Name
Title | ||
|---|---|---|
Provider variation in responses to warnings: do the same providers run stop signs repeatedly? |
Abstract | ||
|---|---|---|
Methods Responses to warnings were prospectively logged. Random effects models were used to calculate provider-to-provider variation in the rates for the decisions to override warnings in 6 different clinical domains: medication allergies, drug-drug interactions, duplicate drugs, renal recommendations, age-based recommendations, and formulary substitutions. Results A total of 157 482 responses were logged. Differences between 1717 providers accounted for 11% of the overall variability in override rates, so that while the average override rate was 45.2%, individual provider rates had a wide range with a 95% confidence interval (CI) (13.7%-76.7% ). The highest variations between providers were observed in the categories age-based (25.4% of total variability; average override rate 70.2% [95% CI, 29.1%-100% ]) and renal recommendations (24.2%; average 70% [95% CI, 29.5%-100% ]), and provider responses within these 2 categories were most often clinically inappropriate according to prior work. Among providers who received at least 10 age-based recommendations, 64 of 238 (27%) overrode a parts per thousand yenaEuro parts per thousand 90% of the warnings and 13 of 238 (5%) overrode all of them. Of those who received at least 10 renal recommendations, 36 of 92 (39%) overrode a parts per thousand yenaEuro parts per thousand 90% of the alerts and 9 of 92 (10%) overrode all of them. Conclusions The decision to override prescribing warnings shows variation between providers, and the magnitude of variation differs among the clinical domains of the warnings; more variation was observed in areas with more inappropriate overrides. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1093/jamia/ocv117 | JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION |
Keywords | Field | DocType |
clinical practice variation,clinical decision support systems,attitude of health personnel,computer-assisted drug therapy,medical order entry systems | Data mining,Random effects model,Electronic prescribing,Confidence interval,Medicine,Formulary | Journal |
Volume | Issue | ISSN |
23 | E1 | 1067-5027 |
Citations | PageRank | References |
3 | 0.42 | 3 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Patrick E Beeler | 1 | 12 | 3.96 |
| E. John Orav | 2 | 8 | 2.90 |
| Diane L Seger | 3 | 11 | 2.45 |
| Patricia C. Dykes | 4 | 113 | 40.88 |
| David W Bates | 5 | 6 | 1.23 |