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Objective: To describe treatment regimen changes of patients with type 2 diabetes mellitus (T2DM) initiating metformin monotherapy, and assess factors associated with those changes 12 months post-initiation.Methods: Retrospective cohort analysis of medical, pharmacy and laboratory claims of 17,527 Medicare Advantage (MAPD) Humana members aged 18-89, who had ≥1 medical claim with primary diagnosis or ≥2 medical claims with secondary diagnosis of T2DM (ICD-9-CM code 250.x0 or 250.x2) who filled an initial prescription for metformin (GPI code 2725) between 1 January 2008 and 30 September 2011. The main outcome measure was change in metformin monotherapy during the 12 months following initiation. Factors associated with treatment changes during follow-up were examined using Cox proportional hazards regression models.Results: Fifty-nine percent of patients (mean age 69.6 years) remained on metformin monotherapy with no changes. Discontinuation was the most common treatment change (33%), followed by addition (5%), and switching (2%) to other antidiabetics. Of patients who discontinued treatment (median time to discontinuation = 90 days), 61% did not reinitiate any diabetic treatment during the follow-up period. Among patients who added or switched to other antidiabetics, sulfonylureas were the most common addition or replacement agent. Predictors of discontinuation were being female, Black or Hispanic, low-income subsidy eligible, having higher initial out-of-pocket metformin costs, or a diagnosis of depression. Discontinuation was less likely during follow-up if patients had higher pre-index pill burdens or records of a pre-index A1C screening test. A higher risk of discontinuation was observed for patients with low baseline A1C. One study limitation was that exact discontinuation dates could not be determined using claims.Conclusions: The findings suggest that gender, race, ethnicity, depression, and low income status were contributory factors to metformin discontinuation. More intensive monitoring and treatment adjustments may be warranted for patients newly initiated on metformin. This could ultimately improve morbidity, mortality, and costs associated with poor glycemic control. [ABSTRACT FROM AUTHOR]

Introduction: An often key component to coordinating surveillance activities across distributed networks is the design and implementation of a common data model (CDM). The purpose of this study was to evaluate two drug safety surveillance CDMs from an ecosystem perspective to better understand how differences in CDMs and analytic tools affect usability and interpretation of results.Methods: Humana claims data from 2007 to 2012 were mapped to Observational Medical Outcomes Partnership (OMOP) and Mini-Sentinel CDMs. Data were described and compared at the patient level by source code and mapped concepts. Study cohort construction and effect estimates were also compared using two different analytical methods--one based on a new user design implementing a high-dimensional propensity score (HDPS) algorithm and the other based on univariate self-controlled case series (SCCS) design--across six established positive drug-outcome pairs to learn how differences in CDMs and analytics influence steps in the database analytic process and results.Results: Claims data for approximately 7.7 million Humana health plan members were transformed into the two CDMs. Three health outcome cohorts and two drug cohorts showed differences in cohort size and constituency between Mini-Sentinel and OMOP CDMs, which was a result of multiple factors. Overall, the implementation of the HDPS procedure on Mini-Sentinel CDM detected more known positive associations than that on OMOP CDM. The SCCS method results were comparable on both CDMs. Differences in the implementation of the HDPS procedure between the two CDMs were identified; analytic model and risk period specification had a significant impact on the performance of the HDPS procedure on OMOP CDM.Conclusions: Differences were observed between OMOP and Mini-Sentinel CDMs. The analysis of both CDMs at the data model level indicated that such conceptual differences had only a slight but not significant impact on identifying known safety associations. Our results show that differences at the ecosystem level of analyses across the CDMs can lead to strikingly different risk estimations, but this can be primarily attributed to the choices of analytic approach and their implementation in the community-developed analytic tools. The opportunities of using CDMs are clear, but our study shows the need for judicious comparison of analyses across the CDMs. Our work emphasizes the need for ongoing efforts to ensure sustainable transparent platforms to maintain and develop CDMs and associated tools for effective safety surveillance. [ABSTRACT FROM AUTHOR]

Few studies have examined, in a prospective cohort study, factors causing delay of access to tuberculosis (TB) diagnosis among new, active TB patients. A prospective cohort study (2009-2011) was carried out among 408 889 Chinese. Data on known/potential influencing factors were obtained from baseline questionnaires. We used stepwise logistic regression models to analyze the association between several known/potential influencing factors and diagnosis delay, assessed the current situation, and explored determinants of diagnosis delay. During follow-up and final visits, 202 new, active TB patients were found. Median patient delay was 5.4 (quartile 2.7-26) weeks, health system delay was 0 (quartile 0-1.6) weeks, and diagnosis delay was 9.9 (quartile 3.1-28.1) weeks. The influencing factors on patient delay were age and duration of symptoms. Smoking and sputum smear status were influencing factors for health system delay, and duration of symptoms was one of the factors for diagnosis delay. These findings provide information on the current situation of diagnosis delay and evidence for specific strategy development for TB control in China. [ABSTRACT FROM PUBLISHER]

Rationale, aims and objectives Multiple treatments are available for osteoporosis; however, little is known about treatment change patterns and associated factors. Osteoporosis treatment change patterns, discontinuation and factors associated with treatment change in members of a large national health plan were examined. Methods A retrospective cohort study was conducted in 7315 commercial and 34 146 Medicare Advantage Prescription Drug (MAPD) members newly initiated on an osteoporosis medication between 2006 and 2008. Osteoporosis treatment change, discontinuation and re-initiation patterns were assessed. Multivariate logistic regression was used to examine factors associated with treatment change. Commercial and MAPD members were assessed separately because of differences in demographics and insurance benefits. Results Approximately 12% of members had a change in index therapy within 12 months. Almost 60% of members discontinued the index medication at least once, based on a 90-day refill gap. Over 40% of members discontinued all osteoporosis medications by the end of 12 months post-index. Among MAPD and commercial members, women and those with risedronate, ibandronate or calcitonin at index, index therapy in 2008 and an osteoporosis diagnosis were more likely to have a treatment change while members with health plans other than health maintenance organizations and generic alendronate at index were less likely to have a treatment change. Conclusions Osteoporosis treatment change occurred in approximately 12% of members, while a greater proportion of members discontinued treatment completely within 12 months. Member characteristics may be used to predict therapy change for evaluation and quality initiatives within a health plan. [ABSTRACT FROM AUTHOR]