The past two years have been fraught with difficulties for the healthcare industry. Labor shortages have negatively impacted hospitals and health systems nationwide, intensifying the burden on healthcare workers already strained. In fact, the latest job report from the U.S. Bureau of Labor Statistics has shown healthcare employment down by nearly half a million since February 2020.
While a lack of sufficient staff has obvious implications on providing patient care, the labor shortage has revealed another consequence much less discussed: a lack of healthcare professionals to capture and interpret clinical data that leads to medical research, the development of new treatments, and improvement in patient care.
The Need for High-Quality, Clinical Data
Real-world data, or data extracted from sources such as patient medical records or health information, has been widely recognized by the FDA as paramount to the development of medical innovations and advancements. Scott Gottlieb, a former commissioner of the FDA, identified the leveraging of real-world data as a “key strategic priority for the FDA” in 2018. Just recently, the FDA approved an immunosuppressant to help prevent organ rejection in patients receiving lung transplants based on patient data collected by the U.S. Scientific Registry of Transplant Recipients, as well as the Social Security Administration’s Death Master File. In this instance, real-world data played an integral role in regulatory decision-making, potentially affecting the lives of millions.
The pandemic has only accelerated the use of real-world data. During a time of rapid escalation, electronic health records and clinical data have been pivotal in decision-making. For example, the CDC has been using real-world evidence from Israel to make decisions on boosters based on evidence of fading vaccine immunity over time.
This has set a precedent for the role of real-world data in the advancement of medicine moving forward, and one of the most viable sources of real-world data are clinical data registries. The FDA has acknowledged that information available through registries has the potential to support medical product development and offer an advantage over other data sources because of the insights that can be gathered on a defined patient population and disease history, complications, and medical care. Yet, for registry data to be useful for real-world data applications, it must be recent and of the highest quality, which hinges on hospitals’ capture and submission processes.
The Clinical Data Supply Chain Issues
Though these examples highlight the tremendous value of tapping into clinical data, the challenge for hospitals and health systems is the need to capture and analyze this data in a timely manner. Data becomes stale quickly the farther it’s removed from the moment of care, rendering it mostly irrelevant for the development of new treatment modalities and drugs.
While the demand for clinical data only continues to increase, hospitals and health systems are unable to keep up. A scarcity of professionals to capture and interpret this data has resulted in a massive backlog of untapped information. Over time, these backlogs not only compound to millions of dollars worth of labor to catch up on but have a direct impact on the quality of patient care as well. However, if promptly captured, the details found from data embedded within a lab test or in a physician’s notes can be transformed into valuable knowledge.
How Hospitals and Health Systems Can Improve Clinical Data Capture
A fundamental aspect in understanding how hospitals and health systems can better unlock the value inherent in clinical data lies in the distinction between unstructured and structured data. Structured data typically encompasses obvious numerical or categorical values, such as a patient’s sex, age, or blood type. Unstructured data, however, including imaging studies or doctor’s notes, must be clinically interpreted and structured to be of meaningful use.
Currently, hospitals mostly use structured data for (and from) medical claims, capturing some but not nearly all clinical data elements for billing purposes. This data often fails to be comprehensive enough to provide a full picture of a patient’s rich clinical history. As a result, a wealth of information remains undetected, with hospitals and health systems struggling to amass the necessary professional resources to ameliorate the issue.
By adopting and investing in modern data infrastructure, hospitals can begin unlocking the value of clinical data to make impactful changes for the healthcare industry. This requires a combination of clinical experts and modern technology to enable the extraction, curation, management, and analysis of high-fidelity clinical data across healthcare systems and within key clinical segments like oncology, cardiology, surgical, and others.
Enterprise solutions utilized and governed across all departments will prove essential to ensure clinical data isn’t siloed, but rather shared to enhance data accuracy and utility. Clinical experts who have the expertise will always be necessary to sort through unstructured data and properly curate it to be as impactful as possible, but the implementation of technology and robust processes to augment this process will help hospitals and health systems streamline and optimize clinical data capture and utilization across their organization. By combining people, processes, and technology, the potential of unstructured data can be fully realized, allowing for results that will not only fuel medical innovations for the future but ultimately bring data closer to actual patient interactions. As a result, hospitals will transform—from patient care facilities to information technology companies—with higher productivity, innovation, and quality care.
The Future of Healthcare is in Clinical Data
With healthcare data comprising one-third of all new data in the world, hospitals and health systems must begin to prioritize investing in a modern clinical data infrastructure, not only to improve the patient outcomes at their facility but to contribute to the improvement of care and patient outcomes globally. Recent delays in treatments and screenings are sure to increase chronic disease incidence in the near future, only amplifying the need for efficient clinical data management. While the breadth of information obtainable through abstracted clinical data is difficult to quantify exactly, it promises limitless opportunities to enhance the healthcare system as we know it. As an observer, a participant, and a consumer in this healthcare industry, I am hopeful that the sooner we take full advantage of the powerful insights available through clinical data, the more capable we will be to drive meaningful clinical innovations from it.
About Raghu Bukkapatnam
Raghu oversees the company’s commercialization efforts including sales, marketing, professional services and customer experience. Immediately prior to joining Q-Centrix, Bukkapatnam led enterprise strategy and growth initiatives at Change Healthcare, including the development of its $1 billion Technology Enabled Services business unit. Prior to that, he served four years as a Senior Director at the Advisory Board, where he played a key role in launching consulting and technology products for revenue cycle and physician practice management.
He started his career as a Fellow in the medical errors taskforce at the Lister Hill Center for Health Policy within the Agency for Healthcare Research and Quality. Bukkapatnam received master’s degrees in public health and business administration from the University of Alabama-Birmingham and a bachelor’s degree from Washington University in St. Louis
