Catherine Hudon

Prevalence of Multimorbidity Among Adults Seen in Family Practice

PURPOSE There are few valid data that describe the extent of multimorbidity in primary care patients. The purpose of this study was to estimate its prevalence in family practice patients by counting the number of chronic medical conditions and using a measure that considers the severity of these conditions, the Cumulative Illness Rating Scale (CIRS). METHODS The study was carried out in the Saguenay region (Québec, Canada) in 2003. The participation of adult patients from 21 family physicians was solicited during consecutive consultation periods. A research nurse reviewed medical records and extracted the data regarding chronic illnesses. For each chronic condition, a severity rating was determined in accordance with the CIRS scoring guidelines. RESULTS The sample consisted of 320 men and 660 women. Overall, 9 of 10 patients had more than 1 chronic condition. The prevalence of having 2 or more medical conditions in the 18- to 44-year, 45- to 64-year, and 65-year and older age-groups was, respectively, 68%, 95%, and 99% among women and 72%, 89%, and 97% among men. The mean number of conditions and mean CIRS score also increased significantly with age. CONCLUSIONS Whether measured by simply counting the number of conditions or using the CIRS, the prevalence of multimorbidity is quite high and increases significantly with age in both men and women. Patients with multimorbidity seen in family practice represent the rule rather than the exception.

Multimorbidity and quality of life in primary care: a systematic review

BackgroundMany 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.MethodsMedline 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.ResultsOf 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.ConclusionsOur 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.

Relationship Between Multimorbidity and Health-Related Quality of Life of Patients in Primary Care

Previous studies about the association of multimorbidity and the health-related quality of life (HRQOL) in primary-care patients are limited because of their reliance on simple counts of diseases from a limited list of diseases and their failure to assess the severity of disease. We evaluated the association while taking into account the severity of the medical conditions based on the Cumulative Illness Rating Scale (CIRS) score, and controlling for potential confounders (age, sex, household income, education, self-perception of economic status, number of people living in the same dwelling, and perceived social support). We randomly selected 238 patients to construct quintiles of increasing multimorbidity (CIRS). Patients completed the 36-item Medical Outcomes study questionnaire (SF-36) to evaluate their HRQOL. Applying bivariate and multivariate linear regression analyses, we used the CIRS as either a continuous or a categorical (quintiles) variable. Use of the CIRS revealed a stronger association of HRQOL with multimorbidity than using a simple count of chronic conditions. Physical more than mental health deteriorated with increasing multimorbidity. Perceived social support and self-perception of economic status were significantly related to all scales of the SF-36 (p < 0.05). Increased multimorbidity adversely affected HRQOL in primary-care adult patients, even when confounding variables were controlled for.

Managing patients with multimorbidity : systematic review of interventions in primary care and community settings

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.

Multimorbidity's many challenges

Time to focus on the needs of this vulnerable and growing population

Prevalence estimates of multimorbidity: a comparative study of two sources.

BackgroundPublished 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.MethodsPrevalence 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.ResultsPrevalence 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.ConclusionsThe 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.

Measuring Patients’ Perceptions of Patient-Centered Care: A Systematic Review of Tools for Family Medicine

PURPOSE Patient-centered care is widely acknowledged as a core value in family medicine. In this systematic review, we aimed to identify and compare instruments, subscales, or items assessing patients’ perceptions of patient-centered care in family medicine. METHODS We conducted a systematic literature review using the MEDLINE, Embase, and Cochrane databases covering 1980 through April 2009, with a specific search strategy for each database. The search strategy was supplemented with searching by hand and expert suggestions. We looked for articles meeting all of the following criteria: (1) describing self-administered instruments measuring patient perceptions of patient-centered care; (2) reporting quantitative or psychometric results of development or validation; (3) being relevant to an ambulatory family medicine context. The quality of each article retained was assessed using a modified version of the Standards for Reporting of Diagnostic Accuracy. Instrument’ items were mapped to dimensions of a patient-centered care conceptual framework. RESULTS Of the 3,045 articles identified, 90 were examined in detail, and 26, covering 13 instruments, met our inclusion criteria. Two instruments (5 articles) were dedicated to patient-centered care: the Patient Perception of Patient-Centeredness and the Consultation Care Measure, and 11 instruments (21 articles) included relevant subscales or items. CONCLUSIONS The 2 instruments dedicated to patient-centered care address key dimensions but are visit-based, limiting their applicability for the study of care processes over time, such as chronic illness management. Relevant items from the 11 other instruments provide partial coverage of the concept, but these instruments were not designed to provide a specific assessment of patient-centered care.

Psychological Distress and Multimorbidity in Primary Care

PURPOSE Psychological distress may decrease adherence to medical treatments and lead to poorer health outcomes of chronic diseases. The aim of this study was to evaluate the relationship between psychological distress and multimorbidity among patients seen in family practice after controlling for potential confounding variables and taking into account the severity of diseases. METHODS We evaluated 238 patients to construct quintiles of increasing multimorbidity based on the Cumulative Illness Rating Scale (CIRS), which is a comprehensive multimorbidity index that takes into account disease severity. Patients completed a psychiatric symptom questionnaire as a measurement of their psychological distress. In the first model of logistic regression analyses, we used the counted number of chronic diseases as the independent variable. In subsequent models, we used the quintiles of CIRS. RESULTS After adjusting for confounding factors, multimorbidity measured by a simple count of chronic diseases was not related to psychological distress (OR, 1.12; 95% CI, 0.97–1.29; P = .188), whereas multimorbidity measured by the CIRS remained significantly associated (OR, 1.67; 95% CI, 1.19–2.37; P = .002). The estimate risk of psychological distress by quintile of CIRS was as follows: Q1/2 = 1.0; Q3 = OR, 1.72; 95% CI, 0.53–5.86; Q4 = OR, 2.99; 95% CI, 1.01–9.74; Q5 = OR, 4.67; 95% CI, 1.61–15.16. CONCLUSIONS Psychological distress increased with multimorbidity when we accounted for disease severity. Clinicians should be aware of the possible presence of psychological distress, which can further complicate the comprehensive management of these complex patients.

Comparative assessment of three different indices of multimorbidity for studies on health-related quality of life

BackgroundMeasures 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.MethodsWe 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.ResultsThe 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.ConclusionThe 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.

Learning and Caring in Communities of Practice: Using Relationships and Collective Learning to Improve Primary Care for Patients with Multimorbidity

We introduce a primary care practice model for caring for patients with multimorbidity. Primary care for these patients requires flexibility and ongoing coordination, and it often must be tailored to individual circumstances. Such complex and flexible care could be accomplished within communities of practice, whose participants are willing to learn from their shared practice, further each other’s goals, share their stories of success and failure, and promote the continued evolution of collective learning. Primary care in these communities would be conceived as a complex adaptive process in which the participants use an iterative approach to care improvement that integrates what they learn and do collectively over time. Clinicians in these communities would define common goals, cocreate care plans, and engage in reflective case-based learning. As community members manage their knowledge, gain insights, and develop new care strategies, they can improve care for patients with multiple conditions. Using a mix of methods, future research should explore the conditions that are necessary for collective learning within communities of clinicians who care for patients with multimorbidity and who develop new knowledge in practice. By understanding these conditions, we can foster the development of collective learning and improve primary care for these patients.