Impact of a Provider Tele-mentoring Learning Model on the Care of Medicaid-enrolled Patients With Diabetes.

BACKGROUND: Project ECHO (Extension for Community Healthcare Outcomes), a tele-mentoring program for health care providers, has been shown to improve provider-reported outcomes, but there is insufficient research on patient-level outcomes. OBJECTIVES: To evaluate the impact of primary care provider (PCP) participation in Project ECHO on the care of Medicaid enrollees with diabetes. RESEARCH DESIGN: New Jersey Medicaid claims and encounter data and difference-in-differences models were used to compare utilization and spending between Medicaid patients seen by PCPs participating in a Project ECHO program to those of matched nonparticipating PCPs. SUBJECTS: A total of 1776 adult Medicaid beneficiaries (318 with diabetes), attributed to 25 participating PCPs; and 9126 total (1454 diabetic) beneficiaries attributed to 119 nonparticipating PCPs. MEASURES: Utilization and spending for total inpatient, diabetes-related inpatient, emergency department, primary care, and endocrinologist services; utilization of hemoglobin A1c tests, eye exams, and diabetes prescription medications among diabetics, and total Medicaid spending. RESULTS: Participation in Project ECHO was associated with decreases of 44.3% in inpatient admissions (P=0.001) and 61.9% in inpatient spending (P=0.021) among treatment relative to comparison patients. Signs of most other outcome estimates were consistent with hypothesized program effects but without statistical significance. Sensitivity analyses largely confirmed these findings. CONCLUSIONS: We find evidence that Project ECHO participation was associated with large and statistically significant reductions of inpatient hospitalization and spending. The study was observational and limited by a small sample of participating PCPs. This study demonstrates the feasibility and potential value of quasi-experimental evaluation of Project ECHO patient outcomes using claims data.

Chronic Medication Nonadherence and Potentially Preventable Healthcare Utilization and Spending Among Medicare Patients.

BACKGROUND: The association between nonadherence to chronic medications and potentially preventable healthcare utilization and spending is largely unknown. OBJECTIVES: To examine the associations of chronic medication nonadherence with potentially preventable utilization and spending among patients who were prescribed diabetic medications, renin-angiotensin system antagonists (RASA) for hypertension, or statins for high cholesterol, and compare the associations by patient race/ethnicity and socioeconomic status. DESIGN: Retrospective cohort study. Medicare fee-for-service claims data from 2013 to 2016 for 177,881 patients. MEASURES: Medication nonadherence was defined as having a below 80% proportion of days covered in each 6-month interval after the index prescription. Potentially preventable utilization was measured by preventable emergency department visits and preventable hospitalizations. Potentially preventable spending was calculated as the geographically adjusted spending associated with preventable encounters. RESULTS: After adjustment for other patient characteristics, medication nonadherence was associated with a 1.7-percentage-point increase (95% confidence interval [CI]: 1.4 to 2.0 percentage points, p < 0.001) in the probability of preventable utilization among the diabetic medication cohort, a 1.7-percentage-point increase (95% CI: 1.5 to 1.9 percentage points, p < 0.001) among the RASA cohort, and a 1.0-percentage-point increase (95% CI: 0.8 to 1.1 percentage points, p < 0.001) among the statin cohort. Among patients with at least one preventable encounter, medication nonadherence was associated with $679-$898 increased preventable spending. The incremental probability of preventable utilization and incremental spending associated with nonadherence were higher among racial/ethnic minority and low socioeconomic groups. CONCLUSIONS: Improving medication adherence is a potential avenue to reducing preventable utilization and spending. Interventions are needed to address racial/ethnic and socioeconomic disparities.

Angiotensin-Converting Enzyme Inhibitors Used Concomitantly with Insulin Secretagogues and the Risk of Serious Hypoglycemia.

Serious hypoglycemia is a major adverse event associated with insulin secretagogues. Previous studies have suggested a potential relationship between angiotensin-converting enzyme inhibitors (ACEIs) used with sulfonylureas and serious hypoglycemia, and widely used drug compendia warn of this potential drug-drug interaction. We investigated the association between serious hypoglycemia and concomitant use of ACEIs in patients receiving insulin secretagogues, using the self-controlled case series design and Medicaid claims data from 5 US states linked to Medicare claims from 1999-2011. The exposure of interest was active prescription for ACEIs during insulin secretagogue or metformin (negative control object drug) episodes. The outcome was hospital presentation for serious hypoglycemia, identified by discharge diagnosis codes in inpatient and emergency department claims (positive predictive value ~ 78-89%). We calculated confounder-adjusted rate ratios (RRs) and 95% confidence internals (CIs) of outcome occurrence during ACEI-exposed vs. ACEI-unexposed time using conditional Poisson regression. The RRs for ACEIs were not statistically elevated during observation time of glipizide (RR, 1.06; CI, 0.98-1.15), glyburide (RR, 1.05; CI, 0.96-1.15), repaglinide (RR, 1.15; CI, 0.94-1.41), or metformin (RR, 1.02; CI, 0.97-1.06); but was modestly elevated with glimepiride (RR, 1.23; CI, 1.11-1.37) and modestly reduced with nateglinide (RR, 0.73; CI, 0.56-0.96). The overall pattern of results do not suggest that ACEIs used with insulin secretagogues were associated with increased rates of serious hypoglycemia, with the possible exception of glimepiride.

Clinical subphenotypes in COVID-19: derivation, validation, prediction, temporal patterns, and interaction with social determinants of health.

The coronavirus disease 2019 (COVID-19) is heterogeneous and our understanding of the biological mechanisms of host response to the viral infection remains limited. Identification of meaningful clinical subphenotypes may benefit pathophysiological study, clinical practice, and clinical trials. Here, our aim was to derive and validate COVID-19 subphenotypes using machine learning and routinely collected clinical data, assess temporal patterns of these subphenotypes during the pandemic course, and examine their interaction with social determinants of health (SDoH). We retrospectively analyzed 14418 COVID-19 patients in five major medical centers in New York City (NYC), between March 1 and June 12, 2020. Using clustering analysis, 4 biologically distinct subphenotypes were derived in the development cohort (N = 8199). Importantly, the identified subphenotypes were highly predictive of clinical outcomes (especially 60-day mortality). Sensitivity analyses in the development cohort, and rederivation and prediction in the internal (N = 3519) and external (N = 3519) validation cohorts confirmed the reproducibility and usability of the subphenotypes. Further analyses showed varying subphenotype prevalence across the peak of the outbreak in NYC. We also found that SDoH specifically influenced mortality outcome in Subphenotype IV, which is associated with older age, worse clinical manifestation, and high comorbidity burden. Our findings may lead to a better understanding of how COVID-19 causes disease in different populations and potentially benefit clinical trial development. The temporal patterns and SDoH implications of the subphenotypes may add insights to health policy to reduce social disparity in the pandemic.

Compared to commercially insured patients, Medicare advantage patients adopt newer diabetes drugs more slowly and adhere to them less.

AIMS: To compare rates of use and adherence for newer versus older second-line diabetes drug classes in commercially insured, Medicare Advantage and dual-eligible (covered by both Medicare and Medicaid) patients. MATERIALS AND METHODS: Longitudinal cohort study using insurance claims data from 1/1/2012 to 12/31/2016 to identify patients with a first prescription, after metformin, of a second-line diabetes drug (eg sulphonylurea, DPP-4 inhibitor, thiazolidinedione, SGLT-2 inhibitor or GLP-1 receptor agonist) and to estimate their adherence to that drug class. Univariate analysis and multivariable logistic regression were used to examine the association between insurance type and use of each drug class, and between insurance type and adherence to each drug class. RESULTS: The study population included 96,663 patients. Trends in drug use differed by insurance type. For example, sulphonylurea use declined among the commercially insured (from 46% to 39%, p < .001) but not among Medicare Advantage or dual-eligible patients. Patterns of adherence also differed between insurance groups. For example, compared to commercial insurance, Medicare Advantage was associated with higher adherence to sulphonylurea (odds ratio [OR] 1.32, 95% CI 1.21-1.43)) but lower adherence to SGLT-2 inhibitors (OR 0.43 (95% CI 0.33-0.56)). CONCLUSIONS: This study finds differences in utilization and adherence for diabetes drugs across insurance types. Older medications such as sulphonylureas appear to be more used and better adhered to among Medicare Advantage recipients, while the opposite is true for newer medication classes. These findings suggest a need to personalize selection of diabetes drugs according to insurance status, particularly when adherence needs optimization.

Risk of sudden cardiac arrest and ventricular arrhythmia with sulfonylureas: An experience with conceptual replication in two independent populations.

Sulfonylureas are commonly used to treat type 2 diabetes mellitus. Despite awareness of their effects on cardiac physiology, a knowledge gap exists regarding their effects on cardiovascular events in real-world populations. Prior studies reported sulfonylurea-associated cardiovascular death but not serious arrhythmogenic endpoints like sudden cardiac arrest (SCA) or ventricular arrhythmia (VA). We assessed the comparative real-world risk of SCA/VA among users of second-generation sulfonylureas: glimepiride, glyburide, and glipizide. We conducted two incident user cohort studies using five-state Medicaid claims (1999-2012) and Optum Clinformatics commercial claims (2000-2016). Outcomes were SCA/VA events precipitating hospital presentation. We used Cox proportional hazards models, adjusted for high-dimensional propensity scores, to generate adjusted hazard ratios (aHR). We identified 624,406 and 491,940 sulfonylurea users, and 714 and 385 SCA/VA events, in Medicaid and Optum, respectively. Dataset-specific associations with SCA/VA for both glimepiride and glyburide (vs. glipizide) were on opposite sides of and could not exclude the null (glimepiride: aHRMedicaid 1.17, 95% CI 0.96-1.42; aHROptum 0.84, 0.65-1.08; glyburide: aHRMedicaid 0.87, 0.74-1.03; aHROptum 1.11, 0.86-1.42). Database differences in data availability, populations, and documentation completeness may have contributed to the incongruous results. Emphasis should be placed on assessing potential causes of discrepancies between conflicting studies evaluating the same research question.

The risk of sudden cardiac arrest and ventricular arrhythmia with rosiglitazone versus pioglitazone: real-world evidence on thiazolidinedione safety.

BACKGROUND: The low cost of thiazolidinediones makes them a potentially valuable therapeutic option for the > 300 million economically disadvantaged persons worldwide with type 2 diabetes mellitus. Differential selectivity of thiazolidinediones for peroxisome proliferator-activated receptors in the myocardium may lead to disparate arrhythmogenic effects. We examined real-world effects of thiazolidinediones on outpatient-originating sudden cardiac arrest (SCA) and ventricular arrhythmia (VA). METHODS: We conducted population-based high-dimensional propensity score-matched cohort studies in five Medicaid programs (California, Florida, New York, Ohio, Pennsylvania | 1999-2012) and a commercial health insurance plan (Optum Clinformatics | 2000-2016). We defined exposure based on incident rosiglitazone or pioglitazone dispensings; the latter served as an active comparator. We controlled for confounding by matching exposure groups on propensity score, informed by baseline covariates identified via a data adaptive approach. We ascertained SCA/VA outcomes precipitating hospital presentation using a validated, diagnosis-based algorithm. We generated marginal hazard ratios (HRs) via Cox proportional hazards regression that accounted for clustering within matched pairs. We prespecified Medicaid and Optum findings as primary and secondary, respectively; the latter served as a conceptual replication dataset. RESULTS: The adjusted HR for SCA/VA among rosiglitazone (vs. pioglitazone) users was 0.91 (0.75-1.10) in Medicaid and 0.88 (0.61-1.28) in Optum. Among Medicaid but not Optum enrollees, we found treatment effect heterogeneity by sex (adjusted HRs = 0.71 [0.54-0.93] and 1.16 [0.89-1.52] in men and women respectively, interaction term p-value = 0.01). CONCLUSIONS: Rosiglitazone and pioglitazone appear to be associated with similar risks of SCA/VA.

Review of Metformin Use for Type 2 Diabetes Prevention.

CONTEXT: Prediabetes is prevalent and significantly increases lifetime risk of progression to type 2 diabetes. This review summarizes the evidence surrounding metformin use for type 2 diabetes prevention. EVIDENCE ACQUISITION: Articles published between 1998 and 2017 examining metformin use for the primary indication of diabetes prevention available on MEDLINE. EVIDENCE SYNTHESIS: Forty articles met inclusion criteria and were summarized into four general categories: (1) RCTs of metformin use for diabetes prevention (n=7 and n=2 follow-up analyses); (2) observational analyses examining metformin use in heterogeneous subgroups of patients with prediabetes (n=9 from the Diabetes Prevention Program, n=1 from the biguanides and the prevention of the risk of obesity [BIGPRO] trial); (3) observational analyses examining cost effectiveness of metformin use for diabetes prevention (n=11 from the Diabetes Prevention Program, n=1 from the Indian Diabetes Prevention Program); and (4) real-world assessments of metformin eligibility or use for diabetes prevention (n=9). Metformin was associated with reduced relative risk of incident diabetes, with the strongest evidence for use in those at highest risk (i.e., aged <60 years, BMI ≥35, and women with histories of gestational diabetes). Metformin was also deemed cost effective in 11 economic analyses. Recent studies highlighted low rates of metformin use for diabetes prevention in real-world settings. CONCLUSIONS: Two decades of evidence support metformin use for diabetes prevention among higher-risk patients. However, metformin is not widely used in real-world practice, and enhancing the translation of this evidence to real-world practice has important implications for patients, providers, and payers.

Comparative risk of serious hypoglycemia with oral antidiabetic monotherapy: A retrospective cohort study.

PURPOSE: To examine and compare risks of serious hypoglycemia among antidiabetic monotherapy-treated adults receiving metformin, a sulfonylurea, a meglitinide, or a thiazolidinedione. METHODS: We performed a retrospective cohort study of apparently new users of monotherapy with metformin, glimepiride, glipizide, glyburide, pioglitazone, rosiglitazone, nateglinide, or repaglinide within a dataset of Medicaid beneficiaries from California, Florida, New York, Ohio, and Pennsylvania. We did not include users of dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 agonists, or sodium-glucose co-transporter 2 inhibitors. We identified serious hypoglycemia outcomes within 180 days following new use using a validated, diagnosis-based algorithm. We calculated age- and sex-standardized outcome occurrence rates for each drug and generated propensity score-adjusted hazard ratios vs metformin using Cox proportional hazards regression. RESULTS: The ranking of standardized occurrence rates of serious hypoglycemia was glyburide > glimepiride > glipizide > repaglinide > nateglinide > rosiglitazone > pioglitazone > metformin. Rates were increased for all study drugs at higher average daily doses. Adjusted hazard ratios (95% confidence intervals) vs metformin were 3.95 (3.66-4.26) for glyburide, 3.28 (2.98-3.62) for glimepiride, 2.57 (2.38-2.78) for glipizide, 2.03 (1.64-2.52) for repaglinide, 1.21 (0.89-1.66) for nateglinide, 0.90 (0.75-1.07) for rosiglitazone, and 0.80 (0.68-0.93) for pioglitazone. CONCLUSIONS: Sulfonylureas were associated with the highest rates of serious hypoglycemia. Among all study drugs, the highest rate was seen with glyburide. Pioglitazone was associated with a lower adjusted hazard for serious hypoglycemia vs metformin, while rosiglitazone and nateglinide had hazards similar to that of metformin.

Missing laboratory results data in electronic health databases: implications for monitoring diabetes risk.

AIM: Laboratory test (lab) results may be useful to detect incident diabetes in electronic health record and claims-based studies. RESEARCH DESIGN & METHODS: Using the Mini-Sentinel distributed database, we assessed the value of lab results added to diagnosis codes and dispensing claims to identify incident diabetes. RESULTS: Inclusion of lab results increased the number of diabetes outcomes identified by 21%. In settings where capture of lab results was relatively complete, the absence of lab results was associated with implausibly low rates of the outcome. CONCLUSION: Lab results can increase sensitivity of algorithms for detecting diabetes, and missing lab results are associated with much lower rates of diabetes ascertainment regardless of algorithm. Patterns of missing lab results may identify ascertainment bias.