https://orcid.org/0000-0003-1015-3935
Abstract
Purpose
To compare three methods for identifying patient preferences (MIPPs) at the point of decision-making: analysis of video-recorded patient-clinician encounters, post-encounter interviews, and post-encounter surveys.
Patients and Methods
For the decision of whether to use a spinal cord stimulator device (SCS), a video coding scheme, interview guide, and patient survey were iteratively developed with 30 SCS decision-making encounters in a tertiary academic medical center pain clinic. Burke’s grammar of motives was used to classify the attributed source or justification for a potential preference for each preference block. To compare the MIPPs, 13 patients’ encounters with their clinician were video recorded and subsequently analyzed by 4 coders using the final video coding scheme. Six of these patients were interviewed, and 7 surveyed, immediately following their encounters.
Results
For videos, an average of 66 (range 33–106) sets of utterances potentially indicating a patient preference (a preference block), surveys 33 (range 32–34), and interviews 25 (range 18–30) were identified. Thirty-eight unique themes (75 subthemes), each a preference topic, were identified from videos, surveys 19 themes (12 subthemes), and interviews 39 themes (54 subthemes). The proportion of preference blocks that were judged as expressing a preference that was clearly important to the patient or affected their decision was highest for interviews (72.8%), surveys (68.0%), and videos (27.0%). Videos mostly attributed preferences to the patient’s situation (scene) (65%); interviews, the act of receiving or living with SCS (43%); surveys, the purpose of SCS (40%).
Conclusion
MIPPs vary in the type of preferences identified and the clarity of expressed preferences in their data sets. The choice of which MIPP to use depends on projects’ goals and resources, recognizing that the choice of MIPP may affect which preferences are found.
Acknowledgments
Montserrat León-García is a doctoral candidate for the Ph.D. in Methodology of Biomedical Research and Public Health, Universitat Autònoma de Barcelona, Barcelona, Spain; and this study will be part of her thesis dissertation.
Disclosure
Victor Montori works at Mayo Clinic’s Knowledge and Encounter Research Unit where we design, test, implement and disseminate shared decision-making interventions. We release free to use and derive no income from their use. The authors report no other conflicts of interest in this work.