Food Insecurity and Hypoglycemia among Older Patients with Type 2 Diabetes Treated with Insulin or Sulfonylureas: The Diabetes & Aging Study.

BACKGROUND: Severe hypoglycemia is a serious adverse drug event associated with hypoglycemia-prone medications; older patients with diabetes are particularly at high risk. Economic food insecurity (food insecurity due to financial limitations) is a known risk factor for hypoglycemia; however, less is known about physical food insecurity (due to difficulty cooking or shopping for food), which may increase with age, and its association with hypoglycemia. OBJECTIVE: Study associations between food insecurity and severe hypoglycemia. DESIGN: Survey based cross-sectional study. PARTICIPANTS: Survey responses were collected in 2019 from 1,164 older (≥ 65 years) patients with type 2 diabetes treated with insulin or sulfonylureas. MAIN MEASURES: Risk ratios (RR) for economic and physical food insecurity associated with self-reported severe hypoglycemia (low blood glucose requiring assistance) adjusted for age, financial strain, HbA1c, Charlson comorbidity score and frailty. Self-reported reasons for hypoglycemia endorsed by respondents. KEY RESULTS: Food insecurity was reported by 12.3% of the respondents; of whom 38.4% reported economic food insecurity only, 21.1% physical food insecurity only and 40.5% both. Economic food insecurity and physical food insecurity were strongly associated with severe hypoglycemia (RR = 4.3; p = 0.02 and RR = 4.4; p = 0.002, respectively). Missed meals ("skipped meals, not eating enough or waiting too long to eat") was the dominant reason (77.5%) given for hypoglycemia. CONCLUSIONS: Hypoglycemia prevention efforts among older patients with diabetes using hypoglycemia-prone medications should address food insecurity. Standard food insecurity questions, which are used to identify economic food insecurity, will fail to identify patients who have physical food insecurity only.

Development and Validation of the Life Expectancy Estimator for Older Adults with Diabetes (LEAD): the Diabetes and Aging Study.

BACKGROUND: Estimated life expectancy for older patients with diabetes informs decisions about treatment goals, cancer screening, long-term and advanced care, and inclusion in clinical trials. Easily implementable, evidence-based, diabetes-specific approaches for identifying patients with limited life expectancy are needed. OBJECTIVE: Develop and validate an electronic health record (EHR)-based tool to identify older adults with diabetes who have limited life expectancy. DESIGN: Predictive modeling based on survival analysis using Cox-Gompertz models in a retrospective cohort. PARTICIPANTS: Adults with diabetes aged ≥ 65 years from Kaiser Permanente Northern California: a 2015 cohort (N = 121,396) with follow-up through 12/31/2019, randomly split into training (N = 97,085) and test (N = 24,311) sets. Validation was conducted in the test set and two temporally distinct cohorts: a 2010 cohort (n = 89,563; 10-year follow-up through 2019) and a 2019 cohort (n = 152,357; 2-year follow-up through 2020). MAIN MEASURES: Demographics, diagnoses, utilization and procedures, medications, behaviors and vital signs; mortality. KEY RESULTS: In the training set (mean age 75 years; 49% women; 48% racial and ethnic minorities), 23% died during 5 years follow-up. A mortality prediction model was developed using 94 candidate variables, distilled into a life expectancy model with 11 input variables, and transformed into a risk-scoring tool, the Life Expectancy Estimator for Older Adults with Diabetes (LEAD). LEAD discriminated well in the test set (C-statistic = 0.78), 2010 cohort (C-statistic = 0.74), and 2019 cohort (C-statistic = 0.81); comparisons of observed and predicted survival curves indicated good calibration. CONCLUSIONS: LEAD estimates life expectancy in older adults with diabetes based on only 11 patient characteristics widely available in most EHRs and claims data. LEAD is simple and has potential application for shared decision-making, clinical trial inclusion, and resource allocation.

Challenges and solutions to employing natural language processing and machine learning to measure patients' health literacy and physician writing complexity: The ECLIPPSE study.

OBJECTIVE: In the National Library of Medicine funded ECLIPPSE Project (Employing Computational Linguistics to Improve Patient-Provider Secure Emails exchange), we attempted to create novel, valid, and scalable measures of both patients' health literacy (HL) and physicians' linguistic complexity by employing natural language processing (NLP) techniques and machine learning (ML). We applied these techniques to > 400,000 patients' and physicians' secure messages (SMs) exchanged via an electronic patient portal, developing and validating an automated patient literacy profile (LP) and physician complexity profile (CP). Herein, we describe the challenges faced and the solutions implemented during this innovative endeavor. MATERIALS AND METHODS: To describe challenges and solutions, we used two data sources: study documents and interviews with study investigators. Over the five years of the project, the team tracked their research process using a combination of Google Docs tools and an online team organization, tracking, and management tool (Asana). In year 5, the team convened a number of times to discuss, categorize, and code primary challenges and solutions. RESULTS: We identified 23 challenges and associated approaches that emerged from three overarching process domains: (1) Data Mining related to the SM corpus; (2) Analyses using NLP indices on the SM corpus; and (3) Interdisciplinary Collaboration. With respect to Data Mining, problems included cleaning SMs to enable analyses, removing hidden caregiver proxies (e.g., other family members) and Spanish language SMs, and culling SMs to ensure that only patients' primary care physicians were included. With respect to Analyses, critical decisions needed to be made as to which computational linguistic indices and ML approaches should be selected; how to enable the NLP-based linguistic indices tools to run smoothly and to extract meaningful data from a large corpus of medical text; and how to best assess content and predictive validities of both the LP and the CP. With respect to the Interdisciplinary Collaboration, because the research required engagement between clinicians, health services researchers, biomedical informaticians, linguists, and cognitive scientists, continual effort was needed to identify and reconcile differences in scientific terminologies and resolve confusion; arrive at common understanding of tasks that needed to be completed and priorities therein; reach compromises regarding what represents "meaningful findings" in health services vs. cognitive science research; and address constraints regarding potential transportability of the final LP and CP to different health care settings. DISCUSSION: Our study represents a process evaluation of an innovative research initiative to harness "big linguistic data" to estimate patient HL and physician linguistic complexity. Any of the challenges we identified, if left unaddressed, would have either rendered impossible the effort to generate LPs and CPs, or invalidated analytic results related to the LPs and CPs. Investigators undertaking similar research in HL or using computational linguistic methods to assess patient-clinician exchange will face similar challenges and may find our solutions helpful when designing and executing their health communications research.

Association of Real-time Continuous Glucose Monitoring With Glycemic Control and Acute Metabolic Events Among Patients With Insulin-Treated Diabetes.

Importance: Continuous glucose monitoring (CGM) is recommended for patients with type 1 diabetes; observational evidence for CGM in patients with insulin-treated type 2 diabetes is lacking. Objective: To estimate clinical outcomes of real-time CGM initiation. Design, Setting, and Participants: Exploratory retrospective cohort study of changes in outcomes associated with real-time CGM initiation, estimated using a difference-in-differences analysis. A total of 41 753 participants with insulin-treated diabetes (5673 type 1; 36 080 type 2) receiving care from a Northern California integrated health care delivery system (2014-2019), being treated with insulin, self-monitoring their blood glucose levels, and having no prior CGM use were included. Exposures: Initiation vs noninitiation of real-time CGM (reference group). Main Outcomes and Measures: Ten end points measured during the 12 months before and 12 months after baseline: hemoglobin A1c (HbA1c); hypoglycemia (emergency department or hospital utilization); hyperglycemia (emergency department or hospital utilization); HbA1c levels lower than 7%, lower than 8%, and higher than 9%; 1 emergency department encounter or more for any reason; 1 hospitalization or more for any reason; and number of outpatient visits and telephone visits. Results: The real-time CGM initiators included 3806 patients (mean age, 42.4 years [SD, 19.9 years]; 51% female; 91% type 1, 9% type 2); the noninitiators included 37 947 patients (mean age, 63.4 years [SD, 13.4 years]; 49% female; 6% type 1, 94% type 2). The prebaseline mean HbA1c was lower among real-time CGM initiators than among noninitiators, but real-time CGM initiators had higher prebaseline rates of hypoglycemia and hyperglycemia. Mean HbA1c declined among real-time CGM initiators from 8.17% to 7.76% and from 8.28% to 8.19% among noninitiators (adjusted difference-in-differences estimate, -0.40%; 95% CI, -0.48% to -0.32%; P < .001). Hypoglycemia rates declined among real-time CGM initiators from 5.1% to 3.0% and increased among noninitiators from 1.9% to 2.3% (difference-in-differences estimate, -2.7%; 95% CI, -4.4% to -1.1%; P = .001). There were also statistically significant differences in the adjusted net changes in the proportion of patients with HbA1c lower than 7% (adjusted difference-in-differences estimate, 9.6%; 95% CI, 7.1% to 12.2%; P < .001), lower than 8% (adjusted difference-in-differences estimate, 13.1%; 95% CI, 10.2% to 16.1%; P < .001), and higher than 9% (adjusted difference-in-differences estimate, -7.1%; 95% CI, -9.5% to -4.6%; P < .001) and in the number of outpatient visits (adjusted difference-in-differences estimate, -0.4; 95% CI, -0.6 to -0.2; P < .001) and telephone visits (adjusted difference-in-differences estimate, 1.1; 95% CI, 0.8 to 1.4; P < .001). Initiation of real-time CGM was not associated with statistically significant changes in rates of hyperglycemia, emergency department visits for any reason, or hospitalizations for any reason. Conclusions and Relevance: In this retrospective cohort study, insulin-treated patients with diabetes selected by physicians for real-time continuous glucose monitoring compared with noninitiators had significant improvements in hemoglobin A1c and reductions in emergency department visits and hospitalizations for hypoglycemia, but no significant change in emergency department visits or hospitalizations for hyperglycemia or for any reason. Because of the observational study design, findings may have been susceptible to selection bias.

Eating with others and meal location are differentially associated with nutrient intake by sex: The Diabetes Study of Northern California (DISTANCE).

Though eating with others is often a social behavior, relationships between social contexts of eating and nutrient intake have been underexplored. This study evaluates how social aspects of eating - frequencies of eating meals with others, meals prepared at home, and meals outside the home - are associated with nutrient intake. Because diet improvement can reduce complications of diabetes mellitus, we surveyed a multi-ethnic cohort of persons with type 2 diabetes (n = 770) about social aspects of diet (based on 24-hour recalls). Sex-stratified multiple regression analyses adjusted for confounders assessed the relationship between frequency of eating with others and nutrient intake (total energy, energy from fat, energy from carbohydrates, Healthy Eating Index/HEI, Dietary Approaches to Stop Hypertension/DASH score). Although there was slight variation in men's versus women's propensity to share meals, after adjustment for confounders, there was no consistently significant association between meals with others and the 5 nutrient intake measures for either men or women. The directions of association between categories of eating with others and diet quality (HEI and DASH scores) - albeit not significant - were different for men (positive) and women (mostly negative), which warrants further investigation. The next analyses estimated nutrient intake associated with meals prepared at home, and meals consumed outside the home. Analyses indicated that greater meal frequency at home was associated with significantly better scores on diet quality indices for men (but not women), while meal frequency outside the home was associated with poorer diet quality and energy intake for women (but not men). Better measurement of social dimensions of eating may inform ways to improve nutrition, especially for persons with diabetes for whom diet improvement can result in better disease outcomes.

Association of Initiation of Basal Insulin Analogs vs Neutral Protamine Hagedorn Insulin With Hypoglycemia-Related Emergency Department Visits or Hospital Admissions and With Glycemic Control in Patients With Type 2 Diabetes.

Importance: In clinical trials of patients with type 2 diabetes, long-acting insulin analogs modestly reduced the risk of nocturnal hypoglycemia compared with human neutral protamine Hagedorn (NPH) insulin, but cost 2 to 10 times more. Outcomes in clinical practice may differ from trial results. Objective: To compare the rates of hypoglycemia-related emergency department (ED) visits or hospital admissions associated with initiation of long-acting insulin analogs vs human NPH insulin in patients with type 2 diabetes. Design, Setting, and Participants: A retrospective observational study using data from Kaiser Permanente of Northern California from January 1, 2006, through September 30, 2015. Patients with type 2 diabetes who initiated a long-acting insulin analog or NPH insulin were included and censored at death, loss of health plan coverage, change in insulin treatment, or study end on September 30, 2015. Exposure: Initiation of basal insulin analogs (glargine or detemir) vs NPH insulin. Main Outcomes and Measures: The primary outcome was the time to a hypoglycemia-related ED visit or hospital admission and the secondary outcome was the change in hemoglobin A1c level within 1 year of insulin initiation. Results: There were 25 489 patients with type 2 diabetes who initiated basal insulin therapy (mean age, 60.2 [SD, 11.8] years; 51.9% white; 46.8% female). During a mean follow-up of 1.7 years, there were 39 hypoglycemia-related ED visits or hospital admissions among 1928 patients who initiated insulin analogs (11.9 events [95% CI, 8.1 to 15.6] per 1000 person-years) compared with 354 hypoglycemia-related ED visits or hospital admissions among 23 561 patients who initiated NPH insulin (8.8 events [95% CI, 7.9 to 9.8] per 1000 person-years) (between-group difference, 3.1 events [95% CI, -1.5 to 7.7] per 1000 person-years; P = .07). Among 4428 patients matched by propensity score, the adjusted hazard ratio was 1.16 (95% CI, 0.71 to 1.78) for hypoglycemia-related ED visits or hospital admissions associated with insulin analog use. Within 1 year of insulin initiation, hemoglobin A1c level decreased from 9.4% (95% CI, 9.3% to 9.5%) to 8.2% (95% CI, 8.1% to 8.2%) after initiation of insulin analogs and from 9.4% (95% CI, 9.3% to 9.5%) to 7.9% (95% CI, 7.9% to 8.0%) after initiation of NPH insulin (adjusted difference-in-differences for glycemic control, -0.22% [95% CI, -0.09% to -0.37%]). Conclusions and Relevance: Among patients with type 2 diabetes, initiation of a basal insulin analog compared with NPH insulin was not associated with a reduced risk of hypoglycemia-related ED visits or hospital admissions or with improved glycemic control. These findings suggest that the use of basal insulin analogs in usual practice settings may not be associated with clinical advantages for these outcomes.

Association Between Neighborhood Supermarket Presence and Glycated Hemoglobin Levels Among Patients With Type 2 Diabetes Mellitus.

We estimated associations between neighborhood supermarket gain or loss and glycemic control (assessed by glycated hemoglobin (HbA1c) values) in patients from the Kaiser Permanente Northern California Diabetes Registry (n = 434,806 person-years; 2007-2010). Annual clinical measures were linked to metrics from a geographic information system for each patient's address of longest residence. We estimated the association between change in supermarket presence (gain, loss, or no change) and change in HbA1c value, adjusting for individual- and area-level attributes and according to baseline glycemic control (near normal, <6.5%; good, 6.5%-7.9%; moderate, 8.0%-8.9%; and poor, ≥9.0%). Supermarket loss was associated with worse HbA1c trajectories for those with good, moderate, and poor glycemic control at baseline, while supermarket gain was associated with marginally better HbA1c outcomes only among patients with near normal HbA1c values at baseline. Patients with the poorest baseline HbA1c values (≥9.0%) had the worst associated changes in glycemic control following either supermarket loss or gain. Differences were not clinically meaningful relative to no change in supermarket presence. For patients with type 2 diabetes mellitus, gaining neighborhood supermarket presence did not benefit glycemic control in a substantive way. The significance of supermarket changes on health depends on a complex interaction of resident, neighborhood, and store characteristics.

Hypoglycemia Patients and Transport by EMS in Alameda County, 2013-15.

OBJECTIVE: To estimate the rate, characteristics, and dispositions of hypoglycemia events among persons who received care from Alameda County, California, Emergency Medical Services (EMS). METHODS: This study was based on data for 601,077 Alameda County EMS encounters during 2013-15. Subjects were defined as having hypoglycemia if EMS personnel recorded a primary impression of hypoglycemia or low blood glucose (<60 mg/dl or "unspecified low"). The outcome of interest was patient transport or non-transport to an emergency department or other care setting; we excluded 33,177 (6%) encounters which lacked clear disposition outcomes. RESULTS: Among 567,900 eligible encounters, 8,332 (1.47%) were attributed to hypoglycemia, of which 1,125 (13.5%) were not transported. Non-transport was more likely among males, adult patients age <60, initial blood glucose >60 mg/dl or EMS arrival time 18:00-6:00. CONCLUSIONS: Without an understanding of EMS encounters and non-transport rates, surveillance based solely on emergency department and hospital data will significantly underestimate rates of severe hypoglycemia. Additionally, given that hypoglycemia is often safely and effectively treated by non-physicians, EMS protocols should provide guidance for non-transport of hypoglycemic patients whose blood glucose levels have normalized.

Diabetes and Prior Coronary Heart Disease are Not Necessarily Risk Equivalent for Future Coronary Heart Disease Events.

BACKGROUND: For more than a decade, the presence of diabetes has been considered a coronary heart disease (CHD) "risk equivalent". OBJECTIVE: The objective of this study was to revisit the concept of risk equivalence by comparing the risk of subsequent CHD events among individuals with or without history of diabetes or CHD in a large contemporary real-world cohort over a period of 10 years (2002 to 2011). DESIGN: Population-based prospective cohort analysis. PARTICIPANTS: We studied a cohort of 1,586,061 adult members (ages 30-90 years) of Kaiser Permanente Northern California, an integrated health care delivery system. MAIN MEASUREMENTS: We calculated hazard ratios (HRs) from Cox proportional hazard models for CHD among four fixed cohorts, defined by prevalent (baseline) risk group: no history of diabetes or CHD (None), prior CHD alone (CHD), diabetes alone (DM), and diabetes and prior CHD (DM + CHD). KEY RESULTS: We observed 80,012 new CHD events over the follow-up period (~10,980,800 person-years). After multivariable adjustment, the HRs (reference: None) for new CHD events were as follows: CHD alone, 2.8 (95% CI, 2.7-2.85); DM alone 1.7 (95% CI, 1.66-1.74); DM + CHD, 3.9 (95% CI, 3.8-4.0). Individuals with diabetes alone had significantly lower risk of CHD across all age and sex strata compared to those with CHD alone (12.2 versus 22.5 per 1000 person-years). The risk of future CHD for patients with a history of either DM or CHD was similar only among those with diabetes of long duration (≥10 years). CONCLUSIONS: Not all individuals with diabetes should be unconditionally assumed to be a risk equivalent of those with prior CHD.

Police-Recorded Crime and Perceived Stress among Patients with Type 2 Diabetes: the Diabetes Study of Northern California (DISTANCE).

While stress has been linked to poor health outcomes, little is known about the impact of objective measures of neighborhood crime on stress in patients with chronic disease. Using the Kaiser Permanente Diabetes Study of Northern California (DISTANCE), we examined associations between police-recorded crime (2005-2007) and stress (Perceived Stress Scale-4) in four large Northern California cities (Oakland, Sacramento, San Francisco, and San Jose). We performed stratified analysis by gender and race/ethnicity using generalized linear regression models. In our study sample (n = 3188, mean age 59, range 30-77), 10 % reported high stress. In adjusted analyses, higher neighborhood all crimes rate was associated with modest increase in high stress for African-American (OR = 1.10; 95 % CI 1.02-1.22) and Latina women (OR = 1.36; 95 % CI 1.10-1.67) and property crime showed similar associations with stress for these groups of women. Visible crime was associated with stress only for Latina women (OR = 1.43; 95 % CI 1.14-1.78). We found no association between crime and stress among men or other racial/ethnic groups of women. High crime levels may disproportionately impact health among certain subpopulations. Studies using additional measures of stress are necessary to differentiate the health impact of crime-related stress from other forms of stressors among individuals living with diabetes.

Communication Barriers and the Clinical Recognition of Diabetic Peripheral Neuropathy in a Diverse Cohort of Adults: The DISTANCE Study.

The purpose of this study was to explore communication barriers as independent predictors and potential mediators of variation in clinical recognition of diabetic peripheral neuropathy (DPN). In this cross-sectional analysis, we estimated the likelihood of having a DPN diagnosis among 4,436 patients with DPN symptoms. We controlled for symptom frequency, demographic and clinical characteristics, and visit frequency using a modified Poisson regression model. We then evaluated 4 communication barriers as independent predictors of clinical documentation and as possible mediators of racial/ethnic differences: difficulty speaking English, not talking to one's doctor about pain, limited health literacy, and reports of suboptimal patient-provider communication. Difficulty speaking English and not talking with one's doctor about pain were independently associated with not having a diagnosis, though limited health literacy and suboptimal patient-provider communication were not. Limited English proficiency partially attenuated, but did not fully explain, racial/ethnic differences in clinical documentation among Chinese, Latino, and Filipino patients. Providers should be encouraged to talk with their patients about DPN symptoms, and health systems should consider enhancing strategies to improve timely clinical recognition of DPN among patients who have difficult speaking English. More work is needed to understand persistent racial/ethnic differences in diagnosis.

Identifying Spanish Language Competent Physicians: The Diabetes Study of Northern California (DISTANCE).

OBJECTIVES: Language barriers negatively impact health care access and quality for US immigrants. Latinos are the second largest immigrant group and the largest, fastest growing minority. Health care systems need simple, low cost and accurate tools that they can use to identify physicians with Spanish language competence. We sought to address this need by validating a simple and low-cost tool already in use in a major health plan. DESIGN SETTING PARTICIPANTS: A web-based survey conducted in 2012 among physicians caring for patients in a large, integrated health care delivery system. Of the 2,198 survey respondents, 111 were used in additional analysis involving patient report of those physicians' fluency. MAIN OUTCOME MEASURES: We compared health care physicians' responses to a single item, Spanish language self-assessment tool (measuring "medical proficiency") with patient-reported physician language competence, and two validated physician self-assessment tools (measuring "fluency" and "confidence"). RESULTS: Concordance between medical proficiency was moderate with patient reports (weighted Kappa .45), substantial with fluency (weighted Kappa .76), and moderate-to-substantial with confidence (weighted Kappas .53 to .66). CONCLUSIONS: The single-question self-reported medical proficiency tool is a low-cost tool useful for quickly identifying Spanish competent physicians and is potentially suitable for use in clinical settings. A reasonable approach for health systems is to designate only those physicians who self-assess their Spanish medical proficiency as "high" as competent to provide care without an interpreter.

Does food vendor density mediate the association between neighborhood deprivation and BMI?: a G-computation mediation analysis.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Use of the refill function through an online patient portal is associated with improved adherence to statins in an integrated health system.

BACKGROUND: Online patient portals are being widely implemented, but their impact on health behaviors are not well-studied. OBJECTIVE: To determine whether statin adherence improved after initiating use of the portal refill function. RESEARCH DESIGN: Observational cohort study within an integrated health care delivery system. SUBJECTS: Diabetic patients on statins who had registered for online portal access by 2010. A total of 8705 subjects initiated the online refill function use within the study window, including "exclusive" and "occasional" users (ie, requesting all vs. some refills online, respectively). Using risk-set sampling, we temporally matched 9055 reference group patients who never used online refills. MEASURES: We calculated statin adherence before and after refill function initiation, assessed as percent time without medications (nonadherence defined as a gap of >20%). Secondary outcome was dyslipidemia [low-density lipoprotein (LDL)≥ 100]. Difference-in-differences regression models estimated pre-post changes in nonadherence and dyslipidemia, comparing refill function users to the reference group and adjusting for age, sex, race/ethnicity, medications, frequency of portal use, and outpatient visits. RESULTS: In unadjusted examinations, nonadherence decreased only among patients initiating occasional or exclusive use of the refill function (26%-24% and 22%-15%, respectively). In adjusted models, nonadherence declined by an absolute 6% (95% confidence interval, 4%-7%) among exclusive users, without significant changes among occasional users. Similar LDL decreases were also seen among exclusive users. CONCLUSIONS: Compared with portal users who did not refill medications online, adherence to statin medications and LDL levels improved among diabetic patients who initiated and exclusively used the patient portal for refills, suggesting that wider adoption of online refills may improve adherence.

Associations between antidepressant adherence and shared decision-making, patient-provider trust, and communication among adults with diabetes: diabetes study of Northern California (DISTANCE).

BACKGROUND: 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. OBJECTIVE: To determine whether shared decision-making, patient-provider trust, or communication are associated with early stage and ongoing antidepressant adherence. DESIGN: Observational new prescription cohort study. SETTING: Kaiser Permanente Northern California. PATIENTS: 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. MEASUREMENTS: 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). RESULTS: 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). LIMITATIONS: All patients were insured and had consistent access to and quality of care. CONCLUSIONS: 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.

Social support and lifestyle vs. medical diabetes self-management in the diabetes study of Northern California (DISTANCE).

BACKGROUND: In chronic illness self-care, social support may influence some health behaviors more than others. PURPOSE: 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). METHODS: 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. RESULTS: 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. CONCLUSIONS: Findings suggest that social support diminished in importance as self-care progresses from lifestyle to more skilled "medical" behaviors.

Spatial pattern of body mass index among adults in the diabetes study of Northern California (DISTANCE).

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Continuous Glucose Monitor Metrics Are Associated with Emergency Department Visits and Hospitalizations for Hypoglycemia and Hyperglycemia, but Have Low Predictive Value.

Objective: Determine whether continuous glucose monitor (CGM) metrics can provide actionable advance warning of an emergency department (ED) visit or hospitalization for hypoglycemic or hyperglycemic (dysglycemic) events. Research Design and Methods: Two nested case-control studies were conducted among insulin-treated diabetes patients at Kaiser Permanente, who shared their CGM data with their providers. Cases included dysglycemic events identified from ED and hospital records (2016-2021). Controls were selected using incidence density sampling. Multiple CGM metrics were calculated among patients using CGM >70% of the time, using CGM data from two lookback periods (0-7 and 8-14 days) before each event. Generalized estimating equations were specified to estimate odds ratios and C-statistics. Results: Among 3626 CGM users, 108 patients had 154 hypoglycemic events and 165 patients had 335 hyperglycemic events. Approximately 25% of patients had no CGM data during either lookback; these patients had >2 × the odds of a hypoglycemic event and 3-4 × the odds of a hyperglycemic event. While several metrics were strongly associated with a dysglycemic event, none had good discrimination. Conclusion: Several CGM metrics were strongly associated with risk of dysglycemic events, and these can be used to identify higher risk patients. Also, patients who are not using their CGM device may be at elevated risk of adverse outcomes. However, no CGM metric or absence of CGM data had adequate discrimination to reliably provide actionable advance warning of an event and thus justify a rapid intervention.

Risk of Infection in Older Adults With Type 2 Diabetes With Relaxed Glycemic Control.

OBJECTIVE: To compare the risk of hospitalization for infection among patients who achieve intensive versus relaxed glycemic control. RESEARCH DESIGN AND METHODS: This retrospective cohort study included adults age ≥65 years with type 2 diabetes from an integrated health care delivery system. Negative binomial models were used to estimate incidence rates and relative risk (RR) of hospitalization for infections (respiratory; genitourinary; skin, soft tissue, and bone; and sepsis), comparing two levels of relaxed (hemoglobin A1c [HbA1c] 7% to <8% and 8% to <9%) with intensive (HbA1c 6% to <7%) glycemic control from 1 January 2019 to 1 March 2020. RESULTS: Among 103,242 older patients (48.5% with HbA1c 6% to <7%, 35.3% with HbA1c 7% to <8%, and 16.1% with HbA1c 8% to <9%), the rate of hospitalization for infections was 51.3 per 1,000 person-years. Compared with HbA1c 6% to <7%, unadjusted risk of hospitalization for infections was significantly elevated among patients with HbA1c 8% to <9% (RR 1.25; 95% CI 1.13, 1.39) but not among patients with HbA1c 7% to <8% (RR 0.99; 95% CI 0.91, 1.08), and the difference became nonsignificant after adjustment. Across categories of infections, the adjusted RR of hospitalization was significantly higher among patients with HbA1c 8% to <9% only for skin, soft tissue, and bone infection (RR 1.33; 95% CI 1.05, 1.69). CONCLUSIONS: Older patients with type 2 diabetes who achieve relaxed glycemic control levels endorsed by clinical guidelines are not at significantly increased risk of hospitalization for most infections, but HbA1c 8% to <9% is associated with an increased risk of hospitalization for skin, soft tissue, and bone infections.

Willingness to take less medication for type 2 diabetes among older patients: The Diabetes & Aging Study.

BACKGROUND: To examine the willingness of older patients to take less diabetes medication (de-intensify) and to identify characteristics associated with willingness to de-intensify treatment. METHODS: Survey conducted in 2019 in an age-stratified, random sample of older (65-100 years) adults with diabetes on glucose-lowering medications in the Kaiser Permanente Northern California Diabetes Registry. We classified survey responses to the question: "I would be willing to take less medication for my diabetes" as willing, neutral, or unwilling to de-intensify. Willingness to de-intensify treatment was examined by several clinical characteristics, including American Diabetes Association (ADA) health status categories used for individualizing glycemic targets. Analyses were weighted to account for over-sampling of older individuals. RESULTS: A total of 1337 older adults on glucose-lowering medication(s) were included (age 74.2 ± 6.0 years, 44% female, 54.4% non-Hispanic white). The proportions of participants willing, neutral, or unwilling to take less medication were 51.2%, 27.3%, and 21.5%, respectively. Proportions of willing to take less medication varied by age (65-74 years: 54.2% vs. 85+ years: 38.5%) and duration of diabetes (0-4 years: 61.0% vs. 15+ years: 44.2%), both p < 0.001. Patients on 1-2 medications were more willing to take less medication(s) compared with patients on 10+ medications (62.1% vs. 46.6%, p = 0.03). Similar proportions of willingness to take less medications were seen across ADA health status, and HbA1c. Willingness to take less medication(s) was similar across survey responses to questions about patient-clinician relationships. CONCLUSIONS: Clinical guidelines suggest considering treatment de-intensification in older patients with longer duration of diabetes, yet patients with these characteristics are less likely to be willing to take less medication(s).