So, what is a search engine?
It may seem rudimentary, but it’s a question worth asking (and answering) right off the top.
A search engine is a software system that is designed to index vast amounts of data so that users can enter a search string and instantly receive a list of the results that are the best semantic match for what they are seeking. Search engines use proprietary algorithms that consider several factors in order to present the results, which are ranked in order from highest to lowest match scores. The goal is to present the information being searched for at the top of the list.
What is personalized search?
Search engines have evolved a great deal over the last two decades. A key advancement is personalized search, which was introduced by Google in 2004. It is a feature many of us now take for granted. We simply expect that when we search for something online – a restaurant or a pair of shoes – the engine will quickly find exactly what we are looking for.
Today, search engines have access to information about us which is factored into each query for a better machine understanding of an individual’s intent. This process then translates into more personalized, relevant results. As the machine continues to learn more, it is better able to predict intent and constantly improve the relevance of search suggestions and results.
Some of the top factors used in personalizing search are:
- Geolocation
- Search history
- Web history
- Social networks
Furthermore, as search engines learn new details about us, these factors are aggregated based on large groups of individuals who share similar profiles and search histories. This information is used to further improve and influence search results for like-minded individuals.
How does IMO’s personalized search improve EHR workflows?
More than 740,000 US physicians rely on IMO’s clinical terminology to accurately document problems and diagnoses during patient encounters. Our supporting search technology, which processes more than 15 million requests daily, ensures providers find accurate, specific terms with the smallest number of search attempts, keystrokes, or clicks. As a result, IMO has access to a large volume of search data that can be used to gain a better understanding of what providers are looking for and what is subsequently selected from their search results to complete this part of the EHR workflow.
Some of the key details IMO is able to collect and leverage to personalize the search experience are:
- UserID
- Organization
- Provider specialty
- Search and selection history, or what was searched and then selected or used
This information is continuously collected, evaluated, and applied to dynamically improve the clinician’s search experience. IMO’s search engine learns from this data to gain a better understanding of the searcher’s intent and ultimately provide the most relevant results. Indeed, as search terms are entered, character by character, IMO is able to refine and present a predictive list of suggested search terms, freeing clinicians to spend less time on documentation and more time caring for patients.
