166 research outputs found

    QL3: DIABETIC PATIENTS'WILLINGNESS TO PAY FOR DIABETES EDUCATION BY PHARMACISTS: VALIDITY OF CONTINGENT VALUATION METHOD

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    Multiple uncontrolled conditions and blood pressure medication intensification: an observational study

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    Abstract Background Multiple uncontrolled medical conditions may act as competing demands for clinical decision making. We hypothesized that multiple uncontrolled cardiovascular risk factors would decrease blood pressure (BP) medication intensification among uncontrolled hypertensive patients. Methods We observed 946 encounters at two VA primary care clinics from May through August 2006. After each encounter, clinicians recorded BP medication intensification (BP medication was added or titrated). Demographic, clinical, and laboratory information were collected from the medical record. We examined BP medication intensification by presence and control of diabetes and/or hyperlipidemia. 'Uncontrolled' was defined as hemoglobin A1c ≥ for diabetes, BP ≥ 140/90 mmHg (≥ 130/80 mmHg if diabetes present) for hypertension, and low density lipoprotein cholesterol (LDL-c) ≥ 130 mg/dl (≥ 100 mg/dl if diabetes present) for hyperlipidemia. Hierarchical regression models accounted for patient clustering and adjusted medication intensification for age, systolic BP, and number of medications. Results Among 387 patients with uncontrolled hypertension, 51.4% had diabetes (25.3% were uncontrolled) and 73.4% had hyperlipidemia (22.7% were uncontrolled). The BP medication intensification rate was 34.9% overall, but higher in individuals with uncontrolled diabetes and uncontrolled hyperlipidemia: 52.8% overall and 70.6% if systolic BP ≥ 10 mmHg above goal. Intensification rates were lowest if diabetes or hyperlipidemia were controlled, lower than if diabetes or hyperlipidemia were not present. Multivariable adjustment yielded similar results. Conclusions The presence of uncontrolled diabetes and hyperlipidemia was associated with more guideline-concordant hypertension care, particularly if BP was far from goal. Efforts to understand and improve BP medication intensification in patients with controlled diabetes and/or hyperlipidemia are warranted.http://deepblue.lib.umich.edu/bitstream/2027.42/78266/1/1748-5908-5-55.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78266/2/1748-5908-5-55.pdfPeer Reviewe

    Associations Between Very Low Concentrations of LDL-Cholesterol, hs-CRP and Health Outcomes in the Reasons for Geographical and Racial Differences in Stroke (REGARDS) Study

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    Introduction: Recent findings have demonstrated the important contribution of inflammation to the risk of cardiovascular disease (CVD) in individuals with optimally managed low density lipoprotein cholesterol (LDL-C). We explored relationships between LDL-C, high sensitivity C-reactive protein (hsCRP) and clinical outcomes in a free-living US population. Methods: We used data from the REasons for Geographical And Racial Differences in Stroke (REGARDS), and selected individuals at “high risk” for coronary events with a Framingham Coronary Risk Score of >10% or atherosclerotic cardiovascular disease (ASCVD) risk >7.5% in order to explore relationships between low LDL-C (70 mg/dl [1.8 mmol/L]); hs-CRP <2 compared to ≥2 mg/L and clinical outcomes (all-cause mortality, incident coronary heart disease [CHD] and incident stroke). To assess the association between the LDL-C and hs-CRP categories and each outcome, a series of incremental Cox proportional hazards models were employed on complete cases. To account for missing observations, the most adjusted model was used to interrogate the data using multiple imputation with chained equations (MICE). Results: In this analysis, 6136 REGARDS high risk participants were included. In the MICE analysis, participants with high LDL-C (>70 mg/dl) and low hs-CRP (<2 mg/L) had a lower risk of incident stroke (hazard ratio [HR] 0.69, 0.47-0.997) incident CHD (HR 0.71, 0.53- 0.95) and CHD death (HR 0.70, 0.50-0.99) than those in the same LDL-C category high hs- CRP (≥2 mg/L). In participants with high hsCRP (≥2 mg/dL), low LDL-C (<70 mg/dL [1.8 mmol/L]) was not associated with additional risk reduction of any investigated outcome, but with the significant increase of all-cause mortality (HR 1.37, 1.07-1.74). Conclusions: In this high-risk population, we found that low hsCRP (<2mg/L) appeared to be associated with reduced risk of incident stroke, incident CHD and CHD death, whereas low LDL-C (<70 mg/dL) was not associated with protective effects. Thus, our results support other data with respect to the importance of inflammatory processes in the pathogenesis of CVD

    Patient complexity in quality comparisons for glycemic control: An observational study

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    <p>Abstract</p> <p>Background</p> <p>Patient complexity is not incorporated into quality of care comparisons for glycemic control. We developed a method to adjust hemoglobin A1c levels for patient characteristics that reflect complexity, and examined the effect of using adjusted A1c values on quality comparisons.</p> <p>Methods</p> <p>This cross-sectional observational study used 1999 national VA (US Department of Veterans Affairs) pharmacy, inpatient and outpatient utilization, and laboratory data on diabetic veterans. We adjusted individual A1c levels for available domains of complexity: age, social support (marital status), comorbid illnesses, and severity of disease (insulin use). We used adjusted A1c values to generate VA medical center level performance measures, and compared medical center ranks using adjusted versus unadjusted A1c levels across several thresholds of A1c (8.0%, 8.5%, 9.0%, and 9.5%).</p> <p>Results</p> <p>The adjustment model had R<sup>2 </sup>= 8.3% with stable parameter estimates on thirty random 50% resamples. Adjustment for patient complexity resulted in the greatest rank differences in the best and worst performing deciles, with similar patterns across all tested thresholds.</p> <p>Conclusion</p> <p>Adjustment for complexity resulted in large differences in identified best and worst performers at all tested thresholds. Current performance measures of glycemic control may not be reliably identifying quality problems, and tying reimbursements to such measures may compromise the care of complex patients.</p

    Rethinking the patient: using Burden of Treatment Theory to understand the changing dynamics of illness

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    &lt;b&gt;Background&lt;/b&gt; In this article we outline Burden of Treatment Theory, a new model of the relationship between sick people, their social networks, and healthcare services. Health services face the challenge of growing populations with long-term and life-limiting conditions, they have responded to this by delegating to sick people and their networks routine work aimed at managing symptoms, and at retarding - and sometimes preventing - disease progression. This is the new proactive work of patient-hood for which patients are increasingly accountable: founded on ideas about self-care, self-empowerment, and self-actualization, and on new technologies and treatment modalities which can be shifted from the clinic into the community. These place new demands on sick people, which they may experience as burdens of treatment.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Discussion&lt;/b&gt; As the burdens accumulate some patients are overwhelmed, and the consequences are likely to be poor healthcare outcomes for individual patients, increasing strain on caregivers, and rising demand and costs of healthcare services. In the face of these challenges we need to better understand the resources that patients draw upon as they respond to the demands of both burdens of illness and burdens of treatment, and the ways that resources interact with healthcare utilization.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Summary&lt;/b&gt; Burden of Treatment Theory is oriented to understanding how capacity for action interacts with the work that stems from healthcare. Burden of Treatment Theory is a structural model that focuses on the work that patients and their networks do. It thus helps us understand variations in healthcare utilization and adherence in different healthcare settings and clinical contexts

    Patient Complexity: More Than Comorbidity. The Vector Model of Complexity

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    BACKGROUND: The conceptualization of patient complexity is just beginning in clinical medicine. OBJECTIVES: This study aims (1) to propose a conceptual approach to complex patients; (2) to demonstrate how this approach promotes achieving congruence between patient and provider, a critical step in the development of maximally effective treatment plans; and (3) to examine availability of evidence to guide trade-off decisions and assess healthcare quality for complex patients. METHODS/RESULTS: The Vector Model of Complexity portrays interactions between biological, socioeconomic, cultural, environmental and behavioral forces as health determinants. These forces are not easily discerned but exert profound influences on processes and outcomes of care for chronic medical conditions. Achieving congruence between patient, physician, and healthcare system is essential for effective, patient-centered care; requires assessment of all axes of the Vector Model; and, frequently, requires trade-off decisions to develop a tailored treatment plan. Most evidence-based guidelines rarely provide guidance for trade-off decisions. Quality measures often exclude complex patients and are not designed explicitly to assess their overall healthcare. CONCLUSIONS/RECOMMENDATIONS: We urgently need to expand the evidence base to inform the care of complex patients of all kinds, especially for the clinical trade-off decisions that are central to tailoring care. We offer long- and short-term strategies to begin to incorporate complexity into quality measurement and performance profiling, guided by the Vector Model. Interdisciplinary research should lay the foundation for a deeper understanding of the multiple sources of patient complexity and their interactions, and how provision of healthcare should be harmonized with complexity to optimize health

    Reasons of general practitioners for not prescribing lipid-lowering medication to patients with diabetes: a qualitative study

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    Background: Lipid-lowering medication remains underused, even in high-risk populations. The objective of this study was to determine factors underlying general practitioners' decisions not to prescribe such drugs to patients with type 2 diabetes. Methods: A qualitative study with semi-structured interviews using real cases was conducted to explore reasons for not prescribing lipid-lowering medication after a guideline was distributed that recommended the use of statins in most patients with type 2 diabetes. Seven interviews were conducted with general practitioners (GPs) in The Netherlands, and analysed using an analytic inductive approach. Results: Reasons for not-prescribing could be divided into patient and physician-attributed factors. According to the GPs, some patients do not follow-up on agreed medication and others object to taking lipid-lowering medication, partly for legitimate reasons such as expected or perceived side effects. Furthermore, the GPs themselves perceived reservations for prescribing lipid-lowering medication in patients with short life expectancy, expected compliance problems or near goal lipid levels. GPs sometimes postponed the start of treatment because of other priorities. Finally, barriers were seen in the GPs' practice organisation, and at the primary-secondary care interface. Conclusion: Some of the barriers mentioned by GPs seem to be valid reasons, showing that guideline non-adherence can be quite rational. On the other hand, treatment quality could improve by addressing issues, such as lack of knowledge or motivation of both the patient and the GP. More structured management in general practice may also lead to better treatment

    Associations between cardiovascular disease, cancer and very low HDL cholesterol in the REasons for Geographical And Racial Differences in Stroke (REGARDS) study.

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    AIMS: Relatively little is known about the health outcomes associated with very low plasma concentrations of high density lipoprotein cholesterol (HDL-C) mainly because of the small numbers of individuals with such extreme values included in clinical trials. We therefore investigated the association between low and very low HDL-C concentration at baseline and incident all-cause-mortality, death from malignant disease (i.e. cancer), and with fatal or non-fatal incident coronary heart disease (CHD) in individuals from the Reasons for Geographical And Racial Differences in Stroke (REGARDS) study. METHODS AND RESULTS: Analysis was based on 21,751 participants from the REGARDS study who were free of CHD, other cardiovascular disease and cancer at baseline and were categorized by baseline HDL-C into <30 mg/dL (very low), 30 -<40 mg/dL (low), and ≥40 mg/dL (reference). A series of incremental Cox proportional hazards models were employed to assess the association between the HDL-C categories and outcomes. Statistical analysis was performed using both complete case methods and multiple imputations with chained equations. After adjustment for age, race and sex, the hazard ratios (HRs) comparing the lowest and highest HDL-C categories were 1.48 (95% confidence interval [CI]: 1.28, 1.73) for all-cause mortality, 1.35 (95%Cl: 1.03, 1.77) for cancer-specific mortality and 1.39 (95%Cl: 0.99, 1.96) for incident CHD. These associations became non-significant in models adjusting for demographics, cardiovascular risk factors and treatment for dyslipidemia. We found evidence for an ‘HDL paradox’ whereby low HDL (30-<40 mg/dL) was associated with reduced risk of incident CHD in black participants in a fully-adjusted complete case model (HR 0.63; 95%CI: 0.46, 0.88) and after multiple imputation analyses (HR 0.76; 95%CI 0.58, 0.98). HDL-C (<30 mg/dL) was significantly associated with poorer outcomes in women for all outcomes, especially with respect to cancer mortality (HR 2.31; 95%Cl: 1.28, 4.16) in a fully-adjusted complete case model, replicated using multiple imputation (HR 1.81; 95%CI 1.03, 3.20). CONCLUSIONS: Low HDL-C was associated with reduced risk of incident CHD in black participants suggesting a potential HDL paradox for incident CHD. Very low HDL-C in women was significantly associated with cancer mortality in a fully-adjusted complete case model
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