Developing voluntary patient safety incident reporting of high-maturity electronic health records
Keywords:
Classification, Class, Electronic Health Records, Patient Safety, ReportingAbstract
Patient safety incident reporting is currently considered a cornerstone of efforts to improve patient safety. For incidents related to high-maturity electronic health record systems (EHRs), there is a need to develop a classification appropriate to clinical operating environment that would benefit the identification of incidents and enhance structured reporting and analysis. The overall aim of the study was to advance use of a voluntary patient safety incident reporting system and to develop the usability of reports in the field of EHR safety. The aim was to categorize and reason patient safety incidents related to high-maturity EHRs so that the classification responds to the characteristics of errors in these systems. Previous research results on the error types in EHRs and incident reports were analyzed and classified for a six-month period immediately after the implementation of the EHRs. The guiding principles of the classification work were based on the features, usage and usability of the classification. The 13 main classes describe the incidents that occur during the clinical use of the advanced EHRs. The largest instance of classes in this dataset were interface, usability, workflow, medication section, and documentation problems. Half of the main classes are supplemented by 2 to 6 subclasses, resulting in 35 classes. The results reflect both theoretical and methodological objectives for the qualitative and contentual development of the classification and practical objectives for the development of reporting. From a clinical point of view, the problem type descriptions are intended to guide the classification of incidents in practice. The study produced a theoretical-practical result in the field of classification research. The classification can be applied to the reporting and analysis of incidents related to high-maturity EHRs. The results highlight the specific features of the category and the distinguishing factors in relation to the other categories, and reasoning for these outcomes. The use of classification is assumed to support incident reporting and use of data. In the future, systematic maintenance and development of the classification based on empirical data will be required in order to further develop the quality of data to support patient safety in the use of EHRs.
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