Obesity Disparities Among Adult Single-Race and Multiracial Asian and Pacific Islander Populations.

Importance: Despite increasing numbers of multiracial individuals, they are often excluded in studies or aggregated within larger race and ethnicity groups due to small sample sizes. Objective: To examine disparities in the prevalence of obesity among single-race and multiracial Asian and Pacific Islander individuals compared with non-Hispanic White (hereafter, White) individuals. Design, Setting, and Participants: This cross-sectional study used electronic health record (EHR) data linked to social determinants of health and health behavior data for adult (age ≥18 years) members of 2 large health care systems in California and Hawai'i who had at least 1 ambulatory visit to a primary care practitioner between January 1, 2006, and December 31, 2018. Data were analyzed from October 31, 2022, to July 31, 2023. Exposure: Self-identified race and ethnicity provided in the EHR as a single-race category (Asian Indian, Chinese, Filipino, Japanese, Native Hawaiian only, Other Pacific Islander, or White) or a multiracial category (Asian and Pacific Islander; Asian, Pacific Islander, and White; Asian and White; or Pacific Islander and White). Main Outcomes and Measures: The main outcome was obesity (body mass index [BMI] ≥30.0), based on last measured height and weight from the EHR. Logistic regression was used to examine the association between race and ethnicity and odds of obesity. Results: A total of 5229 individuals (3055 [58.4%] male; mean [SD] age, 70.73 [11.51] years) were examined, of whom 444 (8.5%) were Asian Indian; 1091 (20.9%), Chinese; 483 (9.2%), Filipino; 666 (12.7%), Japanese; 91 (1.7%), Native Hawaiian; 95 (1.8%), Other Pacific Islander; and 888 (17.0%), White. The percentages of individuals who identified as multiracial were as follows: 417 (8.0%) were Asian and Pacific Islander; 392 (7.5%), Asian, Pacific Islander, and White; 248 (4.7%), Asian and White; and 414 (7.9%), Pacific Islander and White. A total of 1333 participants (25.5%) were classified as having obesity based on standard BMI criteria. Obesity was highest among people who identified as Asian, Pacific Islander, and White (204 of 392 [52.0%]) followed by those who identified as Other Pacific Islander (47 of 95 [49.5%]), Native Hawaiian (44 of 91 [48.4%]), and Pacific Islander and White (186 of 414 [44.9%]). After accounting for demographic, socioeconomic, and health behavior factors, people who identified as Asian, Pacific Islander, and White (odds ratio [OR], 1.80; 95% CI, 1.37-2.38) or Pacific Islander and White (OR, 1.55; 95% CI, 1.18-2.04) had increased odds of obesity compared with White individuals. All single-race Asian groups had lower odds of obesity compared with White individuals: Asian Indian (OR, 0.29; 95% CI, 0.20-0.40), Chinese (OR, 0.22; 95% CI, 0.17-0.29), Filipino (OR, 0.46; 95% CI, 0.35-0.62), and Japanese (OR, 0.38, 95% CI, 0.29-0.50). Conclusions and Relevance: In this study, multiracial Asian and Pacific Islander individuals had an increased prevalence of obesity compared with many of their single-race counterparts. As the number of multiracial individuals increases, it will be important for clinical and public health systems to track disparities in these populations.

Herpes zoster diagnosis and treatment in relation to incident dementia: A population-based retrospective matched cohort study.

BACKGROUND: Evidence suggests that some infectious diseases, such as herpes zoster (HZ), are associated with elevated risk of subsequent dementia, while certain anti-viral medications are associated with lower risk. We sought to evaluate associations between HZ diagnosis and treatment with incident dementia in a large, retrospective matched cohort. METHODS: Using ICD-9 and ICD-10 diagnosis codes in electronic medical records, we identified members of Kaiser Permanente Northwest age 50 and older from 2000-2019 with a HZ diagnosis during this period. A comparison group without HZ diagnosis was individually matched 3:1 on age at HZ diagnosis date (index date), sex, and membership length prior to index date. We excluded subjects with dementia diagnosed before the index date. Antiherpetic medication was identified using pharmacy fills 1 month before to 12 months after the index date. We employed survival analysis to examine the associations between dementia and HZ diagnosis and antiherpetic medication, adjusting multivariable models for demographic and clinical factors. We stratified on age and sex and conducted a sensitivity analysis with a 5-year lag period. RESULT: The study included 101,328 persons, 25,332 with HZ. Over a median follow-up of 4.8 years, 6,000 developed dementia. HZ diagnosis was not associated with higher hazard of dementia (hazard ratio (HR) = 0.99, 95% CI 0.93-1.05) in the primary analysis. Among persons with HZ diagnoses, the HR for receipt of any antiherpetic medication was 0.79 (95% CI 0.70-0.90) in univariate analysis and 0.88 (95% CI 0.77-1.00) after adjustment for demographic and clinical factors. Dementia was not associated with trends in duration of medication use or cumulative dose. CONCLUSIONS: We found little evidence for an association between HZ diagnosis and dementia overall. Antiherpetic medication prescribed around the time of HZ diagnosis was statistically associated with lower risk of subsequent dementia in some but not all analyses and subgroups.

Opioid-related variables did not improve suicide risk prediction models in samples with mental health diagnoses.

Background: Suicide risk prediction models derived from machine learning of electronic health records and insurance claims are an innovation in suicide prevention. Some models do not include opioid-related variables despite the relationship between opioids and suicide. This study evaluated whether inclusion of opioid-related variables improved suicide risk prediction models developed by the Mental Health Research Network. Methods: Approximately 630 opioid-related variables and interactions terms were introduced into existing suicide prediction models run in datasets of patient visits in mental health care (n = 27,755,401 visits) or primary care when a mental health diagnosis was given (n = 19,340,461 visits). Training and validation datasets were created. LASSO regression with 10-fold validation identified variables to be added to the models. Results: The new models predicting suicide attempts and suicide deaths in the mental health specialty visit sample performed as well as the existing models (new C-statistic for attempts model = 0.855, CI: 0.853-0.857 versus original C-statistic = 0.851, CI 0.848-0.853; death model = 0.868, CI: 0.856-0.879 versus 0.861, CI 0.848-0.875). The new model for suicide death in the primary care sample improved (0.855, CI: 0.837-0.874 versus 0.833, CI 0.813-0.853) while performance of the new model for suicide attempt in that sample degraded (0.843, CI: 0.839-0.847 versus 0.853, CI 0.849-0.857). Limitations: Analyses did not include patients without recent care, data did not include illicit opioid use or unrecognized opioid use disorder. Conclusions: Among patients with mental health diagnoses, inclusion of opioid-related variables did not improve prediction of suicide risk beyond mental health predictors.

First year infant weight trajectories predict overweight/obesity at age 2 in a diverse population.

BACKGROUND: Obesity is emerging as early as two years of age and risk may be elucidated by differences in infant growth trajectories. We examined infant weight gain in the first year of life and association with overweight/obesity at age two. METHODS: In a diverse, population-based cohort study we conducted growth curve analysis using Health Maintenance Organization electronic medical record data from January 1, 2012 through December 31, 2013. RESULTS: Among 930 infants, there was a linear relationship with birth weight and initial weight gain from birth and increased odds of developing overweight/obesity at age two [Odds Ratio OR = 1.001; (95% CI: 1.000-1.002), p = 0.0274] and [OR = 1.009; (1.006-1.01), p = 0.0001) respectively. The odds of becoming overweight/obese at age 2 increased in infants who had slower weight deceleration rates (OR third quartile = 2.78, fourth quartile = 4.3) compared to the first quartile. Other factors associated with overweight/obesity risk at age two included female sex and Native Hawaiian race/ethnicity. CONCLUSIONS: Rate of weight gain in the first year may be an important risk factor for early childhood obesity. A deeper dive into first year growth patterns and related sociocultural and nutritional factors is needed to inform targetable points for intervention.

Kidney disease progression and all-cause mortality across estimated glomerular filtration rate and albuminuria categories among patients with vs. without type 2 diabetes.

BACKGROUND: Studies of progression of kidney dysfunction typically focus on renal replacement therapy or percentage decline in estimated glomerular filtration rate (eGFR) as outcomes. Our aim was to compare real-world patients with and without T2D to estimate progression from and to clinically defined categories of kidney disease and all-cause mortality. METHODS: This was an observational cohort study of 31,931 patients with and 33,201 age/sex matched patients without type 2 diabetes (T2D) who had a serum creatinine and urine albumin-to-creatinine ratio (UACR) or dipstick proteinuria (DP) values. We used the first available serum creatinine value between 2006 and 2012 to calculate baseline eGFR and categorized them and the corresponding UACR/DP values using the Kidney Disease Improving Global Outcomes (KDIGO) categories. To assess our primary outcomes, we extracted probabilities of eGFR progression or mortality from life-table analyses and conducted multivariable Cox regression analyses of relative risk adjusted for age, sex, race/ethnicity, smoking, ischemic heart disease, heart failure, and use of renal-angiotensin-aldosterone system inhibitors. RESULTS: Patterns of eGFR decline were comparable among patients with vs. without T2D with larger percentage declines at higher albuminuria levels across all eGFR categories. eGFR decline was generally larger among T2D patients, particularly in those with severely increased albuminuria. Across all CKD categories, risk of progression to the next higher category of eGFR was substantially increased with increasing albuminuria. For example, the risk was 23.5, 36.2, and 65.1% among T2D patients with eGFR 30-59 ml/min/1.73m2 and UACR < 30, 30-299, and > 300 mg/dL, respectively (p < 0.001). Other comparisons were similarly significant. Among patients with low eGFR and normal to mildly increased albuminuria, the relative risk was up to 8-fold greater for all-cause mortality compared with the non-CKD subgroup (eGFR> 60 ml/min/1.73m2 with normal to mildly increased albuminuria). CONCLUSIONS: Presence of albuminuria was associated with accelerated eGFR decline independent of T2D. Risk for adverse outcomes was remarkably high among patients with CKD and normal to mildly increased albuminuria levels. Independent of T2D or albuminuria, a substantial risk for adverse outcomes exists for CKD patients in a routine care setting.

Correction to: Kidney disease progression and all-cause mortality across estimated glomerular filtration rate and albuminuria categories among patients with vs. without type 2 diabetes.

An amendment to this paper has been published and can be accessed via the original article.

Demographic, Clinical, and Prescribing Characteristics Associated with Future Opioid Use in an Opioid-Naive Population in an Integrated Health System.

INTRODUCTION: Health systems and prescribers need additional tools to reduce the risk of opioid dependence, abuse, and overdose. Identifying opioid-naive individuals who are at risk of opioid dependence could allow for the development of needed interventions. METHODS: We conducted a retrospective cohort analysis of 23,804 adults in an integrated health system who had received a first opioid prescription between 2010 and 2015. We compared the demographic, clinical, and prescribing characteristics of individuals who later received a third opioid dispense at least 27 days later, indicating long-term opioid use, with those who did not. RESULTS: The strongest predictors of continued opioid use were an initial prescription dosage of 90 morphine milligram equivalence or more; prescription of extended-release opioids, rather than short-release; and being prescribed outside of a hospital setting. Patients with a third prescription were also more likely to be older than 45 years, white, and non-Hispanic and to have physical comorbidities or prior substance abuse or mental health diagnoses. DISCUSSION: Our findings are largely consistent with prior research but provide new insight into differences in continued opioid use by opioid type, prescribing location, ethnicity, and comorbidities. Together with previous research, our data support a pattern of higher opioid use among older adults but higher rates of diagnosed opioid abuse among younger adults. CONCLUSIONS: By identifying population characteristics associated with continued opioid use following a first prescription, our data pave the way for quality improvement interventions that target individuals who are at higher risk of opioid dependence.

Fall Ascertainment and Development of a Risk Prediction Model Using Electronic Medical Records.

OBJECTIVES: To examine the use of electronic medical record (EMR) data to ascertain falls and develop a fall risk prediction model in an older population. DESIGN: Retrospective longitudinal study using 10 years of EMR data (2004-2014). A series of 3-year cohorts included members continuously enrolled for a minimum of 3 years, requiring 2 years pre-fall (no previous record of a fall) and a 1-year fall risk period. SETTING: Kaiser Permanente Hawaii, an ambulatory setting. PARTICIPANTS: A total of 57 678 adults, age 60 years and older. MEASUREMENTS: Initial EMR searches were guided by current literature and geriatricians to understand coding sources of falls as our outcome. Falls were captured by two coding sources: International Classification of Diseases, Ninth Revision (ICD-9) codes (E880-889) and/or a fall listed as a "primary reason for visit." A comprehensive list of EMR predictors of falls were included into prediction models enabling statistical subset selection from many variables and modeling by logistic regression. RESULTS: Although 72% of falls in the training data set were coded as "primary reason for visit," 22% of falls were coded as ICD-9 and 6% coded as both. About 80% were reported in face-to-face encounters (eg, emergency department). A total of 2164 individuals had a fall in the risk period. Using the 13 key predictors (age, comorbidities, female sex, other mental disorder, walking issues, Parkinson's disease, urinary incontinence, depression, polypharmacy, psychotropic and anticonvulsant medications, osteoarthritis, osteoporosis) identified through LASSO regression, the final model had a sensitivity of 67%, specificity of 69%, positive predictive value of 8%, negative predictive value of 98%, and area under the curve of .74. CONCLUSION: This study demonstrated how the EMR can be used to ascertain falls and develop a fall risk prediction model with moderate sensitivity/specificity. Concurrent work with clinical providers to enhance fall documentation will improve the ability of the EMR to capture falls and consequently may improve the model to predict fall risk.

Balancing Adherence and Expense: The Cost-Effectiveness of Two-Sample vs One-Sample Fecal Immunochemical Test.

Colorectal cancer (CRC) causes more than 50,000 deaths each year in the United States but early detection through screening yields survival gains; those diagnosed with early stage disease have a 5-year survival greater than 90%, compared to 12% for those diagnosed with late stage disease. Using data from a large integrated health system, this study evaluates the cost-effectiveness of fecal immunochemical testing (FIT), a common CRC screening tool. A probabilistic decision-analytic model was used to examine the costs and outcomes of positive test results from a 1-FIT regimen compared with a 2-FIT regimen. The authors compared 5 diagnostic cutoffs of hemoglobin concentration for each test (for a total of 10 screening options). The principal outcome from the analysis was the cost per additional advanced neoplasia (AN) detected. The authors also estimated the number of cancers detected and life-years gained from detecting AN. The following costs were included: program management of the screening program, patient identification, FIT kits and their processing, and diagnostic colonoscopy following a positive FIT. Per-person costs ranged from $33 (1-FIT at 150ng/ml) to $92 (2-FIT at 50ng/ml) across screening options. Depending on willingness to pay, the 1-FIT 50 ng/ml and the 2-FIT 50 ng/ml are the dominant strategies with cost-effectiveness of $11,198 and $28,389, respectively, for an additional AN detected. The estimates of cancers avoided per 1000 screens ranged from 1.46 to 4.86, depending on the strategy and the assumptions of AN to cancer progression.

Evaluating Atypical Features of Femur Fractures: How Change in Radiological Criteria Influenced Incidence and Demography of Atypical Femur Fractures in a Community Setting.

Identification of atypical femoral fractures (AFFs) can be challenging. To assist in the radiological assessment, an American Society for Bone and Mineral Research (ASBMR) Task Force developed a case definition for AFFs in 2010, revising it in 2013. How the revised definition performs in a community setting compared with the 2010 definition is unknown. We applied the 2013 criteria to 372 femoral fractures that occurred between January 1, 1996, and June 30, 2009, employing two independent expert physician reviewers. We used radiographs that had been categorized in a previous study on the incidence of atypical fractures using 2010 ASMBR criteria (BEAK1). In this follow-up study (BEAK2), the same reviewers reviewed all previously identified femoral shaft fractures (FSFs) (n = 197) and distal femur fractures (n = 131) plus a 15% random sample of intertrochanteric fractures (n = 49). After initial review, agreement between the two reviewers ranged from 63% to 100% for specific features, and 84% of radiographs received the same overall classification. Fewer fractures met the 2013 compared with 2010 ASMBR case definition of AFFs (37 per 2013 criteria versus 74 per 2010 criteria). Forty-three radiographs (58%) categorized as AFFs according to 2010 criteria were no longer AFFs when 2013 criteria were applied, and an additional 12 non-atypical FSFs according to 2010 criteria were reclassified as AFFs according to 2013 criteria. The major cause of AFF reclassification was the change in the definition of transverse configuration. The modification of the comminution, non-traumatic, and periosteal/endosteal thickness criteria resulted in the reclassification of non-atypical FSFs to AFFs. Incidence rate of AFFs according to 2013 ASBMR criteria was lower overall during the 13 years of observation than when the 2010 ASBMR criteria were applied, although we saw a slight increase starting in 2000. As in BEAK1, we found that those with AFFs were younger, more often female, and had a higher exposure rate to bisphosphonates than those with non-atypical FSFs. As we continue to unravel the demographics of those who suffer from AFFs, our study adds information about how the change in criteria influences epidemiological work. © 2017 American Society for Bone and Mineral Research.

The Change in HbA1c Associated with Initial Adherence and Subsequent Change in Adherence among Diabetes Patients Newly Initiating Metformin Therapy.

Introduction. Whether changes in adherence are associated with changes in HbA1c is assumed but not known. Methods. We conducted a observational study of 2,844 type 2 diabetes patients who initiated metformin as their first antihyperglycemic drug. Using HbA1c measures before, 6-12 months after, and up to 3 years after metformin initiation, we analyzed HbA1c change as a function of initial adherence and change in adherence. Results. Compared with no adherence, initial adherence of 50-79% was associated with an adjusted reduction in HbA1c of 0.45% while adherence ≥80% was associated with HbA1c reduction of 0.73%. Change from some initial adherence (1-79%) to total nonadherence was associated with 0.25% increase in HbA1c. Change from some to full adherence was associated with an HbA1c decrease of 0.15%. Those associations were accentuated among patients not in glycemic control: change from some to no adherence was associated with an HbA1c increase of 0.63% and change from some to full adherence was associated with an HbA1c decrease of 0.40%. Conclusions. Initial adherence to newly prescribed metformin therapy produces substantial HbA1c reduction. Among those with modest adherence but suboptimal glycemic control, the difference between moving to full adherence versus nonadherence results in lower HbA1c of one percentage point.

Trimethoprim-sulfonamide use during the first trimester of pregnancy and the risk of congenital anomalies.

BACKGROUND: Sulfonamide antibacterials are widely used in pregnancy, but evidence about their safety is mixed. The objective of this study was to assess the association between first-trimester sulfonamide exposure and risk of specific congenital malformations. METHODS: Mother-infant pairs were selected from a cohort of 1.2 million live-born deliveries (2001-2008) at 11 US health plans comprising the Medication Exposure in Pregnancy Risk Evaluation Program. Mothers with first-trimester trimethoprim-sulfonamide (TMP-SUL) exposures were randomly matched 1:1 to (i) a primary comparison group (mothers exposed to penicillins and/or cephalosporins) and (ii) a secondary comparison group (mothers with no dispensing of an antibacterial, antiprotozoal, or antimalarial medication during the same time period). The outcomes were cardiovascular abnormalities, cleft palate/lip, clubfoot, and urinary tract abnormalities. RESULTS: We first identified 7615 infants in the TMP-SUL exposure group, of which 7595 (99%) were exposed to a combination of TMP-SUL and the remaining 1% to sulfonamides alone. After matching (1:1) to the comparator groups and only including those with complete data on covariates, there were 20 064 (n = 6688 per group) in the primary analyses. Overall, cardiovascular defects (1.52%) were the most common and cleft lip/palate (0.10%) the least common that were evaluated. Compared with penicillin/cephalosporin exposure, and no antibacterial exposure, TMP-SUL exposure was not associated with statistically significant elevated risks for cardiovascular, cleft lip/palate, clubfoot, or urinary system defects. CONCLUSIONS: First-trimester TMP-SUL exposure was not associated with a higher risk of the congenital anomalies studied, compared with exposure to penicillins and/or cephalosporins, or no exposure to antibacterials.

Do patient or provider characteristics impact management of diabetes?

OBJECTIVES: Patients with diabetes often exceed desired glycated hemoglobin (A1C) levels for months prior to medication adjustments. To determine if provider and patient characteristics predict glycemic control and treatment intensification. STUDY DESIGN: Observational retrospective cohort study using electronic medical record data. METHODS: We studied 149 Kaiser Permanente Northwest primary care providers of 14,430 patients with diabetes, of whom 5823 (40.4%) were in optimal control (all A1Cs < 7%) and 2446 (17%) were in poor control (at least 1 A1C > 9%) in 2011. We also identified a subset of 107 primary care providers of 912 patients with diabetes who were initially in optimal control (A1C < 7%) but had a subsequent A1C > 7.5% from 2010 to 2011. We used hierarchical linear modeling to assess both patient and provider characteristics as predictors of glycemic control and treatment intensification after incident hyperglycemia. RESULTS: Patient characteristics associated with optimal control included older age, lower baseline A1C, shorter diabetes duration, and not using insulin (P < .001 for all). The inverse of these variables predicted poor control. No provider characteristics were associated with glycemic control or intensification. Older patients with a greater change in A1C were more likely to have therapy intensified after loss of glycemic control. CONCLUSIONS: Patient, but not provider characteristics, predicted glycemic control and therapy intensification. Improving systems of care such as disease management services may be a better use of resources than focusing on individual providers.

Comparison of Risk of Re-hospitalization, All-Cause Mortality, and Medical Care Resource Utilization in Patients With Heart Failure and Preserved Versus Reduced Ejection Fraction.

Because heart failure (HF) with reduced ejection fraction (HFrEF) and preserved ejection fraction (HFpEF) are different clinical entities with differing demographic characteristics, common HF outcomes may occur at different rates. Comparative outcome studies have been equivocal, and studies comparing resource utilization are scant. We used an observational cohort design to study 6,513 patients hospitalized for HF who had an EF measured during the hospitalization and were discharged alive within 30 days. We excluded 677 patients with borderline EF values (41% to 49%) and categorized the remaining as HFrEF (EF ≤40%, n = 2,205) and HFpEF (EF >50%, n = 3,631). Patients were followed for up to 1 year for all-cause re-hospitalization and mortality and annualized medical resource utilization. Patients with HFrEF and HFpEF experienced similar adjusted incidence rates of re-hospitalization, but those with HFrEF had a 39% increased risk of mortality at 30 days (rate ratio 1.39, 95% confidence interval 1.10 to 1.76) and 25% greater risk at 1 year (rate ratio1.25, 95% confidence interval 1.12 to 1.41). After adjustment for covariates, patients with HFpEF incurred significantly more annualized outpatient visits (21.5 vs 20.1, p = 0.002) and emergency room visits (3.24 vs 2.94, p = 0.002) than those with HFrEF, but absolute differences were small. High inpatient and pharmacy utilization did not differ. Our study suggests that whether a patient has HFrEF or HFpEF has little bearing on risk of re-hospitalization or inpatient resource utilization in the year after an HF hospitalization. Both groups experienced high mortality, but those with HFrEF had greater risk. In conclusion, from the standpoint of resource use, HF can be considered a single entity.

Relation of Acute Heart Failure Hospital Length of Stay to Subsequent Readmission and All-Cause Mortality.

Heart failure (HF) hospitalization length of stay (LOS) has been associated with the risk of subsequent readmission and mortality. We identified 19,927 hospitalized patients with HF who were discharged alive from 2008 to 2011 from 3 Kaiser Permanente regions. In adjusted Cox models using LOS 3 to 4 days as the reference category, shorter LOS was not significantly associated with hospital readmissions. LOS of 5 to 10 days was associated with 17% greater risk of readmission within 30 days (hazard ratio [HR] 1.17, 95% confidence interval [CI] 1.07 to 1.28) and 9% greater risk within 1 year (HR 1.09, 95% CI 1.03 to 1.15). LOS of 11 to 29 days was associated with increased readmission risk of 52% at 30 days (HR 1.52, 95% CI 1.30 to 1.76) and 25% at 1 year (HR 1.25, 95% CI 1.16 to 1.35). Mortality risk within 30 days among those with LOS of 1 day was 47% lower (HR 0.53, 95% CI 0.43 to 0.65) and 32% lower at 1 year (HR 0.68, 95% CI 0.62 to 0.74). LOS of 2 days was associated with lower mortality risk of 17% (HR 0.83, 95% CI 0.76 to 0.90) at 1 year. At LOS 5 to 10 days, 30-day and 1-year risk of mortality was increased by 52% (HR 1.52, 95% CI 1.30 to 1.76) and 25% (HR 1.25, 95% CI 1.16 to 1.35), respectively. LOS of 11 to 29 days was associated with 171% higher mortality risk at 30 days (HR 2.71, 95% CI 2.19 to 3.35) and 73% at 1 year (HR 1.73, 95% CI 1.53 to 1.97). Longer LOS during the index HF hospitalization was associated with readmission and mortality within 30 days and 1 year independent of co-morbidities and cardiovascular risk factors. These results suggest that LOS may be a proxy for the severity of HF during the index hospitalization.

Provider beliefs about diabetes treatment have little impact on glycemic control of their patients with diabetes.

OBJECTIVE: To improve the health of people with diabetes, it is essential to identify why patients experience extended periods of poor glycemic control before therapeutic intensification. RESEARCH DESIGN AND METHODS: We surveyed 252 primary care providers at Kaiser Permanente Northwest to determine their beliefs about the glycemic goals of their patients, treatment intensification behavior, and barriers to achieving optimal glycemic control. We linked the responses of 149 providers to the health records of their 18 346 patients with diabetes. RESULTS: Patient glycemic levels were not related to either individualized glycemic goals or provider intensification behavior. Providers' beliefs about diabetic treatment and glycated hemoglobin (HbA1c) goals were poorly associated with patient HbA1c levels. Providers identified patients' resistance to lifestyle behaviors and taking insulin, lack of medication adherence, and psychosocial issues as the main barriers to optimal glycemic control. Lack of time to care for complex patients was also a barrier. Providers who agreed that "current research did not support A1C levels <7%" were less likely to have patients with HbA1c levels <7% (OR=0.87, 95% CI 0.78 to 0.97) and patients of providers who disagreed that "some patients will have an A1C >9% no matter what I do" were 16% more likely to have patients with HbA1c <7% (1.16, 1.03 to 1.30) compared with providers who were neutral about those statements. CONCLUSIONS: Given the consistency of HbA1c levels across providers despite differences in beliefs and intensification behaviors, these barriers may be best addressed by instituting changes at the system level (ie, instituting institutional glycemic targets or outreach for dysglycemia) rather than targeting practice patterns of individual providers.

The association between different A1C-based measures of glycemia and risk of cardiovascular disease hospitalization.

OBJECTIVE We tested whether average monthly glycemic burden (AMGB), a marker of hyperglycemia that is a function of the extent and duration that A1C exceeded 7%, indicated greater risk of cardiovascular disease (CVD) than traditional A1C measures. RESEARCH DESIGN AND METHODS Using a case-control design, we studied 2,456 members of Kaiser Permanente Northwest with type 2 diabetes: 1,228 who experienced a CVD hospitalization, matched on age, sex, and duration of diabetes to 1,228 patients who were not hospitalized for CVD. We calculated AMGB from diabetes diagnosis until CVD hospitalization as a function of the difference between each actual or interpolated A1C measurement and 7%, resulting in an area under the curve estimate of hyperglycemic exposure, adjusted for number of months of observation. We used conditional logistic regression to compare the association between several A1C-based measures of glycemia and CVD, controlling for clinical characteristics and comorbidities. RESULTS AMGB was associated with increased CVD risk of 29% (odds ratio 1.29 [95% CI 1.16-1.44]; P < 0.001), while mean A1C was associated with a 22% risk increase (1.22 [1.09-1.37]; P < 0.001). A1C ever exceeding 7% was associated with increased CVD risk of 39% (1.39 [1.08-1.79]; P = 0.010). No model with a glycemia measure provided substantially more information than an identical model without a glycemia measure. CONCLUSIONS AMGB demonstrated somewhat greater CVD risk than mean A1C, but its clinical usefulness may be limited. A1C ever rising above 7% (53 mmol/mol) was a simple predictor of CVD risk that may have important clinical ramifications for newly diagnosed patients.

Automated telephone calls to enhance colorectal cancer screening: economic analysis.

OBJECTIVES: To estimate the cost-effectiveness of an automated telephone intervention for colorectal cancer screening from a managed care perspective, using data from a pragmatic randomized controlled trial. METHODS: Intervention patients received calls for fecal occult blood testing (FOBT) screening. We searched patients' electronic medical records for any screening (defined as FOBT, flexible sigmoidoscopy, double-contrast barium enema, or colonoscopy) during follow-up. Intervention costs included project implementation and management, telephone calls, patient identification, and tracking. Screening costs included FOBT (kits, mailing, and processing) and any completed screening tests during follow-up. We estimated the incremental cost-effectiveness ratio (ICER) of the cost per additional screen. RESULTS: At 6 months, average costs for intervention and control patients were $37 (25% screened) and $34 (19% screened), respectively. The ICER at 6 months was $42 per additional screen, less than half what other studies have reported. Cost-effectiveness probability was 0.49, 0.84, and 0.99 for willingness-to-pay thresholds of $40, $100, and $200, respectively. Similar results were seen at 9 months. A greater increase in FOBT testing was seen for patients aged >70 years (45/100 intervention, 33/100 control) compared with younger patients (25/100 intervention, 21/100 control). The intervention was dominant for patients aged >70 years and was $73 per additional screen for younger patients. It increased screening rates by about 6% and costs by $3 per patient. CONCLUSIONS: At willingness to pay of $100 or more per additional screening test, an automated telephone reminder intervention can be an optimal use of resources.

Incidence and demography of femur fractures with and without atypical features.

The case definition, community incidence, and characteristics of atypical femoral shaft fractures (FSFs) are poorly understood. This retrospective study utilized electronic medical records and radiograph review among women ≥50 years of age and men ≥65 years of age from January 1996 to June 2009 at Kaiser Permanente Northwest to describe the incidence rates and characteristics of subgroups of femur fractures. Fractures were categorized based on the American Society for Bone and Mineral Research (ASBMR) as atypical fracture major features (AFMs) (low force, shaft location, transverse or short oblique, noncomminuted) and AFMs with additional minor radiograph features (AFMms) (beaking, cortical thickening, or stress fracture). There were 5034 fractures in the study. The incidence rates of FSFs (without atypical features) and AFMs appeared flat (cumulative incidence: 18.2 per 100,000 person-years, 95% CI = 16.0-20.7; 5.9 per 100,000 person-years, 95% CI = 4.6-7.4; respectively) with 1,271,575 person-years observed. The proportion of AFMs that were AFMms increased over time. Thirty percent of AFMs had any dispensing of a bisphosphonate prior to the fracture, compared to 15.8% of the non-atypical FSFs. Years of oral glucocorticosteroid dispensing appeared highest in AFM and AFMm fractures. Those with AFMs only were older and had a lower frequency of bisphosphonate dispensing compared to those with AFMms. We conclude that rates of FSFs, with and without atypia, were low and stable over 13.5 years. Patients with only AFMs appear to be different from those with AFMms; it may be that only the latter group is atypical. There appear to be multiple associated risk factors for AFMm fractures.

Change in high-density lipoprotein cholesterol and risk of subsequent hospitalization for coronary artery disease or stroke among patients with type 2 diabetes mellitus.

The association between the changes in high-density lipoprotein (HDL) cholesterol and the risk of cardiovascular (CVD) or cerebrovascular hospitalization among patients with type 2 diabetes remains unclear. We conducted a retrospective observational cohort study of 30,067 members of the Kaiser Permanente Northwest and Georgia regions, who had type 2 diabetes and 2 HDL cholesterol measurements 6 to 24 months apart in 2001 to 2006. We followed up the cohort for ≤8 years (through 2009) to determine whether the change in HDL cholesterol was associated with subsequent CVD hospitalization. We examined the HDL cholesterol change continuously and by 3 categories: HDL cholesterol increased ≥6.5 mg/dl, decreased ≥6.5 mg/dl, or remained within ±6.4 mg/dl. The Cox regression models were adjusted for the baseline HDL cholesterol and demographic and clinical risk factors. During a mean follow-up of 55.8 ± 23.8 months, 3,023 patients (10.1%) experienced a CVD hospitalization. After multivariate adjustment, each 5 mg/dl of baseline HDL cholesterol was significantly associated with a 6% lower CVD hospitalization risk (hazard ratio 0.94 per 5 mg/dl, 95% confidence interval 0.92 to 0.95, p <0.0001) and each 5-mg/dl increase in HDL cholesterol was associated with a 4% CVD risk reduction (hazard ratio 0.96, 95% confidence interval 0.94 to 0.99, p <0.003). In the categorical analysis, a ≥6.5-mg/dl HDL cholesterol decrease was associated with an 11% increased CVD risk (hazard ratio 1.11, 95% confidence interval 1.00 to 1.24, p = 0.047) and a ≥6.5-mg/dl increase was associated with an 8% CVD risk reduction (hazard ratio 0.92, 95% confidence interval 0.84 to 1.01, p = 0.077) relative to those with stable HDL cholesterol. In conclusion, our results add to the growing body of evidence that increasing the HDL cholesterol levels might be an important strategy for CVD risk reduction. The prevention of HDL cholesterol decreases could be equally important.