https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(12)60240-2.pdf

Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study

https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(07)61415-9.pdf

Depression, chronic diseases, and decrements in health: results from the World Health Surveys

Depression, chronic diseases, and decrements in health : results from the world health surveys. Commentary

Measuring Health: A Guide to Rating Scales and Questionnaires

This presentation will set out the eScience agenda by explaining the current scientific data deluge and the case for a “Fourth Paradigm” for scientific exploration. Examples of data intensive science will be used to illustrate the explosion of data and the associated new challenges for data capture, curation, analysis, and sharing. The role of cloud computing, collaboration services, and research repositories will be discussed.

/pdf/the-fourth-paradigm-data-intensive-scientific-discovery-2j2x5xux2r.pdf

The Fourth Paradigm: Data-Intensive Scientific Discovery

PURPOSE We sought to identify and compare studies reporting the prevalence of multimorbidity and to suggest methodologic aspects to be considered in the conduct of such studies. METHODS We searched the literature for English- and French-language articles published between 1980 and September 2010 that described the prevalence of multimorbidity in the general population, in primary care, or both. We assessed quality of included studies with a modified version of the Strengthening the Reporting of Observational Studies in Epidemiology checklist. Results of individual prevalence studies were adjusted so that they could be compared graphically. RESULTS The final sample included 21 articles: 8 described studies conducted in primary care, 12 in the general population, and 1 in both. All articles were of good quality. The largest differences in prevalence of multimorbidity were observed at age 75 in both primary care (with prevalence ranging from 3.5% to 98.5% across studies) and the general population (with prevalence ranging from 13.1% to 71.8% across studies). Apart from differences in geographic settings, we identified differences in recruitment method and sample size (primary care: 980–60,857 patients; general population: 1,099–316,928 individuals), data collection, and the operational definition of multimorbidity used, including the number of diagnoses considered (primary care: 5 to all; general population: 7 to all). This last aspect seemed to be the most important factor in estimating prevalence. CONCLUSIONS Marked variation exists among studies of the prevalence of multimorbidity with respect to both methodology and findings. When undertaking such studies, investigators should carefully consider the specific diagnoses included and their number, as well as the operational definition of multimorbidity.

https://www.annfammed.org/content/annalsfm/10/2/142.full.pdf

A Systematic Review of Prevalence Studies on Multimorbidity: Toward a More Uniform Methodology

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.

Relationship between multimorbidity and health-related quality of life of patients in primary care.

PURPOSE Many randomized controlled trials (RCTs) exclude patients who have multiple comorbidities. The aim of this study was to illustrate the prevalence of comorbidities among patients followed up in primary care who would have met the inclusion criteria of selected RCTs focusing on treatment of a particular condition. We used hypertension as an example of a particular chronic condition.

METHODS We used an existing database of 980 patients (660 women) that was representative of a population consulting primary care family doctors and that contained information about all chronic conditions. We randomly selected 5 RCTs that focused on patients with hypertension. The inclusion and exclusion criteria used in each of the 5 RCTs were applied (1 study at a time) to the patients in our database. The patients from our data set who met the inclusion criteria of a given RCT were considered eligible for that RCT.

RESULTS Of the patients from our data set who were eligible for each of the RCTs, 89% to 100% had multiple chronic conditions. The mean number of chronic conditions of patients eligible for each RCT ranged from 5.5 ± 3.3 to 11.7 ± 5.3.

CONCLUSIONS Results from this study suggest that RCTs targeting a chronic medical condition such as hypertension could find that, in a sample taken from family practice, most eligible patients have comorbid conditions. Whether these patients are sampled or excluded should be reported. Research results intended to be applied in medical practice should take the complex reality of effective treatment of these patients into consideration.

https://www.annfammed.org/content/annalsfm/4/2/104.full.pdf

Randomized controlled trials: do they have external validity for patients with multiple comorbidities?

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. 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. 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. 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.

https://link.springer.com/content/pdf/10.1186%2F1472-6963-10-111.pdf

Prevalence estimates of multimorbidity: a comparative study of two sources

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.

https://www.annfammed.org/content/annalsfm/4/5/417.full.pdf

José Almirall

Papers

A Systematic Review of Prevalence Studies on Multimorbidity: Toward a More Uniform Methodology

Relationship between multimorbidity and health-related quality of life of patients in primary care.

Randomized controlled trials: do they have external validity for patients with multiple comorbidities?

Prevalence estimates of multimorbidity: a comparative study of two sources

Psychological Distress and Multimorbidity in Primary Care