Responding to
COVID-19 Together

We are honored to have worked over the past decade with our country’s first responders, doctors, nurses, and healthcare administration and we have been amazed with their response and selflessness.

The situation is evolving quickly, and Arcadia is rapidly developing and deploying novel tools to support our delivery systems throughout the crisis. This site will be updated with our latest progress and success stories from the field.

Move quickly, share freely, learn, iterate and adapt

Arcadia’s Long-COVID Research Initiative

As many as 1 in 10 people may have symptoms of COVID-19 for months after their initial infection. To address this public health crisis, Arcadia is contributing our research data asset (comprising aggregated, de-identified records for more than 155 million patients) and our data science expertise to the COVID Patient Recovery Alliance (PRA). The PRA is a multi-sector collaboration supporting the energy and innovation of government and private-sector leaders as they care for patients with long-term health consequences from COVID-19 infection.

Key finding: Vaccination may reduce the odds of experiencing Long-COVID, even if the vaccine occurs after COVID-19 infection

 Arcadia analyzed de-identified real world data on over 25 million patients in a search for potential drivers of Long-COVID.  Our most recent finding is that vaccination against COVID-19 reduces the likelihood that patients will experience long-COVID symptoms in the event that they are infected. Our data also suggest that a single dose of a COVID-19 vaccine, even if received after the patient is diagnosed with COVID, still correlates with a reduced likelihood of presenting long-COVID symptoms.

  • One Dose — That’s all it takes to reduce long-COVID symptoms. Patients who received at least one dose of any of the three COVID-19 vaccines (Pfizer-BioNTech, Moderna, and Johnson & Johnson) prior to a diagnosis were 7-10 times less likely to report two or more long-COVID symptoms compared to unvaccinated patients. 
  • 4 Weeks — The amount of time a patient has after infection to significantly reduce long-COVID symptoms via vaccination. Unvaccinated patients who received their first COVID-19 vaccination after four weeks of SARS-CoV-2 infection were 4-6 times less likely to report multiple long-COVID symptoms
  • 300% — The reduction of reported long-COVID symptoms even after receiving a vaccination up to 8 weeks after infection. Those who received their first dose 4-8 weeks after diagnosis were three times less likely to report multiple long-COVID symptoms compared to those who remained unvaccinated. 
  • Long-Term Protection — Vaccines work. The findings show that vaccination has a protective effect even when the first dose was administered up to 12 weeks after diagnosis

Learn more here.

Get updates on our research

Arcadia and the PRA continue to collaborate on research initiatives. To receive periodic updates and more clinical and technical detail, you can get in touch below or follow us on LinkedIn.

Arcadia’s Evolving Population Health Response Kit

As we work together to flatten the curve in the spread of COVID-19, health systems are now using the new COVID-19-specific algorithms and workflows within Arcadia’s population-level platform. Arcadia is supporting the healthcare system in several ways, among them:

On March 20th Arcadia met with its customer base remotely and unveiled a series of tools and strategies for supporting the COVID-19 response with population health. Since then we have been rapidly deploying new stratification algorithms, patient engagement tools, and surveillance analytics on a national scale. The video below is a snippet of our initial Mar 20 presentation. Watch the full video

Watch the full COVID-19 video

Patient Stratification

Population Stratification Algorithms

At the center of our population health strategy to support COVID-19 is a novel set of stratification models to identify patients of highest need and risk. These inform engagement efforts and the allocation of limited primary care and navigation services. Arcadia is rolling these out for all patients with any activity in the last 5 years. 

High-to-moderate risk of complications from COVID-19

  • High risk for COVID-19 complications with behavioral health complications
  • High risk for COVID-19 complications without behavioral health complications
  • Moderate risk for COVID-19 complications with behavioral health complications
  • Moderate risk for COVID-19 complications without behavioral health complications

Patients with chronic or current care needs

  • Physical Health Vulnerabilities
  • Mental Health Vulnerabilities

Patients that are symptomatic, or diagnosed with COVID-19

  • Symptomatic or Diagnosed and sent home
  • Discharged/Recovered

Patients that are healthy or otherwise historically unengaged

Cohorts were designed from factors that are believed to elevate a patient’s risk of having serious complications should they become infected with COVID-19. An additional behavioral health stratification was layered in as it can further complicate feelings to isolation and anxiety. Younger populations are generally at lower risk of serious illness or death from COVID-19, while over 50% of members age 80 or older have evidence of a condition that will increase their likelihood of serious complications as it relates to COVID-19. 

Outreach, Education, Symptom Checking and Triage

Arcadia has configured its Outreach and Engage products with content specific to education and triage of COVID-19. The interactive content, currently available in 9 languages, is delivered to patients directly on their mobile device without any pre-configured software. Acting as an extension of the care team, the content guides patients through access information for telehealth and hotlines, provides a personalized interactive COVID symptom checker, and allows health systems to securely capture information about patients’ symptoms and care needs.


As organizations quickly evolve to meet the demands and constraints of COVID-19, patients need consistent, trusted information about access to care and new or relevant services to help them cope with the crisis. 

  • Branded and tailored message gives patients a trusted local face.
  • Tailored list of resources available to the patient, including hotlines, mental health programs and e-visit capabilities.
  • Information about practice closures and alternative access points.
  • Direct link integration to patient portals for scheduling and telehealth.
  • Link to dynamic symptom check screener or other web tools from the provider. 

Symptom Check Screening tool

Give patients the most accurate, up-to-date information on COVID-19 symptoms and pair it with “escalation points” to urgent care, emergency room, telehealth visits and hotline numbers. 

  • Patients receive a dynamic mobile screening tool aligned with evolving CDC guidance. 
  • Patients attest to symptoms and describe recent travel or testing. 
  • Patients without known symptoms are re-assured and reminded to stay home and practice social distancing.
  • Patients with known symptoms are directed to the provider’s phone numbers or web portals to access care.

Patient Reported Outcomes

For symptomatic patients or those at higher risk, provide a regular electronic check-in on evolving symptoms, care needs and social factors.

  • Ongoing symptom surveillance lets the patient attest to the quality and severity of their symptoms and builds a longitudinal dataset.
  • Self-triage with dynamic reactions. If patient attests to major symptoms or care needs, dynamically respond and direct them to specific medical or social services.
  • We all have higher level of anxiety. Reassure the patient (when appropriate) that certain symptoms are not associated by the CDC to COVID-19.
  • Regular re-enforcement of clinical and mental health services and public health guidance.

Care Team Extension

Now, more than ever, care teams around the country need the support and extenders that population health programs can provide. Access to primary care is severely reduced due to office closures and patients’ fear of getting sick. The most vulnerable of our population risk falling through the cracks during this crisis.

Care management programs

Combining our enhanced stratification algorithms and our broad automated engagement platform, care teams can isolate and focus on complex co-morbid patients at the highest risk of falling through the cracks.

Our care management software has been enhanced to include support for COVID, as well as dozens of high risk medical and social factors.

An automation engine can “escalate” patients to a navigator phone call within minutes of a patient responding to a mobile screener.

Research and Analytics

You need access to good, fast, trusted data to effectively deploy resources to respond to the pandemic. Arcadia is surveilling systems and diagnostics from all your EHRs, HIEs, labs, claims systems and directly from patients.


Nightly extractions of patient charts including structured, pseudo-structured, and unstructured note data.


Real time alerts of admissions, discharges, and transfers from hospitals and HIEs.


Testing response made available to understand what is happening to patients with an integrated dataset. 

Patient Responses

Real time additions of data entered by patients via text message surveys or entered by care managers on the phone with a patient.  

Public/Private Partnerships

Arcadia has joined with other private sector organizations to form the COVID-19 Healthcare Coalition, a collaborative private-industry response to the novel coronavirus. Its mission is to save lives by providing real-time learning to preserve healthcare delivery capacity and protect U.S. populations. Each coalition partner is bringing its unique assets, sharing resources and plans, and working together to support those on the front lines in responding to COVID-19. Learn More

Educational Items We’ve Found Helpful

New York Times COVID-19 Data

An ongoing repository of data on coronavirus cases and deaths in the U.S.:

McKinsey & Company

The COVID-19 outbreak is a human tragedy and has a growing impact on the global economy. This is McKinsey’s evolving take on coronavirus’ business implications.

Simulating an Epidemic by 3Blue1Brown

Modelling the spread of infectious disease, looking at the effect of various containment measures on the incidence and growth rate of infection. COVID-19-data

Unpivoted and cleaned data sets on the COVID-19 pandemic.

COVID-19 Healthcare Coalition Resource Library

Pandemics thrive in confusion. Help our nation achieve clarity.

Unacast Social Distancing Scoreboard

Understand which areas of the country are best at exhibiting social distancing behavior.

Corona Data Scraper

COVID-19 Coronavirus data scraped from government and curated data sources.

Institute for Health Metrics and Evaluation

Explore projected hospital bed use, need for intensive care beds, and ventilator use due to COVID-19 based on projected deaths for all 50 US states and District of Columbia.

Arcadia Data Gallery

This Is What The Flu Looks Like

Nick Stepro, Simon Ioffe. 2020. D3.js, with Illustrator. Data sourced from Commercial, Medicare and Medicaid claims from Arcadia Benchmark Database

The 2017 – 2018 influenza season was the worst on record since the 2009 H1N1 swine flu. The CDC estimates 45 million people nationally caught the flu, with 810,000 hospitalizations and 61,000 deaths.

In 2020, viral outbreaks are on most of our minds. While mortality and transmission rates of the novel coronavirus (COVID-19) far exceeds those of the 2017-2018 flu, a look backwards can still be instructive. Even with its reduced virality, and the presence/distribution of vaccines, the 2017-2018 outbreak was explosive.

Looking at Massachusetts transmissions using medical claims data, we visualize not just the growth rate of total cases but the algae-like “blooms” of infections. A few small clusters at thanksgiving bloom into thousands of cases by new years, each interaction a potential for transmission. For the purposes of illustration, the artist draws a linkage between each new case and the closest person that had a diagnosis four days prior. This simulates the transmission graph as a social network of sorts, and highlights the importance of current calls for “social distancing” as we deal with an ever more deadly virus.

A Population Under A Microscope

Samir Farooq, Michael Simon, Nick Stepro. 2019. Python, D3.js, with Illustrator. Data sourced from Commercial, Medicare and Medicaid claims from Arcadia Benchmark Database

Care management programs are not one-size fits all. Rather, patients have subtle characteristics requiring tailored patient-centered plans of care. Similarly, the extent to which the patient will benefit from the targeted program varies as well. Identifying those who will be most successful in a given care program takes a combination of medical expertise, research, and mathematical estimation. Arcadia quantifies this “impactability” with learning algorithms that look through hundreds of thousands of past cases, finding shared attributes in those that had the greatest success.

This illustration analyzes about 64,000 patients and their predicted impactability (main diagram) along with their characteristics (sub-diagrams) to answer the question: what characteristics are the strongest indicators of success in complex care management?

Taking the population under a microscope, by applying t-SNE (a dimensionality reduction technique) and subsequently studying the resulting clusters, we find that four distinct groups of patients exist that have high impact scores, and many more small groups. While the largest group is composed of the most predictable at-risk patients (high cost and complex conditions; top left), the other groups show: 1) a unique pattern of avoidable and emergent Emergency Department utilization lead to high impact scores (top right), 2) a particular combination of chronic, psychosocial, and frailty conditions lead to high impact scores (bottom right), and 3) certain socioeconomic traits, along with a set of specific conditions, lead to high impact scores (bottom left).

Arcadia’s impactability algorithm consumes more than thirty specific risk factors – nearly impossible for care managers to keep track of over all patients, but easy for the algorithm to combine into one risk score tailored to care management. This algorithmic assist not only finds more actionable patients, but also lets program coordinators repurpose their valuable time from patient identification to patient engagement and program design.

Harmony Of Data Integration

Jeff Soloman. 2018. D3.js SVG, with Illustrator. Data from Arcadia integration logs, with metadata from leading EHRs and health plan claims data.

The complexity of the data integration challenge in healthcare, is often ethereal, or even escaping. It is near impossible to instinctively grasp the sheer magnitude of data, the complexity of connecting it, and the value of simplifying it. Years of experience in the industry make it easier. But it requires a deep understanding of numbers that have been proven outside of human capabilities to understand. In this work the artist takes an emotional and stunningly beautiful approach to helping the reader see how 2 billion health records across 58 data sources, 3,909 tables, across 1 million patients, and 27 different vendor systems can be simplified.

The artist’s use of a chord diagram helps emphasize the connectivity and relationships between the source data and Arcadia data warehouse. The imbalance between the almost 4 thousand source tables and the 27 destinations creates an emotional connection with the movement and flow of data that even those familiar with a chord diagram may find jarring.

For those who want to look further, the artist shares two other dimensions in the data. The size of each data source is represented as an outer ring, and the size of each of the 3,909 tables in depicted in the bar charts surrounding the edge of the chord diagram.

Through this work, the artist hopes the viewer leaves with a clear understanding of what are otherwise staggeringly incomprehensible amounts of data, and an emotional connection to what happens when you simplify and unify healthcare data.

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