HLT 362 Describe how epidemiological data influences changes in health practices
HLT 362 Describe how epidemiological data influences changes in health practices
HLT 362 Describe how epidemiological data influences changes in health practices
Epidemiology is a field that deals with the study of healthcare problems, how they affect the population and the interventions necessary when dealing with the healthcare issues (CDC, 2012). Not only does the field offer quantitative data about a health care problem using hypothesis in human behavior, biology and physics but also offers proper action plans based on data and research done to help solve the healthcare problem.
When epidemiologists want to study a disease, they focus on all factors contributing to the spread of the disease and conduct a descriptive research that is able to answer the questions of who, how much, when, among who?, of the healthcare problem so that change can be made (CDC, 2020).
An example of a healthcare problem currently being studied is the Covid-19 pandemic, epidemiologist have carried out research on the risk factors, spread and the necessary action plan needed to help curb the pandemic. They have focused on quantitative and descriptive data that has shown high mortality rates are to those with diabetes, hypertension, and heart problems and with those necessary changes in the healthcare system have been made. Not only has the study helped to educate the public but also has helped given the healthcare professionals an idea of the changes needed using the data collected to help fight the pandemic.
Reference:
Center for Disease Control and Prevention (2012-2020) Epidemic intelligence Service, retrieved from https://www.cdc.gov/eis/field-epi-manual/chapters/Describing-Epi-Data.html
I agree with you, Covid-19 is a great example and the most recent event that epidemiologists continue conducting public health surveillance, collecting, analyzing, and interpreting health data. Epidemiology data plays a big role during the Covid-19 pandemic, one of the epidemiologist’s roles is to estimate the impact of the disease or other health outcomes on the population (CDC.org, n.d.). And as you mentioned, epidemiologists are focusing on quantitative and descriptive data that allows them to calculate, incidence (number of new cases reported over a specific period of time), Prevalence (number of cases at one specific point in time), hospitalizations (number of cases resulting in hospitalization), deaths (number of cases resulting in death). Also, it is important to mention that public surveillance is also helpful and it uses to create epidemiological models to predict where, how long, and how far a disease will spread (CDC.org, n.d.) Very interesting post. Thank you for sharing.
References
Coronavirus Disease 2019 (COVID-19). (2020, February 11). Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/science/about-epidemiology/monitoring-and-tracking.html
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Study limitations include the retrospective design with a potential interviewer or recall bias and uncertain validity of the data regarding the type and duration of symptoms. Moreover, the data were collected during the heyday of the first pandemic wave as part of infection control and containment measures, precluding a thorough planning of the interviews. Also, the follow-up interview could not be conducted within a fixed time frame for each individual but was performed if at least 6 weeks had passed since the reported onset of symptoms, potentially resulting in variation in the timing of the data collected on symptom duration and state of recovery. The data on symptom duration may not be entirely generalizable because mild cases may have been more likely to be contacted than severe cases. As in other studies relying on reported infections, an uncertain number of a- or oligosymptomatic cases may have been missed.
Furthermore, exposure patterns and testing modalities might have changed during the course of the outbreak, such that hospitalizations were more likely to occur at the beginning of the pandemic even in mild cases, whereas PCR testing was initially more restrictive due to a lack of laboratory capacities.
In conclusion, the Regensburg outbreak was characterized by relatively low numbers of cases and fatalities, particularly in elderly patients and those with COVID-19 risk factors. By comparison, the outbreak affected a relatively large proportion of younger individuals. COVID-19 showed a variety of symptoms and varying symptom duration, some of them lasting for weeks. Further prospective research is needed to clarify and confirm the presented data.
References
WHO Coronavirus disease (COVID-19) – Weekly Epidemiological Update. 6 September 2020: https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200907-weekly-epi-update-4.pdf?sfvrsn=f5f607ee_2. Accessed 10 Sept 2020
Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395(10223):507–13. https://doi.org/10.1016/S0140-6736(20)30211-7.
Covid-19 data is and will continue to be a very interesting topic for researchers and data collectors. The epidemic produced such a large response at local, state, and federal levels which produced a large amount of data not only on mortality and infection rates but on disparities among various communities. A May 2020 article noted conducted a retrospective cohort analysis using California’s Sutter Health’s integrated EHR and noted that from January 1, 2020-April 8, 2020 non-Hispanic African Americans were 2.7 % times more likely to be hospitalized when compared with non-Hispanic White patients. (Azar et al., 2020)
This EHR data is very interesting because, at that time, we were still in the early stages of the Covid-19 pandemic and shutdown. It would be interesting to see the trend of this data using the same EHR system and if the recognition of disparities was addressed. (Azar et al., 2020)
On a larger scale, an article published in 2022 also conducted a retrospective data analysis using Kaiser Permanente’s western region (Colorado, Northwest, Washington) to follow up on March-Sept 2020 data which indicated continued US health inequities among Asians, Black /African Americans, Hispanic, Indigenous American and Alaskan Natives. (Shortreed et al., 2022)
This information and analyzed EHR data expose the continued challenges with epidemiology in the healthcare system requiring more changes in healthcare practice.
References:
Azar, K. M. J., Shen, Z., Romanelli, R. J., Lockhart, S. H., Smits, K., Robinson, S., Brown, S., & Pressman, A. R. (2020). Disparities In Outcomes Among COVID-19 Patients In A Large Health Care System In California. Health Affairs, 39(7), 10.1377/hlthaff. https://doi.org/10.1377/hlthaff.2020.00598
Shortreed, S. M., Gray, R., Akosile, M. A., Walker, R. L., Fuller, S., Temposky, L., Fortmann, S. P., Albertson-Junkans, L., Floyd, J. S., Bayliss, E. A., Harrington, L. B., Lee, M. H., & Dublin, S. (2022). Increased COVID-19 Infection Risk Drives Racial and Ethnic Disparities in Severe COVID-19 Outcomes. Journal of Racial and Ethnic Health Disparities, 10. https://doi.org/10.1007/s40615-021-01205-2
Epidemiology is the study of the distribution and determinants of health related to events within a specified population, its purpose being to inform decisions about the control of health problems (Hannaford, & Owen-Smith, 1998). It can also detect risk factors and the study of health relationships with multiple dangerous substances. On example, if from this weeks topic readings and it is assessing the risk factors of oral birth control and cardiovascular disease among women less than 35 years of age and take contraceptives (Hannaford, & Owen-Smith, 1998). The epidemiological knowledge gained from this study can help woman who already have cardiovascular disease issues from contraceptives. It provides a disease control measures for patients. In turn this can help protect other women from acquiring this disease and protect the public health. The epidemiological data gathered from studies can provide evidence-based practice and help identify correlations between variables. Another example of epidemiology is an article called “acute promyelocytic leukaemia: population-based study of epidemiology and outcome with ATRA and oral-ATO from 1991 to 2021″. This article, studies a specific population which is leukaemia patients and the treatments. This study focuses on the health relationships between an oral medication called oral-ATO and its outcomes. This medication had three end points that were calculated and they were: APL occurrence, early deaths, and overall survival (Gill, Raghupathy, Lee, Yung, Chu, Ni, Xiao, Flores, Yim, Lee, Chin, Mohan, Kumana, & Kwong, 2023).
References
Gill, H., Raghupathy, R., Lee, C. Y. Y., Yung, Y., Chu, H.-T., Ni, M. Y., Xiao, X., Flores, F. P., Yim, R., Lee, P., Chin, L., Li, V. W. K., Au, L., Au, W.-Y., Ma, E. S. K., Mohan, D., Kumana, C. R., & Kwong, Y.-L. (2023). Acute promyelocytic leukaemia: population-based study of epidemiology and outcome with ATRA and oral-ATO from 1991 to 2021. BMC Cancer, 23(1), 1–14. https://doi-org.lopes.idm.oclc.org/10.1186/s12885-023-10612-z
Hannaford, P. C., & Owen-Smith, V. (1998, March 28). Using epidemiological data to guide clinical practice: Review of studies on cardiovascular disease and use of combined oral contraceptives. BMJ (Clinical research ed.). Retrieved March 1, 2023, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC28503/