22 research outputs found

    Applying systems biology to biomedical research and health care: a précising definition of systems medicine

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    Background: Systems medicine has become a key word in biomedical research. Although it is often referred to as P4-(predictive, preventive, personalized and participatory)-medicine, it still lacks a clear definition and is open to interpretation. This conceptual lack of clarity complicates the scientific and public discourse on chances, risks and limits of Systems Medicine and may lead to unfounded hopes. Against this background, our goal was to develop a sufficiently precise and widely acceptable definition of Systems Medicine. Methods: In a first step, PubMed was searched using the keyword “systems medicine”. A data extraction tabloid was developed putting forward a means/ends-division. Full-texts of articles containing Systems Medicine in title or abstract were screened for definitions. Definitions were extracted; their semantic elements were assigned as either means or ends. To reduce complexity of the resulting list, summary categories were developed inductively. In a second step, we applied six criteria for adequate definitions (necessity, non-circularity, non-redundancy, consistency, non-vagueness, and coherence) to these categories to derive a so-called prĂ©cising definition of Systems Medicine. Results: We identified 185 articles containing the term Systems Medicine in title or abstract. 67 contained at least one definition of Systems Medicine. In 98 definitions, we found 114 means and 132 ends. From these we derived the prĂ©cising definition: Systems Medicine is an approach seeking to improve medical research (i.e. the understanding of complex processes occurring in diseases, pathologies and health states as well as innovative approaches to drug discovery) and health care (i.e. prevention, prediction, diagnosis and treatment) through stratification by means of Systems Biology (i.e. data integration, modeling, experimentation and bioinformatics). Our study also revealed the visionary character of Systems Medicine. Conclusions: Our insights, on the one hand, allow for a realistic identification of actual ethical as well as legal issues arising in the context of Systems Medicine and, in consequence, for a realistic debate of questions concerning its matter and (future) handling. On the other hand, they help avoiding unfounded hopes and unrealistic expectations. This especially holds for goals like improving patient participation which are intensely debated in the context of Systems Medicine, however not implied in the concept

    Effectiveness of the Austrian disease-management-programme for type 2 diabetes: study protocol of a cluster-randomized controlled trial

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    <p>Abstract</p> <p>Background</p> <p>Due to its rising prevalence type 2 diabetes plays an important role concerning population health in Austria and other western countries. In various studies deficiencies in the care of diabetic patients have been revealed. These deficiencies may be overcome by disease-management-programmes (DMPs), but international experience shows that the effectiveness of DMPs is inconsistent. In particular large programmes designed by state-affiliated public health insurances have not been evaluated in randomized controlled trials (RCTs). We are therefore conducting a large scale RCT of the Austrian DMP for type 2 diabetic patients in the province of Salzburg to evaluate the programme regarding its effects on metabolic control, guideline adherent care and the quality of life of diabetic patients.</p> <p>Methods/Design</p> <p>The study is open for participation to all GPs and internists in the province of Salzburg. Physicians are randomized before recruitment of patients with the districts of Salzburg as clusters of randomisation. A total of over 1200 patients with type 2 diabetes will then be recruited. In the intervention group the DMP is applied for one year. Controls receive usual care. Endpoints are a decrease in HbA1c in the intervention group > 0,5% compared to controls, a higher percentage of patients with required diagnostic measures according to guidelines, improved cardiovascular risk profile and higher quality of life scores within one year.</p> <p>Current status of the study</p> <p>98 Physicians agreed to participate in the study. 96 of them recruited 1494 patients, 654 in the intervention and 840 in the control group.</p> <p>Trail Registration</p> <p>This trial has been registered with Current Controlled Trials Ltd. (ISRCTN27414162).</p

    The effectiveness of the Austrian disease management programme for type 2 diabetes: a cluster-randomised controlled trial

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    <p>Abstract</p> <p>Background</p> <p>Disease management programmes (DMPs) are costly and impose additional work load on general practitioners (GPs). Data on their effectiveness are inconclusive. We therefore conducted a cluster-randomised controlled trial to evaluate the effectiveness of the Austrian DMP for diabetes mellitus type 2 on HbA1c and quality of care for adult patients in primary care.</p> <p>Methods</p> <p>All GPs of Salzburg-province were invited to participate. After cluster-randomisation by district, all patients with diabetes type 2 were recruited consecutively from 7-11/2007. The DMP, consisting mainly of physician and patient education, standardised documentation and agreement on therapeutic goals, was implemented in the intervention group while the control group received usual care. We aimed to show superiority of the intervention regarding metabolic control and process quality. The primary outcome measure was a change in HbA1c after one year. Secondary outcomes were days in the hospital, blood pressure, lipids, body mass index (BMI), enrolment in patient education and regular guideline-adherent examination. Blinding was not possible.</p> <p>Results</p> <p>92 physicians recruited 1489 patients (649 intervention, 840 control). After 401 ± 47 days, 590 intervention-patients and 754 controls had complete data. In the intention to treat analysis (ITT) of all 1489 patients, HbA1c decreased 0.41% in the intervention group and 0.28% in controls. The difference of -0.13% (95% CI -0.24; -0.02) was significant at p = 0.026. Significance was lost in mixed models adjusted for baseline value and cluster-effects (adjusted mean difference -0.03 (95% CI -0.15; 0.09, p = 0.607). Of the secondary outcome measures, BMI and cholesterol were significantly reduced in the intervention group compared to controls in ITT after adjustments (-0.53 kg/mÂČ; 95% CI -1.03;-0.02; p = 0.014 and -0.10 mmol/l; 95% CI -0.21; -0.003; p = 0.043). Additionally, more patients received patient education (49.5% vs. 20.1%, p < 0.0001), eye- (71.0% vs. 51.2%, p < 0.0001), foot examinations (73.8% vs. 45.1%, p < 0.0001), and regular HbA1c checks (44.1% vs. 36.0%, p < 0.01) in the intervention group.</p> <p>Conclusion</p> <p>The Austrian DMP implemented by statutory health insurance improves process quality and enhances weight reduction, but does not significantly improve metabolic control for patients with type 2 diabetes mellitus. Whether the small benefit seen in secondary outcome measures leads to better patient outcomes, remains unclear.</p> <p>Trial Registration</p> <p>Current Controlled trials Ltd., ISRCTN27414162.</p

    Effectiveness of a Peer Support Programme versus Usual Care in Disease Management of Diabetes Mellitus Type 2 regarding Improvement of Metabolic Control: A Cluster-Randomised Controlled Trial

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    Aim. Testing the effectiveness of peer support additionally to a disease management programme (DMP) for type 2 diabetes patients. Methods. Unblinded cluster-randomised controlled trial (RCT) involving 49 general practices, province of Salzburg, Austria. All patients enrolled in the DMP were eligible, n=337 participated (intervention: 148 in 19 clusters; control: 189 in 20 clusters). The peer support intervention ran over 24 months and consisted of peer supporter recruitment and training, and group meetings weekly for physical exercise and monthly for discussion of diabetes related topics. Results. At two-year follow-up, adjusted analysis revealed a nonsignificant difference in HbA1c change of 0.14% (21.97 mmol/mol) in favour of the intervention (95% CI −0.08 to 0.36%, p=0.22). Baseline values were 7.02 ± 1.25% in the intervention and 7.08 ± 1.25 in the control group. None of the secondary outcome measures showed significant differences except for improved quality of life (EQ-5D-VAS) in controls (4.3 points on a scale of 100; 95% CI 0.08 to 8.53, p=0.046) compared to the intervention group. Conclusion. Our peer support intervention as an additional DMP component showed no significant effect on HbA1c and secondary outcome measures. Further RTCs with a longer follow-up are needed to reveal whether peer support will have clinically relevant effects. Trial Registration. This trial has been registered with Current Controlled Trials Ltd. (ISRCTN10291077)

    The impact of a disease management programme for type 2 diabetes on health-related quality of life:Multilevel analysis of a cluster-randomised controlled trial ISRCTN27414162 ISRCTN

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    Abstract Background Type 2 diabetes is a chronic disease associated with poorer health outcomes and decreased health related quality of life (HRQoL). The aim of this analysis was to explore the impact of a disease management programme (DMP) in type 2 diabetes on HRQoL. A multilevel model was used to explain the variation in EQ-VAS. Methods A cluster-randomized controlled trial—analysis of the secondary endpoint HRQoL. Our study population were general practitioners and patients in the province of Salzburg. The DMP “Therapie-Aktiv” was implemented in the intervention group, and controls received usual care. Outcome measure was a change in EQ-VAS after 12 months. For comparison of rates, we used Fisher’s Exact test; for continuous variables the independent T test or Welch test were used. In the multilevel modeling, we examined various models, continuously adding variables to explain the variation in the dependent variable, starting with an empty model, including only the random intercept. We analysed random effects parameters in order to disentangle variation of the final EQ-VAS. Results The EQ-VAS significantly increased within the intervention group (mean difference 2.19, p = 0.005). There was no significant difference in EQ-VAS between groups (mean difference 1.00, p = 0.339). In the intervention group the improvement was more distinct in women (2.46, p = 0.036) compared to men (1.92, p = 0.063). In multilevel modeling, sex, age, family and work circumstances, any macrovascular diabetic complication, duration of diabetes, baseline body mass index and baseline EQ-VAS significantly influence final EQ-VAS, while DMP does not. The final model explains 28.9% (EQ-VAS) of the total variance. Most of the unexplained variance was found on patient-level (95%) and less on GP-level (5%). Conclusion DMP “Therapie-Aktiv” has no significant impact on final EQ-VAS. The impact of DMPs in type 2 diabetes on HRQoL is still unclear and future programmes should focus on patient specific needs and predictors in order to improve HRQoL. Trial registration Current Controlled trials Ltd., ISRCTN2741416

    Diabetology & Metabolic Syndrome / The impact of a disease management programme for type 2 diabetes on health-related quality of life : multilevel analysis of a cluster-randomised controlled trial

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    Background: Type 2 diabetes is a chronic disease associated with poorer health outcomes and decreased health related quality of life (HRQoL). The aim of this analysis was to explore the impact of a disease management programme (DMP) in type 2 diabetes on HRQoL. A multilevel model was used to explain the variation in EQ-VAS. Methods: A cluster-randomized controlled trialanalysis of the secondary endpoint HRQoL. Our study population were general practitioners and patients in the province of Salzburg. The DMP “Therapie-Aktiv” was implemented in the intervention group, and controls received usual care. Outcome measure was a change in EQ-VAS after 12 months. For comparison of rates, we used Fishers Exact test; for continuous variables the independent T test or Welch test were used. In the multilevel modeling, we examined various models, continuously adding variables to explain the variation in the dependent variable, starting with an empty model, including only the random intercept. We analysed random effects parameters in order to disentangle variation of the final EQ-VAS. Results: The EQ-VAS significantly increased within the intervention group (mean difference 2.19, p = 0.005). There was no significant difference in EQ-VAS between groups (mean difference 1.00, p = 0.339). In the intervention group the improvement was more distinct in women (2.46, p = 0.036) compared to men (1.92, p = 0.063). In multilevel modeling, sex, age, family and work circumstances, any macrovascular diabetic complication, duration of diabetes, baseline body mass index and baseline EQ-VAS significantly influence final EQ-VAS, while DMP does not. The final model explains 28.9% (EQ-VAS) of the total variance. Most of the unexplained variance was found on patient-level (95%) and less on GP-level (5%). Conclusion: DMP “Therapie-Aktiv” has no significant impact on final EQ-VAS. The impact of DMPs in type 2 diabetes on HRQoL is still unclear and future programmes should focus on patient specific needs and predictors in order to improve HRQoL.(VLID)253289
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