Background Metabolic multimorbidity, characterized by the clustering of metabolic dysfunction-associated steatotic liver disease (MASLD, formerly NAFLD) and metabolic syndrome (MetS), is increasingly recognized in young adults and may reflect early systemic metabolic dysfunction. However, simple biomarkers for identifying metabolic abnormalities in asymptomatic populations remain limited. Objective To evaluate the ALT/AST ratio as a marker of metabolic multimorbidity and examine its association with modifiable behavioral factors. Methods This community-based cross-sectional study included 3,796 asymptomatic adults aged 20–40 years. Moderate-to-severe fatty liver was assessed by ultrasonography. The discriminatory performance of the ALT/AST ratio was evaluated using ROC analysis and compared with ALT, white blood cell count, and neutrophil-to-lymphocyte ratio. Multivariable logistic regression identified independent associations. Results An ALT/AST ratio >1.3 showed moderate discriminatory performance for fatty liver (AUC 0.791) and MetS (AUC 0.780), with modestly improved discrimination compared with ALT alone and inflammatory markers, particularly in reclassification analyses. Individuals with ALT/AST >1.3 were more likely to have fatty liver (OR 6.13, 95% CI 5.15–7.30) and MetS (OR 5.81, 95% CI 4.61–7.34). Regular physical activity and dental scaling were associated with lower odds of metabolic abnormalities, whereas smoking and betel nut chewing were associated with higher odds of metabolic abnormalities. Conclusion The ALT/AST ratio was associated with fatty liver and metabolic syndrome in young adults and showed moderate discriminatory performance. Further longitudinal and external validation is needed before clinical implementation.
Background Obesity and multimorbidity are increasing challenges for public health. While obesity is a well-recognized risk factor for multimorbidity, evidence commonly comes from cross-sectional studies using body mass index (BMI). Evidence on the body roundness index (BRI), a novel indicator of central obesity, remains limited. Objectives This study assessed midlife obesity as a risk factor for multimorbidity in a Finnish population cohort during 23 years of follow-up. Methods A total of 1007 participants born between 1933 and 1956 and living in the Savitaipale municipality were enrolled between 1994 and 1996. Baseline data were collected using questionnaires and clinical examinations. Information on 38 chronic diseases was obtained from health registers. Obesity was assessed using BMI, waist circumference (WC), and BRI. Cox proportional hazards models estimated associations with incident multimorbidity, and receiver operating characteristic (ROC) analysis was used to derive BMI, WC and BRI thresholds with the best sensitivity–specificity balance. Results Over 23 years, obesity defined by BMI and WC, as well as higher BRI, was associated with increased multimorbidity risk. Hazard ratios ranged from 1.52 (95% CI: 1.21–1.92) to 2.17 (95% CI: 1.59–2.97) in women and from 2.41 (95% CI: 1.82–3.19) to 2.79 (95% CI: 2.00–3.90) in men, depending on obesity and multimorbidity definitions. ROC-derived thresholds for multimorbidity prediction were: BMI 26.4 in women and 26.1 in men; WC 76.3 cm and 93.3 cm; and BRI 3.41 and 3.70, respectively. Conclusion This 23-year study highlights midlife obesity as a risk factor for multimorbidity in later life.
Background This study aims to investigate the extent to which two frequently used multimorbidity measures, the Charlson Comorbidity Index (CCI) and the 2+ count of chronic diseases, are underestimated when primary care data are absent, and to examine if this varies by sociodemographic factors. Methods This register-based study included adults, aged 60 years and older, living in Stockholm, Sweden from 2017-2022 (n=497736). Multimorbidity was operationalized as 1) 2+ chronic diseases from a list of 60 and 2) CCI score of 2+. The multimorbidity prevalences were calculated using only outpatient specialist and hospital data, then after adding primary care data. The proportion of the prevalence underestimated without primary care data was estimated for both measures. Stratified analyses were conducted to assess the underestimation by age, sex, education, cohabitation, and care status. Findings Without primary care data, approximately 20% of individuals with multimorbidity were missed (2+count: 19.4%,95%CI:19.3%-19.5%; 2+CCI: 23.9%,95%CI:23.8%-24.0%). The proportion of missed cases was highest among community-dwelling individuals (2+count: 21.0%,95%CI:20.8%-21.1%; 2+CCI: 25.5%,95%CI:25.3%-25.6%) and decreased with greater social care need (home care: 2+count: 4.33%,95%CI:4.09%-4.58%; 2+CCI: 16.0%,95%CI:15.5%-16.4%; nursing homes: 2+count: 7.78%,95%CI:7.35%-8.22%, 2+CCI: 18.0%,95%CI:17.3%-18.6%). The underestimation without primary care was greater among younger age groups for the 2+count, and women and older individuals for the 2+CCI. Interpretation Multimorbidity is underestimated without primary care data, particularly among community-dwelling and independent older adults, as well as the youngest and oldest segments of the older population. Caution is warranted when comparing multimorbidity across age groups, care status, or social factors in the absence of primary care data.
Background Heart failure (HF) remains a global cause of morbidity and mortality and is increasingly complex to manage due to high prevalence of multimorbidity and coexisting cardiorenal and metabolic (CaReMe) syndrome. Individualised care through integrated service models can improve quality and maximise patient outcomes. This scoping review identifies and synthesises models of integrated care for multimorbid HF and CaReMe syndrome, analysing organisation, implementation, and reported outcome measures. Methods A systematic search was conducted in MEDLINE, PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), COCHRANE library, and grey literature. Eligible studies included primary research published between 2014 and 2025 describing integrated, multispecialty, or multidisciplinary team (MDT) models of care for adults with multimorbid HF and CaReMe disease. The search followed PRISMA-ScR reporting standards and studies reviewed using standardised tools informed by Joanna Briggs Institute (JBI) and Cochrane Collaborations Tool methodologies. Results Five studies were identified from upper-middle and high-income countries that incorporated MDT integrated care models. Models were mapped to the Effective Practice and Organisation of Care (EPOC) framework explaining key components of integrated care. Positive outcomes included reduced hospitalisations, improved treatment adherence, enhanced collaborative processes, and patient engagement. Limited governance structures, variable outcome measures, gaps in financial and technological evaluations were also identified. Conclusion Integrated care models for multimorbid HF and CaReMe syndrome demonstrate potential to enhance care coordination and quality of life. Evidence gaps persist regarding practical implementation, economic viability, and flexibility across healthcare settings. Future research should prioritise patient co-design, standardised outcomes, and shared decision-making frameworks.
Background:Limited evidence exists on how multimorbidity combinations influence the risk of secondary bacterial infections. This study identified multimorbidity clusters among hospitalised COVID-19 patients in Victoria (2020-2023) and examined their association with secondary bacterial infections and admission outcomes, including ICU admission, hospital and ICU length of stay, and mortality. Methods:We used population-wide linked hospital data and applied cluster analysis to ICD-10 coded chronic conditions to identify multimorbidity clusters. Risks of secondary bacterial infection across clusters were compared to patients with one or no chronic conditions. We used multivariate logistic regression, negative binomial regression, Kaplan-Meier curves, and Cox proportional hazards models to analyse associations with secondary bacterial infection and admission outcomes. Results:Among 179,688 COVID-19 hospital admissions, three multimorbidity clusters were identified: neuropsychiatric, cardiometabolic-multisystem, and neoplastic. Compared to no multimorbidity, each cluster was associated with significantly higher odds of secondary bacterial infection: neuropsychiatric (Odds Ratio (OR) 2.74, 95% CI 2.59-2.89), cardiometabolic-multisystem (OR 3.87, 95% CI 3.63-4.13), and neoplastic (OR 1.98, 95% CI 1.84-2.14; all p<0.001). For patients with secondary bacterial infection, cardiometabolic-multisystem multimorbidity had the highest increase in hospital length of stay (Incident Rate Ratio (IRR) 1.94, 95% CI 1.82-2.05) and ICU length of stay (IRR 2.75, 95% CI 2.36-3.20). Mortality was significantly elevated across all clusters and was highest in the cardiometabolic-multisystem group. Conclusions:Multimorbidity was associated with increased risk of secondary bacterial infection and poorer clinical outcomes in hospitalised COVID-19 patients. Integrating multimorbidity profiles into clinical decision-making may enhance antimicrobial stewardship by identifying patients most likely to benefit from antibiotic therapy.
Background Multimorbidity is widespread, influencing disease progression and patient outcomes. Understanding the impact on the use of healthcare resources and healthcare associated harm is crucial for population-level interventions to reduce disease burden and improve quality of life. Methods This retrospective study used administrative and clinical registry data from a 30% sample of the adult Estonian population. Multimorbidity was defined as ≥2 chronic diseases. Prevalence of chronic disease and multimorbidity was estimated among adults on January 1, 2024 (n = 324,942). Healthcare utilization included inpatient, outpatient, emergency visits, and prescription counts. Survival was assessed over five years following entry into multimorbidity strata (0–1, 2–4, 5–9, ≥10 conditions) in 2012–2024. We estimated 5-year risk of healthcare-associated harm diagnoses comparing patients with and without multimorbidity. Results Chronic disease affected 60.3% of adults and multimorbidity 42.0%, increasing steeply with age. Multimorbidity was strongly associated with mortality, with adjusted hazard ratios of 1.61 (95% CI 1.57–1.66) for 2–4 conditions, 2.43 (2.36–2.51) for 5–9, and 3.35 (3.22–3.48) for ≥10 conditions compared with ≤1 condition. Healthcare utilization increased approximately linearly with each additional chronic disease, with 0.025 more inpatient visits, 0.034 emergency visits, 1.49 outpatient visits, and 4.04 prescriptions per person-year. Multimorbidity was also associated with higher risk of healthcare-associated adverse events, with up to sevenfold higher hazards for several complications, particularly related to procedural/surgical and prosthesis-related complications, including infections. Conclusion Multimorbidity is prevalent in the Estonian population, increases mortality and healthcare use, and may increase healthcare-associated harm.
Multimorbidity—the coexistence of multiple chronic conditions within a single individual—has emerged as a powerful lens through which to understand the growing mismatch between population health needs and health systems historically organised around single diseases. In many lower-income countries, multimorbidity has reinvigorated calls for more integrated and person-centred models of care. Yet responses have often been fragmented and incremental, remaining tethered to the vertical programmes and disease-specific architectures they seek to overcome. The recent disruption of USAID funding represents a critical juncture for health systems that have long relied on externally funded programmes. While the immediate consequences for service delivery are substantial, this moment also presents an opportunity to move beyond piecemeal integration towards more fundamental health system transformation. Realising this opportunity will require greater emphasis on locally led adaptation, recognising that multimorbidity is experienced and managed within highly contextual social, organisational and epidemiological realities. Learning health systems offer a promising conceptual horizon for this transition by providing a framework through which health systems can continuously generate, interpret and act upon knowledge in response to changing needs. The challenge ahead is not simply sustaining services, but building more integrated, adaptive and person-centred systems capable of responding to shifting realities of multimorbidity.
Background Individuals with multimorbidity often have complex health and social care needs and experience frequent transitions across various settings and providers, including home, community services, primary care, and hospitals. These transitions represent pivotal moments within their care trajectories, where the risk of care fragmentation is significantly increased. Although these transitions play an important role in shaping patient experiences and outcomes, the factors associated with them remain insufficiently documented. Objective This study aimed to identify individual and environmental factors associated with either positive or negative experiences of care transition among individuals with complex needs. Design Using a prospective correlational design, participants were recruited from emergency departments at three sites in two Canadian provinces. Eligible individuals had ≥3 ED visits in the past year, screened positive on the COmplex NEeds Case-finding Tool–6 (CONECT-6), and had complex needs confirmed by an INTERMED Self-Assessment (IMSA) score of 19 or higher. Baseline data included sociodemographic, clinical, and psychosocial variables; environmental variables were derived from geocoded postal codes. At six months, participants completed a 12-item scale on care transitions adapted from the Patient Experience of Integrated Care Scale (PEICS). Multivariable linear regression identified factors associated with transition experiences. Results Of 292 participants recruited, 167 completed the follow-up. Biopsychosocial complexity, self-management capacity, and recruitment site were significantly associated with transition experiences. Higher complexity was associated with less favorable experiences, while stronger self-management was linked to more positive transitions. Conclusion Care transition experiences are associated with biopsychosocial complexity and self-management abilities, with site-level differences point to organizational and systemic influences. Further research is needed to examine how organizational and system-level factors shape transition experiences for individuals with complex needs.
Background Psoriatic arthritis (PsA) is a chronic inflammatory musculoskeletal disease associated with psoriasis, affecting an estimated 0.13% of adults worldwide. People living with PsA often experience multiple long-term conditions (MLTCs) or multimorbidity (the presence of two or more long-term health conditions), such as hypertension, diabetes, obesity, and metabolic syndrome. Multimorbidity and treatment burden which is the workload of healthcare experienced by individuals and its impact on wellbeing may exacerbate poor health outcomes and complicate disease management in PsA. However, the influence of MLTCs and/or treatment burden on adverse health-related outcomes in this population remains poorly understood. Objective This systematic review protocol will outline the methods to evaluate the current evidence regarding the impact, if any, of MLTCs and/or treatment burden on mortality and other adverse health-related outcomes in individuals with PsA. Design Systematic review of the literature. The following databases will be searched: MEDLINE, EMBASE, CINAHL, PsycINFO, and Scopus. Longitudinal quantitative studies will be eligible for inclusion. Study selection will follow predefined eligibility criteria, and methodological quality and risk of bias will be assessed using the Cochrane Quality in Prognostic Studies tool. A narrative synthesis will be undertaken, and meta-analysis will be considered where appropriate. This protocol follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) 2015 guidelines. Conclusions Understanding the impact of MLTCs and/or treatment burden on health-related outcomes in PsA is essential for improving future clinical management. This review will help identify existing knowledge gaps and advance precision medicine strategies to improve health-related outcomes for individuals living with PsA.
Background Depression and obesity are common chronic conditions in adolescence with major health consequences. While adverse childhood experiences (ACEs), socioeconomic disadvantage, and sexual minority (SM) identity are linked to higher mental health–obesity (MH-OB) comorbidity, evidence on predictors of change during adolescence is limited. Methods Data came from 10,353 UK adolescents (49% male, 80.9% White, 9.1% SM) in the Millennium Cohort Study. MH-OB comorbidity was defined using overweight/obesity (International Obesity Task Force criteria) and depression/anxiety symptoms (Strengths and Difficulties Questionnaire emotional symptoms subscale) at ages 14 and 17. Change in comorbidity was categorised as none, persistent, resolved, or newly developed. Predictors included sex at birth, ethnicity, sexual identity, socioeconomic position, and cumulative ACEs. Multinomial logistic regression estimated adjusted relative risk ratios (aRRRs). Results At age 14, 7.7% of adolescents were obese, 19.5% overweight, and 27.8% reported depression/anxiety symptoms. By age 17, 2.5% had persistent MH-OB comorbidity, 6.2% newly developed comorbidity, and 2.8% resolved; 88.0% had no comorbidity. Female sex, SM identity, lower household income, and increasing ACE exposure were associated with persistent and newly developed comorbidity. Associations were strongest among SM adolescents and females. Exposure to three or more ACEs increased risk of persistent comorbidity. Conclusion Adolescents who experienced socioeconomic disadvantage, exposure to adversity, and with SM identity were more likely to show persistent or new-onset MH-OB comorbidity, with associations generally stronger in females than in males. These findings highlight the importance of early, integrated interventions that address both mental health and weight-related risks in structurally disadvantaged groups.
Background Projections suggest that the number of adults living with multimorbidity will continue growing in the coming decades. Little is known, however, about the potential impact of prevention policies on multimorbidity. Methods & findings We applied a validated microsimulation model of multimorbidity accumulation to simulate theoretical scenarios of health improvement and inequality reduction in England over 30 years (2019-2049), compared to a baseline scenario of continuing patterns in accumulation. Four theoretical scenarios were based on Benach et al.’s typology of health policies: 1) targeted intervention on the worst-off; 2) universal policy + additional focus on the gap; 3) redistributive policy; 4) proportionate universalism; plus an idealistic fifth scenario completely removing socioeconomic inequality in transition times between states. We selected a target of 3% reduction in mortality for scenarios 1-4, based on reductions seen from tobacco control policies. Outputs compared were: difference in 2049 projected prevalence and numbers compared to baseline, total cases prevented/postponed compared to baseline, and expected years lived without multimorbidity at age 30. Our results suggest that gains in levelling socioeconomic inequalities in health would prevent/postpone multimorbidity cases and reduce relative health inequalities among those aged <65. However, this would also likely lead to increased absolute numbers living with multimorbidity overall. Conclusions Our theoretical modelling suggests effective and equitable policies have potential to reduce the population-level burden of multimorbidity, postponing a substantial number of multimorbidity cases, particularly before age 65. This is, however, likely to lead to greater absolute numbers of multimorbidity cases as individuals live for longer.
Background Incomplete and inconsistent reporting amongst research studies in people with Multiple Long-Term Conditions (MLTC) hinders the comprehensive evaluation, synthesis, and interpretation of study findings for application by clinicians, researchers, patients and policymakers. This limitation leads to heterogeneous findings, duplication of work and restricts the practical application of research outcomes in clinical settings, public health strategies, and policymaking. Given the high prevalence and complexity of MLTC, there is a pressing need for standardised guidelines to promote clarity, consistency, and comprehensiveness in study reporting. Such guidelines can enhance transparency and reproducibility, thereby increasing the impact of research on healthcare decisions and policy development. Methods We followed a four-stage process of guidelines development: a review of MLTC reporting practices; a workshop with diverse stakeholders to identify and refine items for inclusion; a prioritisation consensus exercise to agree on key items; and pilot-testing to refine interpretation and usability of the guidelines. Results This work has produced the first set of reporting guidelines addressing the need for standardised reporting in MLTC research. Application of these guidelines has the potential to improve research clarity and reproducibility, enabling better comparisons across studies and shared learning. Improved reporting standards will also facilitate the translation of research findings into effective healthcare strategies and policies, contributing to better health outcomes for MLTC patients. Conclusion These initial guidelines offer a structured approach to improving the reporting quality of MLTC research. Future evaluations will assess its impact on research transparency and real-world application.
The growing prevalence of multiple long-term conditions (MLTC) - two or more long-term health conditions - has been recognised as one of the most significant health challenges facing contemporary societies. People living with MLTC experience poorer outcomes than people with one long-term condition and may be disadvantaged by health care systems configured for single conditions. Recognition of the significance of these inequities has led to increased investments in MLTC research, and a body of qualitative literature on lived experience is developing. However, conducting qualitative MLTC research presents challenges to researchers. Encompassing an extensive range of condition combinations, the MLTC population is incredibly diverse, and constructing a sampling strategy for the small numbers of participants typical in qualitative inquiry requires careful thought. Additionally, MLTC is a construct not embedded in public consciousness, which may affect participant self-identification and research engagement. Furthermore, the risk of issues commonly experienced in qualitative health research, such as participant distress and low recruitment rates, can be exacerbated due to the ill-health experienced by some people living with MLTC. In this article, we share reflections from a cross-institution Qualitative Methods Community of Practice in MLTC Research, describing the challenges experienced and practical steps taken to address difficulties and mitigate risks. We aim to provide tips and guidance to qualitative health researchers new to MLTC inquiry to support planning and delivery of their research in this rapidly growing field.
Introduction Multiple long-term conditions (MLTCs), defined as the co-existence of two or more chronic health conditions, are increasingly prevalent across all age groups and disproportionately affect socioeconomically disadvantaged and ethnic minority populations. Trials targeting MLTCs face methodological challenges due to patient heterogeneity, variation in selection of conditions and limitations in design and analysis. These challenges may contribute to the lack of evidence to inform effective interventions for people with MLTCs. This study aims to systematically identify and prioritise key methodological uncertainties in the design, conduct and analysis of future trials aiming to improve health outcomes for people with MLTCs. Methods We will conduct a four-round modified Delphi study involving key interest groups including methodologists, trialists, MLTC researchers, research funders, commissioners, regulators, people with MLTC lived experience and MLTC carers. The process will include two rounds of online questionnaires, one lived-experience meeting (in-person or virtual) and a final virtual consensus meeting. To promote inclusivity and diversity of input, participants may join at any stage. Responses from each round will be analysed and summarised to inform the next stage, with final priorities agreed through structured consensus voting. Expected Outcomes This consensus study will produce a ranked list of methodological research uncertainties to guide future research and clinical trial design, conduct and analysis in MLTCs. Findings will be disseminated through a facilitated online dissemination workshop, academic channels and targeted public engagement activities to support inclusive and relevant MLTC research.
Background:People living with multimorbidity often experience unmet social care needs, which can negatively affect wellbeing and increase pressure on health and social care systems. Artificial intelligence (AI)-enabled tools may support more timely and tailored responses to these needs. Large language models (LLMs) are emerging as tools to support qualitative research, although research detailing their integration into qualitative analytic workflows remains limited. Methods:We conducted a secondary thematic analysis of 75 qualitative interview transcripts involving people with multimorbidity and their carers. The dataset was coded according to an analytic framework of exploratory, interpretive, and integrative layers of meaning. The dataset was analysed according to two parallel analytic streams: human reflexive thematic analysis, and qualitative analysis using Claude Sonnet 4. Model outputs were iteratively reviewed and compared against manual thematic analysis for convergence and divergence. Results:Across the analytic workflow, twelve themes from the original human-led analysis were used as a reference framework for examining areas of alignment, extension, or divergence in LLM-generated interpretations. The LLM-assisted analysis highlighted shifts in analytic emphasis and candidate interpretive nuances, including emotive tone and latent cross-cutting concerns, while requiring human oversight to determine evidential grounding. Conclusions:We present a structured methodological illustration for integrating LLM-assisted outputs within qualitative analysis. Using convergence-divergence mapping, we examine how LLM-generated interpretations may function as an additional analytic lens that can support reflexivity, transparency, and analytic auditability in qualitative research applied within the context of multimorbidity.
Background:Bullous pemphigoid (BP) has been linked to neurological and psychiatric disorders, but no nationwide population-based study has comprehensively examined the association of various comorbidities in BP patients in Sweden. Objectives:To investigate the associations between BP and various comorbidities, comparing these conditions before and after BP diagnosis with a matched control group. Methods:A nationwide cohort study was conducted in Sweden from 2005 to 2016, including 5,738 BP cases and 17,167 age, sex and county of residence matched controls. Multivariable Cox proportional hazard regression models were used to calculate hazard ratios (HR). Univariable logistic regression assessed pre-diagnosis comorbidities, generating prevalence odds ratios (POR) with 95% confidence intervals (CI). Results:BP was associated with a significantly higher overall HR for comorbidity (HR: 2.20, 95% CI: 2.08-2.33). Before BP diagnosis, the overall comorbidity was significantly increased POR 2.72 (95% CI: 2.56-2.90). Pre-diagnosis association included dementia, Parkinson's disease, epilepsy, amyotrophic lateral sclerosis, multiple sclerosis, schizophrenia, unipolar/bipolar disorders, suicide, diabetes, stroke, systemic lupus erythematosus, systemic sclerosis, psoriasis, lichen planus, alopecia areata, and vitiligo. After diagnosis, the overall hazard ratio (HR) for comorbidities was highest within the first year (HR 2.88, 95% CI: 2.68-3.10) and remained elevated beyond one year (HR 1.57, 95% CI: 1.44-1.71). Post-diagnosis associations remained elevated for dementia, Parkinson's disease, epilepsy, schizophrenia, unipolar/bipolar, diabetes, psoriasis, lichen planus and autoimmune diseases such as systemic sclerosis and Sjögren's syndrome. Conclusion:BP is strongly associated with neurodegenerative, psychiatric, autoimmune, and metabolic comorbidities before and after diagnosis, highlighting their clinical significance as predisposing and prognostic factors in BP patients.
Background Multimorbidity is a growing global challenge, associated with premature death, impaired activities of daily living, reduced capacity for independent living, poor functional outcomes, and lower quality of life. However, there is limited evidence on multimorbidity and their determining factors among stroke survivors in the Ethiopian context. This study aimed to assess the prevalence of multimorbidity and its associated factors among stroke survivors in public hospitals of Amhara Regional State Northwest Ethiopia. Methods A multi-center, institution-based cross-sectional study was conducted from June 26 to August 30, 2024. Systematic random sampling was used to select 292 study participants. Data were collected using a structured, interviewer-administered questionnaire and chart review. Bivariable and multivariable logistic regression analyses were performed to identify factors associated with multimorbidity. Variables with a p-value < 0.05 in multivariable analysis were considered statistically significant. Result The prevalence of multimorbidity was 72.9%. Hypertension was the most frequently reported comorbidity. Significant factors associated with multimorbidity included age 50 and above (AOR: 2.48, 95% CI: 1.29, 4.74), having no formal education (AOR: 3.72, 95% CI: 1.49, 9.26), secondary education (AOR: 3.76, 95% CI: 1.46, 9.73), use of assistive technology (AOR: 2.60, 95% CI: 1.32, 5.09), duration of hospitalization (AOR:3.08,95%CI:1.37,6.95) , and post-stroke disability (AOR: 4.47, 95% CI: 2.23,8.93). Conclusions Multimorbidity is highly prevalent. Targeted interventions particular focus on aged population, educational status, assistive technology provision, and post-stroke disability are essential to improve health outcomes.
Background The growing prevalence of multiple long-term conditions (MLTC) poses a public health challenge. Existing quality of care (QoC) indicators are poorly suited to the needs of MLTC populations with limited clarity on how quality should be measured. This scoping review aimed to map QoC indicators for MLTC in primary care developed with patient and caregiver input, and to characterise the methods and extent of that involvement. Methods Scoping review following the six-stage framework by Arksey and O’Malley refined by Levac et al. Searches were conducted on six databases. Studies were included if adults with two or more chronic conditions were involved. Data were charted on indicator content (name, quality domain, data sources, measurement characteristics) and development processes (methodological approaches and stakeholders involved). Where indicators were not specified, qualitative findings were synthesised to identify QoC domains and mapped to the Donabedian model and Institute of Medicine quality domains. Community partners with lived experience of MLTC were involved. Results Twenty-five studies were included, 78 QoC indicators were identified and a further 33 quality domains were synthesised through thematic analysis. Quality was predominately measured through patient-experience surveys rather than indicators. Studies articulated quality through care processes such as care coordination, shared decision-making and holistic assessments. Outcomes focused on functional capacity, social participation and quality of life. Conclusion Despite robust evidence on what matters to people living with MLTC, few patient-derived QoC indicators have been developed into measurable indicators. Further work is needed to co-produce indicators suitable to existing primary care settings.
