Background: Physicians and nurses are responsible for reporting medical adverse events. Each views these events through a different lens subject to their role-based perceptions and barriers. Physicians typically engage with diagnosis and treatment while nurses primarily care for patients' daily lives and mental well-being. This results in reporting and describing medical adverse events differently.
Objective: We aimed to compare adverse medical event reports generated by physicians and nurses to better understand the differences and similarities in perspective as well as the nature of adverse medical events using social network analysis (SNA) and latent Dirichlet allocation (LDA).
Methods: The current study examined data from the Maccabi Healthcare Community. Approximately 17,868 records were collected from 2000 to 2017 regarding medical adverse events. Data analysis used SNA and LDA to perform descriptive text analytics and understand underlying phenomenon.
Results: A significant difference in harm levels reported by physicians and nurses was discovered. Shared topic keyword lists broken down by physicians and nurses were derived. Overall, communication, lack of attention, and information transfer issues were reported in medical adverse events data. Specialized keywords, more likely to be used by a physician were determined as: repeated prescriptions, diabetes complications, and x-ray examinations. For nurses, the most common special adverse event behavior keywords were vaccine problem, certificates of fitness, death and incapacity, and abnormal dosage.
Conclusions: Communication and inattentiveness appeared most frequently in medical adverse events reports regardless of whether doctors or nurses did the reporting. Findings suggest feedback and information sharing processes could be implemented as a step toward alleviating many issues. Institutional management, healthcare managers and government officials should take actions to decrease medical adverse events, many of which may be preventable.
Keywords: Patient safety; latent Dirichlet allocation (LDA); medical adverse event; medical adverse event reporting system; nurse; physician; social network analysis (SNA).