Affinity Chart Analysis: A Method for Structured Collection, Aggregation, and Response to Customer Needs in Radiology.

Published

Journal Article

OBJECTIVE: The objective of this study is to analyze implementation of the voice-of-the-customer method to assess the current state of image postprocessing and reporting delivered by a radiology department and to plan improvements on the basis of referring physicians' preferences. SUBJECTS AND METHODS: The voice-of-the-customer method consisted of discovery, analysis, and optimization phases. Fifty referring physicians were invited to be interviewed. Interviews addressed the topics of structure, process, outcome, and support. Interviews were dissected into individual statements categorized as fact or feeling. Statements were grouped to find collective voices. Improvements were compiled from affinity charts and were processed by identifying insights. RESULTS: Ninety-four percent (47/50) of physicians participated, generating 352 statements (81 facts and 271 feelings) that subsequently underwent affinity chart clustering. The resultant affinity charts covered distinct themes: "we need you to know us better," "we need you to consider our workflow," "we need more from your services," "we want to review your data in certain ways," and "we want to do more with you." As a result of the insights gained, the following optimizations were implemented: a software application that improves study requesting, performance tracking, study prioritization, and longitudinal data archiving; six prototype reports containing tabulated data and annotated images; two prototype longitudinal reporting templates assessing aneurysm evolution and treatment-induced changes in organ size over time; and a teaching curriculum for trainees. CONCLUSION: This study has shown the clinical feasibility to assess the current state of image postprocessing and reporting and to implement improvements of and investments in image postprocessing and reporting infrastructure on the basis of referring physicians' preferences using the voice-of-the-customer method.

Full Text

Duke Authors

Cited Authors

  • Boll, DT; Rubin, GD; Heye, T; Pierce, LJ

Published Date

  • April 2017

Published In

Volume / Issue

  • 208 / 4

Start / End Page

  • W134 - W145

PubMed ID

  • 28140618

Pubmed Central ID

  • 28140618

Electronic International Standard Serial Number (EISSN)

  • 1546-3141

Digital Object Identifier (DOI)

  • 10.2214/AJR.16.16673

Language

  • eng

Conference Location

  • United States