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Background: The elderly population deals with multimorbidity (three chronic conditions) and increasinged drug use with age. A comprehensive characterisation of the medication – including prescription and over-the-counter (OTC) drugs – of elderly patients in primary care is still insufficient.
Objectives: This study aims to characterise the medication (prescription and OTC) of multimorbid elderly patients in primary care and living at home by identifying drug patterns to evaluate the relationship between drugs and drug groups and reveal associations with recently published multimorbidity clusters of the same cohort.
Methods: MultiCare was a multicentre, prospective, observational cohort study of 3189 multimorbid patients aged 65 to 85 years in primary care in Germany. Patients and general practitioners were interviewed between 2008 and 2009. Drug patterns were identified using exploratory factor analysis. The relations between the drug patterns with the three multimorbidity clusters were analysed with Spearman-Rank-Correlation.
Results: Patients (59.3% female) used in mean 7.7 drugs; in total 24,535 drugs (23.7% OTC) were detected. Five drug patterns for men (drugs for obstructive pulmonary diseases (D-OPD), drugs for coronary heart diseases and hypertension (D-CHD), drugs for osteoporosis (D-Osteo), drugs for heart failure and drugs for pain) and four drug patterns for women (D-Osteo, D-CHD, D-OPD and drugs for diuretics and gout) were detected. Significant associations between multimorbidity clusters and drug patterns were detectable (D-CHD and CMD: male: ρ = 0.376, CI 0.322–0.430; female: ρ = 0.301, CI 0.624–0.340).
Conclusion: The drug patterns demonstrate non-random relations in drug use in multimorbid elderly patients and systematic associations between drug patterns and multimorbidity clusters were found in primary care.
Objectives The aims of our study were to examine the anticholinergic drug use and to assess the association between anticholinergic burden and cognitive function in the multimorbid elderly patients of the MultiCare cohort.
Setting MultiCare was conducted as a longitudinal cohort study in primary care, located in eight different study centres in Germany.
Participants 3189 patients (59.3% female).
Primary and secondary outcome measures Baseline data were used for the following analyses. Drugs were classified according to the well-established anticholinergic drug scale (ADS) and the recently published German anticholinergic burden (German ACB). Cognitive function was measured using a letter digit substitution test (LDST) and a mixed-effect multivariate linear regression was performed to calculate the influence of anticholinergic burden on the cognitive function.
Results Patients used 1764 anticholinergic drugs according to ADS and 2750 anticholinergics according to the German ACB score (prevalence 38.4% and 53.7%, respectively). The mean ADS score was 0.8 (±1.3), and the mean German ACB score was 1.2 (±1.6) per patient. The most common ADS anticholinergic was furosemide (5.8%) and the most common ACB anticholinergic was metformin (13.7%). The majority of the identified anticholinergics were drugs with low anticholinergic potential: 80.2% (ADS) and 73.4% (ACB), respectively. An increasing ADS and German ACB score was associated with reduced cognitive function according to the LDST (−0.26; p=0.008 and −0.24; p=0.003, respectively).
Conclusion Multimorbid elderly patients are in a high risk for using anticholinergic drugs according to ADS and German ACB score. We especially need to gain greater awareness for the contribution of drugs with low anticholinergic potential from the cardiovascular system. As anticholinergic drug use is associated with reduced cognitive function in multimorbid elderly patients, the importance of rational prescribing and also deprescribing needs to be further evaluated.
Trial registration number ISRCTN89818205.
Purpose: Collaborative care is effective in improving symptoms of patients with depression. The aims of this study were to characterize symptom trajectories in patients with major depression during one year of collaborative care and to explore associations between baseline characteristics and symptom trajectories.
Methods: We conducted a cluster-randomized controlled trial in primary care. The collaborative care intervention comprised case management and behavioral activation. We used the Patient Health Questionnaire-9 (PHQ-9) to assess symptom severity as the primary outcome. Statistical analyses comprised latent growth mixture modeling and a hierarchical binary logistic regression model.
Results: We included 74 practices and 626 patients (310 intervention and 316 control recipients) at baseline. Based on a minimum of 12 measurement points for each intervention recipient, we identified two latent trajectories, which we labeled "fast improvers" (60.5%) and "slow improvers" (39.5%). At all measurements after baseline, "fast improvers" presented higher PHQ mean values than "slow improvers". At baseline, "fast improvers" presented fewer physical conditions, higher health-related quality of life, and had made fewer suicide attempts in their history.
Conclusions: A notable proportion of 39.5% of patients improved only "slowly" and probably needed more intense treatment. The third follow-up in month two could well be a sensible time to adjust treatment to support "slow improvers".
Introduction: In this article three research questions are addressed: (1) Is there an association between socioeconomic status (SES) and patient-reported outcomes in a cohort of multimorbid patients? (2) Does the association vary according to SES indicator used (income, education, occupational position)? (3) Can the association between SES and patient-reported outcomes (self-rated health, health-related quality of life and functional status) be (partly) explained by burden of disease?
Methods: Analyses are based on the MultiCare Cohort Study, a German multicentre, prospective, observational cohort study of multimorbid patients from general practice. We analysed baseline data and data from the first follow-up after 15 months (N = 2,729). To assess burden of disease we used the patients’ morbidity data from standardized general practitioner (GP) interviews based on a list of 46 groups of chronic conditions including the GP’s severity rating of each chronic condition ranging from marginal to very severe.
Results: In the cross-sectional analyses SES was significantly associated with the patient-reported outcomes at baseline. Associations with income were more consistent and stronger than with education and occupational position. Associations were partly explained (17% to 44%) by burden of disease. In the longitudinal analyses only income (but not education and occupational position) was significantly related to the patient-reported outcomes at follow-up. Associations between income and the outcomes were reduced by 18% to 27% after adjustment for burden of disease.
Conclusions: Results indicate social inequalities in self-rated health, functional status and health related quality of life among older multimorbid patients. As associations with education and occupational position were inconsistent, these inequalities were mainly due to income. Inequalities were partly explained by burden of disease. However, even among patients with a similar disease burden, those with a low income were worse off in terms of the three patient-reported outcomes under study.
Background. Depression is the most common type of mental disorder in Germany. It is associated with a high level of suffering for individuals and imposes a significant burden on society. The aim of this study was to estimate the depression related costs in Germany taking a societal perspective.
Materials and Methods. Data were collected from the primary care monitoring for depressive patients trial (PRoMPT) of patients with major depressive disorder who were treated in a primary care setting. Resource utilisation and days of sick leave were observed and analysed over a 1-year period.
Results. Average depression related costs of €3813 were calculated. Significant differences in total costs due to sex were demonstrated. Male patients had considerable higher total costs than female patients, whereas single cost categories did not differ significantly. Further, differences in costs according to severity of disease and age were observed. The economic burden to society was estimated at €15.6 billion per year.
Conclusion. The study results show that depression poses a significant economic burden to society. There is a high potential for prevention, treatment, and patient management innovations to identify and treat patients at an early stage.
Multimorbidity is a health issue mostly dealt with in primary care practice. As a result of their generalist and patient-centered approach, long-lasting relationships with patients, and responsibility for continuity and coordination of care, family physicians are particularly well placed to manage patients with multimorbidity. However, conflicts arising from the application of multiple disease oriented guidelines and the burden of diseases and treatments often make consultations challenging. To provide orientation in decision making in multimorbidity during primary care consultations, we developed guiding principles and named them after the Greek mythological figure Ariadne. For this purpose, we convened a two-day expert workshop accompanied by an international symposium in October 2012 in Frankfurt, Germany. Against the background of the current state of knowledge presented and discussed at the symposium, 19 experts from North America, Europe, and Australia identified the key issues of concern in the management of multimorbidity in primary care in panel and small group sessions and agreed upon making use of formal and informal consensus methods. The proposed preliminary principles were refined during a multistage feedback process and discussed using a case example. The sharing of realistic treatment goals by physicians and patients is at the core of the Ariadne principles. These result from i) a thorough interaction assessment of the patient’s conditions, treatments, constitution, and context; ii) the prioritization of health problems that take into account the patient's preferences – his or her most and least desired outcomes; and iii) individualized management realizes the best options of care in diagnostics, treatment, and prevention to achieve the goals. Goal attainment is followed-up in accordance with a re-assessment in planned visits. The occurrence of new or changed conditions, such as an increase in severity, or a changed context may trigger the (re-)start of the process. Further work is needed on the implementation of the formulated principles, but they were recognized and appreciated as important by family physicians and primary care researchers.
Background: In primary care, patients with multiple chronic conditions are the rule rather than the exception. The Chronic Care Model (CCM) is an evidence-based framework for improving chronic illness care, but little is known about the extent to which it has been implemented in routine primary care. The aim of this study was to describe how multimorbid older patients assess the routine chronic care they receive in primary care practices in Germany, and to explore the extent to which factors at both the practice and patient level determine their views.
Methods: This cross-sectional study used baseline data from an observational cohort study involving 158 general practitioners (GP) and 3189 multimorbid patients. Standardized questionnaires were employed to collect data, and the Patient Assessment of Chronic Illness Care (PACIC) questionnaire used to assess the quality of care received. Multilevel hierarchical modeling was used to identify any existing association between the dependent variable, PACIC, and independent variables at the patient level (socio-economic factors, weighted count of chronic conditions, instrumental activities of daily living, health-related quality of life, graded chronic pain, no. of contacts with GP, existence of a disease management program (DMP) disease, self-efficacy, and social support) and the practice level (age and sex of GP, years in current practice, size and type of practice).
Results: The overall mean PACIC score was 2.4 (SD 0.8), with the mean subscale scores ranging from 2.0 (SD 1.0, subscale goal setting/tailoring) to 3.5 (SD 0.7, delivery system design). At the patient level, higher PACIC scores were associated with a DMP disease, more frequent GP contacts, higher social support, and higher autonomy of past occupation. At the practice level, solo practices were associated with higher PACIC values than other types of practice.
Conclusions: This study shows that from the perspective of multimorbid patients receiving care in German primary care practices, the implementation of structured care and counseling could be improved, particularly by helping patients set specific goals, coordinating care, and arranging follow-up contacts. Studies evaluating chronic care should take into consideration that a patient’s assessment is associated not only with practice-level factors, but also with individual, patient-level factors.
Background: It is not well established how psychosocial factors like social support and depression affect health-related quality of life in multimorbid and elderly patients. We investigated whether depressive mood mediates the influence of social support on health-related quality of life.
Methods: Cross-sectional data of 3,189 multimorbid patients from the baseline assessment of the German MultiCare cohort study were used. Mediation was tested using the approach described by Baron and Kenny based on multiple linear regression, and controlling for socioeconomic variables and burden of multimorbidity.
Results: Mediation analyses confirmed that depressive mood mediates the influence of social support on health-related quality of life (Sobel's p < 0.001). Multiple linear regression showed that the influence of depressive mood (beta = -0.341, p < 0.01) on health-related quality of life is greater than the influence of multimorbidity (beta = -0.234, p < 0.01).
Conclusion: Social support influences health-related quality of life, but this association is strongly mediated by depressive mood. Depression should be taken into consideration in research on multimorbidity, and clinicians should be aware of its importance when caring for multimorbid patients.
Obesity and associated lifestyle in a large sample of multi-morbid German primary care attendees
(2014)
Background: Obesity and the accompanying increased morbidity and mortality risk is highly prevalent among older adults. As obese elderly might benefit from intentional weight reduction, it is necessary to determine associated and potentially modifiable factors on senior obesity. This cross-sectional study focuses on multi-morbid patients which make up the majority in primary care. It reports on the prevalence of senior obesity and its associations with lifestyle behaviors.
Methods: A total of 3,189 non-demented, multi-morbid participants aged 65–85 years were recruited in primary care within the German MultiCare-study. Physical activity, smoking, alcohol consumption and quantity and quality of nutritional intake were classified as relevant lifestyle factors. Body Mass Index (BMI, general obesity) and waist circumference (WC, abdominal obesity) were used as outcome measures and regression analyses were conducted.
Results: About one third of all patients were classified as obese according to BMI. The prevalence of abdominal obesity was 73.5%. Adjusted for socio-demographic variables and objective and subjective disease burden, participants with low physical activity had a 1.6 kg/m2 higher BMI as well as a higher WC (4.9 cm, p<0.001). Current smoking and high alcohol consumption were associated with a lower BMI and WC. In multivariate logistic regression, using elevated WC and BMI as categorical outcomes, the same pattern in lifestyle factors was observed. Only for WC, not current but former smoking was associated with a higher probability for elevated WC. Dietary intake in quantity and quality was not associated with BMI or WC in either model.
Conclusions: Further research is needed to clarify if the huge prevalence discrepancy between BMI and WC also reflects a difference in obesity-related morbidity and mortality. Yet, age-specific thresholds for the BMI are needed likewise. Encouraging and promoting physical activity in older adults might a starting point for weight reduction efforts.
Background: Multimorbidity is a common phenomenon in primary care. Until now, no clinical guidelines for multimorbidity exist. For the development of these guidelines, it is necessary to know whether or not patients are aware of their diseases and to what extent they agree with their doctor. The objectives of this paper are to analyze the agreement of self-reported and general practitioner-reported chronic conditions among multimorbid patients in primary care, and to discover which patient characteristics are associated with positive agreement.
Methods: The MultiCare Cohort Study is a multicenter, prospective, observational cohort study of 3,189 multimorbid patients, ages 65 to 85. Data was collected in personal interviews with patients and GPs. The prevalence proportions for 32 diagnosis groups, kappa coefficients and proportions of specific agreement were calculated in order to examine the agreement of patient self-reported and general practitioner-reported chronic conditions. Logistic regression models were calculated to analyze which patient characteristics can be associated with positive agreement.
Results: We identified four chronic conditions with good agreement (e.g. diabetes mellitus κ = 0.80;PA = 0,87), seven with moderate agreement (e.g. cerebral ischemia/chronic stroke κ = 0.55;PA = 0.60), seventeen with fair agreement (e.g. cardiac insufficiency κ = 0.24;PA = 0.36) and four with poor agreement (e.g. gynecological problems κ = 0.05;PA = 0.10).Factors associated with positive agreement concerning different chronic diseases were sex, age, education, income, disease count, depression, EQ VAS score and nursing care dependency. For example: Women had higher odds ratios for positive agreement with their GP regarding osteoporosis (OR = 7.16). The odds ratios for positive agreement increase with increasing multimorbidity in almost all of the observed chronic conditions (OR = 1.22-2.41).
Conclusions: For multimorbidity research, the knowledge of diseases with high disagreement levels between the patients' perceived illnesses and their physicians' reports is important. The analysis shows that different patient characteristics have an impact on the agreement. Findings from this study should be included in the development of clinical guidelines for multimorbidity aiming to optimize health care. Further research is needed to identify more reasons for disagreement and their consequences in health care.