Using PatientStormChaser, the new relational time pattern based search engine from Lyntek, a continuous quality improvement team can search the EMR system-wide for virtually any pattern of clinical failure in high detail without reviewing a single electronic chart.
A single CQI nurse can accomplish more in-depth quality review and educational presentation formatting of clinical cases in one day than the entire CQI department can accomplish in a month.
For example, with the PatientStormChaser search engine, the determination of diagnostic delay for a selected adverse condition can be determined system-wide, within clinical regions, or by provider, with only a few clicks. All of this is presented in fine detail by a range of user friendly visualizations. Most importantly, these are not results emerging from black box “big data” statistics. The diagnostic delays are presented with the actual data, with complete transparency, so everyone can learn from them. This is a truly revolutionary new type of search engine.
How is it possible?
The determination of system-wide diagnostic delay for a specific diagnosis using conventional CQI software is quite expensive and tedious. With the conventional approach, the nurse first searches the EMR for adverse conditions, searching for text or ICD-codes to identify the potential patients who may have experienced a diagnostic delay. The CQI team then reviews the clinical data, lab tests, vitals, timing of drug administration, etc. in each individual patient record to determine the diagnostic delay for each case. This is very time consuming and presupposes that the correct diagnosis was made and identifiable in the text or ICD-code by the conventional search engine. Therefore, despite all the time and resources spent, cases where the true diagnosis was never suspected before death or discharge may easily be missed.
However, with PatientStormChaser, the nurse not only searches the EMR for text, ICD-codes, and medications, but at the same time, searches the electronic health records (EHR) in a hospital or hospital system for the actual diagnostic delays in relation to the complex relational time patterns of the adverse clinical condition under test. This is performed automatically and without the need for massive and tedious individual chart reviews by the CQI team.
Like PatientStormTracker, PatientStormChaser is computationally transparent, allowing medical professionals and researchers to see and search the underlying data with complete, easy to understand formatting of the adverse event and its timed relationship to procedures and/or drug treatment.
These relationships are presented for all to see and understand. This provides for immediate education which can lead to prompt improvement in protocol compliance.
In addition to continuous quality improvement, PatientStormChaser has applications in advanced research for those scientists, regulators, external quality reviewers, and payers, who wish to have a means for automated study beyond administrative data, to the study of the actual relational time patterns of the adverse clinical event in relation to the timing of treatment and recovery.
To learn more about PatientStormChaser—one of Lyntek’s newest, and most exciting technologies—request a demo of the software, by visiting here.