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“The” international event in Healthcare Social Media, Mobile Apps, & Web 2.0
2015-06-04 - 2015-06-05    
All Day
What is Doctors 2.0™ & You? The fifth edition of the must-attend annual healthcare social media conference will take place in Paris;  it is the [...]
5th International Conference and Exhibition on Occupational Health & Safety
2015-06-06 - 2015-07-07    
All Day
Occupational Health 2016 welcomes attendees, presenters, and exhibitors from all over the world to Toronto, Canada. We are delighted to invite you all to attend [...]
National Healthcare Innovation Summit 2015
2015-06-15 - 2015-06-17    
All Day
The Leading Forum on Fast-Tracking Transformation to Achieve the Triple Aim Innovative leaders from across the health sector shared proven and real-world approaches, first-hand experiences [...]
Health IT Summit in Washington, DC
2015-06-16 - 2015-06-17    
All Day
The 2014 iHT2 Health IT Summit in Washington DC will bring together over 200 C-level, physician, practice management and IT decision-makers from North America's leading provider organizations and [...]
Events on 2015-06-15
Events on 2015-06-16
Health IT Summit in Washington, DC
16 Jun 15
Washington DC
Articles

Clinical trials can be expedited in part by: With electronic medical records, jump straight to the data

It has been projected that the amount of published scientific publications doubles every 17.3 years. But before basic lab studies on cell cultures and animals become clinical trials involving humans, it takes an average of 17 years for health and medical research to lead to real changes that patients observe in the clinic.

Medical research processes as they normally operate are typically ill-prepared to deal with rapidly changing pandemics. This has been particularly clear in the case of the COVID-19 pandemic, partly due to the virus’s frequent mutations. It is frequently left to scientists and public health officials to constantly juggle the development and testing of novel medicines to keep up with evolving varieties.

Thankfully, by utilizing a shared source of existing data, electronic medical records, or EMRs, scientists may be able to circumvent the traditional research timetable and investigate therapies and interventions as they are utilized in the clinic almost in real time.

Our team consists of a cardiologist from the University of Pittsburgh Medical Center, a pharmacist, and an epidemiology. We became aware of the urgency of promptly researching and sharing precise information on the best treatment modalities during the COVID-19 epidemic, particularly for patients who were at a high risk of hospitalization and death. Using electronic medical records (EMR) data, our newly published study demonstrated that early therapy with one or more of five distinct monoclonal antibodies significantly decreased the chance of hospitalization or mortality when compared with delayed or no treatment.

Conducting research with EMR data

EMR systems are commonly used by U.S. health care institutions for billing and administrative functions such as patient care documentation. These systems generally hold comprehensive records that can include sociodemographic data, medical history, test results, surgery and other operations, prescriptions, and billing expenses, even though data gathering is not consistent.

Many sizable health care systems in the United States gather patient data utilizing several EMR systems, in contrast to single-payer health care systems that integrate data into a single EMR system, such those in the United Kingdom and Scandinavian nations.

Using such data for scientific inquiry is made more challenging by the existence of multiple EMR systems. In response, the 40 hospitals and outpatient clinics of the University of Pittsburgh Medical Center utilize seven distinct EMR systems. To address this, the medical center created and manages a clinical data warehouse that gathers and unifies data from these systems.

Simulating medical procedures

Researching using EMR data is not a novel idea. Recently, scientists have begun investigating how to simulate randomized controlled trials—which are seen to be the gold standard study design but are sometimes expensive and take years to finish—using these massive health data platforms.

Our team evaluated five distinct monoclonal antibodies for which the Food and Drug Administration has granted emergency use authorization to treat COVID-19 using this emulation approach and our institution’s EMR data infrastructure. Human-made proteins known as monoclonal antibodies are intended to stop a pathogen—in this case, the COVID-19 virus—from penetrating human cells, proliferating, and posing a major threat to health. Clinical trial data served as the foundation for the initial authorizations. However, when the virus changed, further assessments based on cell

Our goal was to verify that the results of research conducted on cells could be applied to real patients. In order to match the anonymous clinical data from 2,571 patients treated with these monoclonal antibodies within two days of contracting COVID-19 with the data from 5,135 COVID-19 patients who were eligible for treatment but either did not receive it or received it three days or more after infection, we evaluated the data.

Those who received monoclonal antibodies within two days of a positive COVID-19 test, on average, had a 39% lower chance of dying or being admitted to the hospital than those who did not receive the medication or who received it later. Furthermore, regardless of age, patients with weakened immune systems had a 55% lower chance of dying or being admitted to the hospital.

The results of the cell culture investigations were validated by our near-real-time monitoring of COVID-19 patients receiving monoclonal antibodies during the pandemic. According to our findings, researchers may be able to assess therapies quickly and without the need for clinical trials by utilizing data in this manner.

Appropriate usage of EMR data

Researchers can use the EMR systems found in many healthcare facilities to quickly address significant research topics as they come up. However, since this clinical data isn’t being gathered especially for studies, researchers must carefully plan their investigations and employ rigorous data validation and analysis. Additionally, they must exercise extreme caution when choosing suitable patient samples, harmonizing data from various EMR systems, and minimizing any potential sources of bias.

Significant public health issues and new pandemics are likely to appear suddenly and in unexpected ways. We think that judicious use of these data can assist address pressing health concerns in ways that are indicative of who is actually receiving care, given the wealth of information routinely gathered throughout U.S. health care systems.