HbA1c variability associated with dementia risk in people with type 2 diabetes.

INTRODUCTION: Although poor glycemic control is associated with dementia, it is unknown if variability in glycemic control, even in those with optimal glycosylated hemoglobin A1c (HbA1c) levels, increases dementia risk. METHODS: Among 171,964 people with type 2 diabetes, we evaluated the hazard of dementia association with long-term HbA1c variability using five operationalizations, including standard deviation (SD), adjusting for demographics and comorbidities. RESULTS: The mean baseline age was 61 years (48% women). Greater HbA1c SD was associated with greater dementia hazard (adjusted hazard ratio = 1.15 [95% confidence interval: 1.12, 1.17]). In stratified analyses, higher HbA1c SD quintiles were associated with greater dementia hazard among those with a mean HbA1c < 6% (P = 0.0004) or 6% to 8% (P < 0.0001) but not among those with mean HbA1c ≥ 8% (P = 0.42). DISCUSSION: Greater HbA1c variability is associated with greater dementia risk, even among those with HbA1c concentrations at ideal clinical targets. These findings add to the importance and clinical impact of recommendations to minimize glycemic variability. HIGHLIGHTS: We observed a cohort of 171,964 people with type 2 diabetes (mean age 61 years). This cohort was based in Northern California between 1996 and 2018. We examined the association between glycosylated hemoglobin A1c (HbA1c) variability and dementia risk. Greater HbA1c variability was associated with greater dementia hazard. This was most evident among those with normal-low mean HbA1c concentrations.

Evaluation of approaches to recruitment of racially and ethnically diverse breast cancer patients from an integrated health care setting for collection of observational social network data.

PURPOSE: We compared approaches to recruitment of diverse women with breast cancer in a study designed to collect complex social network data. METHODS: We recruited 440 women from the Kaiser Permanente Northern California population newly diagnosed with breast cancer, either in person at a clinic, by email, or by mailed letter. In clinic and mail recruitment, women completed a brief 3-page paper survey (epidemiologic data only), and women had the option to complete a separate, longer (30-40 min) personal social network survey online. In email recruitment, we administered epidemiologic and personal social network measures together in a single online survey. In email and mail recruitment, we limited the sample of non-Hispanic white (NHW) women to 30% of their total. We used descriptive analysis and multinomial logistic regression to examine odds of recruitment vs. mailed letter. RESULTS: Women responded to the social network surveys on average 3.7 months post-diagnosis. Mean age was 59.3 (median = 61.0). In-person clinic recruitment was superior with a 52.1% success rate of recruitment compared with 35.6% by mail or 17.3% by email (χ2 = 65.9, p < 0.001). Email recruitment produced the highest completion rate (82.1%) of personal network data compared with clinic (36.5%) or mail (28.7%), (χ2 = 114.6, p < 0.001). Despite intentional undersampling of NHW patients, response rates for Asian, Hispanic, and Black women by email were lower. However, we found no significant differences in recruitment rates by race and ethnicity for face-to-face clinic recruitment vs. by letter. Letter recruitment produced the highest overall response. CONCLUSION: Mailed letter was the best approach to representative recruitment of diverse women with breast cancer and collection of social network data, and further yielded the highest absolute response.

Tobacco Smoking and Risk of SARS-CoV-2 Infection and Disease Severity Among Adults in an Integrated Healthcare System in California.

INTRODUCTION: The relationship between tobacco smoking status and SARS-CoV-2 infection and coronavirus disease 2019 (COVID-19) severity is highly debated. We conducted a retrospective cohort study of >2.4 million adults in a large healthcare system to evaluate whether smoking is associated with SARS-CoV-2 infection and disease severity. AIMS AND METHODS: This retrospective cohort study of 2,427,293 adults in KPNC from March 5, 2020 (baseline) to December 31, 2020 (pre-vaccine) included smoking status (current, former, never), socio-demographics, and comorbidities from the electronic health record. SARS-CoV-2 infection (identified by a positive PCR test) and COVID-19 severity (hospitalization, ICU admission or death ≤ 30 days of COVID-19 diagnosis) were estimated in time-to-event analyses using Cox proportional hazard regression models adjusting for covariates. Secondary analyses examined COVID-19 severity among patients with COVID-19 using logistic regression. RESULTS: During the study, 44,270 patients had SARS-CoV-2 infection. Current smoking was associated with lower adjusted rates of SARS-CoV-2 infection (aHR = 0.64 95% CI: 0.61-0.67), COVID-19-related hospitalization (aHR = 0.48 95% CI: 0.40-0.58), ICU admission (aHR = 0.62 95% CI: 0.42-0.87), and death (aHR = 0.52 95% CI: 0.27-0.89) than never-smoking. Former smoking was associated with a lower adjusted rate of SARS-CoV-2 infection (aHR = 0.96 95% CI: 0.94-0.99) and higher adjusted rates of hospitalization (aHR = 1.10 95% CI: 1.03-1.08) and death (aHR = 1.32 95% CI: 1.11-1.56) than never-smoking. Logistic regression analyses among patients with COVID-19 found lower odds of hospitalization for current versus never-smoking and higher odds of hospitalization and death for former versus never-smoking. CONCLUSIONS: In the largest US study to date on smoking and COVID-19, current and former smoking showed lower risk of SARS-CoV-2 infection than never-smoking, while a history of smoking was associated with higher risk of severe COVID-19. IMPLICATIONS: In this cohort study of 2.4 million adults, adjusting for socio-demographics and medical comorbidities, current tobacco smoking was associated with a lower risk of both SARS-CoV-2 infection and severe COVID-19 illness compared to never-smoking. A history of smoking was associated with a slightly lower risk of SARS-CoV-2 infection and a modestly higher risk of severe COVID-19 illness compared to never-smoking. The lower observed COVID-19 risk for current versus never-smoking deserves further investigation. Results support prioritizing individuals with smoking-related comorbidities for vaccine outreach and treatments as they become available.

Racial Disparities in COVID-19 Testing and Outcomes : Retrospective Cohort Study in an Integrated Health System.

BACKGROUND: Racial disparities exist in outcomes after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. OBJECTIVE: To evaluate the contribution of race/ethnicity in SARS-CoV-2 testing, infection, and outcomes. DESIGN: Retrospective cohort study (1 February 2020 to 31 May 2020). SETTING: Integrated health care delivery system in Northern California. PARTICIPANTS: Adult health plan members. MEASUREMENTS: Age, sex, neighborhood deprivation index, comorbid conditions, acute physiology indices, and race/ethnicity; SARS-CoV-2 testing and incidence of positive test results; and hospitalization, illness severity, and mortality. RESULTS: Among 3 481 716 eligible members, 42.0% were White, 6.4% African American, 19.9% Hispanic, and 18.6% Asian; 13.0% were of other or unknown race. Of eligible members, 91 212 (2.6%) were tested for SARS-CoV-2 infection and 3686 had positive results (overall incidence, 105.9 per 100 000 persons; by racial group, White, 55.1; African American, 123.1; Hispanic, 219.6; Asian, 111.7; other/unknown, 79.3). African American persons had the highest unadjusted testing and mortality rates, White persons had the lowest testing rates, and those with other or unknown race had the lowest mortality rates. Compared with White persons, adjusted testing rates among non-White persons were marginally higher, but infection rates were significantly higher; adjusted odds ratios [aORs] for African American persons, Hispanic persons, Asian persons, and persons of other/unknown race were 2.01 (95% CI, 1.75 to 2.31), 3.93 (CI, 3.59 to 4.30), 2.19 (CI, 1.98 to 2.42), and 1.57 (CI, 1.38 to 1.78), respectively. Geographic analyses showed that infections clustered in areas with higher proportions of non-White persons. Compared with White persons, adjusted hospitalization rates for African American persons, Hispanic persons, Asian persons, and persons of other/unknown race were 1.47 (CI, 1.03 to 2.09), 1.42 (CI, 1.11 to 1.82), 1.47 (CI, 1.13 to 1.92), and 1.03 (CI, 0.72 to 1.46), respectively. Adjusted analyses showed no racial differences in inpatient mortality or total mortality during the study period. For testing, comorbid conditions made the greatest relative contribution to model explanatory power (77.9%); race only accounted for 8.1%. Likelihood of infection was largely due to race (80.3%). For other outcomes, age was most important; race only contributed 4.5% for hospitalization, 12.8% for admission illness severity, 2.3% for in-hospital death, and 0.4% for any death. LIMITATION: The study involved an insured population in a highly integrated health system. CONCLUSION: Race was the most important predictor of SARS-CoV-2 infection. After infection, race was associated with increased hospitalization risk but not mortality. PRIMARY FUNDING SOURCE: The Permanente Medical Group, Inc.

Advancing clinical trials in nursing homes: A proposed roadmap to success.

An effective clinical research effort in nursing homes to address prevention and treatment of COVID-19 faced overwhelming challenges. Under the Health Care Systems Research Network-Older Americans Independence Centers AGING Initiative, a multidisciplinary Stakeholder Advisory Panel was convened to develop recommendations to improve the capability of the clinical research enterprise in US nursing homes. The Panel considered the nursing home as a setting for clinical trials, reviewed the current state of clinical trials in nursing homes, and ultimately developed recommendations for the establishment of a nursing home clinical trials research network that would be centrally supported and administered. This report summarizes the Panel's recommendations, which were developed in alignment with the following core principles: build on available research infrastructure where appropriate; leverage existing productive partnerships of researchers with groups of nursing homes and nursing home corporations; encompass both efficacy and effectiveness clinical trials; be responsive to a broad range of stakeholders including nursing home residents and their care partners; be relevant to an expansive range of clinical and health care delivery research questions; be able to pivot as necessary to changing research priorities and circumstances; create a pathway for industry-sponsored research as appropriate; invest in strategies to increase diversity in study populations and the research workforce; and foster the development of the next generation of nursing home researchers.

Exploiting nonsystematic covariate monitoring to broaden the scope of evidence about the causal effects of adaptive treatment strategies.

In studies based on electronic health records (EHR), the frequency of covariate monitoring can vary by covariate type, across patients, and over time, which can limit the generalizability of inferences about the effects of adaptive treatment strategies. In addition, monitoring is a health intervention in itself with costs and benefits, and stakeholders may be interested in the effect of monitoring when adopting adaptive treatment strategies. This paper demonstrates how to exploit nonsystematic covariate monitoring in EHR-based studies to both improve the generalizability of causal inferences and to evaluate the health impact of monitoring when evaluating adaptive treatment strategies. Using a real world, EHR-based, comparative effectiveness research (CER) study of patients with type II diabetes mellitus, we illustrate how the evaluation of joint dynamic treatment and static monitoring interventions can improve CER evidence and describe two alternate estimation approaches based on inverse probability weighting (IPW). First, we demonstrate the poor performance of the standard estimator of the effects of joint treatment-monitoring interventions, due to a large decrease in data support and concerns over finite-sample bias from near-violations of the positivity assumption (PA) for the monitoring process. Second, we detail an alternate IPW estimator using a no direct effect assumption. We demonstrate that this estimator can improve efficiency but at the potential cost of increase in bias from violations of the PA for the treatment process.

Prompting Patients with Poorly Controlled Diabetes to Identify Visit Priorities Before Primary Care Visits: a Pragmatic Cluster Randomized Trial.

BACKGROUND: Most patients with diabetes do not meet all evidence-based goals of care, and many patients report poor communication and lack of involvement in decision-making during primary care visits. OBJECTIVE: To test the hypothesis that a "Pre-Visit Prioritization" secure email message could improve visit communication and glycemic control among patients with type 2 diabetes. DESIGN: We conducted a pragmatic, provider-randomized, multi-site clinical trial from March 2015 to October 2016 across 30 primary care practices within Kaiser Permanente Northern California (KPNC), a large integrated care delivery system. PARTICIPANTS: Eligible patients had at least 1 year of KPNC membership, type 2 diabetes with most recently measured hemoglobin A1c (HbA1c) > = 8.0%, and were registered users of the KPNC online patient portal. INTERVENTIONS: Patients in the intervention arm, upon booking an appointment, received a secure email through the KPNC online portal with a link to the EHR allowing them to submit their top one or two priorities prior to the visit. Control patients received usual care. MAIN MEASURES: Glycemic control; change in HbA1c 6 and 12 months after the initial visit; patient-reported outcomes related to patient-provider communication and patient care experiences. KEY RESULTS: During the study period, 1276 patients had at least one eligible visit. In post-visit surveys (n = 457), more intervention arm patients reported preparing questions for their visit (72% vs 63%, p = 0.048) and being given treatment choices to consider (81% vs 73%, p = 0.041). Patients in both arms had similar reductions in HbA1c over the 12-month study period (0.56% ± 1.45%), with no significant differences between arms. CONCLUSIONS: A "light touch" email-based pre-visit intervention resulted in improved measures of visit interaction but did not significantly improve glycemic control relative to usual care. Improving diabetes clinical outcomes through more effective primary care visits may require more intensive approaches to patient visit preparation. TRIAL REGISTRY: NCT02375932.

Targeted learning with daily EHR data.

Electronic health records (EHR) data provide a cost- and time-effective opportunity to conduct cohort studies of the effects of multiple time-point interventions in the diverse patient population found in real-world clinical settings. Because the computational cost of analyzing EHR data at daily (or more granular) scale can be quite high, a pragmatic approach has been to partition the follow-up into coarser intervals of pre-specified length (eg, quarterly or monthly intervals). The feasibility and practical impact of analyzing EHR data at a granular scale has not been previously evaluated. We start filling these gaps by leveraging large-scale EHR data from a diabetes study to develop a scalable targeted learning approach that allows analyses with small intervals. We then study the practical effects of selecting different coarsening intervals on inferences by reanalyzing data from the same large-scale pool of patients. Specifically, we map daily EHR data into four analytic datasets using 90-, 30-, 15-, and 5-day intervals. We apply a semiparametric and doubly robust estimation approach, the longitudinal Targeted Minimum Loss-Based Estimation (TMLE), to estimate the causal effects of four dynamic treatment rules with each dataset, and compare the resulting inferences. To overcome the computational challenges presented by the size of these data, we propose a novel TMLE implementation, the "long-format TMLE," and rely on the latest advances in scalable data-adaptive machine-learning software, xgboost and h2o, for estimation of the TMLE nuisance parameters.

Depression in type 1 diabetes and risk of dementia.

OBJECTIVE: Depression afflicts 14% of individuals with type 1 diabetes (T1D). Depression is a robust risk factor for dementia but it is unknown if this holds true for individuals with T1D, who recently started living to an age conferring dementia risk. We examined if depression is a dementia risk factor among elderly individuals with T1D. METHODS: 3,742 individuals with T1D age ≥50 were followed for dementia from 1/1/96-9/30/2015. Depression, dementia, and comorbidities were abstracted from electronic medical records. Cox proportional hazard models estimated the association between depression and dementia adjusting for demographics, glycosylated hemoglobin, severe dysglycemic epidsodes, stroke, heart disease, nephropathy, and end stage renal disease. The cumulative incidence of dementia by depression was estimated conditional on survival dementia-free to age 55. RESULTS: Five percent (N = 182) were diagnosed with dementia and 20% had baseline depression. Depression was associated with a 72% increase in dementia (fully adjusted HR = 1.72; 95% CI:1.12-2.65). The 25-year cumulative incidence of dementia was more than double for those with versus without depression (27% vs. 12%). CONCLUSIONS: For people with T1D, depression significantly increases dementia risk. Given the pervasiveness of depression in T1D, this has major implications for successful aging in this population recently living to old age.

Evaluating the Impact of Eliminating Copayments for Tobacco Cessation Pharmacotherapy.

OBJECTIVES: We examined the impact of the Affordable Care Act-mandated elimination of tobacco cessation pharmacotherapy (TCP) copayments on patient use of TCP, overall and by income. METHODS: Electronic health record data captured any and combination (eg, nicotine gum plus patch) TCP use among adult smokers newly enrolled in Kaiser Permanente Northern California (KPNC). KPNC eliminated TCP copayments in 2015. We included current smokers newly enrolled in the first 6 months of 2014 (before copayment elimination, N=16,199) or 2015 (after elimination, N=16,469). Multivariable models estimated 1-year changes in rates of any TCP fill, and of combination TCP fill, and tested for differences by income (<$50k, $50≥75k, ≥$75k). Through telephone surveys in 2016 with a subset of smokers newly enrolled in 2014 (n=306), we assessed barriers to TCP use, with results stratified by income. RESULTS: Smokers enrolled in KPNC in 2015 versus 2014 were more likely to have a TCP fill (9.1% vs. 8.2%; relative risk, 1.19; 95% confidence interval, 1.11-1.27), and combination TCP fill, among those with any fill (42.3% vs. 37.9%; relative risk, 1.12; 95% confidence interval, 1.02-1.23); findings were stronger for low-income smokers. Low-income patients (<$50k) were less likely to report that clinicians discussed smoking treatments with them (58%) compared with higher income smokers ($50≥75k, 67%; ≥$75k, 83%), and were less aware that TCP was free (40% vs. 53% and 69%, respectively, P-values<0.05). CONCLUSIONS: The Affordable Care Act's copayment elimination was associated with a modest increase in TCP use and a greater effect among low-income smokers. Uptake may have been enhanced if promoted to patients directly and via providers.

Association of the Affordable Care Act With Smoking and Tobacco Treatment Utilization Among Adults Newly Enrolled in Health Care.

OBJECTIVES: To examine rates of smoking and tobacco treatment utilization by insurance coverage status (Medicaid, commercial, exchange) among newly enrolled patients in the post Affordable Care Act (ACA) era. METHODS: We examined new members who enrolled in Kaiser Permanente Northern California through Medicaid, the California exchange, or nonexchange commercial plans (N=122,298) in the first 6 months of 2014 following ACA implementation. We compared these groups on smoking prevalence and tested whether smokers in each group differed on sociodemographic characteristics and in their utilization of tobacco treatment (pharmacotherapy and counseling) in 2014. RESULTS: Smoking prevalence was higher among Medicaid (22%) than exchange (13%) or commercial (12%) patients (P<0.0001). Controlling for key sociodemographic and clinical characteristics, Medicaid (odds ratio, 1.49; 95% confidence interval, 1.29-1.73) smokers had greater odds of tobacco treatment use than commercial smokers. Other groups at risk for underuse included men, younger patients, Asians, and Latinos. CONCLUSIONS: In this cohort of newly enrolled patients after ACA implementation, Medicaid patients were more likely to be smokers compared with exchange and commercial patients, but they were also more likely to use tobacco treatment. Low tobacco treatment use among exchange and commercial plan smokers, as well as younger men, Asians and Latinos poses a significant obstacle to improving public health and additional targeted outreach strategies may be needed to engage these patients with available health services.

Population Health Management for Diabetes: Health Care System-Level Approaches for Improving Quality and Addressing Disparities.

PURPOSE OF REVIEW: Population care approaches for diabetes have the potential to improve the quality of care and decrease diabetes-related mortality and morbidity. Population care strategies are particularly relevant as accountable care organizations (ACOs), patient-centered medical homes (PCMH), and integrated delivery systems are increasingly focused on managing chronic disease care at the health system level. This review outlines the key elements of population care approaches for diabetes in the current health care environment. RECENT FINDINGS: Population care approaches proactively identify diabetes patients through disease registries and electronic health record data and utilize multidisciplinary care teams, personalized provider feedback, and decision support tools to target and care for patients at risk for poor outcomes. Existing evidence suggests that these strategies can improve care outcomes and potentially ameliorate existing race/ethnic disparities in health care. However, such strategies may be less effective for patients who are disengaged from the health care system. As population care for diabetes continues to evolve, future initiatives should consider ways to tailor population care to meet individual patient needs, while leveraging improvements in clinical information systems and care integration to optimally manage and prevent diabetes in the future.

Effects of Transitioning to Medicare Part D on Access to Drugs for Medical Conditions among Dual Enrollees with Cancer.

OBJECTIVES: To evaluate the impact of transitioning from Medicaid to Medicare Part D drug coverage on the use of noncancer treatments among dual enrollees with cancer. METHODS: We leveraged a representative 5% national sample of all fee-for-service dual enrollees in the United States (2004-2007) to evaluate the impact of the removal of caps on the number of reimbursable prescriptions per month (drug caps) under Part D on 1) prevalence and 2) average days' supply dispensed for antidepressants, antihypertensives, and lipid-lowering agents overall and by race (white and black). RESULTS: The removal of drug caps was associated with increased use of lipid-lowering medications (days' supply 3.63; 95% confidence interval [CI] 1.57-5.70). Among blacks in capped states, we observed increased use of lipid-lowering therapy (any use 0.08 percentage points; 95% CI 0.05-0.10; and days' supply 4.01; 95% CI 2.92-5.09) and antidepressants (days' supply 2.20; 95% CI 0.61-3.78) and increasing trends in antihypertensive use (any use 0.01 percentage points; 95% CI 0.004-0.01; and days' supply 1.83; 95% CI 1.25-2.41). The white-black gap in the use of lipid-lowering medications was immediately reduced (-0.09 percentage points; 95% CI -0.15 to -0.04). We also observed a reversal in trends toward widening white-black differences in antihypertensive use (level -0.08 percentage points; 95% CI -0.12 to -0.05; and trend -0.01 percentage points; 95% CI -0.02 to -0.01) and antidepressant use (-0.004 percentage points; 95% CI -0.01 to -0.0004). CONCLUSIONS: Our findings suggest that the removal of drug caps under Part D had a modest impact on the treatment of hypercholesterolemia overall and may have reduced white-black gaps in the use of lipid-lowering and antidepressant therapies.

The Diabetes Telephone Study: Design and challenges of a pragmatic cluster randomized trial to improve diabetic peripheral neuropathy treatment.

BACKGROUND: Challenges to effective pharmacologic management of symptomatic diabetic peripheral neuropathy include the limited effectiveness of available medicines, frequent side effects, and the need for ongoing symptom assessment and treatment titration for maximal effectiveness. We present here the rationale and implementation challenges of the Diabetes Telephone Study, a randomized trial designed to improve medication treatment, titration, and quality of life among patients with symptomatic diabetic peripheral neuropathy. METHODS: We implemented a pragmatic cluster randomized controlled trial to test the effectiveness of an automated interactive voice response tool designed to provide physicians with real-time patient-reported data about responses to newly prescribed diabetic peripheral neuropathy medicines. A total of 1834 primary care physicians treating patients in the diabetes registry at Kaiser Permanente Northern California were randomized into the intervention or control arm. In September 2014, we began identification and recruitment of patients assigned to physicians in the intervention group who receive three brief interactive calls every 2 months after a medication is prescribed to alleviate diabetic peripheral neuropathy symptoms. These calls provide patients with the opportunity to report on symptoms, side effects, self-titration of medication dose and overall satisfaction with treatment. We plan to compare changes in self-reported quality of life between the intervention group and patients in the control group who receive three non-interactive automated educational phone calls. RESULTS: Successful implementation of this clinical trial required robust stakeholder engagement to help tailor the intervention and to address pragmatic concerns such as provider time constraints. As of 27 October 2015, we had screened 2078 patients, 1447 of whom were eligible for participation. We consented and enrolled 1206 or 83% of those eligible. Among those enrolled, 53% are women and the mean age is 67 (standard deviation = 12) years. The racial ethnic make-up is 56% White, 8% Asian, 13% Black or African American, and 19% Hispanic or Latino. CONCLUSION: Innovative strategies are needed to guide improvements in healthcare delivery for patients with symptomatic diabetic peripheral neuropathy. This trial aims to assess whether real-time collection and clinical feedback of patient treatment experiences can reduce patient symptom burden. Implementation of a clinical trial closely involving clinical care required researchers to partner with clinicians. If successful, this intervention provides a critical information feedback loop that would optimize diabetic peripheral neuropathy medication titration through widely available interactive voice response technology.

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.

Changes in use of lipid-lowering medications among black and white dual enrollees with diabetes transitioning from Medicaid to Medicare Part D drug coverage.

BACKGROUND: The use of lipid-lowering agents is suboptimal among dual enrollees, particularly blacks. OBJECTIVES: To determine whether the removal of restrictive drug caps under Medicare Part D reduced racial differences among dual enrollees with diabetes. RESEARCH DESIGN: An interrupted time series with comparison series design (ITS) cohort study. SUBJECTS: A total of 8895 black and white diabetes patients aged 18 years and older drawn from a nationally representative sample of fee-for-service dual enrollees (January 2004-December 2007) in states with and without drug caps before Part D. MEASURES: We examined the monthly (1) proportion of patients with any use of lipid-lowering therapies; and (2) intensity of use. Stratification measures included age (less than 65, 65 y and older), race (white vs. black), and sex. RESULTS: At baseline, lipid-lowering drug use was higher in no drug cap states (drug cap: 54.0% vs. nondrug cap: 66.8%) and among whites versus blacks (drug cap: 58.5% vs. 44.9%, no drug cap: 68.4% vs. 61.9%). In strict drug cap states only, Part D was associated with an increase in the proportion with any use [nonelderly: +0.07 absolute percentage points (95% confidence interval, 0.06-0.09), P<0.001; elderly: +0.08 (0.06-0.10), P<0.001] regardless of race. However, we found no evidence of a change in the white-black gap in the proportion of users despite the removal of a significant financial barrier. CONCLUSIONS: Medicare Part D was associated with increased use of lipid-lowering drugs, but racial gaps persisted. Understanding non-coverage-related barriers is critical in maximizing the potential benefits of coverage expansions for disparities reduction.

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.

Representativeness of Patients With Lung Cancer in an Integrated Health Care Delivery System.

INTRODUCTION: Observational research is important for understanding the real-world benefits of advancements in lung cancer care. Integrated health care systems, such as Kaiser Permanente Northern California, have extensive electronic health records suitable for such research, but the generalizability of their populations is often questioned. METHODS: Leveraging data from the California Cancer Registry, the authors compared distributions of demographic and clinical characteristics, in addition to neighborhood and environmental conditions, between patients diagnosed with lung cancer from 2015 through 2019 at Kaiser Permanente Northern California, National Cancer Institute-designated cancer centers (NCICCs), and all other non-NCICC hospitals within the same catchment area. RESULTS: Of 20,178 included patients, 30% were from Kaiser Permanente Northern California, 8% from NCICCs, and 62% from other non-NCICC hospitals. Compared to NCICC patients, Kaiser Permanente Northern California patients were more similar to other non-NCICC patients on most characteristics. Compared to other non-NCICC patients, Kaiser Permanente Northern California patients were slightly older, more likely to be female, and less likely to be Hispanic or Asian/Pacific Islander and to reside in lower socioeconomic status (SES) neighborhoods. In contrast, NCICC patients were younger, less likely to be female or from non-Asian/Pacific Islander minoritized racial groups, and more likely to present with early-stage disease and adenocarcinoma and to reside in neighborhoods with higher SES and lower air pollution than Kaiser Permanente Northern California or other non-NCICC patients. DISCUSSION: Patients from Kaiser Permanente Northern California, compared to NCICCs, are more broadly representative of the underlying patient population with lung cancer. CONCLUSION: Research using electronic health record data from integrated health care systems can contribute generalizable real-world evidence to benchmark and improve lung cancer care.