Searchable Title

Improving Interpretation of Publically Reported Statistics on Health and Healthcare: The Figure Interpretation Assessment Tool (FIAT-Health). Copyright: Creative Commons License.

Reference Type

Journal Article

Authors, Section

Gerrits, R. G.; Kringos, D. S.; van den Berg, M. J.; Klazinga, N. S.

Title, Section

Improving Interpretation of Publically Reported Statistics on Health and Healthcare: The Figure Interpretation Assessment Tool (FIAT-Health). Copyright: Creative Commons License.

Publication Year

2018

Journal Title

Health Research Policy and Systems

Volume

16

Issue

1

Pages

20

Availability

online

PMID

PMID: 29514711

DOI

10.1186/s12961-018-0279-z

Abstract

BACKGROUND: Policy-makers, managers, scientists, patients and the general public are confronted daily with figures on health and healthcare through public reporting in newspapers, webpages and press releases. However, information on the key characteristics of these figures necessary for their correct interpretation is often not adequately communicated, which can lead to misinterpretation and misinformed decision-making. The objective of this research was to map the key characteristics relevant to the interpretation of figures on health and healthcare, and to develop a Figure Interpretation Assessment Tool-Health (FIAT-Health) through which figures on health and healthcare can be systematically assessed, allowing for a better interpretation of these figures. METHODS: The abovementioned key characteristics of figures on health and healthcare were identified through systematic expert consultations in the Netherlands on four topic categories of figures, namely morbidity, healthcare expenditure, healthcare outcomes and lifestyle. The identified characteristics were used as a frame for the development of the FIAT-Health. Development of the tool and its content was supported and validated through regular review by a sounding board of potential users. RESULTS: Identified characteristics relevant for the interpretation of figures in the four categories relate to the figures' origin, credibility, expression, subject matter, population and geographical focus, time period, and underlying data collection methods. The characteristics were translated into a set of 13 dichotomous and 4-point Likert scale questions constituting the FIAT-Health, and two final assessment statements. Users of the FIAT-Health were provided with a summary overview of their answers to support a final assessment of the correctness of a figure and the appropriateness of its reporting. CONCLUSIONS: FIAT-Health can support policy-makers, managers, scientists, patients and the general public to systematically assess the quality of publicly reported figures on health and healthcare. It also has the potential to support the producers of health and healthcare data in clearly communicating their data to different audiences. Future research should focus on the further validation of the tool in practice.

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