C O V I D - 1 9 A N DM I N O R I T Y

H E A L T H A C C E S SILLUSTRATING SYMPTOMATIC CASES FROM

REPORTED MINORITY COMMUNITIES ANDHEALTHCARE GAPS DUE TO COVID-19 .

MARCH 2020 | INFECTIOUS DISEASE INSIGHTS

As the emerging novel coronavirus (COVID-19) infectious pathogen rapidly spreadsglobally and in the United States of America(USA), healthcare institutions and affiliatedindustry infrastructure have beenchallenged to respond and serve a growingnumber of patients in need of testing andtreatment. With the number of patients growingexponentially over time, COVID-19 continuesto have far-reaching negative impacts onboth public health and the economy. Despite this, there has been lack of datatransparency pertaining tounderrepresented minorities and vulnerablepopulations who may be disproportionatelyaffected by both the the illness as well asthe economic fall-out. This report wascreated to explore data characteristics ofunderrepresented minorities who presentedwith possible COVID-19 symptoms. Webelieve this is a crucial first step in creatingequitable access to testing and acceleratinga vaccine that can lead to better outcomesfor all affected.

" W e o n l y h a v e o n e m i s s i o n :P a t i e n t I n n o v a t i o n F i r s t .

A l w a y s "

FROM THECEO'S DESK

R U B I X L I F E S C I E N C E S P A G E 1

REGINALD SWIFT

Founder & CEO

It is with the momentum of Rubix LS thatwe continue development efforts towardscientific advances that will directly driveimprovement for minority health andaccess to effective therapies that are socritically needed.

"COVID-19 & Minority Health Access"

MassachusettsConnecticutNew YorkNew JerseyMarylandVirginiaFlorida

Rubix LS has leveraged intelligent data networks thatdrives StarSense as well as incorporating its own datamachination from pulling data on Rubix’s ownsystem.  With the cooperation of 103 groups of healthcareinstitutions– Rubix LS has deployed a basicalgorithmic log application in which patients haveconsented for in the following states:

1.2.3.4.5.6.7.

Black/African Americans     Native AmericansHispanic Americans   Other (Asian, Pacific Islander, patients who self-identify as ‘other’)

Underrepresented groups, as defined inthis data characterization, involves thefollowing groups:

The scope of this data insight is tohighlight patients that were flagged tohave confirmatory testing done whilecapturing the billing of patients byproviders. This data set does not capturewhether patients were confirmed to haveCOVID-19.

R U B I X L I F E S C I E N C E S P A G E 2

BACKGROUND& METHODS

Health authorities in the United States arequickly responding to an outbreak of thenovel coronavirus that was initially detectedin China and subsequently detectedinternationally, including the United States.With this emerging threat, the outbreak nowknown as COVID-19 continues to stress thehealthcare industry as well as patients thatreport symptoms. It also potentially exposesweakness in the United States’ healthcaresystem—all patients may not gain quick orequitable access to care.

As the number of infected patientsincreases drastically, patient identificationand access to testing options isparamount. Unfair rationing within distinctneighborhoods may be directly relevant topatient access to professional care duringthis time. With the current numbersgreater than 370,000 (100,000 at time ofdata capture -03/20/20) confirmed casesin the US, COVID-19 has become thefastest-growing pandemic within thecountry since the Spanish Influenza of 1918.

"COVID-19 & Minority Health Access"

We designed a 41 day data collection sprint (February 9, 2020- March 20, 2020) whichincluded the aforementioned seven states. Of the total data we collected we focused on asample of 67,610 patients who screened positive for one or more symptoms related toCOVID-19. Patients who did not undergo a billable encounter (or received an assessmentbut no in-network provider billing claim was submitted) were classified as “unassessed”. Ifthe patient had a billable encounter with a healthcare provider, we paired Rubix LSStarSense® data with corresponding hospital validated ICD-10-CM codes. Cases thatgenerated a billable provider encounter were further characterized by race and ethnicity.Non-response bias may have contributed to low response rate amongst self-reported“White or Caucasian” patients.

R U B I X L I F E S C I E N C E S P A G E 3

"COVID-19 & Minority Health Access"

Black/African-American:21,034

Hispanic-American: 11,253Native-American: 4,380Causcasian/White: 1,796

Other: 1,803

Black/African-American:6,538

Hispanic: 3,023Native-American: 1175

Caucasian/White: 1,297Other: 889

R U B I X L I F E S C I E N C E S P A G E 4

"COVID-19 & Minority Health Access"

We were able to match 27,344 symptomatic patients with their final diagnosis using billing(claims) codes. Variation in final diagnosis is noted below. Individual testing, treatmentand mortality data were not readily available for this cohort at the time of the report.

DATA

R U B I X L I F E S C I E N C E S P A G E 5

"COVID-19 & Minority Health Access"

DATAWe estimated income of our cohort using intelligent data based on patient’s reportedzip code, Rubix LS’s StarSense® track-in-motion, and neighborhood housing values.

R U B I X L I F E S C I E N C E S P A G E 6

"COVID-19 & Minority Health Access"

INSIGHT

Launched as a pilot project, the data aggregated demonstrates further opportunity forcomprehensive and automated national data collection. This could provide clarity on thestate of health care access and how health providers, sponsors, industry and federalagencies can collaborate to create data driven solutions for health equity.

Our data of over 27,000 patients illustrates that African-Americans and Hispanics with anestimated household income of under $50,000 per year. If COVID-19 disproportionatelyaffects underrepresented minorities, particularly those with lower socioeconomic status, thiscould potentially contribute to increased COVID-19 transmission and economic damage inalready vulnerable communities. Further research needs to be done in this area.

Additionally, Rubix LS has taken initial steps to design data collection programstargeting potential discrepancies of what local, state, and national organizations reportversus data that has the potential to be comprehensive and more accurately reportedthrough an interconnected platform of sensors, applications, and algorithms in whichraw data is supplied daily. We looked at publicly available data for confirmed COVID-19cases during the same time period as our data sprint (February 9, 2020 through March20,2020).

Historically, both healthcare provider bias and structural inequities have amplifiedhealth disparities in minority communities. The need for vigilant policy and practicestargeted toward already vulnerable groups is paramount. As healthcare systemsbecome more strained and public anxiety rises, a coordinated network of industry,academia, federal agencies, and non-profits need to drive collaboration toexpeditiously address potential health inequities during the COVID-19 crisis.

Despite the small number of total hospital groups (103) in our pilot study, the totalnumber of patients exhibiting COVID-19 symptoms greatly exceeded publicly reportedcases in each state. This can be attributed to a number of possible factors includingbut not limited to testing availability, subjectivity of testing criteria, inequities in testingand treatment, and variability in presentation of COVID-19 symptoms. Currently, thereis limited information available regarding COVID-19 symptom tracking using local andstate information. Using an automated network of data tracking may more accuratelyaccount for the both tested and untested cases of COVID-19 both in the USA andglobally.

R U B I X L I F E S C I E N C E S P A G E 7

"COVID-19 & Minority Health Access"

Data as of 03/20/2020

COVID-19 7-state Symptomatic Cases