Framing Bias in the Interpretation of Quality Improvement Data: Evidence From an Experiment

Author:

Ballard Andrew1

Affiliation:

1. School of Public Affairs and Administration, Rutgers University, Newark, NJ, USA.

Abstract

Background: A growing body of public management literature sheds light on potential shortcomings to quality improvement (QI) and performance management efforts. These challenges stem from heuristics individuals use when interpreting data. Evidence from studies of citizens suggests that individuals’ evaluation of data is influenced by the linguistic framing or context of that information and may bias the way they use such information for decision-making. This study extends prospect theory into the field of public health QI by utilizing an experimental design to test for equivalency framing effects on how public health professionals interpret common QI indicators. Methods: An experimental design utilizing randomly assigned survey vignettes is used to test for the influence of framing effects in the interpretation of QI data. The web-based survey assigned a national sample of 286 city and county health officers to a "positive frame" group or a "negative frame" group and measured perceptions of organizational performance. The majority of respondents self-report as organizational leadership. Results: Public health managers are indeed susceptible to these framing effects and to a similar degree as citizens. Specifically, they tend to interpret QI information presented in a "positive frame" as indicating a higher level of performance as the same underlying data presenting in a "negative frame." These results are statistically significant and pass robustness checks when regressed against control variables and alternative sources of information. Conclusion: This study helps identify potential areas of reform within the reporting aspects of QI systems. Specifically, there is a need to fully contextualize data when presenting even to subject matter experts to reduce the existence of bias when making decisions and introduce training in data presentation and basic numeracy prior to fully engaging in QI initiatives.

Publisher

Maad Rayan Publishing Company

Subject

Health Policy,Health Information Management,Leadership and Management,Management, Monitoring, Policy and Law,Health(social science)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3