Design of an algorithm for the diagnostic approach of patients with joint pain.

BACKGROUND: Rheumatic diseases are a reason for frequent consultation with primary care doctors. Unfortunately, there is a high percentage of misdiagnosis. OBJECTIVE: To design an algorithm to be used by primary care physicians to improve the diagnostic approach of the patient with joint pain, and thus improve the diagnostic capacity in four rheumatic diseases. METHODS: Based on the information obtained from a literature review, we identified the main symptoms, signs, and paraclinical tests related to the diagnosis of rheumatoid arthritis, spondyloarthritis with peripheral involvement, systemic lupus erythematosus with joint involvement, and osteoarthritis. We conducted 3 consultations with a group of expert rheumatologists, using the Delphi technique, to design a diagnostic algorithm that has as a starting point "joint pain" as a common symptom for the four diseases. RESULTS: Thirty-nine rheumatologists from 18 countries of Ibero-America participated in the Delphi exercise. In the first consultation, we presented 94 items to the experts (35 symptoms, 31 signs, and 28 paraclinical tests) candidates to be part of the algorithm; 74 items (25 symptoms, 27 signs, and 22 paraclinical tests) were chosen. In the second consultation, the decision nodes of the algorithm were chosen, and in the third, its final structure was defined. The Delphi exercise lasted 8 months; 100% of the experts participated in the three consultations. CONCLUSION: We present an algorithm designed through an international consensus of experts, in which Delphi methodology was used, to support primary care physicians in the clinical approach to patients with joint pain. Key Points • We developed an algorithm with the participation of rheumatologists from 18 countries of Ibero-America, which gives a global vision of the clinical context of the patient with joint pain. • We integrated four rheumatic diseases into one tool with one common symptom: joint pain. It is a novel tool, as it is the first algorithm that will support the primary care physician in the consideration of four different rheumatic diseases. • It will improve the correct diagnosis and reduce the number of paraclinical tests requested by primary care physicians, in the management of patients with joint pain. This point was verified in a recently published study in the journal Rheumatology International (reference number 31).

The effect of an educational intervention, based on clinical simulation, on the diagnosis of rheumatoid arthritis and osteoarthritis.

OBJECTIVE: The aim of the present study was to evaluate the effectiveness of an educational tool for general physicians, based on rheumatological clinical simulation, for the diagnosis of rheumatoid arthritis and osteoarthritis. METHODS: A randomized clinical study was carried out, in which the physician research subjects were assigned to one of two groups: the experimental group (educational intervention for rheumatoid arthritis with clinical simulation) or the control group (educational intervention for the basic aspects of the diagnosis and treatment of osteoporosis). Four weeks after the educational intervention, the members of both groups completed an examination that included four clinical cases with real patients, two clinical cases with two clinical simulation models and six virtual clinical cases. In this examination, the participants noted clinical findings, established a diagnosis and defined the complementary tests they would request, if necessary, to corroborate their diagnosis. RESULTS: A total of 160 doctors participated (80 in the active educational intervention for rheumatoid arthritis and 80 in the control group), of whom 89 were women (56%). The mean age was 35 (standard deviation 7.7) years. Success was defined as a physician correctly diagnosing at least 10 of the 12 cases presented. A significant difference of 81.3% (95% confidence interval 72-90%; p < 0.001) in success was found in favour of the active group (88.8% versus 7.5%). A greater number of correct answers was found in the active group compared with the control group in the detection of clinical findings and in the number of complementary tests requested (p < 0.001). CONCLUSIONS: The study showed the effectiveness of an educational intervention based on clinical simulation to improve the diagnostic approach to rheumatoid arthritis and osteoarthritis. The results open a new horizon in the teaching of rheumatology.