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Published on: October 16, 2016
The Effect of Triage Assessments on Identifying Inflammatory Arthritis and Reducing Rheumatology Wait Times in
Vandana Ahluwalia1,2, Sydney Lineker3,4, Raquel Sweezie3,4
1From the Ontario (Canada) Rheumatology Association, Ontario Best Practices Research Initiative, and the Arthritis Society. vandana@sympatico.ca.
Objective:
We evaluated the influence of triage assessments by extended role practitioners (ERP) on improving timeliness of rheumatology consultations for patients with suspected inflammatory arthritis (IA) or systemic autoimmune rheumatic diseases (SARD).
Methods:
Rheumatologists reviewed primary care providers' referrals and identified patients with inadequate referral information, so that a decision about priority could not be made. Patients were assessed by an ERP to identify those with IA/SARD requiring an expedited rheumatologist consult. The time from referral to the first consultation was determined comparing patients who were expedited to those who were not, and to similar patients in a usual care control group identified through retrospective chart review.
Results:
Seven rheumatologists from 5 communities participated in the study. Among 177 patients who received an ERP triage assessment, 75 patients were expedited and 102 were not. Expedited patients had a significantly shorter median (interquartile range) wait time to rheumatologist consult: 37.0 (24.5-55.5) days compared to non-expedited patients [105 (71.0-135.0) days] and controls [58.0 (24.0-104.0) days]. Accuracy comparing the ERP identification of IA/SARD to that of the rheumatologists was fair (κ 0.39, 95% CI 0.25-0.53).
Conclusion:
Patients triaged and expedited by ERP experienced shorter wait times compared to usual care; however, some patients with IA/SARD were missed and waited longer. Our findings suggest that ERP working in a triage role can improve access to care for those patients correctly identified with IA/SARD. Further research needs to identify an ongoing ERP educational process to ensure the success of the model.
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