Patient Preference and Adherence (Jun 2024)

Comparing Methods for Identifying Post-Market Patient Preferences at the Point of Decision-Making: Insights from Patients with Chronic Pain Considering a Spinal Cord Stimulator Device

  • Golembiewski EH,
  • Leon-Garcia M,
  • Gravholt DL,
  • Brito JP,
  • Spatz ES,
  • Bendel MA,
  • Montori VM,
  • Maraboto AP,
  • Hartasanchez SA,
  • Hargraves IG

Journal volume & issue
Vol. Volume 18
pp. 1325 – 1344

Abstract

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Elizabeth H Golembiewski,1 Montserrat Leon-Garcia,1– 3 Derek Loy Gravholt,1 Juan P Brito,1 Erica S Spatz,4 Markus A Bendel,5 Victor M Montori,1 Andrea P Maraboto,1 Sandra A Hartasanchez,1 Ian G Hargraves1 1Knowledge and Evaluation (KER) Unit, Mayo Clinic, Rochester, MN, USA; 2Biomedical Research Institute Sant Pau (IIB Sant Pau), Barcelona, Spain; 3Department of Pediatrics, Obstetrics, Gynaecology and Preventive Medicine, Universidad Autónoma de Barcelona, Barcelona, Spain; 4Division of Cardiovascular Medicine, School of Medicine, Yale University, New Haven, CT, USA; 5Division of Pain Medicine, Mayo Clinic, Rochester, MN, USACorrespondence: Ian G Hargraves, Knowledge and Evaluation Research (KER) Unit, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA, Email [email protected]: 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.Keywords: patient preferences, decision making, regulatory, preference identification, preference elicitation

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