Influence of AIDET in the improving quality metrics in a small community hospital - before and after analysis
Bibliographic record
Abstract
Background: As the US healthcare system is becoming a more outcomes based system, increasing emphasis is being paidto improving all aspects of health care delivery. Interpersonal and communication skills, an ACGME (Accreditation Councilfor Graduate Medical Education) core competency in resident education, play a fundamental role in this effort. This aspectof healthcare delivery is also part of Medicare hospital reviews. In our hospital, the administration has introduced AIDET (Acknowledge, Introduce, Duration, Explanation, and Thank you) as a communication strategy which promises to improveexchange of information between healthcare professionals as well as with patients and their families. Objective: Determine if theAIDET strategy used in our facility has improved patient satisfaction.Methods: This study was done using pretest post test experimental design. Patient satisfaction was measured using scores fromthe HCAHPS (Hospital Consumer Assessment of Healthcare Providers and Systems) quarterly reports from the 3rd quarter of2010 to the 2nd quarter of 2013. Pre and post AIDET implementation results were statistically analysed using a paired t-test.Results are reported as a p-value with < .05 being statistically significant.Results: There were a total of 1,811 patient responses sampled from the 3rd quarter of 2010 to the 2nd quarter of 2013. Asignificant change < .05 was seen in the way Nurses Explain, Doctors Explain and Nurses listen in the pre and post AIDETimplementation comparison. The change in percentage of patients that believed doctors and nurses explained things to them in away they could understand showed a p-value of .02. The trend in percentage of patients that perceived that nurses always listenedcarefully to them showed a p-value of .02 as well. On the other hand, the data evaluating how doctors listened carefully to themdid not reach statistical significance with a p-value of .08. The remaining categories of “Told About Medication” and “Help afterDischarge” were both found not have changed significantly either.Conclusions: The implementation of AIDET education may have had a significant impact on provider-patient communication inour facility, especially in the patient’s perception of explaining things in a way they could understand. On the other hand, in theresponses to the question of whether or not doctors listened carefully to them, there was some improvement over time, howeverthis did not achieve statistical significance.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".