Translating clinical and patient-reported data to tailored shared decision reports with predictive analytics for knee and hip arthritis

INTRODUCTION: New informatics tools can transform evidence-based information to individualized predictive reports to serve shared decisions in clinic. We developed a web-based system to collect patient-reported outcomes (PROs) and medical risk factors and to compare responses to national registry data. The system generates predicted outcomes for individual patients and a report for use in clinic to support decisions. We present the report development, presentation, and early experience implementing this PRO-based, shared decision report for knee and hip arthritis patients seeking orthopedic evaluation. METHODS: Iterative patient and clinician interviews defined report content and visual display. The web-system supports: (a) collection of PROs and risk data at home or in office, (b) automated statistical processing of responses compared to national data, (c) individualized estimates of likely pain relief and functional gain if surgery is elected, and (d) graphical reports to support shared decisions. The system was implemented at 12 sites with 26 surgeons in an ongoing cluster randomized trial. RESULTS: Clinicians and patients recommended that pain and function as well as clinical risk factors (e.g., BMI, smoking) be presented to frame the discussion. Color and graphics support patient understanding. To date, 7891 patients completed the assessment before the visit and 56% consented to study participation. Reports were generated for 98% of patients and 68% of patients recalled reviewing the report with their surgeon. CONCLUSIONS: Informatics solutions can generate timely, tailored office reports including PROs and predictive analytics. Patients successfully complete the pre-visit PRO assessments and clinicians and patients value the report to support shared surgical decisions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11136-020-02557-8) contains supplementary material, which is available to authorized users.