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Interdisciplinary research on patient-provider communication: a cross-method comparison.
Wen-Ying Sylvia Chou1, Paul Han, Alison Pilsner
1Health Communication and Informatics Research Branch, National Cancer Institute, Bethesda, MD 20892, USA. chouws@mail.nih.gov
Communication & Medicine
|May 24, 2012
Summary
Assessing patient-provider communication requires careful method selection. This study compared three methods, finding that simple ratings differed significantly from detailed analyses like RIAS and discourse analysis.
Area of Science:
- Medical Education
- Health Communication
- Qualitative Research Methods
Background:
- Effective patient-provider communication is crucial for quality healthcare.
- Various methods exist for assessing communication, including satisfaction surveys and direct observation.
- Understanding the strengths and limitations of each assessment method is vital for selecting appropriate tools.
Purpose of the Study:
- To compare three distinct methods for assessing patient-provider communication using the same dataset.
- To evaluate the utility of dichotomized ratings, Roter Interaction Analysis System (RIAS), and inductive discourse analysis.
- To explore the potential of an integrated assessment approach.
Main Methods:
- Analysis of ten videotaped simulated patient-student encounters.
- Application of three assessment techniques: dichotomized Standardized Patient (SP) ratings, RIAS, and inductive discourse analysis.
- Pilot testing of a combined assessment approach by blinded coders.
Main Results:
- Dichotomized SP ratings showed a stark contrast between good and poor communication, which was not reflected in RIAS or discourse analysis.
- Each method yielded different insights into communication dynamics.
- An integrated approach combining qualitative and quantitative data showed promise.
Conclusions:
- Different assessment methods for patient-provider communication yield distinct results.
- Simple rating scales may oversimplify complex communication interactions.
- An integrative approach offers a more nuanced and quantifiable evaluation of clinical encounters.
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