Case Study 1 is about investigators who are analyzing race difference in HIV positive test results. This retrospective data was previously collected at government-funded clinics throughout the Midwest region of the United States from January 2010 to December 2011. The results were from anonymous demographic data collected at the point of service for initial testing. The variables in the analysis include race, ethnicity, gender, socioeconomic status, age group, and education level.
Risks – A retrospective study uses existing data that has been recorded for reasons other than research (Hess,2004). Therefore, there are very few risks to the researcher and the participants in this study. The names of the participants remain anonymous so the people with HIV are not being named to the public. Also, the data is collected and there will not be any continued data collected. The biggest risk would be to the group that is found to have high numbers of HIV people. This group may then face stigma and discrimination.
Benefits – The benefit to this data, is to potentially find a trend in the HIV positive patients. Being able to find a trend could help target these communities or age groups for further education, treatment, and ways for prevention. Also, by leaving the names of the patients anonymous, the researchers are able to get information they may not have been able to get if the names were revealed. There has been a stigma on HIV and it continues today. HIV stigma and discrimination can pose complex barriers to prevention, testing, treatment, and support for people living with or at risk for HIV (HIV Stigma and Discrimination, 2017).
This research involved human participants, therefore requires review by the IRB. The Institutional Review Board (IRB) reviews and approves all research involving human subjects to ensure that it is conducted in accordance with all federal, institutional, and ethical guidelines (Paulson, 2017). There are three different levels of IRB review – Full, Expedited, and Exempt. This research is considered the exempt level. There are different sub-categories at the exempt level of review. This research would be sub-category four – secondary research with identifiable information/specimens collected for some other initial activity. The research must include one of the following criteria: information that is publicly available, information recorded so subjects cannot be readily identified or the investigator does not contact subjects and will not reidentify the subjects, collection and analysis involved investigators use of identifiable health information when used is regulated by HIPAA, or research information is collected by or on behalf of federal government using government generated or collected information obtained for non-research activities (University of Southern California, n.d.).
References
Content Source: HIV.govDate last updated: May 20, 2017. (2018, March 19). Activities Combating HIV Stigma and Discrimination. Retrieved from https://www.hiv.gov/federal-response/federal-activities-agencies/activities-combating-hiv-stigma-and-discrimination
Hess, D. R. (2004, October). Retrospective studies and chart reviews. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/15447798
Paulson, A. (2017, March 9). Institutional Review Board (IRB). Retrieved from https://www.apus.edu/academic-community/research/institutional-review-board/index
University of Southern California. (n.d.). Retrieved from https://oprs.usc.edu/irb-review/types-of-irb-review/exempt/#cat4
I agree with the risks and benefits you listed for this case study, and agree on the IRB review. Retrospective collection makes it easier to look at the historical data of HIV in the Midwest to be able to target a certain trend. One thing I thought about with this case study was the area that the information was taken from. The case study lists that the data is taken from the Midwest region of the United States. I was curious on how the Midwest region compared to other regions in the United States and if data would be compared to results of other regions to help target higher risk groups, if they are comparable. The CDC states that “HIV diagnoses are not evenly distributed across the states and region” and found that southern states accounted for more than half of the new HIV diagnoses in 2017 (Centers for Disease Control and Prevention, 2019). I think this case study is meant to focus on the specific population of the Midwest region, however it may be beneficial to compare to other regions.
Reference:
Centers for Disease Control and Prevention. (2019, October 30). HIV. Retrieved from CDC: https://www.cdc.gov/hiv/statistics/overview/geographicdistribution.html
In 2017, the south made up 52% of the new HIV diagnoses in the U.S. and the Midwest made up only 13% of new diagnoses (Center for Disease Control and Prevention, 2019). I do think it would be interesting to see a current total number of people with HIV in the different regions.
Reference
Geographic Distribution. (2019, October 30). Retrieved from https://www.cdc.gov/hiv/statistics/overview/geographicdistribution.html
I agree with your analysis of IRB level. I, like Sadie, have some serious concerns with the choice of sampling. to be doing a race related study and isolating the sample population to a specific region sounds risky to me. I would definitely be concerned with the implications of labeling a specific race as being more likely to have a positive HIV test result, when the sampling is done irresponsibly. Another potential data skew would be that the data gathered would be from only government-funded clinics. Government-funded clinics must be in areas with medically underserved populations which are oftentimes in inner city areas which are generally populated with minorities in poverty (“Rural Health Information Hub”, 2019). I appreciate the convenience of such a sample but definitely find it ethically concerning.
Resources:
Rural Health Information Hub. (2019, August 23). Retrieved February 9, 2020, from https://www.ruralhealthinfo.org/topics/federally-qualified-health-centers