In The Netherlands, Rich Interaction Among Professionals Conducting Disease Management Led To Better Chronic Care

Health Affairs (Impact Factor: 4.97). 11/2012; 31(11):2493-500. DOI: 10.1377/hlthaff.2011.1304
Source: PubMed


Disease management programs based on the Chronic Care Model are expected to improve the quality of chronic care delivery. However, evidence to date for such improvement and how it is achieved is scarce. In 2010 and again in 2011, we surveyed professionals in twenty-two primary care practices in the Netherlands that had implemented the Chronic Care Model of disease management beginning in 2009. The responses showed that, over time, chronic illness care delivery improved to advanced levels. The gains were attributed primarily to improved relational coordination-that is, raising the quality of communication and task integration among professionals from diverse disciplines who share common objectives. These findings may have implications for other disease management efforts by collaborative care teams, in that they suggest that diverse health care professionals must be strongly connected to provide effective, holistic care.

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Available from: Anna P Nieboer,
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    • "Another large health insurer contracts CVR-DMPs only for patients diagnosed with a CVD (secondary prevention) and not for individuals at risk for CVD (primary prevention). Previous studies found that there is evidence that CVR-DMPs and COPD-DMPs improve process indicators such as coordination of care and communication between caregivers [7] [8]. Whether this translates into better health outcomes for patients and less costs for the health care system needs to be investigated. "
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    ABSTRACT: Background Disease management programs (DMPs) for cardiovascular risk (CVR) and chronic obstructive pulmonary disease (COPD) are increasingly implemented in The Netherlands to improve care and patient’s health behavior. Objective The aim of this study was to provide evidence about the (cost-) effectiveness of Dutch DMPs as implemented in daily practice. Methods We compared the physical activity, smoking status, quality-adjusted life-years, and yearly costs per patient between the most and the least comprehensive DMPs in four disease categories: primary CVR prevention, secondary CVR prevention, both types of CVR prevention, and COPD (N = 1034). Propensity score matching increased comparability between DMPs. A 2-year cost-utility analysis was performed from the health care and societal perspectives. Sensitivity analysis was performed to estimate the impact of DMP development and implementation costs on cost-effectiveness. Results Patients in the most comprehensive DMPs increased their physical activity more (except for primary CVR prevention) and had higher smoking cessation rates. The incremental QALYs ranged from –0.032 to 0.038 across all diseases. From a societal perspective, the most comprehensive DMPs decreased costs in primary CVR prevention (certainty 57%), secondary CVR prevention (certainty 88%), and both types of CVR prevention (certainty 98%). Moreover, the implementation of comprehensive DMPs led to QALY gains in secondary CVR prevention (certainty 92%) and COPD (certainty 69%). Conclusions The most comprehensive DMPs for CVR and COPD have the potential to be cost saving, effective, or cost-effective compared with the least comprehensive DMPs. The challenge for Dutch stakeholders is to find the optimal mixture of interventions that is most suited for each target group.
    Value in Health 09/2015; DOI:10.1016/j.jval.2015.07.007 · 3.28 Impact Factor
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    • "This triggered many new approaches for providing continuous, integrated, pro-active and patient-centred care by a multidisciplinary team of care providers in order to improve health outcomes and reduce costs. There is evidence that these approaches improve the quality of the care as measured by process indicators like coordination of care, communication between caregivers, patient satisfaction, provider adherence to guidelines, and patient adherence to treatment recommendations [2]. However, there is debate about the impact on health outcomes and efficiency improvements, a debate complicated by large differences in study designs, outcome metrics and target populations across studies [3] as well as cultural and political barriers to evaluation [4]. "
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    ABSTRACT: Objectives The aim of the study was to investigate the changes in costs and outcomes after the implementation of various disease management programs (DMPs), to identify their potential determinants, and to compare the costs and outcomes of different DMPs. Methods We investigated the 1-year changes in costs and effects of 1,322 patients in 16 DMPs for cardiovascular risk (CVR), chronic obstructive pulmonary disease (COPD), and diabetes mellitus (DMII) in the Netherlands. We also explored the within-DMP predictors of these changes. Finally, a cost-utility analysis was performed from the healthcare and societal perspective comparing the most and the least effective DMP within each disease category. Results This study showed wide variation in development and implementation costs between DMPs (range:€16;€1,709) and highlighted the importance of economies of scale. Changes in health care utilization costs were not statistically significant. DMPs were associated with improvements in integration of CVR care (0.10 PACIC units), physical activity (+0.34 week-days) and smoking cessation (8% less smokers) in all diseases. Since an increase in physical activity and in self-efficacy were predictive of an improvement in quality-of-life, DMPs that aim to improve these are more likely to be effective. When comparing the most with the least effective DMP in a disease category, the vast majority of bootstrap replications (range:73%;97) pointed to cost savings, except for COPD (21%). QALY gains were small (range:0.003;+0.013) and surrounded by great uncertainty. Conclusions After one year we have found indications of improvements in level of integrated care for CVR patients and lifestyle indicators for all diseases, but in none of the diseases we have found indications of cost savings due to DMPs. However, it is likely that it takes more time before the improvements in care lead to reductions in complications and hospitalizations.
    Cost Effectiveness and Resource Allocation 07/2014; 12(1):17. DOI:10.1186/1478-7547-12-17 · 0.87 Impact Factor
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    • "In addition to collecting demographic data, the questionnaire incorporated the Assessment of Chronic Illness Care short version (ACIC-S) to assess the quality of chronic care delivery (Cramm & Nieboer, 2012a; Cramm, Strating, Tsiachristas, & Nieboer, 2011; Cramm et al., 2013). The ACIC-S is one of the first comprehensive tools developed for the assessment of chronic care organization across disease populations, in contrast to traditional diseasespecific tools such as glycated hemoglobin levels, productivity measures (e.g., number of patients seen), or process indicators (e.g., percentage of diabetic patients receiving foot exams). "
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    ABSTRACT: Empirical evidence on sustainability of programs that improve the quality of care delivery over time is lacking. Therefore, this study aims to identify the predictive role of short and long term improvements in quality of chronic care delivery on program sustainability. In this longitudinal study, professionals [2010 (T0): n=218, 55% response rate; 2011 (T1): n=300, 68% response rate; 2012 (T2): n=265, 63% response rate] from 22 Dutch disease-management programs completed surveys assessing quality of care and program sustainability. Our study findings indicated that quality of chronic care delivery improved significantly in the first 2 years after implementation of the disease-management programs. At T1, overall quality, self-management support, delivery system design, and integration of chronic care components, as well as health care delivery and clinical information systems and decision support, had improved. At T2, overall quality again improved significantly, as did community linkages, delivery system design, clinical information systems, decision support and integration of chronic care components, and self-management support. Multilevel regression analysis revealed that quality of chronic care delivery at T0 (p<0.001) and quality changes in the first (p<0.001) and second (p<0.01) years predicted program sustainability. In conclusion this study showed that disease-management programs based on the chronic care model improved the quality of chronic care delivery over time and that short and long term changes in the quality of chronic care delivery predicted the sustainability of the projects.
    Social Science [?] Medicine 01/2014; 101:148-54. DOI:10.1016/j.socscimed.2013.11.035 · 2.89 Impact Factor
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