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The good, the bad, and the ugly of multiple data sources

The good, the bad, and the ugly of multiple data sources. Barbara J. McMorris, PhD ONRS Seminar May 19, 2011 UMN School of Nursing. Types of Triangulation. Methodological Analysis Interdisciplinary Investigator Data. Why is Data Triangulation Important?.

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The good, the bad, and the ugly of multiple data sources

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  1. The good, the bad, and the ugly of multiple data sources Barbara J. McMorris, PhD ONRS Seminar May 19, 2011 UMN School of Nursing

  2. Types of Triangulation • Methodological • Analysis • Interdisciplinary • Investigator • Data

  3. Why is Data Triangulation Important? • Better research study & results • Reviewers getting savvier; asking for multiple sources of data • More “tools” for your research tool box

  4. Study 1: Administrative Claims Data + Self Reports

  5. Rhinitis Study Goals • Assess burden of allergic and non allergic rhinitis • What is the cost and utilization impact of treatment for rhinitis? • Evaluate providers’ perceptions of rhinitis burden on patients and severity of symptoms

  6. Rhinitis Survey Data Analysis % Agree/Strongly Agree

  7. Rhinitis Claims Data Analysis

  8. Reflection: “good-bad” • Known sampling frame • “Clean” processed data • Timing of data collection different • Lag in health care claims being loaded • Physical report of severity • Low response rate

  9. Results used in marketing • http://www.gsk.com/media/pressreleases/2007/2007_10_19_GSK1134.htm

  10. Study 2: Self Reports + Provider Care Flow Sheets

  11. RA Infusion Study Goals • Describe patient-reported outcomes due to bDMARD infusions: • satisfaction • lost productivity • pain/discomfort • Quantify the amount of time providers spend for initiating infusions (3 types) • Describe provider satisfaction with infusions

  12. Data Sources • Health care claims database • Provider survey • Patient Survey • Case Report Form • Infusion Care Flow Sheet

  13. RA Infusion Results

  14. Reflection: “good” • Good example of triangulation • Comprehensive picture of “burden” • Small sample size

  15. Results used in marketing • http://www.orencia.com/rheumatoid-arthritis-medication/orencia-infusion.aspx

  16. Study 3: Self Reports + Process Data + Official Records

  17. Broadway HS Study Goals • Provide a descriptive profile of pregnant and parenting teen girls • Compare outcomes for Broadway and comparison girls: • progress toward graduation • delaying a repeat birth • keeping children fully immunized

  18. Data Sources • Girls’ self reports on pre/post surveys • Case manager reports of time • Official Records • Program • School district • County

  19. Evaluation Results %

  20. County Data

  21. Reflection: kinda “ugly” • Using survey created/revised by others • Linking datasets – what is the link? • Consent to access official records? • What were the data collected for? • Who entered the data? • Budget enough time & money for both data management & analysis?

  22. Final Cautions about Data Triangulation • Need well-defined goals (no “fishing”) • Costly both in time and $$$ • May not solve bias/error issues • Replication is difficult • Know your “official” records sources and their limitations • Do you have “permission” to link data sets?

  23. “triangulation state of mind”* • “If you self consciously set out to collect and double-check findings using multiple sources and modes of evidence, the verification process will largely be built into the data-gathering process, and little more need be done than to report on one’s procedures.” *Miles & Huberman (1984: p.235)

  24. Thank you! Useful citations: Begley, CM. (1996). Using triangulation in nursing research. Journal of Advanced Nursing 24:122-128. Thurmond, VA. (2001). The Point of Triangulation. Journal of Nursing Scholarship 22(3): 253-258.

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