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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.
Simple Summary: In patients with myeloproliferative neoplasms (MPN) and in patients with kidney dysfunction, a higher rate of thrombosis has been reported compared with the general population. Furthermore, MPN patients are more prone to develop kidney dysfunction. In our study, we assessed the importance of specific risk factors for kidney dysfunction and thrombosis in MPN patients. We found that the rate of thrombosis is correlated with the degree of kidney dysfunction, especially in myelofibrosis. Significant associations for kidney dysfunction included arterial hypertension, MPN treatment, and increased inflammation, and those for thrombosis comprised arterial hypertension, non-excessive platelet counts, and antithrombotic therapy. The identified risk factor associations varied between MPN subtypes. Our data suggest that kidney dysfunction in MPN patients is associated with an increased risk of thrombosis, mandating closer monitoring, and, possibly, early thromboprophylaxis.
Abstract: Inflammation-induced thrombosis represents a severe complication in patients with myeloproliferative neoplasms (MPN) and in those with kidney dysfunction. Overlapping disease-specific attributes suggest common mechanisms involved in MPN pathogenesis, kidney dysfunction, and thrombosis. Data from 1420 patients with essential thrombocythemia (ET, 33.7%), polycythemia vera (PV, 38.5%), and myelofibrosis (MF, 27.9%) were extracted from the bioregistry of the German Study Group for MPN. The total cohort was subdivided according to the calculated estimated glomerular filtration rate (eGFR, (mL/min/1.73 m2)) into eGFR1 (≥90, 21%), eGFR2 (60–89, 56%), and eGFR3 (<60, 22%). A total of 29% of the patients had a history of thrombosis. A higher rate of thrombosis and longer MPN duration was observed in eGFR3 than in eGFR2 and eGFR1. Kidney dysfunction occurred earlier in ET than in PV or MF. Multiple logistic regression analysis identified arterial hypertension, MPN treatment, increased uric acid, and lactate dehydrogenase levels as risk factors for kidney dysfunction in MPN patients. Risk factors for thrombosis included arterial hypertension, non-excessive platelet counts, and antithrombotic therapy. The risk factors for kidney dysfunction and thrombosis varied between MPN subtypes. Physicians should be aware of the increased risk for kidney disease in MPN patients, which warrants closer monitoring and, possibly, early thromboprophylaxis.
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.
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.
Background Multimorbidity is a highly frequent condition in older people, but well designed longitudinal studies on the impact of multimorbidity on patients and the health care system have been remarkably scarce in numbers until today. Little is known about the long term impact of multimorbidity on the patients' life expectancy, functional status and quality of life as well as health care utilization over time. As a consequence, there is little help for GPs in adjusting care for these patients, even though studies suggest that adhering to present clinical practice guidelines in the care of patients with multimorbidity may have adverse effects. Methods The study is designed as a multicentre prospective, observational cohort study of 3.050 patients aged 65 to 85 at baseline with at least three different diagnoses out of a list of 29 illnesses and syndromes. The patients will be recruited in approx. 120 to 150 GP surgeries in 8 study centres distributed across Germany. Information about the patients' morbidity will be collected mainly in GP interviews and from chart reviews. Functional status, resources/risk factors, health care utilization and additional morbidity data will be assessed in patient interviews, in which a multitude of well established standardized questionnaires and tests will be performed. Discussion The main aim of the cohort study is to monitor the course of the illness process and to analyse for which reasons medical conditions are stable, deteriorating or only temporarily present. First, clusters of combinations of diseases/disorders (multimorbidity patterns) with a comparable impact (e.g. on quality of life and/or functional status) will be identified. Then the development of these clusters over time will be analysed, especially with regard to prognostic variables and the somatic, psychological and social consequences as well as the utilization of health care resources. The results will allow the development of an instrument for prediction of the deterioration of the illness process and point at possibilities of prevention. The practical consequences of the study results for primary care will be analysed in expert focus groups in order to develop strategies for the inclusion of the aspects of multimorbidity in primary care guidelines.