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Identification of Hypertension Management-related Errors in a Personal Digital Assistant-based Clinical Log for
Nam-Ju Lee1, Eunhee Cho2, Suzanne Bakken3
1Full-time Instructor and Researcher, Research Institute of Nursing Science, Seoul National University College of Nursing, Seoul, Korea.
Purpose:
The purposes of this study were to develop a taxonomy for detection of errors related to hypertension management and to apply the taxonomy to retrospectively analyze the documentation of nurses in Advanced Practice Nurse (APN) training.
Method:
We developed the Hypertension Diagnosis and Management Error Taxonomy and applied it in a sample of adult patient encounters (N = 15,862) that were documented in a personal digital assistant-based clinical log by registered nurses in APN training. We used Standard Query Language queries to retrieve hypertension-related data from the central database. The data were summarized using descriptive statistics.
Result:
Blood pressure was documented in 77.5% (n = 12,297) of encounters; 21% had high blood pressure values. Missed diagnosis, incomplete diagnosis and misdiagnosis rates were 63.7%, 6.8% and 7.5% respectively. In terms of treatment, the omission rates were 17.9% for essential medications and 69.9% for essential patient teaching. Contraindicated anti-hypertensive medications were documented in 12% of encounters with co-occurring diagnoses of hypertension and asthma.
Conclusion:
The Hypertension Diagnosis and Management Error Taxonomy was useful for identifying errors based on documentation in a clinical log. The results provide an initial understanding of the nature of errors associated with hypertension diagnosis and management of nurses in APN training. The information gained from this study can contribute to educational interventions that promote APN competencies in identification and management of hypertension as well as overall patient safety and informatics competencies.
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Factual:
The following points emphasize the significance of upholding accurate and unbiased documentation in healthcare.

