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Waltham, MA, United States

Zullo A.R.,Brown University | Dore D.D.,Optum Epidemiology | Daiello L.,Brown University | Baier R.R.,Brown University | And 3 more authors.
Journal of the American Medical Directors Association | Year: 2016

Objective Diabetes mellitus is common in the nursing home (NH) population, yet little is known about prescribing of glucose-lowering medications in the NH setting. We describe trends in initiation of glucose-lowering medications in a national cohort of NH residents. Design and setting Retrospective cohort study using Part A and D claims for a random 20% of Medicare enrollees linked to NH Minimum Data Set (MDS) and Online Survey, Certification, and Reporting (OSCAR) databases in 7158 US NHs. Participants A total of 11,531 long-stay (continuous residence of ≥90 days) NH residents 65 years or older with diabetes who received a glucose-lowering medication between 2008 and 2010 after 4 months of nonuse. Measurements Medicare Part D drug dispensing of glucose-lowering treatments; resident and facility characteristics preceding medication initiation. Results We observed decreasing sulfonylurea initiation from 25.4% of initiations in 2008 to 11.7% in 2010, an average decrease of 1% per quarter (95% CLs −1.5 to −0.5). Thiazolidinedione initiation decreased from 4.7% to 1.9%, an average decrease of 0.3% per quarter (95% CLs −0.4 to −0.2), and meglitinide initiation from 1.5% to 0.3%. No appreciable linear trends were observed for metformin (range 12.0%–18.8%) and dipeptidyl peptidase-4 (DPP-4) inhibitors (range 0.9%–2.7%). In contrast, insulin use increased from 51.7% to 68.3% during the same time period, driven by a marked increase in initiation of rapid-acting insulin (11.0% to 29.4%; average increase of 1.4% per quarter, 95% CLs 0.9–1.9) and a modest increase in short-acting insulin (22.6% to 30.3%; an average increase of 0.6% per quarter, 95% CLs −0.1 to 1.3). Conclusions Between 2008 and 2010, there were substantial decreases in the use of oral glucose-lowering agents and corresponding increases in the use of insulin among long-term residents of US NHs. © 2016 AMDA – The Society for Post-Acute and Long-Term Care Medicine Source

Danilack V.A.,Brown University | Nunes A.P.,Optum Epidemiology | Phipps M.G.,Brown University
American Journal of Obstetrics and Gynecology | Year: 2015

Objective Determining appropriate sites of care for any type of medical issue assumes successful matching of patient risks to facility capabilities and resources. In obstetrics, predicting patients who will have a need for additional resources beyond routine obstetric and neonatal care is difficult. Women without prenatal risk factors and their newborns may experience unexpected complications during delivery or postpartum. In this study, we report the risk of unexpected maternal and newborn complications among pregnancies without identified prenatal risk factors. Study Design We conducted a cross-sectional investigation utilizing US natality data to analyze 10 million birth certificate records from 2011 through 2013. We categorized pregnancies as low risk (no prenatal risk factors) or high risk (at least 1 prenatal risk factor) according to 19 demographic, medical, and pregnancy characteristics. We evaluated 21 individual unexpected or adverse intrapartum and postpartum outcomes in addition to a composite indicator of any adverse outcome. Results Among 10,458,616 pregnancies, 38% were identified as low risk and 62% were identified as high risk for unexpected complications. At least 1 unexpected complication was indicated on the birth certificate for 46% of all pregnancies, 29% of low-risk pregnancies, and 57% of high-risk pregnancies. While the risk for unexpected or adverse outcomes was greatly reduced for the low-risk group compared to the high-risk group overall and for several of the individual outcomes, low-risk pregnancies had higher risks of vacuum delivery, forceps delivery, meconium staining, and chorioamnionitis compared to high-risk pregnancies. Conclusion Of births, 29% identified to be low risk had an unexpected complication that would require nonroutine obstetric or neonatal care. Additionally, for select outcomes, risks were higher in the low-risk group compared to the group with identified risk factors. This information is important for planning location of birth and evaluating birthing centers and hospitals for necessary resources to ensure quality care and patient safety. © 2015 Elsevier Inc. All rights reserved. Source

Liang C.,Optum Epidemiology | Seeger J.D.,Optum Epidemiology | Seeger J.D.,Harvard University | Dore D.D.,Optum Epidemiology | Dore D.D.,Brown University
Annals of Epidemiology | Year: 2016

Purpose: The amount of immortal time bias in studies with nonfatal outcomes is unclear. To quantify the magnitude of bias from mishandling of immortal person-time in studies of nonfatal outcomes. Methods: We derived formulas for quantifying bias from misclassified or excluded immortal person-time in settings with nonfatal outcomes, assuming a constant rate of outcome. In the situation of misclassified or excluded immortal person-time, the quantification includes the immortal time and corresponding events mistakenly attributed to the exposed group (misclassified) or excluded from study (excluded) that must be attributed to the comparison group. Results: With misclassified immortal person-time, the magnitude of bias varies according to the incidence rate ratio of immortal time and comparison group as well as the rate ratio of immortal time and exposed group: toward null for both ratios less than 1, no bias for both ratios equal to 1, away from null for both ratios greater than 1. For one ratio less than 1 and the other greater than 1, the direction and magnitude of bias can be obtained from the formula provided. With excluded immortal person-time, the magnitude of bias is associated with the incidence rate ratio of immortal time and comparison group: toward null for the ratio less than 1, no bias for the ratio equal to 1, and away from null for the ratio greater than 1. Conclusions: Bias due to immortal person-time in studies with nonfatal outcomes can vary widely and can be quantified under assumptions that apply to many studies. © 2016 Elsevier Inc. Source

Dore D.D.,Policy and Practice and Epidemiology | Dore D.D.,Center for Gerontology and Health Care Research | Hussein M.,IMS Consulting | Hoffman C.,Optum Epidemiology | And 4 more authors.
Current Medical Research and Opinion | Year: 2013

Objective: To estimate the association between exenatide BID use and acute pancreatitis across two claims-based studies. Research design and methods: We pooled two cohort studies within separate commercial health insurance databases. We included initiators of exenatide BID and all other antihyperglycemic drugs without prior pancreatitis from 2005-2008. Poisson regression models provided rate ratios (RRs) and 95% confidence intervals (CIs) of the association of exenatide BID with acute pancreatitis adjusted for quintiles of propensity scores. Main outcome measures: Primary inpatient diagnoses of acute pancreatitis with correction for misclassification via a validation sub-study. Results: There were 49,956 initiators of exenatide BID and 692,333 initiators of other antihyperglycemic drugs. Patients in the two studies were similar on many demographic and clinical characteristics. Exenatide BID initiators had a higher prevalence of diagnoses consistent with diabetes complications (e.g. peripheral neuropathy) and cardiovascular risk factors (e.g. hypertension). In both studies, current exenatide BID use was not associated with uncorrected outcomes of acute pancreatitis (pooled RR 1.0; CI 0.8-1.3). PPV correction resulted in a slightly higher point estimate for current use (pooled RR 1.3; CI 1.0-1.7) and past use (pooled RR 1.6; 95% CI 1.2-2.1). Conclusions: These data are consistent with little or no higher risk of acute pancreatitis associated with current exenatide BID use relative to nonuse. Although previous work identified non-causal mechanisms, an increased incidence of acute pancreatitis following cessation of treatment remains a possibility. Bias due to residual confounding or outcome misclassification may remain, and should be considered a potential explanation for these findings. © 2013 All rights reserved. Source

Dore D.D.,Brown University | Ziyadeh N.,Optum Epidemiology | Cai B.,Novartis | Clifford C.R.,Optum Epidemiology | And 3 more authors.
BMC Pulmonary Medicine | Year: 2014

Background: Claims data are potentially useful for identifying long-acting β-agonist (LABA) use by patients with asthma, a practice that is associated with increased mortality. We evaluated the accuracy of claims data for classifying prevalent asthma and chronic obstructive pulmonary disease (COPD) among initiators of LABAs.Methods: This study included adult LABA initiators during 2005-2008 in a US commercial health plan. Diagnosis codes from the 6 months before LABA initiation identified potential asthma or COPD and a physician adjudicated case status using abstracted medical records. We estimated the positive predictive value (PPV) and 95% confidence intervals (CI) of covariate patterns for identifying asthma and COPD.Results: We sought 520 medical records at random from 225,079 LABA initiators and received 370 (71%). The PPV for at least one asthma claim was 74% (CI 63-82), and decreased as age increased. Having at least one COPD claim resulted in a PPV of 82% (CI 72-89), and of over 90% among older patients, men, and recipients of inhaled anticholinergic drugs. Only 2% (CI 0.2-7.6) of patients with a claim for COPD alone were found to have both COPD and asthma, while 9% (CI 4-16) had asthma only. Twenty-one percent (CI 14-30) of patients with claims for both diagnoses had both conditions. Among patients with no asthma or COPD claims, 62% (CI 50-72) had no confirmed diagnosis and 29% (CI 19-39) had confirmed asthma.Conclusions: Subsets of patients with asthma, COPD, and both conditions can be identified and differentiated using claims data, although categorization of the remaining patients is infeasible. Safety surveillance for off-label use of LABAs must account for this limitation. © 2014 Dore et al.; licensee BioMed Central Ltd. Source

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