The European Cancer Patient’s Bill of Rights: Action Steps for Success

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140050/1/onco0225.pd

National Trends in Statin Use by Coronary Heart Disease Risk Category

BACKGROUND: Only limited research tracks United States trends in the use of statins recorded during outpatient visits, particularly use by patients at moderate to high cardiovascular risk. METHODS AND FINDINGS: Data collected between 1992 and 2002 in two federally administered surveys provided national estimates of statin use among ambulatory patients, stratified by coronary heart disease risk based on risk factor counting and clinical diagnoses. Statin use grew from 47% of all lipid-lowering medications in 1992 to 87% in 2002, with atorvastatin being the leading medication in 2002. Statin use by patients with hyperlipidemia, as recorded by the number of patient visits, increased significantly from 9% of patient visits in 1992 to 49% in 2000 but then declined to 36% in 2002. Absolute increases in the rate of statin use were greatest for high-risk patients, from 4% of patient visits in 1992 to 19% in 2002. Use among moderate-risk patients increased from 2% of patient visits in 1992 to 14% in 1999 but showed no continued growth subsequently. In 2002, 1 y after the release of the Adult Treatment Panel III recommendations, treatment gaps in statin use were detected for more than 50% of outpatient visits by moderate- and high-risk patients with reported hyperlipidemia. Lower statin use was independently associated with younger patient age, female gender, African American race (versus non-Hispanic white), and non-cardiologist care. CONCLUSION: Despite notable improvements in the past decade, clinical practice fails to institute recommended statin therapy during many ambulatory visits of patients at moderate-to-high cardiovascular risk. Innovative approaches are needed to promote appropriate, more aggressive statin use for eligible patients

Comparing the implementation of team approaches for improving diabetes care in community health centers

Background: Patient panel management and community-based care management may be viable strategies for community health centers to improve the quality of diabetes care for vulnerable patient populations. The objective of our study was to clarify implementation processes and experiences of integrating office-based medical assistant (MA) panel management and community health worker (CHW) community-based management into routine care for diabetic patients. Methods: Mixed methods study with interviews and surveys of clinicians and staff participating in a study comparing the effectiveness of MA and CHW health coaching for improving diabetes care. Participants included 24 key informants in five role categories and 249 clinicians and staff survey respondents from 14 participating practices. We conducted thematic analyses of key informant interview transcripts to clarify implementation processes and describe barriers to integrating the new roles into practice. We surveyed clinicians and staff to assess differences in practice culture among intervention and control groups. We triangulated findings to identify concordant and disparate results across data sources. Results: Implementation processes and experiences varied considerably among the practices implementing CHW and MA team-based approaches, resulting in differences in the organization of health coaching and self-management support activities. Importantly, CHW and MA responsibilities converged over time to focus on health coaching of diabetic patients. MA health coaches experienced difficulty in allocating dedicated time due to other MA responsibilities that often crowded out time for diabetic patient health coaching. Time constraints also limited the personal introduction of patients to health coaches by clinicians. Participants highlighted the importance of a supportive team climate and proactive leadership as important enablers for MAs and CHWs to implement their health coaching responsibilities and also promoted professional growth. Conclusion: Implementation of team-based strategies to improve diabetes care for vulnerable populations was diverse, however all practices converged in their foci on health coaching roles of CHWs and MAs. Our study suggests that a flexible approach to implementing health coaching is more important than fidelity to rigid models that do not allow for variable allocation of responsibilities across team members. Clinicians play an instrumental role in supporting health coaches to grow into their new patient care responsibilities

Factors contributing to disparities in mortality among patients with non-small-cell lung cancer

Historically, non-small-cell lung cancer (NSCLC) patients who are non-white, have low incomes, low educational attainment, and non-private insurance have worse survival. We assessed whether differences in survival were attributable to sociodemographic factors, clinical characteristics at diagnosis, or treatments received. We surveyed a multiregional cohort of patients diagnosed with NSCLC from 2003 to 2005 and followed through 2012. We used Cox proportional hazard analyses to estimate the risk of death associated with race/ethnicity, annual income, educational attainment, and insurance status, unadjusted and sequentially adjusting for sociodemographic factors, clinical characteristics, and receipt of surgery, chemotherapy, and radiotherapy. Of 3250 patients, 64% were white, 16% black, 7% Hispanic, and 7% Asian; 36% of patients had income

Factors contributing to disparities in mortality among patients with non–small‐cell lung cancer

Historically, non–small‐cell lung cancer (NSCLC) patients who are non‐white, have low incomes, low educational attainment, and non‐private insurance have worse survival. We assessed whether differences in survival were attributable to sociodemographic factors, clinical characteristics at diagnosis, or treatments received. We surveyed a multiregional cohort of patients diagnosed with NSCLC from 2003 to 2005 and followed through 2012. We used Cox proportional hazard analyses to estimate the risk of death associated with race/ethnicity, annual income, educational attainment, and insurance status, unadjusted and sequentially adjusting for sociodemographic factors, clinical characteristics, and receipt of surgery, chemotherapy, and radiotherapy. Of 3250 patients, 64% were white, 16% black, 7% Hispanic, and 7% Asian; 36% of patients had incomes <$20 000/y; 23$60 000/y, not attending college, and not having private insurance were all associated with an increased risk of mortality. Black‐white differences were not statistically significant after adjustment for sociodemographic factors, although patients with patients without a high school diploma and patients with incomes <$40 000/y continued to have an increased risk of mortality. Differences by educational attainment were not statistically significant after adjustment for clinical characteristics. Differences by income were not statistically significant after adjustment for clinical characteristics and treatments. Clinical characteristics and treatments received primarily contributed to mortality disparities by race/ethnicity and socioeconomic status in patients with NSCLC. Additional efforts are needed to assure timely diagnosis and use of effective treatment to lessen these disparities.Using data from the Cancer Care Outcomes Research and Surveillance (CanCORS) consortium, a large, multi‐regional observational study of newly diagnosed cancer patients, we documented higher unadjusted mortality for NSCLC among patients who were black, have lower income, less well‐educated, and with non‐private insurance. We used a series of Cox proportional hazards model to estimate the increased risk of death associated with sociodemographic factors, clinical characteristics, and treatments received to determine what accounted for the disparities. We found that patients’ clinical characteristics and treatments received primarily contributed to the mortality disparities that we observed in patients with NSCLC.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146607/1/cam41796.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146607/2/cam41796_am.pd

Predictors of health-related quality of life in patients with colorectal cancer

<p>Abstract</p> <p>Background</p> <p>Most studies that have identified variables associated with the health-related quality of life (HRQL) of patients with colorectal cancer have been cross-sectional or included patients with other diagnoses. The objectives of this study were to identify predictors of HRQL in patients with colorectal cancer and interpret the clinical importance of the results.</p> <p>Methods</p> <p>We conducted a population-based longitudinal study of patients identified through three regions of the California Cancer Registry. Surveys were completed by 568 patients approximately 9 and 19 months post-diagnosis. Three HRQL outcomes from the Functional Assessment of Cancer Therapy – Colorectal (FACT-C) were evaluated: social/family well-being (SWB), emotional well-being (EWB) and the Trial Outcome Index (TOI), which is a colorectal cancer-specific summary measure of physical function and well-being. Sociodemographic, cancer/health, and healthcare variables were assessed in multivariable regression models. We computed the difference in predicted HRQL scores corresponding to a large difference in a predictor variable, defined as a 1 standard deviation difference for interval variables or the difference relative to the reference category for nominal variables. The effect of an explanatory variable on HRQL was considered clinically meaningful if the predicted score difference was at least as large as the minimally important difference.</p> <p>Results</p> <p>Common predictors of better TOI, SWB and EWB were better general health and factors related to better perceived quality of cancer care. Predictor variables in addition to general health and perceived quality of care were identified only for SWB. Being married/living as married was associated with better SWB, whereas being male or of Hispanic ethnicity was associated with worse SWB. Among the sociodemographic, cancer/health, and healthcare variables evaluated, only Hispanic ethnicity had a clinically meaningful effect on an HRQL outcome.</p> <p>Conclusion</p> <p>Our findings, particularly the information on the clinical importance of predictor variables, can help clinicians identify patients who may be at risk for poor future HRQL. Potentially modifiable factors were related to perceived quality of cancer care; thus, future research should evaluate whether improving these factors improves HRQL.</p

Mortality and Readmission After Cervical Fracture from a Fall in Older Adults: Comparison with Hip Fracture Using National Medicare Data

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/115960/1/jgs13670.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/115960/2/jgs13670_am.pd

Diagnosis-based risk adjustment for Medicare capitation payments

Using 1991-92 data for a 5-percent Medicare sample, we develop, estimate, and evaluate risk-adjustment models that utilize diagnostic information from both inpatient and ambulatory claims to adjust payments for aged and disabled Medicare enrollees. Hierarchical coexisting conditions (HCC) models achieve greater explanatory power than diagnostic cost group (DCG) models by taking account of multiple coexisting medical conditions. Prospective models predict average costs of individuals with chronic conditions nearly as well as concurrent models. All models predict medical costs far more accurately than the current health maintenance organization (HMO) payment formula

Using diagnoses to describe populations and predict costs

The Diagnostic Cost Group Hierarchical Condition Category (DCG/HCC) payment models summarize the health care problems and predict the future health care costs of populations. These models use the diagnoses generated during patient encounters with the medical delivery system to infer which medical problems are present. Patient demographics and diagnostic profiles are, in turn, used to predict costs. We describe the logic, structure, coefficients and performance of DCG/HCC models, as developed and validated on three important data bases (privately insured, Medicaid, and Medicare) with more than 1 million people each

Use of disease-modifying medications for rheumatoid arthritis by race and ethnicity in the National Ambulatory Medical Care Survey

Disease-modifying anti-rheumatic drugs (DMARDs) are recommended for virtually all patients with rheumatoid arthritis (RA). We investigated the use of DMARDs in patients with RA in a nationally representative sample of visits to US physicians in the National Ambulatory Care Medical Survey (NAMCS)