How a direct connection to engaged individuals can increase the speed and decrease the cost of clinical trial recruitment

Quick Facts

  • Over 128,00 initial survey respondents
  • 500+ COVID-19 diagnoses reported
  • 4 to 7 times higher incidence rate detected than similar real-world study cohorts
"It's about finding the right people at the right time for the right trial."
- Ernesto Ramirez, Sr. Manager of Consumer Research

Challenge

  • When the infection base rate incidence is low, the cohort size required to measure an effect grows; this may increase the amount of time that might be needed to recruit additional trial participants as well as the associated costs 
  • Evidation developed and conducted a study to examine if and how completing surveys and sharing data from consumer wearable devices could help to identify COVID-19 infections 
  • In order for the trial to meet its analytical goals, a number of positive COVID-19 infections had to be observed; if too few were observed, the study could have failed

Approach

  • Evidation leveraged its longitudinal relationship with members of the Evidation platform and applied machine-learning modeling of COVID-19 risk to determine and recruit a high-risk study population 
  • After deploying two separate surveys to participants, Evidation found that 514 respondents indicated they had received a COVID-19 diagnosis within the ~2 months since completing the initial survey 
  • The machine-learning model was then used to segment individuals based on their likelihood of infection; individuals more likely to be infected were primarily targeted for recruitment and were selected to generate a dataset with balanced demographic variables 

Results

  • By using the novel model and prioritizing recruitment based on the likelihood of infection, Evidation was able to observe a 4- to 7- times greater incidence rate of COVID-19 infection than what was being observed by the vaccine trials going on at the same time 
  • These results demonstrate that a direct connection to engaged individuals allows us to understand how behaviors and demographics may impact infection risk

Contact Us

Learn how Evidation can help with your recruitment needs: Contact us

Have questions?

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How a direct connection to engaged individuals can increase the speed and decrease the cost of clinical trial recruitment

Quick Facts

  • Over 128,00 initial survey respondents
  • 500+ COVID-19 diagnoses reported
  • 4 to 7 times higher incidence rate detected than similar real-world study cohorts
"It's about finding the right people at the right time for the right trial."
- Ernesto Ramirez, Sr. Manager of Consumer Research

Challenge

  • When the infection base rate incidence is low, the cohort size required to measure an effect grows; this may increase the amount of time that might be needed to recruit additional trial participants as well as the associated costs 
  • Evidation developed and conducted a study to examine if and how completing surveys and sharing data from consumer wearable devices could help to identify COVID-19 infections 
  • In order for the trial to meet its analytical goals, a number of positive COVID-19 infections had to be observed; if too few were observed, the study could have failed

Approach

  • Evidation leveraged its longitudinal relationship with members of the Evidation platform and applied machine-learning modeling of COVID-19 risk to determine and recruit a high-risk study population 
  • After deploying two separate surveys to participants, Evidation found that 514 respondents indicated they had received a COVID-19 diagnosis within the ~2 months since completing the initial survey 
  • The machine-learning model was then used to segment individuals based on their likelihood of infection; individuals more likely to be infected were primarily targeted for recruitment and were selected to generate a dataset with balanced demographic variables 

Results

  • By using the novel model and prioritizing recruitment based on the likelihood of infection, Evidation was able to observe a 4- to 7- times greater incidence rate of COVID-19 infection than what was being observed by the vaccine trials going on at the same time 
  • These results demonstrate that a direct connection to engaged individuals allows us to understand how behaviors and demographics may impact infection risk

Contact Us

Learn how Evidation can help with your recruitment needs: Contact us

Have questions?

CONTACT US

How a direct connection to engaged individuals can increase the speed and decrease the cost of clinical trial recruitment

Quick Facts

  • Over 128,00 initial survey respondents
  • 500+ COVID-19 diagnoses reported
  • 4 to 7 times higher incidence rate detected than similar real-world study cohorts
"It's about finding the right people at the right time for the right trial."
- Ernesto Ramirez, Sr. Manager of Consumer Research

Challenge

  • When the infection base rate incidence is low, the cohort size required to measure an effect grows; this may increase the amount of time that might be needed to recruit additional trial participants as well as the associated costs 
  • Evidation developed and conducted a study to examine if and how completing surveys and sharing data from consumer wearable devices could help to identify COVID-19 infections 
  • In order for the trial to meet its analytical goals, a number of positive COVID-19 infections had to be observed; if too few were observed, the study could have failed

Approach

  • Evidation leveraged its longitudinal relationship with members of the Evidation platform and applied machine-learning modeling of COVID-19 risk to determine and recruit a high-risk study population 
  • After deploying two separate surveys to participants, Evidation found that 514 respondents indicated they had received a COVID-19 diagnosis within the ~2 months since completing the initial survey 
  • The machine-learning model was then used to segment individuals based on their likelihood of infection; individuals more likely to be infected were primarily targeted for recruitment and were selected to generate a dataset with balanced demographic variables 

Results

  • By using the novel model and prioritizing recruitment based on the likelihood of infection, Evidation was able to observe a 4- to 7- times greater incidence rate of COVID-19 infection than what was being observed by the vaccine trials going on at the same time 
  • These results demonstrate that a direct connection to engaged individuals allows us to understand how behaviors and demographics may impact infection risk

Contact Us

Learn how Evidation can help with your recruitment needs: Contact us

Have questions?

CONTACT US

How a direct connection to engaged individuals can increase the speed and decrease the cost of clinical trial recruitment

Quick Facts

  • Over 128,00 initial survey respondents
  • 500+ COVID-19 diagnoses reported
  • 4 to 7 times higher incidence rate detected than similar real-world study cohorts
"It's about finding the right people at the right time for the right trial."
- Ernesto Ramirez, Sr. Manager of Consumer Research

Challenge

  • When the infection base rate incidence is low, the cohort size required to measure an effect grows; this may increase the amount of time that might be needed to recruit additional trial participants as well as the associated costs 
  • Evidation developed and conducted a study to examine if and how completing surveys and sharing data from consumer wearable devices could help to identify COVID-19 infections 
  • In order for the trial to meet its analytical goals, a number of positive COVID-19 infections had to be observed; if too few were observed, the study could have failed

Approach

  • Evidation leveraged its longitudinal relationship with members of the Evidation platform and applied machine-learning modeling of COVID-19 risk to determine and recruit a high-risk study population 
  • After deploying two separate surveys to participants, Evidation found that 514 respondents indicated they had received a COVID-19 diagnosis within the ~2 months since completing the initial survey 
  • The machine-learning model was then used to segment individuals based on their likelihood of infection; individuals more likely to be infected were primarily targeted for recruitment and were selected to generate a dataset with balanced demographic variables 

Results

  • By using the novel model and prioritizing recruitment based on the likelihood of infection, Evidation was able to observe a 4- to 7- times greater incidence rate of COVID-19 infection than what was being observed by the vaccine trials going on at the same time 
  • These results demonstrate that a direct connection to engaged individuals allows us to understand how behaviors and demographics may impact infection risk

Contact Us

Learn how Evidation can help with your recruitment needs: Contact us

Have questions?

CONTACT US

How a direct connection to engaged individuals can increase the speed and decrease the cost of clinical trial recruitment

Quick Facts

  • Over 128,00 initial survey respondents
  • 500+ COVID-19 diagnoses reported
  • 4 to 7 times higher incidence rate detected than similar real-world study cohorts
"It's about finding the right people at the right time for the right trial."
- Ernesto Ramirez, Sr. Manager of Consumer Research

Challenge

  • When the infection base rate incidence is low, the cohort size required to measure an effect grows; this may increase the amount of time that might be needed to recruit additional trial participants as well as the associated costs 
  • Evidation developed and conducted a study to examine if and how completing surveys and sharing data from consumer wearable devices could help to identify COVID-19 infections 
  • In order for the trial to meet its analytical goals, a number of positive COVID-19 infections had to be observed; if too few were observed, the study could have failed

Approach

  • Evidation leveraged its longitudinal relationship with members of the Evidation platform and applied machine-learning modeling of COVID-19 risk to determine and recruit a high-risk study population 
  • After deploying two separate surveys to participants, Evidation found that 514 respondents indicated they had received a COVID-19 diagnosis within the ~2 months since completing the initial survey 
  • The machine-learning model was then used to segment individuals based on their likelihood of infection; individuals more likely to be infected were primarily targeted for recruitment and were selected to generate a dataset with balanced demographic variables 

Results

  • By using the novel model and prioritizing recruitment based on the likelihood of infection, Evidation was able to observe a 4- to 7- times greater incidence rate of COVID-19 infection than what was being observed by the vaccine trials going on at the same time 
  • These results demonstrate that a direct connection to engaged individuals allows us to understand how behaviors and demographics may impact infection risk

Contact Us

Learn how Evidation can help with your recruitment needs: Contact us

Have questions?

CONTACT US

How a direct connection to engaged individuals can increase the speed and decrease the cost of clinical trial recruitment

Quick Facts

  • Over 128,00 initial survey respondents
  • 500+ COVID-19 diagnoses reported
  • 4 to 7 times higher incidence rate detected than similar real-world study cohorts
"It's about finding the right people at the right time for the right trial."
- Ernesto Ramirez, Sr. Manager of Consumer Research

Challenge

  • When the infection base rate incidence is low, the cohort size required to measure an effect grows; this may increase the amount of time that might be needed to recruit additional trial participants as well as the associated costs 
  • Evidation developed and conducted a study to examine if and how completing surveys and sharing data from consumer wearable devices could help to identify COVID-19 infections 
  • In order for the trial to meet its analytical goals, a number of positive COVID-19 infections had to be observed; if too few were observed, the study could have failed

Approach

  • Evidation leveraged its longitudinal relationship with members of the Evidation platform and applied machine-learning modeling of COVID-19 risk to determine and recruit a high-risk study population 
  • After deploying two separate surveys to participants, Evidation found that 514 respondents indicated they had received a COVID-19 diagnosis within the ~2 months since completing the initial survey 
  • The machine-learning model was then used to segment individuals based on their likelihood of infection; individuals more likely to be infected were primarily targeted for recruitment and were selected to generate a dataset with balanced demographic variables 

Results

  • By using the novel model and prioritizing recruitment based on the likelihood of infection, Evidation was able to observe a 4- to 7- times greater incidence rate of COVID-19 infection than what was being observed by the vaccine trials going on at the same time 
  • These results demonstrate that a direct connection to engaged individuals allows us to understand how behaviors and demographics may impact infection risk

Contact Us

Learn how Evidation can help with your recruitment needs: Contact us

Have questions?

CONTACT US
Eve: Evidation's brand mark which is a yellow glowing orb

How a direct connection to engaged individuals can increase the speed and decrease the cost of clinical trial recruitment

Quick Facts

  • Over 128,00 initial survey respondents
  • 500+ COVID-19 diagnoses reported
  • 4 to 7 times higher incidence rate detected than similar real-world study cohorts
"It's about finding the right people at the right time for the right trial."
- Ernesto Ramirez, Sr. Manager of Consumer Research

Challenge

  • When the infection base rate incidence is low, the cohort size required to measure an effect grows; this may increase the amount of time that might be needed to recruit additional trial participants as well as the associated costs 
  • Evidation developed and conducted a study to examine if and how completing surveys and sharing data from consumer wearable devices could help to identify COVID-19 infections 
  • In order for the trial to meet its analytical goals, a number of positive COVID-19 infections had to be observed; if too few were observed, the study could have failed

Approach

  • Evidation leveraged its longitudinal relationship with members of the Evidation platform and applied machine-learning modeling of COVID-19 risk to determine and recruit a high-risk study population 
  • After deploying two separate surveys to participants, Evidation found that 514 respondents indicated they had received a COVID-19 diagnosis within the ~2 months since completing the initial survey 
  • The machine-learning model was then used to segment individuals based on their likelihood of infection; individuals more likely to be infected were primarily targeted for recruitment and were selected to generate a dataset with balanced demographic variables 

Results

  • By using the novel model and prioritizing recruitment based on the likelihood of infection, Evidation was able to observe a 4- to 7- times greater incidence rate of COVID-19 infection than what was being observed by the vaccine trials going on at the same time 
  • These results demonstrate that a direct connection to engaged individuals allows us to understand how behaviors and demographics may impact infection risk

Contact Us

Learn how Evidation can help with your recruitment needs: Contact us

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