Evidence-based medicine and the hard problem of multimorbidity

Re-Analyses of 8 Historical Trials in Cardiovascular Medicine Assessing Multimorbidity Burden and Its Association with Treatment Response

OBJECTIVE

The purpose of this study was to examine the multimorbidity burden of clinical trial participants and assess its association with treatment response.

METHODS

We conducted a reanalysis of patient level data. There were 29,954 participants from 8 clinical trials containing 11 comparisons between an intervention and control condition. Patients were classified by Charlson Comorbidity Index (CCI) score. The primary outcomes were the primary study endpoints as originally specified for each trial. A Cox model that included the CCI score groups, the randomized group, and their interaction, was used to compare the primary outcome between randomized groups. The interaction term between randomized group and comorbidity index allowed the treatment effect to differ by level of comorbidity index and comprised the primary effect of interest. Hazard ratios and risk differences were reported for all comparisons.

RESULTS

The mean CCI scores of trial populations ranged from 2.1 to 3.9 points, and the percentage of patients with scores ≥5 from 3% to 39%. Tests of interaction terms in models yielded P values ≤ .10 for 4/11 comparisons and ≤ .05 for 2/11 comparisons. In 3 additional comparisons, potentially important treatment variation on an absolute scale was observed despite interaction tests with P values > .10 on the relative scale.

CONCLUSIONS

These trials were mainly composed of patient populations with CCI scores ≤4. Despite this, biologically plausible treatment interactions were commonly suggested. These results are hypothesis generating; confirmation of results would require larger studies or studies targeted specifically toward patients with higher levels of multimorbidity.

Multimorbidity and its Associated Factors in Korean Shift Workers: Population-Based Cross-Sectional Study

BACKGROUND

Multimorbidity is a crucial factor that influences premature death rates, poor health, depression, quality of life, and use of health care. Approximately one-fifth of the global workforce is involved in shift work, which is associated with increased risk for several chronic diseases and multimorbidity. About 12% to 14% of wage workers in Korea are shift workers. However, the prevalence of multimorbidity and its associated factors in Korean shift workers are rarely reported.

OBJECTIVE

This study aimed to assess multimorbidity prevalence, examine the factors associated with multimorbidity, and identify multimorbidity patterns among shift workers in Korea.

METHODS

This study is a population-based cross-sectional study using Korea National Health and Nutrition Examination Survey data from 2016 to 2020. The study included 1704 (weighted n=2,697,228) Korean shift workers aged 19 years and older. Multimorbidity was defined as participants having 2 or more chronic diseases. Demographic and job-related variables, including regular work status, average working hours per week, and shift work type, as well as health behaviors, including BMI, smoking status, alcohol use, physical activity, and sleep duration, were included in the analysis. A survey-corrected logistic regression analysis was performed to identify factors influencing multimorbidity among the workers, and multimorbidity patterns were identified with a network analysis.

RESULTS

The overall prevalence of multimorbidity was 13.7% (302/1704). Logistic regression indicated that age, income, regular work, and obesity were significant factors influencing multimorbidity. Network analysis results revealed that chronic diseases clustered into three groups: (1) cardiometabolic multimorbidity (hypertension, dyslipidemia, diabetes, coronary heart disease, and stroke), (2) musculoskeletal multimorbidity (arthritis and osteoporosis), and (3) unclassified diseases (depression, chronic liver disease, thyroid disease, asthma, cancer, and chronic kidney disease).

CONCLUSIONS

The findings revealed that several socioeconomic and behavioral factors were associated with multimorbidity among shift workers, indicating the need for policy development related to work schedule modification. Further organization-level screening and intervention programs are needed to prevent and manage multimorbidity among shift workers. We also recommend longitudinal studies to confirm the effects of job-related factors and health behaviors on multimorbidity among shift workers in the future.

Above and Beyond Number of Illnesses: A Two-Sample Replication of Current Approaches to Depressive Symptoms in Multimorbidity

OBJECTIVES

To expand current models of depressive symptoms in older adults with multimorbidity (MM) beyond the number of illnesses as a predictor of worsened mental health.

METHODS

Two-sample replication study of adults ≥62 years old with ≥ two chronic illnesses, who completed validated questionnaires assessing depressive symptoms, and disease- and treatment-related stressors. Data were analyzed using hierarchical linear regression.

RESULTS

The model of cumulative number of illnesses was worse at explaining variance in depressive symptoms (Sample 1 R2 = .035; Sample 2 R2 = .029), compared to models including disease- and treatment-related stressors (Sample 1 R2 = .37; Sample 2 R2 = .47). Disease-related stressors were the strongest factor associated with depressive symptoms, specifically, poor subjective cognitive function (Sample 1: b = -.202, p = .013; Sample 2: b = -.288, p < .001) and greater somatic symptoms (b = .455, p < .001; Sample 2: b = .355, p < .001).

CONCLUSIONS

Using the number of illnesses to understand depressive symptoms in MM is a limited approach. Models that move beyond descriptive relationships between MM and depressive symptoms are needed.

CLINICAL IMPLICATIONS

Providers should consider the role of somatic symptom management in patients with MM and depressive symptoms.

Multimorbidity Patterns and Associations with Gait, Balance and Lower Extremity Muscle Function in the Elderly: A Cross-Sectional Study in Northwest China

Purpose

Fall is a common geriatric syndrome leading to various adverse outcomes in the elderly. Gait and balance disorders and decreased lower extremity muscle function are the major intrinsic risk factors of falls, and studies suggested that they were closely related to the underlying chronic conditions. This study aimed to explore the patterns of multimorbidity and determine the associations of these multimorbidity patterns with gait, balance and lower extremity muscle function.

Patients and Methods

A cross-sectional survey of 4803 participants aged ≥60 years in Shaanxi Province, China was conducted and the self-reported chronic conditions were investigated. The 6-m walk test, timed-up-and-go test (TUG) and 5-sit-to-stand test (5-STS) were conducted to evaluate gait, balance, and lower extremity muscle function respectively. Latent class analysis was used to explore patterns of multimorbidity, and multivariate regression analysis was used to determine the associations of multimorbidity patterns with gait, balance, and lower extremity muscle function.

Results

Five multimorbidity patterns were identified: Degenerative Disease Class, Cardio-metabolic Class, Stroke-Respiratory-Depression Class, Gastrointestinal Class, and Very sick Class, and they were differently associated with gait and balance disorders and decreased lower extremity muscle function. In particular, the multimorbidity patterns of Degenerative Disease Class and Stroke-Respiratory-Depression Class were closely associated with all the three risk factors of falls.

Conclusion

There are significant differences in the impact of different multimorbidity patterns on the major intrinsic risk factors of falls in the elderly population, and appropriate multimorbidity patterns are closely related to the prediction of falls and can help to develop fall prevention strategies in the elderly.

Drugs Targeting Mechanisms of Aging to Delay Age-Related Disease and Promote Healthspan: Proceedings of a National Institute on Aging Workshop

The geroscience hypothesis posits that by targeting key hallmarks of aging we may simultaneously prevent or delay several age-related diseases and thereby increase healthspan, or life span spent free of significant disease and disability. Studies are underway to examine several possible pharmacological interventions for this purpose. As part of a National Institute on Aging workshop on the development of function-promoting therapies, scientific content experts provided literature reviews and state-of-the-field assessments for the studies of senolytics, nicotinamide adenine dinucleotide (NAD+) boosters, and metformin. Cellular senescence increases with age, and preclinical studies demonstrate that the use of senolytic drugs improves healthspan in rodents. Human studies using senolytics are in progress. NAD+ and its phosphorylated form, NADP+, play vital roles in metabolism and cellular signaling. Increasing NAD+ by supplementation with precursors including nicotinamide riboside and nicotinamide mononucleotide appears to extend healthspan in model organisms, but human studies are limited and results are mixed. Metformin is a biguanide widely used for glucose lowering, which is believed to have pleiotropic effects targeting several hallmarks of aging. Preclinical studies suggest it improves life span and healthspan, and observational studies suggest benefits for the prevention of several age-related diseases. Clinical trials are underway to examine metformin for healthspan and frailty prevention. Preclinical and emerging clinical studies suggest there is potential to improve healthspan through the use of pharmacologic agents reviewed. However, much further research is needed to demonstrate benefits and general safety for wider use, the appropriate target populations, and longer-term outcomes.

Understanding multimorbidity requires sign-disease networks and higher-order interactions, a perspective

Background

Count scores, disease clustering, and pairwise associations between diseases remain ubiquitous in multimorbidity research despite two major shortcomings: they yield no insight into plausible mechanisms underlying multimorbidity, and they ignore higher-order interactions such as effect modification.

Objectives

We argue that two components are currently missing but vital to develop novel multimorbidity metrics. Firstly, networks should be constructed which consists simultaneously of signs, symptoms, and diseases, since only then could they yield insight into plausible shared biological mechanisms underlying diseases.Secondly, learning pairwise associations is insufficient to fully characterize the correlations in a system. That is, synergistic (e.g., cooperative or antagonistic) effects are widespread in complex systems, where two or more elements combined give a larger or smaller effect than the sum of their individual effects. It can even occur that pairs of symptoms have no pairwise associations whatsoever, but in combination have a significant association. Therefore, higher-order interactions should be included in networks used to study multimorbidity, resulting in so-called hypergraphs.

Methods

We illustrate our argument using a synthetic Bayesian Network model of symptoms, signs and diseases, composed of pairwise and higher-order interactions. We simulate network interventions on both individual and population levels and compare the ground-truth outcomes with the predictions from pairwise associations.

Conclusion

We find that, when judged purely from the pairwise associations, interventions can have unexpected 'side-effects' or the most opportune intervention could be missed. The hypergraph uncovers links missed in pairwise networks, giving a more complete overview of sign and disease associations.

Treatment effect modification due to comorbidity: Individual participant data meta-analyses of 120 randomised controlled trials

BACKGROUND

People with comorbidities are underrepresented in clinical trials. Empirical estimates of treatment effect modification by comorbidity are lacking, leading to uncertainty in treatment recommendations. We aimed to produce estimates of treatment effect modification by comorbidity using individual participant data (IPD).

METHODS AND FINDINGS

We obtained IPD for 120 industry-sponsored phase 3/4 trials across 22 index conditions (n = 128,331). Trials had to be registered between 1990 and 2017 and have recruited ≥300 people. Included trials were multicentre and international. For each index condition, we analysed the outcome most frequently reported in the included trials. We performed a two-stage IPD meta-analysis to estimate modification of treatment effect by comorbidity. First, for each trial, we modelled the interaction between comorbidity and treatment arm adjusted for age and sex. Second, for each treatment within each index condition, we meta-analysed the comorbidity-treatment interaction terms from each trial. We estimated the effect of comorbidity measured in 3 ways: (i) the number of comorbidities (in addition to the index condition); (ii) presence or absence of the 6 commonest comorbid diseases for each index condition; and (iii) using continuous markers of underlying conditions (e.g., estimated glomerular filtration rate (eGFR)). Treatment effects were modelled on the usual scale for the type of outcome (absolute scale for numerical outcomes, relative scale for binary outcomes). Mean age in the trials ranged from 37.1 (allergic rhinitis trials) to 73.0 (dementia trials) and percentage of male participants range from 4.4% (osteoporosis trials) to 100% (benign prostatic hypertrophy trials). The percentage of participants with 3 or more comorbidities ranged from 2.3% (allergic rhinitis trials) to 57% (systemic lupus erythematosus trials). We found no evidence of modification of treatment efficacy by comorbidity, for any of the 3 measures of comorbidity. This was the case for 20 conditions for which the outcome variable was continuous (e.g., change in glycosylated haemoglobin in diabetes) and for 3 conditions in which the outcomes were discrete events (e.g., number of headaches in migraine). Although all were null, estimates of treatment effect modification were more precise in some cases (e.g., sodium-glucose co-transporter-2 (SGLT2) inhibitors for type 2 diabetes-interaction term for comorbidity count 0.004, 95% CI -0.01 to 0.02) while for others credible intervals were wide (e.g., corticosteroids for asthma-interaction term -0.22, 95% CI -1.07 to 0.54). The main limitation is that these trials were not designed or powered to assess variation in treatment effect by comorbidity, and relatively few trial participants had >3 comorbidities.

CONCLUSIONS

Assessments of treatment effect modification rarely consider comorbidity. Our findings demonstrate that for trials included in this analysis, there was no empirical evidence of treatment effect modification by comorbidity. The standard assumption used in evidence syntheses is that efficacy is constant across subgroups, although this is often criticised. Our findings suggest that for modest levels of comorbidities, this assumption is reasonable. Thus, trial efficacy findings can be combined with data on natural history and competing risks to assess the likely overall benefit of treatments in the context of comorbidity.

Prevalence of multimorbidity combinations and their association with medical costs and poor health: A population-based study of U.S. adults

Background

Multimorbidity is common, but the prevalence and burden of the specific combinations of coexisting disease has not been systematically examined in the general U.S. adult population.

Objective

To identify and estimate the burden of highly prevalent combinations of chronic conditions that are treated among one million or more adults in the United States.

Methods

Cross-sectional analysis of U.S. households in the Medical Expenditure Panel Survey (MEPS), 2016-2019, a large nationally-representative sample of the community-dwelling population. Association rule mining was used to identify the most common combinations of 20 chronic conditions that have high relevance, impact, and prevalence in primary care. The main measures and outcomes were annual treated prevalence, total medical expenditures, and perceived poor health. Logistic regression models with poor health as the outcome and each multimorbidity combination as the exposure were used to calculate adjusted odds ratios and 95% confidence intervals.

Results

Frequent pattern mining yielded 223 unique combinations of chronic disease, including 74 two-way (dyad), 115 three-way (triad), and 34 four-way combinations that are treated in one million or more U.S. adults. Hypertension-hyperlipidemia was the most common two-way combination occurring in 30.8 million adults. The combination of diabetes-arthritis-cardiovascular disease was associated with the highest median annual medical expenditures ($23,850, interquartile range: $11,593-$44,616), and the combination of diabetes-arthritis-asthma/COPD had the highest age-race-sex adjusted odds ratio of poor self-rated health (adjusted odd ratio: 6.9, 95%CI: 5.4-8.8).

Conclusion

This study demonstrates that many multimorbidity combinations are highly prevalent among U.S. adults, yet most research and practice-guidelines remain single disease focused. Highly prevalent and burdensome multimorbidity combinations could be prioritized for evidence-based research on optimal prevention and treatment strategies.

Assessing trial representativeness using serious adverse events: an observational analysis using aggregate and individual-level data from clinical trials and routine healthcare data

BACKGROUND

The applicability of randomised controlled trials of pharmacological agents to older people with frailty/multimorbidity is often uncertain, due to concerns that trials are not representative. However, assessing trial representativeness is challenging and complex. We explore an approach assessing trial representativeness by comparing rates of trial serious adverse events (SAE) to rates of hospitalisation/death in routine care.

METHODS

This was an observational analysis of individual (125 trials, n=122,069) and aggregate-level drug trial data (483 trials, n=636,267) for 21 index conditions compared to population-based routine healthcare data (routine care). Trials were identified from ClinicalTrials.gov . Routine care comparison from linked primary care and hospital data from Wales, UK (n=2.3M). Our outcome of interest was SAEs (routinely reported in trials). In routine care, SAEs were based on hospitalisations and deaths (which are SAEs by definition). We compared trial SAEs in trials to expected SAEs based on age/sex standardised routine care populations with the same index condition. Using IPD, we assessed the relationship between multimorbidity count and SAEs in both trials and routine care and assessed the impact on the observed/expected SAE ratio additionally accounting for multimorbidity.

RESULTS

For 12/21 index conditions, the pooled observed/expected SAE ratio was <1, indicating fewer SAEs in trial participants than in routine care. A further 6/21 had point estimates <1 but the 95% CI included the null. The median pooled estimate of observed/expected SAE ratio was 0.60 (95% CI 0.55-0.64; COPD) and the interquartile range was 0.44 (0.34-0.55; Parkinson's disease) to 0.87 (0.58-1.29; inflammatory bowel disease). Higher multimorbidity count was associated with SAEs across all index conditions in both routine care and trials. For most trials, the observed/expected SAE ratio moved closer to 1 after additionally accounting for multimorbidity count, but it nonetheless remained below 1 for most.

CONCLUSIONS

Trial participants experience fewer SAEs than expected based on age/sex/condition hospitalisation and death rates in routine care, confirming the predicted lack of representativeness. This difference is only partially explained by differences in multimorbidity. Assessing observed/expected SAE may help assess the applicability of trial findings to older populations in whom multimorbidity and frailty are common.

Personalized (N-of-1) Trials for Patient-Centered Treatments of Multimorbidity

Treatment of patients who suffer from concurrent health conditions is not well served by (1) evidence-based clinical guidelines that mainly specify treatment of single conditions and (2) conventional randomized controlled trials (RCTs) that identify treatments as safe and effective on average. Clinical decision-making based on the average patient effect may be inappropriate for treatment of those with multimorbidity who experience burdens and obstacles that may be unique to their personal situation. We describe how the personalized (N-of-1) trials can be integrated with an automatic platform and virtual/remote technologies to improve patient-centered care for those living with multimorbidity. To illustrate, we present a hypothetical clinical scenario-survivors of both coronavirus disease 2019 (COVID-19) and cancer who chronically suffer from sleeplessness and fatigue. Then, we will describe how the four standard phases of conventional RCT development can be modified for personalized trials and applied to the multimorbidity clinical scenario, outline how personalized trials can be adapted and extended to compare the benefits of personalized trials versus between-subject trial design, and explain how personalized trials can address special problems associated with multimorbidity for which conventional trials are poorly suited.

Multimorbidity

Multimorbidity (two or more coexisting conditions in an individual) is a growing global challenge with substantial effects on individuals, carers and society. Multimorbidity occurs a decade earlier in socioeconomically deprived communities and is associated with premature death, poorer function and quality of life and increased health-care utilization. Mechanisms underlying the development of multimorbidity are complex, interrelated and multilevel, but are related to ageing and underlying biological mechanisms and broader determinants of health such as socioeconomic deprivation. Little is known about prevention of multimorbidity, but focusing on psychosocial and behavioural factors, particularly population level interventions and structural changes, is likely to be beneficial. Most clinical practice guidelines and health-care training and delivery focus on single diseases, leading to care that is sometimes inadequate and potentially harmful. Multimorbidity requires person-centred care, prioritizing what matters most to the individual and the individual's carers, ensuring care that is effectively coordinated and minimally disruptive, and aligns with the patient's values. Interventions are likely to be complex and multifaceted. Although an increasing number of studies have examined multimorbidity interventions, there is still limited evidence to support any approach. Greater investment in multimorbidity research and training along with reconfiguration of health care supporting the management of multimorbidity is urgently needed.

Biomarkers of pre-pregnancy allostatic load and subsequent adverse birth outcomes

Racial disparities in birth outcomes are seemingly intractable. Using person-centered methods and drawing from the life course and Weathering Hypothesis literatures, we used data from the National Longitudinal Study of Adolescent to Adult Health to group non-Hispanic White and non-Hispanic Black women ages 24-34 into latent classes based on pre-pregnancy biomarkers of allostatic load. Stratified analyses yielded four latent classes among non-Hispanic White women, characterized by: 1) high blood pressure, 2) high body mass index and waist circumference, 3) high total cholesterol and triglycerides, and low high-density lipoprotein, and 4) low-risk, and two latent classes among non-Hispanic Black women, characterized by: 1) high body mass index and waist circumference, and moderate-risk blood pressure, hbA1c, and c-reactive protein, and 2) low-risk. Allostatic load class membership and other maternal- and infant-level covariates were then included simultaneously as predictors of three separate dichotomous outcomes: preterm birth, macrosomia, and low birth weight in multilevel logistic regression models. In a separate multilevel linear regression model, the same variables were simultaneously entered to predict continuously measured birthweight. In multilevel, multivariate models, White women in the high-risk body mass index and waist circumference class, as compared to the high-risk blood pressure class, had infants with higher birthweights. Other comparisons were not significant or not of meaningful magnitude. Prioritizing temporality so that allostatic load measurement preceded first birth likely biased the composition of the analytical sample. Additional research is needed to help medical providers and public health practitioners understand the complex biological and social mechanisms underlying inequities in birth outcomes and identify prevention strategies.

Multimorbidity patterns and associated factors in older Chinese: results from the China health and retirement longitudinal study

Background

This study aimed to investigate multimorbidity patterns and their associated factors among elderly population in China.

Methods

A total of 10,479 participants aged at least 60 years were drawn from the 2018 wave of the China Health and Retirement Longitudinal Study (CHARLS). Latent class analysis (LCA) was performed to identify distinct multimorbidity classes based on 14 self-reported chronic conditions. The multinomial logit model was used to analyze the associated factors of multimorbidity patterns, focusing on individuals' demographic characteristics, socioeconomic status (SES), and health behaviors.

Results

Among the 10,479 participants (mean age [SD]: 69.1 [7.1]), 65.6% were identified with multimorbidity. Five multimorbidity clusters were identified by LCA: relatively healthy class (49.8%), vascular class (24.7%), respiratory class (5.6%), stomach-arthritis class (14.5%), and multisystem morbidity class (5.4%). Multinomial logit analysis with the relatively healthy class as the reference showed that participants of older age and female sex were more likely to be in the vascular class and multisystem morbidity class. The probability of being in the vascular class was significantly higher for those with high SES. Ever smoking was associated with a higher probability of being in the respiratory class and multisystem morbidity class. Physical activity was associated with lower odds of being assigned to the vascular class, respiratory class, and multisystem class.

Conclusion

The distinct multimorbidity patterns imply that the prevention and care strategy should target a group of diseases instead of a single condition. Prevention interventions should be paid attention to for individuals with risk factors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03154-9.

Barriers and facilitators in using a Clinical Decision Support System for fall risk management for older people: a European survey

PURPOSE

Fall-Risk Increasing Drugs (FRIDs) are an important and modifiable fall-risk factor. A Clinical Decision Support System (CDSS) could support doctors in optimal FRIDs deprescribing. Understanding barriers and facilitators is important for a successful implementation of any CDSS. We conducted a European survey to assess barriers and facilitators to CDSS use and explored differences in their perceptions.

METHODS

We examined and compared the relative importance and the occurrence of regional differences of a literature-based list of barriers and facilitators for CDSS usage among physicians treating older fallers from 11 European countries.

RESULTS

We surveyed 581 physicians (mean age 44.9 years, 64.5% female, 71.3% geriatricians). The main barriers were technical issues (66%) and indicating a reason before overriding an alert (58%). The main facilitators were a CDSS that is beneficial for patient care (68%) and easy-to-use (64%). We identified regional differences, e.g., expense and legal issues were barriers for significantly more Eastern-European physicians compared to other regions, while training was selected less often as a facilitator by West-European physicians. Some physicians believed that due to the medical complexity of their patients, their own clinical judgement is better than advice from the CDSS.

CONCLUSION

When designing a CDSS for Geriatric Medicine, the patient's medical complexity must be addressed whilst maintaining the doctor's decision-making autonomy. For a successful CDSS implementation in Europe, regional differences in barrier perception should be overcome. Equipping a CDSS with prediction models has the potential to provide individualized recommendations for deprescribing FRIDs in older falls patients.

Age and Ageing journal 50th anniversary commentary seriesWhy illness is more important than disease in old age

Clinical reasoning and research in modern geriatrics often prioritises the disease concept. This is understandable as it has brought impressive advances in medicine (e.g. antibiotics, vaccines, successful cancer treatment and many effective surgeries). However, so far the disease framework has not succeeded in getting us to root causes of many age-related chronic diseases (e.g. Alzheimer’s disease, diabetes, osteoarthritis). Moreover, in aging and disease constructs alone fail to explain the variability in illness presentations.

Therefore, we propose to apply the underused illness concept in a new way by reconsidering the importance of common symptoms in the form of a dynamic network of symptoms as a complementary framework. We show that concepts and methods of complex system thinking now enable to fruitfully monitor and analyse the multiple interactions between symptoms in such in networks, offering new routes for prognosis and treatment. Moreover, close attention to the symptoms that bother older persons may also improve weighing the therapeutic objectives of well-being and survival and aligning treatment targets with the patients’ priorities.

Mortality and years of life lost of cardiovascular diseases in China, 2005-2020: Empirical evidence from national mortality surveillance system

OBJECTIVES

Cardiovascular disease (CVD) is leading cause of death in China. We aimed to provide national and subnational estimates and its change of premature mortality burden of CVD during 2005-2020.

METHODS

Data from multi-source on the basis of national mortality surveillance system (NMSS) was used to estimate mortality and years of life lost (YLL) of total CVD and its subcategories in Chinese population across 31 provinces during 2005-2020.

RESULTS

Estimated CVD deaths increased from 3.09 million in 2005 to 4.58 million in 2020; the age-standardized mortality rate (ASMR) decreased from 286.85 per 100,000 in 2005 to 245.39 per 100,000 in 2020. A substantial reduction of 19.27% of CVD premature mortality burden, as measured by age-standardized YLL rate, was observed. Ischemic heart disease (IHD), hemorrhagic stroke (HS) and ischemic stroke (IS) were leading 3 causes of CVD death. Marked differences were observed in geographical patterns for total CVD and its subcategories, and it appeared to be lower in areas with higher economic development. Population ageing was dominant driver contributed to CVD deaths increase, followed by population growth. And, age-specific mortality shifts contributed largely to CVD deaths decline in most provinces.

CONCLUSION

Substantial discrepancies were demonstrated in CVD premature mortality burden across China. Targeted considerations were needed to integrate primary care with clinical care through intensifying further strategies for reducing CVD mortality among specific subcategories, high risk population and regions with inadequate healthcare resources.

Theories of self-care and self-management of long-term conditions by community-dwelling older adults: A systematic review and meta-ethnography

RATIONALE

The proportion of older adults living with long-term conditions (LTCs) is increasing. Self-care and self-management approaches are seen as valuable in helping older people with LTCs to manage their health and care, yet the theoretical overlaps and divergences are not always clear.

OBJECTIVES

The objectives of this review were to: (1) systematically identify and appraise studies of self-care or self-management of LTCs by community-dwelling older adults (aged ≥60 years) either informed by, applying, creating, or testing theory; (2) explore similarities or points of convergence between the identified theories; and (3) use a meta-ethnographic approach to synthesise the theories and group related concepts into core constructs.

METHODS

We conducted a systematic theory synthesis, searching six electronic databases. Three reviewers independently screened titles and abstracts followed by full texts and two reviewers appraised study quality. Theoretical data were synthesised within and across individual theories using meta-ethnographic line-of-argument synthesis.

RESULTS

A total of 141 articles (138 studies) and 76 theories were included in the review. Seven core constructs were developed: (1) temporal and spatial context; (2) stressors; (3) personal resources; (4) informal social resources; (5) formal social resources; (6) behavioural adaptations; and (7) quality of life outcomes. A line of argument was developed that conceptualised older adults' self-care and self-management as a dynamic process of behavioural adaptation, enabled by personal resources and informal and formal social resources, aimed at alleviating the impacts of stressors and maintaining quality of life.

CONCLUSION

This synthesis provides an overview of theories used in research on older adults' LTC self-care and self-management. Our synthesis describes the complex interplay of intrinsic and extrinsic factors influencing self-care and self-management behaviours and provides considerations for future research, intervention design, and implementation. The utility of the constructs in research and practice requires further attention and empirical validation.

Comorbidity Burden and Adverse Outcomes After Transcatheter Aortic Valve Replacement

Background

Transcatheter aortic valve replacement (TAVR) has become the preferred treatment for symptomatic patients with aortic stenosis and elevated procedural risk. Many deaths following TAVR are because of noncardiac causes and comorbid disease burden may be a major determinant of postprocedure outcomes. The prevalence of comorbid conditions and associations with outcomes after TAVR has not been studied.

Methods and Results

This was a retrospective single‐center study of patients treated with TAVR from January 2015 to October 2018. The association between 21 chronic conditions and short‐ and medium‐term outcomes was assessed. A total of 341 patients underwent TAVR and had 1‐year follow‐up. The mean age was 81.4 (SD 8.0) years with a mean Society of Thoracic Surgeons predicted risk of mortality score of 6.7% (SD 4.8). Two hundred twenty (65%) patients had ≥4 chronic conditions present at the time of TAVR. There was modest correlation between Society of Thoracic Surgeons predicted risk of mortality and comorbid disease burden (r=0.32, P<0.001). After adjusting for Society of Thoracic Surgeons predicted risk of mortality, age, and vascular access, each additional comorbid condition was associated with increased rates of 30‐day rehospitalizations (odds ratio, 1.21; 95% CI, 1.02–1.44), a composite of 30‐day rehospitalization and 30‐day mortality (odds ratio, 1.20; 95% CI, 1.02–1.42), and 1‐year mortality (odds ratio, 1.29; 95% CI, 1.05–1.59).

Conclusions

Comorbid disease burden is associated with worse clinical outcomes in high‐risk patients treated with TAVR. The risks associated with comorbid disease burden are not adequately captured by standard risk assessment. A systematic assessment of comorbid conditions may improve risk stratification efforts.

Use of machine learning in geriatric clinical care for chronic diseases: a systematic literature review

Objectives

Geriatric clinical care is a multidisciplinary assessment designed to evaluate older patients’ (age 65 years and above) functional ability, physical health, and cognitive well-being. The majority of these patients suffer from multiple chronic conditions and require special attention. Recently, hospitals utilize various artificial intelligence (AI) systems to improve care for elderly patients. The purpose of this systematic literature review is to understand the current use of AI systems, particularly machine learning (ML), in geriatric clinical care for chronic diseases.

Materials and Methods

We restricted our search to eight databases, namely PubMed, WorldCat, MEDLINE, ProQuest, ScienceDirect, SpringerLink, Wiley, and ERIC, to analyze research articles published in English between January 2010 and June 2019. We focused on studies that used ML algorithms in the care of geriatrics patients with chronic conditions.

Results

We identified 35 eligible studies and classified in three groups: psychological disorder (n = 22), eye diseases (n = 6), and others (n = 7). This review identified the lack of standardized ML evaluation metrics and the need for data governance specific to health care applications.

Conclusion

More studies and ML standardization tailored to health care applications are required to confirm whether ML could aid in improving geriatric clinical care.

Timing of onset and self-management of multiple chronic conditions: A qualitative examination taking a lifespan perspective

OBJECTIVES

Over two-thirds of older individuals live with multiple chronic conditions, yet chronic diseases are often studied in silos. Taking a lifespan approach to understanding the development of multiple chronic conditions in the older population helps to further elucidate opportunities for targeted interventions that address the complexities of multiple chronic conditions.

METHODS

Semi-structured interviews were conducted with 38 older adults (age 64+) diagnosed with at least two chronic health conditions. Content analysis was used to build understanding of how older adults discuss the timing of diagnoses and subsequent self-management of multiple chronic conditions.

RESULTS

Findings highlight the complex process by which illnesses unfold in the context of individuals' lives and the subsequent engagement and/or disengagement in self-management behaviors. Two primary themes were evident regarding timing of illnesses: illnesses were experienced within the context of social life events and/or health events, and illnesses were not predominantly seen as connected to one another by patients. Self-management behaviors were described in response to onset of each illness.

DISCUSSION

Findings provide insight into how older adults understand their experience of multiple chronic conditions and change in self-management behaviors over time. In order for practitioners to ignite behavioral changes, a person's history and life experiences must be considered.

Representation of people with comorbidity and multimorbidity in clinical trials of novel drug therapies: an individual-level participant data analysis

BACKGROUND

Clinicians are less likely to prescribe guideline-recommended treatments to people with multimorbidity than to people with a single condition. Doubts as to the applicability of clinical trials of drug treatments (the gold standard for evidence-based medicine) when people have co-existing diseases (comorbidity) may underlie this apparent reluctance. Therefore, for a range of index conditions, we measured the comorbidity among participants in clinical trials of novel drug therapies and compared this to the comorbidity among patients in the community.

METHODS

Data from industry-sponsored phase 3/4 multicentre trials of novel drug therapies for chronic medical conditions were identified from two repositories: Clinical Study Data Request and the Yale University Open Data Access project. We identified 116 trials (n = 122,969 participants) for 22 index conditions. Community patients were identified from a nationally representative sample of 2.3 million patients in Wales, UK. Twenty-one comorbidities were identified from medication use based on pre-specified definitions. We assessed the prevalence of each comorbidity and the total number of comorbidities (level of multimorbidity), for each trial and in community patients.

RESULTS

In the trials, the commonest comorbidities in order of declining prevalence were chronic pain, cardiovascular disease, arthritis, affective disorders, acid-related disorders, asthma/COPD and diabetes. These conditions were also common in community-based patients. Mean comorbidity count for trial participants was approximately half that seen in community-based patients. Nonetheless, a substantial proportion of trial participants had a high degree of multimorbidity. For example, in asthma and psoriasis trials, 10-15% of participants had ≥ 3 conditions overall, while in osteoporosis and chronic obstructive pulmonary disease trials 40-60% of participants had ≥ 3 conditions overall.

CONCLUSIONS

Comorbidity and multimorbidity are less common in trials than in community populations with the same index condition. Comorbidity and multimorbidity are, nevertheless, common in trials. This suggests that standard, industry-funded clinical trials are an underused resource for investigating treatment effects in people with comorbidity and multimorbidity.

Multimorbidity: Implications and directions for health psychology and behavioral medicine

The increasing prevalence of multimorbidity in the United States and the rest of the world poses problems for patients and for health care providers, care systems, and policy. After clarifying the difference between comorbidity and multimorbidity, this article describes the challenges that the prevalence of multimorbidity presents for well-being, prevention, and medical treatment. We submit that health psychology and behavioral medicine have an important role to play in meeting these challenges because of the holistic vision of health afforded by the foundational biopsychosocial model. Furthermore, opportunities abound for health psychology/behavioral medicine to study how biological, social and psychological factors influence multimorbidity. This article describes three major areas in which health psychologists can contribute to understanding and treatment of multimorbidity: (a) etiology; (b) prevention and self-management; and (c) clinical care. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Self-care research: Where are we now? Where are we going?

BACKGROUND AND OBJECTIVE

The beneficial effects of self-care include improved well-being and lower morbidity, mortality, and healthcare costs. In this article we address the current state of self-care research and propose an agenda for future research based on the inaugural conference of the International Center for Self-Care Research held in Rome, Italy in June 2019. The vision of this Center is a world where self-care is prioritized by individuals, families, and communities and is the first line of approach in every health care encounter. The mission of the Center is to lead the self-care research endeavor, improving conceptual clarity and promoting interdisciplinary work informed by a shared vision addressing knowledge gaps. A focused research agenda can deepen our theoretical understanding of self-care and the mechanisms underlying self-care, which can contribute to the development of effective interventions that improve outcomes.

METHODS

During conference discussions, we identified seven major reasons why self-care is challenging, which can be grouped into the general categories of behavior change and illness related factors. We identified six specific knowledge gaps that, if addressed, may help to address these challenges: the influence of habit formation on behavior change, resilience in the face of stressful life events that interfere with self-care, the influence of culture on self-care behavioral choices, the difficulty performing self-care with multiple chronic conditions, self-care in persons with severe mental illness, and the influence of others (care partners, family, peer supporters, and healthcare professionals) on self-care.

PLANS TO ACHIEVE RESULTS

To achieve the vision and mission of the Center, we will lead a collaborative program of research that addresses self-care knowledge gaps and improves outcomes, create a supportive international network for knowledge transfer and support of innovations in self-care research, and support and train others in self-care research. Beyond these specific short-term goals, important policy implications of this work are discussed.

Health professions digital education on clinical practice guidelines: a systematic review by Digital Health Education collaboration

BACKGROUND

Clinical practice guidelines are an important source of information, designed to help clinicians integrate research evidence into their clinical practice. Digital education is increasingly used for clinical practice guideline dissemination and adoption. Our aim was to evaluate the effectiveness of digital education in improving the adoption of clinical practice guidelines.

METHODS

We performed a systematic review and searched seven electronic databases from January 1990 to September 2018. Two reviewers independently screened studies, extracted data and assessed risk of bias. We included studies in any language evaluating the effectiveness of digital education on clinical practice guidelines compared to other forms of education or no intervention in healthcare professionals. We used the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach to assess the quality of the body of evidence.

RESULTS

Seventeen trials involving 2382 participants were included. The included studies were diverse with a largely unclear or high risk of bias. They mostly focused on physicians, evaluated computer-based interventions with limited interactivity and measured participants' knowledge and behaviour. With regard to knowledge, studies comparing the effect of digital education with no intervention showed a moderate, statistically significant difference in favour of digital education intervention (SMD = 0.85, 95% CI 0.16, 1.54; I2 = 83%, n = 3, moderate quality of evidence). Studies comparing the effect of digital education with traditional learning on knowledge showed a small, statistically non-significant difference in favour of digital education (SMD = 0.23, 95% CI - 0.12, 0.59; I2 = 34%, n = 3, moderate quality of evidence). Three studies measured participants' skills and reported mixed results. Of four studies measuring satisfaction, three studies favoured digital education over traditional learning. Of nine studies evaluating healthcare professionals' behaviour change, only one study comparing email-delivered, spaced education intervention to no intervention reported improvement in the intervention group. Of three studies reporting patient outcomes, only one study comparing email-delivered, spaced education games to non-interactive online resources reported modest improvement in the intervention group. The quality of evidence for outcomes other than knowledge was mostly judged as low due to risk of bias, imprecision and/or inconsistency.

CONCLUSIONS

Health professions digital education on clinical practice guidelines is at least as effective as traditional learning and more effective than no intervention in terms of knowledge. Most studies report little or no difference in healthcare professionals' behaviours and patient outcomes. The only intervention shown to improve healthcare professionals' behaviour and modestly patient outcomes was email-delivered, spaced education. Future research should evaluate interactive, simulation-based and spaced forms of digital education and report on outcomes such as skills, behaviour, patient outcomes and cost.

Why does quality of life remain an under-investigated issue in chronic kidney disease and why is it rarely set as an outcome measure in trials in this population?

The growing importance of quality of life (QoL) measures in health care is reflected by the increased volume and rigor of published research on this topic. The ability to measure and assess patients' experience of symptoms and functions has transformed the development of disease treatments and interventions. However, QoL remains an under-investigated issue in chronic kidney disease (CKD) and is seldom set as an outcome measure in trials in this population. In this article, we present various challenges in using patient-reported outcome (PRO) end points in CKD trials. We outline the need for additional research to examine more closely patient experiences with specific kidney disease symptoms and conditions, as well as caregiver perspectives of patients' symptom burden and end-of-life experiences. These efforts will better guide the development or enhancement of PRO instruments that can be used in clinical trials to more effectively assess treatment benefit, and improve therapy and care. Better understanding of health-related QoL issues would enable providers to deliver more patient-centered care and improve the overall well-being of patients. Even small improvements in QoL could have a large impact on the population's overall health and disease burden.

Audit of anticholinergic medication changes in older hospitalised patients using the Anticholinergic Drug Scale

BACKGROUND/AIM

In patients discharged from an Older Person's Health hospital, we assessed (i) the prevalence of anticholinergic medications (ACM) in this study population and (ii) changes in anticholinergic drug burden during admission using the Anticholinergic Drug Scale (ADS).

METHODS

Cases were identified between September 2010 and January 2011 using discharge coding data. Clinical notes were reviewed to determine which regular oral medications were commenced, altered or ceased during admission with their respective ADS level. The anticholinergic drug burden was measured using the total ADS score for each patient on presentation and at discharge. The difference in these two values was defined as the overall change in ADS.

RESULTS

There was a total of 224 cases. Median age was 83 years (interquartile range 78-87). Median total number of medications per patient on both admission and discharge was 6. Most (168/224, 75%) patients were discharged on ACM, including 25% (56/224) with a high total ADS score. The medications most commonly commenced and ceased were laxatives and diuretics respectively. These medications had ADS level 0-1. There was no significant change in ADS score between admission and discharge (P = 0.50).

CONCLUSION

The total number of medications prescribed and the overall anticholinergic drug burden did not change significantly despite geriatric assessment.

Patient and caregiver goals for dementia care

PURPOSE

Most health outcome measures for chronic diseases do not incorporate specific health goals of patients and caregivers. To elicit patient-centered goals for dementia care, we conducted a qualitative study using focus groups of people with early-stage dementia and dementia caregivers.

METHODS

We conducted 5 focus groups with 43 participants (7 with early-stage dementia and 36 caregivers); 15 participants were Spanish-speaking. Verbatim transcriptions were independently analyzed line-by-line by two coders using both deductive and inductive approaches. Coded texts were grouped into domains and developed into a goal inventory for dementia care.

RESULTS

Participants identified 41 goals for dementia care within five domains (medical care, physical quality of life, social and emotional quality of life, access to services and supports, and caregiver support). Caregiver goals included ensuring the safety of the person with dementia and managing caregiving stress. Participants with early-stage dementia identified engaging in meaningful activity (e.g., work, family functions) and not being a burden on family near the end of life as important goals. Participants articulated the need to readdress goals as the disease progressed and reported challenges in goal-setting when goals differed between the person with dementia and the caregiver (e.g., patient safety vs. living independently at home). While goals were similar among English- and Spanish-speaking participants, Spanish-speaking participants emphasized the need to improve community education about dementia.

CONCLUSIONS

Patient- and caregiver-identified goals for care are different than commonly measured health outcomes for dementia. Future work should incorporate patient-centered goals into clinical settings and assess their usefulness for dementia care.

Disability stage and receipt of recommended care among elderly medicare beneficiaries

BACKGROUND

Receipt of recommended care among older adults is generally low. Findings regarding service use among persons with disabilities supports the notion of disparities but provides inconsistent evidence of underuse of recommended care.

OBJECTIVE

To examine the extent to which receipt of recommended care among older Medicare beneficiaries varies by disability status, using a newly developed staging method to classify individuals according to disability.

METHODS

In a cohort study, we included community-dwelling Medicare beneficiaries aged 65 and older who participated in the Medicare Current Beneficiary Survey between 2001 and 2008. Logistic regression modeling assessed the association of receiving recommended care on 38 indicators across different activity limitation stages.

RESULTS

Nearly one out of every three elderly Medicare beneficiaries did not receive overall recommended care. Adjusted odds ratios (ORs) revealed a decrease in use of recommended care with increasing activity limitation stage. For instance, ORs (95% CIs) across mild, moderate, severe and complete limitation stages (stages I-IV) compared to no limitation (stage 0) in ADLs were 0.99 (0.94-1.05), 0.89 (0.83-0.95), 0.81 (0.75-0.89) and 0.56 (0.46-0.68). Disparities in receipt of recommended care by disability stage were most marked for care related to post-hospitalization follow-up and, to a lesser degree, care of chronic conditions and preventive care.

CONCLUSIONS

Elderly beneficiaries at higher activity limitation stages experienced substantial disparities in receipt of recommended care. Tailored interventions may be needed to reduce disparities in receipt of recommended medical care in this population.

Future Research Directions for Multimorbidity Involving Cardiovascular Diseases

Multimorbidity, defined as the co-occurrence of two or more chronic conditions, increases with age and may be found in approximately two-thirds of older adults in population studies, commonly including a variety of cardiovascular risk factors and chronic diseases. This article offers a research agenda for cardiovascular disease from a patient-centered multimorbidity perspective. Definitional issues remain for multimorbidity, along with high interest in understanding the inter-relationships between aging, diseases, treatments, and organ dysfunction in the development and progression of multimorbidity. Clinical trials, practice-based and population-based observational studies, and linkages of big data can play a role in improving health outcomes among persons with multimorbidity.

Caring for patients with kidney disease: shifting the paradigm from evidence-based medicine to patient-centered care

The last several decades have witnessed the emergence of evidence-based medicine as the dominant paradigm for medical teaching, research and practice. Under an evidence-based approach, populations rather than individuals become the primary focus of investigation. Treatment priorities are largely shaped by the availability, relevance and quality of evidence and study outcomes and results are assumed to have more or less universal significance based on their implications at the population level. However, population-level treatment goals do not always align with what matters the most to individual patients-who may weigh the risks, benefits and harms of recommended treatments quite differently. In this article we describe the rise of evidence-based medicine in historical context. We discuss limitations of this approach for supporting real-world treatment decisions-especially in older adults with confluent comorbidity, functional impairment and/or limited life expectancy-and we describe the emergence of more patient-centered paradigms to address these limitations. We explain how the principles of evidence-based medicine have helped to shape contemporary approaches to defining, classifying and managing patients with chronic kidney disease. We discuss the limitations of this approach and the potential value of a more patient-centered paradigm, with a particular focus on the care of older adults with this condition. We conclude by outlining ways in which the evidence-base might be reconfigured to better support real-world treatment decisions in individual patients and summarize relevant ongoing initiatives.

What to Expect From the Evolving Field of Geriatric Cardiology

The population of older adults is expanding rapidly, and aging predisposes to cardiovascular disease. The principle of patient-centered care must respond to the preponderance of cardiac disease that now occurs in combination with the complexities of old age. Geriatric cardiology melds cardiovascular perspectives with multimorbidity, polypharmacy, frailty, cognitive decline, and other clinical, social, financial, and psychological dimensions of aging. Although some assume that a cardiologist may instinctively cultivate some of these skills over the course of a career, we assert that the volume and complexity of older cardiovascular patients in contemporary practice warrants a more direct approach to achieve suitable training and a more reliable process of care. We present a rationale and vision for geriatric cardiology as a melding of primary cardiovascular and geriatrics skills, thereby infusing cardiology practice with expanded proficiencies in diagnosis, risks, care coordination, communications, end-of-life, and other competences required to best manage older cardiovascular patients.

Trends and interaction of polypharmacy and potentially inappropriate prescribing in primary care over 15 years in Ireland: a repeated cross-sectional study

OBJECTIVES

To examine: (1) changes in polypharmacy in 1997, 2002, 2007 and 2012 and; (2) changes in potentially inappropriate prescribing (PIP) prevalence and the relationship between PIP and polypharmacy in individuals aged ≥65 years over this period in Ireland.

METHODS

This repeated cross-sectional study using pharmacy claims data included all individuals eligible for the General Medical Services scheme in the former Eastern Health Board region of Ireland in 1997, 2002, 2007 and 2012 (range 338,025-539,752 individuals). Outcomes evaluated were prevalence of polypharmacy (being prescribed ≥5 regular medicines) and excessive polypharmacy (≥10 regular medicines) in all individuals and PIP prevalence in those aged ≥65 years determined by 30 criteria from the Screening Tool for Older Persons' Prescriptions.

RESULTS

The prevalence of polypharmacy increased from 1997 to 2012, particularly among older individuals (from 17.8% to 60.4% in those aged ≥65 years). The adjusted incident rate ratio for polypharmacy in 2012 compared to 1997 was 4.16 (95% CI 3.23 to 5.36), and for excessive polypharmacy it was 10.53 (8.58 to 12.91). Prevalence of PIP rose from 32.6% in 1997 to 37.3% in 2012. High-dose aspirin and digoxin prescribing decreased over time, but long-term proton pump inhibitors at maximal dose increased substantially (from 0.8% to 23.8%). The odds of having any PIP in 2012 were lower compared to 1997 after controlling for gender and level of polypharmacy, OR 0.39 (95% CI 0.39 to 0.4).

CONCLUSIONS

Accounting for the marked increase in polypharmacy, prescribing quality appears to have improved with a reduction in the odds of having PIP from 1997 to 2012. With growing numbers of people taking multiple regular medicines, strategies to address the related challenges of polypharmacy and PIP are needed.

Geriatric Pharmacology

Aging involves changes in several physiologic processes that lead to decreased volumes of distribution, slowed metabolism, and increased end-organ sensitivity to anesthetics. These changes generally result in increased potency. Elderly patients require less anesthetic medication, but the true extent of reduction is underappreciated and less uniformly practiced. The impact of potential anesthetic drug overdosing on intermediate and long-term outcomes is not fully appreciated. It may be necessary to consider age as a continuous variable for anesthetic drug dosing in older patients rather than treating adult versus elderly patients. Further pharmacologic studies are required in people more than 85 years old.

Aging and Multimorbidity: New Tasks, Priorities, and Frontiers for Integrated Gerontological and Clinical Research

Aging is characterized by rising susceptibility to development of multiple chronic diseases and, therefore, represents the major risk factor for multimorbidity. From a gerontological perspective, the progressive accumulation of multiple diseases, which significantly accelerates at older ages, is a milestone for progressive loss of resilience and age-related multisystem homeostatic dysregulation. Because it is most likely that the same mechanisms that drive aging also drive multiple age-related chronic diseases, addressing those mechanisms may reduce the development of multimorbidity. According to this vision, studying multimorbidity may help to understand the biology of aging and, at the same time, understanding the underpinnings of aging may help to develop strategies to prevent or delay the burden of multimorbidity. As a consequence, we believe that it is time to build connections and dialogue between the clinical experience of general practitioners and geriatricians and the scientists who study aging, so as to stimulate innovative research projects to improve the management and the treatment of older patients with multiple morbidities.

Drug-disease and drug-drug interactions: systematic examination of recommendations in 12 UK national clinical guidelines

OBJECTIVE

To identify the number of drug-disease and drug-drug interactions for exemplar index conditions within National Institute of Health and Care Excellence (NICE) clinical guidelines.

DESIGN

Systematic identification, quantification, and classification of potentially serious drug-disease and drug-drug interactions for drugs recommended by NICE clinical guidelines for type 2 diabetes, heart failure, and depression in relation to 11 other common conditions and drugs recommended by NICE guidelines for those conditions.

SETTING

NICE clinical guidelines for type 2 diabetes, heart failure, and depression

MAIN OUTCOME MEASURES

Potentially serious drug-disease and drug-drug interactions.

RESULTS

Following recommendations for prescription in 12 national clinical guidelines would result in several potentially serious drug interactions. There were 32 potentially serious drug-disease interactions between drugs recommended in the guideline for type 2 diabetes and the 11 other conditions compared with six for drugs recommended in the guideline for depression and 10 for drugs recommended in the guideline for heart failure. Of these drug-disease interactions, 27 (84%) in the type 2 diabetes guideline and all of those in the two other guidelines were between the recommended drug and chronic kidney disease. More potentially serious drug-drug interactions were identified between drugs recommended by guidelines for each of the three index conditions and drugs recommended by the guidelines for the 11 other conditions: 133 drug-drug interactions for drugs recommended in the type 2 diabetes guideline, 89 for depression, and 111 for heart failure. Few of these drug-disease or drug-drug interactions were highlighted in the guidelines for the three index conditions.

CONCLUSIONS

Drug-disease interactions were relatively uncommon with the exception of interactions when a patient also has chronic kidney disease. Guideline developers could consider a more systematic approach regarding the potential for drug-disease interactions, based on epidemiological knowledge of the comorbidities of people with the disease the guideline is focused on, and should particularly consider whether chronic kidney disease is common in the target population. In contrast, potentially serious drug-drug interactions between recommended drugs for different conditions were common. The extensive number of potentially serious interactions requires innovative interactive approaches to the production and dissemination of guidelines to allow clinicians and patients with multimorbidity to make informed decisions about drug selection.

IOM and DHHS meeting on making clinical practice guidelines appropriate for patients with multiple chronic conditions

BACKGROUND

The increasing prevalence of Americans with multiple (2 or more) chronic conditions raises concerns about the appropriateness and applicability of clinical practice guidelines for patient management. Most guidelines clinicians currently rely on have been designed with a single chronic condition in mind, and many such guidelines are inattentive to issues related to comorbidities.

PURPOSE

In response to the need for guideline developers to address comorbidities in guidelines, the Department of Health and Human Services convened a meeting in May 2012 in partnership with the Institute of Medicine to identify principles and action options.

RESULTS

Eleven principles to improve guidelines' attentiveness to the population with multiple chronic conditions were identified during the meeting. They are grouped into 3 interrelated categories: (1) principles intended to improve the stakeholder technical process for developing guidelines; (2) principles intended to strengthen content of guidelines in terms of multiple chronic conditions; and (3) principles intended to increase focus on patient-centered care.

CONCLUSION

This meeting built upon previously recommended actions by identifying additional principles and options for government, guideline developers, and others to use in strengthening the applicability of clinical practice guidelines to the growing population of people with multiple chronic conditions. The suggested principles are helping professional societies to improve guidelines' attentiveness to persons with multiple chronic conditions.

A framework for crafting clinical practice guidelines that are relevant to the care and management of people with multimorbidity

Many patients of all ages have multiple conditions, yet clinicians often lack explicit guidance on how to approach clinical decision-making for such people. Most recommendations from clinical practice guidelines (CPGs) focus on the management of single diseases, and may be harmful or impractical for patients with multimorbidity. A major barrier to the development of guidance for people with multimorbidity stems from the fact that the evidence underlying CPGs derives from studies predominantly focused on the management of a single disease. In this paper, the investigators from the Improving Guidelines for Multimorbid Patients Study Group present consensus-based recommendations for guideline developers to make guidelines more useful for the care of people with multimorbidity. In an iterative process informed by review of key literature and experience, we drafted a list of issues and possible approaches for addressing important coexisting conditions in each step of the guideline development process, with a focus on considering relevant interactions between the conditions, their treatments and their outcomes. The recommended approaches address consideration of coexisting conditions at all major steps in CPG development, from nominating and scoping the topic, commissioning the work group, refining key questions, ranking importance of outcomes, conducting systematic reviews, assessing quality of evidence and applicability, summarizing benefits and harms, to formulating recommendations and grading their strength. The list of issues and recommendations was reviewed and refined iteratively by stakeholders. This framework acknowledges the challenges faced by CPG developers who must make complex judgments in the absence of high-quality or direct evidence. These recommendations require validation through implementation, evaluation and refinement.