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In the emergency department, the urgency for treating patients is determined according to the Manchester Triage System. The parameters collected in this process are deterministically translated into a treatment priority.
The Manchester Triage System (MTS), which has been in use for at least 20 years, is a widely used, validated and standardized procedure for initial assessment in the emergency department - this initial assessment (triage) is done to prioritize medical assistance at a central point. Especially in emergency situations, critically endangered patients often require the deployment of a large part of the available staff at the same time - the medically correct triage of patients according to objective criteria in order to enable an adequate allocation of the available resources at the right time is the main objective. In the optimal case, each patient is treated by medical professionals within the time frame that is adequate for his/her health condition.
Using artificial intelligence methods, it may be possible to increase the accuracy of treatment priority assignment. In the best case, incorrect prioritization of patients can be prevented and medical care can be ensured for those patients who actually need it most urgently.
However, initial assessment, even if standardized and validated, still runs under limited resource conditions - time, space, material and personnel. Last but not least, the very idea of conducting an initial assessment limits its validity, and the results of the allocation fluctuate according to current research, although the determinants of this are currently unknown.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Admission to General Ward Positive | Admission to General Ward Positive |
| |
| 30 Day Mortality Positive | 30 Day Mortality Positive |
| |
| Admission to Intensive Care Unit Positive | Admission to Intensive Care Unit Positive |
| |
| Admission to General Ward Negative | Admission to General Ward Negative | ||
| 30 Day Mortality Negative | 30 Day Mortality Negative | ||
| Admission to Intensive Care Unit Negative | Admission to Intensive Care Unit Negative |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Admission to General Ward | Other | Admission to General Ward |
| |
| Measure | Description | Time Frame |
|---|---|---|
| AUROC for Classification of Admission to General Ward | AUROC for Classification of Admission to General Ward | 2015-12-01 to 2020-08-31 |
| AUROC for Classification of Admission to Intensive Care Unit | AUROC for Classification of Admission to Intensive Care Unit | 2015-12-01 to 2020-08-31 |
| AUROC for Classification of 30 Day Mortality | AUROC for Classification of 30 Day Mortality | 2015-12-01 to 2020-08-31 |
| Measure | Description | Time Frame |
|---|---|---|
| Confusion Matrix | Confusion Matrix Results: true positives, true negatives, false positive, false negatives and values calculated from these results. | 2015-12-01 to 2020-08-31 |
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Inclusion Criteria:
Exclusion Criteria:
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As described in the inclusion criteria.
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| Name | Affiliation | Role |
|---|---|---|
| Thomas Tschoellitsch, MD | Kepler University Hospital and Johannes Kepler University, Linz, Austria | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Kepler University Hospital | Linz | Upper Austria | 4021 | Austria |
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| ID | Term |
|---|---|
| D009026 | Mortality |
| ID | Term |
|---|---|
| D014798 | Vital Statistics |
| D003625 | Data Collection |
| D004812 | Epidemiologic Methods |
| D008919 | Investigative Techniques |
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| Admission to Intensive Care Unit |
| Other |
Admission to Intensive Care Unit |
|
| 30 Day Mortality | Other | 30 Day Mortality |
|
| D003710 |
| Demography |
| D011154 | Population Characteristics |
| D015991 | Epidemiologic Measurements |
| D011634 | Public Health |
| D004778 | Environment and Public Health |