Fortuna Daniela, Caselli Luana, Romoli Michele, Vignatelli Luca, Vaudano Anna Elisabetta, Mandrioli Jessica, Malagù Susanna, Costantini Massimo, Tibaldi Giuseppe, Gildoni Gabriela, Guarino Maria, Di Pasquale Giuseppe, Iaboli Luca, Alberghini Lucia, Fusconi Marco, Pacilli Angela Maria Grazia, Nava Stefano, Mancinelli Silvia, Rolli Maurizia
Department of Innovation in Healthcare and Social Services, Emilia-Romagna Region, Viale Aldo Moro 21, Bologna, 40127, Italy.
Neurology and Stroke Unit, Ospedale Bufalini, Cesena, Italy.
Popul Health Metr. 2025 Jul 31;23(1):42. doi: 10.1186/s12963-025-00404-x.
Although chronic diseases represent a growing global health priority, significant gaps remain in understanding the burden of multimorbidity. This study developed an original methodology to estimate the burden of thirty major chronic diseases at the individual patient level, in terms of Disability-Adjusted Life years (DALYs), Years Lived with Disability (YLD), and Years of Life Lost due to premature death (YLL).
The Disability weights (DWs) estimated by the Global Burden of Disease (GBD) study were integrated with information from healthcare databases. A panel of medical specialists established the criteria for assigning the level of severity, and thus a specific DW, to each chronic disease. The patient-centred YLD metric was estimated as the cumulative of the combined DWs over the previous ten years. We also measured the Disability Weight Fraction of each coexisting disease (DWF). We illustrated this method using healthcare databases from a large Italian region to assess the impact of chronic diseases and multimorbidity at progressive levels of analysis: health status of the regional chronic disease population, burden of individual chronic diseases and patient clinical complexity.
Unlike the standard GBD estimates, the new method provided precise metrics for multimorbidity, as shown by the comparison on the disability calculated for 4 main chronic diseases. Real-world estimates from the new method highlighted that comorbidity accounted for most of the YLD: for instance, about 88% of the YLD of patients with heart failure was explained by concomitant conditions. DALYs were higher among females than males in most age groups. In the younger groups, psychiatric conditions explained approximately 40% and 25% of YLD among males and females, respectively. Finally, the patient-centred YLD metric was a good predictor of death (c-statistic = 0.779).
This novel method provides insights into the measurement of multimorbidity, based on the disability fraction of each concomitant health condition, which is crucial for defining priority areas for healthcare interventions. The patient-centred estimates may serve to identify subgroups of chronic disease patients with specific healthcare needs and trajectories among a given population. Importantly, measuring the relative contribution of each disease to the patient's burden of multimorbidity favours the planning of multidisciplinary care pathways that are more responsive to individual needs.
尽管慢性病在全球卫生领域的重要性日益凸显，但在理解多重疾病负担方面仍存在显著差距。本研究开发了一种原创方法，以残疾调整生命年（DALYs）、残疾生活年（YLD）和过早死亡导致的生命损失年（YLL）来估计个体患者层面30种主要慢性病的负担。
将全球疾病负担（GBD）研究估计的残疾权重（DWs）与医疗保健数据库中的信息相结合。一个医学专家小组确定了为每种慢性病分配严重程度级别以及相应特定DW的标准。以患者为中心的YLD指标被估计为过去十年中合并DWs的累积值。我们还测量了每种共存疾病的残疾权重分数（DWF）。我们使用意大利一个大地区的医疗保健数据库来说明这种方法，以在不同分析层面评估慢性病和多重疾病的影响：地区慢性病患者的健康状况、个体慢性病负担以及患者临床复杂性。
与标准GBD估计不同，新方法为多重疾病提供了精确的指标，这在对4种主要慢性病计算的残疾情况比较中得到了体现。新方法的实际估计突出表明，合并症占YLD的大部分：例如，心力衰竭患者约88%的YLD可由伴随疾病解释。在大多数年龄组中，女性的DALYs高于男性。在较年轻的组中，精神疾病分别解释了男性和女性约40%和25%的YLD。最后，以患者为中心的YLD指标是死亡情况的良好预测指标（c统计量 = 0.779）。
这种新方法基于每种伴随健康状况的残疾分数，为多重疾病的测量提供了见解，这对于确定医疗保健干预的优先领域至关重要。以患者为中心的估计可用于识别特定人群中具有特定医疗保健需求和病程的慢性病患者亚组。重要的是，测量每种疾病对患者多重疾病负担的相对贡献有利于规划更能响应个体需求的多学科护理路径。
