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| ID | Type | Description | Link |
|---|---|---|---|
| 5R01EB032752-10 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Institute for Biomedical Imaging and Bioengineering (NIBIB) | NIH |
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Alerts related to outlier clinician behavior are generated in real-time by an intelligent system continuously scraping EHR (electronic health record) data. These alerts are passed to the bedside and their potential impact on bedside clinical behavior is evaluated.
A clinician-informed AI model will generate outlier alerts from real-time review of the EHR (electronic health record) of UPMC Presbyterian/Montefiore ICU patients. These alerts will first be reviewed by an ICU clinician, along with the patients' EHR, for clinical relevance. For those alerts deemed potentially relevant, the ICU clinician will contact the treating ICU clinician (eg, an ICU pharmacist, physician, advanced practice provider) and discuss the alert. The treating ICU clinician will take whatever action, including no action, they deem best.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Unrevealed Alerts | Active Comparator |
| |
| Revealed Alerts | Experimental |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Revealed Alerts | Device | Bedside reveal of alerts generated by the alerting system |
| |
| Measure | Description | Time Frame |
|---|---|---|
| Rate of Clinical Actions Following Revealed vs. Non-Revealed Alerts | The primary outcome compares the proportion of alerts that lead to documented clinical actions when revealed to treating ICU clinicians versus when not revealed. Alerts are generated by a decision support system and reviewed daily by ICU study clinicians. On average, 30 alerts are reviewed per ICU per day, with approximately 5 alerts revealed to the treating clinicians. The analysis uses a stepped wedge design with ICU beds as the unit of analysis, where each ICU acts as its own control. The outcome will assess whether revealing alerts increases the rate of appropriate clinical actions taken, as compared to when alerts are withheld. | From time of ICU admission until ICU discharge |
| Measure | Description | Time Frame |
|---|---|---|
| Rate of Any Clinically Responsive Action Following Alerts | For each alert, a range of clinical actions may be deemed "responsive," including but not limited to the specific recommended action. This outcome assesses the differential rate of any clinically appropriate response (whether or not it matches the recommended action) between alerts that are revealed versus not revealed to treating ICU clinicians. |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| David Huang, MD | University of Pittsburgh | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| UPMC Montefiore | Pittsburgh | Pennsylvania | 15213 | United States | ||
| UPMC Presbyterian |
The investigators do not currently have a data sharing plan for sharing with future investigators. If the investigators decide to share data in the future with investigators conducting similar research both inside and outside of the University of Pittsburgh, the investigators will contact the Office of Sponsored Programs before sharing de-identified research data to determine whether an agreement needs to be executed.
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| ID | Term |
|---|---|
| D016638 | Critical Illness |
| ID | Term |
|---|---|
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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Step wedge RCT
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| Unrevealed Alerts |
| Device |
Alerts will be generated but not revealed. |
|
| Up to 90 days after ICU admission |
| True Positive Alert Rate (TPAR) by Study Group and Alert Type | This outcome evaluates the overall and alert-specific True Positive Alert Rate (TPAR), defined as the proportion of alerts that are associated with a clinically appropriate action. TPARs will be calculated separately for the intervention group (alerts revealed), the control group (alerts not revealed), and the combined population. Comparisons will assess whether revealing alerts is associated with a higher TPAR across alert categories. | Up to 90 days after ICU admission |
| Rate of Non-Responsive Actions Following Alerts | This outcome assesses the difference in the rate of clinical actions that are not considered responsive to the alert (i.e., actions taken that do not address the alert's content or recommended intervention) between the intervention group (alerts revealed) and the control group (alerts not revealed). This helps evaluate potential unintended or off-target responses to alerting. | Up to 90 days after ICU admission |
| Overall Alert Rate | Total number of alerts generated per ICU per day. | Through study completion, an average of 2 years |
| Alert Rate per Alerting Model | Number of alerts generated per model type per ICU per day. | Daily, up to 90 days |
| Delay Between Alert Generation and First Responsive Action | Median time from alert generation to the first documented responsive clinical action. | Measured continuously through study completion, an average of 2 years |
| ICU Length of Stay | Total number of days each participant spends in the ICU during the index hospitalization. | Up to 90 days after ICU admission |
| Hospital Length of Stay | Total number of days each participant spends in the hospital during the index hospitalization. | up to 90 days after hospital admission |
| In-Hospital Mortality | Proportion of participants who die during the index hospital stay. | Up to 90 days after hospital admission |
| Time Trend of True Positive Alert Rate (TPAR) | Evaluate changes in the True Positive Alert Rate (TPAR) over time during the study period to assess model performance stability and potential temporal variation in responsiveness. | Through study completion, an average of 2 years |
| Pittsburgh |
| Pennsylvania |
| 15213 |
| United States |