Comparative Effectiveness of Hypoglycemic Medications Among Veterans

Kheirbek, Raya; Alemi, Farrokh; Zargoush, Manaf

doi:10.18553/jmcp.2013.19.9.740

Cited by 6 publications

(8 citation statements)

References 23 publications

(20 reference statements)

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“…MM was represented as a simple count of conditions that were available in the study datasets in 15 studies (32%) [17, 18, 22–25, 29, 38, 44, 47, 48, 50, 52, 54, 56]. The remaining studies measured MM with other indices including the chronic diseases score [20], cumulative illness rating scales [26], total illness burden index [42], severity of illness index [45] and the Elixhauser index [52], or a combination of multiple MM measures [50, 52]. The measure of MM for each of the studies is summarised in S2 Table.…”

Section: Resultsmentioning

confidence: 99%

Associations between multimorbidity, all-cause mortality and glycaemia in people with type 2 diabetes: A systematic review

et al. 2018

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IntroductionType 2 diabetes (T2D) is a major health priority worldwide and the majority of people with diabetes live with multimorbidity (MM) (the co-occurrence of ≥2 chronic conditions). The aim of this systematic review was to explore the association between MM and all-cause mortality and glycaemic outcomes in people with T2D.MethodsThe search strategy centred on: T2D, MM, comorbidity, mortality and glycaemia. Databases searched: MEDLINE, EMBASE, CINAHL Complete, The Cochrane Library, and SCOPUS. Restrictions included: English language, quantitative empirical studies. Two reviewers independently carried out: abstract and full text screening, data extraction, and quality appraisal. Disagreements adjudicated by a third reviewer.ResultsOf the 4882 papers identified; 41 met inclusion criteria. The outcome was all-cause mortality in 16 studies, glycaemia in 24 studies and both outcomes in one study. There were 28 longitudinal cohort studies and 13 cross-sectional studies, with the number of participants ranging from 96–892,223. Included studies were conducted in high or upper-middle-income countries. Fifteen of 17 studies showed a statistically significant association between increasing MM and higher mortality. Ten of 14 studies showed no significant associations between MM and HbA1c. Four of 14 studies found higher levels of MM associated with higher HbA1c. Increasing MM was significantly associated with hypoglycaemia in 9/10 studies. There was no significant association between MM and fasting glucose (one study). No studies explored effects on glycaemic variability.ConclusionsThis review demonstrates that MM in T2D is associated with higher mortality and hypoglycaemia, whilst evidence regarding the association with other measures of glycaemic control is mixed. The current single disease focused approach to management of T2D seems inappropriate. Our findings highlight the need for clinical guidelines to support a holistic approach to the complex care needs of those with T2D and MM, accounting for the various conditions that people with T2D may be living with.Systematic review registrationInternational Prospective Register of Systematic Reviews CRD42017079500

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Section: Resultsmentioning

confidence: 99%

Associations between multimorbidity, all-cause mortality and glycaemia in people with type 2 diabetes: A systematic review

et al. 2018

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“…Our results are more consistent with the recommendation by the American Diabetes Association [60] and the conclusions of Mekuria and colleagues [61], which confirms the effectiveness of metformin monotherapy. One reason for such discrepancies between our study and [39] might be the failure of the logistic regression model to capture complex relationships among variables, leading to incomplete customization of the analyses to various patient types. Another reason might be the lack of optimization in their study.…”

Section: Comparison With Other Methodsmentioning

confidence: 62%

“…First, we compared our proposed method with a previous analysis conducted on the same dataset by Kheirbek et al [39]. That study used logistic regression to predict the effectiveness of diabetic medications in relation to all-cause mortality.…”

Section: Comparison With Other Methodsmentioning

confidence: 99%

Leveraging machine learning and big data for optimizing medication prescriptions in complex diseases: a case study in diabetes management

et al. 2020

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This paper proposes a novel algorithm for optimizing decision variables with respect to an outcome variable of interest in complex problems, such as those arising from big data. The proposed algorithm builds on the notion of Markov blankets in Bayesian networks to alleviate the computational challenges associated with optimization tasks in complex datasets. Through a case study, we apply the algorithm to optimize medication prescriptions for diabetic patients, who have different characteristics, suffer from multiple comorbidities, and take multiple medications concurrently. In particular, we demonstrate how the optimal combination of diabetic medications can be found by examining the comparative effectiveness of the medications among similar patients. The case study is based on 5 years of data for 19,223 diabetic patients. Our results indicate that certain patient characteristics (e.g., clinical and demographic features) influence optimal treatment decisions. Among patients examined, monotherapy with metformin was the most common optimal medication decision. The results are consistent with the relevant clinical guidelines and reports in the medical literature. The proposed algorithm obviates the need for knowledge of the whole Bayesian network model, which can be very complex in big data problems. The procedure can be applied to any complex Bayesian network with numerous features, multiple decision variables, and a target variable.

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“…For inclusion in the study, patients were required to have received at least two diagnoses of T2D (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] of 250.x0 or 250.x2)25,26 from July 1, 2010 through June 30, 2011 (ie, the identification window), and to have received at least one prescription for a GLA over the identification window, with the date of the first such prescription designated as the index date. Additionally, patients were required to be at least aged 65 years as of the index date and to have had continuous insurance coverage from 1 year before (the preperiod) through 3 years after (the postperiod) the index date, as well as valid patient demographic data.…”

Section: Methodsmentioning

confidence: 99%

Associations between adherence and outcomes among older, type 2 diabetes patients: evidence from a Medicare Supplemental database

Boye¹,

Curtis²,

Lage³

et al. 2016

PPA

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ObjectiveTo examine the association between adherence to glucose-lowering agents and patient outcomes, including costs, acute-care resource utilization, and complications, in an older, type 2 diabetic population.Data and methodsThe study used Truven’s Medicare Supplemental database from July 1, 2009 to June 30, 2014. Patients aged 65 years or older were included if they had at least two type 2 diabetes diagnoses and received a glucose-lowering agent from July 1, 2010 through June 30, 2011. Multivariable analyses examined the relationships among 3-year patient outcomes and levels of adherence, proxied by the proportion of days covered. Outcomes included all-cause medical costs, diabetes-related medical costs, acute-care resource utilization, and acute complications.ResultsIn this study (N=123,235), higher adherence was linked to reduced costs and improved health outcomes. For example, comparing an individual with adherence of proportion of days covered <20% to one with proportion of days covered ≥80% illustrates an average saving of $28,824 in total 3-year costs. Furthermore, a 1% increase in adherence among 1,000 patients was associated with all-cause savings of $65,464 over 3 years. The probability of a hospitalization, an emergency room (ER) visit, or an acute complication decreased monotonically as adherence levels got higher, as did the number of hospitalizations, ER visits, and days hospitalized (P<0.005).ConclusionHigher adherence was associated with substantially less need for acute care, as indicated by a lowered probability of hospitalization or ER use, a reduced risk of an acute complication, and a decreased number of hospitalizations, ER visits, and days hospitalized. Higher adherence was also generally associated with lower all-cause and diabetes-related total costs, despite higher drug costs. These lower total costs were driven by the diminished acute care and outpatient costs. Results suggest that higher glucose-lowering agent adherence is associated with significant benefits for payers and older patients with type 2 diabetes.

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Comparative Effectiveness of Hypoglycemic Medications Among Veterans

Abstract: BACKGROUND: The efficacy of diabetic medications among patients with multiple comorbidities is not tested in randomized clinical studies. It is important to monitor the performance of these medications after marketing approvals.

Cited by 6 publications

References 23 publications

Associations between multimorbidity, all-cause mortality and glycaemia in people with type 2 diabetes: A systematic review

Associations between multimorbidity, all-cause mortality and glycaemia in people with type 2 diabetes: A systematic review

Leveraging machine learning and big data for optimizing medication prescriptions in complex diseases: a case study in diabetes management

Associations between adherence and outcomes among older, type 2 diabetes patients: evidence from a Medicare Supplemental database

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