We are motivated to assist in this national emergency by leveraging our expertise, experience, clinical data assets and technology platform for the common good.

What it does

We propose to use clinical data to better understand the variables that can predict morbidity, mortality and resource utilization outcomes in hospitalized COVID-19 patients. These data could assist providers in responding to the needs of individual patients and public health officials responding at the population level.

Why it will work

Medisolv has been in the quality reporting space for 20 years. We are industry leaders and we know the methodologies in current use by healthcare entities nationwide. Furthermore, we know what won't work. Asking clinicians to capture more information - disrupting their already established documentation processes - will lead to incomplete and inaccurate information. With ROARS, data is pulled from clinical information that is readily available without requiring additional documentation by front-line workers.

ROARS gathers clinical information already being captured in a hospital’s EHR such as patient demographics, vital signs, lab results, comorbidities, length of stay and medications and uses predictive analytics and modeling to identify patterns leading to specific COVID-19 outcomes.

The data is already there. By leveraging Medisolv's existing quality reporting platform, hospitals can easily submit the data their providers are already capturing to external entities such as the CDC and other healthcare agencies.

How we propose to build it

Most of this will be built with data from our existing data analytics platform containing clinical, financial and operational data. This makes ROARS ready for rapid production. Our data science team is very skilled at creating predictive models using these data sets and advanced ML/AI techniques. These models could have generalized applicability. Hospitals and providers will also have the ability to electronically submit case reports to their health agency using our existing technology platform used by more than six hundred health systems to submit patient level clinical and demographic data to external entities including the CDC and other healthcare agencies for quality reporting.

Challenges we may run into

We expect potential data quality issues with coding COVID-19 cases as codes and coding guidelines are just being developed with most coders having limited experience.

Accomplishments we want to be proud of

We hope this will enhance the ability of front-line clinicians to improve outcomes of COVID-19 patients and fulfill their public health reporting obligations without additional burden.

What we hope to learn

We are confident much will be learned during this process and will be useful both to the medical and public health communities.



ai, azure, exisiting, machine-learning, microsoft, technology

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