to read a long bio about a doctor who only runs in-lab studies. A patient with suspected narcolepsy needs MSLT capability, which most general sleep doctors do not offer. Insurance acceptance compounds the problem because sleep studies are expensive and out-of-network testing can run into thousands of dollars.

A faceted hospital directory that exposes every filter on one URL cannot rank for the combination queries patients actually run. A sheet-driven directory makes study type, board specialty, insurance, and city first-class data, then slices them with URL patterns so a patient searching for home sleep apnea testing with Cigna in Chicago lands on a page that names the three providers who match. The credentialing system stays the source of truth, and the public directory becomes a downstream consumer rather than a parallel artifact.