Digitalizing quality of care control: a Business Intelligence system for COVID-19 inpatients

Abstract Issue As healthcare systems faced the challenge of COVID-19, need for fast and automated quality care control has grown tremendously. Automatization is widely implemented in form Clinical Decision Support Systems (CDS), however, developing such software can take several years trained IT specialists' work. Description problem We opted an analytics clinical decision support (ACDS) system based on Business Intelligence (BI) software, since it would allow to monitor necessary data, was easy adapt current tasks didn't require any special IT-educated specialists develop implement. From individual patient's electronic health record (EHR) extracted specific as vital signs, laboratory tests CT scans, respiratory data; medication prescribed taken; chronic diseases, etc. Microsoft Power BI used build ACDS. The ACDS consisted three main elements: Flat tables (the data from EHR); Data model, connecting tables; Visualizations (tables charts) depicting patients' condition, which provided integration information, ability sort order, intuitive marks, color indicators parameter values. Results Named visualizations were integrated daily work heads units. Out 1683 patients admitted with 1415 undergoing treatment after implementation system. It correct course 568 patients. following corrections made: Accuracy diagnosis (138 cases) assigned severity (115) Prescribed delivered medicines (32) Dosage adjustment (25) Transfer ICU (2) Discharge (412) Lessons Thus, engineering analytical appears be advantageous way automate challenging time-pressing circumstances. Key messages In a situation unprecedented time pressure resource shortage, best option might simple system, rather than designated CDS software. practice COVID-19 become foundation designing bigger transparent that adapted patient model or entity.