The challenges presented in scenario #1 are interpersonal,
departmental and bureaucratic. The physician in question seems to
have no departmental obligation to remove himself from the data
collection process and so, may have taken the opportunity to delete
patients that are less than optimal to achieve the study’s desired
outcome. The interpersonal dynamics are that the data collector is
not independent of the researcher and has been employed by him.
Steps that can be taken to address this situation: c
1. Have independent teams for research design, data analysis and
data collection.
2. The hiring of data collectors should be conducted by the
department and not the head of the research project.
3. Use research databases that require a field for follow-up
explanations if study subjects or data is removed or changed.
4. Create protocols/avenues for individuals involved in research to
express concerns with research design and implementation. c
c Some critics point out that there is not enough consistency among
researchers in defining poor data quality and how to verify data
adequately, particularly in clinical research (Houston, Probst, and
Martin, 2018). Houston et. al, demonstrate that verifying the source
of the data does not necessarily ensure that the study design will be
free of errors. They argue for a more unified approach in the scientific
community to develop monitoring based on risk for error. The NIH
has also acted to promote responsible research, releasing updated
criteria for research projects in its publication “Implementing Rigor
and Transparency in NIH & AHRQ Research Grant Applications”
which includes guidelines for data management and sharing (Gandhi
and Linford, 2021).
c The relationship between ethics and policy in any institution should
be —but is not always — aligned with one another. Medical and
research ethics are enforced by HIPPA and defined in federal codes
that protect human subjects and lay out the necessary conditions for
IRBS (independent review boards) and clinical practice (HHS, 2022).
These codes concern ethics that are legal requirements and must be
followed by researchers and institutions who do not wish to lose
grants and public funding. If individual ethics do not align with
organizational policy, the result could not only be loss of funding but
of reputation for the individual as well as the institution. c However,
there may be ethical considerations not currently encoded by law or
institutional policy and these areas may be the most difficult to
navigate. The data collector should bring his/her concerns about the
patients who were removed and possible manipulation of the study
design to the department head. c
References
Gandhi, C. S., & Linford, N. (2021). Considerations for Developing
Ethical Biomedical Grant Proposals for the National Institutes of
Health. AMWA Journal: American Medical Writers Association
Journal, 36 (2), 90–93. https://doi-
org.ezproxy.snhu.edu/10.55752/amwa.2021.25
Houston, L., Probst, Y., & Martin, A. (2018). Assessing data quality and
the variability of source data verification auditing methods in clinical
research settings. Journal of Biomedical Informatics, 83, 25–32.
https://doi-org.ezproxy.snhu.edu/10.1016/j.jbi.2018.05.010
U.S. Department of Health and Human Services – HHS. (2022).
Ethical Codes & Research Standards. Office for Human Research
Protections. Retrieved July 11, 2022, from
https://www.hhs.gov/ohrp/international/ethical-codes-and-
research-standards/index.html
