SmartDocFinder™ employs state-of-the-art matching technology, developed through university-industry collaboration, partially funded by the National Science Foundation.
HOW DOES SMARTDOCFINDER LEARN PATIENT AND PROVIDER PROFILES?
SmartDocFinder™ learns every patient’s healthcare needs, personality and priorities, and every provider’s expertise and care delivery style. For that, it employs proprietary data analysis methods on the patients’ interaction with the system and dozens of external data sources, including:
Interviews with local providers.
Quality and performance measures for healthcare providers, hospitals and insurance plans published by government and other agencies. These include referrals data, procedures performed and associated costs provided by the Centers for Medicare & Medicaid Services.
Provider listings from government sources, which SmartDocFinder™augments through integrating with dozens of other sources, for instance, to display health insurance and board certification information.
Hospital listings provided by government sources.
Patient opinions from SmartDocFinder and other sources.
SmartDocFinder suggests providers based on three complementary dimensions.
HOW DOES SMARTDOCFINDER MATCH PATIENTS TO PROVIDERS?
As more quality and outcome measures are being generated and published, SmartDocFinder™ is uniquely capable to identify and combine the most relevant metrics for a patient’s condition. In addition to quality metrics, expert models identify the impact of provider care attributes such as experience and affiliated hospitals to the patient’s condition and preferences.
PATIENT PERSONAL PREFERENCES
As an example, past research has shown that patients who are younger, more educated, and experiencing less severe illness prefer more information and active participation in their medical treatment. SmartDocFinder™ goes a step further by identifying the best providers for every single patient and not just for demographic groups.
OPINION OF SIMILAR PATIENTS
SmartDocFinder™ does not believe in the simplistic stars-based rating system. Research has shown that current rating schemes are ineffective in the context of healthcare, because patients rate a very narrow set of attributes of a provider, primarily the wait and visit times. As a result, 41% of patients think that current rating sites are not important when selecting a primary care physician. SmartDocFinder™ analyzes reviews using proprietary domain-specific text mining, and deeply integrates them into the multi-dimensional ranking model.