# Use Cases - US Situational Awareness Framework for Reporting (US SAFR) Implementation Guide v1.0.0

* [**Table of Contents**](toc.md)
* **Use Cases**

## Use Cases

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| *Page standards status:*[Informative](http://hl7.org/fhir/R4/versions.html#std-process) |

The US SAFR IG includes example use cases demonstrating its application across various levels of healthcare resource management. These use cases highlight the framework’s ability to address immediate and strategic challenges. For more context, see [Reporting Scenarios](specification.md) where the data exchange methods are detailed. Federal agencies will typically receive data from NHSN.

Note: the use cases here are **examples only**, and are specific to the example measures included in this IG for Bed Capacity and Hospital Respiratory Data (HRD) reporting. However, the framework that this IG creates can be used for other situational awareness use cases beyond Bed Capacity and HRD.

### United States Situational Awareness for Facilitation of Response Measure Reporting Use Cases

#### Use Case #1: Real-Time Bed Capacity and Staffing Needs During a Flu Surge

**Scenario** During a severe flu season, hospitals in a specific jurisdiction experience a high influx of patients with respiratory illnesses, straining bed capacity and staffing resources.

**Facility/Hospital-Level Use**

**1. Bed and Staffing Allocation**

* Hospitals use US SAFR to report real-time bed occupancy and availability every 15 minutes, categorized by bed type.
* Hospital administrators leverage this data to monitor hospital capacity and prioritize staffing where it is most urgently needed.

**2. Resource Allocation**

* By analyzing near real-time bed occupancy and patient influx data, hospitals coordinate with temporary staffing agencies or reallocate internal staff to address shortages effectively.

**Jurisdiction-Level Use**

**1. Capacity Tracking Across Hospitals**

* Local health departments use US SAFR to monitor bed and ICU capacity across multiple facilities, identifying hospitals under the greatest strain.

**2. Cross-Jurisdictional Resource Support**

* Capacity data sharing enables neighboring jurisdictions to coordinate patient transfers and resource reallocation, easing pressure on overwhelmed facilities.

**Federal-Level Use**

**1. National Monitoring and Resource Allocation**

* Federal agencies, including the CDC, receive aggregated data to identify high-occupancy states and allocate emergency resources accordingly.

**2. Trend Analysis and Early Warning System**

* Analysis of surge data enables early detection of trends, guiding preventative measures like vaccination campaigns or public advisories in affected areas.

#### Use Case #2: Emergency Response Coordination for Natural Disaster Evacuations (Declaration of Emergency)

**Scenario** In response to an approaching hurricane on the Texas coastline, local and state emergency management and health departments plan for hospital evacuations of patients to inland facilities.

**Facility/Hospital-Level Use**

**1. Resource Mobilization and Preparedness**

* Coastal hospitals report real-time bed availability and anticipated needs using US SAFR to local and state officials, enabling inland hospitals to prepare and allocate resources in advance.

**2. Evacuation Logistics**

* Real-time data supports collaboration with EMS and transport services, identifying available ICU and specialty care beds at inland facilities for safe patient transfers.

**Jurisdiction-Level Use**

**1. Cross-Hospital Coordination**

* Local and state officials monitor bed capacity across facilities and direct ambulances to locations with adequate resources.

**2. Resource Allocation Across Jurisdictions**

* Aggregated data informs the deployment of critical supplies, ensuring inland hospitals are prepared to receive evacuees.

**Federal-Level Use**

**1. Emergency Support and Resource Allocation**

* Federal agencies assess regional capacity and deploy FEMA medical personnel or National Guard resources as needed.

**2.Unified Federal and State Response**

* US SAFR facilitates coordinated federal-state responses, optimizing resource distribution and avoiding redundancies.

#### Bed Inclusion Criteria

For all bed censuses and counts, the following bed types should be _included_:

1. All inpatient staffed and unblocked beds
1. Observation beds

#### Bed Exclusion Criteria

For all bed censuses and counts, the following bed types should be _excluded_:

1. Virtual beds or locations in the EMR that are not physical spaces (i.e., beds used for interoperative phase of care or in certain operative settings or virtual staging areas for admissions.)
1. Beds no longer in use, even in case of surge
1. Blocked beds (i.e., beds blocked due to logistical or maintenance challenges, staffing restrictions, isolation, etc.)

#### Unit Inclusion Criteria

* ED Emergency department
* ICU Intensive care unit
* LOC Level of care
* MT/MS Medicine telemetry/medicine surgery acute care bed
* NICU Neonatal intensive care unit
* NP Negative pressure
* OB Obstetrics
* OBS Observation
* PCU Progressive care unit
* Peds Pediatric
* PICU Pediatric intensive care unit
* Psych Psychiatric
* Rehab Rehabilitation

#### Bed Capacity Example

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| [Measure - Bed Capacity Measure Example](Measure-BedCapacityMeasureExample.md) | Example of a bed capacity measure for ICU, ED, and Pediatric beds for NHSN reporting. |
| [Library - Library of Bed Capacity Measure Example](Library-BedCapacityMeasure.md) | This library contains CQL logic for evaluating structural measures related to bed capacity reporting capabilities. |
| [MeasureReport - Bed Capacity MeasureReport Example](MeasureReport-BedCapacityMeasureReport.md) | Example MeasureReport for NHSN bed capacity monitoring showing ICU, ED, and Pediatric bed capacity |
| [Bundle - Bed Capacity Report Bundle Example](Bundle-HospitalBedCapacityReportBundle.md) | Bundle containing a measure report and all referenced resources for NHSN bed capacity reporting. |

