Data Mining Strategies for Shaping Nursing and Health Policy Agendas

Abstract

Data mining of electronic databases is becoming more popular as a method for researchers to study issues in the health policy arena. The advantages of using electronic databases, such as the decreased investments in time and costs associated with subject recruitment and data collection, contribute to its appeal. Despite these features, the use of electronic databases to address health policy issues in nursing has been limited. This article discusses potential uses of secondary analysis for nursing research and outlines the steps involved in the process of data mining. Examples of health services research using samples generated from electronic databases support the discussion. The growing popularity of secondary analyses has given rise to concerns regarding the protection of patient rights and confidentiality. The authors discuss steps taken by federal agencies and institutional review boards to ensure that data are protected while preserving the research potential of this method of analysis.

Get full access to this article

View all access options for this article.

References

Aiken, L. H. , Smith, H. L. , & Lake, E. T. (1994). Lower Medicare mortality among a set of hospitals known for good nursing care. Medical Care, 32, 771-787.

Cheung, R. B. (1997). Prevention and recognition of deep venous thrombosis and pulmonary embolism. International Journal of Trauma Nursing, 3(3), 91-92.

Diers, D. , & Bozzo, J. (1999). Using administrative data for practice and management. Nursing Economics, 17, 233-238.

Field, M. J. , Tranquada, R. E. , & Feasley, J. F. (1995). Health services research: Work force and educational issues. Washington DC: National Academy Press.

Freiman, M. P. , & Altman, B. M. (1999). Advance directives among nursing home residents: Health care cost and utilization project. Unpublished manuscript.

Health Insurance Portability and Accountability Act of 1996, Pub. L. No. 104.191, F of title II. 45 CFR Parts 160 and 162 (HCFA-0149-F) RIN 0938-A158 (pp. 60313-50372). (1996, August 21).

Institute of Medicine . (2000). Protecting data privacy in health services research (Executive Summary, pp. 1-15). Committee on the Role of Institutional Review Boards in Health Services Research Data Privacy Protection. Washington, DC: National Academy Press.

Jairath, N. , & Fain, J. A. (1999). A strategy for converting clinical data into research databases. Nursing Research, 48, 340-344.

Kovner, C. , & Gergen, P. J. (1998). Nurse staffing levels and adverse events following surgery in U.S. hospitals. Image: Journal of Nursing Scholarship, 30, 315-321.

10.

Kovner, C. T. , Jones, B. J. , & Gergen, P. J. (2000). Nurse staffing in acute care hospitals, 1990-1996. Policy, Politics, & Nursing Practice, 1, 194-204.

11.

Mattison, R. (2001). Data warehousing: Strategies, technologies and techniques. Retrieved August 2, 2001, from ftp://ftp.spss.com/pub/web/wp/DMWP.pdf

12.

Moody, L. E. , Small, B. B. , & Jones, C. B. (in press). Advance directive preferences of functionally and cognitively impaired nursing home residents in the United States. Journal of Applied Gerontology.

13.

National Academy of Sciences . (1998). Topics in health services research. Retrieved May 25, 2001, from http://www4.nationalacademies.org/IOM/IOMHome.nsf/Pages/MSHSRbox2

14.

National Health Care Survey Workshop . (2000, October). National Health Care Survey. Seminar presented at the Seminars in Health Services Research Methods: Using Federal and State Databases, Georgetown University Conference Center, Washington, DC.

15.

Office for Civil Rights . (n.d.). OCR HIPAA Privacy TA 164.512I.001. Retrieved October 13, 2001, from http://www.hhs.gov/ocr/hipaa/research.html

16.

Patterson, T. L. , & Jeste, D. V. (1999). The potential impact of the baby-boom generation on substance abuse among the elderly. Psychiatric Services, 50(9), 1184-1188.

17.

Polit, D. , & Hungler, B. P. (1999). Nursing research: Principles and methods. Philadelphia: Lippincott.

18.

Pollack, C. D. (1999). Methodological considerations with secondary analyses. Outcomes Management for Nursing Practice, 3, 147-152.

19.

Rhoades, J. , Potter, D.E.B. , & Krauss, N. (1998). Nursing homes—Structure and selected characteristics, 1996 (MEPS Research Findings No. 4; AHRQ Pub. No. 98-0006). Rockville, MD: Agency for Health Research and Quality.

20.

Schonfeld, L. , & Dupree, L. W. (1999). Alcohol use and misuse in older adults. Reviews in Clinical Gerontology, 9(2), 151-162.

21.

Shah, B. V. , Sample, A. T. , Barnwell, B. G. , & Bieler, G. S. (1995). SUDAAN user’s manual: Software for the statistical analysis of correlated data. Research Triangle Park, NC: Research Triangle Institute.

22.

SPSS . (n.d.). More on what data mining is—And isn’t. Retrieved August, 2, 2001, from http://www.spss.com/datamine/what2.htm

23.

Stiles, P. , & Schonfeld, L. (2001). Use of the Florida public mental health system by older adults. Report to USF Institute on Aging. Tampa: University of South Florida, the Louis de la Parte Florida Mental Health Institute.

24.

Young, W. B. , & Ryu, H. (2000). Secondary data for policy studies: Benefits and challenges. Policy, Politics, & Nursing Practice, pp. 302-330.