Multimorbidity Trends in United States Adults, 1988-2014

Discrimination and Multimorbidity Among Black Americans: Findings from the National Survey of American Life

OBJECTIVES

There is a notable lack of research on the risk factors for multimorbidity, which has become more common over recent decades. Black Americans experience discrimination more often than their White counterparts, and also have significantly higher prevalence of multimorbidity. This paper examines the associations between discrimination and multimorbidity among Black Americans.

METHODS

We analyzed data from the National Survey of American Life to calculate the prevalence of two types of discrimination (everyday discrimination, major discriminatory events) and multimorbidity (physical, psychiatric, mixed, any). Using multivariable logistic regression, we examined the associations between discrimination and multimorbidity, adjusting for age, sex, years of education, income-to-poverty ratio, and ethnicity. The everyday discrimination scale was discretized into five categories (none, low, medium, high, very high), but was also treated as a continuous variable. The major discriminatory events were analyzed in separate adjusted models, and as a count of events.

RESULTS

When compared with those who did not experience any discrimination, people who experienced everyday discrimination were significantly more likely to report all types of multimorbidity in a dose-response fashion at a conventional level of statistical significance. Most major discriminatory events were associated with greater odds of reporting all types of multimorbidity, as were the counts of major discriminatory events, in a dose-response fashion.

CONCLUSIONS

We found strong evidence to suggest that discrimination was associated with greater odds of reporting multimorbidity. Future studies can expand on these findings using longitudinal data to capture the relations between discrimination and health over time, or by testing preventive interventions that allay the damaging health effects of discrimination.

Immune checkpoint inhibitor use, multimorbidity and healthcare expenditures among older adults with late-stage melanoma

Background: The objective of this study is to assess the impact of immune checkpoint inhibitors (ICIs) and multimorbidity on healthcare expenditures among older patients with late-stage melanoma. Materials & methods: A retrospective longitudinal cohort study using Surveillance, Epidemiology and End Results linked with Medicare claims was conducted. Generalized linear mixed models were used to analyze adjusted relationships of ICI, multimorbidity and ICI-multimorbidity interaction on average healthcare expenditures. Results: Patients who received ICI and those who had multimorbidity had significantly higher average total healthcare expenditures compared with ICI nonusers and no multimorbidity. In the fully adjusted model using ICI-multimorbidity interaction, no excess cost was added by multimorbidity. Conclusion: Use of ICIs, regardless of multimorbidity, is associated with increased healthcare expenditures.

Gender Differences in Factors Affecting Life Satisfaction of the Elderly with Multimorbidity in Korea

To enhance the life satisfaction of the elderly with multimorbidity, it is necessary to investigate the relevant factors and to examine the differences in factors according to gender. The aim of this study was to identify factors affecting life satisfaction of the elderly with multimorbidity in the community by gender in Korea. We analyzed data from 2140 participants with multimorbidity who were aged 65 or older and participated in the Korean Longitudinal Study of Ageing (KLoSA) in 2016. A multivariate linear regression analysis was conducted to examine the factors affecting life satisfaction among male and female older participants with multimorbidity. The most common pattern of multimorbidity of women was hypertension and arthritis/rheumatism, while that of men was hypertension and diabetes mellitus. Some factors, such as depression, exercise, and number of chronic diseases, affected both male and female participants, but others related to life satisfaction varied by gender. Therefore, it is necessary to consider the characteristics of multiple chronic diseases, and policy support should be provided in consideration of gender differences to improve the life satisfaction of the elderly.

A cross-sectional study investigating the relationship between handgrip strength with multimorbidity in Korean adults: Findings from the Korea National Health and Nutrition Examination Survey VI-VII (2014-2017)

To date research investigating the associations between handgrip strength and multimorbidity when stratifying by age and sex is limited. Furthermore, this is the first study in a Korean population, and the first to include adults ≥ 19 years of age. Here we investigated the associations between handgrip strength and multimorbidity in Korean adults aged ≥ 19 years.In this cross-sectional study data from the Korean National Health and Nutrition Examination Survey were used. Multimorbidity was defined as having 2 or more chronic diseases. A total of 19,779 participants were eligible for the study (8730 male and 11,049 female). We grouped and analysed participants based on age and sex (men and women aged 19-49 years, men and women aged 50-80 years) and examined the associations between handgrip strength and multimorbidity using multivariate logistic regressions using stratification by age, sex and body mass index (BMI).Multivariate logistic regressions revealed a significant inverse association irrespective of sex, between relative handgrip strength and multimorbidity. Participants with the lowest handgrip strength had a significantly higher odds ratio (OR) of multimorbidity (men aged 19-49 years: 3.76 and aged 50 years to 80 years: 2.11; women aged 19 years to 49 years: 1.52 and aged 50-80 years: 2.15) when compared to those with highest handgrip strength after adjusting for confounding variables. The highest OR was observed in men aged 19 years to 49 years with a BMI ≥ 25 kg/m2.In the current study we observed a significant inverse relationship between handgrip strength and multimorbidity in males and females with 2 or more chronic diseases. Male participants with a low handgrip strength aged between 19 years to 49 years with a BMI ≥25 kg/m2 may be at greater risk of multimorbidity. This study highlights the need for further longitudinal studies to investigate the effects of increasing handgrip strength combined with weight loss, as an effective strategy to reduce the incidence of multimorbidity.

Utilization and Spending on Potentially Inappropriate Medications by US Older Adults with Multiple Chronic Conditions using Multiple Medications

BACKGROUND

The utilization of potentially inappropriate medications (PIMs) in older adults can lead to adverse events and increased healthcare costs. Polypharmacy, the concurrent utilization of multiple medications, is common in older adults with multiple chronic conditions.

OBJECTIVE

To investigate the utilization and costs of PIMs in multimorbid older adults with polypharmacy over time.

METHODS

This retrospective cross-sectional study used linked Medicare claims and electronic health records from seven hospitals/medical centers in Massachusetts (2007-2014). Participants were ≥65 years old, had ≥2 chronic conditions (to define multimorbidity), and used drugs from ≥5 pharmaceutical classes for ≥90 days (to define polypharmacy). Chronic conditions were defined using the Chronic Conditions Indicator from the Agency for Health Research and Quality. PIMs were defined using the American Geriatrics Society 2019 version of the Beers criteria. We calculated the percentage of patients with ≥1 PIMs and the percentages of patients using different types of PIMs. We used logistic regression analyses to test the odds of taking ≥1 PIMs. We calculated mean costs spent on PIMs by dividing the costs spent on PIMs by the total medication cost.

RESULTS

≥69% of patients used ≥1 PIM. After adjusting for healthcare utilization, chronic conditions, medication intake, and demographic factors, female sex (2014: Odds ratio (OR)=1.27, 95%CI 1.25-1.30), age (2014: OR=0.92, 95%CI 0.90-0.93), and Hispanic ethnicity (2014: OR=1.41, 95%CI 1.27-1.56) were associated with PIM use. Gastrointestinal drugs and central nervous system drugs were the most commonly-used PIMs. In patients using ≥1 PIM, >10% of medication costs were spent on PIMs.

CONCLUSION

The utilization of PIMs in US older adults with multimorbidity and polypharmacy is high.

Identifying multimorbid patients with high care needs - A study based on electronic medical record data

Background

Patients with multimorbidity who frequently contact the general practice, use emergency care or have unplanned hospitalisations, may benefit from a proactive integrated care intervention. General practitioners are not always aware of who these ‘high need’ patients are. Electronic medical records are a potential source to identify them.

Objectives

To find predictors of high care needs in general practice electronic medical records of patients with multimorbidity and assess their predictive value.

Methods

General practice electronic medical records of 245,065 patients with ≥2 chronic diseases were linked to hospital claims data. Probit regression analysis was conducted to predict i) having at least 12 general practice contacts per year, ii) emergency department visit(s), and iii) unplanned hospitalisation(s). Predictors were patients’ age, sex, morbidity, health services and medication use in the previous year.

Results

11% of multimorbid patients had ≥12 general practice contacts, which could be reliably predicted by the number of contacts in the previous year (PPV 42%). The model containing all predictors had only slightly better predictive value (PPV 44%). Emergency department visits and unplanned hospitalisations (12% and 7% of multimorbid patients, respectively) could be predicted less accurately (PPV 27% and 20%). Those with frequent contact with the general practice hardly overlapped with ED visitors (29%) or persons with unplanned hospitalisations (17%).

Conclusion

Among multimorbid populations various ‘high need’ groups exist. Patients with high needs for general practice care can be identified by their previous use of general practice care. To identify frequent ED visitors and persons with unplanned hospitalisations, additional information is needed.

Comparing the prevalence of multimorbidity using different operational definitions in primary care in Singapore based on a cross-sectional study using retrospective, large administrative data

OBJECTIVES

Multimorbidity is a norm in primary care. A consensus on its operational definition remains lacking especially in the list of chronic conditions considered. This study aimed to compare six different operational definitions of multimorbidity previously reported in the literature for the context of primary care in Singapore.

DESIGN, SETTING AND PARTICIPANTS

This is a retrospective study using anonymised primary care data from a study population of 787 446 patients. We defined multimorbidity as having three or more chronic conditions in an individual. The prevalence of single conditions and multimorbidity with each operational definition was tabulated and standardised prevalence rates (SPRs) were obtained by adjusting for age, sex and ethnicity. We compared the operational definitions based on (1) number of chronic diseases, (2) presence of chronic diseases of high burden and (3) relevance in primary care in Singapore. IBM SPSS V.23 and Microsoft Office Excel 2019 were used for all statistical calculations and analyses.

RESULTS

The SPRs of multimorbidity in primary care in Singapore varied from 5.7% to 17.2%. The lists by Fortin et al, Ge et al, Low et al and Quah et al included at least 12 chronic conditions, the recommended minimal number of conditions. Quah et al considered the highest proportion of chronic diseases (92.3%) of high burden in primary care in Singapore, with SPRs of at least 1.0%. Picco et al and Subramaniam et al considered the fewest number of conditions of high relevance in primary care in Singapore.

CONCLUSIONS

Fortin et al's list of conditions is most suitable for describing multimorbidity in the Singapore primary care setting. Prediabetes and 'physical disability' should be added to Fortin et al's list to augment its comprehensiveness. We propose a similar study methodology be performed in other countries to identify the most suitable operational definition in their own context.

The experience of financial burden for people with multimorbidity: A systematic review of qualitative research

Background

Multimorbidity prevalence is increasing globally. People with multimorbidity have higher health care costs, which can create a financial burden.

Objective

To synthesize qualitative research exploring experience of financial burden for people with multimorbidity.

Search strategy

Six databases were searched in May 2019. A grey literature search and backward and forward citation checking were also conducted.

Inclusion criteria

Studies were included if they used a qualitative design, conducted primary data collection, included references to financial burden and had at least one community‐dwelling adult participant with two or more chronic conditions.

Data extraction and synthesis

Screening and critical appraisal were conducted by two reviewers independently. One reviewer extracted data from the results section; this was checked by a second reviewer. GRADE‐CERQual was used to summarize the certainty of the evidence. Data were analysed using thematic synthesis.

Main results

Forty‐six studies from six continents were included. Four themes were generated: the high costs people with multimorbidity experience, the coping strategies they use to manage these costs, and the negative effect of both these on their well‐being. Health insurance and government supports determine the manageability and level of costs experienced.

Discussion

Financial burden has a negative effect on people with multimorbidity. Continuity of care and an awareness of the impact of financial burden of multimorbidity amongst policymakers and health care providers may partially address the issue.

Patient or public contribution

Results were presented to a panel of people with multimorbidity to check whether the language and themes ‘resonated’ with their experiences.

Genetic associations with temporal shifts in obesity and severe obesity during the obesity epidemic in Norway: A longitudinal population-based cohort (the HUNT Study)

BACKGROUND

Obesity has tripled worldwide since 1975 as environments are becoming more obesogenic. Our study investigates how changes in population weight and obesity over time are associated with genetic predisposition in the context of an obesogenic environment over 6 decades and examines the robustness of the findings using sibling design.

METHODS AND FINDINGS

A total of 67,110 individuals aged 13-80 years in the Nord-Trøndelag region of Norway participated with repeated standardized body mass index (BMI) measurements from 1966 to 2019 and were genotyped in a longitudinal population-based health study, the Trøndelag Health Study (the HUNT Study). Genotyping required survival to and participation in the HUNT Study in the 1990s or 2000s. Linear mixed models with observations nested within individuals were used to model the association between a genome-wide polygenic score (GPS) for BMI and BMI, while generalized estimating equations were used for obesity (BMI ≥ 30 kg/m2) and severe obesity (BMI ≥ 35 kg/m2). The increase in the average BMI and prevalence of obesity was steeper among the genetically predisposed. Among 35-year-old men, the prevalence of obesity for the least predisposed tenth increased from 0.9% (95% confidence interval [CI] 0.6% to 1.2%) to 6.5% (95% CI 5.0% to 8.0%), while the most predisposed tenth increased from 14.2% (95% CI 12.6% to 15.7%) to 39.6% (95% CI 36.1% to 43.0%). Equivalently for women of the same age, the prevalence of obesity for the least predisposed tenth increased from 1.1% (95% CI 0.7% to1.5%) to 7.6% (95% CI 6.0% to 9.2%), while the most predisposed tenth increased from 15.4% (95% CI 13.7% to 17.2%) to 42.0% (95% CI 38.7% to 45.4%). Thus, for 35-year-old men and women, respectively, the absolute change in the prevalence of obesity from 1966 to 2019 was 19.8 percentage points (95% CI 16.2 to 23.5, p < 0.0001) and 20.0 percentage points (95% CI 16.4 to 23.7, p < 0.0001) greater for the most predisposed tenth compared with the least predisposed tenth, defined using the GPS for BMI. The corresponding absolute changes in the prevalence of severe obesity for men and women, respectively, were 8.5 percentage points (95% CI 6.3 to 10.7, p < 0.0001) and 12.6 percentage points (95% CI 9.6 to 15.6, p < 0.0001) greater for the most predisposed tenth. The greater increase in BMI in genetically predisposed individuals over time was apparent after adjustment for family-level confounding using a sibling design. Key limitations include a slightly lower survival to date of genetic testing for the older cohorts and that we apply a contemporary genetic score to past time periods. Future research should validate our findings using a polygenic risk score constructed from historical data.

CONCLUSIONS

In the context of increasingly obesogenic changes in our environment over 6 decades, our findings reveal a growing inequality in the risk for obesity and severe obesity across GPS tenths. Our results suggest that while obesity is a partially heritable trait, it is still modifiable by environmental factors. While it may be possible to identify those most susceptible to environmental change, who thus have the most to gain from preventive measures, efforts to reverse the obesogenic environment will benefit the whole population and help resolve the obesity epidemic.

The use of geroprotectors to prevent multimorbidity: Opportunities and challenges

Over 60 % of people over the age of 65 will suffer from multiple diseases concomitantly but the common approach is to treat each disease separately. As age-associated diseases have common underlying mechanisms there is potential to tackle many diseases with the same pharmacological intervention. These are known as geroprotectors and could overcome the problems related to polypharmacy seen with the use of the single disease model. With some geroprotectors now reaching the end stage of preclinical studies and early clinical trials, there is a need to review the evidence and assess how they can be translated practically and effectively into routine practice. Despite promising evidence, there are many gaps and challenges in our understanding that must be addressed to make geroprotective medicine effective in the treatment of age-associated multimorbidity. Here we highlight the key barriers to clinical translation and discuss whether geroprotectors such as metformin, rapamycin and senolytics can tackle all age-associated diseases at the same dose, or whether a more nuanced approach is required. The evidence suggests that geroprotectors' mode of action may differ in different tissues or in response to different inducers of accelerating ageing, suggesting that a blunt 'one drug for many diseases' approach may not work. We make the case for the use of artificial intelligence to better understand multimorbidity, allowing identification of clusters and networks of diseases that are significantly associated beyond chance and the underpinning molecular pathway of ageing causal to each cluster. This will allow us to better understand the development of multimorbidity, select a more homogenous group of patients for intervention, match them with the appropriate geroprotector and identify biomarkers specific to the cluster.

A bibliometric analysis of multimorbidity from 2005 to 2019

Context:

Multimorbidity is frequently seen in primary care. We aimed to identify and analyze publications on multimorbidity, including those that most influenced this field.

Method:

A bibliometric analysis of publications from 2005 to 2019 in the PubMed database containing “multimorbidity” or “multi-morbidity” identified with the tool iCite. We analyzed the number of publications, total citations, the article-level metric Relative Citation Ratio (RCR), type of study, and journals with the most cited articles.

Results:

The number of publications using “multimorbidity” has continuously increased since 2005 (2005–2009: 138; 2010–2014: 823; 2015–2019: 3068). The median number of total citations per article was 3. The median RCR was 1.04. Articles with RCR at or above the 97th percentile (RCR = 7.43) were analyzed in detail (n = 104). In 34 publications of this subgroup (33%), the word multimorbidity was used but was not the subject of study. The remaining top 70 publications included 32 observational studies, 22 reviews, five guideline statements, three analysis papers, two randomized trials, three qualitative studies, two measurement development reports, and one conceptual framework development report. The publications were produced by authors from 32 countries. They were published in 37 different journals, ranging from one to four articles in the same journal.

Conclusions:

We found a continuous increase in the number of publications about multimorbidity since 2005. However, our study suggests that the numbers should be considered only a general trend because multimorbidity was not the main subject in 33% of publications in a subgroup of 104 analyzed in detail.

Multimorbidity of chronic non-communicable diseases in low- and middle-income countries: A scoping review

Background:

Multimorbidity is rising in low- and middle-income countries (LMICs). However, the evidence on its epidemiology from LMICs settings is limited and the available literature has not been synthesized as yet.

Objectives:

To review the available evidence on the epidemiology of multimorbidity in LMICs.

Methods:

PubMed, Scopus, PsycINFO and Grey literature databases were searched. We followed the PRISMA-ScR reporting guideline.

Results:

Of 33, 110 articles retrieved, 76 studies were eligible for the epidemiology of multimorbidity. Of these 76 studies, 66 (86.8%) were individual country studies. Fifty-two (78.8%) of which were confined to only six middle-income countries: Brazil, China, South Africa, India, Mexico and Iran. The majority (n = 68, 89.5%) of the studies were crosssectional in nature. The sample size varied from 103 to 242, 952. The largest proportion (n = 33, 43.4%) of the studies enrolled adults. Marked variations existed in defining and measuring multimorbidity. The prevalence of multimorbidity in LMICs ranged from 3.2% to 90.5%.

Conclusion and Recommendations:

Studies on the epidemiology of multimorbidity in LMICs are limited and the available ones are concentrated in few countries. Despite variations in measurement and definition, studies consistently reported high prevalence of multimorbidity. Further research is urgently required to better understand the epidemiology of multimorbidity and define the best possible interventions to improve outcomes of patients with multimorbidity in LMICs.

Association of Multimorbidity with Cardiovascular Endpoints and Treatment Effectiveness in Patients 75 Years and Older with Atrial Fibrillation

BACKGROUND

The burden imposed by multimorbidity on outcomes and on the effectiveness of atrial fibrillation therapies in elderly adults with atrial fibrillation is unknown.

METHODS

Patients with nonvalvular atrial fibrillation ages ≥75 years in the MarketScan Medicare Supplemental database from 2007-2015. Prevalence of 14 chronic conditions at the time of atrial fibrillation diagnosis were obtained and classified as cardiometabolic or noncardiometabolic. Cox regression estimated the associations of the number and type of conditions with stroke, severe bleeding, and heart failure hospitalizations. Tests for interaction were assessed between atrial fibrillation treatments and multimorbidity.

RESULTS

Among 275,617 patients with atrial fibrillation (mean age 83 years, 51% women), the mean (SD) number of conditions per participant was 3.0 (2.1). Over a mean follow-up of 23 months, 7814 strokes, 13,622 severe bleeds, and 19,252 heart failure events occurred. After adjustment, an increase in the number of cardiometabolic conditions was associated with greater risk of stroke (hazard ratio [HR] 1.07; 95% confidence interval [CI], 1.05-1.10), severe bleeding (HR 1.09; 95% CI, 1.07-1.11), and heart failure (HR 1.19, 95% CI, 1.18-1.20). In contrast, number of noncardiometabolic conditions had weak or null associations with risk of cardiovascular endpoints. Overall, the effectiveness of atrial fibrillation treatment on stroke and heart failure were similar across multimorbidity status, but bleeding risk associated with atrial fibrillation treatments was higher in patients with overall and subgroup multimorbidity.

CONCLUSION

Cardiometabolic multimorbidity was associated with worse outcomes and modified bleeding risk in atrial fibrillation patients. These findings underscore the impact of cardiometabolic conditions on atrial fibrillation outcomes and highlights the need to incorporate multimorbidity management in atrial fibrillation treatment guidelines.

Obesity-related multimorbidity and risk of cardiovascular disease in the middle-aged population in the United States

To investigate the prevalence of obesity-related multimorbidity (co-occurrence of ≥2 obesity-related chronic diseases, ORCDs) and the risk of cardiovascular disease in the presence of multimorbidity in middle-aged adults in the United States. National Health and Nutrition Examination Survey data from 2007 to 2016 were used. Target ORCDs included hypertension (H), diabetes (D), coronary heart disease (C), and stroke (S). Age-standardized prevalence for obesity-related multimorbidity in its combination and permutation was calculated. Risk for cardiovascular disease (C or S) was estimated conditional on demographics, degree of obesity, and presence and duration of pre-existing ORCDs. Analyses were conducted at Washington University in 2019. The analytic sample included 14,243 individuals age 40-79 years, representing a population size of 110,003,550. Age-standardized prevalence for obesity-related multimorbidity was 12.3%. Hypertension was most commonly the first diagnosed ORCD for populations with 2-4 ORCDs, followed by diabetes for populations with 2-3 ORCDs. Compared with no pre-existing hypertension/diabetes/stroke, pre-existing hypertension in combination with diabetes/stroke significantly increased risk of coronary heart disease [H + S (multivariable-adjusted hazard ratio, aHR 27.6, 95% CI 10.9-70.2), D + H + S (aHR 20.3, 95% CI 7.9-52.2)]. Compared with no hypertension/diabetes/coronary heart disease, pre-existing hypertension in combination with diabetes/coronary heart disease significantly increased risk of stroke [C + D + H (aHR 32.6, 95% CI 12.2-87.1), C + H (aHR 25.4, 95% CI 12.1-53.6), D + H (aHR 5.3, 95% CI 2.6-10.8)]. Obesity-related multimorbidity is prevalent and highly associated with cardiovascular disease development. To reduce the detrimental health impact of multimorbidity, intervention strategies should target preventing increasing multimorbidity and detecting/managing diabetes and hypertension prior to the onset of cardiovascular disease.

Sociodemographic and lifestyle predictors of incident hospital admissions with multimorbidity in a general population, 1999-2019: the EPIC-Norfolk cohort

BACKGROUND

The ageing population and prevalence of long-term disorders with multimorbidity are a major health challenge worldwide. The associations between comorbid conditions and mortality risk are well established; however, few prospective community-based studies have reported on prior risk factors for incident hospital admissions with multimorbidity. We aimed to explore the independent associations for a range of demographic, lifestyle and physiological determinants and the likelihood of subsequent hospital incident multimorbidity.

METHODS

We examined incident hospital admissions with multimorbidity in 25 014 men and women aged 40-79 in a British prospective population-based study recruited in 1993-1997 and followed up until 2019. The determinants of incident multimorbidity, defined as Charlson Comorbidity Index ≥3, were investigated using multivariable logistic regression models for the 10-year period 1999-2009 and repeated with independent measurements in a second 10-year period 2009-2019.

RESULTS

Between 1999 and 2009, 18 179 participants (73% of the population) had a hospital admission. Baseline 5-year and 10-year incident multimorbidities were observed in 6% and 12% of participants, respectively. Age per 10-year increase (OR 2.19, 95% CI 2.06 to 2.33) and male sex (OR 1.32, 95% CI 1.19 to 1.47) predicted incident multimorbidity over 10 years. In the subset free of the most serious diseases at baseline, current smoking (OR 1.86, 95% CI 1.60 to 2.15), body mass index >30 kg/m² (OR 1.48, 95% CI 1.30 to 1.70) and physical inactivity (OR 1.16, 95% CI 1.04 to 1.29) were positively associated and plasma vitamin C (a biomarker of plant food intake) per SD increase (OR 0.86, 95% CI 0.81 to 0.91) inversely associated with incident 10-year multimorbidity after multivariable adjustment for age, sex, social class, education, alcohol consumption, systolic blood pressure and cholesterol. Results were similar when re-examined for a further time period in 2009-2019.

CONCLUSION

Age, male sex and potentially modifiable lifestyle behaviours including smoking, body mass index, physical inactivity and low fruit and vegetable intake were associated with increased risk of future incident hospital admissions with multimorbidity.

Helpfulness of Clinical Visit Summary Content From Multi-Specialty Care: A Mixed-Methods Assessment

Objective:

We surveyed patients who visited multiple outpatient specialty practices to understand what summary content was most helpful with the goal of optimizing meaningful outpatient clinical visit summary content.

Materials and Methods:

We constructed a survey instrument to measure delivery, use, and contents of clinical visit summaries. We surveyed patients who visited with at least 2 different outpatient medical specialties to understand preferences.

Results:

Most patients in our sample valued the summary information they received, and retained it as healthcare documentation (84%) and/or quick reference in supporting self-care (70%). Patients most commonly reported that information on results of completed tests (91%) and treatment plan instructions (89%) were very helpful. Additionally, patients expressed the importance of online access to clinical visit summary information.

Discussion:

Most patients used the clinical visit summary as healthcare documentation, and valued online availability of their summary information. Patients most often reported that information on results of recently completed tests and specific instructions on treatment plan were very helpful. Patients who sought further information after their visit most often looked to a provider and/or online.

Conclusions:

Patients valued clinical visit summary accessibility and as a reference tool to summarize care and provide next steps. Optimal clinical visit summaries might collate and integrate assessments and recommendations from multiple specialties into coherent care plans for patients.

Physical Activity and Physical Function in Older Adults Living in a Retirement Community: A Cross-Sectional Analysis Focusing on Self-Rated Health

Perceived health is a widely used proxy for measuring individuals' health status across different populations, including older adults. This measure is commonly reported as a subjective indicator, as a strong predictor of longer-term morbidity and mortality, and as a method to identify high-risk groups with health needs. This study examined differences in physical activity (PA) and physical function (PF) among older adults living in a retirement community located in the Midwest region of the United States as a function of perceived health. Results suggest that older adults perceiving their health as excellent reported significantly higher PA and performed significantly better on PF assessments than those reporting it as good or fair. Programs focusing on increasing PA in older adults living in retirement communities should be considered as potential strategies to enhance the health and health perception of this population.

Development and validation of the Cambridge Multimorbidity Score

BACKGROUND

Health services have failed to respond to the pressures of multimorbidity. Improved measures of multimorbidity are needed for conducting research, planning services and allocating resources.

METHODS

We modelled the association between 37 morbidities and 3 key outcomes (primary care consultations, unplanned hospital admission, death) at 1 and 5 years. We extracted development (n = 300 000) and validation (n = 150 000) samples from the UK Clinical Practice Research Datalink. We constructed a general-outcome multimorbidity score by averaging the standardized weights of the separate outcome scores. We compared performance with the Charlson Comorbidity Index.

RESULTS

Models that included all 37 conditions were acceptable predictors of general practitioner consultations (C-index 0.732, 95% confidence interval [CI] 0.731-0.734), unplanned hospital admission (C-index 0.742, 95% CI 0.737-0.747) and death at 1 year (C-index 0.912, 95% CI 0.905-0.918). Models reduced to the 20 conditions with the greatest combined prevalence/weight showed similar predictive ability (C-indices 0.727, 95% CI 0.725-0.728; 0.738, 95% CI 0.732-0.743; and 0.910, 95% CI 0.904-0.917, respectively). They also predicted 5-year outcomes similarly for consultations and death (C-indices 0.735, 95% CI 0.734-0.736, and 0.889, 95% CI 0.885-0.892, respectively) but performed less well for admissions (C-index 0.708, 95% CI 0.705-0.712). The performance of the general-outcome score was similar to that of the outcome-specific models. These models performed significantly better than those based on the Charlson Comorbidity Index for consultations (C-index 0.691, 95% CI 0.690-0.693) and admissions (C-index 0.703, 95% CI 0.697-0.709) and similarly for mortality (C-index 0.907, 95% CI 0.900-0.914).

INTERPRETATION

The Cambridge Multimorbidity Score is robust and can be either tailored or not tailored to specific health outcomes. It will be valuable to those planning clinical services, policymakers allocating resources and researchers seeking to account for the effect of multimorbidity.

Cancer Survivorship Care Roles for Primary Care Physicians

PURPOSE

Despite a burgeoning population of cancer survivors and pending shortages of oncology services, clear definitions and systematic approaches for engaging primary care in cancer survivorship are lacking. We sought to understand how primary care clinicians perceive their role in delivering care to cancer survivors.

METHODS

We conducted digitally recorded interviews with 38 clinicians in 14 primary care practices that had national reputations as workforce innovators. Interviews took place during intense case study data collection and explored clinicians' perspectives regarding their role in cancer survivorship care. We analyzed verbatim transcripts using an inductive and iterative immersion-crystallization process.

RESULTS

Divergent views exist regarding primary care's role in cancer survivor care with a lack of coherence about the concept of survivorship. A few clinicians believed any follow-up care after acute cancer treatment was oncology's responsibility; however, most felt cancer survivor care was within their purview. Some primary care clinicians considered cancer survivors as a distinct population; others felt cancer survivors were like any other patient with a chronic disease. In further interpretative analysis, we discovered a deeply ingrained philosophy of whole-person care that creates a professional identity dilemma for primary care clinicians when faced with rapidly changing specialized knowledge.

CONCLUSIONS

This study exposes an emerging identity crisis for primary care that goes beyond cancer survivorship care. Facilitated national conversations might help specialists and primary care develop knowledge translation platforms to support the prioritizing, integrating, and personalizing functions of primary care for patients with highly complicated issues requiring specialized knowledge.

Identifying high-need patients with multimorbidity from their illness perceptions and personal resources to manage their health and care: a longitudinal study

Background

A proactive person-centred care process is advocated for people with multimorbidity. To that aim, general practitioners may benefit from support in the identification of high-need patients, i.e. patients who are high or suboptimal users of health services and/or have a poor quality of life. To develop such support, we examined whether knowledge about patients’ illness perceptions and personal resources to manage their health and care is useful to identify high-need patients among multimorbid general practice populations.

Methods

Survey data, collected in 2016 and 2017, of 601 patients with two or more chronic diseases (e.g. COPD, diabetes, Parkinson’s disease) registered with 40 general practices in the Netherlands were analysed by logistic regression analysis to predict frequent contact with the general practice, contact with general practice out-of-office services, unplanned hospitalisations and poor health related quality of life. Patients’ illness perceptions and personal resources (education, health literacy, mastery, mental health status, financial resources, social support) were included as predictors.

Results

The four outcomes were only weakly associated among themselves (Phi .07–.19). Patients’ illness perceptions and personal resources were of limited value to predict potentially suboptimal health service use, but they were important predictors of health related quality of life. Patients with a poor health related quality of life could be identified by their previously reported illness perceptions (attributing many symptoms to their chronic conditions (B = 1.479, P < .001), a high level of concern (B = 0.844, P = .002) and little perceived control over their illness (B = -0.728, P = .006)) combined with an experienced lack of social support (B = -0.527, P = .042) and a poor mental health status (B = -0.966, P = .001) (sensitivity 80.7%; specificity 68.1%).

Conclusions

Multimorbid patients who frequently contact the general practice, use general practice out-of-office services, have unplanned hospitalisations or a poor health related quality of life are largely distinct high-need subgroups. Multimorbid patients at risk of developing a poor quality of life can be identified from specific illness beliefs, a poor mental health status and unmet social needs.

Examining Interprofessional teams structures and processes in the implementation of a primary care intervention (Health TAPESTRY) for older adults using normalization process theory

BACKGROUND

Many countries are engaged in primary care reforms to support older adults who are living longer in the community. Health Teams Advancing Patient Experience: Strengthening Quality [Health TAPESTRY] is a primary care intervention aimed at supporting older adults that involves trained volunteers, interprofessional teams, technology, and system navigation. This paper examines implementation of Health TAPESTRY in relation to interprofessional teamwork including volunteers.

METHODS

This study applied Normalization Process Theory (NPT) and used a descriptive qualitative approach [1] embedded in a mixed-methods, pragmatic randomized controlled trial. It was situated in two primary care practice sites in a large urban setting in Ontario, Canada. Focus groups and interviews were conducted with primary care providers, clinical managers, administrative assistants, volunteers, and a volunteer coordinator. Data was collected at 4 months (June-July 2015) and 12 months (February-March 2016) after intervention start-up. Patients were interviewed at the end of the six-month intervention. Field notes were taken at weekly huddle meetings.

RESULTS

Overall, 84 participants were included in 17 focus groups and 13 interviews; 24 field notes were collected. Themes were organized under four NPT constructs of implementation: 1) Coherence- (making sense/understanding of the program's purpose/value) generating comprehensive assessments of older adults; strengthening health promotion, disease prevention, and self-management; enhancing patient-focused care; strengthening interprofessional care delivery; improving coordination of health and community services. 2) Cognitive Participation- (enrolment/buy-in) tackling new ways of working; attaining role clarity. 3) Collective Action- (enactment/operationalizing) changing team processes; reconfiguring resources. 4) Reflective Monitoring- (appraisal) improving teamwork and collaboration; reconfiguring roles and processes.

CONCLUSIONS

This study contributes key strategies for effective implementation of interventions involving interprofessional primary care teams. Findings indicate that regular communication among all team members, the development of procedures and/or protocols to support team processes, and ongoing review and feedback are critical to implementation of innovations involving primary care teams.

TRIAL REGISTRATION

ClinicalTrials.gov, no. NCT02283723 November 5, 2014. Prospectively registered.

Trends in life expectancy: did the gap between the healthy and the ill widen or close?

BACKGROUND

During the past decades, life expectancy has continued to increase in most high-income countries. Previous research suggests that improvements in life expectancy have primarily been driven by advances at the upper end of the health distribution, while parts of the population have lagged behind. Using data from the entire Swedish population, this study aims to examine the life expectancy development among subgroups of individuals with a history of common diseases relative to that of the general population.

METHODS

The remaining life expectancy at age 65 was estimated for each year in 1998-2017 among individuals with a history of disease, and for the total Swedish population. We defined population subgroups as individuals with a history of myocardial infarction, ischemic or hemorrhagic stroke, hip fracture, or colon, breast, or lung cancer. We further distinguished between different educational levels and Charlson comorbidity index scores.

RESULTS

Life expectancy gains have been larger for men and women with a history of myocardial infarction, ischemic or hemorrhagic stroke, and colon or breast cancer than for the general population. The life expectancy gap between individuals with a history of hip fracture or lung cancer and the general population has, however, been growing. Education and comorbidity have affected mortality levels, but have not altered the rate of increase in life expectancy among individuals with disease history. The female advantage in life expectancy was less pronounced among individuals with disease history than among the general population.

CONCLUSIONS

Life expectancy has increased faster in many subpopulations with a history of disease than in the general population, while still remaining at lower levels. Improvements in life expectancy have been observed regardless of comorbidity or educational level. These findings suggest that the rise in overall life expectancy reflects more than just improved survival among the healthy or the delayed onset of disease.

Era of geriatric medical challenges: Multimorbidity among older patients

The number of older adults is increasing worldwide, including in Asian countries. Various problems associated with medical care for older adults are being highlighted in aging societies. As the number of chronic diseases increases with age, older adults are more likely to have multiple chronic diseases simultaneously (multimorbidity). Multimorbidity results in poor health-related outcomes, leading to increased use and cost of healthcare. Above all, it leads to deterioration in older adults' quality of life. However, it is unclear whether any medical interventions are effective for multimorbidity, which means medical practitioners currently offer medical care "in the dark." It is therefore necessary for researchers and medical professionals involved in geriatric medicine to establish ways to manage multimorbidity among older adults. This means that the development of research in this field is essential. Geriatr Gerontol Int 2019; 19: 699-704.

Physical multimorbidity and suicidal behavior in the general population in the United States

BACKGROUND

As yet, there has been little research on the association between physical multimorbidity (the co-occurrence of two or more physical illnesses) and suicide, and results have been mixed. This study examined if physical multimorbidity is associated with suicidal behavior in the general population in the United States.

METHOD

Data were analyzed from 15,311 adults that were obtained from the Collaborative Psychiatric Epidemiology Surveys (CPES). Information was obtained on nine self-reported physical health conditions and lifetime suicidal behavior (suicidal ideation, plan, and attempts). Logistic regression analysis was used to examine associations.

RESULTS

An increasing number of physical health conditions was associated with higher odds for suicidal behavior. Compared to those with no physical conditions, individuals with ≥ 4 physical illnesses had 2.99, 4.82, and 4.39 times higher odds for reporting suicidal ideation, a suicide plan, and suicide attempts, respectively. An interaction analysis showed that for suicide attempts the association was stronger in younger rather than older adults.

LIMITATIONS

The data were cross-sectional and information on physical conditions and suicidal behavior was self-reported and may have been subject to reporting bias.

CONCLUSIONS

As multimorbidity has increased in recent decades in the United States, alerting medical practitioners to the increased risk of suicidal behavior in adults who have multiple medical conditions as well as screening for suicidality in this group may be important preventive measures to help reduce suicidal behavior in the general population.

Annual Wellness Visits and Influenza Vaccinations among Older Adults in the US

OBJECTIVES

Investigate whether combinations of sociodemographic factors, chronic conditions, and other health indicators pose barriers for older adults to access Annual Wellness Visits (AWVs) and influenza vaccinations.

METHODS

Data on 4999 individuals aged ≥65 years from the 2012 wave of the Health and Retirement Study linked with Medicare claims were analyzed. Conditional Inference Tree (CIT) and Random Forest (CIRF) analyses identified the most important predictors of AWVs and influenza vaccinations. Multivariable logistic regression (MLR) was used to quantify the associations.

RESULTS

Two-year uptake was 22.8% for AWVs and 65.9% for influenza vaccinations. For AWVs, geographical region and wealth emerged as the most important predictors. For influenza vaccinations, number of somatic conditions, race/ethnicity, education, and wealth were the most important predictors.

CONCLUSIONS

The importance of geographic region for AWV utilization suggests that this service was unequally adopted. Non-Hispanic black participants and/or those with functional limitations were less likely to receive influenza vaccination.

Longitudinal Investigation of Older Adults' Ability to Self-Manage Complex Drug Regimens

OBJECTIVES

We sought to investigate older patients' ability to correctly and efficiently dose multidrug regimens over nearly a decade and to explore factors predicting declines in medication self-management.

DESIGN

Longitudinal cohort study funded by the National Institute on Aging.

SETTING

One academic internal medicine clinic and six community health centers.

PARTICIPANTS

Beginning in 2008, 900 English-speaking adults, aged 55 to 74 years, were enrolled in the study, completing a baseline (T1) assessment. To date, 303 participants have completed the same assessment 9 years postbaseline (T4).

MEASUREMENTS

At T1, subjects were given a standardized, seven-drug regimen and asked to demonstrate how they would take medicine over 24 hours. The number of dosing errors made and times per day that a participant would take medicine were recorded. Health literacy was measured via the Newest Vital Sign, and cognitive decline was measured by the Mini-Mental State Examination.

RESULTS

Participants on average made 2.9 dosing errors (SD = 2.5 dosing errors; range = 0-21 dosing errors) of 21 potential errors at T1 and 5.0 errors (SD = 2.1 errors; range = 1-18 errors; P < .001) at T4. In a multivariate model, limited literacy (β = .69; 95% confidence interval [CI] = .18-1.20; P = .01), meaningful cognitive decline (β = 1.72; 95% CI = .70-2.74; P = .01), number of chronic conditions (β = .21; 95% CI = .07-.34; P = .01), and number of baseline dosing errors (β = -.76; 95% CI = -.85 to -.67; P < .001) were significant, independent predictors of changes in dosing errors. Most patients overcomplicated their daily medication schedule; no sociodemographic characteristics were predictive of poor regimen organization in multivariate models. In a multivariate model, there were no significant predictors of changes in regimen consolidation over time, except regimen consolidation at T1.

CONCLUSIONS

Older patients frequently overcomplicated drug regimens and increasingly made more dosing errors over 9 years of follow-up. Patients with limited literacy, cognitive decline, and multimorbidity were at greatest risk for errors. J Am Geriatr Soc 68:569-575, 2020.

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).

Depression and multimorbidity: Considering temporal characteristics of the associations between depression and multiple chronic diseases

OBJECTIVES

Depression frequently co-occurs with multiple chronic diseases in complex, costly, and dangerous patterns of multimorbidity. The field of health psychology may benefit from evaluating the temporal characteristics of depression's associations with common diseases, and from determining whether depression is a central connector in multimorbid disease clusters. The present review addresses these issues by focusing on 4 of the most prevalent diseases: hypertension, ischemic heart disease, arthritis, and diabetes.

METHOD

Study 1 assessed how prior chronic disease diagnoses were associated with current depression in a large, cross-sectional, population-based study. It assessed depression's centrality using network analysis accounting for disease prevalence. Study 2 presents a systematic scoping review evaluating the extent to which depression was prospectively associated with the onset of the 4 prevalent chronic diseases.

RESULTS

In Study 1 depression had the fourth highest betweenness centrality ranking of 26 network nodes and centrally connected many existing diseases and unhealthy behaviors. In Study 2 depression was associated with subsequent incidence of ischemic heart disease and diabetes across multiple meta-analyses. Insufficient information was available about depression's prospective associations with incident hypertension and arthritis.

CONCLUSIONS

Depression is central in patterns of multimorbidity and is associated with incident disease for several of the most common chronic diseases, justifying the focus on screening and treatment of depression in those at risk for developing chronic disease. 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. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Social Vulnerability in Patients with Multimorbidity: A Cross-Sectional Analysis

BACKGROUND

Social aspects play an important role in individual health and should be taken into consideration in the long-term care for people with multimorbidity.

PURPOSES

To describe social vulnerability, to examine its correlation with the number of chronic conditions, and to investigate which chronic conditions were significantly associated with the most socially vulnerable state in patients with multimorbidity.

METHODS

Cross-sectional analysis from the baseline data of the Patient-Centred Innovations for Persons with Multimorbidity (PACEinMM) Study. Participants were patients attending primary healthcare settings in Quebec, Canada. A social vulnerability index was applied to identify social vulnerability level. The index value ranges from 0 to 1 (1 as the most vulnerable). Spearman's rank correlation coefficient was calculated for the correlation between the social vulnerability index and the number of chronic conditions. Logistic regression was applied to investigate which chronic conditions were independently associated with the most socially vulnerable state.

RESULTS

There were 301 participants, mean age 61.0 ± 10.5, 53.2% female. The mean number of chronic health conditions was 5.01 ± 1.82, with the most common being hyperlipidemia (78.1%), hypertension (69.4%), and obesity (54.2%). The social vulnerability index had a median value of 0.13 (range 0.00⁻0.78). There was a positive correlation between the social vulnerability index and the number of chronic conditions (r = 0.24, p < 0.001). Obesity, depression/anxiety, and cardiovascular diseases were significantly associated with the most socially vulnerable patients with multimorbidity.

CONCLUSIONS

There was a significant correlation between social vulnerability and the total number of chronic conditions, with depression/anxiety, obesity, and cardiovascular diseases being the most related to social vulnerability.