It’s a simple fact of the current state of healthcare that most providers are not using the data they gather via EHRs as best they could.
The case of missed technological opportunities is nothing new to healthcare, but in the case of search engines, not employing them to mine existing information could be costing your clients, and their patients, unnecessary tests, wasted time, and missed information that would have been helpful in achieving desired patient outcomes.
Search And EHR
The premise behind implementing search engine technology in the area of EHRs is simple. Any provider that has access to a patient’s electronic records has a wealth of data available to them. Unfortunately, most of this data still exists in a state that has to be manually pulled or manipulated if a clinician is looking to get a picture of a patient’s holistic medical history. Medical histories regularly being extensive, having to do the legwork of manual search is often perceived as more difficult than simply sending the patient for a brand new battery of tests.
Search In The Emergency Department
A study published by the Journal Of The American College Of Radiology titled “Optimizing Emergency Department Imaging Utilization Through Advanced Health Record Technology” addresses the application of search functions to clinical environments, specifically the emergency department (ED). This department presents special challenges because of the nature of the work involving evaluating complex patients while under time pressure. These challenges are made worse by the incomplete medical history that typically comes with patients who enter the department.
The study covers QPID, which is a programmable health record intelligence system that adds semantic search and knowledge management layers to an EHR system. QPID works as an extension of its data repository, facilitating extraction from it. While most EHR systems do include databases that handle rudimentary data retrieval, QPID allows users to pull data by topic-related “packages” of data and concepts in saved, operable queries that can be used on both structured and unstructured data sources.
So for example, if a doctor would like to be able to search the concept of “abscess” with text and additional EHR data, QPID can do so, by creating a group of terms and concepts such as “fever,” “white blood cell count,” or “antibiotic administration” to provide for automated information retrieval.
Systems like QPID offer four distinct and significant advantages over manual EHR searches:
Solutions providers interested in reading the results, and more details on the QPID study, can access the report here.