Andrew J Karter

Kaiser Permanente, Oakland, California, United States

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Publications (185)1132.21 Total impact

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    ABSTRACT: The risk of future coronary heart disease (CHD) in subjects with diabetes and "metabolic dyslipidemia" (high triglyceride [TGs] and low high-density cholesterol levels) remains a matter of concern. Little is known regarding the risk of CHD for this phenotype with low-density lipoprotein cholesterol (LDL-C) levels <100 mg/dl. We analyzed a diabetes cohort of 28,318 members (aged 30 to 90 years) of Kaiser Permanente Northern California during 2002 to 2011 (192,356 person-years [p-y] follow-up), with LDL-C levels <100 mg/dl and without known CHD. We compared the incidence and hazard ratios (HRs) for CHD events in groups using Cox models: normal high-density lipoprotein (HDL) and TG (reference; n = 7,278, 25.7%); normal HDL and high TG (≥150 mg/dl; n = 4,484,15.8%); low HDL (≤50 mg/dl for women and ≤40 mg/dl for men) and normal TG (n = 4,048, 14.3%); low HDL and high TG (metabolic dyslipidemia; n = 12,508, 44%). Patients with metabolic dyslipidemia had the highest age-adjusted CHD events/1,000 p-y (12.7/1,000 p-y and 19.0/1,000 p-y for women and men, respectively). After multivariate adjustment for age, gender, ethnicity, hypertension, smoking, statin use, duration of diabetes, and hemoglobin A1c, we observed an increased CHD risk in women (HR 1.35, 95% confidence interval 1.14 to 1.60) and men (HR 1.62, 95% confidence interval 1.43 to 1.83) with metabolic dyslipidemia compared to those with normal HDL and TG. Even in subjects with an LDL-C <100 mg/dl, presence of metabolic dyslipidemia in adults with diabetes is associated with an increased risk of CHD. In conclusion, effective CHD prevention strategies are needed for adults with diabetes and metabolic dyslipidemia.
    The American journal of cardiology 10/2015; DOI:10.1016/j.amjcard.2015.08.039 · 3.28 Impact Factor
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    ABSTRACT: Objective: Online patient portals are being widely implemented; however, no studies have examined whether portals influence health behaviors or outcomes similarly across patient racial/ethnic subgroups. We evaluated longitudinal changes in statin adherence to determine whether racial/ethnic minorities initiating use of the online refill function in patient portals had similar changes over time compared with Whites. Methods: We examined a retrospective cohort of diabetes patients who were existing patient portal users. The primary exposure was initiating online refill use (either exclusively for all statin refills or occasionally for some refills), compared with using the portal for other tasks (eg, exchanging secure messages with providers). The primary outcome was change in statin adherence, measured as the percentage of time a patient was without a supply of statins. Adjusted generalized estimating equation models controlled for race/ethnicity as a primary interaction term. Results: Fifty-eight percent of patient portal users were white, and all racial/ethnic minority groups had poorer baseline statin adherence compared with Whites. In adjusted difference-in-difference models, statin adherence improved significantly over time among patients who exclusively refilled prescriptions online, even after comparing changes over time with other portal users (4% absolute decrease in percentage of time without medication). This improvement was statistically similar across all racial/ethnic groups. Discussion: Patient portals may encourage or improve key health behaviors, such as medication adherence, for engaged patients, but further research will likely be required to reduce underlying racial/ethnic differences in adherence. Conclusion: In a well-controlled examination of diabetes patients' behavior when using a new online feature for their healthcare management, patient portals were linked to better medication adherence across all racial/ethnic groups.
    Journal of the American Medical Informatics Association 09/2015; DOI:10.1093/jamia/ocv126 · 3.50 Impact Factor
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    ABSTRACT: Examining trends in cardiovascular events and mortality in US health systems can guide the design of targeted clinical and public health strategies to reduce cardiovascular events and mortality rates. We conducted an observational cohort study from 2005 to 2011 among 1.25 million diabetic subjects and 1.25 million nondiabetic subjects from 11 health systems that participate in the Surveillance, Prevention and Management of Diabetes Mellitus (SUPREME-DM) DataLink. Annual rates (per 1000 person-years) of myocardial infarction/acute coronary syndrome (International Classification of Diseases-Ninth Revision, 410.0-410.91, 411.1-411.8), stroke (International Classification of Diseases-Ninth Revision, 430-432.9, 433-434.9), heart failure (International Classification of Diseases-Ninth Revision, 428-428.9), and all-cause mortality were monitored by diabetes mellitus (DM) status, age, sex, race/ethnicity, and a prior cardiovascular history. We observed significant declines in cardiovascular events and mortality rates in subjects with and without DM. However, there was substantial variation by age, sex, race/ethnicity, and prior cardiovascular history. Mortality declined from 44.7 to 27.1 (P<0.0001) for those with DM and cardiovascular disease (CVD), from 11.2 to 10.9 (P=0.03) for those with DM only, and from 18.9 to 13.0 (P<0.0001) for those with CVD only. Yet, in the ≈85% of subjects with neither DM nor CVD, overall mortality (7.0 to 6.8; P=0.10) and stroke rates (1.6-1.6; P=0.77) did not decline and heart failure rates increased (0.9-1.15; P=0.0005). To sustain improvements in myocardial infarction, stroke, heart failure, and mortality, health systems that have successfully focused on care improvement in high-risk adults with DM or CVD must broaden their improvement strategies to target lower risk adults who have not yet developed DM or CVD. © 2015 American Heart Association, Inc.
    Circulation Cardiovascular Quality and Outcomes 08/2015; DOI:10.1161/CIRCOUTCOMES.115.001717 · 5.66 Impact Factor
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    ABSTRACT: Among patients with diabetes, racial differences in cardiometabolic risk factor control are common. The extent to which differences in medication adherence contribute to such disparities is not known. We examined whether medication adherence, controlling for treatment intensification, could explain differences in risk factor control between black and white patients with diabetes. We identified three cohorts of black and white patients treated with oral medications and who had poor risk factor control at baseline (2009): those with glycated hemoglobin (HbA1c) >8 % (n = 37,873), low-density lipoprotein cholesterol (LDL-C) >100 mg/dl (n = 27,954), and systolic blood pressure (SBP) >130 mm Hg (n = 63,641). Subjects included insured adults with diabetes who were receiving care in one of nine U.S. integrated health systems comprising the SUrveillance, PREvention, and ManagEment of Diabetes Mellitus (SUPREME-DM) consortium. Baseline and follow-up risk factor control, sociodemographic, and clinical characteristics were obtained from electronic health records. Pharmacy-dispensing data were used to estimate medication adherence (i.e., medication refill adherence [MRA]) and treatment intensification (i.e., dose increase or addition of new medication class) between baseline and follow-up. County-level income and educational attainment were estimated via geocoding. Logistic regression models were used to test the association between race and follow-up risk factor control. Models were specified with and without medication adherence to evaluate its role as a mediator. We observed poorer medication adherence among black patients than white patients (p < 0.01): 50.6 % of blacks versus 39.7 % of whites were not highly adherent (i.e., MRA <80 %) to HbA1c oral medication(s); 58.4 % of blacks and 46.7 % of whites were not highly adherent to lipid medication(s); and 33.4 % of blacks and 23.7 % of whites were not highly adherent to BP medication(s). Across all cardiometabolic risk factors, blacks were significantly less likely to achieve control (p < 0.01): 41.5 % of blacks and 45.8 % of whites achieved HbA1c <8 %; 52.6 % of blacks and 60.8 % of whites achieved LDL-C <100; and 45.7 % of blacks and 53.6 % of whites achieved SBP <130. Adjusting for medication adherence/treatment intensification did not alter these patterns or model fit statistics. Medication adherence failed to explain observed racial differences in the achievement of HbA1c, LDL-C, and SBP control among insured patients with diabetes.
    Journal of General Internal Medicine 08/2015; DOI:10.1007/s11606-015-3486-0 · 3.42 Impact Factor
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    ABSTRACT: To examine self-reported financial strain in relation to pharmacy utilization adherence data. Survey, administrative, and electronic medical data from Kaiser Permanente Northern California. Retrospective cohort design (2006, n = 7,773). We compared survey self-reports of general and medication-specific financial strain to three adherence outcomes from pharmacy records, specifying adjusted generalized linear regression models. Eight percent and 9 percent reported general and medication-specific financial strain. In adjusted models, general strain was significantly associated with primary nonadherence (RR = 1.37; 95 percent CI: 1.04-1.81) and refilling late (RR = 1.34; 95 percent CI: 1.07-1.66); and medication-specific strain was associated with primary nonadherence (RR = 1.42, 95 percent CI: 1.09-1.84). Simple, minimally intrusive questions could be used to identify patients at risk of poor adherence due to financial barriers. © Health Research and Educational Trust.
    Health Services Research 08/2015; DOI:10.1111/1475-6773.12346 · 2.78 Impact Factor
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    ABSTRACT: With the expansion of Medicaid and low-cost health insurance plans among diverse patient populations, objective measures of medication adherence using pharmacy claims could advance clinical care and translational research for safety net care. However, safety net patients may experience fluctuating prescription drug coverage, affecting the performance of adherence measures. OBJECTIVE: To evaluate the performance of continuous medication gap (CMG) for diverse, low-income managed care members with diabetes. We conducted this cross-sectional analysis using administrative and clinical data for 680 members eligible for a self-management support trial at a nonprofit, government-sponsored managed care plan. We applied CMG methodology to cardiometabolic medication claims for English- , Cantonese- , or Spanish-speaking members with diabetes. We examined inclusiveness (the proportion with calculable CMG) and selectivity (sociodemographic and medical differences from members without CMG). For validity, we examined unadjusted associations of suboptimal adherence (CMG greater than 20%) with suboptimal cardiometabolic control. 429 members (63%) had calculable CMG. Compared with members without CMG, members with CMG were younger, more likely employed, and had poorer glycemic control but had better blood pressure and lipid control. Suboptimal adherence occurred more frequently among members with poor cardiometabolic control than among members with optimal control (28% vs. 12%, P = 0.02). CONCLUSIONS: CMG demonstrated acceptable inclusiveness and validity in a diverse, low-income safety net population, comparable with its performance in studies among other insured populations. CMG may provide a useful tool to measure adherence among increasingly diverse Medicaid populations, complemented by other strategies to reach those not captured by CMG.
    08/2015; 21(8):688-698.
  • Melissa M Parker · Howard H Moffet · Alyce Adams · Andrew J Karter ·
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    ABSTRACT: Identifying patients who are medication nonpersistent (fail to refill in a timely manner) is important for healthcare operations and research. However, consistent methods to detect nonpersistence using electronic pharmacy records are presently lacking. We developed and validated a nonpersistence algorithm for chronically used medications. Refill patterns of adult diabetes patients (n = 14,349) prescribed cardiometabolic therapies were studied. We evaluated various grace periods (30-300 days) to identify medication nonpersistence, which is defined as a gap between refills that exceeds a threshold equal to the last days' supply dispensed plus a grace period plus days of stockpiled medication. Since data on medication stockpiles are typically unavailable for ongoing users, we compared nonpersistence to rates calculated using algorithms that ignored stockpiles. When using grace periods equal to or greater than the number of days' supply dispensed (i.e., at least 100 days), this novel algorithm for medication nonpersistence gave consistent results whether or not it accounted for days of stockpiled medication. The agreement (Kappa coefficients) between nonpersistence rates using algorithms with versus without stockpiling improved with longer grace periods and ranged from 0.63 (for 30 days) to 0.98 (for a 300-day grace period). Our method has utility for health care operations and research in prevalent (ongoing) and new user cohorts. The algorithm detects a subset of patients with inadequate medication-taking behavior not identified as primary nonadherent or secondary nonadherent. Healthcare systems can most comprehensively identify patients with short- or long-term medication underutilization by identifying primary nonadherence, secondary nonadherence, and nonpersistence. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email:
    Journal of the American Medical Informatics Association 06/2015; 22(5). DOI:10.1093/jamia/ocv054 · 3.50 Impact Factor
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    ABSTRACT: Objectives To investigate the prevalence, predictors, and costs associated with unused results from self-monitoring of blood glucose (SMBG). Study Design Observational cohort study. Methods We studied 7320 patients with type 2 diabetes mellitus who were not prescribed insulin and who reported SMBG. Patients reported whether they used SMBG results to make adjustments to diet, exercise, or medicines; and whether their physician/provider reviewed their SMBG results. We categorized SMBG results as "used" (by patient and/or provider) or "unused" (not used by either patient or provider). Results SMBG results were unused by patient and provider in 15.2% of patients. In separate models adjusted for demographic and clinical differences, major predictors of SMBG without patient or physician using the results included a patient reporting that diabetes was not a high priority (relative risk [RR], 1.81; 95% CI, 1.58-2.07); the physician not engaging in shared decision making (RR, 1.66; 95% CI, 1.46-1.90); and no healthcare professional teaching the patient how to adjust diet/medicines based on SMBG results in the past year (RR, 2.27; 95% CI, 2.00-2.57). Patients with unused results were dispensed 171 ± 191 test strips per year at an estimated annual cost of $168. Conclusions Nearly 1 in 6 non-insulin-treated patients practiced SMBG without either the patient or physician using the results. This represents a wasteful and ineffective practice for patients and health systems alike. Our results suggest that the decision to initiate and continue SMBG must be made in concert with the patient's own priorities, and, if prescribed, SMBG requires effective patient provider communication and patient education.
    The American journal of managed care 04/2015; 21(2):e119-29. · 2.26 Impact Factor
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    ABSTRACT: Diabetes is a leading cause of chronic kidney disease (CKD). Different methods of CKD ascertainment may impact prevalence estimates. We used data from 11 integrated health systems in the United States to estimate CKD prevalence in adults with diabetes (2005-2011), and compare the effect of different ascertainment methods on prevalence estimates. We used the SUPREME-DM DataLink (n=879,312) to estimate annual CKD prevalence. Methods of CKD ascertainment included: diagnosis codes alone, impaired estimated glomerular filtration rate (eGFR) alone (eGFR<60mL/min/1.73m(2)), albuminuria alone (spot urine albumin creatinine ratio>30mg/g or equivalent), and combinations of these approaches. CKD prevalence was 20.0% using diagnosis codes, 17.7% using impaired eGFR, 11.9% using albuminuria, and 32.7% when one or more method suggested CKD. The criteria had poor concordance. After age- and sex-standardization to the 2010 U.S. Census population, prevalence using diagnosis codes increased from 10.7% in 2005 to 14.3% in 2011 (P<0.001). The prevalence using eGFR decreased from 9.7% in 2005 to 8.6% in 2011 (P<0.001). Our data indicate that CKD prevalence and prevalence trends differ according to the CKD ascertainment method, highlighting the necessity for multiple sources of data to accurately estimate and track CKD prevalence. Copyright © 2015. Published by Elsevier Inc.
    Journal of diabetes and its complications 04/2015; 29(5). DOI:10.1016/j.jdiacomp.2015.04.007 · 3.01 Impact Factor
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    ABSTRACT: In previous research, neighborhood deprivation was positively associated with body mass index (BMI) among adults with diabetes. We assessed whether the association between neighborhood deprivation and BMI is attributable, in part, to geographic variation in the availability of healthful and unhealthful food vendors. Subjects were 16,634 participants of the Diabetes Study of Northern California, a multiethnic cohort of adults living with diabetes. Neighborhood deprivation and healthful (supermarket and produce) and unhealthful (fast food outlets and convenience stores) food vendor kernel density were calculated at each participant's residential block centroid. We estimated the total effect, controlled direct effect, natural direct effect, and natural indirect effect of neighborhood deprivation on BMI. Mediation effects were estimated using G-computation, a maximum likelihood substitution estimator of the G-formula that allows for complex data relations such as multiple mediators and sequential causal pathways. We estimated that if neighborhood deprivation was reduced from the most deprived to the least deprived quartile, average BMI would change by -0.73 units (95% confidence interval: -1.05, -0.32); however, we did not detect evidence of mediation by food vendor density. In contrast to previous findings, a simulated reduction in neighborhood deprivation from the most deprived to the least deprived quartile was associated with dramatic declines in both healthful and unhealthful food vendor density. Availability of food vendors, both healthful and unhealthful, did not appear to explain the association between neighborhood deprivation and BMI in this population of adults with diabetes.
    Epidemiology (Cambridge, Mass.) 03/2015; 26(3). DOI:10.1097/EDE.0000000000000271 · 6.20 Impact Factor

  • Journal of the American College of Cardiology 03/2015; 65(10):A1341. DOI:10.1016/S0735-1097(15)61341-9 · 16.50 Impact Factor
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    ABSTRACT: Background: The Centers for Medicare and Medicaid Services provide significant incentives to health plans that score well on Medicare STAR metrics for cardiovascular disease risk factor medication adherence. Information on modifiable health system-level predictors of adherence can help clinicians and health plans develop strategies for improving Medicare STAR scores, and potentially improve cardiovascular disease outcomes. Objective: To examine the association of Medicare STAR adherence metrics with system-level factors. Research design: A cross-sectional study. Subjects: A total of 129,040 diabetes patients aged 65 years and above in 2010 from 3 Kaiser Permanente regions. Measures: Adherence to antihypertensive, antihyperlipidemic, and oral antihyperglycemic medications in 2010, defined by Medicare STAR as the proportion of days covered ≥ 80%. Results: After controlling for individual-level factors, the strongest predictor of achieving STAR-defined medication adherence was a mean prescribed medication days' supply of > 90 days (RR=1.61 for antihypertensives, oral antihyperglycemics, and statins; all P < 0.001). Using mail order pharmacy to fill medications > 50% of the time was independently associated with better adherence with these medications (RR = 1.07, 1.06, 1.07; P < 0.001); mail order use had an increased positive association among black and Hispanic patients. Medication copayments ≤ $10 for 30 days' supply (RR = 1.02, 1.02, 1.02; P < 0.01) and annual individual out-of-pocket maximums ≤ $2000 (RR = 1.02, 1.01, 1.02; P < 0.01) were also significantly associated with higher adherence for all 3 therapeutic groupings. Conclusions: Greater medication days' supply and mail order pharmacy use, and lower copayments and out-of-pocket maximums, are associated with better Medicare STAR adherence. Initiatives to improve adherence should focus on modifiable health system-level barriers to obtaining evidence-based medications.
    Medical Care 02/2015; 53(4). DOI:10.1097/MLR.0000000000000328 · 3.23 Impact Factor
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    ABSTRACT: The objective of this study was to assess the incidence of major cardiovascular (CV) hospitalization events and all-cause deaths among adults with diabetes with or without CV disease (CVD) associated with inadequately controlled glycated hemoglobin (A1C), high LDL cholesterol (LDL-C), high blood pressure (BP), and current smoking. Study subjects included 859,617 adults with diabetes enrolled for more than 6 months during 2005-2011 in a network of 11 U.S. integrated health care organizations. Inadequate risk factor control was classified as LDL-C ≥100 mg/dL, A1C ≥7% (53 mmol/mol), BP ≥140/90 mm Hg, or smoking. Major CV events were based on primary hospital discharge diagnoses for myocardial infarction (MI) and acute coronary syndrome (ACS), stroke, or heart failure (HF). Five-year incidence rates, rate ratios, and average attributable fractions were estimated using multivariable Poisson regression models. Mean (SD) age at baseline was 59 (14); 48% of subjects were female, 45% were white, and 31% had CVD. Mean follow-up was 59 months. Event rates per 100 person-years for adults with diabetes and CVD versus those without CVD were 6.0 vs. 1.7 for MI/ACS, 5.3 vs. 1.5 for stroke, 8.4 vs. 1.2 for HF, and 18.1 vs. 5.0 for all-cause mortality. The percentages of CV events and deaths associated with inadequate risk factor control were 11% and 3%, respectively, for those with CVD and 34% and 7%, respectively, for those without CVD. Additional attention to traditional CV risk factors could yield further substantive reductions in CV events and mortality in adults with diabetes. © 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.
    Diabetes Care 02/2015; 38(5). DOI:10.2337/dc14-1877 · 8.42 Impact Factor
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    ABSTRACT: The aim of this study was to evaluate ethnic differences in burden of prevalent geriatric conditions and diabetic complications among older, insured adults with diabetes. An observational study was conducted among 115,538 diabetes patients, aged ≥60, in an integrated health care system with uniform access to care. Compared with Whites, Asians and Filipinos were more likely to be underweight but had substantively lower prevalence of falls, urinary incontinence, polypharmacy, depression, and chronic pain, and were least likely of all groups to have at least one geriatric condition. African Americans had significantly lower prevalence of incontinence and falls, but higher prevalence of dementia; Latinos had a lower prevalence of falls. Except for end-stage renal disease (ESRD), Whites tended to have the highest rates of prevalent diabetic complications. Among these insured older adults, ethnic health patterns varied substantially; differences were frequently small and rates were often better among select minority groups, suggesting progress toward the Healthy People 2020 objective to reduce health disparities. © The Author(s) 2015.
    Journal of Aging and Health 02/2015; 27(5). DOI:10.1177/0898264315569455 · 1.56 Impact Factor
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    ABSTRACT: Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol l(-1), P=3.4 × 10(-12)), T2D risk (OR[95%CI]=0.86[0.76-0.96], P=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose(-1), P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l(-1), P=4.3 × 10(-4)). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l(-1), P=1.3 × 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
    Nature Communications 01/2015; 6:5897. DOI:10.1038/ncomms6897 · 11.47 Impact Factor
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    ABSTRACT: Background: Data-sharing is encouraged to fulfill the ethical responsibility to transform research data into public health knowledge, but data sharing carries risks of improper disclosure and potential harm from release of individually identifiable data. Methods: The study objective was to develop and implement a novel method for scientific collaboration and data sharing which distributes the analytic burden while protecting patient privacy. A procedure was developed where in an investigator who is external to an analytic coordinating center (ACC) can conduct original research following a protocol governed by a Publications and Presentations (P&P) Committee. The collaborating investigator submits a study proposal and, if approved, develops the analytic specifications using existing data dictionaries and templates. An original data set is prepared according to the specifications and the external investigator is provided with a complete but de-identified and shuffled data set which retains all key data fields but which obfuscates individually identifiable data and patterns; this" scrambled data set" provides a "sandbox" for the external investigator to develop and test analytic code for analyses. The analytic code is then run against the original data at the ACC to generate output which is used by the external investigator in preparing a manuscript for journal submission. Results: The method has been successfully used with collaborators to produce many published papers and conference reports. Conclusion: By distributing the analytic burden, this method can facilitate collaboration and expand analytic capacity, resulting in more science for less money.
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    ABSTRACT: An observational cohort analysis was conducted within the Surveillance, Prevention, and Management of Diabetes Mellitus (SUPREME-DM) DataLink, a consortium of 11 integrated health-care delivery systems with electronic health records in 10 US states. Among nearly 7 million adults aged 20 years or older, we estimated annual diabetes incidence per 1,000 persons overall and by age, sex, race/ethnicity, and body mass index. We identified 289,050 incident cases of diabetes. Age- and sex-adjusted population incidence was stable between 2006 and 2010, ranging from 10.3 per 1,000 adults (95% confidence interval (CI): 9.8, 10.7) to 11.3 per 1,000 adults (95% CI: 11.0, 11.7). Adjusted incidence was significantly higher in 2011 (11.5, 95% CI: 10.9, 12.0) than in the 2 years with the lowest incidence. A similar pattern was observed in most prespecified subgroups, but only the differences for persons who were not white were significant. In 2006, 56% of incident cases had a glycated hemoglobin (hemoglobin A1c) test as one of the pair of events identifying diabetes. By 2011, that number was 74%. In conclusion, overall diabetes incidence in this population did not significantly increase between 2006 and 2010, but increases in hemoglobin A1c testing may have contributed to rising diabetes incidence among nonwhites in 2011. © The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail:
    American Journal of Epidemiology 12/2014; 181(1). DOI:10.1093/aje/kwu255 · 5.23 Impact Factor
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    ABSTRACT: The role that environmental factors, such as neighborhood socioeconomics, food, and physical environment, play in the risk of obesity and chronic diseases is not well quantified. Understanding how spatial distribution of disease risk factors overlap with that of environmental (contextual) characteristics may inform health interventions and policies aimed at reducing the environment risk factors. We evaluated the extent to which spatial clustering of extreme body mass index (BMI) values among a large sample of adults with diabetes was explained by individual characteristics and contextual factors. We quantified spatial clustering of BMI among 15,854 adults with diabetes from the Diabetes Study of Northern California (DISTANCE) cohort using the Global and Local Moran's I spatial statistic. As a null model, we assessed the amount of clustering when BMI values were randomly assigned. To evaluate predictors of spatial clustering, we estimated two linear models to estimate BMI residuals. First we included individual factors (demographic and socioeconomic characteristics). Then we added contextual factors (neighborhood deprivation, food environment) that may be associated with BMI. We assessed the amount of clustering that remained using BMI residuals. Global Moran's I indicated significant clustering of extreme BMI values; however, after accounting for individual socioeconomic and demographic characteristics, there was no longer significant clustering. Twelve percent of the sample clustered in extreme high or low BMI clusters, whereas, only 2.67% of the sample was clustered when BMI values were randomly assigned. After accounting for individual characteristics, we found clustering of 3.8% while accounting for neighborhood characteristics resulted in 6.0% clustering of BMI. After additional adjustment of neighborhood characteristics, clustering was reduced to 3.4%, effectively accounting for spatial clustering of BMI. We found substantial clustering of extreme high and low BMI values in Northern California among adults with diabetes. Individual characteristics explained somewhat more of clustering of the BMI values than did neighborhood characteristics. These findings, although cross-sectional, may suggest that selection into neighborhoods as the primary explanation of why individuals with extreme BMI values live close to one another. Further studies are needed to assess causes of extreme BMI clustering, and to identify any community level role to influence behavior change.
    International Journal of Health Geographics 12/2014; 13(1):48. DOI:10.1186/1476-072X-13-48 · 2.62 Impact Factor
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    ABSTRACT: Objective: To estimate the incidence of remission in adults with type 2 diabetes not treated with bariatric surgery and to identify variables associated with remission. Research design and methods: We quantified the incidence of diabetes remission and examined its correlates among 122,781 adults with type 2 diabetes in an integrated healthcare delivery system. Remission required the absence of ongoing drug therapy and was defined as follows: 1) partial: at least 1 year of subdiabetic hyperglycemia (hemoglobin A1c [HbA₁c] level 5.7-6.4% [39-46 mmol/mol]); 2) complete: at least 1 year of normoglycemia (HbA₁c level <5.7% [<39 mmol/mol]); and 3) prolonged: complete remission for at least 5 years. Results: The incidence density (remissions per 1,000 person-years; 95% CI) of partial, complete, or prolonged remission was 2.8 (2.6-2.9), 0.24 (0.20-0.28), and 0.04 (0.01-0.06), respectively. The 7-year cumulative incidence of partial, complete, or prolonged remission was 1.47% (1.40-1.54%), 0.14% (0.12-0.16%), and 0.007% (0.003-0.020%), respectively. The 7-year cumulative incidence of achieving any remission was 1.60% in the whole cohort (1.53-1.68%) and 4.6% in the subgroup with new-onset diabetes (<2 years since diagnosis) (4.3-4.9%). After adjusting for demographic and clinical characteristics, correlates of remission included age >65 years, African American race, <2 years since diagnosis, baseline HbA₁c level <5.7% (<39 mmol/mol), and no diabetes medication at baseline. Conclusions: In community settings, remission of type 2 diabetes does occur without bariatric surgery, but it is very rare.
    Diabetes Care 09/2014; 37(12). DOI:10.2337/dc14-0874 · 8.42 Impact Factor
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    ABSTRACT: Objective To assess the impact of a pharmacy benefit change on mail order pharmacy (MOP) uptake.Data Sources/Study SettingRace-stratified, random sample of diabetes patients in an integrated health care delivery system.Study DesignIn this natural experiment, we studied the impact of a pharmacy benefit change that conditionally discounted medications if patients used MOP and prepaid two copayments. We compared MOP uptake among those exposed to the benefit change (n = 2,442) and the reference group with no benefit change (n = 8,148), and estimated differential MOP uptake across social strata using a difference-in-differences framework.Data Collection/Extraction Methods Ascertained MOP uptake (initiation among previous nonusers).Principal FindingsThirty percent of patients started using MOP after receiving the benefit change versus 9 percent uptake among the reference group (p < .0001). After adjustment, there was a 26 percentage point greater MOP uptake (benefit change effect). This benefit change effect was significantly smaller among patients with inadequate health literacy (15 percent less), limited English proficiency (14 percent less), and among Latinos and Asians (24 and 16 percent less compared to Caucasians).Conclusions Conditionally discounting medications delivered by MOP effectively stimulated MOP uptake overall, but it unintentionally widened previously existing social gaps in MOP use because it stimulated less MOP uptake in vulnerable populations.
    Health Services Research 08/2014; 50(2). DOI:10.1111/1475-6773.12223 · 2.78 Impact Factor

Publication Stats

9k Citations
1,132.21 Total Impact Points


  • 1997-2015
    • Kaiser Permanente
      Oakland, California, United States
  • 2008-2013
    • University of Washington Seattle
      • Department of Epidemiology
      Seattle, Washington, United States
  • 2009
    • Centers for Disease Control and Prevention
      • Division of Diabetes Translation
      Druid Hills, GA, United States
  • 2007
    • California State University, Los Angeles
      Los Ángeles, California, United States
  • 2006
    • University of Lausanne
      • Department of Community Health and Medicine
      Lausanne, VD, Switzerland
    • University of California, San Francisco
      • Center for Vulnerable Populations (CVP)
      San Francisco, California, United States
  • 2005
    • Morehouse School of Medicine
      Atlanta, Georgia, United States
  • 1996-2005
    • University of Texas at San Antonio
      San Antonio, Texas, United States
  • 2004
    • University of Kuopio
      Kuopio, Northern Savo, Finland
    • University of Toronto
      • Department of Medicine
      Toronto, Ontario, Canada
  • 2003
    • Indiana University-Purdue University Indianapolis
      Indianapolis, Indiana, United States
  • 2001
    • Permanente Medical Group
      Pasadena, California, United States