The European General Practice Research Network presents a comprehensive definition of multimorbidity in family medicine and long term care, following a systematic review of relevant literature

Agreement between self-reported morbidity and pharmacy claims data for prescribed medications in an older community based population

Background

Studies have indicated variability around prevalence estimates of multimorbidity due to poor consensus regarding its definition and measurement. Medication-based measures of morbidity may be valuable resources in the primary-care setting where access to medical data can be limited. We compare the agreement between patient self-reported and medication-based morbidity; and examine potential patient-level predictors of discordance between these two measures of morbidity in an older (≥ 50 years) community-based population.

Methods

A retrospective cohort study was performed using national pharmacy claims data linked to The Irish LongituDinal study on Ageing (TILDA). Morbidity was measured by patient self-report (TILDA) and two medication-based measures, the Rx-Risk (< 65 years) and Rx-Risk-V (≥65 years), which classify drug claims into chronic disease classes. The kappa statistic measured agreement between self-reported and medication-based morbidity at the individual patient-level. Multivariate logistic regression was used to examine patient-level characteristics associated with discordance between measures of morbidity.

Results

Two thousand nine hundred twenty-five patients were included (< 65 years: N = 1095, 37.44%; and ≥ 65 years: N = 1830 62.56%). Hypertension and high cholesterol were the most prevalent self-reported morbidities in both age cohorts. Agreement was good or very good (κ = 0.61–0.81) for diabetes, osteoporosis and glaucoma; and moderate for high cholesterol, asthma, Parkinson’s and angina (κ = 0.44–0.56). All other conditions had fair or poor agreement. Age, gender, marital status, education, poor-delayed recall, depression and polypharmacy were significantly associated with discordance between morbidity measures.

Conclusions

Most conditions achieved only moderate or fair agreement between self-reported and medication-based morbidity. In order to improve the accuracy in prevalence estimates of multimorbidity, multiple measures of multimorbidity may be necessary. Future research should update the current Rx-Risk algorithms in-line with current treatment guidelines, and re-assess the feasibility of using these indices alone, or in combination with other methods, to yield more accurate estimates of multimorbidity.

Multimorbidity and consultation time: a systematic review

BACKGROUND

Multimorbidity (MM) is one of the major challenges health systems currently face. Management of time length of a medical consultation with a patient with MM is a matter of concern for doctors.

METHODS

A systematic review was performed to describe the impact of MM on the average time of a medical consultation considering the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines. The systematic online searches of the Embase and PubMed databases were undertaken, from January 2000 to August 2018. The studies were independently screened by two reviewers to decide which ones met the inclusion criteria. (Kappa = 0.84 and Kappa = 0.82). Differing opinions were solved by a third person. This systematic review included people with MM criteria as participants (two or more chronic conditions in the same individual). The type of outcome included was explicitly defined - the length of medical appointments with patients with MM. Any strategies aiming to analyse the impact of MM on the average consultation time were considered. The length of time of medical appointment for patients without MM was the comparator criteria. Experimental and observational studies were included.

RESULTS

Of 85 articles identified, only 1 observational study was included, showing a clear trend for patients with MM to have longer consultations than patients without MM criteria (p < 0.001).

CONCLUSIONS

More studies are required to better assess allocation length-time for patients with MM and to measure other characteristics like doctors' workload.

An integrated model of multimorbidity and symptom science

BACKGROUND

Prevalence and complexity of persons with multiple chronic conditions (MCC), also known as multimorbidity, are shifting clinical practice from a single disease focus to one considering MCC and symptoms. Although symptoms are intricately bound to concepts inherent in MCC science, symptoms are largely ignored in multimorbidity research and literature.

PURPOSE

Introduce an Integrated Model of Multimorbidity and Symptom Science.

METHODS

Critical integrative review and synthesis process.

FINDINGS

The model comprises three primary domains: 1. Contributing/ Risk Factors; 2. Symptom/Disease/Treatment Interactions; and 3. Patient Outcomes.

DISCUSSION

The model highlights the multilevel nature of contributing factors and the recursive interactions among multiple etiologies, conditions, symptoms, therapies, and outcomes.

Difficulties that patients with chronic diseases face in the primary care setting in Singapore: a cross-sectional study

INTRODUCTION

Patients with chronic diseases face difficulties when navigating the healthcare system. Using the Healthcare System Hassles Questionnaire (HSHQ) developed by Parchman et al, this study aimed to explore the degree of hassles faced by primary care patients in Singapore and identify the characteristics associated with higher hassles.

METHODS

A cross-sectional study was conducted among patients with chronic disease at Hougang Polyclinic, Singapore, using interviewer-administered HSHQ. Mean HSHQ score was compared with Parchman et al's study. The associations between number of chronic diseases, demographic variables and healthcare hassles were assessed using multivariate linear logistic regression analysis.

RESULTS

217 outpatients aged 21 years and above were enrolled. Our overall mean HSHQ score (4.77 ± 6.18) was significantly lower than that in Parchman et al's study (15.94 ± 14.23, p < 0.001). Participants with five or more chronic diseases scored 3.38 (95% confidence interval [CI] 0.11-6.65, p = 0.043) points higher than those with one chronic disease. With each increasing year of age, mean HSHQ score decreased by 0.17 (95% CI -0.26 to -0.08, p = 0.001) points. Those with polytechnic/diploma/university education and higher scored 2.65 (95% CI 0.19-5.11, p = 0.035) points higher than those with primary education and lower.

CONCLUSION

Patients in our population reported lower hassles than those in Parchman et al's study. Increasing age and lower education level were associated with lower hassles. Further analysis of the types of chronic diseases may yield new information about the association of healthcare hassles with the number and types of chronic diseases.

Multimorbidity and cardiovascular disease: a perspective on low- and middle-income countries

New and changing patterns of multimorbidity (MM), i.e., multiple concurrent acute or chronic diseases in a person, are emerging in low- and middle-income countries (LMICs). The interplay of underlying population-specific factors and lifestyle habits combined with the colliding epidemics of communicable and non-communicable diseases presents new disease combinations, complexities and risks that are not common in high-income countries (HICs). The complexities and risks include those arising from potentially harmful drug-drug and drug-disease interactions (DDIs), the management of which may be considered as MM in the true sense. A major concern in LMICs is the increasing burden of leading cardiovascular diseases, prevalence of associated risk factors and co-occurrence with other morbidities. New models of MM management and integrated care can respond to the needs of specific multimorbid populations, with some LMICs making substantial progress (e.g., integration of tuberculosis and HIV services in South Africa). But there is a dearth of relevant data on the changing patterns and underlying factors and determinants of MM, the associated complexities and risks of DDIs in MM management, and the barriers to integrated care in LMICs. This requires careful attention.

Best Definitions of Multimorbidity to Identify Patients With High Health Care Resource Utilization

Objective

To compare different definitions of multimorbidity to identify patients with higher health care resource utilization.

Patients and Methods

We used a multinational retrospective cohort including 147,806 medical inpatients discharged from 11 hospitals in 3 countries (United States, Switzerland, and Israel) between January 1, 2010, and December 31, 2011. We compared the area under the receiver operating characteristic curve (AUC) of 8 definitions of multimorbidity, based on International Classification of Diseases codes defining health conditions, the Deyo-Charlson Comorbidity Index, the Elixhauser-van Walraven Comorbidity Index, body systems, or Clinical Classification Software categories to predict 30-day hospital readmission and/or prolonged length of stay (longer than or equal to the country-specific upper quartile). We used a lower (yielding sensitivity ≥90%) and an upper (yielding specificity ≥60%) cutoff to create risk categories.

Results

Definitions had poor to fair discriminatory power in the derivation (AUC, 0.61-0.65) and validation cohorts (AUC, 0.64-0.71). The definitions with the highest AUC were number of (1) health conditions with involvement of 2 or more body systems, (2) body systems, (3) Clinical Classification Software categories, and (4) health conditions. At the upper cutoff, sensitivity and specificity were 65% to 79% and 50% to 53%, respectively, in the validation cohort; of the 147,806 patients, 5% to 12% (7474 to 18,008) were classified at low risk, 38% to 55% (54,484 to 81,540) at intermediate risk, and 32% to 50% (47,331 to 72,435) at high risk.

Conclusion

Of the 8 definitions of multimorbidity, 4 had comparable discriminatory power to identify patients with higher health care resource utilization. Of these 4, the number of health conditions may represent the easiest definition to apply in clinical routine. The cutoff chosen, favoring sensitivity or specificity, should be determined depending on the aim of the definition.

Measuring the impact of chronic conditions and associated multimorbidity on health-related quality of life in the general population in Hong Kong SAR, China: A cross-sectional study

Objectives

The aims of this study were to 1) evaluate the impact of eight common chronic conditions and multimorbidity on preference-based health-related quality of life (HRQoL), and 2) estimate the minimally important difference (MID) in the general population of Hong Kong (HK).

Design

Data were analyzed using secondary data analysis based on a cross-sectional, population-based validation study of HK’s general population.

Participants

A representative sample was recruited across eighteen geographical districts in HK, and 1,014 HK Chinese residents aged 18 years and older participated in the survey. The prevalence of chronic conditions among the respondents was 30.3%.

Interventions

The HRQoL was assessed using the locally validated version of EQ-5D-5L. The five-dimension descriptive system, and the utility scores of EQ-5D-5L were used as the dependent variable in the study. Eight common chronic conditions, multimorbidity, and demographic characteristics were defined as predictors in the analysis. Chi-squared test, analysis of variance (ANOVA), logistic regression, and Tobit regression models were used to analyze the data. A simulation-based approach was used to calculate the MID based on instrument-defined single level transitions.

Results

The findings indicated that respondents with physical disabilities were more likely to report problems on all five dimensions of the EQ-5D-5L than those with other chronic conditions. In addition, respondents with multiple chronic conditions were more likely to report health problems and lower utility scores of EQ-5D-5L. The mean of MID estimates among the respondents in HK was 0.093 (standard deviation = 0.001), which is higher than in other Asian countries.

Conclusions

The findings suggest that having more chronic conditions is strongly associated with a lower HRQoL. Healthcare reforms to address foreseeable challenges arising as more patients live with chronic conditions and multimorbidity could improve the HRQoL of HK citizens.

Multiple chronic conditions at a major urban health system: a retrospective cross-sectional analysis of frequencies, costs and comorbidity patterns

OBJECTIVE

To (1) examine the burden of multiple chronic conditions (MCC) in an urban health system, and (2) propose a methodology to identify subpopulations of interest based on diagnosis groups and costs.

DESIGN

Retrospective cross-sectional study.

SETTING

Mount Sinai Health System, set in all five boroughs of New York City, USA.

PARTICIPANTS

192 085 adult (18+) plan members of capitated Medicaid contracts between the Healthfirst managed care organisation and the Mount Sinai Health System in the years 2012 to 2014.

METHODS

We classified adults as having 0, 1, 2, 3, 4 or 5+ chronic conditions from a list of 69 chronic conditions. After summarising the demographics, geography and prevalence of MCC within this population, we then described groups of patients (segments) using a novel methodology: we combinatorially defined 18 768 potential segments of patients by a pair of chronic conditions, a sex and an age group, and then ranked segments by (1) frequency, (2) cost and (3) ratios of observed to expected frequencies of co-occurring chronic conditions. We then compiled pairs of conditions that occur more frequently together than otherwise expected.

RESULTS

61.5% of the study population suffers from two or more chronic conditions. The most frequent dyad was hypertension and hyperlipidaemia (19%) and the most frequent triad was diabetes, hypertension and hyperlipidaemia (10%). Women aged 50 to 65 with hypertension and hyperlipidaemia were the leading cost segment in the study population. Costs and prevalence of MCC increase with number of conditions and age. The disease dyads associated with the largest observed/expected ratios were pulmonary disease and myocardial infarction. Inter-borough range MCC prevalence was 16%.

CONCLUSIONS

In this low-income, urban population, MCC is more prevalent (61%) than nationally (42%), motivating further research and intervention in this population. By identifying potential target populations in an interpretable manner, this segmenting methodology has utility for health services analysts.

Describing the current state of post-rehabilitation health system surveillance in Ontario - an invited review

Context: Spinal cord injury (SCI) presents numerous physiological, psychosocial, and environmental complexities resulting in significant healthcare system resource demands. Objective: To describe the current health system surveillance mechanisms in Ontario, Canada and highlight gaps in health surveillance among adults with SCI across their lifespan. Methods: A review of administrative data sources capturing SCI-specific information took place via internet searching and networking among SCI rehabilitation and health services experts with emphasis on functionality, health service utilization, and quality of life data. Results: The review identified a distinct paucity of data elements specific to the health surveillance needs of individuals with SCI living in the community. The gaps identified are: (1) a lack of data usability; (2) inadequate linkage between available datasets; (3) inadequate/infrequent reporting of outcomes; (4) a lack of relevant content/patient-reported outcomes; and, (5) failure to incorporate additional data sources (e.g. Insurance datasets). Conclusion: Currently, SCI-specific health data is disproportionately weighted towards the first 3-6 months post injury with detailed data regarding pre-hospital care, acute management and rehabilitation, but little existing infrastructure supporting community-based health surveillance. Given this reality, the bolstering of meaningful community health surveillance of this population across the lifespan is needed. Addressing the identified gaps in health surveillance must inform the creation of a comprehensive community health dataset incorporating patient-reported outcome measures and enabling linkage with existing administrative and/or clinical databases. A future harmonized data surveillance strategy would, in turn, positively impact function, health services, resource utilization and health-related quality of life surveillance.

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).

Physical activity, multimorbidity, and life expectancy: a UK Biobank longitudinal study

BACKGROUND

Multimorbidity is an emerging public health priority. Physical activity (PA) is recommended as one of the main lifestyle behaviours, yet the benefits of PA for people with multimorbidity are unclear. We assessed the benefits of PA on mortality and life expectancy in people with and without multimorbidity.

METHODS

Using the UK Biobank dataset, we extracted data on 36 chronic conditions and defined multimorbidity as (a) 2 or more conditions, (b) 2 or more conditions combined with self-reported overall health, and (c) 2 or more top-10 most common comorbidities. Leisure-time PA (LTPA) and total PA (TPA) were measured by questionnaire and categorised as low (< 600 metabolic equivalent (MET)-min/week), moderate (600 to < 3000 MET-min/week), and high (≥ 3000 MET-min/week), while objectively assessed PA was assessed by wrist-worn accelerometer and categorised as low (4 min/day), moderate (10 min/day), and high (22 min/day) walking at brisk pace. Survival models were applied to calculate adjusted hazard ratios (HRs) and predict life expectancy differences.

RESULTS

491,939 individuals (96,622 with 2 or more conditions) had a median follow-up of 7.0 (IQR 6.3-7.6) years. Compared to low LTPA, for participants with multimorbidity, HR for mortality was 0.75 (95% CI 0.70-0.80) and 0.65 (0.56-0.75) in moderate and high LTPA groups, respectively. This finding was consistent when using TPA measures. Using objective PA, HRs were 0.49 (0.29-0.80) and 0.29 (0.13-0.61) in the moderate and high PA groups, respectively. These findings were similar for participants without multimorbidity. In participants with multimorbidity, at the age of 45 years, moderate and high LTPA were associated with an average of 3.12 (95% CI 2.53, 3.71) and 3.55 (2.34, 4.77) additional life years, respectively, compared to low LTPA; in participants without multimorbidity, corresponding figures were 1.95 (1.59, 2.31) and 1.85 (1.19, 2.50). Similar results were found with TPA. For objective PA, moderate and high levels were associated with 3.60 (- 0.60, 7.79) and 5.32 (- 0.47, 11.11) life years gained compared to low PA for those with multimorbidity and 3.88 (1.79, 6.00) and 4.51 (2.15, 6.88) life years gained in those without. Results were consistent when using other definitions of multimorbidity.

CONCLUSIONS

There was an inverse dose-response association between PA and mortality. A moderate exercise is associated with a longer life expectancy, also in individuals with multimorbidity.

Multimorbidity Frameworks Impact Prevalence and Relationships with Patient-Important Outcomes

OBJECTIVES

To explore how different frameworks and categories of chronic conditions impact multimorbidity (defined as two or more chronic conditions) prevalence estimates and associations with patient-important functional outcomes.

DESIGN

Baseline data from a population-based cohort study.

SETTING

National sample of Canadians.

PARTICIPANTS

A total of 51 338 community-living adults, aged 45 to 85 years.

MAIN OUTCOME MEASURES

Chronic conditions from three commonly recognized frameworks were categorized as: (1) diseases, (2) risk factors, or (3) symptoms. Estimates of multimorbidity prevalence were compared among frameworks by age and sex. Separate weighted logistic regression models were used to explore the impact of the different frameworks and categories of chronic conditions on odds ratios (ORs) for multimorbidity for four patient-important functional outcomes: disability, social participation restriction, and self-rated physical and mental health.

RESULTS

One framework included diseases and risk factors, and two frameworks included diseases, risk factors, and symptoms. The prevalence of multimorbidity differed among the frameworks, ranging from 33.5% to 60.6% having two or more chronic conditions. Including risk factors in frameworks increased prevalence estimates, while including symptoms increased prevalence estimates and associations with most patient-important outcomes. The two frameworks that included symptoms had the largest ORs for associations with disability, social participation restriction, and self-rated physical health but not self-rated mental health. Similar results were found when we compared ORs for patient-important outcome for multimorbidity based on three subframeworks: one including diseases only, one including diseases and risk factors, and one including diseases, risk factors, and symptoms.

CONCLUSIONS

Including risk factors appeared to increase only the prevalence of multimorbidity without significantly altering relationships to outcomes. The inclusion of symptoms increased prevalence and associations with patient-important outcomes. These findings underscore the importance of considering not only the number, but also the category, of conditions included in multimorbidity frameworks, as simply counting the number of diagnoses may reduce sensitivity to outcomes that are important to individuals. J Am Geriatr Soc 67:1632-1640, 2019.

The social networks of New Zealand patients with multimorbidity and the work of those nominated as their 'significant supporters': An exploratory study

Social networks are informal relationships often with social ties and voluntary or mandatory obligations that can positively support a patient with multimorbidity. This exploratory study sought insights into the social networks of New Zealand people with multimorbidity and also the work of those nominated as providing significant support. Ten participants were recruited from general practice as part of an education programme in which health professional students discussed living with multimorbidity and completed a social network template together with patients. Each patient nominated an individual from their social network whom they considered provided significant support. A researcher interviewed each supporter about their experience of providing support, and their view of the patient's social network. Significant supporters included three classified as 'lay' supporters (sister, wife and daughter) and seven classified as 'professional' supporters (exercise physiologist, general practitioners, nurse, medical specialists). The activities described by supporters was classified according to Vassilev et al.'s expansion of Corbin and Strauss's 1985 classification of work in chronic illness, including the categories of "illness," "everyday" and "emotional" work. Irrespective of whether supporters were lay or professional, they gave examples of each category. While this is expected of lay supporters, it is not expected of professional supporters who are typically viewed as undertaking illness work. Lay supporters described a complex array of activities sometimes impacting on their own personal well-being, making them more akin to meeting the formal definition of being a carer, while professional supports gave objective yet professionally invested descriptions. The work of lay and professional supporters is complementary in the provision of support for those with multimorbidity. Consideration should be given to the role of lay supporters and to their own needs if they are to be able to sustain their support work with patients.

Management of comorbid mental and somatic disorders in stepped care approaches in primary care: a systematic review

BACKGROUND

Stepped care models comprise a graded treatment intensity and a systematic monitoring. For an effective implementation, stepped care models have to account for the high rates of mental and somatic comorbidity in primary care.

OBJECTIVES

The aim of the systematic review was to take stock of whether present stepped care models take comorbidities into consideration. A further aim was to give an overview on treatment components and involved health care professionals.

METHODS

A systematic literature search was performed using the databases PubMed, PsycINFO, Cochrane Library and Web of Science. Selection criteria were a randomized controlled trial of a primary-care-based stepped care intervention, adult samples, publication between 2000 and 2017 and English or German language.

RESULTS

Of 1009 search results, 39 studies were eligible. One-third of the trials were conceived for depressive disorders only, one-third for depression and further somatic and/or mental comorbidity and one-third for conditions other than depression. In 39% of the studies comorbidities were explicitly integrated in treatment, mainly via transdiagnostic self-management support, interprofessional collaboration and digital approaches for treatment, monitoring and communication. Most care teams were composed of a primary care physician, a care manager and a psychiatrist and/or psychologist. Due to the heterogeneity of the addressed disorders, no meta-analysis was performed.

CONCLUSIONS

Several stepped care models in primary care already account for comorbidities, with depression being the predominant target disorder. To determine their efficacy, the identified strategies to account for comorbidities should be investigated within stepped care models for a broader range of disorders.

Sex-specific intergenerational trends in morbidity burden and multimorbidity status in Hong Kong community: an age-period-cohort analysis of repeated population surveys

OBJECTIVES

Prevalence of multimorbidity has been increasing worldwide. While population ageing undoubtedly contributes, secular trends have seldom been decomposed into age, period and cohort effects to investigate intergenerational differences. This study examines the birth cohort effect on morbidity burden and multimorbidity in Hong Kong community.

DESIGN

Sex-specific age-period-cohort analysis with repeated cross-sectional surveys.

SETTING

A territory-wide population survey database.

PARTICIPANTS

69 636 adults aged 35 or above who participated in the surveys in 1999, 2001, 2005 or 2008.

MAIN OUTCOME MEASURES

Morbidity burden was operationalised as number of chronic conditions from a list of 14, while multimorbidity was defined as a dichotomous status of whether participants had two or more conditions.

RESULTS

For both sexes, there was an upward inflection (positive change) of risk of increased morbidity burden starting from cohort 1955-1959. For men born after 1945-1954, there was a trend of lower risk (relative risk=0.63, 95% CI 0.50 to 0.80 for 1950-1954 vs 1935-1939) which continued through subsequent cohorts but with no further declines. In women, there had been a gradual increase of risk, although only significant for cohort 1970-1974 (relative risk=1.90, 95% CI 1.08 to 1.34 vs 1935-1939). Similar results were found for dichotomous multimorbidity status.

CONCLUSIONS

The trend of lower risk starting from men born in 1945-1954 may be due to a persistent decline in smoking rates since the 1980s. On the other hand, the childhood obesity epidemic starting from the late 1950s coincided with the observed upward inflection of risk for both sexes, that is, notably more drastic increase of risk in women and the levelling-off of the decline of risk in men. These findings highlight that the cohort effects on morbidity burden and multimorbidity may be sex-specific and contextual. By examining such effects in different world populations, localised sex-specific and generation-specific risk factors can be identified to inform policy-making.

Primary care and multimorbidity in six Latin American and Caribbean countries

Objectives

To describe patterns of multimorbidity in six diverse Latin American and Caribbean countries, examine its effects on primary care experiences, and assess its influence on reported overall health care assessments.

Methods

Cross-sectional data are from the Inter-American Development Bank's international primary care survey, conducted in 2013/2014, and represent the adult populations of Brazil, Colombia, El Salvador, Jamaica, Mexico and Panama. Robust Poisson regression models were used to estimate the extent to which those with multimorbidity receive adequate and appropriate primary care, have confidence in managing their health condition, and are able to afford needed medical care.

Results

The prevalence of multimorbidity ranged from 17.5% in Colombia to 37.3% in Jamaica. Most of the examined conditions occur along with others, with diabetes and heart disease being the two problems most associated with other conditions. The proportions of adults with high out-of-pocket payments, problems paying their medical bills, seeing multiple doctors, and being in only fair/poor health were higher among those with greater levels of multimorbidity and poorer primary care experiences. Multimorbidity and difficulties with primary care were positively associated with trouble paying for medical care and managing one's conditions. Nonetheless, adults with multimorbidity were more likely to have received lifestyle advice and to be up to date with preventive exams.

Conclusions

Multimorbidity is reported frequently. Providing adequate care for the growing number of such patients is a major challenge facing most health systems, which will require considerable strengthening of primary care along with financial protection for those most in need.

Effectiveness and cost-effectiveness of integrated care models for elderly, complex patients: A narrative review. Don’t we need a value-based approach?

Introduction

The management of patients with complex health and social needs is one of the main challenges for healthcare systems. Integrated care seems to respond to this issue, with collaborative working and integration efforts of the care system components professionals and service providers aimed at improving efficiency, appropriateness and person centeredness of care. We conducted a narrative review to analyse the available evidences published on effectiveness and cost-effectiveness of integrated care models targeted on the management of such elderly patients.

Methods

MEDLINE, Scopus and EBSCO were searched. We reported this narrative review according to the PRISMA Checklist. For studies to be included, they had to: (i) refer to integrated care models through implemented experimental or demonstration projects; (ii) focus on frail elderly ≥65 years old, with complex health and social needs, not disease-specific; (iii) evaluate effectiveness and/or cost and/or cost-effectiveness; (iv) report quantitative data (e.g. health outcomes, utilization outcomes, cost and cost-effectiveness).

Results

Thirty articles were included, identifying 13 integrated care models. Common features were identified in case management, geriatric assessment and multidisciplinary team. Favourable impacts on healthcare facilities utilization rates, though with mixed results on costs, were found. The development of community-based and cost-effective integrated systems of care for the elderly is possible, thanks to the cooperation across care professionals and providers, to achieving a relevant impact on healthcare and efficient resource management. The elements of success or failure are not always unique and identifiable, but the potential clearly exists for these models to be successful and generalized on a large scale.

Discussion

We found out a favourable impact of integrated care models/methods on health outcomes, care utilization and costs. The selected interventions are likely to be implemented at community level, focused on the patient management in terms of continuity of care. Thus, we propose a value-based framework for the evaluation of these services.

Prevalence and patterns of multimorbidity in Amazon Region of Brazil and associated determinants: a cross-sectional study

OBJECTIVES

To estimate the prevalence of multimorbidity and to identify factors associated with it in the adult population from the metropolitan region of Manaus.

DESIGN

Cross-sectional population-based study.

SETTING

Interviews conducted between May and August of 2015 in eight cities that compose the metropolitan region of Manaus, Amazonas, Brazil.

PARTICIPANTS

4001 adults aged ≥18 years.

PRIMARY OUTCOME MEASURES

Multimorbidity, measured by the occurrence of ≥2 and ≥3 chronic diseases, was the primary outcome. The associated factors were investigated by calculating the prevalence ratio (PR) obtained by Poisson regression, with robust adjustment of the variance in a hierarchical model. A factor analysis was conducted to investigate multimorbidity clusters.

RESULTS

Half of the interviewees were women. The presence of a chronic disease was reported by 57.2% (95% CI 56.6% to 59.7%) of the interviewees, and the mean morbidity was 1.2 (1.1-1.2); 29.0% (95% CI 27.6% to 30.5%) reported ≥2 morbidities and 15.2% (95% CI 14.1% to 16.4%) reported ≥3 chronic conditions. Back pain was reported by one-third of the interviewees. Multimorbidity was highest in women, PR=1.66 (95% CI 1.50 to 1.83); the elderly, PR=5.68 (95% CI 4.51 to 7.15) and individuals with worse health perception, PR=3.70 (95% CI 2.73 to 5.00). Associated factors also included undergoing medical consultations, hospitalisation in the last year, suffering from dengue in the last year and seeking the same healthcare service. Factor analysis revealed a pattern of multimorbidity in women. The factor loading the most strength of association in women was heart disease. In men, an association was identified in two groups, and lung disease was the disease with the highest factorial loading.

CONCLUSION

Multimorbidity was frequent in the metropolitan region of Manaus. It occurred most often in women, in the elderly and in those with worse health perception.

Multimorbidity: The Brazilian Longitudinal Study of Aging (ELSI-Brazil)

OBJECTIVE

To evaluate the occurrence and factors associated with multimorbidity among Brazilians aged 50 years and over.

METHODS

This is a cross-sectional study in a nation-based cohort of the non-institutionalized population in Brazil. Data were collected between 2015 and 2016. Multimorbidity was assessed from a list of 19 morbidities, which were categorized into ≥ 2 and ≥ 3 diseases. The analysis included the calculation of frequencies and the most frequent 10 pairs and triplets of combinations of diseases. The crude and adjusted analyses evaluated the demographic, socioeconomic, behavioral, and contextual variables (area of residence, geopolitical region, and coverage of the Family Health Strategy) using Poisson regression.

RESULTS

From the total of 9,412 individuals, 67.8% (95%CI 65.6–69.9) and 47.1% (95%CI 44.8–49.4) showed ≥ 2 and ≥ 3 diseases, respectively. In the adjusted analysis, women, older persons, and those who did not consume alcohol had increased multimorbidity. There were no associations with race, area of residence, geopolitical region, and coverage of the Family Health Strategy. The 10 pairs (frequencies observed between 11.6% and 23.2%) and the 10 triplets (frequencies observed between 4.9% and 9.5%) of the most frequent diseases mostly included back problems (15 times) and systemic arterial hypertension (11 times). All combinations were statistically higher than expected by chance.

CONCLUSIONS

The occurrence of multimorbidity was high even among younger individuals (50 to 59 years). Approximately two in three (≥ 2 diseases) and one in two (≥ 3 diseases) individuals aged 50 years and over presented multimorbidity, which represents 26 and 18 million persons in Brazil, respectively. We observed high frequencies of combinations of morbidities.

Physiological markers and multimorbidity: A systematic review

Background:

Multimorbidity is the co-occurrence of two or more diseases in the same individual. One method to identify this condition at an early stage is the use of specific markers for various combinations of morbidities. Nonetheless, evidence related to physiological markers in multimorbidity is limited.

Objective:

The aim was to perform a systematic review to identify physiological markers associated with multimorbidity.

Design:

Articles available on PubMed, Register of Controlled Trials, Academic Search Premier, CINAHL, Scopus, SocINDEX, Web of Science, LILACS, and SciELO, from their inception to May 2018, were systematically searched and reviewed. The project was registered in PROSPERO under the number CRD42017055522.

Results:

The systematic search identified 922 papers. After evaluation, 18 articles were included in the full review reporting at least one physiological marker in coexisting diseases or which are strongly associated with the presence of multimorbidity in the future. Only five of these studies examined multimorbidity in general, identifying five physiological markers associated with multimorbidity, namely, dehydroepiandrosterone sulfate (DHEAS), interleukin 6 (IL-6), C-reactive protein (CRP), lipoprotein (Lp), and cystatin C (Cyst-C).

Conclusions:

There is a paucity of studies related to physiological markers in multimorbidity. DHEAS, IL-6, CRP, Lp, and Cyst-C could be the initial focus for further investigation of physiological markers related to multimorbidity.

The development of multimorbidity during 16 years after diagnosis of type 2 diabetes

Objective:

The aims of this study were to (1) quantify the development and composition of multimorbidity (MM) during 16 years following the diagnosis of type 2 diabetes and (2) evaluate whether the effectiveness of structured personal diabetes care differed between patients with and without MM.

Research design and methods:

One thousand three hundred eighty-one patients with newly diagnosed type 2 diabetes were randomized to receive either structured personal diabetes care or routine diabetes care. Patients were followed up for 19 years in Danish nationwide registries for the occurrence of outcomes. We analyzed the prevalence and degree of MM based on 10 well-defined disease groups. The effect of structured personal care in diabetes patients with and without MM was analyzed with Cox regression models.

Results:

The proportion of patients with MM increased from 31.6% at diabetes diagnosis to 80.4% after 16 years. The proportion of cardiovascular and gastrointestinal diseases in surviving patients decreased, while, for example, musculoskeletal, eye, and neurological diseases increased. The effect of the intervention was not different between type 2 diabetes patients with or without coexisting chronic disease.

Conclusions:

In general, the proportion of patients with MM increased after diabetes diagnosis, but the composition of chronic disease changed during the 16 years. We found cardiovascular and musculoskeletal disease to be the most prevalent disease groups during all 16 years of follow-up. The post hoc analysis of the intervention showed that its effectiveness was not different among patients who developed MM compared to those who continued to have diabetes alone.

Key factors to consider when measuring multimorbidity: Results from an expert panel and online survey

Background:

There are multiple multimorbidity measures but little consensus on which measures are most appropriate for different circumstances.

Objective:

To share insights gained from discussions with experts in the fields of ageing research and multimorbidity on key factors to consider when measuring multimorbidity.

Design:

Descriptive study of expert opinions on multimorbidity measures, informed by literature to identify available measures followed by a face-to-face meeting and an online survey.

Results:

The expert group included clinicians, researchers and policymakers in Canada with expertise in the fields of multimorbidity and ageing. Of the 30 experts invited, 15 (50%) attended the in-person meeting and 14 (47%) responded to the subsequent online survey. Experts agreed that there is no single multimorbidity measure that is suitable for all research studies. They cited a number of factors that need to be considered in selecting a measure for use in a research study including: (1) fit with the study purpose; (2) the conditions included in multimorbidity measures; (3) the role of episodic conditions or diseases; and (4) the role of social factors and other concepts missing in existing approaches.

Conclusions:

The suitability of existing multimorbidity measures for use in a specific research study depends on factors such as the purpose of the study, outcomes examined and preferences of the involved stakeholders. The results of this study suggest that there are areas that require further building out in both the conceptualization and measurement of multimorbidity for the benefit of future clinical, research and policy decisions.

General Practitioners Records Are Epidemiological Predictors of Comorbidities: An Analytical Cross-Sectional 10-Year Retrospective Study

Background. Comorbidity represents the co-occurrence of pathological conditions in the same individual, and presents with very complex patterns. In most cases, reference data for the study of various types of comorbidities linked to complex diseases are those of hospitalized patients. Such patients may likely require cure due to acute conditions. We consider the emerging role of EHR (Electronic Healthcare Records), and study comorbidity patterns in a general population, focusing on diabetic and non-diabetic patients. Methods. We propose a cross-sectional 10-year retrospective study of 14,958 patients and 1,728,736 prescriptions obtained from family doctors, and thus refer to these data as General Practitioner Records (GPR). We then choose networks as the tools to analyze the diabetes comorbidity patterns, distinguished by both prescription type and main patient characteristics (age, gender). Results. As expected, comorbidity increases with patients’ age, and the network representations allow the assessment of associations between morbidity groups. The specific morbidities present in the diabetic population justify the higher comorbidity patterns observed in the target group compared to the non-diabetic population. Conclusions. GPR are usually combined with other data types in EHR studies, but we have shown that prescription data have value as standalone predictive tools, useful to anticipate trends observed at epidemiological level on large populations. This study is thus relevant to policy makers seeking inference tools for an efficient use of massive administrative database resources, and suggests a strategy for detecting comorbidities and investigating their evolution.

Multimorbidity is associated with uptake of influenza vaccination

OBJECTIVE

Patients with chronic conditions have higher rates of severe influenza-related illness and mortality. However, influenza vaccination coverage in high-risk populations continues to be suboptimal. We describe the association between cumulative disease morbidity, measured by a previously validated multimorbidity index, and influenza vaccination among community-dwelling adults.

METHODS

We obtained interview and medical record data for participants  ≥18 years who sought outpatient care for influenza-like illness between 2011 and 2016 as part of an outpatient-based study of influenza vaccine effectiveness. We defined cumulative disease morbidity by using medical diagnosis codes to calculate a multimorbidity-weighted index (MWI) for each participant. MWI and influenza vaccination status was evaluated by logistic regression. Akaike information criterion was calculated for all models.

RESULTS

Overall, 1458 (48%) of participants out of a total of 3033 received influenza vaccination. The median MWI was 0.9 (IQR 0.00-3.5) and was higher among vaccinated participants (median 1.6 versus 0.0; p < 0.001). We found a positive linear association between MWI and vaccination, and vaccination percentages were compared between categories of MWI. Compared to patients with no multimorbidity (MWI = 0), odds of vaccination were 17% higher in the second category (MWI 0.01-1.50; [OR: 1.17, 95% CI: 0.92-1.50]), 58% higher in the third category (MWI 1.51-3.00; [OR: 1.58, 95% CI: 1.26-1.99]), 130% higher in the fourth category (MWI 3.01-6.00; [OR: 2.30, 95% CI: 1.78-2.98]) and 214% higher in the fifth category (MWI 6.01-45.00;[OR: 3.14, 95% CI: 2.41-4.10]). Participants defined as high-risk had 86% greater odds of being vaccinated than non-high-risk individuals (OR: 1.86, 95% CI: 1.56-2.21). The AIC was lowest for MWI compared with high-risk conditions.

CONCLUSIONS

Our results suggest a dose response relationship between level of multimorbidity and likelihood of influenza vaccination. Compared with high-risk condition designations, MWI provided improved precision and a better model fit for the measurement of chronic disease and influenza vaccination.

[Multimorbidity management and the physician's daily clinical dilemma]

About 20-25% of all persons and about 90% of all patients who are acutely hospitalized in internal medicine departments have multiple acute or chronic diseases. They are multimorbid. The encounter with multimorbid patients has become the most common situation in the health care system. Theoretically, multimorbidity results in an innumerable potential disease constellations. In addition, the likelihood of interactions between diseases (disease-disease interactions, DDI) and the complexity increases overproportionately with each additional disease. However, multimorbidity often occurs in typical diadic, triadic, or higher characteristic combinations, in "disease clusters", e. g., vascular risk factors, heart and lung diseases, Frailty and dementia, psychiatric and somatic disorders. Such combinations lead to a worsening of the overall prognosis. In addition, DDIs are often difficult to treat or are life-threatening. Examples of DDIs include the following: anticoagulation and simultaneous severe bleeding, pain treatment and hypertension or renal insufficiency, depression and reduced medication adherence, chronic obstructive pulmonary disease and depression, Frailty and neurodepressant drugs and frequent falls, and combined psychiatric and somatic disorders. Such DDIs are common. Nevertheless, there are few studies and clinical guidelines that address these issues. The care of multimorbid patients is, therefore, heavily reliant upon guidelines developed mostly for single diseases. However, multimorbidity and serious DDIs are usually not addressed in these. Clinical guidelines can thus inadvertently jeopardize the safety of persons suffering from multiple diseases. In addition, stressful dilemmas arise for physicians encountering DDIs because of difficult treatment decisions.

Multimorbidity and mortality: A 15-year longitudinal registry-based nationwide Danish population study

BACKGROUND

Knowledge about prevalent and deadly combinations of multimorbidity is needed.

OBJECTIVE

To determine the nationwide prevalence of multimorbidity and estimate mortality for the most prevalent combinations of one to five diagnosis groups. Furthermore, to assess the excess mortality of the combination of two groups compared to the product of mortality associated with the single groups.

DESIGN

A prospective cohort study using Danish registries and including 3.986.209 people aged ≥18 years on 1 January, 2000. Multimorbidity was defined as having diagnoses from at least 2 of 10 diagnosis groups: lung, musculoskeletal, endocrine, mental, cancer, neurological, gastrointestinal, cardiovascular, kidney, and sensory organs. Logistic regression (odds ratios, ORs) and ratio of ORs (ROR) were used to study mortality and excess mortality.

RESULTS

Prevalence of multimorbidity was 7.1% in the Danish population. The most prevalent combination was the musculoskeletal-cardiovascular (0.4%), which had double the mortality (OR, 2.03) compared to persons not belonging to any of the diagnosis groups but showed no excess mortality (ROR, 0.97). The neurological-cancer combination had the highest mortality (OR, 6.35), was less prevalent (0.07%), and had no excess mortality (ROR, 0.94). Cardiovascular-lung was moderately prevalent (0.2%), had high mortality (OR, 5.75), and had excess mortality (ROR, 1.18). Endocrine-kidney had high excess mortality (ROR, 1.81) and cancer-mental had low excess mortality (ROR, 0.66). Mortality increased with the number of groups.

CONCLUSIONS

All combinations had increased mortality risk with some of them having up to a six-fold increased risk. Mortality increased with the number of diagnosis groups. Most combinations did not increase mortality above that expected, that is, were additive rather than synergistic.

Multimorbidity and quality of life at mid-life: A systematic review of general population studies

There is substantial multimorbidity at mid-life but little is known about the strength of evidence on multimorbidity and health-related quality of life (HrQoL) at mid-life. This review addresses this gap, focusing on studies of the general population. PubMed, Web of Science, Embase and APA PsycNET databases were screened on 6 March 2017 for original research on multimorbidity and HrQoL in adults aged 40-65 years from the general population. Studies focused on index conditions, using single-item HrQoL measures, unlikely to represent the general population (e.g. primary care), and papers that were not in the English language were excluded. A narrative synthesis was presented due to heterogeneity in the measurement of multimorbidity. Of the 2557 articles, 83 underwent full text screening and 8 were included in the review. Included studies were of moderate to high quality and no exclusions were made on the basis of quality or bias. Multimorbidity was associated with poorer HrQoL at mid-life. Two cross-sectional studies found that adults with multimorbidity at early mid-life reported poorer HrQoL than adults with multimorbidity at late mid-life, while another found the reverse. Two distinct disease clusters were identified: mental health conditions and cardiovascular disease (CVD). Those in the mental health cluster reported poorer HrQoL than those in the CVD cluster, women more so than men. Limitations of the selected studies include lack of longitudinal evidence, use of self-reported conditions and no assessment of disease severity. Multimorbidity is associated with poor HrQoL at mid-life at the population level, with some evidence of differences in association with age and disease cluster and sparse evidence on sex differences. Longitudinal research using a weighted disease severity index and multimorbidity trajectories is needed to strengthen the evidence base.

Impact of multimorbidity on healthcare professional task shifting potential in patients with type 2 diabetes in primary care: a French cross-sectional study

OBJECTIVES

To estimate the transferability of processes of care from general practitioners (GPs) to allied healthcare professionals and the determinants of such transferability.

DESIGN

French national cross-sectional multicentre study SETTING: 128 family practices providing supervised training for residents in general practice.

PARTICIPANTS

All patients consulting with their GP over a total number of 20 days (ie, 1 day a week from December 2011 to April 2012). Encounters where type 2 diabetes was one of the managed health problems were selected for analysis.

PRIMARY AND SECONDARY OUTCOME MEASURES

Processes that were associated with specific health problems were collected by 54 residents. Potential process transferability was the main outcome assessed, as well as the professionals involved in the collaboration and the eventual conditions associated with transfer.

RESULTS

From 8572 processes of care that concerned 1088 encounters of patients with diabetes, 21.9% (95% CI 21.1% to 22.8%) were considered eligible for transfer from GPs to allied healthcare professionals (78.1% to nurses, 36.7% to pharmacists). Processes were transferable with condition(s) for 70.6% (ie, a protocol, shared record or supervision). The most transferable processes concerned health maintenance (32.1%) and cardiovascular risk factors (hypertension (28.7%), dyslipidaemia (25.3%) and diabetes (24.3%)). Multivariate analysis showed that educational processes or a long-term condition status were associated with increased transferability (OR 3.26 and 1.47, respectively), whereas patients with higher intellectual occupations or those with two or more associated health problems were associated with lower transferability (OR 0.33 and 0.81, respectively).

CONCLUSIONS

A significant part of GP activity relating to patients with multimorbidity including type 2 diabetes could be transferred to allied healthcare professionals, mainly on prevention and global education to cardiovascular risk factors. The organisational and finance conditions of team work as views of patients and healthcare professionals must be explored before implementation in primary care.

Multimorbid outpatients: A high frequency of FP appointments and/or family difficulties, should alert FPs to the possibility of death or acute hospitalization occurring within six months; A primary care feasibility study

Background

The European General Practitioners Research Network (EGPRN) designed and validated a comprehensive definition of multimorbidity using a systematic literature review and qualitative research throughout Europe. This definition was tested as a model to assess death or acute hospitalization in multimorbid outpatients.

Objective

To assess which criteria in the EGPRN concept of multimorbidity could detect outpatients at risk of death or acute hospitalization in a primary care cohort at a 6-month follow-up and to assess whether a large scale cohort with FPs would be feasible.

Method

Family Physicians included a random sample of multimorbid patients who attended appointments in their offices from July to December 2014. Inclusion criteria were those of the EGPRN definition of Multimorbidity. Exclusion criteria were patients under legal protection and those unable to complete the 2-year follow-up. Statistical analysis was undertaken with uni- and multivariate analysis at a 6-month follow-up using a combination of approaches including both automatic classification and expert decision making. A Multiple Correspondence Analysis (MCA) completed the process with a projection of illustrative variables. A logistic regression was finally performed in order to identify and quantify risk factors for decompensation.

Results

19 FPs participated in the study. 96 patients were analyzed. 3 different clusters were identified. MCA showed the central function of psychosocial factors and peaceful versus conflictual relationships with relatives in all clusters. While taking into account the limit of a small cohort, age, frequency of family physician visits and extent of family difficulties were the factors which predicted death or acute hospitalization.

Conclusion

A large scale cohort seems feasible in primary care. A sense of alarm should be triggered to prevent death or acute hospitalization in multimorbid older outpatients who have frequent family physician visits and who experience family difficulties.

The contribution of musculoskeletal disorders in multimorbidity: Implications for practice and policy

People frequently live for many years with multiple chronic conditions (multimorbidity) that impair health outcomes and are expensive to manage. Multimorbidity has been shown to reduce quality of life and increase mortality. People with multimorbidity also rely more heavily on health and care services and have poorer work outcomes. Musculoskeletal disorders (MSDs) are ubiquitous in multimorbidity because of their high prevalence, shared risk factors, and shared pathogenic processes amongst other long-term conditions. Additionally, these conditions significantly contribute to the total impact of multimorbidity, having been shown to reduce quality of life, increase work disability, and increase treatment burden and healthcare costs. For people living with multimorbidity, MSDs could impair the ability to cope and maintain health and independence, leading to precipitous physical and social decline. Recognition, by health professionals, policymakers, non-profit organisations, and research funders, of the impact of musculoskeletal health in multimorbidity is essential when planning support for people living with multimorbidity.

Multimorbidity and health-related quality of life among the community-dwelling elderly: A longitudinal study

OBJECTIVES

Multimorbidity is a growing public health problem. The objective of this study was to investigate the impact of multimorbidity on health-related quality of life (HRQoL) of the elderly.

METHODS

A 24-month longitudinal study was conducted on the community-dwelling elderly. There were 411 elderly persons with complete follow-up. Information on thirteen chronic conditions was collected at baseline. Via a multi-dimensional scale, HRQoL was measured at baseline, 18 and 24 months post-baseline, respectively. Exploratory factor analyses were performed to identify multimorbidity patterns. The linear mixed effects models were conducted to analyze the associations between all dimensions of HRQoL and multimorbidity including distinct multimorbidity patterns.

RESULTS

Multimorbidity was found to be negatively associated with HRQoL except memory function. We identified three multimorbidity patterns, which were mainly labelled as degenerative disorders, digestive/respiratory disorders, cardiovascular/metabolic disorders, respectively. And three multimorbidity patterns were associated with lower HRQoL including general health, body function, self-care ability and social adaptability. Besides, the elderly with the multimorbidity pattern mainly labelled as digestive/respiratory disorders or cardiovascular/metabolic disorders had a decline on emotion than those without multimorbidity. According to the analysis of the longitudinal data of the sample, general health, self-care ability, emotion and social adaptability of the participants decreased in different degrees every month.

CONCLUSIONS

Multimorbidity was associated with lower HRQoL of the community-dwelling elderly. Distinct multimorbidity patterns had various impacts on different dimensions of HRQoL. Further studies should be carried out to investigate effective measures to improve HRQoL of the elderly with multimorbidity.

Effect of socio-demographic factors on the association between multimorbidity and healthcare costs: a population-based, retrospective cohort study

OBJECTIVES

To estimate the attributable costs of multimorbidity and assess whether the association between the level of multimorbidity and health system costs varies by socio-demographic factors in young (<65 years) and older (≥65 years) adults living in Ontario, Canada.

DESIGN

A population-based, retrospective cohort study SETTING: The province of Ontario, Canada PARTICIPANTS: 6 639 089 Ontarians who were diagnosed with at least one of 16 selected medical conditions on 1 April 2009.

MAIN OUTCOME MEASURES

From the perspective of the publicly funded healthcare system, total annual healthcare costs were derived from linked provincial health administrative databases using a person-level costing method. We used generalised linear models to examine the association between the level of multimorbidity and healthcare costs and the extent to which socio-demographic variables modified this association.

RESULTS

Attributable total costs of multimorbidity ranged from C$377 to C$2073 for young individuals and C$1026 to C$3831 for older adults. The association between the degree of multimorbidity and healthcare costs was significantly modified by age (p<0.001), sex (p<0.001) and neighbourhood income (p<0.001) in both age groups, and the positive association between healthcare costs and levels of multimorbidity was statistically stronger for older than younger adults. For individuals aged 65 years or younger, the increase in healthcare costs was more gradual in women than in their male counterparts, however, for those aged 65 years or older, the increase in healthcare costs was significantly greater among women than men. Lastly, we also observed that the positive association between the level of multimorbidity and healthcare costs was significantly greater at higher levels of marginalisation.

CONCLUSION

Socio-demographic factors are important effect modifiers of the relationship between multimorbidity and healthcare costs and should therefore be considered in any discussion of the implementation of healthcare policies and the organisation of healthcare services aimed at controlling healthcare costs associated with multimorbidity.

Evidence on multimorbidity from definition to intervention: An overview of systematic reviews

The increasing challenge of multiple chronic diseases (multimorbidity) requires more evidence-based knowledge and effective practice. In order to better understand the existing evidence on multimorbidity, we performed a systematic review of systematic reviews on multimorbidity with pre-established search strategies and exclusion criteria by searching multiple databases and grey literature. Of 8006 articles found, 53 systematic reviews (including meta-analysis and qualitative research synthesis performed in some reviews) that stated multimorbidity as the main focus were included, with 79% published during 2013-2016. Existing evidence on definition, measurement, prevalence, risk factors, health outcomes, clinical practice and medication (polypharmacy), and intervention and management were identified and synthesised. There were three major definitions from three perspectives. Seven studies on prevalence reported a range from 3.5% to 100%. As six studies showed, depression, hypertension, diabetes, arthritis, asthma, and osteoarthritis were prone to be comorbid with other conditions. Four groups of risk factors and eight multimorbidity associated outcomes were explored by five and six studies, respectively. Nine studies evaluated interventions, which could be categorized into either organizational or patient-oriented, the effects of these interventions were varied. Self-management process, priority setting and decision making in multimorbidity were synthesised by evidence from 4 qualitative systematic reviews. We were unable to draw solid conclusions from this overview due to the heterogeneity in methodology and inconsistent findings among included reviews. As suggested by all included studies, there is a need for prospective research, especially longitudinal cohort studies and randomized control trials, to provide more definitive evidence on multimorbidity.

Exploring interprofessional, interagency multimorbidity care: case study based observational research

BACKGROUND

The increase in multimorbidity or co-occurring chronic illnesses is a leading healthcare concern. Patients with multimorbidity require ongoing care from many different professionals and agencies, and often report a lack of integrated care.

OBJECTIVE

To explore the daily help-seeking behaviours of patients with multimorbidity, including which health professionals they seek help from, how professionals work together, and perceptions and characteristics of effective interprofessional, interagency multimorbidity care.

DESIGN

Using a case study observational research design, multiple data sources were assembled for four patients with multimorbidity, identified by two general practitioners in New Zealand. In this paper, two case studies are presented, including the recorded instances of contact and communication between patients and professionals, and between professionals. Professional interactions were categorized as consultation, coordination, or collaboration.

RESULTS

The two case studies illustrated two female patients with likely similar educational levels, but with different profiles of multimorbidity, social circumstances, and personal capabilities, involving various professionals and agencies. Engagement between professionals showed varying levels of interaction and a lack of clarity about leadership or care coordination. The majority of interactions were one-to-one consultations and rarely involved coordination and collaboration. Patients were rarely included in communications between professionals.

CONCLUSION

Cases constructed from multiple data sources illustrate the complexity of day-to-day, interprofessional, interagency multimorbidity care. While consultation is the most frequent mode of professional interaction, targeted coordinated and collaborative interactions (including the patient) are highly effective activities. Greater attention should be given to developing and facilitating these interactions and determining who should lead them.

Multimorbidity and health-related quality of life (HRQoL) in a nationally representative population sample: implications of count versus cluster method for defining multimorbidity on HRQoL

Background

No universally accepted definition of multimorbidity (MM) exists, and implications of different definitions have not been explored. This study examined the performance of the count and cluster definitions of multimorbidity on the sociodemographic profile and health-related quality of life (HRQoL) in a general population.

Methods

Data were derived from the nationally representative 2007 Australian National Survey of Mental Health and Wellbeing (n = 8841). The HRQoL scores were measured using the Assessment of Quality of Life (AQoL-4D) instrument. The simple count (2+ & 3+ conditions) and hierarchical cluster methods were used to define/identify clusters of multimorbidity. Linear regression was used to assess the associations between HRQoL and multimorbidity as defined by the different methods.

Results

The assessment of multimorbidity, which was defined using the count method, resulting in the prevalence of 26% (MM2+) and 10.1% (MM3+). Statistically significant clusters identified through hierarchical cluster analysis included heart or circulatory conditions (CVD)/arthritis (cluster-1, 9%) and major depressive disorder (MDD)/anxiety (cluster-2, 4%). A sensitivity analysis suggested that the stability of the clusters resulted from hierarchical clustering. The sociodemographic profiles were similar between MM2+, MM3+ and cluster-1, but were different from cluster-2. HRQoL was negatively associated with MM2+ (β: −0.18, SE: −0.01, p < 0.001), MM3+ (β: −0.23, SE: −0.02, p < 0.001), cluster-1 (β: −0.10, SE: 0.01, p < 0.001) and cluster-2 (β: −0.36, SE: 0.01, p < 0.001).

Conclusions

Our findings confirm the existence of an inverse relationship between multimorbidity and HRQoL in the Australian population and indicate that the hierarchical clustering approach is validated when the outcome of interest is HRQoL from this head-to-head comparison. Moreover, a simple count fails to identify if there are specific conditions of interest that are driving poorer HRQoL. Researchers should exercise caution when selecting a definition of multimorbidity because it may significantly influence the study outcomes.

The Knowledge, Awareness, and Practices of Portuguese General Practitioners Regarding Multimorbidity and its Management: Qualitative Perspectives from Open-Ended Questions

Multimorbidity's high prevalence and negative impact has made it a subject of worldwide interest. The main aim of this study was to access the Portuguese knowledge, awareness, and practices of general practitioners (GPs) regarding multimorbidity and its management, in order to aid in the development of interventions for improving outcomes in multimorbid patients in primary care. A web-based qualitative descriptive study was carried out in the first trimester of 2016 with primary care physicians working in two districts of the Centre region of Portugal. Open-ended questions were analysed via inductive thematic content analysis. GPs pointed out several difficulties and challenges while managing multimorbidity. Extrinsic factors were associated with the healthcare system logistics' management (consultation time, organization of care teams, clinical information) and society (media pressure, social/family support). Intrinsic factors related to the GP, patient, and physician-patient relationship were also stated. The most significant conclusion to emerge from this study is that although GPs perceived difficulties and challenges towards multimorbidity, they also have the tools to deal with them: the fundamental characteristics of family medicine. Also, the complex care required by multimorbid patients needs adequate consultation time, multidisciplinary teamwork, and more education/training.

Diverse Cumulative Impact of Chronic Diseases on Physical Health-Related Quality of Life: Implications for a Measure of Multimorbidity

Debate continues on how to measure and weight diseases in multimorbidity. We quantified the association of a broad range of chronic diseases with physical health-related qualify of life and used these weights to develop and validate a multimorbidity weighted index (MWI). Community-dwelling adults in 3 national, prospective studies-the Nurses' Health Study (n = 121,701), Nurses' Health Study II (n = 116,686), and Health Professionals Follow-up Study (n = 51,529)-reported physician-diagnosed diseases and completed the Short Form 36 physical functioning (PF) scale over multiple survey cycles between 1992 and 2008. Mixed models were used to obtain regression coefficients for the impact of 98 morbid conditions on PF. The MWI was formed by weighting conditions by these coefficients and was validated through bootstrapping. The final sample included 612,592 observations from 216,890 participants (PF mean score = 46.5 (standard deviation, 11)). The association between diseases and PF varied severalfold (median, -1.4; range, -10.6 to 0.8). End-stage organ diseases were associated with the greatest reduction in PF. The mean MWI score was 4.8 (median, 3.7; range, 0-53), and the mean number of comorbid conditions was 3.3 (median, 2.8; range, 0-34). This validated MWI weights diseases by severity using PF, a patient-centered outcome. These results suggest that simple disease count is unlikely to capture the full impact of multimorbidity on health-related quality of life, and that the MWI is feasible and readily implemented.

Meeting the needs of a complex population: a functional health- and patient-centered approach to managing multimorbidity

Individuals with multimorbidity have complex care needs along with significant impacts to their functional health and quality of life. Recent evidence-based and experience-based explorations have revealed the importance of patient perspectives and functional health management in improving care delivery and health outcomes for individuals with multimorbidity. The impact of managing multimorbidity is evident at multiple levels of healthcare – the individual, the provider, and the system. Our local experience dealing with these challenges has led to the development of a functional health model that includes patient perspectives in care delivery within the Integrated Chronic Care Service (ICCS) of the health authority in Nova Scotia. In this paper, we present a discussion of the challenges, guiding models, and service-level transformations that have been integrated into care delivery at the ICCS to meet the healthcare needs of people with multiple health conditions. We describe our redesign strategies for care team planning, treatment approach, and patient inclusion.

Nutritional assessment and post-procedural complications in older stroke patients after insertion of percutaneous endoscopic gastrostomy - a retrospective study

Background

Oropharyngeal dysphagia is one of the major complications of stroke and a risk factor for malnutrition and prolonged in-hospital stay.

Objective

The overall aim was to describe to what extent nutritional assessments (i.e. BMI kg/m², eating problem, and weight loss) were performed and documented in the records of older stroke patients treated with enteral nutrition by percutaneous endoscopic gastrostomy (PEG). A secondary aim was to identify documented post-procedural complications after PEG insertion during hospital stay.

Design

The study is retrospective. Data were collected from records of 161 stroke patients ≥65 years, who received PEG, admitted to three stroke units during a 4-year period.

Results

Mean age of the patients was 82.2 (±7) years, and 86% of the patients were ≥75 years old. On admission, body weight was documented in 50% of the patients and at discharge in 38% of the patients. BMI data were not documented at all at discharge in one of the units. Almost 80% of the patients fulfilled the European Network criteria for multimorbidity. Morbidity and multimorbidity correlated to the length of stay (p<0.0005). Complications were reported in 111 (69%) of the patient records. In 53 patients (33%) more than one complication was reported. A total of 116 pressure ulcers were reported and 30 patients had more than one pressure ulcer. The number of complications was related to weight loss (p=0.046) and BMI change (p=0.018).

Conclusions

Essential information of the patient's nutritional status was poorly recorded which could affect the patient's nutritional treatment during the hospital stay. This study indicates that implementation of guidelines in patients with stroke is needed. The high number of pressure ulcers was an unexpected finding.