Here are four ways providers are using clinical surveillance and decision support technology to ensure early intervention and proper treatment in cases of COVID-19
Throughout the pandemic and into the reopening and recovery stage, patient, clinician and staff safety continues to be a top priority. Healthcare providers are relying on technology solutions to track COVID-19 cases across the continuum and help guide the appropriate clinical response more than ever.
Sophisticated clinical surveillance and decision support technologies are helping clinicians identify cases of COVID-19 when symptoms first appear as well as patients’ associated risk for severe complications. These technologies automate alerts and offer up the latest, evidence-based guidance, and can even indicate potential deterioration before the clinical signs are visible – an early warning system that gives clinicians an advantage as they initiate life-saving care.
Here are four ways leading providers are using clinical surveillance and decision support technology to ensure early intervention and proper treatment in cases of COVID-19.
1. To monitor for warning signs in certain systems, thereby predicting future cases.
Clinical decision support that uses natural language processing and machine learning is flagging suspected or confirmed COVID-19 patient cases for providers directly in the electronic health record (EHR), regardless of site of care. This technology extends beyond the functions of current EHR systems by reading free text, including clinical symptoms such as “fever” or “shortness of breath” recorded within physicians’ notes. Clinical decision support that aggregates multiple symptoms indicative of COVID-19 can predict its surge in a specific locality, enabling providers and public health officials to forecast disease progression.
2. To monitor all COVID-19 suspected or positive cases and isolate them appropriately
In an outbreak environment, research shows that 80 percent of hospital epidemiologists’ time is spent on preparation1, as opposed to performing normal surveillance and prevention activities. During the COVID-19 pandemic, real-time, actionable data has become paramount. In a clinical setting, COVID-19 content offered at the point of care allows providers to initiate the right treatment for the right patient at the right time. Alerts for suspected or positive cases enables infection preventionists to ensure cases are isolated appropriately and prevent the spread. Infection preventionists should utilize surveillance technology that includes COVID-19-specific alerts and patient flags for tracking and analytics.
3. To alert clinicians of the most up-to-date clinical guidance in the EHR
As nurses and physicians maximize their time in patient care during a pandemic, they also want to be sure they are incorporating the most recent evidence regarding clinical findings from the Centers for Disease Control and Prevention (CDC) and other agencies into their treatment protocols – which can be tricky, as guidance continually evolves during the outbreak. To overcome this, providers are using clinical decision support that presents the latest and most relevant recommendation in the clinicians’ EHR workflow to guide appropriate care
4. To use patterns in the data to proactively respond to elevated health risks and avoid unnecessary therapy
Predictive analytics monitoring tools are allowing providers to track patients’ clinical patterns specific to COVID-19 and foresee conditions that could require invasive respiratory support up to eight hours before the clinical signs appear.2
Approximately 45 percent of hospitalized COVID-19 patients receive invasive ventilation, and research shows that COVID-19 has an 81 percent mortality rate among patients who receive mechanical ventilation.3,4 However, when predictive technology presents early warnings, clinicians are equipped to respond to an elevated risk score and can intervene to prevent emergent intubation and associated mortality.
Research also demonstrates that critically ill COVID-19 patients often develop septic shock, which may require intubation and invasive ventilation. As an aerosol-generating procedure, intubation can present a high risk of virus transmission for the clinicians.5 Predictive intelligence is further enabling clinicians to anticipate an associated septic shock diagnosis in time to change the course of care for patients.
Learn more about Premier’s COVID-19 resources and tools that enable providers with the intelligence, insights and supplies they need to care for their healthcare workers and community members during COVID-19 and beyond.
1Morgan DJ, Braun B, Milstone AM, et al. Lessons Learned From Hospital Ebola Preparation. Infection Control & Hospital Epidemiology. 2015;36(6):627-631. doi:10.1017/ice.2015.61
2University of Virginia at Arlington retrospective CoMET® technology walkthrough of patient bed 97 February 5, 2018 (slide 115).
3 Yang X, Yu Y, Xu J, et al; Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: A single-centered, retrospective, observational study. Lancet Respir Med 2020 Accessed: April 3, 2020 Available at: https://www.thelancet.com/action/showPdf?pii=S2213-2600%2820%2930079-5
4Wang D, Hu B, Hu C, et al; Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus–infected pneumonia in Wuan, China. JAMA 2020. Accessed: April 3, 2020. Available at: https://www.ncbi.nlm.nih.gov/pubmed/32031570
5Tran K, Cimon K, Severn M, et al. Aerosol generating procedures and risk of transmission of acute respiratory infections to healthcare workers: a systematic review. PLoS One. 2012;7(4):e35797. Accessed April 3, 2020. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3338532/pdf/pone.0035797.pdf