| Author . | Study context . | Result . | Lessons . |
|---|---|---|---|
| Montoy et al.45 | Randomization of clinicians to different prepopulated quantities of discharge prescriptions for opioids in emergency departments | A lower default quantity was associated with fewer prescriptions | To minimize possible bias, the study intervention was made without announcement, and prescribers were not informed of the study itself |
| Manz et al.46 | A stepped-wedge cluster RCT, with behavioural nudges directed at oncologists, combined with machine learning mortality predictions positively influenced clinician behaviour through initiating more care planning conversations | Absolute increase of 4% among all patients and 11% in those with high predicted mortality | Integrating behavioural economic principles into the machine learning-based nudge, as a series of co-interventions including peer comparison, feedback, and opt-out reminders |
| Sacarny et al.47 | RCT comparing peer comparison letter vs. placebo letter, across 5055 highest Medicare prescribers of the antipsychotic quetiapine | Over 9 months, the treatment arm supplied 11.1% fewer quetiapine days per prescriber vs. the control arm | Effects were larger than those observed in existing large-scale behavioural interventions, potentially because of the content of the peer comparison letter |
| Author . | Study context . | Result . | Lessons . |
|---|---|---|---|
| Montoy et al.45 | Randomization of clinicians to different prepopulated quantities of discharge prescriptions for opioids in emergency departments | A lower default quantity was associated with fewer prescriptions | To minimize possible bias, the study intervention was made without announcement, and prescribers were not informed of the study itself |
| Manz et al.46 | A stepped-wedge cluster RCT, with behavioural nudges directed at oncologists, combined with machine learning mortality predictions positively influenced clinician behaviour through initiating more care planning conversations | Absolute increase of 4% among all patients and 11% in those with high predicted mortality | Integrating behavioural economic principles into the machine learning-based nudge, as a series of co-interventions including peer comparison, feedback, and opt-out reminders |
| Sacarny et al.47 | RCT comparing peer comparison letter vs. placebo letter, across 5055 highest Medicare prescribers of the antipsychotic quetiapine | Over 9 months, the treatment arm supplied 11.1% fewer quetiapine days per prescriber vs. the control arm | Effects were larger than those observed in existing large-scale behavioural interventions, potentially because of the content of the peer comparison letter |
Studies stretch across medical contexts and also include non-digital platforms but with a generalizable lesson to all EHR-based nudges.
| Author . | Study context . | Result . | Lessons . |
|---|---|---|---|
| Montoy et al.45 | Randomization of clinicians to different prepopulated quantities of discharge prescriptions for opioids in emergency departments | A lower default quantity was associated with fewer prescriptions | To minimize possible bias, the study intervention was made without announcement, and prescribers were not informed of the study itself |
| Manz et al.46 | A stepped-wedge cluster RCT, with behavioural nudges directed at oncologists, combined with machine learning mortality predictions positively influenced clinician behaviour through initiating more care planning conversations | Absolute increase of 4% among all patients and 11% in those with high predicted mortality | Integrating behavioural economic principles into the machine learning-based nudge, as a series of co-interventions including peer comparison, feedback, and opt-out reminders |
| Sacarny et al.47 | RCT comparing peer comparison letter vs. placebo letter, across 5055 highest Medicare prescribers of the antipsychotic quetiapine | Over 9 months, the treatment arm supplied 11.1% fewer quetiapine days per prescriber vs. the control arm | Effects were larger than those observed in existing large-scale behavioural interventions, potentially because of the content of the peer comparison letter |
| Author . | Study context . | Result . | Lessons . |
|---|---|---|---|
| Montoy et al.45 | Randomization of clinicians to different prepopulated quantities of discharge prescriptions for opioids in emergency departments | A lower default quantity was associated with fewer prescriptions | To minimize possible bias, the study intervention was made without announcement, and prescribers were not informed of the study itself |
| Manz et al.46 | A stepped-wedge cluster RCT, with behavioural nudges directed at oncologists, combined with machine learning mortality predictions positively influenced clinician behaviour through initiating more care planning conversations | Absolute increase of 4% among all patients and 11% in those with high predicted mortality | Integrating behavioural economic principles into the machine learning-based nudge, as a series of co-interventions including peer comparison, feedback, and opt-out reminders |
| Sacarny et al.47 | RCT comparing peer comparison letter vs. placebo letter, across 5055 highest Medicare prescribers of the antipsychotic quetiapine | Over 9 months, the treatment arm supplied 11.1% fewer quetiapine days per prescriber vs. the control arm | Effects were larger than those observed in existing large-scale behavioural interventions, potentially because of the content of the peer comparison letter |
Studies stretch across medical contexts and also include non-digital platforms but with a generalizable lesson to all EHR-based nudges.
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