Co-Production of Diagnostic Excellence – Patients, Clinicians, and Artificial Intelligence; Comment on “Achieving Diagnostic Excellence: Roadmaps to Develop and Use Patient-Reported Measures With an Equity Lens”

Articles in Press

Document Type : Commentary

Authors

1 Division of Hospital Medicine, Department of Medicine, UCSF at San Francisco General Hospital, San Francisco, CA, USA

2 Division of Clinical Informatics and Digital Transformation, Department of Medicine, University of California San Francisco, San Francisco, CA, USA

3 Division of Hospital Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA

Abstract

 Patients often experience long journeys within the health care system before obtaining a diagnosis. Though progress has been made in measuring the quality of diagnosis, existing measures largely fail to capture the diagnostic process from the patient’s perspective. McDonald et al.’s paper presents 7 overarching goals for the use of patient-reported measures (PRMs) in diagnostic excellence and presents visual roadmaps to guide the development, implementation, and evaluation of these measures. To accelerate the real-world use of PRMs, organizations should initially prioritize the use of patient-reported metrics that are already in development, such as patient-reported experience measures (PREMs). Pairing PRMs with artificial intelligence techniques, such as “diagnostic wayfinding” (analysis of electronic health record metadata to characterize clinician and patient behavior throughout the diagnostic process a dynamic diagnostic refinement process that also includes analysis of electronic health record data and metadata to characterize the diagnostic journey), should also improve diagnostic performance. Ultimately, combining patient-reported measures with technological advancements holds the potential to achieve true co-production of diagnostic excellence. 

Keywords

International Journal of Health Policy and Management

Articles in Press, Accepted Manuscript
Available Online from 19 May 2025

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History

  • Receive Date: 31 December 2024
  • Revise Date: 14 May 2025
  • Accept Date: 18 May 2025
  • First Publish Date: 19 May 2025

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