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ORIGINAL ARTICLE
Year : 2019  |  Volume : 63  |  Issue : 10  |  Page : 797-804

Completeness of manual data recording in the anaesthesia information management system: A retrospective audit of 1000 neurosurgical cases


1 Department of Neuroanaesthesia and Neurocritical Care, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
2 Brains Neuro Spine Centre, Bengaluru, Karnataka, India

Correspondence Address:
Dr. Kamath Sriganesh
Department of Neuroanaesthesia and Neurocritical Care, Neurosciences Faculty Block, 3rd Floor, National Institute of Mental Health and Neurosciences, Bengaluru - 560 029, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ija.IJA_450_19

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Background and Aims: Anaesthesia information management system (AIMS) is increasingly implemented in many hospitals. Considering the capital cost involved in its installation and maintenance, it is important to evaluate its performance and adoptability by end users. This study assessed the completeness of manual data recording in the AIMS one year after its implementation and also evaluated potential predictors for completeness. Methods: In this retrospective audit of AIMS, 1000 electronic anaesthesia records of patients undergoing neurosurgical procedures over one year were assessed for completeness of 41 preidentified items, one year after its implementation. Parameters evaluated were patient identifiers, personnel identifiers, demographics, airway management parameters, anaesthesia management items and end-of-anaesthesia parameters. We hypothesised that completeness of anaesthesia record can be predicted by nature of surgeries, case sequence, seniority of anaesthesiologist and phase ( first or second) of the study period. Results: We observed higher completeness of manual data recording during phase 2 of AIMS use compared to phase 1. Higher grade of anaesthesiologist, second case of the day and emergency surgery led to reduction in completeness of data entry. Anaesthesiologist grade significantly predicted complete entry of 18 (44%) variables, case number predicted 8 (20%) variables and phase- and procedure-type predicted 6 (15%) and 5 (12%) variables, respectively. Conclusion: Completeness of manual data recording in the electronic AIMS is poor after one year of implementation. First case of the day, second phase of study period, elective cases and trainee anaesthesiologist are associated with better completeness of manual data recording in the AIMS.


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