 | The 131st Annual Meeting (November 15-19, 2003) of APHA |
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| The 131st Annual Meeting (November 15-19, 2003) of APHA |
Andrew Brunskill, MB, BS, MPH, Uniform Medical Plan, State of Washington., 1511 Third Avenue, Suite 201, Seattle, WA 98101, 206-521-2000, jaberwok@drizzle.com
It is increasingly recognized and recommended that health plan policy, like clinical practice, should be evidence based. Interpretable local and national data is a critical component of evidence for health policy. But in administrative and clinical practice there are numerous ways in which the data used can be misleading or incorrect in their presentation or interpretation. Errors in the use of data for policy may well be as significant as medical errors at the clinical level. In this talk I outline ten years of experience at the health plan level of some obvious and non obvious ways in which data used or produced by health plans can mislead. Examples will be provided which include data entry issues, selective reporting, lack of controls, improper extrapolation, seasonality, fraud, data inadequacy, misclassification, data selection & data timing. The ways in which these errors were recognized will be discussed. An attempt will be made to relate these errors to the Generic Error Modelling System (GEMS). However, additional examples of errors and suggestions as to systematic approaches to their detection and avoidance would be welcomed. “It is not so much the things that we don’t know that get us into trouble. It’s the things that we know that just ain’t so”. Attrib to Artemus Ward.
Learning Objectives:
Keywords: Data Collection, Policy/Policy Development
Presenting author's disclosure statement:
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.