Patient and Healthcare Provider Priorities for Risk Prediction of Hospital Readmission: A Nominal Group Technique...

Area of Science:

• Healthcare research
• Patient safety
• Predictive modeling

Background:

• Hospital readmissions affect nearly 10% of adults within 30 days.
• Existing readmission risk models often lack effectiveness and user-centered design.
• Identifying patient and provider priorities is crucial for developing effective prediction frameworks.

Purpose of the Study:

• To identify patient and healthcare provider priorities for hospital readmission risk prediction.
• To inform the development of a novel readmission risk prediction framework tailored to user needs.

Main Methods:

• Nominal group technique (NGT) was employed with 22 participants (patients, caregivers, clinicians) in Alberta, Canada.
• In-person and virtual meetings were conducted between February and April 2025.
• Participants ranked candidate predictors and features for readmission risk prediction tools.

Main Results:

• Patients prioritized tools that inform them and aid discharge planning.
• Clinicians focused on a 30-day risk horizon and discharge summary alerts.
• Both groups supported targeting all unplanned readmissions and identified social determinants of health and lab markers as key predictors.

Conclusions:

• Patient and provider priorities for readmission risk prediction differ from current models.
• These identified priorities can guide the creation of new, user-centered readmission prediction tools.
• The findings support the development of novel frameworks to enhance patient care and reduce readmissions.