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Open research questions in Chronic Disease Management Strategies

58 unresolved questions extracted from the limitations and future-work sections of 538 Chronic Disease Management Strategies papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • The association between SES and mortality, as well as the effect-modifying role of specific comorbidities, are not yet fully understood within the critical care context of insurance-based universal healthcare systems.

    Socioeconomic Disparities and the Role of Comorbidity in Hospital Mortality: A Dutch Nationwide Critical Care Cohort Study · 2026 · DOI

  • A 22-feature matrix combining continuous clinical biomarkers (systolic blood pressure, waist circumference, HbA1c) and categorical social variables was projected using Factor Analysis of Mixed Data (FAMD).

    Life-Stage Heterogeneity in the Mental Health Treatment Gap: An Unsupervised Machine Learning Profiling of Symptomatic US Adults · 2026 · DOI

  • Abstract Background Intrinsic capacity (IC) and comorbidity burden are both associated with health outcomes in older postmenopausal women, yet whether they capture independent dimensions of health remains unclear.

    Intrinsic capacity and comorbidity burden capture distinct but age-driven dimensions of health in older postmenopausal women · 2026 · DOI

  • For older adults requiring concomitant ACEI/ARBs therapy, rig- orous evaluation of medication necessity and close surveillance of overall intrinsic capacity status are warranted.

    Association between aspirin use and decline in intrinsic capacity among community-dwelling elderly: a study based on the Lianyungang ICOPE pilot project · 2026 · DOI

  • However, the implementation of these interventions in the context of cardiometabolic multimorbidity (CMM) within the unique demographic and cultural milieu of India is inadequately explored, despite Indians exhibiting distinct susceptibility to cardiovascular diseases.

    Implementing a lifestyle toolkit in individuals with cardiometabolic multimorbidity: study protocol for a cluster randomised, type III effectiveness–implementation trial (SHRADDHA-CMM) · 2026 · DOI

  • Background Chronic kidney disease (CKD) requires accurate identification and consistent management in primary care, but the extent to which coding accuracy reflects care quality across Hampshire and Isle of Wight (HIOW) practices remains uncertain.

    Does better coding mean better care? A study of CKD coding and management indicators in Hampshire and Isle of Wight · 2026 · DOI

  • Abstract Background: Socio-economic status (SES) is associated with many adverse health outcomes, yet it remains unclear how SES relates to the rate at which people accumulate long-term conditions (LTCs) over time.

    Relationship between socioeconomic inequality and multimorbidity progression in UK Biobank data · 2026 · DOI

  • This study has several limitations that should be considered when interpreting the results. In the first place, the pre-post quasi-experimental study design with no control group limits the possibility of establishing causal relationships. The changes seen during the implementation of the care model and in the use of healthcare resources may have been influenced by external factors not directly related to the intervention, such as the natural clinical course. However, it should be noted that the study was conducted as part of routine clinical practice at the hospital, which justifies the choice of design. The inclusion of a control group would have meant depriving some patients of a coordinated care model that is part of standard care practice. Secondly, the results of the implementation of the care model (at 3 months) and those assessing its effectiveness (at 6 months) were analysed only for patients still alive at the time of the analyses. This may have led to a survivorship bias, as it excludes the deceased patients, who may have had different patterns of use of resources or response to the intervention. However, we analysed the prior use of resources by both the patients who were deceased at 6 months and the survivors and observed no significant differences. It should also be considered that we have not assessed whether the absence of validation or recording of information by some in our study is due to discrepancies between IC and PC concerning the identification of CCP or ACP and the proposed ICP. This study has several strengths. First, it presents a practical, real-life implementation of a conceptual model for an especially vulnerable population: patients with dementia and highly complex conditions. This makes the 8 intervention an example of translational research, as it contributes to narrowing the gap between healthcare theory and practice. Secondly, it institutes an innovative strategy using a coordinated care model that combines technological and clinical factors: structuring information in the discharge summary with specific ICP proposals, sending computer alerts to the PC teams and more active use of the SCR, not only as an information repository, but as a dynamic coordination tool. The study also addresses significant gaps in knowledge around coordination between levels of care, providing preliminary results on effectiveness and presenting an organizational model with potential for scalability to other healthcare system settings. Finally, it integrates key aspects for current healthcare system transformation processes, such as digitalisation, efficient use of clinical information, and the promotion of person centred care.

    Evaluation of the Impact of a Coordinated Intervention Model for Complex Older Patients with Dementia · 2026 · DOI

  • The continuous rise in chronic and mental conditions, along with associated healthcare costs, is not an unprecedented phenomenon. Following the COVID-19 pandemic, there has been a heightened awareness of the need for innovative approaches to healthcare delivery for these Table 3 Summary of selected key studies illustrating the impact of DTx and CDSS on medication management and healthcare expenditure. These studies were chosen based on the narrative review criteria (Sect. 1.1) to provide representative clinical and economic evidence PMID / Study [PMID: 32554566] Rieckert et al.

    The Use of Digital Therapeutics in the Management of Chronic Diseases: State of the Art, Evidence and Prospects · 2026 · DOI

  • associated with conventional dosage forms, such as poor solubility, rapid degradation, and systemic side effects. Nanoparticle-based drug delivery systems, including liposomes, niosomes, dendrimers, and polymeric nanoparticles, enable targeted drug delivery to specific tissues or cells. These systems enhance drug stability, improve pharmacokinetics, and reduce off-target effects [25,26]. In the context of can nanoparticle comorbidities, simultaneously deliver multiple drugs to different targets, thereby addressing multiple disease pathways efficiently. Controlled and sustained release systems are widely used in the management of chronic diseases associated with comorbidities. These systems maintain therapeutic drug concentrations over extended periods, reducing dosing frequency and improving patient adherence. Technologies such as matrix tablets, osmotic pumps, and transdermal delivery systems are commonly employed to achieve controlled drug release. Smart drug delivery systems represent an advanced class of delivery platforms that respond to specific physiological stimuli such as pH, temperature, enzymes, or redox conditions. These stimuli-responsive systems enable site-specific and on-demand drug release, thereby improving therapeutic precision and minimizing adverse effects. 5.3 Combination Therapy Approaches Combination therapy has become a cornerstone in the management of comorbidities due to its ability to target multiple disease pathways simultaneously. This approach enhances therapeutic efficacy while reducing the risk of resistance and adverse effects. Fixed-dose combinations (FDCs) are widely used to simplify treatment regimens by combining two or more active pharmaceutical ingredients into a single dosage form. FDCs improve patient adherence, reduce pill burden, and enhance treatment outcomes, particularly in chronic diseases such as hypertension, diabetes, and infectious diseases [31,32]. Synergistic drug strategies involve the use of drugs with complementary mechanisms of action to achieve enhanced therapeutic effects. By targeting different pathways, these combinations can produce additive or synergistic effects, allowing for lower doses and reduced toxicity. This approach is commonly applied in oncology, antimicrobial therapy, and cardiometabolic diseases. Rational drug design computational modeling, molecular leverages docking, and structure–activity relationship (SAR) studies to develop drugs that specifically target disease-related pathways. Advances in computational biology and cheminformatics have accelerated the discovery of novel therapeutic agents with improved efficacy and safety profiles. These strategies are particularly valuable in addressing the complexity of comorbid conditions, where multiple molecular targets must be considered. 5.4 Digital Health and AI Integration platforms those residing Digital health technologies and artificial intelligence have transformed the landscape of comorbidity management by enabling continuous monitoring, early diagnosis, and data-driven decision-making. These technologies support proactive and preventive healthcare approaches, which are essential for managing complex chronic conditions. Telemedicine has emerged as a vital tool for improving healthcare accessibility and continuity of care. It allows remote consultation, monitoring, and follow-up, reducing the timely for hospital visits and enabling need intervention are. Telehealth particularly beneficial for patients with mobility limitations or in remote areas. Wearable health monitoring devices, such as smartwatches, biosensors, and implantable devices, provide real-time data on physiological parameters including heart rate, blood pressure, glucose levels, and physical activity. These devices facilitate early detection of abnormalities and enable personalized health management. AI in diagnosis and treatment optimization plays a critical role in identify disease analyzing complex datasets patterns, predict outcomes, and recommend treatment strategies. Machine learning algorithms can integrate clinical, imaging, and genomic data to support clinical decision-making and improve diagnostic accuracy [37,38]. AI-driven predictive models are especially valuable in managing multimorbidity, where interactions between multiple diseases must be considered simultaneously.

    Recent Advancements in the Management and Treatment of Comorbidities: A Review · 2026 · DOI

  • The future management of comorbidities is expected to be driven by rapid advancements in technology, deeper biological insights, and the development of integrated healthcare models. As the burden of multimorbidity continues to rise globally, there is a growing need for innovative strategies that can address the complexity of multiple coexisting conditions in a more precise, efficient, and patientcentered manner. 9.1 Emerging Technologies to revolutionize Emerging technologies such as artificial intelligence, machine learning, nanotechnology, and robotics are expected the management of comorbidities. AI-driven predictive models can enable early detection of disease progression and facilitate personalized treatment planning. Nanotechnology-based systems are being developed for highly targeted drug delivery, allowing simultaneous treatment of multiple disease pathways with improved precision and reduced toxicity.

    Recent Advancements in the Management and Treatment of Comorbidities: A Review · 2026 · DOI

  • Strengths of our study include a longitudinal design exploring not only static status of MetSS, but also dynamic MetSS changes in a large-scale nationally rep- resentative population. The application of advanced sta- tistical modeling techniques, such as K-means clustering, enabled the classification of distinct trends of MetSS changes. Additionally, our study provides evidence for the early identification of high-risk CMM individuals to prevent CMM progression in middle-aged and older adults. Zhang et al. Cardiovascular Diabetology – Endocrinology Reports (2026) 12:18 Page 12 of 14 progression, further study with longer follow-up period is necessary to validate the findings of our study. Finally, CMM is a complex multimorbidity affected by numerous factors, there still can be confounding factors that are not considered in our study.

    Association of cumulative exposure and dynamic change patterns of metabolic syndrome score with cardiometabolic multimorbidity progression among middle-aged and older Chinese adults: a longitudinal analysis based on CHARLS · 2026 · DOI

  • This research supports a shift to a more proactive, health promotion/risk mitigation paradigm through informing intervention research targeting AL, which is currently scarce.

    Allostatic Load, Morbidity, and Mortality Among Older Adults: A Multi-Wave Analysis From the National Health and Aging Trends Study · 2024 · DOI

  • The importance of informal caregiving for chronic illness has been well established in African contexts but is underexplored in the context of HIV/NCD multimorbidity, particularly in South Africa.

    Exploring the workload of informal caregiving in the context of HIV/NCD multimorbidity in South Africa · 2024 · DOI

  • The Agency for Healthcare Research and Quality's (AHRQ's) vision for “a sustainable health care system that delivers high-value coordinated, integrated patient-centered care based in primary care, optimizing individual and population health by preventing and effectively managing MCC” remains elusive.

    Transforming care for people with multiple chronic conditions: Agency for Healthcare Research and Quality's research agenda · 2021 · DOI

  • Programmatic efforts have prioritized parasitological and ocular outcomes, so the socio-economic and psychological burden of the disease within affected communities remains poorly quantified.

    The pervasive socio-economic and psychological burden of onchocerciasis in endemic communities of Bo District, Sierra Leone: an explanatory sequential mixed-methods study · 2026 · DOI

  • Multiple causes of death (MCoD) data, recording all conditions on the death certificate, are increasingly used as a proxy for end-of-life multimorbidity, yet how accurately they represent it remains underinvestigated.

    Understanding end-of-life multimorbidity: An analysis of multiple causes of death in Denmark · 2026 · DOI

  • Multimorbidity is the dominant clinical reality of primary care, yet the temporal dynamics governing when and how persistent comorbidity associations emerge remain poorly characterised.

    The biological clock of multimorbidity: temporal dynamics of disease co-occurrence in primary care · 2026 · DOI

  • At the core of this issue lays a vagueness of the definition of a cluster, leading to a lack of standards in their methods and evaluation, while implementation details are often not completely reported or explicit in their assumptions.

    Towards reproducible multimorbidity clustering in electronic health records: a transparent pipeline for aligning research aims and methodology · 2026 · DOI

  • BACKGROUND: Chronic somatic diseases (CSDs), particularly cardiometabolic diseases (CMDs) are recognized contributors to functional disability, yet limited evidence examines these associations by employing longitudinal approaches.

    Accelerated multimorbidity in early adulthood and long-term functional disability in later life: a life-course epidemiological study · 2026 · DOI

  • Differences in multimorbidity trends and sex‐stratified disease burden, emphasize the need for further investigation into the environmental, diagnostic, and systemic factors that influence outcomes.

    Ageing Across Continents: Insights Into the Physical Health of Older Adults With Intellectual Disability From Ireland and Australia · 2025 · DOI

  • Additional support networks, access to grants or financial security, and feeling a duty to care eased the perceived carer burden while a lack of social support, financial hardship and insufficient information decreased their capacity to support others.

    Exploring the workload of informal caregiving in the context of HIV/NCD multimorbidity in South Africa · 2024 · DOI

  • * Addressing chronic conditions and their determinants in young adulthood can help slow disease progression and improve well-being across the life course (1); however, recent prevalence estimates examining chronic conditions in young adults overall and by subgroup have not been reported.

    Chronic Conditions Among Adults Aged 18─34 Years — United States, 2019 · 2022 · DOI

  • Our two-step approach integrated mixed data types, first, by making meta-inferences at five time frames during his illness trajectory and, second, by developing “global meta-inferences,” or interpretations across the meta-inferences from each of the five time frames using joint display analysis.

    A Fully Longitudinal Mixed Methods Case Study Design: An Example Based on the Illness Trajectory of a Person With Chronic Conditions in Home-Monitoring-Based Telenursing During the COVID-19 Pandemic · 2021 · DOI

  • Future research should investigate the mediating and moderating roles of health behaviors in the association between depression and the staggered emergence over time of clusters of multimorbid chronic diseases.

    Depression and multimorbidity: Considering temporal characteristics of the associations between depression and multiple chronic diseases. · 2019 · DOI

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58 open questions have been extracted from the limitations and future-work passages of 538 Chronic Disease Management Strategies papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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