Data disaggregation: the case of Asian and Pacific Islander data and the role of health sciences librarians
DOI:
https://doi.org/10.5195/jmla.2022.1372Keywords:
data disaggregation, Asian and Pacific Islander, health sciences librarians, health sciences librarianshipAbstract
Health disparities within Asian and Pacific Islander (API) communities are often masked due to aggregated data. Lack of adequate data limits required health care services for these communities. While moving forward toward health equity, it is critical that disparities for API communities are acknowledged and addressed. This article focuses on the issues of aggregated data for API communities followed by suggestions on how health sciences librarians can support and promote better practices for data disaggregation.
References
Holland AT, Palaniappan LP. Problems with the collection and interpretation of Asian-American health data: omission, aggregation, and extrapolation. Ann Epidemiol. 2012 Jun;22(6):397–405.
Srinivasan S, Guillermo T. Toward improved health: disaggregating Asian American and Native Hawaiian/Pacific Islander data. Am J Public Health. 2000 Nov;90(11):1731–4.
Kauh TJ, Read JG, Scheitler AJ. The critical role of racial/ethnic data disaggregation for health equity. Popul Res Policy Rev. 2021 Jan 8:1–7.
Ponce NA, Shimkhada R, Tulua A. Disaggregating California’s COVID-19 data for Native Hawaiians and Pacific Islanders and Asians. Los Angeles, CA: UCLA Center for Health Policy Research; 2021.
Gordon NP, Lin TY, Rau J, Lo JC. Aggregation of Asian-American subgroups masks meaningful differences in health and health risks among Asian ethnicities: an electronic health record based cohort study. BMC Public Health. 2019 Nov 25;19(1):1551.
AAPI Data. Ethnicity data [Internet]. [cited 17 June 2021]. <https://aapidata.com/ethnicitydata/>.
Byrne, G. A statistical primer: understanding descriptive and inferential statistics. Evidence Based Library and Information Practice. 2007 Mar;2(1):32–34.
Shah NS, Luncheon C, Kandula NR, Cho P, Loustalot F, Fang J. Self-reported diabetes prevalence in Asian American subgroups: behavioral risk factor surveillance system, 2013-2019. J Gen Intern Med. 2021 Jun 9.
Kirby JB, Berdahl TA, Torres Stone RA. Perceptions of patient-provider communication across the six largest Asian subgroups in the USA. J Gen Intern Med. 2021 Apr;36(4):888–93.
Chen L, Shi L, Zhang D, Chao SM. Influence of acculturation on risk for gestational diabetes among Asian women. Prev Chronic Dis. 2019 Dec 5;16:E158.
Badrinathan S, Kapur D, Kay J, Vaishnav M. Social realities of Indian Americans: results from the 2020 Indian American Attitudes Survey. Washington, DC: Carnegie Endowment for International Peace (US); 2021 June. 1–63.
Haris-Hooker S. Moving toward equitable health sciences knowledge sharing [Internet]. 4 May 2021. Medical Library Association. InSight Initiative Summit 6: Keynote Address. <https://www.mlanet.org/p/cm/ld/fid=1841>.
Clark LT, Watkins L, Piña IL, Elmer M, Akinboboye O, Gorham M, Jamerson B, McCullough C, Pierre C, Polis AB, Puckrein G, Regnante JM. Increasing diversity in clinical trials: overcoming critical barriers. Curr Probl Cardiol. 2019 May;44(5):148–72.
Swanson GM, Ward AJ. Recruiting minorities into clinical trials: toward a participant-friendly system. J Natl Cancer Inst. 1995 Dec 6;87(23):1747–59.
Strategies to reach diverse populations for clinical trials: approaches used by practices recognized with the 2006 clinical trials participation award. J Oncol Pract. 2006 Sep;2(5):241–3.
National Institutes of Health. All of Us research program [Internet]. [cited 16 June 2021] <https://allofus.nih.gov/>.
Network of the National Library of Medicine. Get involved: NNLM All of Us community engagement network [Internet]. [cited 16 June 2021] <https://nnlm.gov/all-of-us/engage>.
Ellaway RH, Pusic MV, Galbraith RM, Cameron T. Developing the Role of big data and analytics in health professional education. Medical Teacher. 2014;36(3): 216–22.
Crow G, Wiles R, Health S, Charles V. Research ethics and data quality: the implications of informed consent. International Journal of Social Research Methodology. 2016;9(2):83–95.
George S, Duran N, Norris K. A systematic review of barriers and facilitators to minority research participation among African Americans, Latinos, Asian Americans, and Pacific Islanders. Am J Public Health. 2014 Feb;104(2):e16–31.
Kitzie V, Francis D, Vera N. Establishing partnerships between librarians and community health workers to promote LGBTQIA+ health [Internet]. 9 June 2021. Forth Worth, TX: Network of the National Library of Medicine South Central Region. <https://nnlm.gov/training/class/establishing-partnerships-promote-lgbtqia-health-june-9-2021-0>.
Whitney W, Keselman A, Humphreys B. Libraries and librarians: key partners for progress in health literacy research and practice. Stud Health Technol Inform. 2017;240:415–32.
Islam NS, Zanowiak JM, Riley L, Nadkarni SK, Kwon SC, Trinh-Shevrin C. Characteristics of Asian American, Native Hawaiian, and Pacific Islander community health worker programs: a systematic review. J Health Care Poor Underserved. 2015 May;26(2 Suppl):238–68.
McElfish PA, Yeary K, Sinclair IA, Steelman S, Esquivel MK, Aitaoto N, Kaholokula K, Purvis RS, Ayers BL. Best practices for community-engaged research with Pacific Islander Communities in the US and USAPI: a scoping review. J Health Care Poor Underserved. 2019;30(4):1302–30.
Polubriaginof FCG, Ryan P, Salmasian H, Shapiro AW, Perotte A, Safford MM, Hripcsak G, Smith S, Tatonetti NP, Vawdrey DK. Challenges with quality of race and ethnicity data in observational databases. J Am Med Inform Assoc. 2019 Aug 1;26(8-9):730–6.
Klinger EV, Carlini SV, Gonzalez I, Hubert SS, Linder JA, Rigotti NA, Kontos EZ, Park ER, Marinacci LX, Haas JS. Accuracy of race, ethnicity, and language preference in an electronic health record. J Gen Intern Med. 2015 Jun;30(6):719–23.
Lee WC, Veeranki SP, Serag H, Eschbach K, Smith KD. Improving the collection of race, ethnicity, and language data to reduce healthcare disparities: a case study from an academic medical center. Perspect Health Inf Manag. 2016 Oct 1;13(Fall):1g.
Roeschley A, Khader M. Defining Data Ethics in Library and Information Science. iConference 2020 Proceedings. University of Illinois at Urbana-Champaign; 2020 March 23. Available from: http://hdl.handle.net/2142/106536.
Westin A. Privacy and freedom. New York: Atheneum; 1967.
Daniel, B. Big Data and Analytics in higher education: opportunities and challenges. British Journal of Educational Technology. 2015;46(5):904–20.
Eschenfelder KR, Johnson A. Managing the data commons: controlled sharing of scholarly data. Journal of the Association for Information Science and Technology. 2014;65(9):175774.
Wyatt LC, Ung T, Park R, Kwon SC, Trinh-Shevrin C. Risk factors of suicide and depression among Asian American, Native Hawaiian, and Pacific Islander youth: a systematic literature review. J Health Care Poor Underserved. 2015 May;26(2 Suppl):191–237.
Barr-Walker J, Sharifi C. Critical librarianship in health sciences libraries: an introduction. J Med Libr Assoc. 2019 Apr;107(2):258–64.
Kroll SM, Brandigan PS. MEDLINE search strategies for literature on Asian Americans/Pacific Islanders. Asian Am Pac Isl J Health. 1993 Summer;1(1):56–62
Tsai W, Nusrath S, Zhu R. Systematic review of depressive, anxiety and post-traumatic stress symptoms among Asian American breast cancer survivors. BMJ Open. 2020 Sep 6;10(9):e037078.
Solikhah S, Nurdjannah S. Assessment of the risk of developing breast cancer using the Gail model in Asian females: a systematic review. Heliyon. 2020 Apr 22;6(4):e03794.
Published
Issue
Section
License
Copyright (c) 2022 Seema Bhakta
This work is licensed under a Creative Commons Attribution 4.0 International License.
