Victor G. Villagra

Strategies to control costs and quality: a focus on outcomes research for disease management.

Rapid adoption of disease management has outpaced systematic evaluation of its net value in improving health outcomes and mitigating healthcare cost. This article identifies areas in which outcomes research in disease management is needed to demonstrate its value or to enhance its performance. Patient identification for disease management relies on administrative database queries but the trade-offs in sensitivity, specificity, and predictive value of alternative queries are not well known. Large-scale deployment, rapid patient engagement, and repeated interactions between patients and nurses could be important attributes for attaining measurable improvements in quality and cost reduction over short periods of time, but these hypothesis need to be tested. There is a trend toward integration of multiple chronic disease management programs onto a single platform. To support this trend, there is a need for a corresponding set of integrated clinical guidelines or “meta-guidelines” that combine the contents of individual practice guidelines. The relative contribution of various disease management interventions in improving clinical results, lowering costs, and their respective ease of implementation is not known. Research leading to a better understanding of tradeoffs could lead to more rational resource allocation and better overall outcomes. Coordination between disease management programs and physician practices is lacking. Research aimed at defining operational and technical interfaces and cultural and behavioral professional adjustments necessary to achieve integration and coordination is needed. The lack of a consistent analytical framework for evaluating clinical and financial outcomes has made comparisons of reported results impossible and has rendered many reports unreliable. Theoretical work on a standard methodology that integrates clinical and financial outcomes and empiric validation is needed.

The paired t-test as a simple latent change score model.

The t-test is a common statistical test of differences in means. Despite the fact that its extension, the paired t-test (t-testP), appears in most introductory statistics textbooks, it is less known that for repeated variables the t-testP is in fact a model of change that can be replicated within the Structural Equation Modeling (SEM) framework. We show how to perform the t-testP with latent change scores (LCS) models, which allow for direct testing of significance of mean changes, and moreover can explain inter-individual (and group) differences in changes over time.

The health care and productivity costs of back and neck pain in a multi-employer sample of utility industry employees.

Objective: To determine the cost of back and/or neck (B/N) pain among predominantly rural employees insured through an employee benefits trust. Methods: Eligible employees had 1 year or more of medical coverage and completed a survey subsequently linked to their claims data. B/N pain costs consisted of medical and pharmacy claims, over-the-counter expenses, and presenteeism and absenteeism costs valued according to median occupational earnings. Results: Of 1342 eligible employees, 52.7% currently had B/N pain of which 87.9% was chronic. The average annualized cost of B/N pain per employee was

An Obesity/Cardiometabolic Risk Reduction Disease Management Program : A Population-Based Approach

1727; 56.1% was due to lost productivity. Covered medical care was utilized by 35.6% of employees, 55.7% used pharmacy care, and 71.6% purchased uncovered over-the-counter pain medication. Conclusions: Many covered employees did not use formal care. The effect of care choices on productivity costs requires closer scrutiny.

Impact of the elimination of cost sharing for mammographic breast cancer screening among rural US women: A natural experiment

Obesity is a critical health concern that has captured the attention of public and private healthcare payers who are interested in controlling costs and mitigating the long-term economic consequences of the obesity epidemic. Population-based approaches to obesity management have been proposed that take advantage of a chronic care model (CCM), including patient self-care, the use of community-based resources, and the realization of care continuity through ongoing communications with patients, information technology, and public policy changes. Payer-sponsored disease management programs represent an important conduit to delivering population-based care founded on similar CCM concepts. Disease management is founded on population-based disease identification, evidence-based care protocols, and collaborative practices between clinicians. While substantial clinician training, technology infrastructure commitments, and financial support at the payer level will be needed for the success of disease management programs in obesity and cardiometabolic risk reduction, these barriers can be overcome with the proper commitment. Disease management programs represent an important tool to combat the growing societal risks of overweight and obesity.

National survey of breast cancer screening in rural America.

Rural US women experience disparities in breast cancer screening and outcomes. In 2006, a national rural health insurance provider, the National Rural Electric Cooperative Association (NRECA), eliminated out‐of‐pocket costs for screening mammography.

Effectiveness Of A Disease Management Program For Patients With Diabetes

13 Background: Screening mammography leads to early detection of breast cancer and improved survival. We conducted a survey of predominantly rural U.S. women who receive health insurance through the National Rural Electric Cooperative Association (NRECA) to evaluate the prevalence of annual and biennial screening and to identify potential disparities and barriers to breast cancer screening. METHODS We conducted a national cross-sectional survey of women between ages 40 and 65 who are insured by the NRECA regarding their utilization of mammography screening and barriers to screening. A study specific survey was mailed to 2,000 randomly selected eligible women without prior diagnosis of breast cancer. We assessed demographics and receipt of mammography within past 12 months (all women) and number of screening mammograms within the past 4 years (among women age 44 and older) to identify consistent annual screening and biennial screening patterns. RESULTS 1,204 women responded to the survey (response rate 60.2%). 74% live in rural areas, 18% suburban, 8% urban. 73% report less than 4 years college education and 19% have family incomes <

Managing the space between visits: a randomized trial of disease management for diabetes in a community health center.

50,000/year. Overall, 72% reported screening mammography within 12 months, 59% reported consistent annual screening and 84% reported at least biennial screening. Rural women were less likely to undergo consistent annual (56% vs. 66%, p = 0.003) or biennial screening (82% vs. 89%, p = 0.01) compared to women in non-rural areas. Women under 50 were less likely to report screening within 12 months (67% vs. 77%, p = 0.0002), consistent annual (49% vs. 63%, p < 0.0001) or biennial screening (79% vs. 86%, p = 0.002). Significantly more rural women cited cost and distance as barriers, while busy schedule, fear of diagnosis, and fear of discomfort were important barriers among all demographic groups. Fear of the test was a greater barrier among younger vs. older women (p < 0.02). In univariate analysis; household income did not correlate with screening, and education was only a factor among younger women. CONCLUSIONS A substantial percentage of rural U.S. women fail to undergo screening mammography. Potentially modifiable barriers include out of pocket expenses, convenience of screening, and fear of diagnosis and the test itself.