Comparing care pathways between COVID-19 pandemic waves using electronic health records: a process mining case study (preprint)

Purpose: The COVID-19 pandemic caused rapid shifts in the workflow of many health services, but evidence of how this affected multidisciplinary care settings is limited. We propose a Process Mining approach that utilises timestamped data from Electronic Health Records to compare care provider patterns across pandemic waves.  Methods: We collected routine events from Scottish hospital episodes in adults with COVID-19 status and linked health provider inputs to generate standardised treatment logs. Conformance checking metrics were used to select the optimal model (Inductive Miner infrequent [IMi]) for downstream analysis. Visual diagrams from the discovered Petri Nets indicated the interactions on pre-coded provider and activity-level subsets. We used cross-log conformance checking and graph similarity to measure distances between adverse and less adverse groups across pandemic waves.  Results: We included 1,153 patients with COVID-19 (302 [26%] in Wave 1 and 851 [74%] in Wave 2) with 55,212 relevant care provider events. At the conformance checking stage, the IMi model, achieved good log fitness (LF=0.95) and generalisation (G=0.89), but limited precision (PR=0.27) across all granularity levels. More structured care procedures in Wave 1 were present, compared to mixed multidisciplinary patterns in Wave 2. Care activities differed in patients with extended stay (GED=348, PR=0.231 vs GED=197, PR=0.429 in shorter stays). Patients in out-of-hours care and intensive therapy were linked with more standardised patterns.  Conclusion: Process Mining can be incorporated alongside clinical oversight to provide visual and quantitative comparisons of care interactions in COVID-19 episodes and enhance further research in complex cases.

Cold Atmospheric Helium Plasma In The Post-Covid Era: A Promising Tool For The Disinfection Of Silicone Endotracheal Prostheses (preprint)

The COVID-19 pandemic resulted in a high prevalence of laryngotracheal stenosis. The endoluminal tracheal prostheses used to treat this condition are made of medical-grade silicone (MGS). Despite their excellent properties, the main limitation of these prostheses is the formation of a polymicrobial biofilm on their surfaces that interacts with the underlying mucosa, causing local inflammation and interfering with the local healing process, ultimately leading to further complications in the clinical scenario. Cold atmospheric plasma (CAP) shows antibiofilm properties on several microbial species. The present study evaluated the inhibitory effect of CAP on multispecies biofilms grown on MGS surfaces. In addition to the MGS characterization before and after CAP exposure, the cytotoxicity of CAP on immortalized human bronchial epithelium cell line (BEAS-2B) was evaluated. The aging time test reported that CAP could temporarily change the MGS surface wetting characteristics from hydrophilic (80.5 degrees) to highly hydrophilic (< 5 degrees). ATR-FTIR shows no significant alterations in the surficial chemical composition of MGS before and after CAP exposure for 5 min. A significant log reduction of viable cells in mono-species biofilms (log CFU/mL) of C. albicans, S. aureus, and P. aeruginosa (0.636, 0.738, and 1.445, respectively) were detected after CAP exposure. Multi-species biofilms exposed to CAP showed significant viability reduction for C. albicans and S. aureus (1.385 and 0.831, respectively). The protocol was not cytotoxic to BEAS-2B. It could be concluded that CAP can be a simple and effective method to delay the multi-species biofilm formation inside the endotracheal prosthesis.