Publication date: Jan 08, 2025
To perform risk assessment and analysis of potential infection during stomatology workflow in a hospital in the context of a major infectious disease outbreak, and to determine the key failure modes and measures to prevent and control infection. Following the Failure Modes and Effects Analysis (FMEA) method based on the stomatology workflow, the opinions of 30 domain-experts in related fields were collected through questionnaires to determine all potential failure modes in the severity (S), occurrence (O), and detectability (D) dimensions. The group score was then integrated through the median method and the risk priority number (RPN) was obtained. Finally, combined with expert experience, a score above 100 was considered to define a key potential failure mode. The data collection period for this study was from August to September 2023. The key failure modes identified were “Patient concealed epidemiological history (A) (RPN: 149. 6; Rank: 1),” “At the pre-examination door, safe distancing cannot be practiced due to the large number of visitors (A) (RPN: 147; Rank: 2),” “The patient does not cooperate in checking the health code or itinerary code (A) (RPN: 128, Rank: 3),” “The patient provides a non-personal health code or itinerary code (A) (RPN:121. 5; Rank: 4),” “Pre-examination personnel did not strictly implement the inquiry of epidemiological history (A) (RPN: 120; Rank: 5),” and “The patient did not wear a mask according to the specification (A) (RPN:108. 0; Rank: 6)”. The key risk area was “Before diagnosis and treatment (A)”. Insufficient records of patient epidemiological history may increase the spread of COVID-19 in the oral diagnosis and treatment environment. High-density areas where patients gather are prone to become sources of infection. Finally, improper use of personal protective equipment increases the risk of cross-infection with COVID-19. However, in the face of the potential spread of major infectious diseases in the future, the government and hospitals need to build a more comprehensive epidemiological notification system to provide the population with early action trajectories and warning reports.
Open Access PDF
Semantics
| Type | Source | Name |
|---|---|---|
| disease | MESH | infectious diseases |
| disease | MESH | infection |
| pathway | REACTOME | Infectious disease |
| disease | IDO | infectious disease |
| disease | IDO | history |
| disease | MESH | COVID-19 |
| disease | MESH | cross infection |
| pathway | REACTOME | Reproduction |
| drug | DRUGBANK | Coenzyme M |
| drug | DRUGBANK | Etoperidone |
| drug | DRUGBANK | Medical air |
| drug | DRUGBANK | Serine |
| disease | MESH | emergency |
| disease | MESH | anxiety |
| disease | MESH | depression |
| drug | DRUGBANK | Esomeprazole |
| drug | DRUGBANK | Fenamole |
| disease | IDO | process |
| drug | DRUGBANK | Trestolone |
| disease | IDO | object |
| disease | MESH | privacy |
| disease | MESH | coronavirus infection |
| disease | MESH | Rare Diseases |
| disease | MESH | Oral Health |
| disease | IDO | intervention |
| disease | MESH | myocardial infarction |
| disease | IDO | blood |