Ubiquitous Search and Browse Features
The remodeled homepage provides visitors with several fast and intuitive search and browsing mechanisms to find medical information and doctors:
- Search Conditions & Treatments: Jump to a condition or treatment based on first letter using an A-Z search:
- Find a Doctor: Search by name, location or other keyword:
- Browse Clinical Trials: Quick links area to find active Clinical Trials affiliated with the Medical Center:
"Quick Finders" as time savers
The site features reusable code blocks called "macros". These macros are implemented as "Quick Searches" and "A to Z Finders":
- "Find a Doctor": All data on doctors is indexed and searchable, so users can easily find a doctor by typing in keywords such as name, specialty, location, etc. This feature is available on both the homepage and Doctors area of the site.
- "Locations & Directions": Keyword search on location (e.g., city or street), name, service, etc. to narrow down a list of locations on the map view.
- "Clinical Trials": Quickly find a clinical trial by searching by condition or disease, doctor's name, or IRB-HSR number.
The "A to Z Finders" enable narrowing lists down by a title's first letter for:
- "Conditions and Treatments": Via the homepage and Services area of the site
- "Clinical Locations": Browse locations by name
Advanced Search using Faceted Navigation
The University of Virginia Health System website also utilizes a faceted navigation system for browsing doctors. This tool allows visitors to narrow down the list of doctors by one or more Specialty, Languages Spoken and/or Gender.
Synonyms, Ranking and Weighting
Six Feet Up extended the basic Plone search features for the UVA Health System web site by adding:
- Synonyms: Site administrators can easily add terms so keyword searches return similar items. For example:
- Searching for "myocardial infarction" will return documents with keywords like "heart attack"
- Searching for "H1N1" will return documents tagged with "flu"
- Ranking and Weighting: The number of times a keyword is used in the site is calculated. When compared to the number of documents in the site, the document term frequency is calculated. The larger the document term frequency, the higher the document is ranked within the search results.