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| Name | Class |
|---|---|
| Datavant | INDUSTRY |
| American Heart Association | OTHER |
| BioIntelliSense | UNKNOWN |
| PWNHealth |
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ACCESS enables individuals to contribute to critical research, via an iOS and Android smartphone mobile application. ACCESS combines patient reported outcomes, data from wearable devices and real-world data (such as claims, EHRs, etc), with an opt-in to participate in current and future studies for diagnostics, treatments and vaccines. The data that people share can be quickly and anonymously matched to research studies, providing researchers with a foundational framework for dynamic research at scale and participants a way to be personally matched and prescreened for future research.
In the urgency of the COVID-19 outbreak, Medable will enable an observational study protocol under which clinical trials can rapidly be conducted. The observational study protocol will include the conduct of smartphone based research to capture an essential dataset to improve our understanding of disease evolution, risk factors, and outcomes as well as enable population-based monitoring to reduce the spread of disease. Under this protocol, sub-studies and clinical trials can be conducted for interventions, including vaccine trials. The work may include new tools such as surface environmental or personal swabs to test for presence or absence of disease. Data collection efforts on behalf of rapidly evolving multiple study designs and participant opt-in data sharing, will enable the compilation of critical epidemiological and other data across the United States to accelerate the understanding for effective mitigation and treatment of COVID-19.
ACCESS (American COVID-19 Collaborative Enabling Seamless Science), a novel COVID-19 digital research infrastructure, provides a mobile app tool for participants to report specific data and facilitate remote access to accelerate critical research and clinical treatment development.
ACCESS leverages leading digital health technologies to facilitate at-home research, clinical trials, and population-based long-term outcome studies and data de-identification measures (data coding/tokenization). The infrastructure combines opt-in wearable sensors, patient reported data and outcomes, opt-in data aggregation and additional opportunities for users to participate in clinical trials and share their de-identified data based upon reported information.
Prior to COVID-19, the FDA expressed an interest in expediting drug development through developing trial designs that test multiple drugs and/or multiple subpopulations in parallel under a single protocol, without a need to develop new protocols for every trial. This has become even more important during the COVID-19 pandemic. This type of work will also be enabled under the ACCESS system.
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| Measure | Description | Time Frame |
|---|---|---|
| Development of population-based models of disease risk | To use multifaceted participant data consisting of participant reported outcomes, environmental surface and presence or absence of COVID-19 based on testing results, prescription medications (including off-label use), claims, lab, and medical record data to develop population-based models of disease risk, short and long-term outcomes, and efficacy of interventions and prevention measures. | Up to 10 years |
| Relation between disease burden and geolocation | To leverage geolocation and lab results to provide population-level real-time data regarding disease burden at the community, state and national levels. | Up to 10 years |
| Effect of medications on symptoms of COVID19 | To specifically identify medications and regimens that address disease symptoms | Up to 10 years |
| Effect of medications on disease severity of COVID19 | To specifically identify medications and regimens that treat and reduce disease severity. | Up to 10 years |
| Measure | Description | Time Frame |
|---|---|---|
| Rate of COVID19 infection and disease outcomes | To identify regional variations in disease incidence and outcomes. | Up to 10 years |
| Effect of COVID19 on health outcomes | To understand long-term outcomes such as risk of pulmonary and cardiovascular disease complications. |
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Inclusion Criteria:
Exclusion Criteria:
1. Do not have a personal smartphone
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This is a national surveillance study for the general public.
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| Name | Affiliation | Role |
|---|---|---|
| Ingrid Oakley-Girvan, PhD | Medable Inc. | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Medable Inc. | Palo Alto | California | 94301 | United States |
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| Label | URL |
|---|---|
| Press Release of Collaborative Framework for ACCESS | View source |
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Please reach out to the study team for data sharing policies and procedures. Only de-identified and aggregate data may be considered for sharing.
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| ID | Term |
|---|---|
| D018352 | Coronavirus Infections |
| D000086382 | COVID-19 |
| ID | Term |
|---|---|
| D003333 | Coronaviridae Infections |
| D030341 | Nidovirales Infections |
| D012327 | RNA Virus Infections |
| D014777 | Virus Diseases |
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| Up to 10 years |
| Long-term follow up and recontact | To conduct long-term follow up of individuals who tested positive for COVID-19 compared to demographically matched individuals that did not. | Up to 10 years |
| D007239 |
| Infections |
| D011024 | Pneumonia, Viral |
| D011014 | Pneumonia |
| D012141 | Respiratory Tract Infections |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |