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Leveraging Health and Community Data: Insights into Social Determinants of Health

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Nursing Informatics

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Abstract

The field of health informatics is rapidly evolving to encompass data from outside health care systems. Much of the external data is at the community level and is analyzed in conjunction with patient-level data to identify potential living circumstances that adversely affect patients’ health. These circumstances, or social determinants of health, are often the key to resolving chronic health problems and preventable use of health care facilities. The effective resolution of these problems frequently requires a partnership between health professionals and others, such as attorneys, social workers, or civil agencies. The exponential growth of data that are available presents challenges in management, secure storage, and translation into actionable knowledge that facilitates gained insights in a timely manner, and recruitment and retention of skilled personnel.

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References

  1. National Quality Forum. National Quality Partners™ action brief. 2019. Retrieved from https://www.qualityforum.org/News_And_Resources/Press_Releases/2019/National_Quality_Forum_Leads_National_Call_to_Address_Social_Determinants_of_Health__through_Quality_and_Payment_Innovation.aspx.

    Google Scholar 

  2. Datz, T. ZIP code better predictor of health than genetic code. The Harvard Gazette. 2014, August 13. Retrieved from https://www.hsph.harvard.edu/news/features/zip-code-better-predictor-of-health-than-genetic-code/

  3. Mullangi S, Pollak J, Ibrahim S. Harnessing digital information to improve population health. Harvard Business Review. 2019, May 14;

    Google Scholar 

  4. Metzger R, Hall M. A teaching strategy for social determinants of health screening in primary care. Annals of Nursing and Practice. 2018;5(3)

    Google Scholar 

  5. Beck A, Huang B, Chundur R, Kahn R. Housing code violation density associated with emergency department and hospital use. Health Aff. 2014;33(11):1993–2002.

    Article  Google Scholar 

  6. Agency for Healthcare Research and Quality (AHRQ). Computerized disease registries. n.d.. Retrieved May 17, 2020 from https://digital.ahrq.gov/key-topics/computerized-disease-registries.

  7. National Rural Health Resource Center. Using claims data. 2020. Retrieved May 17, 2020, from https://www.ruralcenter.org/population-health-toolkit/data/using-claims-data.

    Google Scholar 

  8. U.S. Centers for Disease Control and Prevention. National notifiable diseases surveillance system: data collection and reporting. 2018. Retrieved May 17, 2020 from https://wwwn.cdc.gov/nndss/data-collection.html.

    Google Scholar 

  9. World Health Organization. What are social determinants of health? 2019. Retrieved from https://www.who.int/social_determinants/en/.

    Google Scholar 

  10. Ellison K. Social media posts and online searches hold vital clues about pandemic spread. Sci Am. 2020; Retrieved from https://www.scientificamerican.com/article/social-media-posts-and-online-searches-hold-vital-clues-about-pandemic-spread/

  11. University of Wisconsin Population Health Institute. County health rankings and roadmaps. 2020. Retrieved from https://www.countyhealthrankings.org/.

    Google Scholar 

  12. Gamache R, Kharrazi H, Weiner J. Public and population health informatics: the bridging of big data to benefit communities. In: IMIA yearbook of medical informatics; 2018. Retrieved May 17, 2020 from https://www.thieme-connect.com/products/ejournals/pdf/10.1055/s-0038-1667081.pdf.

    Google Scholar 

  13. Omnisci.com. Geospatial–a complete introduction. 2020. Retrieved from https://www.omnisci.com/learn/geospatial.

    Google Scholar 

  14. esri.com. What is GIS? 2020. Retrieved from https://www.esri.com/en-us/what-is-gis/overview#image.

    Google Scholar 

  15. Metzger R. Substandard rental housing in the promise zone of a mid-sized U.S. city. (doctoral dissertation). Minneapolis, MN: Walden University; 2018.

    Google Scholar 

  16. Accenture.com. Introduction to cloud computing. 2020. Retrieved from https://www.accenture.com/us-en/insights/cloud-computing-index?c=acn_glb_cloudgoogle_11261453&n=psgs_0620&gclid=CjwKCAjw34n5BRA9EiwA2u9k3-nJRhnT4OgIi19lhvHi-UrXHIWAqiSdaWjuJCU618v_d01BDxDxaxoC5SEQAvD_BwE&gclsrc=aw.ds.

    Google Scholar 

  17. Rouse M. Artificial intelligence. Business Analytics. 2020; Retrieved from https://searchenterpriseai.techtarget.com/definition/AI-Artificial-Intelligence#:~:text=Artificial%20intelligence%20(AI)%20is%20the,speech%20recognition%20and%20machine%20vision

  18. Avidon E. AI tools in analytics software key in fighting COVID-19. Business Analytics. 2020, April 3; Retrieved from https://searchbusinessanalytics.techtarget.com/feature/AI-tools-in-analytics-software-key-in-fighting-COVID-19?_ga=2.131220742.820365397.1596209138-1883762057.1596209138

  19. Kent J. 5 ways to ethically use social determinants of health data. Health IT Analytics. 2019, June 27; Retrieved from https://healthitanalytics.com/news/5-ways-to-ethically-use-social-determinants-of-health-data

  20. National Center for Medical-Legal Partnerships. We’re helping to build an integrated health care system that better addresses health-harming social needs by leveraging legal services and expertise to advance individual and population health. 2019. Retrieved November 18, 2019 from https://medical-legalpartnership.org/.

    Google Scholar 

  21. Centers for Disparities in Health, Build Health Places Network, Robert Wood Johnson Foundation. How do neighborhood conditions shape health? An excerpt from making the case for linking community development health. 2015. Retrieved from https://www.buildhealthyplaces.org/content/uploads/2015/09/How-Do-Neighborhood-Conditions-Shape-Health.pdf.

    Google Scholar 

  22. American Public Health Association. Health in all policies. 2020. Retrieved from https://www.apha.org/topics-and-issues/health-in-all-policies.

    Google Scholar 

  23. Beck A, Sandel M, Ryan P, Kahn R. Mapping neighborhood health geomarkers to clinical care decisions to promote equity in child health. Health Aff. 2017;36(6):999–1005. https://doi.org/10.1377/hlthaff.2016.1425.

    Article  Google Scholar 

  24. Colorado Department of Public Health and Environment. The connection between health disparities and the social determinants of health in early childhood. Health Watch. 2010. Retrieved from https://www.cohealthdata.dphe.state.co.us/chd/Resources/pubs/ECHealthDisparities2.pdf

  25. Beck A, Klein M, Schaffzin J, Tallent V, Gillam M, Kahn R. Identifying and treating a substandard housing cluster using a medical-legal partnership. Pediatrics. 2012;130(5)

    Google Scholar 

  26. Shah G, Waterfield K. Promoting determinants of health services; informatics is the answer. J Public Health Manag Pract. 2019; Retrieved from https://jphmpdirect.com/2019/03/13/promoting-social-determinants-of-health-services-informatics-is-the-answer/

  27. IBM Big Data & Analytics Hub. 3 top data challenges and how firms solved them. 2018. Retrieved from https://www.ibmbigdatahub.com/blog/3-top-data-challenges-and-how-firms-solved-them.

  28. Datamation. Big data challenges. 2017. Retrieved from https://www.datamation.com/big-data/big-data-challenges.html

  29. Agency for Healthcare Research and Quality. Quadruple aim proposed to address workforce burnout. 2019. Retrieved from https://integrationacademy.ahrq.gov/news-and-events/news/quadruple-aim-proposed-address-workforce-burnout

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Appendix: Answers to Review Questions

Appendix: Answers to Review Questions

  1. 1.

    As a health services researcher, you are interested in a pattern you observed in population health data that indicate a higher-than normal prevalence of pancreatic cancer in the lower Ohio River Valley in the U.S. You want to explore potential factors associated with this cancer, including the characteristics of the people who developed this cancer and any environmental exposures people with this cancer may have experienced. Identify at least two sources of data you might find available in the cloud where you can explore data you need.

    There are many resources for information; here are some examples.

Resource

Type of data

Cancer registries

Detailed information about cancer patients, distribution of cancer cases by gender, race/ethnicity, age, and other demographic factors, what prevention efforts work best, who is most likely to get cancer. Cancer registries analyze data and share with groups working to fight cancer.

National Vital Statistics database (CDC)

Captures all deaths from all causes across every state in the nation. These data help track the characteristics of those dying in the United States, help determine life expectancy, and allow comparisons of death trends with other countries

Death certificates

Details vary from state to state, but often include:

• Full name,

• Address,

• Birth date and birthplace,

• father’s name and birthplace,

• mother’s name and birthplace,

• If a veteran, the discharge or claim number,

• Education,

• Marital status and name of surviving spouse, if any,

• Date, place, and time of death, and,

• Cause of death.

Labor statistics

Types and prevalence of employers and industries in the areas, products manufactured, services provided.

Environmental Protection Agency

Toxic discharges from industry, agriculture, or other sources in the area where the patient lived

Interviews with patients and families

Qualitative data regarding where the patient’s place of employment, lifestyle, smoker or non-smoker, other relatives with cancer and what type of cancer, possible exposures to toxins

  1. 2.

    Identify three challenges health care providers experience that are related to collecting relevant data on patients’ SDOH. Suggest one potential response to each challenge.

    There are many challenges and these are a few examples:

Challenge

Response

Lack of standards for defining social determinants of health

Work within your organization and across organizations to be part of developing standards; be consistent within your own organization; provide input to national organizations working to define standards

Inadequate healthcare-based solutions for the core problems such as access to care, poverty and food insecurity

Develop partnerships with partners who can provide solutions, such as social work agencies and medical-legal partnerships

Reluctance of some providers to bring up sensitive topics such as abuse with patients

Educate providers—include opportunities to practice in with classmates before taking the skills to patients; allow clients to self-report via paper or electronic survey; ensure privacy during face-to-face conversations

  1. 3.

    You are a social worker helping a family that is struggling to obtain disability payments and health coverage for the husband, who was injured on his job as a construction worker. He has applied for disability and workmen’s compensation and been denied. The family is very frustrated with the “run around” he has gotten from the Social Security and Workmen’s Compensation offices and is suffering financially. Identify at least one external resource the health care provider could engage to help the family resolve this problem.

    The most useful resource to address denial of benefits is legal assistance through a medical-legal partnership. If an MLP is not available, the local Legal Aid Society is another option.

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Metzger, R., Beck, A.F., Henize, A.W. (2022). Leveraging Health and Community Data: Insights into Social Determinants of Health. In: Hübner, U.H., Mustata Wilson, G., Morawski, T.S., Ball, M.J. (eds) Nursing Informatics . Health Informatics. Springer, Cham. https://doi.org/10.1007/978-3-030-91237-6_16

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  • DOI: https://doi.org/10.1007/978-3-030-91237-6_16

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