Man versus Machine: the importance of manual blood pressure measurement skills amongst registered nurses
Bibliographic record
Abstract
Background: The manual recording of blood pressure is widely accepted to be more accurate than the recording of blood pressure using an automated device. Despite this many western healthcare systems have moved almost entirely to the automated recording of this important vital sign using oscillometric devices. Such devices may either fail to record the patient’s blood pressure in persistent hypotension or may give inaccurate readings in people with arteriosclerotic or atherosclerotic changes. This paper explores the importance of manual blood pressure recording, the availability of aneroid sphygmomanometers in UK hospitals and the maintenance of the skills of the workforce following initial nurse education.Methods: Using a survey of nursing students to explore what opportunities they have to practice manual blood pressures in the clinical setting, the paper explores the maintenance of skills following initial nurse education. The paper also describes the results of data collection, using unobtrusive methods, regarding the availability of aneroid sphygmomanometers in general and specialist hospital facilities in Northern England (UK). Data using both methods were collected in the spring of 2014.Results: The results suggest that despite most hospitals having some aneriod sphygmomanometers available (mean was 1 device for every 6 beds in acute, 1 device for every 3 beds in specialist hospitals and 1 device for every 12 beds in mental health) they were rarely used in clinical practice with only 35% of students reporting that they had undertaken a manual blood pressure in a clinical setting during the first year of their course. In addition, some hospitals had no aneroid devices and several others had no central record of location and regular calibration of such devices.Conclusions: The suggested infrequent use of aneroid devices raises a concern that nurses skills in manual blood pressure recording may be subject to decay over time. Given the importance of these skills in patient safety and, in ensuring accurate and effective care, failure to ensure adequate equipment and opportunities for skill maintenance could result in practitioners and hospitals being open to negligence claims
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".