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COVID-19 is at the forefront of the consciousness of humanity, by and large, and the informatics tools we implement for managing, treating, and surveilling the disease are of great import. From disease databases to electronic health records, from bioinformatics tools for peptide and protein modeling to laboratory tools such as LIMS and LIS, we continue to fight back against the threat of the SARS-CoV-2 virus. Yet despite the gravity of the pandemic, this is neither the first nor the last time laboratory and scientific informatics will play a positive role in testing for disease and improving public health outcomes.

Health informatics technology, when used responsibly, has already proven to be useful in studying and treating contagious diseases. In a 2013 research paper published in the journal BMJ Quality & Safety, El-Kareh et al. analyzed and described the state of diagnostic health information technology (HIT). They noted that without the aid of HIT, clinicians are more error-prone, leaving them "vulnerable to fallible human memory, variable disease presentation, clinical processes plagued by communication lapses, and a series of well-documented ‘heuristics,’ biases, and disease-specific pitfalls." Appropriate, well-designed HIT systems are capable of helping clinicians and laboratorians by providing more timely access to information, improved communication, better clinical reasoning and decision making, and improved workflows, as well as a reduction in diagnostic errors, and, as a result, improved patient safety and health outcomes.

From a public health perspective, the application of informatics to disease surveillance, reporting, and health habit promotion is also vital. Winters-Miner et al. note in particular the value of using informatics tools and methods to implement predictive analytics and data mining into public health. They use disease prevention and biosurveillance as major examples. We could, for example "analyze large populations of people to quantify risks related to public health, and help physicians to develop intervention programs for those patients at highest risk of some ailment or medical condition." Additionally, through the use of syndromic surveillance systems (tools aiding in the detection of indicators leading up to disease diagnosis for individuals and populations), they suggest that outbreaks can be better detected at local and national levels, and public health measures can be better implemented, increasing public awareness and hindering the spread of disease.

In the clinical laboratory, informatics systems have been influencing workflow improvements and improved service delivery for more than five decades. And while improvements have been seen in the laboratory from not only the introduction of computerized systems but also the realization of quality control and point-of-care testing, more challenges remain. For example, quality management in the laboratory is still often a manual, time-consuming activity. While the LIMS and LIS have some tools to assist with this task, the inclusion of laboratory analytics and business intelligence tools into those systems may lead to even further improvements in quality and efficiency in the lab. And in the realm of point-of-care testing, oversight and control of instruments can be lost when connectivity and training is lacking. Proper interfacing of these lab instruments could lead to improvements in those areas, says Siemens Healthineers' Daniel Gundler. "Maintaining POC instruments and overseeing the operators performing POC tests would be much easier if all the information and data from each instrument were accessible through one user interface in which coordinators could manage both the instruments and operators."