Differences in demographic composition and in work, social, and functional limitations among the populations with unipolar depression and bipolar disorder: results from a nationally representative sample

<p>Abstract</p> <p>Background</p> <p>Existing literature on mood disorders suggests that the demographic distribution of bipolar disorder may differ from that of unipolar depression, and also that bipolar disorder may be especially disruptive to personal functioning. Yet, few studies have directly compared the populations with unipolar depressive and bipolar disorders, whether in terms of demographic characteristics or personal limitations. Furthermore, studies have generally examined work-related costs, without fully investigating the extensive personal limitations associated with diagnoses of specific mood disorders. The purpose of the present study is to compare, at a national level, the demographic characteristics, work productivity, and personal limitations among individuals diagnosed with bipolar disorder versus those diagnosed with unipolar depressive disorders and no mood disorder.</p> <p>Methods</p> <p>The Medical Expenditure Panel Survey 2004-2006, a nationally representative survey of the civilian, non-institutionalized U.S. population, was used to identify individuals diagnosed with bipolar disorder and unipolar depressive disorders based on ICD-9 classifications. Outcomes of interest were indirect costs, including work productivity and personal limitations.</p> <p>Results</p> <p>Compared to those with depression and no mood disorder, higher proportions of the population with bipolar disorder were poor, living alone, and not married. Also, the bipolar disorder population had higher rates of unemployment and social, cognitive, work, and household limitations than the depressed population. In multivariate models, patients with bipolar disorder or depression were more likely to be unemployed, miss work, and have social, cognitive, physical, and household limitations than those with no mood disorder. Notably, findings indicated particularly high costs for bipolar disorder, even beyond depression, with especially large differences in odds ratios for non-employment (4.6 for bipolar disorder versus 1.9 for depression, with differences varying by gender), social limitations (5.17 versus 2.85), cognitive limitations (10.78 versus 3.97), and work limitations (6.71 versus 3.19).</p> <p>Conclusion</p> <p>The bipolar disorder population is distinctly more vulnerable than the population with depressive disorder, with evidence of fewer personal resources, lower work productivity, and greater personal limitations. More systematic analysis of the availability and quality of care for patients with bipolar disorder is encouraged to identify effectively tailored treatment interventions and maximize cost containment.</p

Overwhelmed patients: a videographic analysis of how patients with type 2 diabetes and clinicians articulate and address treatment burden during clinical encounters.

OBJECTIVE: Patients with diabetes may experience high burden of treatment (BOT), including treatment-related effects and self-care demands. We examined whether patients with type 2 diabetes and their clinicians discuss BOT, the characteristics of their discussions, and their attempts to address BOT during visits. RESEARCH DESIGN AND METHODS: Two coders independently reviewed videos of 46 primary care visits obtained during a practice-based trial and identified utterances concerning BOT, classifying them by topic and by whether BOT was addressed (i.e., whether statements emerged aimed at alleviating BOT). RESULTS: Of the 46 visits, 43 (93.5%) contained BOT discussions. Both coders identified 83 discussions: 12 involving monitoring, 28 treatment administration, 19 access, and 24 treatment effects. BOT was unambiguously addressed only 30% of the time. CONCLUSIONS: BOT discussions usually arise during visits but rarely beget problem-solving efforts. These discussions represent missed opportunities for reducing treatment-related disruptions in the lives of patients with diabetes, which may affect adherence and well-being

Examining health promotion interventions for patients with chronic conditions using a novel patient-centered complexity model: protocol for a systematic review and meta-analysis.

BACKGROUND: Successful chronic care self-management requires adherence to healthy lifestyle behaviors, but many healthcare-based health promotion interventions have resulted in small and unsustainable changes in patient behavior. Patients with chronic conditions may already be overwhelmed by burdensome illnesses and treatments, and not have the capacity to respond well to the additional work required of behavior modifications. To explore this phenomenon, we will apply the cumulative complexity model (CCM), a patient-centered model of patient complexity, to a systematic review and meta-analysis of healthcare-based health behavior interventions. METHODS/DESIGN: This systematic review will include randomized trials published between 2002 and 2012 that compared healthcare-based interventions aimed at improving healthy diet and physical activity in community dwelling adult patients with chronic conditions. After extracting study and risk of bias features from each trial, we will classify the interventions according to the conceptual model. We will then use meta-analysis and subgroup analysis to test hypotheses based on the conceptual model. DISCUSSION: Healthcare providers need evidence of successful health promoting interventions for patients with chronic conditions who display common behavioral risk factors. To better understand how patients respond to interventions, we will apply the CCM, which accounts for both the capacity of patients with chronic conditions and their treatment-related workload, and posits that a balance between capacity and workload predicts successful enactment of self-care. Analysis will also include whether patients with multiple chronic conditions respond differently to interventions compared to those with single chronic conditions. The results of this review will provide insights as to how patients with chronic conditions respond to health-promoting interventions. REVIEW REGISTRATION: PROSPERO registration number: CRD42012003428

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

&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 capacity and constraints in the experience of chronic disease: a qualitative systematic review and thematic synthesis.

BACKGROUND: Life and healthcare demand work from patients, more so from patients living with multimorbidity. Patients must respond by mobilizing available abilities and resources, their so-called capacity. We sought to summarize accounts of challenges that reduce patient capacity to access or use healthcare or to enact self-care while carrying out their lives. METHODS: We conducted a systematic review and synthesis of the qualitative literature published since 2000 identifying from MEDLINE, EMBASE, Psychinfo, and CINAHL and retrieving selected abstracts for full text assessment for inclusion. After assessing their methodological rigor, we coded their results using a thematic synthesis approach. RESULTS: The 110 reports selected, when synthesized, showed that patient capacity is an accomplishment of interaction with (1) the process of rewriting their biographies and making meaningful lives in the face of chronic condition(s); (2) the mobilization of resources; (3) healthcare and self-care tasks, particularly, the cognitive, emotional, and experiential results of accomplishing these tasks despite competing priorities; (4) their social networks; and (5) their environment, particularly when they encountered kindness or empathy about their condition and a feasible treatment plan. CONCLUSION: Patient capacity is a complex and dynamic construct that exceeds "resources" alone. Additional work needs to translate this emerging theory into useful practice for which we propose a clinical mnemonic (BREWS) and the ICAN Discussion Aid

supplementary_material – Supplemental material for Changes in Quality of Life Among Enrollees in Hennepin Health: A Medicaid Expansion ACO

<p>Supplemental material, supplementary_material for Changes in Quality of Life Among Enrollees in Hennepin Health: A Medicaid Expansion ACO by Katherine D. Vickery , Nathan D. Shippee, Laura M. Guzman-Corrales, Cindy Cain, Sarah Turcotte Manser, Tom Walton, Jessica Richards and Mark Linzer in Medical Care Research and Review</p

Preventing 30-day hospital readmissions

Importance &lt;/b&gt;Reducing early (&lt;30 days) hospital readmissions is a policy priority aimed at improving health care quality. The cumulative complexity model conceptualizes patient context. It predicts that highly supportive discharge interventions will enhance patient capacity to enact burdensome self-care and avoid readmissions. Objective: To synthesize the evidence of the efficacy of interventions to reduce early hospital readmissions and identify intervention features—including their impact on treatment burden and on patients’ capacity to enact postdischarge self-care—that might explain their varying effects. Data sources:We searched PubMed, Ovid MEDLINE, Ovid EMBASE, EBSCO CINAHL, and Scopus (1990 until April 1, 2013), contacted experts, and reviewed bibliographies. Study selection: Randomized trials that assessed the effect of interventions on all-cause or unplanned readmissions within 30 days of discharge in adult patients hospitalized for a medical or surgical cause for more than 24 hours and discharged to home. Data extraction and synthesis: Reviewer pairs extracted trial characteristics and used an activity-based coding strategy to characterize the interventions; fidelity was confirmed with authors. Blinded to trial outcomes, reviewers noted the extent to which interventions placed additional work on patients after discharge or supported their capacity for self-care in accordance with the cumulative complexity model. Main outcomes and measures &lt;/b&gt;Relative risk of all-cause or unplanned readmission with or without out-of-hospital deaths at 30 days postdischarge. &lt;b&gt;Results &lt;/b&gt;In 42 trials, the tested interventions prevented early readmissions (pooled random-effects relative risk, 0.82 [95% CI, 0.73-0.91]; P &lt; .001; I2 = 31%), a finding that was consistent across patient subgroups. Trials published before 2002 reported interventions that were 1.6 times more effective than those tested later (interaction P = .01). In exploratory subgroup analyses, interventions with many components (interaction P = .001), involving more individuals in care delivery (interaction P = .05), and supporting patient capacity for self-care (interaction P = .04) were 1.4, 1.3, and 1.3 times more effective than other interventions, respectively. A post hoc regression model showed incremental value in providing comprehensive, postdischarge support to patients and caregivers.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusions and relevance &lt;/b&gt;Tested interventions are effective at reducing readmissions, but more effective interventions are complex and support patient capacity for self-care. Interventions tested more recently are less effective

Implementation of an Anticoagulation Practice Guideline for COVID-19 via a Clinical Decision Support System in a Large Academic Health System and Its Evaluation: Observational Study

BackgroundStudies evaluating strategies for the rapid development, implementation, and evaluation of clinical decision support (CDS) systems supporting guidelines for diseases with a poor knowledge base, such as COVID-19, are limited. ObjectiveWe developed an anticoagulation clinical practice guideline (CPG) for COVID-19, which was delivered and scaled via CDS across a 12-hospital Midwest health care system. This study represents a preplanned 6-month postimplementation evaluation guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework. MethodsThe implementation outcomes evaluated were reach, adoption, implementation, and maintenance. To evaluate effectiveness, the association of CPG adherence on hospital admission with clinical outcomes was assessed via multivariable logistic regression and nearest neighbor propensity score matching. A time-to-event analysis was conducted. Sensitivity analyses were also conducted to evaluate the competing risk of death prior to intensive care unit (ICU) admission. The models were risk adjusted to account for age, gender, race/ethnicity, non-English speaking status, area deprivation index, month of admission, remdesivir treatment, tocilizumab treatment, steroid treatment, BMI, Elixhauser comorbidity index, oxygen saturation/fraction of inspired oxygen ratio, systolic blood pressure, respiratory rate, treating hospital, and source of admission. A preplanned subgroup analysis was also conducted in patients who had laboratory values (D-dimer, C-reactive protein, creatinine, and absolute neutrophil to absolute lymphocyte ratio) present. The primary effectiveness endpoint was the need for ICU admission within 48 hours of hospital admission. ResultsA total of 2503 patients were included in this study. CDS reach approached 95% during implementation. Adherence achieved a peak of 72% during implementation. Variation was noted in adoption across sites and nursing units. Adoption was the highest at hospitals that were specifically transformed to only provide care to patients with COVID-19 (COVID-19 cohorted hospitals; 74%-82%) and the lowest in academic settings (47%-55%). CPG delivery via the CDS system was associated with improved adherence (odds ratio [OR] 1.43, 95% CI 1.2-1.7; P<.001). Adherence with the anticoagulation CPG was associated with a significant reduction in the need for ICU admission within 48 hours (OR 0.39, 95% CI 0.30-0.51; P<.001) on multivariable logistic regression analysis. Similar findings were noted following 1:1 propensity score matching for patients who received adherent versus nonadherent care (21.5% vs 34.3% incidence of ICU admission within 48 hours; log-rank test P<.001). ConclusionsOur institutional experience demonstrated that adherence with the institutional CPG delivered via the CDS system resulted in improved clinical outcomes for patients with COVID-19. CDS systems are an effective means to rapidly scale a CPG across a heterogeneous health care system. Further research is needed to investigate factors associated with adherence at low and high adopting sites and nursing units