Characteristics of urban versus rural utilization of the Polish Helicopter Emergency Medical Service in patients with ST-segment elevation myocardial infarction.

BACKGROUND: In patients with acute phase of ST­segment elevation myocardial infarction (STEMI), quick transportation to a specialist therapeutic center is of utmost importance to increase the chances of surviving. AIMS: The objective of this study was to characterize the missions of the Polish Helicopter Emergency Medical Service (HEMS) to patients with STEMI in urban and rural areas and to assess the utilization of air ambulance support as part of an early stage of the therapeutic process. METHODS: This retrospective analysis included 6099 patients with STEMI treated by the Polish HEMS crews from January 2011 to December 2018. RESULTS: The study group included mainly men (68.9%) and persons aged 60 to 79 years (53.9%). The mean (SD) age of the entire group was 64.8 (11.9) years. The level of consciousness measured by the Glasgow Coma Scale score ranged from 13 to 15 (84.8% of patients), the mean (SD) Revised Trauma Score was 11.4 (1.9) points, and the mean (SD) number of points on the National Advisory Committee for Aeronautics scale was 4 (1). In rural areas, the Polish HEMS crews were more frequently dispatched to medical emergencies (99.3% vs 59.6%). Sudden cardiac arrest occurred more often in those areas (6% vs 3.8%), which resulted in the death of the patient (2.4% vs 0.4%; P <0.05 for both). CONCLUSIONS: There were differences in utilization of the Polish HEMS in patients with STEMI in urban and rural areas. The results demonstrated a positive impact of the utilization of HEMS in the early stages of the therapeutic process of these patients.

Data governance in predictive toxicology: A review.

BACKGROUND: Due to recent advances in data storage and sharing for further data processing in predictive toxicology, there is an increasing need for flexible data representations, secure and consistent data curation and automated data quality checking. Toxicity prediction involves multidisciplinary data. There are hundreds of collections of chemical, biological and toxicological data that are widely dispersed, mostly in the open literature, professional research bodies and commercial companies. In order to better manage and make full use of such large amount of toxicity data, there is a trend to develop functionalities aiming towards data governance in predictive toxicology to formalise a set of processes to guarantee high data quality and better data management. In this paper, data quality mainly refers in a data storage sense (e.g. accuracy, completeness and integrity) and not in a toxicological sense (e.g. the quality of experimental results). RESULTS: This paper reviews seven widely used predictive toxicology data sources and applications, with a particular focus on their data governance aspects, including: data accuracy, data completeness, data integrity, metadata and its management, data availability and data authorisation. This review reveals the current problems (e.g. lack of systematic and standard measures of data quality) and desirable needs (e.g. better management and further use of captured metadata and the development of flexible multi-level user access authorisation schemas) of predictive toxicology data sources development. The analytical results will help to address a significant gap in toxicology data quality assessment and lead to the development of novel frameworks for predictive toxicology data and model governance. CONCLUSIONS: While the discussed public data sources are well developed, there nevertheless remain some gaps in the development of a data governance framework to support predictive toxicology. In this paper, data governance is identified as the new challenge in predictive toxicology, and a good use of it may provide a promising framework for developing high quality and easy accessible toxicity data repositories. This paper also identifies important research directions that require further investigation in this area.