Related Articles

Background

Obstructive sleep apnea (OSA) is becoming increasingly prevalent in North America and has been described in association with specific chronic diseases, particularly cardiovascular diseases. In primary care, where the prevalence of co-occurring chronic conditions is very high, the potential association with OSA is unknown. The purpose of this study was to explore the association between OSA and 1) the presence and severity of multimorbidity (multiple co-occurring chronic conditions), and 2) subcategories of multimorbidity.

Methods

A cluster sampling technique was used to recruit 120 patients presenting with OSA of various severities from the records of a sleep laboratory in 2008. Severity of OSA was based on the results of the polysomnography. Patients invited to participate received a mail questionnaire including questions on sociodemographic characteristics and the Disease Burden Morbidity Assessment (DBMA). They also consented to give access to their medical records. The DBMA was used to provide an overall multimorbidity score and sub-score of diseases affecting various systems.

Results

Bivariate analysis did not demonstrate an association between OSA and multimorbidity (r = 0.117; p = 0.205). However, severe OSA was associated with multimorbidity (adjusted odds ratio = 7.33 [1.67-32.23], p = 0.05). OSA was moderately correlated with vascular (r = 0.26, p = 0.01) and metabolic syndrome (r = 0.26, p = 0.01) multimorbidity sub-scores.

Conclusions

This study showed that severe OSA is associated with severe multimorbidity and sub-scores of multimorbidity. These results do not allow any causal inference. More research is required to confirm these associations. However, primary care providers should be aware of these potential associations and investigate OSA when deemed appropriate.

Background

Abundant literature supports the beneficial effects of physical activity for improving health of people with chronic diseases. The relationship between multimorbidity and physical activity levels, however, has been little evaluated. The purpose of the current exploratory study was to examine the relationship between a) multimorbidity and physical activity levels, and b) long-term limitations on activity, self-rated general health, psychological distress, and physical activity levels for each sex in adults, after age, education, income, and employment factors were controlled for.

Methods

Data from the Quebec Health Survey 1998 were used. The sample included 16,782 adults 18–69 yr of age. Independent variables were multimorbidity, long-term limitations on activity, self-rated general health, and psychological distress. The dependent variable was physical activity levels. Links between the independent and dependent variables were assessed separately for men and women with multinomial regressions while accounting for the survey sampling design and household clustering.

Results

About 46% of the participants were men. Multimorbidity was not associated with physical activity levels for either men or women. Men and women with long-term limitations on activity and with poor-to-average self-rated general health were less likely to be physically active. No relationship between psychological distress and physical activity was found for men. Women with high levels of psychological distress were less likely to be physically active.

Conclusion

Multimorbidity was not associated with physical activity levels in either sex, when age, education, income, and employment factors were controlled for. Long-term limitations on activity and poor-to-average self-rated general health seem related to a reduction in physical activity levels for both sexes, whereas psychological distress was associated with a reduction in physical activity levels only among women. Longitudinal studies using a comorbidity or multimorbidity index to account for severity of the chronic diseases are needed to replicate the results of this exploratory study.

Background

Multimorbidity is common in primary care populations. Within cardiovascular disease, important differences in disease prevalence and risk factor management by ethnicity are recognised.

Aim

To examine the population burden of cardiovascular multimorbidity and the management of modifiable risk factors by ethnicity.

Design and setting

Cross-sectional study of general practices (148/151) in the east London primary care trusts of Tower Hamlets, City and Hackney, and Newham, with a total population size of 843 720.

Method

Using MIQUEST, patient data were extracted from five cardiovascular registers. Logistic regression analysis was used to examine the risk of being multimorbid by ethnic group, and the control of risk factors by ethnicity and burden of cardiovascular multimorbidity.

Results

The crude prevalence of cardiovascular multimorbidity among patients with at least one cardiovascular condition was 34%. People of non-white ethnicity are more likely to be multimorbid than groups of white ethnicity, with adjusted odds ratios of 2.04 (95% confidence interval [CI] = 1.94 to 2.15) for South Asians and 1.23 (95% CI = 1.18 to 1.29) for groups of black ethnicity. Achievement of targets for blood pressure, cholesterol, and glycated haemoglobin (HbA1c) was higher for patients who were multimorbid than unimorbid. For cholesterol and blood pressure, South Asian patients achieved better control than those of white and black ethnicity. For HbA1c levels, patients of white ethnicity had an advantage over other groups as the morbidity burden increased.

Conclusion

The burden of multiple disease varies by ethnicity. Risk factor management improves with increasing levels of cardiovascular multimorbidity, but clinically important differences by ethnicity remain and contribute to health inequalities.

Background

In developed countries, primary health care increasingly involves the care of patients with multiple chronic conditions, referred to as multimorbidity.

Aim

To describe the epidemiology of multimorbidity and relationships between multimorbidity and primary care consultation rates and continuity of care.

Design of study

Retrospective cohort study.

Setting

Random sample of 99 997 people aged 18 years or over registered with 182 general practices in England contributing data to the General Practice Research Database.

Method

Multimorbidity was defined using two approaches: people with multiple chronic conditions included in the Quality and Outcomes Framework, and people identified using the Johns Hopkins University Adjusted Clinical Groups (ACG®) Case-Mix System. The determinants of multimorbidity (age, sex, area deprivation) and relationships with consultation rate and continuity of care were examined using regression models.

Results

Sixteen per cent of patients had more than one chronic condition included in the Quality and Outcomes Framework, but these people accounted for 32% of all consultations. Using the wider ACG list of conditions, 58% of people had multimorbidity and they accounted for 78% of consultations. Multimorbidity was strongly related to age and deprivation. People with multimorbidity had higher consultation rates and less continuity of care compared with people without multimorbidity.

Conclusion

Multimorbidity is common in the population and most consultations in primary care involve people with multimorbidity. These people are less likely to receive continuity of care, although they may be more likely to gain from it.

Background

Published prevalence studies on multimorbidity present diverse data collection methods, sources of data, targeted age groups, diagnoses considered and study populations, making the comparability of prevalence estimates questionable. The objective of this study was to compare prevalence estimates of multimorbidity derived from two sources and to examine the impact of the number of diagnoses considered in the measurement of multimorbidity.

Methods

Prevalence of multimorbidity was estimated in adults over 25 years of age from two separate Canadian studies: a 2005 survey of 26,000 respondents randomly selected from the general population and a 2003 study of 980 patients from 21 family practices. We estimated the prevalence of multimorbidity based on the co-occurrence of ≥ 2 and ≥ 3 diseases of the seven diseases listed in the general population survey. For primary care patients, we also estimated multimorbidity prevalence using an open list of chronic diseases.

Results

Prevalence estimates were considerably higher for each age group in the primary care sample than in the general population. For primary care patients, the number of chronic diseases considered for estimates resulted in large differences, especially in younger age groups. The prevalence of multimorbidity increased with age in both study populations.

Conclusions

The prevalence of multimorbidity was substantially lower when estimated in a general population than in a family practice-based sample and was higher when the number of conditions considered increased.

Background

Measures of multimorbidity are often applied to source data, populations or outcomes outside the scope of their original developmental work. As the development of a multimorbidity measure is influenced by the population and outcome used, these influences should be taken into account when selecting a multimorbidity index. The aim of this study was to compare the strength of the association of health-related quality of life (HRQOL) with three multimorbidity indices: the Cumulative Illness Rating Scale (CIRS), the Charlson index (Charlson) and the Functional Comorbidity Index (FCI). The first two indices were not developed in light of HRQOL.

Methods

We used data on chronic diseases and on the SF-36 questionnaire assessing HRQOL of 238 adult primary care patients who participated in a previous study. We extracted all the diagnoses for every patient from chart review to score the CIRS, the FCI and the Charlson. Data for potential confounders (age, sex, self-perceived economic status and self-perceived social support) were also collected. We calculated the Pearson correlation coefficients (r) of the SF-36 scores with the three measures of multimorbidity, as well as the coefficient of determination, R2, while controlling for confounders.

Results

The r values for the CIRS (range: -0.55 to -0.18) were always higher than those for the FCI (-0.47 to -0.10) and Charlson (-0.31 to -0.04) indices. The CIRS explained the highest percent of variation in all scores of the SF-36, except for the Mental Component Summary Score where the variation was not significant. Variations explained by the FCI were significant in all scores of SF-36 measuring physical health and in two scales evaluating mental health. Variations explained by the Charlson were significant in only three scores measuring physical health.

Conclusion

The CIRS is a better choice as a measure of multimorbidity than the FCI and the Charlson when HRQOL is the outcome of interest. However, the FCI may provide a good option to evaluate the physical aspect of HRQOL for the ease in its administration and scoring. The Charlson index may not be recommended as a measure of multimorbidity in studies related to either physical or mental aspects of HRQOL.

BACKGROUND

The growing interest in pay-for-performance and other quality improvement programs has generated concerns about potential performance measurement penalties for providers who care for more complex patients, such as patients with more chronic conditions. Few data are available on how multimorbidity affects common performance metrics.

OBJECTIVE

To examine the relationship between multimorbidity and patients’ ratings of communication, a common performance metric.

DESIGN

Cross-sectional study

SETTING

Nationally representative sample of U.S. residents

PARTICIPANTS

A total of 15,709 noninstitutionalized adults living in the United States participated in a telephone interview.

MEASUREMENTS

We used 2 different measures of multimorbidity: 1) “individual conditions” approach disregards similarities/concordance among chronic conditions and 2) “condition-groups” approach considers similarities/concordance among conditions. We used a composite measure of patients’ ratings of patient–physician communication.

RESULTS

A higher number of individual conditions is associated with lower ratings of communication, although the magnitude of the relationship is small (adjusted average communication scores: 0 conditions, 12.20; 1–2 conditions, 12.06; 3+ conditions, 11.90; scale range 5 = worst, 15 = best). This relationship remains statistically significant when concordant relationships among conditions are considered (0 condition groups 12.19; 1–2 condition groups 12.03; 3+ condition groups 11.94).

CONCLUSIONS

In our nationally representative sample, patients with more chronic conditions gave their doctors modestly lower patient–doctor communication scores than their healthier counterparts. Accounting for concordance among conditions does not widen the difference in communication scores. Concerns about performance measurement penalty related to patient complexity cannot be entirely addressed by adjusting for multimorbidity. Future studies should focus on other aspects of clinical complexity (e.g., severity, specific combinations of conditions).

Background

Multimorbidity is a phenomenon with high burden and high prevalence in the elderly. Our previous research has shown that multimorbidity can be divided into the multimorbidity patterns of 1) anxiety, depression, somatoform disorders (ADS) and pain, and 2) cardiovascular and metabolic disorders. However, it is not yet known, how these patterns are influenced by patient characteristics. The objective of this paper is to analyze the association of socio-demographic variables, and especially socio-economic status with multimorbidity in general and with each multimorbidity pattern.

Methods

The MultiCare Cohort Study is a multicentre, prospective, observational cohort study of 3.189 multimorbid patients aged 65+ randomly selected from 158 GP practices. Data were collected in GP interviews and comprehensive patient interviews. Missing values have been imputed by hot deck imputation based on Gower distance in morbidity and other variables. The association of patient characteristics with the number of chronic conditions is analysed by multilevel mixed-effects linear regression analyses.

Results

Multimorbidity in general is associated with age (+0.07 chronic conditions per year), gender (-0.27 conditions for female), education (-0.26 conditions for medium and -0.29 conditions for high level vs. low level) and income (-0.27 conditions per logarithmic unit). The pattern of cardiovascular and metabolic disorders shows comparable associations with a higher coefficient for gender (-1.29 conditions for female), while multimorbidity within the pattern of ADS and pain correlates with gender (+0.79 conditions for female), but not with age or socioeconomic status.

Conclusions

Our study confirms that the morbidity load of multimorbid patients is associated with age, gender and the socioeconomic status of the patients, but there were no effects of living arrangements and marital status. We could also show that the influence of patient characteristics is dependent on the multimorbidity pattern concerned, i.e. there seem to be at least two types of elderly multimorbid patients. First, there are patients with mainly cardiovascular and metabolic disorders, who are more often male, have an older age and a lower socio-economic status. Second, there are patients mainly with ADS and pain-related morbidity, who are more often female and equally distributed across age and socio-economic groups.

Trial registration

ISRCTN89818205

Background

Many patients with several concurrent medical conditions (multimorbidity) are seen in the primary care setting. A thorough understanding of outcomes associated with multimorbidity would benefit primary care workers of all disciplines. The purpose of this systematic review was to clarify the relationship between the presence of multimorbidity and the quality of life (QOL) or health-related quality of life (HRQOL) of patients seen, or likely to be seen, in the primary care setting.

Methods

Medline and Embase electronic databases were screened using the following search terms for the reference period 1990 to 2003: multimorbidity, comorbidity, chronic disease, and their spelling variations, along with quality of life and health-related quality of life. Only descriptive studies relevant to primary care were selected.

Results

Of 753 articles screened, 108 were critically assessed for compliance with study inclusion and exclusion criteria. Thirty of these studies were ultimately selected for this review, including 7 in which the relationship between multimorbidity or comorbidity and QOL or HRQOL was the main outcome measure. Major limitations of these studies include the lack of a uniform definition for multimorbidity or comorbidity and the absence of assessment of disease severity. The use of self-reported diagnoses may also be a weakness. The frequent exclusion of psychiatric diagnoses and presence of potential confounding variables are other limitations. Nonetheless, we did find an inverse relationship between the number of medical conditions and QOL related to physical domains. For social and psychological dimensions of QOL, some studies reveal a similar inverse relationship in patients with 4 or more diagnoses.

Conclusions

Our findings confirm the existence of an inverse relationship between multimorbidity or comorbidy and QOL. However, additional studies are needed to clarify this relationship, including the various dimensions of QOL affected. Those studies must employ a clear definition of multimorbidity or comorbidity and valid ways to measure these concepts in a primary care setting. Pursuit of this research will help to better understand the impact of chronic diseases on patients.

Background

General practitioners often care for patients with several concurrent chronic medical conditions (multimorbidity). Recent data suggest that multimorbidity might be observed more often than isolated diseases in primary care. We explored the age- and gender-related prevalence of multimorbidity and compared these estimates to the prevalence estimates of other common specific diseases found in Swiss primary care.

Methods

We analyzed data from the Swiss FIRE (Family Medicine ICPC Research using Electronic Medical Record) project database, representing a total of 509,656 primary care encounters in 98,152 adult patients between January 1, 2009 and July 31, 2011. For each encounter, medical problems were encoded using the second version of the International Classification of primary Care (ICPC-2). We defined chronic health conditions using 147 pre-specified ICPC-2 codes and defined multimorbidity as 1) two or more chronic health conditions from different ICPC-2 rubrics, 2) two or more chronic health conditions from different ICPC-2 chapters, and 3) two or more medical specialties involved in patient care. We compared the prevalence estimates of multimorbidity defined by the three methodologies with the prevalence estimates of common diseases encountered in primary care.

Results

Overall, the prevalence estimates of multimorbidity were similar for the three different definitions (15% [95%CI 11-18%], 13% [95%CI 10-16%], and 14% [95%CI 11-17%], respectively), and were higher than the prevalence estimates of any specific chronic health condition (hypertension, uncomplicated 9% [95%CI 7-11%], back syndrome with and without radiating pain 6% [95%CI 5-7%], non-insulin dependent diabetes mellitus 3% [95%CI 3-4%]), and degenerative joint disease 3% [95%CI 2%-4%]). The prevalence estimates of multimorbidity rose more than 20-fold with age, from 2% (95%CI 1-2%) in those aged 20–29 years, to 38% (95%CI 31-44%) in those aged 80 or more years. The prevalence estimates of multimorbidity were similar for men and women (15% vs. 14%, p=0.288).

Conclusions

In primary care, prevalence estimates of multimorbidity are higher than those of isolated diseases. Among the elderly, more than one out of three patients suffer from multimorbidity. Management of multimorbidity is a principal concern in this vulnerable patient population.

Background

Although multiple co-occurring chronic illnesses within the same individual are increasingly common, few studies have examined the challenges of multimorbidity from the patient perspective.

Objective

The aim of this study is to examine the self-management learning needs and willingness to see non-physician providers of patients with multimorbidity compared to patients with single chronic illnesses.

Design

This research is designed as a cross-sectional survey.

Participants

Based upon ICD-9 codes, patients from a single VHA healthcare system were stratified into multimorbidity clusters or groups with a single chronic illness from the corresponding cluster. Nonproportional sampling was used to randomly select 720 patients.

Measurements

Demographic characteristics, functional status, number of contacts with healthcare providers, components of primary care, self-management learning needs, and willingness to see nonphysician providers.

Results

Four hundred twenty-two patients returned surveys. A higher percentage of multimorbidity patients compared to single morbidity patients were “definitely” willing to learn all 22 self-management skills, of these only 2 were not significant. Compared to patients with single morbidity, a significantly higher percentage of patients with multimorbidity also reported that they were “definitely” willing to see 6 of 11 non-physician healthcare providers.

Conclusions

Self-management learning needs of multimorbidity patients are extensive, and their preferences are consistent with team-based primary care. Alternative methods of providing support and chronic illness care may be needed to meet the needs of these complex patients.

Background

Although multiple co-occurring chronic illnesses within the same individual are increasingly common, few studies have examined the challenges of multimorbidity from the patient perspective.

Objective

The aim of this study is to examine the self-management learning needs and willingness to see non-physician providers of patients with multimorbidity compared to patients with single chronic illnesses.

Design

This research is designed as a cross-sectional survey.

Participants

Based upon ICD-9 codes, patients from a single VHA healthcare system were stratified into multimorbidity clusters or groups with a single chronic illness from the corresponding cluster. Nonproportional sampling was used to randomly select 720 patients.

Measurements

Demographic characteristics, functional status, number of contacts with healthcare providers, components of primary care, self-management learning needs, and willingness to see nonphysician providers.

Results

Four hundred twenty-two patients returned surveys. A higher percentage of multimorbidity patients compared to single morbidity patients were “definitely” willing to learn all 22 self-management skills, of these only 2 were not significant. Compared to patients with single morbidity, a significantly higher percentage of patients with multimorbidity also reported that they were “definitely” willing to see 6 of 11 non-physician healthcare providers.

Conclusions

Self-management learning needs of multimorbidity patients are extensive, and their preferences are consistent with team-based primary care. Alternative methods of providing support and chronic illness care may be needed to meet the needs of these complex patients.

Background

Like many patients with diabetes, Department of Veterans Affairs (VA) patients frequently fall short of self-management goals and experience multiple barriers to self-care. Health information technologies (HITs) may provide the tools that patients need to manage their illness under the direction of their primary care team.

Methods

We describe several ongoing projects focused on HIT resources for self-management in VA. VA researchers are developing HITs that seek to bolster a variety of potential avenues for self-management support, including patients′ relationships with other patients, connections with their informal care networks, and communication with their health care teams.

Results

Veterans Affairs HIT research projects are developing services that can address the needs of patients with multiple challenges to disease self-care, including multimorbidity, health literacy deficits, and limited treatment access. These services include patient-to-patient interactive voice response (IVR) calling systems, IVR assessments with feedback to informal caregivers, novel information supports for clinical pharmacists based on medication refill data, and enhanced pedometers.

Conclusion

Large health care systems such as the VA can play a critical role in developing HITs for diabetes self-care. To be truly effective, these efforts should include a continuum of studies: observational research to identify barriers to self-management, developmental studies (e.g., usability testing), efficacy trials, and implementation studies to evaluate utility in real-world settings. VA HIT researchers partner with operations to promote the dissemination of efficacious services, and such relationships will be critical to move HIT innovations into practice.

OBJECTIVE

Family physicians often have to care for patients with several concurrent chronic conditions (multimorbidity or comorbidity). Consequently, they need to inform themselves by reading indexed publications on multimorbidity. This study aimed to assess how well the concept of multimorbidity was covered in the medical literature. Objectives were first, to quantify the literature on multimorbidity (or comorbidity) and to compare the number of publications on it with the number of publications on three common chronic conditions (asthma, hypertension, and diabetes), and second, to describe the articles on multimorbidity.

DESIGN

Bibliometric study.

METHOD

We consulted MEDLINE for the reference period 1990 to the end of 2002. The term “multimorbidity” and its various spellings was used as the search term. Comorbidity, asthma, hypertension, and diabetes were searched for using their respective MeSH terms. For comparison purposes, prevalence data were taken from published sources. Abstracts of articles relating to multimorbidity were reviewed and their content analyzed.

MAIN OUTCOME MEASURES

Number and type of articles.

RESULTS

Multimorbidity has a prevalence of 60% among people aged 55 to 74. This prevalence is much higher than that of asthma (6.5%), hypertension (29.6%), and diabetes (8.7%). Few articles in the medical literature deal specifically with multimorbidity (or comorbidity), however. For each article on multimorbidity, there are 74 on asthma, 94 on hypertension, and 38 on diabetes. Content analysis of abstracts of articles on multimorbidity revealed a high proportion of epidemiologic studies (50.0%) followed by validation studies (22.4%) and opinion pieces (11.8%). The few experimental studies on multimorbidity were not done in primary care settings.

CONCLUSION

This study shows that the prevalence of multimorbidity is not matched by the number of indexed publications on it in the medical literature. To date, the number and diversity of articles on multimorbidity are both insufficient to provide scientific background for strong evidence-based care of patients affected by multiple concurrent chronic conditions. Research is needed to increase knowledge and understanding of this important clinical topic.

Background

Studies on the prevalence of multimorbidity, defined as having two or more chronic conditions, have predominantly focused on the elderly. We estimated the prevalence and specific patterns of multimorbidity across different adult age groups. Furthermore, we examined the associations of multimorbidity with socio-demographic factors.

Methods

Using data from the Health Quality Council of Alberta (HQCA) 2010 Patient Experience Survey, the prevalence of self reported multimorbidity was assessed by telephone interview among a sample of 5010 adults (18 years and over) from the general population. Logistic regression analyses were performed to determine the association between a range of socio-demographic factors and multimorbidity.

Results

The overall age- and sex-standardized prevalence of multimorbidity was 19.0% in the surveyed general population. Of those with multimorbidity, 70.2% were aged less than 65 years. The most common pairing of chronic conditions was chronic pain and arthritis. Age, sex, income and family structure were independently associated with multimorbidity.

Conclusions

Multimorbidity is a common occurrence in the general adult population, and is not limited to the elderly. Future prevention programs and practice guidelines should take into account the common patterns of multimorbidity.

Background

Multimorbidity is defined as the occurrence of two or more chronic diseases in one individual. Patients with multimorbidity generally have poorer health and functioning and higher rates of attendance in primary care and specialty settings.

Aim

To explore the views and attitudes of GPs and pharmacists managing patients with multimorbidity in primary care.

Design of study

Qualitative study using focus groups.

Setting

Primary care in Ireland.

Method

Three focus groups were held in total, involving 13 GPs and seven pharmacists. Focus groups were recorded, transcribed, and analysed using the ‘framework’ approach.

Results

The predominant themes to emerge from the focus groups were: 1) the concept of multimorbidity and the link to polypharmacy and ageing; 2) health systems issues relating to lack to time, inter-professional communication difficulties, and fragmentation of care; 3) individual issues from clinicians relating to professional roles, clinical uncertainty, and avoidance; 4) patient issues; and 5) potential management solutions.

Conclusion

This study provides information on the significant impact of multimorbidity from a professional perspective. It highlights potential elements of an intervention that could be designed and tested to achieve improvements in the management of multimorbidity, outcomes for individuals affected, and the experiences of those providing healthcare.

Objectives

The primary objective of this study was to identify the existence of chronic disease multimorbidity patterns in the primary care population, describing their clinical components and analysing how these patterns change and evolve over time both in women and men. The secondary objective of this study was to generate evidence regarding the pathophysiological processes underlying multimorbidity and to understand the interactions and synergies among the various diseases.

Methods

This observational, retrospective, multicentre study utilised information from the electronic medical records of 19 primary care centres from 2008. To identify multimorbidity patterns, an exploratory factor analysis was carried out based on the tetra-choric correlations between the diagnostic information of 275,682 patients who were over 14 years of age. The analysis was stratified by age group and sex.

Results

Multimorbidity was found in all age groups, and its prevalence ranged from 13% in the 15 to 44 year age group to 67% in those 65 years of age or older. Goodness-of-fit indicators revealed sample values between 0.50 and 0.71. We identified five patterns of multimorbidity: cardio-metabolic, psychiatric-substance abuse, mechanical-obesity-thyroidal, psychogeriatric and depressive. Some of these patterns were found to evolve with age, and there were differences between men and women.

Conclusions

Non-random associations between chronic diseases result in clinically consistent multimorbidity patterns affecting a significant proportion of the population. Underlying pathophysiological phenomena were observed upon which action can be taken both from a clinical, individual-level perspective and from a public health or population-level perspective.

Background. Individuals with multimorbidity are vulnerable to poor quality of care due to issues related to care coordination. Ambulatory care sensitive hospitalizations (ACSHs) are widely accepted quality indicators because they can be avoided by timely, appropriate, and high-quality outpatient care. Objective. To examine the association between multimorbidity, mental illness, and ACSH. Study Design. We used a longitudinal panel design with data from multiple years (2000–2005) of Medicare Current Beneficiary Survey. Individuals were categorized into three groups: (1) multimorbidity with mental illness (MM/MI); (2) MM/no MI; (3) no MM. Multivariable logistic regressions were used to analyze the association between multimorbidity and ACSH. Results. Any ACSH rates varied from 10.8% in MM/MI group to 8.8% in MM/No MI group. Likelihood of any ACSH was higher among beneficiaries with MM/MI (AOR = 1.62; 95% CI = 1.14, 2.30) and MM (AOR = 1.54; 95% CI = 1.12, 2.11) compared to beneficiaries without multimorbidity. There was no statistically significant difference in likelihood of ACSH between MM/MI and MM/No MI groups. Conclusion. Multimorbidity (with or without MI) had an independent and significant association with any ACSH. However, presence of mental illness alone was not associated with poor quality of care as measured by ACSH.

Background

Multimorbidity has been defined as the co-existence of two or more chronic conditions. It has a profound impact on both the individuals affected and on their use of healthcare services. The limited research to date has focused on its epidemiology rather than the development of interventions to improve outcomes in multimorbidity patients, particularly for patients aged less than 65 years. Potential barriers to such research relate to methods of disease recording and coding and examination of the process of care. We aimed to assess the feasibility of identifying younger individuals with multimorbidity at general practice level and to explore the effect of multimorbidity on the type and volume of health care delivered. We also describe the barriers encountered in attempting to carry out this exploratory research.

Methods

Cross sectional survey of GP records in two large urban general practices in Dublin focusing on poorer individuals with at least three chronic conditions and aged between 45 and 64 years.

Results

92 patients with multimorbidity were identified. The median number of conditions was 4 per patient. Individuals received a mean number of 7.5 medications and attended a mean number of GP visits of 11.3 in the 12 months preceding the survey. Barriers to research into multimorbidity at practice level were identified including difficulties relating to GP clinical software; variation in disease coding; assessment of specialist sector activity through the GP-specialist communications and assessment of the full scale of primary care activity in relation to other disciplines and other types of GP contacts such as home visits and telephone contacts.

Conclusion

This study highlights the importance of multimorbidity in general practice and indicates that it is feasible to identify younger patients with multimorbidity through their GP records. This is a first step towards planning a clinical intervention to improve outcomes for such patients in primary care.

Health literacy refers to an individual’s ability to understand healthcare information to make appropriate decisions (S. C Ratzen & R. M. Parker, 2000). Healthcare professionals are obligated to make sure that patients understand information to maximize the benefits of healthcare. The National Assessment of Adult Literacy (NAAL) provides information on the literacy/health literacy levels of the U.S. adult population. The NAAL is the only large-scale survey of health literacy. The results of the NAAL provide information on literacy/health literacy and the relationship between background variables and literacy/health literacy. Multiple variables with potential for a relationship with literacy/health literacy were chosen for the NAAL including, but not limited to, education, language, race, gender, income, overall health, seeking health information, and health insurance.

Background

Although multimorbidity has important implications for patient care in general practice, limited research has examined chronic illness and health service utilisation among problem drug users. This study aimed to determine chronic illness prevalence and health service utilisation among problem drug users attending primary care for methadone treatment, to compare these rates with matched 'controls' and to develop and pilot test a valid study instrument.

Methods

A cross-sectional study of patients attending three large urban general practices in Dublin, Ireland for methadone treatment was conducted, and this sample was compared with a control group matched by practice, age, gender and General Medical Services (GMS) status.

Results

Data were collected on 114 patients. Fifty-seven patients were on methadone treatment, of whom 52(91%) had at least one chronic illness (other then substance use) and 39(68%) were prescribed at least one regular medication. Frequent utilisation of primary care services and secondary care services in the previous six months was observed among patients on methadone treatment and controls, although the former had significantly higher chronic illness prevalence and primary care contact rates. The study instrument facilitated data collection that was feasible and with minimal inter-observer variation.

Conclusion

Multimorbidity is common among problem drug users attending general practice for methadone treatment. Primary care may therefore have an important role in primary and secondary prevention of chronic illnesses among this population. This study offers a feasible study instrument for further work on this issue. (238 words)

Multimorbidity, i.e., the presence of multiple diseases within one person, is a significant health-care problem for western societies: diagnosis, prognosis and treatment in the presence of of multiple diseases can be complex due to the various interactions between diseases. A literature review reveals that there is a variety of definitions that describe different concepts with respect to multimorbidity, both for the cause of multimorbidity as well as the implications of multimorbidity. To be able to aid computerized decision support systems within patient care, e.g. electronic clinical guidelines that can be personalized given the patient’s problems, these multimorbidity aspects need to be defined rigorously in a formal language. In this paper, we employ causal Bayesian networks to define and analyze a novel framework that can be used to model a spectrum of aspects related to multimorbidity. We conclude that this framework provides a solid basis for modeling interactions between multiple diseases.

Objectives

To examine the relationship between literacy and asthma management with a focus on the oral exchange.

Methods

Study participants, all of whom reported asthma, were drawn from the New England Family Study (NEFS), an examination of links between education and health. NEFS data included reading, oral (speaking), and aural (listening) literacy measures. An additional survey was conducted with this group of study participants related to asthma issues, particularly asthma management. Data analysis focused on bivariate and multivariable logistic regression.

Results

In bivariate logistic regression models exploring aural literacy, there was a statistically significant association between those participants with lower aural literacy skills and less successful asthma management (OR:4.37, 95%CI:1.11, 17.32). In multivariable logistic regression analyses, controlling for gender, income, and race in separate models (one-at-a-time), there remained a statistically significant association between those participants with lower aural literacy skills and less successful asthma management.

Conclusion

Lower aural literacy skills seem to complicate asthma management capabilities.

Practice Implications

Greater attention to the oral exchange, in particular the listening skills highlighted by aural literacy, as well as other related literacy skills may help us develop strategies for clear communication related to asthma management.

Background

Among the strategies used to reform primary care, the participation of nurses in primary care practices appears to offer a promising avenue to better meet the needs of vulnerable patients. The present study explores the perceptions and expectations of patients with multimorbidity regarding nurses' presence in primary care practices.

Methods

18 primary (health) care patients with multimorbidity participated in semi-directed interviews, in order to explore their perceptions and expectations in regard to the involvement of nurses in primary care practices. Interviews were audio-recorded and transcribed. After reviewing the transcripts, the principal investigator and research assistants performed thematic analysis independently and reached consensus on the retained themes.

Results

Patients with multimorbidity were open to the participation of nurses in primary care practices. They expected greater accessibility, for both themselves and for new patients. However, the issue of shared roles between nurses and doctors was a source of concern. Many patients held the traditional view of the nurse's role as an assistant to the doctor in his or her various duties. In general, participants said they were confident about nurses' competency but expressed concern about nurses performing certain acts that their doctor used to, notwithstanding a close collaboration between the two professionals.

Conclusion

Patients with multimorbidity are open to the involvement of nurses in primary care practices. However, they expect this participation to be established using clear definitions of professional roles and fields of practice.

Objective To determine the effectiveness of interventions designed to improve outcomes in patients with multimorbidity in primary care and community settings.

Design Systematic review.

Data sources Medline, Embase, CINAHL, CAB Health, Cochrane central register of controlled trials, the database of abstracts of reviews of effectiveness, and the Cochrane EPOC (effective practice and organisation of care) register (searches updated in April 2011).

Eligibility criteria Randomised controlled trials, controlled clinical trials, controlled before and after studies, and interrupted time series analyses reporting on interventions to improve outcomes for people with multimorbidity in primary care and community settings. Multimorbidity was defined as two or more chronic conditions in the same individual. Outcomes included any validated measure of physical or mental health and psychosocial status, including quality of life outcomes, wellbeing, and measures of disability or functional status. Also included were measures of patient and provider behaviour, including drug adherence, utilisation of health services, acceptability of services, and costs.

Data selection Two reviewers independently assessed studies for eligibility, extracted data, and assessed study quality. As meta-analysis of results was not possible owing to heterogeneity in participants and interventions, a narrative synthesis of the results from the included studies was carried out.

Results 10 studies examining a range of complex interventions totalling 3407 patients with multimorbidity were identified. All were randomised controlled trials with a low risk of bias. Two studies described interventions for patients with specific comorbidities. The remaining eight studies focused on multimorbidity, generally in older patients. Consideration of the impact of socioeconomic deprivation was minimal. All studies involved complex interventions with multiple components. In six of the 10 studies the predominant component was a change to the organisation of care delivery, usually through case management or enhanced multidisciplinary team work. In the remaining four studies, intervention components were predominantly patient oriented. Overall the results were mixed, with a trend towards improved prescribing and drug adherence. The results indicated that it is difficult to improve outcomes in this population but that interventions focusing on particular risk factors in comorbid conditions or functional difficulties in multimorbidity may be more effective. No economic analyses were included, although the improvements in prescribing and risk factor management in some studies could provide potentially important cost savings.

Conclusions Evidence on the care of patients with multimorbidity is limited, despite the prevalence of multimorbidity and its impact on patients and healthcare systems. Interventions to date have had mixed effects, although are likely to be more effective if targeted at risk factors or specific functional difficulties. A need exists to clearly identify patients with multimorbidity and to develop cost effective and specifically targeted interventions that can improve health outcomes.