Andrew J Karter

Kaiser Permanente, Oakland, California, United States

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Publications (175)1078.17 Total impact

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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: journals.permissions@oup.com.
    Journal of the American Medical Informatics Association 06/2015; DOI:10.1093/jamia/ocv054 · 3.93 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 · 1.93 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 · 6.18 Impact Factor
  • Journal of the American College of Cardiology 03/2015; 65(10):A1341. DOI:10.1016/S0735-1097(15)61341-9 · 15.34 Impact Factor
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    ABSTRACT: 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. To examine the association of Medicare STAR adherence metrics with system-level factors. A cross-sectional study. A total of 129,040 diabetes patients aged 65 years and above in 2010 from 3 Kaiser Permanente regions. Adherence to antihypertensive, antihyperlipidemic, and oral antihyperglycemic medications in 2010, defined by Medicare STAR as the proportion of days covered ≥80%. 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. 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.This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivitives 3.0 License, where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially. http://creativecommons.org/licenses/by-nc-nd/3.0.
    Medical Care 02/2015; DOI:10.1097/MLR.0000000000000328 · 2.94 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 · 8.57 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; DOI:10.1177/0898264315569455 · 1.56 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 01/2015; 21(2):e119-29. · 2.17 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 · 10.74 Impact Factor
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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: journals.permissions@oup.com.
    American Journal of Epidemiology 12/2014; DOI:10.1093/aje/kwu255 · 4.98 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: 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.
    Diabetes Care 09/2014; 37(12). DOI:10.2337/dc14-0874 · 8.57 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 · 2.49 Impact Factor
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    ABSTRACT: Purpose Inadequate literacy is common among patients with diabetes and may lead to adverse outcomes. The authors reviewed the relationship between literacy and health outcomes in patients with diabetes and potential interventions to improve outcomes. Methods We reviewed 79 articles covering 3 key domains: (1) evaluation of screening tools to identify inadequate literacy and numeracy, (2) the relationships of a range of diabetes-related health outcomes with literacy and numeracy, and (3) interventions to reduce literacy-related differences in health outcomes. Results Several screening tools are available to assess patients' print literacy and numeracy skills, some specifically addressing diabetes. Literacy and numeracy are consistently associated with diabetes-related knowledge. Some studies suggest literacy and numeracy are associated with intermediate outcomes, including self-efficacy, communication, and self-care (including adherence), but the relationship between literacy and glycemic control is mixed. Few studies have assessed more distal health outcomes, including diabetes-related complications, health care utilization, safety, or quality of life, but available studies suggest low literacy may be associated with increased risk of complications, including hypoglycemia. Several interventions appear to be effective in improving diabetes-related outcomes regardless of literacy status, but it is unclear if these interventions can reduce literacy-related differences in outcomes. Conclusions Low literacy is associated with less diabetes-related knowledge and may be related to other important health outcomes. Further studies are needed to better elucidate pathways by which literacy skills affect health outcomes. Promising interventions are available to improve diabetes outcomes for patients with low literacy; more research is needed to determine their effectiveness outside of research settings.
    The Diabetes Educator 06/2014; 40(5). DOI:10.1177/0145721714540220 · 1.92 Impact Factor
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    ABSTRACT: IMPORTANCE The increasing intensity of diabetes mellitus management over the past decade may have resulted in lower rates of hyperglycemic emergencies but higher rates of hospital admissions for hypoglycemia among older adults. Trends in these hospitalizations and subsequent outcomes are not known. OBJECTIVE To characterize changes in hyperglycemia and hypoglycemia hospitalization rates and subsequent mortality and readmission rates among older adults in the United States over a 12-year period, and to compare these results according to age, sex, and race. DESIGN, SETTING, AND PATIENTS Retrospective observational study using data from 33 952 331 Medicare fee-for-service beneficiaries 65 years or older from 1999 to 2011. MAIN OUTCOMES AND MEASURES Hospitalization rates for hyperglycemia and hypoglycemia, 30-day and 1-year mortality rates, and 30-day readmission rates. RESULTS A total of 279 937 patients experienced 302 095 hospitalizations for hyperglycemia, and 404 467 patients experienced 429 850 hospitalizations for hypoglycemia between 1999 and 2011. During this time, rates of admissions for hyperglycemia declined by 38.6% (from 114 to 70 admissions per 100 000 person-years), while admissions for hypoglycemia increased by 11.7% (from 94 to 105 admissions per 100 000 person-years). In analyses designed to account for changing diabetes mellitus prevalence, admissions for hyperglycemia and hypoglycemia declined by 55.2% and 9.5%, respectively. Trends were similar across age, sex, and racial subgroups, but hypoglycemia rates were 2-fold higher for older patients (≥75 years) when compared with younger patients (65-74 years), and admission rates for both hyperglycemia and hypoglycemia were 4-fold higher for black patients compared with white patients. The 30-day and 1-year mortality and 30-day readmission rates improved during the study period and were similar after an index hospitalization for either hyperglycemia or hypoglycemia (5.4%, 17.1%, and 15.3%, respectively, after hyperglycemia hospitalizations in 2010; 4.4%, 19.9%, and 16.3% after hypoglycemia hospitalizations). CONCLUSIONS AND RELEVANCE Hospital admission rates for hypoglycemia now exceed those for hyperglycemia among older adults. Although admissions for hypoglycemia have declined modestly since 2007, rates among black Medicare beneficiaries and those older than 75 years remain high. Hospital admissions for severe hypoglycemia seem to pose a greater health threat than those for hyperglycemia, suggesting new opportunities for improvement in care of persons with diabetes mellitus.
    JAMA Internal Medicine 05/2014; 174(7). DOI:10.1001/jamainternmed.2014.1824 · 13.25 Impact Factor
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    ABSTRACT: In chronic illness self-care, social support may influence some health behaviors more than others. Examine social support's association with seven individual chronic illness self-management behaviors: two healthy "lifestyle" behaviors (physical activity, diet) and five more highly skilled and diabetes-specific (medical) behaviors (checking feet, oral medication adherence, insulin adherence, self-monitored blood glucose, primary care appointment attendance). Using cross-sectional administrative and survey data from 13,366 patients with type 2 diabetes, Poisson regression models estimated the adjusted relative risks (ARR) of practicing each behavior at higher vs lower levels of social support. Higher emotional support and social network scores were significantly associated with increased ARR of both lifestyle behaviors. Both social support measures were also associated with increased ARR for checking feet. Neither measure was significantly associated with other medical behaviors. Findings suggest that social support diminished in importance as self-care progresses from lifestyle to more skilled "medical" behaviors.
    Annals of Behavioral Medicine 05/2014; 48(3). DOI:10.1007/s12160-014-9623-x · 4.20 Impact Factor
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    ABSTRACT: Objectives To compare the strength of the association between depression and mortality between elderly and younger individuals with diabetes mellitus.DesignA survival analysis conducted in a longitudinal cohort study of persons with diabetes mellitus to test the association between depression and mortality in older (≥65) and younger (18–65) adults.SettingManaged care.ParticipantsPersons aged 18 and older with diabetes mellitus who participated in the Wave 2 survey of the Translating Research Into Action for Diabetes (TRIAD) Study (N = 3,341).MeasurementsThe primary outcome was mortality risk, which was measured as days until death using linked data from the National Death Index. Depression was measured using the Patient Health Questionnaire.ResultsAfter controlling for age, sex, race and ethnicity, income, and other comorbidities, mortality risk in persons with diabetes mellitus was 49% higher in those with depression than in those without, although results varied according to age. After controlling for the same variables, mortality risk in persons aged 65 and older with depression was 78% greater than in those without. For those younger than 65, the effect of depression on mortality was smaller and not statistically significant.Conclusion This analysis suggests that the effect of depression on mortality in persons with diabetes mellitus is most significant for older adults. Because there is evidence in the literature that treatment of depression in elderly adults can lead to lower mortality, these results may suggest that older adults with diabetes mellitus should be considered a high-priority population for depression screening and treatment.
    Journal of the American Geriatrics Society 05/2014; 62(6). DOI:10.1111/jgs.12833 · 4.22 Impact Factor
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    ABSTRACT: Depression and adherence to antidepressant treatment are important clinical concerns in diabetes care. While patient-provider communication patterns have been associated with adherence for cardiometabolic medications, it is unknown whether interpersonal aspects of care impact antidepressant medication adherence. To determine whether shared decision-making, patient-provider trust, or communication are associated with early stage and ongoing antidepressant adherence. Observational new prescription cohort study. Kaiser Permanente Northern California. One thousand five hundred twenty-three adults with type 2 diabetes who completed a survey in 2006 and received a new antidepressant prescription during 2006-2010. Exposures included items based on the Trust in Physicians and Interpersonal Processes of Care instruments and the Consumer Assessment of Healthcare Providers and Systems (CAHPS) communication scale. Measures of adherence were estimated using validated methods with physician prescribing and pharmacy dispensing data: primary non-adherence (medication never dispensed), early non-persistence (dispensed once, never refilled), and new prescription medication gap (NPMG; proportion of time without medication during 12 months after initial prescription). After adjusting for potential confounders, patients' perceived lack of shared decision-making was significantly associated with primary non-adherence (RR = 2.42, p < 0.05), early non-persistence (RR = 1.34, p < 0.01) and NPMG (estimated 5 % greater gap in medication supply, p < 0.01). Less trust in provider was significantly associated with early non-persistence (RRs 1.22-1.25, ps < 0.05) and NPMG (estimated NPMG differences 5-8 %, ps < 0.01). All patients were insured and had consistent access to and quality of care. Patients' perceptions of their relationships with providers, including lack of shared decision-making or trust, demonstrated strong associations with antidepressant non-adherence. Further research should explore whether interventions for healthcare providers and systems that foster shared decision-making and trust might also improve medication adherence.
    Journal of General Internal Medicine 04/2014; 29(8). DOI:10.1007/s11606-014-2845-6 · 3.42 Impact Factor
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    ABSTRACT: Background: Persons with type 2 diabetes are at an increased risk of dementia compared to those without, but the etiology of this increased risk is unclear. Objective: Cerebral microvascular disease may mediate the link between diabetes and dementia. Given the anatomical and physiological similarities between cerebral and retinal microvessels, we examined the longitudinal association between diabetic retinal disease and dementia in patients with type 2 diabetes. Methods: Longitudinal cohort study of 29,961 patients with type 2 diabetes aged ≥60 years. Electronic medical records were used to collect diagnoses and treatment of severe diabetic retinal disease (i.e., diabetic proliferative retinopathy and macular edema) between 1996-1998 and dementia diagnoses for the next ten years (1998-2008). The association between diabetic retinal disease and dementia was evaluated by Cox proportional hazard models adjusted for sociodemographics, as well as diabetes-specific (e.g., diabetes duration, pharmacotherapy, HbA1c, hypoglycemia, hyperglycemia) and vascular (e.g., vascular disease, smoking, body mass index) factors. Results: 2,008 (6.8%) patients had severe diabetic retinal disease at baseline and 5,173 (17.3%) participants were diagnosed with dementia during follow-up. Those with diabetic retinal disease had a 42% increased risk of incident dementia (demographics adjusted Hazards Ratio (HR) = 1.42, 95% Confidence Interval (CI) 1.27, 1.58); further adjustment for diabetes-specific (HR1.29; 95%CI 1.14,1.45) and vascular-related disease conditions (HR 1.35; 95%CI 1.21,1.52) attenuated the relation slightly. Conclusion: Diabetic patients with severe diabetic retinal disease have an increased risk of dementia. This may reflect a causal link between microvascular disease and dementia.
    Journal of Alzheimer's disease: JAD 03/2014; 42. DOI:10.3233/JAD-132570 · 3.61 Impact Factor
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    ABSTRACT: Background. Social risk factors for hypoglycemia are not well understood. Methods. Cross-sectional analysis from the DISTANCE study, a multi-language, ethnically-stratified random sample of adults in the Kaiser Permanente Northern California diabetes registry, conducted in 2005-2006 (response rate 62%). Exposures were income and educational attainment; outcome was patient report of severe hypoglycemia. To test the association, we used multivariable logistic regression to adjust for demographic and clinical factors. Results. 14,357 patients were included. Reports of severe hypoglycemia were common (11%), and higher in low-income vs. high-income (16% vs. 8.8) and low-education vs. high-education (11.9% vs. 8.9%) groups. In multivariable analysis, incomes of less than $15,000 (OR 1.51 95%CI 1.19-1.91), $15,000-$24,999 (OR 1.57 95%CI 1.27-1.94), and high school or less education (OR 1.42, 95% CI 1.24-1.63) were associated with increased hypoglycemia, similar to insulin use (OR 1.44 95%CI 1.19-1.74). Conclusions. Low income and educational attainment are important risk factors for hypoglycemia.
    Journal of Health Care for the Poor and Underserved 01/2014; 25(2):478-90. DOI:10.1353/hpu.2014.0106 · 1.10 Impact Factor

Publication Stats

7k Citations
1,078.17 Total Impact Points

Institutions

  • 1997–2015
    • Kaiser Permanente
      • Department of Endocrinology
      Oakland, California, United States
    • Wake Forest University
      • Department of Public Health Sciences
      Winston-Salem, North Carolina, United States
  • 2013
    • University of Colorado
      Denver, Colorado, United States
  • 2009–2013
    • University of Washington Seattle
      • Department of Epidemiology
      Seattle, Washington, United States
    • Centers for Disease Control and Prevention
      • Division of Diabetes Translation
      Druid Hills, GA, United States
  • 2003–2013
    • University of California, San Francisco
      • • Center for Vulnerable Populations (CVP)
      • • Division of General Internal Medicine
      San Francisco, California, United States
  • 2003–2010
    • University of California, Los Angeles
      • Department of Medicine
      Los Angeles, CA, 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
  • 2003–2006
    • Indiana University-Purdue University Indianapolis
      Indianapolis, Indiana, 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
  • 2002
    • Wake Forest School of Medicine
      • Division of Public Health Sciences
      Winston-Salem, NC, United States
  • 2001
    • Permanente Medical Group
      Pasadena, California, United States
  • 1999
    • University of North Carolina at Chapel Hill
      North Carolina, United States