Background: The approval of novel therapies for patients diagnosed with hematologic malignancies have improved survival outcomes but increased the challenge of aligning chemotherapy choices with patient preferences. We previously developed paper versions of a discrete choice experiment (DCE) and a best-worst scaling (BWS) instrument to quantify the treatment outcome preferences of patients with hematologic malignancies to inform shared decision making.
Objective: We aim to develop an electronic health care tool (EHT) to guide clinical decision making that uses either a BWS or DCE instrument to capture patient preferences. The primary objective of this study is to use both qualitative and quantitative methods to evaluate the perceived usability, cognitive workload (CWL), and performance of electronic prototypes that include the DCE and BWS instrument.
Methods: This mixed methods study includes iterative co-design methods that will involve healthy volunteers, patient-caregiver pairs, and health care workers to evaluate the perceived usability, CWL, and performance of tasks within distinct prototypes. Think-aloud sessions and semistructured interviews will be conducted to collect qualitative data to develop an affinity diagram for thematic analysis. Validated assessments (Post-Study System Usability Questionnaire [PSSUQ] and the National Aeronautical and Space Administration's Task Load Index [NASA-TLX]) will be used to evaluate the usability and CWL required to complete tasks within the prototypes. Performance assessments of the DCE and BWS will include the evaluation of tasks using the Single Easy Questionnaire (SEQ), time to complete using the prototype, and the number of errors. Additional qualitative assessments will be conducted to gather participants' feedback on visualizations used in the Personalized Treatment Preferences Dashboard that provides a representation of user results after completing the choice tasks within the prototype.
Results: Ethical approval was obtained in June 2021 from the Institutional Review Board of the University of North Carolina at Chapel Hill. The DCE and BWS instruments were developed and incorporated into the PRIME (Preference Reporting to Improve Management and Experience) prototype in early 2021 and prototypes were completed by June 2021. Heuristic evaluations were conducted in phase 1 and completed by July 2021. Recruitment of healthy volunteers began in August 2021 and concluded in September 2021. In December 2021, our findings from phase 2 were accepted for publication. Phase 3 recruitment began in January 2022 and is expected to conclude in September 2022. The data analysis from phase 3 is expected to be completed by November 2022.
Conclusions: Our findings will help differentiate the usability, CWL, and performance of the DCE and BWS within the prototypes. These findings will contribute to the optimization of the prototypes, leading to the development of an EHT that helps facilitate shared decision making. This evaluation will inform the development of EHTs to be used clinically with patients and health care workers.
International Registered Report Identifier (irrid): DERR1-10.2196/39586.
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http://dx.doi.org/10.2196/39586 | DOI Listing |
Appl Health Econ Health Policy
December 2024
Département de gestion, évaluation et politique de santé, School of Public Health, University of Montreal, Montreal, QC, Canada.
Background: The dead state can affect the value sets derived from discrete choice experiments (DCEs). Our aim was to empirically assess the direct impact of the immediate death state on health utilities using discrete choice experiment with time (DCE).
Methods: A sample of the general population in Quebec, Canada, completed two approaches: DCE followed by a best-worst scaling with time (BWS) (hereafter referred to as DCE), versus DCE followed by the dominated option and the immediate death state (hereafter referred to as DCE), both designed with the SF-6Dv2.
Eur J Health Econ
September 2024
School of Public Health, University of Montreal, Montreal, QC, Canada.
Objective: To empirically compare four preference elicitation approaches, the discrete choice experiment with time (DCE), the Best-Worst Scaling with time (BWS), DCE with BWS (DCE), and the Standard Gamble (SG) method, in valuing health states using the SF-6Dv2.
Methods: A representative sample of the general population in Quebec, Canada, completed 6 SG tasks or 13 DCE (i.e.
Patient Prefer Adherence
August 2024
School of Public Health, Fudan University, Shanghai, People's Republic of China.
BMC Cancer
July 2024
Johnson and Johnson, 66 Waterloo Road, Macquarie Park, NSW, 2113, Australia.
Background: Listening to patient voices is critical, in terms of how people experience their condition as well as their treatment preferences. This research explored the patient journey, therapy attributes and goals among treatment experienced adults with chronic lymphocytic leukemia (CLL). We sought to understand patient experiences, needs and expectations to identify areas for improvement of treatment and care delivery.
View Article and Find Full Text PDFVaccines (Basel)
May 2024
Pfizer Inc., New York, NY 10001, USA.
We assessed the impact of respiratory syncytial virus (RSV) preventive characteristics on the intentions of pregnant people and healthcare providers (HCPs) to protect infants with a maternal vaccine or monoclonal antibodies (mAbs). Pregnant people and HCPs who treated pregnant people and/or infants were recruited via convenience sample from a general research panel to complete a cross-sectional, web-based survey, including a discrete choice experiment (DCE) wherein respondents chose between hypothetical RSV preventive profiles varying on five attributes (effectiveness, preventive type [maternal vaccine vs. mAb], injection recipient/timing, type of medical visit required to receive the injection, and duration of protection during RSV season) and a no-preventive option.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!