COVID-19 Risk Profile Assessment

Purpose	Predict the risk of COVID-19 infection in patients during the imaging scheduling process through the analysis of clinical symptoms and environmental and occupational risk factors. Staff would then be alerted of patients at high-risk for COVID-19 infection who are being scheduled for upcoming imaging. This risk information would then be used to ensure that high-risk patients are scheduled at specific times, at specific facilities, and on specific reserved equipment and that any staff handling these patients takes appropriate protective precautions.
Tag(s)
Panel	Non-Interpretive, COVID-19
Define-AI ID	20160005
Originator	COVID-19 Sub-Panel
Panel Chair	Woojin Kim, Ben Wandtke
Panel Reviewers	Rob Ambrosini
License	Creative Commons 4.0
Status	Public Comment

Clinical Implementation

Value Proposition

COVID-19 and other viral infections can result in significant illness and even death. Highly contagious infections, such as COVID-19, are transmitted mainly through droplets, but also by contact with infected surfaces and other modes of transmission. Effective prevention of viral spread includes measures like social distancing (keeping 6 ft/2 meters or more between persons), wearing personal protective equipment, frequent handwashing, and cleaning of surfaces.

Knowledge of patients at high-risk for COVID-19 infection during the imaging scheduling process can help reduce the exposure of other patients and limit the potential infection spread. Additionally, when high-risk patients present for imaging exams, receptionists, technologists, and other imaging staff can take necessary precautions to protect themselves and other patients from potential infection. Infection risk mitigation can be accomplished by scheduling high-risk patients for specific times, at specific facilities, and/or on specific equipment reserved for high-risk patients. The goal is to avoid crowding in patient waiting and service areas, and this has to take into account additional time needed for exam room turnover.

Narrative(s)

Clinical Scenario 1: An 80-year-old man presents for outpatient CT imaging to follow up previously treated lung cancer. The patient is a nursing home resident with recent development of a cough and sore throat. The patient has not been tested for COVID-19 infection.

Clinical Scenario 2: A 65-year-old woman presents for pre-surgical breast MRI prior to cancer resection. The patient flew back from a country with a level 3 travel advisory within the last 5 days.

Clinical Scenario 3: A 25-year-old woman presents for outpatient abdominal CT for abdominal pain. She works as a nurse in the COVID-19 unit at her hospital.

Clinical Scenario 4: A 45-year-old male presents to the emergency room after a fall from a ladder with loss of consciousness and worsening mental status change, needing a head CT. The patient also reports fever, cough, shortness of breath, and loss of smell over the past few days, raising suspicion for COVID-19 infection. The patient is now a person under investigation (PUI) for COVID-19.

Clinical scenario 5: A 45-year-old woman presents for a mammogram screening exam. She is extremely anxious because her friend was just diagnosed with breast cancer, and she experiences the same discomfort in her breasts that her friend did.

Clinica scenario 6: A 14-year-old boy presents with a 1st time febrile seizure. He is otherwise healthy and has no risk factors for COVID-19.

Workflow Description

Clinical signs and symptoms and risk factor data are collected from manual patient screening (facilitated by telephone questionnaires completed by the scheduling team) and automated screening via search of the electronic medical record for a patient during the imaging scheduling process. This search should identify patients who have had or are scheduled for a COVID-19 test and the result of COVID-19 testing, if the test result is available. This data is processed by the AI model. The model determines if the patient is high-risk for being infected with COVID-19. A message is then sent to the clinical staff through the radiology information system regarding the patient’s high-risk status and the patient is scheduled accordingly. An annotation is made on the patient’s scheduled appointment to alert the reception staff, technologists, and other imaging staff of the patient’s high-risk status at the time of their presentation to the imaging center.

Data Elements

Inputs

Data Element	Data Type	Description	Notes
Fever	Categorical	Patient presents with fever. (Y/N)
Body temperature	Numerical
Chills	Categorical	Patient presents with chills. (Y/N)
Cough	Categorical	Patient presents with a cough. (Y/N)
Shortness of breath or difficulty breathing	Categorical	Patient presents with shortness of breath or difficulty breathing. (Y/N)
Respiratory rate	Numerical
Fatigue	Categorical	Patient presents with fatigue. (Y/N)
Muscles or body aches	Categorical	Patient presents with body aches. (Y/N)
Headache	Categorical	Patient presents with a headache. (Y/N)
New loss of taste or smell	Categorical	Patent presents with a new loss of taste or smell. (Y/N)
Sore throat	Categorical	Patient presents with a sore throat. (Y/N)
Congestion or runny nose	Categorical	Patient presents with congestion or a runny nose. (Y/N)
Nausea or vomiting	Categorical	Patient presents with nausea or vomiting. (Y/N)
Diarrhea	Categorical	Patient presents with diarrhea. (Y/N)
Nursing/Group home resident	Categorical	Patient is a resident of nursing or group home. (Y/N)
Medical worker	Categorical	Patient is a medical worker. (Y/N)
Known exposure to COVID-19 positive individual or location	Categorical	Patient has interacted with someone with a known COVID-19 diagnosis or visited a location with a relatively higher prevalence of COVID-19 cases. (Y/N)
Travel history	List	List of patient’s recent travel history
Clinical urgency	Categorical	Category of clinical urgency
Patient is an essential worker	Categorical	Indicates whether the patient is an essential worker during the outbreak. Essential vs. non-essential.
Age	Integer	Patient’s age at the time of registration
Comorbidities	Categorical	List of comorbidities for COVID-19 People with chronic lung disease or moderate to severe asthma People who have serious heart conditions People who are immunocompromised Many conditions can cause a person to be immunocompromised, including: cancer treatment, smoking, bone marrow or organ transplantation, immune deficiencies, poorly controlled HIV or AIDS, and prolonged use of corticosteroids and other immune weakening medications People with severe obesity (body mass index [BMI] of 40 or higher) People with diabetes People with chronic kidney disease undergoing dialysis People with liver disease	Ref 1
Sex	Categorical	Value representing the sex of the patient
Recent imaging	Categorical	Recent imaging exam results with evidence or suggestion of COVID-19 infection
Patient anxiety	Categorical	If the patient suffers from anxiety over a postponed imaging study, and their anxiety outweighs the risk of infection while at the imaging center, the study should be performed

Primary Outputs

Categorical Risk that Patient is COVID-19 Positive

Definition	Patient’s COVID-19 positive risk based on clinical signs and symptoms as well as risk factors
Data Type	Categorical
Value Set	High risk Low risk Unknown
Units	N/A

Categorical Risk that Patient is COVID-19 Positive

Definition	Patient’s COVID-19 positive risk based on clinical signs and symptoms as well as risk factors
Data Type	Categorical
Value Set	High risk Low risk Unknown
Units	N/A

Numerical Risk that Patient is COVID-19 Positive

Definition	Scale of risk that patient is COVID-19 positive
Data Type	Numeric
Value Set	N/A
Units	N/A

Risk Factors

Definition	Risk factors predisposing of worse outcomes with COVID-19 infection
Data Type	Categorical
Value Set	Risk factors present No risk factors
Units	N/A

Clinical Indication

Definition	Level of urgency for obtaining the study
Data Type	Categorical
Value Set	Emergent Essential Elective
Units	N/A

References

People Who Are at Increased Risk for Severe Illness. (2020, June 25). Available at: <https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-at-increased-risk.html?CDC_AA_refVal=https%3A%2F%2Fwww.cdc.gov%2Fcoronavirus%2F2019-ncov%2Fneed-extra-precautions%2Fpeople-at-higher-risk.html>
Catalyst.nejm.org. 2020. Identifying Patients With Increased Risk Of Severe Covid-19 Complications: Building An Actionable Rules-Based Model For Care Teams | Catalyst Non-Issue Content. Available at: <https://catalyst.nejm.org/doi/full/10.1056/CAT.20.0116>.

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