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3. Workflow and information management for COVID-19 (and other pandemics)

3.2 Laboratory informatics and reporting requirements

Epidemiology can broadly be split into two categories: descriptive epidemiology and analytical epidemiology. Descriptive epidemiology involves studies and other activites that deal with geographical comparisons and temporal trend descriptions of disease. As such, the collection and use of quality incidence data is vital to developing hypotheses. Analytical epidemiology allows for the testing of those hypotheses using both experimental and obsevational studies, as well as control groups. Similarly, the collection and use of quality experimental and observational data is vital for proving or disproving hypotheses. In both cases, proper reporting of data is critical to the success of epidemiologists' response to outbreaks and pandemics, as well as the credibility of their research.

The proper reporting of COVID-19 case data is no exception. In the United States, the CDC has taken a standardized approach to collecting reports on "individuals with at least one respiratory specimen that tested positive for the virus that causes COVID-19." Their COVID-19 Case Report Form is designed to collect a wide variety of information about a COVID-19 case, including patient demographics, epidemiological characteristics, exposure and contact history, and clinical diagnosis and treatment procedures. Currently, the CDC is asking local and state health departments to submit case reports, and asking healthcare providers to contact those health departments when "concerned that a patient may have COVID-19." The CDC has also slimmed its reporting requirements, limiting reporting of "persons under investigation" to areas where testing must be forwarded to the CDC due to insufficient capacity to test locally. Electronic reporting using the CDC's system is preferred, but they have a protocol for those areas unable to submit electronically. Canada has similar reporting expectations, with their own case report form and electronic data submission process through the Public Health Agency of Canada. And in the European Union, member countries and the U.K. are asked to report through the Early Warning and Response System.

Somewhat related are any internal reporting requirements, particularly for test reporting in labs and medical facilities. The International Statistical Classification of Diseases and Related Health Problems (ICD) is a system of diagnostic codes for classifying diseases, including nuanced classifications of a wide variety of signs, symptoms, abnormal findings, complaints, social circumstances, and external causes of injury or disease. Their ICD-10-CM code set has been modified to include lab testing codes for COVID-19, as has the Current Procedural Terminology (CPT) code set. Green and Bradley provide insight into these additions, as does the American Academy of Pediatrics.

Laboratories analyzing specimens for SARS-CoV-2 therefore must be equipped to not only handle analytical testing and test orders using the new test codes, but they also must be able to quickly and accurately transfer vital case information to the appropriate health authority.

Table 1. U.S. state-based COVID-19 reporting requirements State Electronic file (Y/N) Fax? (Y/N) Report form Contact Additional details Alabama Y N Novel Coronavirus Report Form ALNEDSSsupport@adph.state.al.us "Providers who are either reporting laboratory results for patients tested by a commercial or clinical laboratory (not tested by the BCL) or reporting deaths among patients with positive results must complete" the report form. "Laboratories are required to report all negative and positive COVID-19 virus test results electronically (faxes do not count). If not already enrolled, laboratories will need to manually enter test results directly into the surveillance system." Email the contact to enroll staff access to the system.

3.3 Additional benefits of laboratory informatics in disease testing and public health

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 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.

https://www.nature.com/articles/s41746-019-0110-4 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4204239/ https://www.nap.edu/read/21794/chapter/7#241 https://www.mlo-online.com/home/article/13017228/poct-made-easier-with-informatics