As we, the healthcare community, all watch – and experience – the evolving situation of the coronavirus pandemic, we’ve been introduced to Dr. Deborah Birx, a recognized expert and leader in HIV/AIDS immunology, vaccine research and global health. Today, she has become a rising leader in the fight against the coronavirus pandemic. If Dr. Birx has taught us anything in this fight, it is that data is king and that informed decisions are always better decisions.
In the battle against coronavirus, Dr. Birx and her team of data analysts examine who has the virus, where they reside, how many are hospitalized and who appears to be the most vulnerable to this disease. All of these data points help inform critical decisions around how to mitigate the spread of the virus, how to treat those severely impacted by it and even how to anticipate where critical (but limited) resources such as ventilators, personal protective equipment (PPE), hospital beds and healthcare providers will be needed next.
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George Gray Bio: George Gray, CTO and VP of research & development at Ivenix, has more than three decades of healthcare experience in clinical information systems, clinical analytics and patient monitoring. Prior to joining Ivenix, George was a senior architect at Philips Healthcare for both the Intellivue Clinical Information Portfolio and Intellivue Information Center. He […]
Though playing out in a way that is almost bigger than life, the use of data to drive clinical decisions is an important part of healthcare in this country. Unfortunately, just as Dr. Birx struggles to get all the data she needs to inform the daily decisions of the coronavirus task force, many healthcare institutions struggle with a lack of timely data that could lead to insights, such as how to improve their own delivery of care. And though most document an enormous amount of information, much of this information is hard to access in the aggregate, retrospectively and when not involved in the direct care of the patient.
With the Covid-19 battle as a backdrop, many are recognizing the need for vendors of medical systems and medical devices to step up their efforts in their ability to collect and make available data that can be used to inform retrospective clinical decisions. This starts with collecting the right data, but also requires open access to that data, normalizing the data into a standardized form that can be consumed by other systems and/or stakeholders and finally rapidly transforming data in a form that is representative, meaningful and can be used to help drive decision making.
Collecting the Right Data
In the heat of battle, assessing the effectiveness of new COVID-19 treatments can be difficult and time-consuming. Though responses to the treatment can vary based on the patients’ preexisting conditions, it could also vary in the way the therapy is delivered. For example, in the evaluation of infused medications, knowing the specifics of how infused medications are delivered might provide insights not considered by many clinicians today.
Unfortunately, much of this data is not available because most infusions systems are not collecting it. Though clinicians record doses and total volumes, the intricate details of how the infusion was delivered is typically lost. And it is easy to not notice the fact that much of the infused medication remained trapped in the tubing after the infusion ends. Simple data points like when an infusion is started and/or ended are often overlooked, not to mention understanding when an infusion is paused, ramped up, or titrated down. The physiologic effect of increasing or decreasing the infusion rate for some high-risk medications can easily go unnoticed because this information is simply not available to those who would want to study it in retrospect. Similar examples exist throughout healthcare, creating oversights around things that aren’t considered in medical studies because the data is lost from view. Better data and granularity of data from medical devices is important in bringing these insights into view.
A Deep-dive Into Specialty Pharma
A specialty drug is a class of prescription medications used to treat complex, chronic or rare medical conditions. Although this classification was originally intended to define the treatment of rare, also termed “orphan” diseases, affecting fewer than 200,000 people in the US, more recently, specialty drugs have emerged as the cornerstone of treatment for chronic and complex diseases such as cancer, autoimmune conditions, diabetes, hepatitis C, and HIV/AIDS.
Providing Open Access to Data
The vast amount of data collected today in patient records is extremely valuable, however, for most healthcare institutions, the cost of accessing this information often makes it impractical. It’s like sitting on a gold mine but not having the means to start digging.
In general, access to this data has been an afterthought to most electronic medical record (EMR) systems, which focused primarily on providing a legal record of care rather than a repository of medical knowledge. Though many claim it is possible, gaining access usually comes with a price tag that is too high for most healthcare institutions. This needs to change as these health systems evolve. Medical device vendors need to provide open access to their data in support of care improvement initiatives and evaluations of new treatments in this rapidly changing world.
Normalizing Data into a Standard Format
Even once data is made available, it is often in a proprietary form, making it hard to share with other medical systems or with national or international databases. Data cleanup and post-processing is typical when using data across different applications. However, a lack of data standards across medical systems makes the challenge of creating across-hospital datasets that much more difficult.
Most makers of medical systems seem disinterested in the standardization of medical data. Instead, they are focused on locking out their competition and encouraging health systems to align on a single solution. But this only exasperates the problem of trying to aggregate data across all health systems, as is being done in the battle against Covid-19. Despite the sophistication of EMRs in many U.S. hospitals, most find it easier to use manual means to collect and share data with national databases. The standardization of data can change all this and allow hospitals to participate in a national discussion around improving the effectiveness of care and responding to aggressive diseases such as Covid-19.
Providing Timely and Meaningful Access to Data
Making meaningful data available to decision-makers in a timely manner is always a significant challenge when looking at data in the aggregate. Often times, it is unclear what data is needed or what pieces of data or relationships between pieces of data are relevant until you are well into the process of collection. In more complex situations, Artificial Intelligence (AI) becomes an important technology for harvesting insights from data but requires a significant investment in time and money.
Even when insights can be gained through simple reporting, the work required to get there can be overwhelming to most institutions. Getting there involves first coming up with an approach to handling wrong, missing or inconsistent data. These things tend to exist because of the way the information is collected. Consequently, resolving these issues often involves making a change to the medical system used to collect this data. Unfortunately, because many of these systems were not designed to support retrospective analysis of their data, this process is not always easy.
Once data has been adequately cleaned up, the institution needs to define how the data will be used to drive decision making, how current it needs to be and what actions it is expected to provoke with the target user(s). This will eventually lead to picking the tools and/or reports that will be required and how the aggregated data will be presented to the user. Fortunately, there are numerous tools with various levels of sophistication that can support hospitals in the effort.
Supporting Clinical Teams & Saving Lives Depends on Access to Data
If the battle against aggressive diseases, such as Covid-19, remain in our future, our ability to access and make sense of medical information quickly is imperative. Lives and, as we now know, economies literally depend upon it. It’s no longer good enough to just document care.
We need to support clinical teams with the information they need to improve the effectiveness of their care and, of course, help respond to these silent killers. The information can no longer be restricted to what clinicians see in the patient’s record. It must also include what can be seen in the aggregate. With this knowledge, clinicians are able to make better, more informed decisions. Armed with usable data, clinicians may be able to better anticipate what lies ahead for themselves and their patients in a world that continues to feel smaller and move faster.
Photo: shylendrahoode, Getty Images
Bio: George Gray, CTO and VP of research & development at Ivenix, has more than three decades of healthcare experience in clinical information systems, clinical analytics and patient monitoring.
Prior to joining Ivenix, George was a senior architect at Philips Healthcare for both the Intellivue Clinical Information Portfolio and Intellivue Information Center. He also founded Envision Solutions Inc., a provider of clinical analytics and data integration solutions. Previous to this, George was the engineering manager for Hewlett Packard’s Systems Integration Organization and held various engineering leadership positions in the development of HP CareVue 9000 Clinical Information System.
