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 te...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
|
| Series: | Population Health Metrics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12963-025-00404-x |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849332127869435904 |
|---|---|
| author | Daniela Fortuna Luana Caselli Michele Romoli Luca Vignatelli Anna Elisabetta Vaudano Jessica Mandrioli Susanna Malagù Massimo Costantini Giuseppe Tibaldi Gabriela Gildoni Maria Guarino Giuseppe Di Pasquale Luca Iaboli Lucia Alberghini Marco Fusconi Angela Maria Grazia Pacilli Stefano Nava Silvia Mancinelli Maurizia Rolli |
| author_facet | Daniela Fortuna Luana Caselli Michele Romoli Luca Vignatelli Anna Elisabetta Vaudano Jessica Mandrioli Susanna Malagù Massimo Costantini Giuseppe Tibaldi Gabriela Gildoni Maria Guarino Giuseppe Di Pasquale Luca Iaboli Lucia Alberghini Marco Fusconi Angela Maria Grazia Pacilli Stefano Nava Silvia Mancinelli Maurizia Rolli |
| author_sort | Daniela Fortuna |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-8a6a251f2ad144c1bc248fbad119935c |
| institution | Kabale University |
| issn | 1478-7954 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | BMC |
| record_format | Article |
| series | Population Health Metrics |
| spelling | doaj-art-8a6a251f2ad144c1bc248fbad119935c2025-08-20T03:46:19ZengBMCPopulation Health Metrics1478-79542025-07-0123111810.1186/s12963-025-00404-xPatient-centred estimation of multimorbidity in chronic disease populations: a novel approach integrating global burden of disease metrics and healthcare administrative dataDaniela Fortuna0Luana Caselli1Michele Romoli2Luca Vignatelli3Anna Elisabetta Vaudano4Jessica Mandrioli5Susanna Malagù6Massimo Costantini7Giuseppe Tibaldi8Gabriela Gildoni9Maria Guarino10Giuseppe Di Pasquale11Luca Iaboli12Lucia Alberghini13Marco Fusconi14Angela Maria Grazia Pacilli15Stefano Nava16Silvia Mancinelli17Maurizia Rolli18Department of Innovation in Healthcare and Social ServicesDepartment of Innovation in Healthcare and Social ServicesNeurology and Stroke Unit, Ospedale BufaliniEpidemiology e Statistic Unit, IRCCS Istituto delle Scienze Neurologiche di BolognaDepartment of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio EmiliaDepartment of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio EmiliaNeurology and Stroke Unit, Ospedale BufaliniFondazione IRCCS Istituto Nazionale dei TumoriDepartment of Mental Health, Local Health AuthorityDepartment of Child and Adolescent Neuropsychiatry, Local Health AuthorityNeurology Unit, IRCCS-S. Orsola-MalpighiCoordination of the Cardiology and Cardiovascular Surgery NetworkLocal Health AuthorityDepartment of Innovation in Healthcare and Social ServicesDepartment of Internal Medicine - Rheumatic, Connective and Bone Metabolic Diseases, IRCCS-S. Orsola-MalpighiDepartment of Medical and Surgical Sciences (DIMEC), University of Bologna, IRCCS-SDepartment of Medical and Surgical Sciences (DIMEC), University of Bologna, IRCCS-SRespiratory and Critical Care Unit, Ospedale BufaliniDepartment of Innovation in Healthcare and Social ServicesAbstract 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.https://doi.org/10.1186/s12963-025-00404-xMultimorbidityPatient-centred burden of chronic diseaseDisability adjusted life yearsYears lived with disabilityDisability weight fraction attributable |
| spellingShingle | Daniela Fortuna Luana Caselli Michele Romoli Luca Vignatelli Anna Elisabetta Vaudano Jessica Mandrioli Susanna Malagù Massimo Costantini Giuseppe Tibaldi Gabriela Gildoni Maria Guarino Giuseppe Di Pasquale Luca Iaboli Lucia Alberghini Marco Fusconi Angela Maria Grazia Pacilli Stefano Nava Silvia Mancinelli Maurizia Rolli Patient-centred estimation of multimorbidity in chronic disease populations: a novel approach integrating global burden of disease metrics and healthcare administrative data Population Health Metrics Multimorbidity Patient-centred burden of chronic disease Disability adjusted life years Years lived with disability Disability weight fraction attributable |
| title | Patient-centred estimation of multimorbidity in chronic disease populations: a novel approach integrating global burden of disease metrics and healthcare administrative data |
| title_full | Patient-centred estimation of multimorbidity in chronic disease populations: a novel approach integrating global burden of disease metrics and healthcare administrative data |
| title_fullStr | Patient-centred estimation of multimorbidity in chronic disease populations: a novel approach integrating global burden of disease metrics and healthcare administrative data |
| title_full_unstemmed | Patient-centred estimation of multimorbidity in chronic disease populations: a novel approach integrating global burden of disease metrics and healthcare administrative data |
| title_short | Patient-centred estimation of multimorbidity in chronic disease populations: a novel approach integrating global burden of disease metrics and healthcare administrative data |
| title_sort | patient centred estimation of multimorbidity in chronic disease populations a novel approach integrating global burden of disease metrics and healthcare administrative data |
| topic | Multimorbidity Patient-centred burden of chronic disease Disability adjusted life years Years lived with disability Disability weight fraction attributable |
| url | https://doi.org/10.1186/s12963-025-00404-x |
| work_keys_str_mv | AT danielafortuna patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT luanacaselli patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT micheleromoli patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT lucavignatelli patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT annaelisabettavaudano patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT jessicamandrioli patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT susannamalagu patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT massimocostantini patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT giuseppetibaldi patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT gabrielagildoni patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT mariaguarino patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT giuseppedipasquale patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT lucaiaboli patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT luciaalberghini patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT marcofusconi patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT angelamariagraziapacilli patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT stefanonava patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT silviamancinelli patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata AT mauriziarolli patientcentredestimationofmultimorbidityinchronicdiseasepopulationsanovelapproachintegratingglobalburdenofdiseasemetricsandhealthcareadministrativedata |