The economic burden of diagnostic uncertainty on rare disease patients.

IF 2.7 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES BMC Health Services Research Pub Date : 2024-11-12 DOI:10.1186/s12913-024-11763-w
Lukas Willmen, Lukas Völkel, Tina Willmen, Thilo Deckersbach, Siegfried Geyer, Annette Doris Wagner
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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.

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诊断不确定性对罕见病患者造成的经济负担。
背景:罕见疾病往往需要很长时间才能确诊。没有确诊,往往就无法进行正确的治疗,而没有正确的治疗,患者就没有机会治愈或缓解症状。此外,罕见病还会给患者带来经济后果。本研究旨在调查罕见病在多大程度上影响了相关患者的收入和工作表现,以及在诊断中使用人工智能是否有可能减少经济损失:方法:分析了汉诺威医学院罕见炎症性系统疾病(肾脏受累)门诊 71 名患者在患病期间的工作表现和收入情况。收集数据时使用了世界卫生组织的健康和工作表现问卷(HPQ)。在对患者的访谈中,问卷共填写了四次:首次出现症状时、诊断决策支持系统(DDSS)建议正确诊断时、诊断时和当前状态时:结果:随着诊断奥德赛的开始,研究对象的月净收入平均下降了 5.32%,原因是工作表现下降或旷工。如果诊断正确,则可以获得原来甚至更好的 11.92% 的收入。与罕见血管炎患者相比,患有关节、肌肉和结缔组织受累的罕见疾病的患者因病造成的收入损失更为严重。如果使用残疾程度分类标准,收入损失将为 2.66%,而不是实际的 5.32%:结论:罕见疾病导致 28.17% 的患者暂时或长期失去收入。工作表现和收入损失与疾病类型有关,关节、肌肉或结缔组织疾病患者的工作表现和收入损失比罕见血管病患者更为明显。使用DDSS有可能通过更早的正确诊断来减少对患者收入的负面影响:回顾性注册。
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来源期刊
BMC Health Services Research
BMC Health Services Research 医学-卫生保健
CiteScore
4.40
自引率
7.10%
发文量
1372
审稿时长
6 months
期刊介绍: BMC Health Services Research is an open access, peer-reviewed journal that considers articles on all aspects of health services research, including delivery of care, management of health services, assessment of healthcare needs, measurement of outcomes, allocation of healthcare resources, evaluation of different health markets and health services organizations, international comparative analysis of health systems, health economics and the impact of health policies and regulations.
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