User:Shawndouglas/sandbox/sublevel34

From LIMSWiki
Jump to navigationJump to search

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

3.1 Laboratory informatics and workflow management

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.[1] 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 providing or disproving hypotheses.[2] 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.[3][4]

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."[5] 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.[5] 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.[6] And in the European Union, member countries and the U.K. are asked to report through the Early Warning and Response System.[7]

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[8], as does the American Academy of Pediatrics.[9]

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. TO BE CONTINUED...


3.3 Additional benefits of laboratory informatics in disease testing

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."[10] 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.[11]

3.3.1 Bioinformatics

References

  1. Naito, M. (2014). "Utilization and application of public health data in descriptive epidemiology". Journal of Epidemiology 24 (6): 435–6. doi:10.2188/jea.je20140182. PMC PMC4213216. PMID 25327184. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4213216. 
  2. Centers for Disease Control and Prevention (2012) (PDF). Principles of Epidemiology in Public Health Practice (3rd ed.). Centers for Disease Control and Prevention. https://www.cdc.gov/csels/dsepd/ss1978/SS1978.pdf. Retrieved 11 April 2020. 
  3. Hamilton, J.J.; Hopkins, R.S. (2019). "Chapter 5: Using Technologies for Data Collection and Management". In Rasmussen, S.A.; Goodman, R.A.. The CDC Field Epidemiology Manual (4th ed.). Oxford University Press. pp. 71–104. ISBN 9780190933692. 
  4. von Elm, E.; Altman, D.G.; Egger, M. et al. (2007). "The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies". PLoS Medicine 4 (10): e296. doi:10.1371/journal.pmed.0040296. PMC PMC2020495. PMID 17941714. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2020495. 
  5. 5.0 5.1 Centers for Disease Control and Prevention (21 March 2020). "Information for Health Departments on Reporting Cases of COVID-19". Coronavirus Disease 2019 (COVID-19). Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/php/reporting-pui.html. Retrieved 21 March 2020. 
  6. Government of Canada (10 February 2020). "Interim national surveillance guidelines for human infection with Coronavirus disease (COVID-19)". Government of Canada. https://www.canada.ca/en/public-health/services/diseases/2019-novel-coronavirus-infection/health-professionals/interim-guidance-surveillance-human-infection.html. Retrieved 11 April 2020. 
  7. European Centre for Disease Prevention and Control (2 March 2020). "Case definition and European surveillance for COVID-19, as of 2 March 2020". COVID-19 Portal. European Centre for Disease Prevention and Control. https://www.ecdc.europa.eu/en/case-definition-and-european-surveillance-human-infection-novel-coronavirus-2019-ncov. Retrieved 11 April 2020. 
  8. Green, C.; Bradley, V. (1 April 2020). "Coding guidance for new ICD-10-CM and lab testing codes for COVID-19". MGMA Stat. https://www.mgma.com/data/data-stories/coding-guidance-for-new-icd-10-cm-and-lab-testing. Retrieved 11 April 2020. 
  9. AAP Division of Health Care Finance (12 March 2020). "How to use ICD-10-CM, new lab testing codes for COVID-19". American Academy of Pediatrics. https://www.aappublications.org/news/2020/03/12/coding031220. Retrieved 11 April 2020. 
  10. El-Kareh, R.; Hasan, O.; Schiff, G.D. (2013). "Use of health information technology to reduce diagnostic errors". BMJ Quality & Safety 22 (Suppl. 2): ii40–ii51. doi:10.1136/bmjqs-2013-001884. PMC PMC3786650. PMID 23852973. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3786650. 
  11. National Academies of Sciences, Engineering, and Medicine (2015). "Chapter 5: Technology and Tools in the Diagnostic Process". Improving Diagnosis in Health Care. The National Academies Press. pp. 217–62. doi:10.17226/21794. ISBN 9780309377720. https://www.nap.edu/read/21794/chapter/7.