Abstract
BACKGROUND: It often takes a long time before a rare disease is diagnosed. Without a diagnosis, the right therapy often cannot be carried out and without the right therapy, the patients are denied the opportunity for a cure or relief from their symptoms. In addition, rare diseases can also have economic consequences for those affected. This study aimed to investigate the extent to which a rare disease affects the income and work performance of the patients concerned and whether the use of AI in diagnostics would have the potential to reduce economic losses. METHODS: The work performance and income of 71 patients of the outpatient clinic for rare inflammatory systemic diseases with renal involvement at Hannover Medical School were analyzed during the course of the disease. The WHO Health and Work Performance Questionnaire (HPQ) was used to collect data. During the patient interviews, the questionnaire was completed four times: at the onset of the first symptoms, when a diagnostic decision support system (DDSS) would have suggested the correct diagnosis, at the time of diagnosis and at the current status. RESULTS: With the onset of the diagnostic odyssey, the monthly net income of the patients under study dropped by an average of 5.32% due to lower work performance or work absenteeism. With the correct diagnosis, the original or even a better income of 11.92% could be achieved. Loss of income due to illness was more massive in patients with a rare disease with joint, muscle and connective tissue involvement than in patients with rare vasculitides. If a DDSS had been used, the loss of income would have been 2.66% instead of the actual 5.32%. CONCLUSION: Rare diseases resulted in temporary or existing income losses in 28.17% of the patients. Losses in work performance and income were related to the type of disease and were more pronounced in patients with joint, muscle or connective tissue disease than in patients with rare vasculitides. The use of a DDSS may have the potential to reduce the negative income effects of patients through earlier correct diagnosis. TRIAL REGISTRATION: Retrospectively registered.