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Using secondary information to inform public policy

Full APA Reference

Blake, C. L. (2012, September). Using secondary information to inform public policy. Paper presented at Internet, Politics, Policy 2012, Oxford, United Kingdom.

Publication Abstract

Scientific literature plays a critical role in informing public health policy. For example, systematic reviews by the Cochrane Collaboration and Health Technology Assessment play an important role in evidence based medicine which in turn can influence government policies on standards of health care. In epidemiology meta-analytic results (a quantitative form of a systematic review) can influence legislation, product label requirements, and public services.

The systematic review process is typically a group activity that requires users to identify a comprehensive collection of articles, extract information from those articles, verify the accuracy of those extracted facts, and analyze the extracted facts using either qualitative or quantitative techniques (Blake & Pratt, 2006). Although systematic reviews accurately capture evidence, the process is time-consuming, taking 28 months from the original conception through to publication (Petrosino, 1999) and 1139 hours (Allen & Olkin, 1999). With more than 21 million citations in MEDLINE and an additional 1900 new citations added every week, the manual techniques currently used are becoming increasingly difficult to apply. Consider a breast cancer expert. It would be difficult, but necessary for her to consider the 33,883 articles published on breast cancer during the 28 months required to conduct a systematic review. Faced with the daunting task of sifting through currently available and recently added articles, our breast cancer expert may turn to other strategies to reduce the number of articles, such as constraining her hypothesis or her selection criterion. However, both of these constraints introduce undesirable biases, and thus reduce the validity of her review to inform public policy.

The second key challenge of a systematic review is that articles considered in are drawn from published literature and thus may suffer from publication bias, which is when articles that find statistically significant findings are more likely to be published than articles that do not show statistical significance, even though the methodology of the both study are the same. “For any given research area, one cannot tell how many studies have been conducted but never reported. The extreme view of the ""file drawer problem"" is that journals are filled with the 5% of the studies that show Type I errors, while the file drawers are filled with the 95% of the studies that show nonsignificant results.” (Rosenthal, 1979)