The fight against a deadly pandemic requires a wide range of resources, including different forms of data. As researchers, epidemiologists and front-line medical providers have tried to contain the spread of COVID-19, they’ve encountered the need for more robust, advanced data gathering tools than ever before.
For example, the Brookings Institution (Brookings) notes that suppressing the pandemic will require information above and beyond what’s found in a simple electronic health record (EHR). Researchers also require sophisticated insights into how the disease spreads, which populations are most at risk and which treatments are most effective. Brookings reports that nations like Taiwan have compiled large volumes of travel and tourism data; just one example of the extraordinary efforts required to better understand the virus’s trajectory.
Countless tools—from medical records to patient surveys, to health apps and beyond—are available to health informatics professionals who are collecting and assessing disease data. But these tools in and of themselves are insufficient for promoting population health. To be effective, they must be leveraged strategically by trained health informatics specialists.
What Types of Data are Available During a Public Health Crisis?
During a pandemic, health informatics professionals have at their disposal many types of data they can mine for actionable insights and noteworthy trends.
One key source of data is administrative data. Healthcare organizations inevitably generate copious amounts of data that reflect the realities of the populations they serve. Some examples include data about insurance claims, enrollment and encounters between providers and patients. During a pandemic, these sources can help identify populations in which the disease is spreading quickest.
Clinical data sources are also important, such as patient records. These can provide useful insights into risk factors that contribute to the disease and pre-existing health conditions that make recovery more or less likely.
Types of Disease Data
Not only do health informatics professionals have access to different sources of disease data, they also collect different types of data. A few common examples include the following.
- City and county data: Pandemic trends charted by city or county health departments can provide insight into the virus’s geographic reach.
- Lab data: Data produced by labs can help health informatics professionals in monitoring positive testing rates and mitigating medical or demographic factors.
- Population mobility: Understanding the spread of a disease requires tracking a population’s movements across state or national lines.
- Predictive modeling: Health informatics professionals can use statistical modeling to make predictions about how the pandemic will spread based on currently available information.
Health Issue Data
Finally, data collection may also examine a number of health issues that relate to the pandemic. For example, data collection can inform professionals about the progression of a chronic illness; or, in the case of something like COVID-19, yield some insight into how the virus interacts with chronic diseases. Additionally, health informatics professionals can monitor trends to identify the preponderance of viral outbreaks and ensuing side effects.
Additional information about different types of disease data that may be collected during a pandemic can be found here.
- The Centers for Disease Control, Chronic Disease Data. Take a closer look at the efforts made by the CDC to monitor and capture chronic disease data.
- Agency for Health Care Research and Quality, Data Sources for Health Care Quality Measures. Learn more about how clinical and administrative data can be used to improve healthcare outcomes.
- National Institutes of Health, Common Data Types in Public Health. Survey some of the data types that can be used in public health advocacy.
Disease Data Collection Tools During a Pandemic
As health informatics professionals work to glean information from such broad data sources, they have a number of important tools at their disposal. Each of these tools can provide different information. Bringing this information together can help health informatics professionals adopt a truly comprehensive data-gathering approach.
Electronic Health Records (EHR)
An EHR is essentially an electronic version of a patient’s medical file, focusing on the diagnostic and treatment history of a single individual. EHRs provide health informatics professionals with a wealth of clinical data, including information about pre-existing conditions and risk factors and records of both failed and successful treatments.
Patient Surveys and Questionnaires
Through patient surveys and questionnaires, health researchers can add to their profiles of patient groups or populations. For example, surveys and questionnaires can be used to inquire about the lifestyles and nutritional factors of a patient or a patient’s family members. This information may provide clues about behavioral factors that impact the spread of a pandemic.
Evaluation models provide scientific, critical assessment of a particular aspect of healthcare. For example, a model can be constructed to systematically study the benefits of a particular healthcare protocol, as measured by patient outcomes. The model may also study the protocol’s efficiency, accessibility and equity. These models can be invaluable for studying the impact of public health initiatives during a pandemic.
Public Health Grid (PHGrid)
Public health grids seek to provide an infrastructure for understanding interrelated public health problems and responses. For example, a public health grid may show the relationships between individuals, private healthcare providers and public health institutions. Again, health informatics professionals can use these grids to assess the efficacy of pandemic response measures.
Many healthcare organizations now encourage their patients to download and use mobile health apps, or mHealth apps. These can provide patients with self-service tools that let them schedule appointments, leave messages for their provider or check lab results. The apps typically generate large volumes of data about patient habits and their encounters with physicians, which can be illuminating to health informatics professionals.
Contact tracing has been a significant part of the COVID-19 response. Those who have tested positive for the virus, or have been around people who’ve had it, are encouraged to report any recent physical contact they’ve had with anyone. By reviewing the results of contact tracing, health informatics professionals can define the trajectory and spread of a virus.
To learn more about the tools used for collecting disease data, consult these resources.
- Centers for Disease Control and Prevention, COVID-19 Contact Tracing. Find out more about the importance of contact tracing.
- Health IT Analytics, “Are Universal EHRs Key to Healthcare Value, Trust, and AI Adoption?” Get more information about the value of EHRs.
Health Informatics Professionals and the COVID-19 Pandemic
It’s clear that big data sources can play an important role in understanding COVID-19, hopefully enabling researchers to develop new strategies of prevention, containment and treatment. Deriving value from these sources, however, requires the expertise of trained health informatics professionals with the skills to assemble, synthesize, analyze and extrapolate key data points.
Understanding the Virus
One role health informatics professionals can play involves adding to our shared understanding of the complex properties of COVID-19. Information gathered through clinical data sources, including EHRs, can shed some light on the ways in which the virus grows, how it interacts with other health conditions and more.
By collecting disease data, health informatics professionals can play a crucial role in developing strategies that mitigate the spread of the disease within a defined population area. For example, contact tracing and population mobility information may point to some common ways in which the disease is transmitted, necessitating temporary shutdowns or encouraging behavioral changes.
Prevention and Control
Clinical data, as well as more general population metrics may also provide clues as to how the disease can be prevented, or at least controlled. For example, by reviewing disease trends and patterns, health informatics professionals may be able to alert healthcare providers to potential surges in cases, allowing for better preparation.
Stopping the Spread
Public surveillance tools can also be useful in stopping the spread of COVID-19. A good example is cell phone tracking, which allows epidemiologists to monitor patterns in how the virus moves through populations that are communicating and interacting.
One final benefit to rigorous data collection is that it enables public health officials to keep the population up to date about a fluid situation. For example, armed with the data provided by health informatics professionals, public health leaders can inform the community about changes in case numbers, mortality rates, recoveries and more.
Find out more about health informatics in the COVID-19 era with these resources.
- FiveThirtyEight, “Where the Latest COVID-19 Models Think We’re Headed – and Why They Disagree.” Learn more about the complexities involved with COVID forecasting.
- BigData Mining, “Ideas for How Informaticians Can Get Involved with COVID-19 Research.” Explore some ways health informatics professionals can engage in the fight against the pandemic.
Disease Data and the Fight Against Pandemics
In the effort to predict, prevent or suppress a pandemic—data can be invaluable. Health informatics professionals can play an essential role not only in gathering that data, but using it to maximum effect to save countless lives.