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Objective: The objective of this study was to describe and analyze the effects of depression on health care utilization and costs in a sample of multimorbid elderly patients.
Method: This cross-sectional analysis used data of a prospective cohort study, consisting of 1,050 randomly selected multimorbid primary care patients aged 65 to 85 years. Depression was defined as a score of six points or more on the Geriatric Depression Scale (GDS-15). Subjects passed a geriatric assessment, including a questionnaire for health care utilization. The impact of depression on health care costs was analyzed using multiple linear regression models. A societal perspective was adopted.
Results: Prevalence of depression was 10.7%. Mean total costs per six-month period were €8,144 (95% CI: €6,199-€10,090) in patients with depression as compared to €3,137 (95% CI: €2,735-€3,538; p<0.001) in patients without depression. The positive association between depression and total costs persisted after controlling for socio-economic variables, functional status and level of multimorbidity. In particular, multiple regression analyses showed a significant positive association between depression and pharmaceutical costs.
Conclusion: Among multimorbid elderly patients, depression was associated with significantly higher health care utilization and costs. The effect of depression on costs was even greater than reported by previous studies conducted in less morbid patients.
Background: Care management programmes are an effective approach to care for high risk patients with complex care needs resulting from multiple co-occurring medical and non-medical conditions. These patients are likely to be hospitalized for a potentially "avoidable" cause. Nurse-led care management programmes for high risk elderly patients showed promising results. Care management programmes based on health care assistants (HCAs) targeting adult patients with a high risk of hospitalisation may be an innovative approach to deliver cost-efficient intensified care to patients most in need. Methods: PraCMan is a cluster randomized controlled trial with primary care practices as unit of randomisation. The study evaluates a complex primary care practice-based care management of patients at high risk for future hospitalizations. Eligible patients either suffer from type 2 diabetes mellitus, chronic obstructive pulmonary disease, chronic heart failure or any combination. Patients with a high likelihood of hospitalization within the following 12 months (based on insurance data) will be included in the trial. During 12 months of intervention patients of the care management group receive comprehensive assessment of medical and non-medical needs and resources as well as regular structured monitoring of symptoms. Assessment and monitoring will be performed by trained HCAs from the participating practices. Additionally, patients will receive written information, symptom diaries, action plans and a medication plan to improve self-management capabilities. This intervention is addition to usual care. Patients from the control group receive usual care. Primary outcome is the number of all-cause hospitalizations at 12 months follow-up, assessed by insurance claims data. Secondary outcomes are health-related quality of life (SF12, EQ5D), quality of chronic illness care (PACIC), health care utilisation and costs, medication adherence (MARS), depression status and severity (PHQ-9), self-management capabilities and clinical parameters. Data collection will be performed at baseline, 12 and 24 months (12 months post-intervention). Discussion: Practice-based care management for high risk individuals involving trained HCAs appears to be a promising approach to face the needs of an aging population with increasing care demands. Trial registration: Current Controlled Trials ISRCTN56104508
Background: Complex care management is seen as an approach to face the challenges of an ageing society with increasing numbers of patients with complex care needs. The Medical Research Council in the United Kingdom has proposed a framework for the development and evaluation of complex interventions that will be used to develop and evaluate a primary care-based complex care management program for chronically ill patients at high risk for future hospitalization in Germany. Methods and design: We present a multi-method procedure to develop a complex care management program to implement interventions aimed at reducing potentially avoidable hospitalizations for primary care patients with type 2 diabetes mellitus, chronic obstructive pulmonary disease, or chronic heart failure and a high likelihood of hospitalization. The procedure will start with reflection about underlying precipitating factors of hospitalizations and how they may be targeted by the planned intervention (pre-clinical phase). An intervention model will then be developed (phase I) based on theory, literature, and exploratory studies (phase II). Exploratory studies are planned that entail the recruitment of 200 patients from 10 general practices. Eligible patients will be identified using two ways of 'case finding': software based predictive modelling and physicians' proposal of patients based on clinical experience. The resulting subpopulations will be compared regarding healthcare utilization, care needs and resources using insurance claims data, a patient survey, and chart review. Qualitative studies with healthcare professionals and patients will be undertaken to identify potential barriers and enablers for optimal performance of the complex care management program. Discussion: This multi-method procedure will support the development of a primary care-based care management program enabling the implementation of interventions that will potentially reduce avoidable hospitalizations.
E-Learning soll im Rahmen der allgemeinmedizinischen Ausbildung von Medizinstudierenden erprobt werden. Ein zielgruppenspezifisches, multimodulares Online-Angebot begleitet Medizinstudenten des 10. Semesters während ihres dezentralen Praktikums in hausärztlichen Praxen. Folgende Lehrziele werden angestrebt: (1) Einführung in das E-Learning, (2) Klinische Allgemeinmedizin - Online-Modul, (3) Chronic Care Online-Modul, (4) Online-Bewerbung. Die systematische Evaluation zeigt, dass E-Learning die Kommunikation der Studierenden untereinander und mit der universitären Lehreinheit während des Praktikum fördert. Auf der Grundlage der in diesem Pilotversuch gewonnenen Erfahrungen erscheint die Kombination mit Präsenzunterricht (Blended Learning) eine vielversprechende Option für die allgemeinmedizinische Ausbildung zu sein.
Background: Depression is a disorder with high prevalence in primary health care and a significant burden of illness. The delivery of health care for depression, as well as other chronic illnesses, has been criticized for several reasons and new strategies to address the needs of these illnesses have been advocated. Case management is a patient-centered approach which has shown efficacy in the treatment of depression in highly organized Health Maintenance Organization (HMO) settings and which might also be effective in other, less structured settings. Methods/Design: PRoMPT (PRimary care Monitoring for depressive Patients Trial) is a cluster randomised controlled trial with General Practice (GP) as the unit of randomisation. The aim of the study is to evaluate a GP applied case-management for patients with major depressive disorder. 70 GPs were randomised either to intervention group or to control group with the control group delivering usual care. Each GP will include 10 patients suffering from major depressive disorder according to the DSM-IV criteria. The intervention group will receive treatment based on standardized guidelines and monthly telephone monitoring from a trained practice nurse. The nurse investigates the patient's status concerning the MDD criteria, his adherence to GPs prescriptions, possible side effects of medication, and treatment goal attainment. The control group receives usual care – including recommended guidelines. Main outcome measure is the cumulative score of the section depressive disorders (PHQ-9) from the German version of the Prime MD Patient Health Questionnaire (PHQ-D). Secondary outcome measures are the Beck-Depression-Inventory, self-reported adherence (adapted from Moriskey) and the SF-36. In addition, data are collected about patients' satisfaction (EUROPEP-tool), medication, health care utilization, comorbidity, suicide attempts and days out of work. The study comprises three assessment times: baseline (T0) , follow-up after 6 months (T1) and follow-up after 12 months (T2). Discussion: Depression is now recognized as a disorder with a high prevalence in primary care but with insufficient treatment response. Case management seems to be a promising intervention which has the potential to bridge the gap of the usually time-limited and fragmented provision of care. Case management has been proven to be effective in several studies but its application in the private general medical practice setting remains unclear.
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: Diabetes model projects in different regions of Germany including interventions such as quality circles, patient education and documentation of medical findings have shown improvements of HbA1c levels, blood pressure and occurrence of hypoglycaemia in before-after studies (without control group). In 2002 the German Ministry of Health defined legal regulations for the introduction of nationwide disease management programs (DMP) to improve the quality of care in chronically ill patients. In April 2003 the first DMP for patients with type 2 diabetes was accredited. The evaluation of the DMP is essential and has been made obligatory in Germany by the Fifth Book of Social Code. The aim of the study is to assess the effectiveness of DMP by example of type 2 diabetes in the primary care setting of two German federal states (Rheinland-Pfalz and Sachsen-Anhalt). Methods/Design: The study is three-armed: a prospective cluster-randomized comparison of two interventions (DMP 1 and DMP 2) against routine care without DMP as control group. In the DMP group 1 the patients are treated according to the current situation within the German-Diabetes-DMP. The DMP group 2 represents diabetic care within ideally implemented DMP providing additional interventions (e.g. quality circles, outreach visits). According to a sample size calculation a sample size of 200 GPs (each GP including 20 patients) will be required for the comparison of DMP 1 and DMP 2 considering possible drop-outs. For the comparison with routine care 4000 patients identified by diabetic tracer medication and age (> 50 years) will be analyzed. Discussion: This study will evaluate the effectiveness of the German Diabetes-DMP compared to a Diabetes-DMP providing additional interventions and routine care in the primary care setting of two different German federal states.
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.
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.