Patient-centred estimation of multimorbidity in chronic disease populations: a novel approach integrating global burden of disease metrics and healthcare administrative data

Abstract

Background: 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).

Methods: 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.

Results: 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).

Conclusions: 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.

Keywords: Disability adjusted life years; Disability weight fraction attributable; Multimorbidity; Patient-centred burden of chronic disease; Years lived with disability.

Fig. 1

Main steps of the patient-centred BoD methodology (all the metrics are estimated for an example patient k) Legend: DWs = Disability Weights; yld = years lived with disability, calculated by summing up the DWs of the disease (in the case of a single chronic disease) or the combined DWs of 2 or more coexisting diseases (in the case of multimorbidity) of each year; dwfi = disability weight fraction of a specific disease, calculated as the ratio of the yld of that disease to the sum of the yld of all coexisting diseases; dwai = disability weight attributable to a specific disease, calculated as the dwfi re-proportioned to the combined DWs of the coexisting chronic diseases; yll = years of life lost due to premature death, calculated for each deceased patient as the difference between the actual and expected age of death; dalys = disability-adjusted life years, calculated as the sum of the yld and yll components

Fig. 2

DALYs per 1,000 inhabitants (A) and DWFs (B) of chronic disease categories, by age group (A) DALYs are indicated as YLD + YLL. Each chronic disease category is reported as DWA, i.e. Disability Weight attributable to the category, reproportioned to the overall YLD component (B) Each chronic disease category is reported as DWF, i.e. Disability Weight Fraction of the overall YLD component

Fig. 3

DALYs per 1,000 inhabitants by age group in females (A) and males (B); DWF of each chronic disease category by age group in females (C) and males (D) (A) and (B) DALYs are indicated as YLD + YLL. Each chronic disease category is reported as DWA, i.e. Disability Weight attributable to the category, reproportioned to the overall YLD component (C) and (D) Each chronic disease category is reported as DWF, i.e. Disability Weight fraction of the overall YLD component

Fig. 4

DALYs (and their YLD and YLL components) for the 11 chronic disease categories included in the study From the innermost to the outermost circle: - Ranking of DALYs for the 11 diagnostic categories; - YLD component (broken down into DWAs associated with the individual chronic diseases included in the diagnostic category) + YLL component for each diagnostic category; - Proportion (%) of YLD explained by comorbidities (0, 1, 2 or more) DALYs = Disability-Adjusted Life Years; YLD = Years Lived with Disability; DWA = Disability Weight Attributable to single chronic diseases; YLL = Years of Life Lost due to premature death

Fig. 5

Composition of YLD of 4 example chronic diseases: COPD (A); Alzheimer’s disease and other dementias (B); Depression (C); Heart failure (D) Numbers are DWFs (%) of concomitant diseases, accompanied by their frequency (in brackets). Colour intensity indicates the degree of disability attributable to the individual disease and varies according to the DWF (concomitant diseases with the lowest values are not shown)

Fig. 6

(A) Relation between yld and probability of mortality (with death = 1; 95% confidence limits); (B) Relation between yld and number of pathologies

Fig. 7

Comparison between GBD and new method estimates, in a cross-sectional perspective