With the broadening availability of COVID-19 vaccines, it seems the US is finally beginning to see the light at the end of the pandemic-enveloped tunnel. After more than a year of uncertainty and unease, the vaccines represent the...“Being a very large healthcare organization, we had about 30,000 employees that needed to be vaccinated first. So, we had a little bit of lead time between when the vaccines were approved and when we were able to start vaccinating...
For organizations seeking to improve their population health management capabilities, big data is a critical part of the journey. Gathering information from different sources – such as claims, medical records, and lab systems –...“We have been on a population health journey for about four years,” Robert Millette, executive director of population health at Lee Health, told HealthITAnalytics. “Our goal is to be a clinically integrated network across...
In healthcare, predictive analytics tools have always been one of the most promising applications of big data. The ability to anticipate negative consequences before they occur is a major asset for any organization looking to improve...“We’ve used this tool because biologically, it’s also accurate in identifying patients who have a high risk of developing hyper inflammatory syndrome from the virus,” Brandon Webb, MD, an infectious diseases...These tools have also helped Intermountain identify and address health disparities. The models have incited the health system to develop strategies related to outreach, testing, and treatment as the pandemic has worn on. “When the...
Since the onset of the COVID-19 pandemic, leaders have developed and deployed health data collection technologies to track virus exposure, monitor outbreaks, and aggregate hospital data. As communities begin to navigate vaccine rollouts,...In order to better understand the intersection of governance and surveillance technology in the context of public health emergencies, the Social Science Research Council convened a cross-disciplinary, multinational group of experts in the...
At first glance, mining clinical data to extract meaningful insights seems like a task well-suited for machine learning algorithms. The principal aim of advanced analytics tools is to evaluate multiple sources of information and discover...“TL-Lite is a visualization tool designed to bring healthcare experts closer to machine learning,” said Jeremy Weiss, assistant professor of health informatics at CMU’s Heinz College. “The current paradigm for using...
Among the many gaps in care that pervade the medical industry, rural health disparities are some of the most prevalent. For individuals living in rural parts of the country, geographic isolation, limited access to healthcare, and higher...Now, a new initiative is seeking to collect big data on individuals in rural areas to understand and alleviate these health disparities. The Risk Underlying Rural Areas Longitudinal (RURAL) cohort study is working to address critical gaps...
The emergence of next-generation sequencing technology has led to widespread genomic testing and the availability of genomic data, providing a way for clinicians and patients to better understand disease risk and health outcomes. However,...“Genomics is moving rapidly and the technology is changing quickly, so agility is very important. We decided we needed to build a solution internally to have competency in this area,” Kamalakar Gulukota, PhD, Director of the...
Of the many truths brought to light during the pandemic, the importance of providers’ voices is among the most consequential. The experiences and daily operations of frontline healthcare workers can inform the development of helpful,...Using data from emergency department patients, including demographics, labs, and vitals, researchers designed an algorithm that can predict whether patients have a high risk of respiratory failure within 48 hours. “Since the start of...
In hopsitals and emergency departments, it’s essential for providers to continually monitor patients in order to stay ahead of potential adverse events. However, patient deterioration can be very difficult to anticipate,...The noninvasive clinical tool established an automated way of monitoring patients for hemodynamic instability, one of the most common causes of death for critically ill or injured patients. “Hemodynamic instability can happen...
Throughout the era of COVID-19, it’s become apparent that the only constant is change. The crisis continues to rapidly evolve, with updated guidelines and fluctuating case numbers, highlighting the need for up-to-date, real-time...Providence cares for thousands of patients each day, enabling the health system to capture a large volume of information about the illnesses patients are experiencing. This was especially helpful when it came to developing the DetectionMap,...
Medical imaging data has always played a critical role in healthcare delivery, allowing researchers and providers to collect meaningful information for better decision-making. Since the dawn of COVID-19, medical imaging data has become even...“It's considered good clinical practice to try to obtain any old exams on a patient when you're treating them and they were not imaged in your institution. If you can gain access, that’s a good thing.” But...With the release of the Carequality Imaging Data Exchange Implementation Guide, effective December 2019, both RSNA and Carequality aim to enhance the use of imaging in treating patients with COVID-19. “With the implementation guide,...
Throughout the COVID-19 pandemic, predictive analytics have helped healthcare organizations plan for surges in patients, allocate necessary resources, and anticipate which populations would be at greatest risk for poor outcomes from the...
Current care delivery is, for the most part, conducted on an episodic basis. Patients generally see their doctors when they don’t feel well, limiting clinicians’ ability to provide holistic, comprehensive care....
In care delivery today, it’s well understood that a patient’s social determinants of health have a profound impact on both physical well-being and healthcare spending – sometimes even more so than clinical factors....While better than nothing, this method was not exactly effective, Reider said. There was no way for providers to tell whether a person actually received the services that were recommended to them. Clinicians also had no way of knowing if...
While cancer obviously takes a momentous physical toll on the body, the disease can have dire effects on a person’s mental health as well – a trend that has only grown more common with the spread of COVID-19. A recent survey...In order to better understand which patients were at risk and why, the organization worked with Cardinal Health to leverage a clinical artificial intelligence solution from Jvion that examines individuals’ clinical and...
While the healthcare industry has made significant strides in leveraging data and technology to treat cancer, gaps in treatments and outcomes continue to persist. Cancer care disparities still pervade the oncology sector, showing that...“The hope is that the ERACE Initiative is part of a larger range of activities to try and combat disparities not just in cancer, but in other diseases as well,” added Warner, who will serve as an ERACE leadership advisory board...
While the dawn of the EHR promised streamlined, accelerated healthcare delivery, the technology can also include burdensome alerts and documentation requirements that lead to clinician burnout. Providers often spend more time documenting...To improve both the patient and provider experience, Providence recently partnered with Nuance Communications to leverage an artificial intelligence platform that uses ambient sensing technology to securely and privately listen to...
When COVID-19 began spreading across the US, the healthcare industry quickly moved to improve its secure data sharing practices in order to accelerate research efforts and treatment development. For more coronavirus updates, visit...The N3C is a partnership among the National Center for Data to Health (CD2H) and National Center for Advancing Translational Sciences (NCATS)-supported Clinical and Translational Science Awards (CTSA) Program hubs, with stewardship by...
While the promises of precision medicine in healthcare are seemingly boundless, the industry has had to overcome several challenges to integrating these approaches with everyday clinical care. From seamlessly incorporating genomic and...“For example, it might make sense to use precision medicine approaches when selecting antidepressant medication. But it may not make sense for other treatments and diagnoses. You have to know some of those things so that you can work...
In order to provide holistic, quality care for patients, clinicians have to address the non-clinical factors that influence overall wellness – individuals’ social determinants of health. While it is widely understood that these...To help providers identify primary care patients with social risks, researchers at Regenstrief Institute and Indiana University turned to machine learning technology. The team developed Uppstroms, a machine learning application that...
